The Use of Wearable Inertial Motion Sensors in Human Lower Limb Biomechanics Studies: A Systematic Review

PubMed Central

Fong, Daniel Tik-Pui; Chan, Yue-Yan

2010-01-01

Wearable motion sensors consisting of accelerometers, gyroscopes and magnetic sensors are readily available nowadays. The small size and low production costs of motion sensors make them a very good tool for human motions analysis. However, data processing and accuracy of the collected data are important issues for research purposes. In this paper, we aim to review the literature related to usage of inertial sensors in human lower limb biomechanics studies. A systematic search was done in the following search engines: ISI Web of Knowledge, Medline, SportDiscus and IEEE Xplore. Thirty nine full papers and conference abstracts with related topics were included in this review. The type of sensor involved, data collection methods, study design, validation methods and its applications were reviewed. PMID:22163542

The use of wearable inertial motion sensors in human lower limb biomechanics studies: a systematic review.

PubMed

Fong, Daniel Tik-Pui; Chan, Yue-Yan

2010-01-01

Wearable motion sensors consisting of accelerometers, gyroscopes and magnetic sensors are readily available nowadays. The small size and low production costs of motion sensors make them a very good tool for human motions analysis. However, data processing and accuracy of the collected data are important issues for research purposes. In this paper, we aim to review the literature related to usage of inertial sensors in human lower limb biomechanics studies. A systematic search was done in the following search engines: ISI Web of Knowledge, Medline, SportDiscus and IEEE Xplore. Thirty nine full papers and conference abstracts with related topics were included in this review. The type of sensor involved, data collection methods, study design, validation methods and its applications were reviewed.

Vibration welding system with thin film sensor

DOEpatents

Cai, Wayne W; Abell, Jeffrey A; Li, Xiaochun; Choi, Hongseok; Zhao, Jingzhou

2014-03-18

A vibration welding system includes an anvil, a welding horn, a thin film sensor, and a process controller. The anvil and horn include working surfaces that contact a work piece during the welding process. The sensor measures a control value at the working surface. The measured control value is transmitted to the controller, which controls the system in part using the measured control value. The thin film sensor may include a plurality of thermopiles and thermocouples which collectively measure temperature and heat flux at the working surface. A method includes providing a welder device with a slot adjacent to a working surface of the welder device, inserting the thin film sensor into the slot, and using the sensor to measure a control value at the working surface. A process controller then controls the vibration welding system in part using the measured control value.

Tests of UFXC32k chip with CdTe pixel detector

NASA Astrophysics Data System (ADS)

Maj, P.; Taguchi, T.; Nakaye, Y.

2018-02-01

The paper presents the performance of the UFXC32K—a hybrid pixel detector readout chip working with CdTe detectors. The UFXC32K has a pixel pitch of 75 μm and can cope with both input signal polarities. This functionality allows operating with widely used silicon sensors collecting holes and CdTe sensors collecting electrons. This article describes the chip focusing on solving the issues connected to high-Z sensor material, namely high leakage currents, slow charge collection time and thick material resulting in increased charge-sharring effects. The measurements were conducted with higher X-ray energies including 17.4 keV from molybdenum. Conclusions drawn inside the paper show the UFXC32K's usability for CdTe sensors in high X-ray energy applications.

Space charge dosimeters for extremely low power measurements of radiation in shipping containers

DOEpatents

Britton, Jr., Charles L.; Buckner, Mark A [Oak Ridge, TN; Hanson, Gregory R [Clinton, TN; Bryan, William L [Knoxville, TN

2011-05-03

Methods and apparatus are described for space charge dosimeters for extremely low power measurements of radiation in shipping containers. A method includes insitu polling a suite of passive integrating ionizing radiation sensors including reading-out dosimetric data from a first passive integrating ionizing radiation sensor and a second passive integrating ionizing radiation sensor, where the first passive integrating ionizing radiation sensor and the second passive integrating ionizing radiation sensor remain situated where the dosimetric data was integrated while reading-out. Another method includes arranging a plurality of ionizing radiation sensors in a spatially dispersed array; determining a relative position of each of the plurality of ionizing radiation sensors to define a volume of interest; collecting ionizing radiation data from at least a subset of the plurality of ionizing radiation sensors; and triggering an alarm condition when a dose level of an ionizing radiation source is calculated to exceed a threshold.

Space charge dosimeters for extremely low power measurements of radiation in shipping containers

DOEpatents

Britton, Jr; Charles, L [Alcoa, TN; Buckner, Mark A [Oak Ridge, TN; Hanson, Gregory R [Clinton, TN; Bryan, William L [Knoxville, TN

2011-04-26

Methods and apparatus are described for space charge dosimeters for extremely low power measurements of radiation in shipping containers. A method includes in situ polling a suite of passive integrating ionizing radiation sensors including reading-out dosimetric data from a first passive integrating ionizing radiation sensor and a second passive integrating ionizing radiation sensor, where the first passive integrating ionizing radiation sensor and the second passive integrating ionizing radiation sensor remain situated where the dosimetric data was integrated while reading-out. Another method includes arranging a plurality of ionizing radiation sensors in a spatially dispersed array; determining a relative position of each of the plurality of ionizing radiation sensors to define a volume of interest; collecting ionizing radiation data from at least a subset of the plurality of ionizing radiation sensors; and triggering an alarm condition when a dose level of an ionizing radiation source is calculated to exceed a threshold.

System for RFID-Enabled Information Collection

NASA Technical Reports Server (NTRS)

Kennedy, Timothy F. (Inventor); Fink, Patrick W. (Inventor); Lin, Gregory Y. (Inventor); Ngo, Phong H. (Inventor)

2017-01-01

A sensor and system provide for radio frequency identification (RFID)-enabled information collection. The sensor includes a ring-shaped element and an antenna. The ring-shaped element includes a conductive ring and an RFID integrated circuit. The antenna is spaced apart from the ring-shaped element and defines an electrically-conductive path commensurate in size and shape to at least a portion of the conductive ring. The system may include an interrogator for energizing the ring-shaped element and receiving a data transmission from the RFID integrated circuit that has been energized for further processing by a processor.

Towards the development of tamper-resistant, ground-based mobile sensor nodes

NASA Astrophysics Data System (ADS)

Mascarenas, David; Stull, Christopher; Farrar, Charles

2011-11-01

Mobile sensor nodes hold great potential for collecting field data using fewer resources than human operators would require and potentially requiring fewer sensors than a fixed-position sensor array. It would be very beneficial to allow these mobile sensor nodes to operate unattended with a minimum of human intervention. In order to allow mobile sensor nodes to operate unattended in a field environment, it is imperative that they be capable of identifying and responding to external agents that may attempt to tamper with, damage or steal the mobile sensor nodes, while still performing their data collection mission. Potentially hostile external agents could include animals, other mobile sensor nodes, or humans. This work will focus on developing control policies to help enable a mobile sensor node to identify and avoid capture by a hostile un-mounted human. The work is developed in a simulation environment, and demonstrated using a non-holonomic, ground-based mobile sensor node. This work will be a preliminary step toward ensuring the cyber-physical security of ground-based mobile sensor nodes that operate unattended in potentially unfriendly environments.

A smart home application to eldercare: current status and lessons learned.

PubMed

Skubic, Marjorie; Alexander, Gregory; Popescu, Mihail; Rantz, Marilyn; Keller, James

2009-01-01

To address an aging population, we have been investigating sensor networks for monitoring older adults in their homes. In this paper, we report ongoing work in which passive sensor networks have been installed in 17 apartments in an aging in place eldercare facility. The network under development includes simple motion sensors, video sensors, and a bed sensor that captures sleep restlessness and pulse and respiration levels. Data collection has been ongoing for over two years in some apartments. This longevity in sensor data collection is allowing us to study the data and develop algorithms for identifying alert conditions such as falls, as well as extracting typical daily activity patterns for an individual. The goal is to capture patterns representing physical and cognitive health conditions and then recognize when activity patterns begin to deviate from the norm. In doing so, we strive to provide early detection of potential problems which may lead to serious health events if left unattended. We describe the components of the network and show examples of logged sensor data with correlated references to health events. A summary is also included on the challenges encountered and the lessons learned as a result of our experiences in monitoring aging adults in their homes.

Interstate-35 bridge instrumentation renaissance.

DOT National Transportation Integrated Search

2012-09-01

An updated, accelerometer-based, sensor and data acquisition system was installed and verified on the I-35 Walnut Creek Bridge in Purcell, Oklahoma. The data collection system also includes a microwave communication system to move sensor and video da...

Distributive, Non-destructive Real-time System and Method for Snowpack Monitoring

NASA Technical Reports Server (NTRS)

Frolik, Jeff (Inventor); Skalka, Christian (Inventor)

2013-01-01

A ground-based system that provides quasi real-time measurement and collection of snow-water equivalent (SWE) data in remote settings is provided. The disclosed invention is significantly less expensive and easier to deploy than current methods and less susceptible to terrain and snow bridging effects. Embodiments of the invention include remote data recovery solutions. Compared to current infrastructure using existing SWE technology, the disclosed invention allows more SWE sites to be installed for similar cost and effort, in a greater variety of terrain; thus, enabling data collection at improved spatial resolutions. The invention integrates a novel computational architecture with new sensor technologies. The invention's computational architecture is based on wireless sensor networks, comprised of programmable, low-cost, low-powered nodes capable of sophisticated sensor control and remote data communication. The invention also includes measuring attenuation of electromagnetic radiation, an approach that is immune to snow bridging and significantly reduces sensor footprints.

Planning and Scheduling for Environmental Sensor Networks

NASA Astrophysics Data System (ADS)

Frank, J. D.

2005-12-01

Environmental Sensor Networks are a new way of monitoring the environment. They comprise autonomous sensor nodes in the environment that record real-time data, which is retrieved, analyzed, integrated with other data sets (e.g. satellite images, GIS, process models) and ultimately lead to scientific discoveries. Sensor networks must operate within time and resource constraints. Sensors have limited onboard memory, energy, computational power, communications windows and communications bandwidth. The value of data will depend on when, where and how it was collected, how detailed the data is, how long it takes to integrate the data, and how important the data was to the original scientific question. Planning and scheduling of sensor networks is necessary for effective, safe operations in the face of these constraints. For example, power bus limitations may preclude sensors from simultaneously collecting data and communicating without damaging the sensor; planners and schedulers can ensure these operations are ordered so that they do not happen simultaneously. Planning and scheduling can also ensure best use of the sensor network to maximize the value of collected science data. For example, if data is best recorded using a particular camera angle but it is costly in time and energy to achieve this, planners and schedulers can search for times when time and energy are available to achieve the optimal camera angle. Planning and scheduling can handle uncertainty in the problem specification; planners can be re-run when new information is made available, or can generate plans that include contingencies. For example, if bad weather may prevent the collection of data, a contingent plan can check lighting conditions and turn off data collection to save resources if lighting is not ideal. Both mobile and immobile sensors can benefit from planning and scheduling. For example, data collection on otherwise passive sensors can be halted to preserve limited power and memory resources and to reduce the costs of communication. Planning and scheduling is generally a heavy consumer of time, memory and energy resources. This means careful thought must be given to how much planning and scheduling should be done on the sensors themselves, and how much to do elsewhere. The difficulty of planning and scheduling is exacerbated when reasoning about uncertainty. More time, memory and energy is needed to solve such problems, leading either to more expensive sensors, or suboptimal plans. For example, scientifically interesting events may happen at random times, making it difficult to ensure that sufficient resources are availanble. Since uncertainty is usually lowest in proximity to the sensors themselves, this argues for planning and scheduling onboard the sensors. However, cost minimization dictates sensors be kept as simple as possible, reducing the amount of planning and scheduling they can do themselves. Furthermore, coordinating each sensor's independent plans can be difficult. In the full presentation, we will critically review the planning and scheduling systems used by previously fielded sensor networks. We do so primarily from the perspective of the computational sciences, with a focus on taming computational complexity when operating sensor networks. The case studies are derived from sensor networks based on UAVs, satellites, and planetary rovers. Planning and scheduling considerations include multi-sensor coordination, optimizing science value, onboard power management, onboard memory, planning movement actions to acquire data, and managing communications.These case studies offer lessons for future designs of environmental sensor networks.

Seasat. Volume 2: Flight systems

NASA Technical Reports Server (NTRS)

Pounder, E. (Editor)

1980-01-01

Flight systems used in the Seasat Project are described. Included are (1) launch operation; (2) satellite performance after launch; (3) sensors that collected data; and (4) the launch vehicle that placed the satellite into Earth orbit. Techniques for sensor management are explained.

Potential of IMU Sensors in Performance Analysis of Professional Alpine Skiers

PubMed Central

Yu, Gwangjae; Jang, Young Jae; Kim, Jinhyeok; Kim, Jin Hae; Kim, Hye Young; Kim, Kitae; Panday, Siddhartha Bikram

2016-01-01

In this paper, we present an analysis to identify a sensor location for an inertial measurement unit (IMU) on the body of a skier and propose the best location to capture turn motions for training. We also validate the manner in which the data from the IMU sensor on the proposed location can characterize ski turns and performance with a series of statistical analyses, including a comparison with data collected from foot pressure sensors. The goal of the study is to logically identify the ideal location on the skier’s body to attach the IMU sensor and the best use of the data collected for the skier. The statistical analyses and the hierarchical clustering method indicate that the pelvis is the best location for attachment of an IMU, and numerical validation shows that the data collected from this location can effectively estimate the performance and characteristics of the skier. Moreover, placement of the sensor at this location does not distract the skier’s motion, and the sensor can be easily attached and detached. The findings of this study can be used for the development of a wearable device for the routine training of professional skiers. PMID:27043579

Two-axis direct fluid shear stress sensor

NASA Technical Reports Server (NTRS)

Bajikar, Sateesh (Inventor); Scott, Michael A. (Inventor); Adcock, Edward E. (Inventor)

2011-01-01

A micro sized multi-axis semiconductor skin friction/wall shear stress induced by fluid flow. The sensor design includes a shear/strain transduction gimble connected to a force collecting plate located at the flow boundary surface. The shear force collecting plate is interconnected by an arm to offset the tortional hinges from the fluid flow. The arm is connected to the shear force collecting plate through dual axis torsional hinges with piezoresistive torsional strain gauges. These gauges are disposed on the tortional hinges and provide a voltage output indicative of applied shear stress acting on the force collection plate proximate the flow boundary surface. Offsetting the torsional hinges creates a force concentration and resolution structure that enables the generation of a large stress on the strain gauge from small shear stress, or small displacement of the collecting plate. The design also isolates the torsional sensors from exposure to the fluid flow.

EVA Glove Sensor Feasbility II Abstract

NASA Technical Reports Server (NTRS)

Melone, Kate

2014-01-01

The main objectives for the glove project include taking various measurements from human subjects during and after they perform different tasks in the glove box, acquiring data from these tests and determining the accuracy of these results, interpreting and analyzing this data, and using the data to better understand how hand injuries are caused during EVAs.1 Some of these measurements include force readings, temperature readings, and micro-circulatory blood flow.1 The three glove conditions tested were ungloved (a comfort glove was worn to house the sensors), Series 4000, and Phase VI. The general approach/procedure for the glove sensor feasibility project is as follows: 1. Prepare test subject for testing. This includes attaching numerous sensors (approximately 50) to the test subject, wiring, and weaving the sensors and wires in the glove which helps to keep everything together. This also includes recording baseline moisture data using the Vapometer and MoistSense. 2. Pressurizing the glove box. Once the glove box is pressurized to the desired pressure (4.3 psid), testing can begin. 3. Testing. The test subject will perform a series of tests, some of which include pinching a load cell, making a fist, pushing down on a force plate, and picking up metal pegs, rotating them 90 degrees, and placing them back in the peg board. 4. Post glove box testing data collection. After the data is collected from inside the glove box, the Vapometer and MoistSense device will be used to collect moisture data from the subject's hand. 5. Survey. At the conclusion of testing, he/she will complete a survey that asks questions pertaining to comfort/discomfort levels of the glove, glove sizing, as well as offering any additional feedback.

Spacecraft attitude calibration/verification baseline study

NASA Technical Reports Server (NTRS)

Chen, L. C.

1981-01-01

A baseline study for a generalized spacecraft attitude calibration/verification system is presented. It can be used to define software specifications for three major functions required by a mission: the pre-launch parameter observability and data collection strategy study; the in-flight sensor calibration; and the post-calibration attitude accuracy verification. Analytical considerations are given for both single-axis and three-axis spacecrafts. The three-axis attitudes considered include the inertial-pointing attitudes, the reference-pointing attitudes, and attitudes undergoing specific maneuvers. The attitude sensors and hardware considered include the Earth horizon sensors, the plane-field Sun sensors, the coarse and fine two-axis digital Sun sensors, the three-axis magnetometers, the fixed-head star trackers, and the inertial reference gyros.

Standards-based sensor interoperability and networking SensorWeb: an overview

NASA Astrophysics Data System (ADS)

Bolling, Sam

2012-06-01

The War fighter lacks a unified Intelligence, Surveillance, and Reconnaissance (ISR) environment to conduct mission planning, command and control (C2), tasking, collection, exploitation, processing, and data discovery of disparate sensor data across the ISR Enterprise. Legacy sensors and applications are not standardized or integrated for assured, universal access. Existing tasking and collection capabilities are not unified across the enterprise, inhibiting robust C2 of ISR including near-real time, cross-cueing operations. To address these critical needs, the National Measurement and Signature Intelligence (MASINT) Office (NMO), and partnering Combatant Commands and Intelligence Agencies are developing SensorWeb, an architecture that harmonizes heterogeneous sensor data to a common standard for users to discover, access, observe, subscribe to and task sensors. The SensorWeb initiative long term goal is to establish an open commercial standards-based, service-oriented framework to facilitate plug and play sensors. The current development effort will produce non-proprietary deliverables, intended as a Government off the Shelf (GOTS) solution to address the U.S. and Coalition nations' inability to quickly and reliably detect, identify, map, track, and fully understand security threats and operational activities.

Crowd-Sourcing Seismic Data: Lessons Learned from the Quake-Catcher Network

NASA Astrophysics Data System (ADS)

Cochran, E. S.; Sumy, D. F.; DeGroot, R. M.; Clayton, R. W.

2015-12-01

The Quake Catcher Network (QCN; qcn.caltech.edu) uses low cost micro-electro-mechanical system (MEMS) sensors hosted by volunteers to collect seismic data. Volunteers use accelerometers internal to laptop computers, phones, tablets or small (the size of a matchbox) MEMS sensors plugged into desktop computers using a USB connector to collect scientifically useful data. Data are collected and sent to a central server using the Berkeley Open Infrastructure for Network Computing (BOINC) distributed computing software. Since 2008, when the first citizen scientists joined the QCN project, sensors installed in museums, schools, offices, and residences have collected thousands of earthquake records. We present and describe the rapid installations of very dense sensor networks that have been undertaken following several large earthquakes including the 2010 M8.8 Maule Chile, the 2010 M7.1 Darfield, New Zealand, and the 2015 M7.8 Gorkha, Nepal earthquake. These large data sets allowed seismologists to develop new rapid earthquake detection capabilities and closely examine source, path, and site properties that impact ground shaking at a site. We show how QCN has engaged a wide sector of the public in scientific data collection, providing the public with insights into how seismic data are collected and used. Furthermore, we describe how students use data recorded by QCN sensors installed in their classrooms to explore and investigate earthquakes that they felt, as part of 'teachable moment' exercises.

Mars 2020 Entry, Descent and Landing Instrumentation 2 (MEDLI2)

NASA Technical Reports Server (NTRS)

Hwang, Helen H.; Bose, Deepak; White, Todd R.; Wright, Henry S.; Schoenenberger, Mark; Kuhl, Christopher A.; Trombetta, Dominic; Santos, Jose A.; Oishi, Tomomi; Karlgaard, Christopher D.;

Distributed Transforms for Efficient Data Gathering in Sensor Networks

NASA Technical Reports Server (NTRS)

Ortega, Antonio (Inventor); Shen, Godwin (Inventor); Narang, Sunil K. (Inventor); Perez-Trufero, Javier (Inventor)

2014-01-01

Devices, systems, and techniques for data collecting network such as wireless sensors are disclosed. A described technique includes detecting one or more remote nodes included in the wireless sensor network using a local power level that controls a radio range of the local node. The technique includes transmitting a local outdegree. The local outdegree can be based on a quantity of the one or more remote nodes. The technique includes receiving one or more remote outdegrees from the one or more remote nodes. The technique includes determining a local node type of the local node based on detecting a node type of the one or more remote nodes, using the one or more remote outdegrees, and using the local outdegree. The technique includes adjusting characteristics, including an energy usage characteristic and a data compression characteristic, of the wireless sensor network by selectively modifying the local power level and selectively changing the local node type.

Efficient and Robust Data Collection Using Compact Micro Hardware, Distributed Bus Architectures and Optimizing Software

NASA Technical Reports Server (NTRS)

Chau, Savio; Vatan, Farrokh; Randolph, Vincent; Baroth, Edmund C.

2006-01-01

Future In-Space propulsion systems for exploration programs will invariably require data collection from a large number of sensors. Consider the sensors needed for monitoring several vehicle systems states of health, including the collection of structural health data, over a large area. This would include the fuel tanks, habitat structure, and science containment of systems required for Lunar, Mars, or deep space exploration. Such a system would consist of several hundred or even thousands of sensors. Conventional avionics system design will require these sensors to be connected to a few Remote Health Units (RHU), which are connected to robust, micro flight computers through a serial bus. This results in a large mass of cabling and unacceptable weight. This paper first gives a survey of several techniques that may reduce the cabling mass for sensors. These techniques can be categorized into four classes: power line communication, serial sensor buses, compound serial buses, and wireless network. The power line communication approach uses the power line to carry both power and data, so that the conventional data lines can be eliminated. The serial sensor bus approach reduces most of the cabling by connecting all the sensors with a single (or redundant) serial bus. Many standard buses for industrial control and sensor buses can support several hundreds of nodes, however, have not been space qualified. Conventional avionics serial buses such as the Mil-Std-1553B bus and IEEE 1394a are space qualified but can support only a limited number of nodes. The third approach is to combine avionics buses to increase their addressability. The reliability, EMI/EMC, and flight qualification issues of wireless networks have to be addressed. Several wireless networks such as the IEEE 802.11 and Ultra Wide Band are surveyed in this paper. The placement of sensors can also affect cable mass. Excessive sensors increase the number of cables unnecessarily. Insufficient number of sensors may not provide adequate coverage of the system. This paper also discusses an optimal technique to place and validate sensors.

Fieldservers and Sensor Service Grid as Real-time Monitoring Infrastructure for Ubiquitous Sensor Networks

PubMed Central

Honda, Kiyoshi; Shrestha, Aadit; Witayangkurn, Apichon; Chinnachodteeranun, Rassarin; Shimamura, Hiroshi

2009-01-01

The fieldserver is an Internet based observation robot that can provide an outdoor solution for monitoring environmental parameters in real-time. The data from its sensors can be collected to a central server infrastructure and published on the Internet. The information from the sensor network will contribute to monitoring and modeling on various environmental issues in Asia, including agriculture, food, pollution, disaster, climate change etc. An initiative called Sensor Asia is developing an infrastructure called Sensor Service Grid (SSG), which integrates fieldservers and Web GIS to realize easy and low cost installation and operation of ubiquitous field sensor networks. PMID:22574018

Sub-micron surface plasmon resonance sensor systems

NASA Technical Reports Server (NTRS)

Glazier, James A. (Inventor); Amarie, Dragos (Inventor)

2012-01-01

A sensor for detecting the presence of a target analyte, ligand or molecule in a test fluid, comprising a light transmissive substrate on which an array of surface plasmon resonant (SPR) elements is mounted is described. A multi-channel sensor for detecting the presence of several targets with a single microchip sensor is described. A multi-channel sensor including collections of SPR elements which are commonly functionalized to one of several targets is also described. The detectors sense changes in the resonant response of the SPR elements indicative of binding with the targets.

Sub-micron surface plasmon resonance sensor systems

NASA Technical Reports Server (NTRS)

Amarie, Dragos (Inventor); Glazier, James A. (Inventor)

2011-01-01

A sensor for detecting the presence of a target analyte, ligand or molecule in a test fluid, comprising a light transmissive substrate on which an array of surface plasmon resonant (SPR) elements is mounted is described. A multichannel sensor for detecting the presence of several targets with a single microchip sensor is described. A multichannel sensor including collections of SPR elements which are commonly functionalized to one of several targets is also described. The detectors sense changes in the resonant response of the SPR elements indicative of binding with the targets.

Sub-micron surface plasmon resonance sensor systems

NASA Technical Reports Server (NTRS)

Glazier, James A. (Inventor); Dragnea, Bogdan (Inventor); Amarie, Dragos (Inventor)

2010-01-01

A sensor for detecting the presence of a target analyte, ligand or molecule in a test fluid, comprising a light transmissive substrate on which an array of surface plasmon resonant (SPR) elements is mounted is described. A multi-channel sensor for detecting the presence of several targets with a single microchip sensor is described. A multi-channel sensor including collections of SPR elements which are commonly functionalized to one of several targets is also described. The detectors sense changes in the resonant response of the SPR elements indicative of binding with the targets.

Sub-micron surface plasmon resonance sensor systems

NASA Technical Reports Server (NTRS)

Amarie, Dragos (Inventor); Glazier, James A. (Inventor); Dragnea, Bogdan (Inventor)

2010-01-01

A sensor for detecting the presence of a target analyte, ligand or molecule in a test fluid, comprising a light transmissive substrate on which an array of surface plasmon resonant (SPR) elements is mounted is described. A multi-channel sensor for detecting the presence of several targets with a single micro-chip sensor is described. A multi-channel sensor including collections of SPR elements which are commonly functionalized to one of several targets is also described. The detectors sense changes in the resonant response of the SPR elements indicative of binding with the targets.

Sub-micron surface plasmon resonance sensor systems

NASA Technical Reports Server (NTRS)

Glazier, James A. (Inventor); Amarie, Dragos (Inventor)

2011-01-01

A sensor for detecting the presence of a target analyte, ligand or molecule in a test fluid, comprising a light transmissive substrate on which an array of surface plasmon resonant (SPR) elements is mounted is described. A multi-channel sensor for detecting the presence of several targets with a single micro-chip sensor is described. A multi-channel sensor including collections of SPR elements which are commonly functionalized to one of several targets is also described. The detectors sense changes in the resonant response of the SPR elements indicative of binding with the targets.

Data collection system: Earth Resources Technology Satellite-1

NASA Technical Reports Server (NTRS)

Cooper, S. (Editor); Ryan, P. T. (Editor)

1975-01-01

Subjects covered at the meeting concerned results on the overall data collection system including sensors, interface hardware, power supplies, environmental enclosures, data transmission, processing and distribution, maintenance and integration in resources management systems.

Operating systems and network protocols for wireless sensor networks.

PubMed

Dutta, Prabal; Dunkels, Adam

2012-01-13

Sensor network protocols exist to satisfy the communication needs of diverse applications, including data collection, event detection, target tracking and control. Network protocols to enable these services are constrained by the extreme resource scarcity of sensor nodes-including energy, computing, communications and storage-which must be carefully managed and multiplexed by the operating system. These challenges have led to new protocols and operating systems that are efficient in their energy consumption, careful in their computational needs and miserly in their memory footprints, all while discovering neighbours, forming networks, delivering data and correcting failures.

Method and apparatus for detecting and determining event characteristics with reduced data collection

NASA Technical Reports Server (NTRS)

Totman, Peter D. (Inventor); Everton, Randy L. (Inventor); Egget, Mark R. (Inventor); Macon, David J. (Inventor)

2007-01-01

A method and apparatus for detecting and determining event characteristics such as, for example, the material failure of a component, in a manner which significantly reduces the amount of data collected. A sensor array, including a plurality of individual sensor elements, is coupled to a programmable logic device (PLD) configured to operate in a passive state and an active state. A triggering event is established such that the PLD records information only upon detection of the occurrence of the triggering event which causes a change in state within one or more of the plurality of sensor elements. Upon the occurrence of the triggering event, the change in state of the one or more sensor elements causes the PLD to record in memory which sensor element detected the event and at what time the event was detected. The PLD may be coupled with a computer for subsequent downloading and analysis of the acquired data.

A sensor data format incorporating battery charge information for smartphone-based mHealth applications

NASA Astrophysics Data System (ADS)

Escobar, Rodrigo; Akopian, David; Boppana, Rajendra

2015-03-01

Remote health monitoring systems involve energy-constrained devices, such as sensors and mobile gateways. Current data formats for communication of health data, such as DICOM and HL7, were not designed for multi-sensor applications or to enable the management of power-constrained devices in health monitoring processes. In this paper, a data format suitable for collection of multiple sensor data, including readings and other operational parameters is presented. By using the data format, the system management can assess energy consumptions and plan realistic monitoring scenarios. The proposed data format not only outperforms other known data formats in terms of readability, flexibility, interoperability and validation of compliant documents, but also enables energy assessment capability for realistic data collection scenarios and maintains or even reduces the overhead introduced due to formatting. Additionally, we provide analytical methods to estimate incremental energy consumption by various sensors and experiments to measure the actual battery drain on smartphones.

Sense, decide, act, communicate (SDAC): next generation of smart sensor systems

NASA Astrophysics Data System (ADS)

Berry, Nina; Davis, Jesse; Ko, Teresa H.; Kyker, Ron; Pate, Ron; Stark, Doug; Stinnett, Regan; Baker, James; Cushner, Adam; Van Dyke, Colin; Kyckelhahn, Brian

2004-09-01

The recent war on terrorism and increased urban warfare has been a major catalysis for increased interest in the development of disposable unattended wireless ground sensors. While the application of these sensors to hostile domains has been generally governed by specific tasks, this research explores a unique paradigm capitalizing on the fundamental functionality related to sensor systems. This functionality includes a sensors ability to Sense - multi-modal sensing of environmental events, Decide - smart analysis of sensor data, Act - response to environmental events, and Communication - internal to system and external to humans (SDAC). The main concept behind SDAC sensor systems is to integrate the hardware, software, and networking to generate 'knowledge and not just data'. This research explores the usage of wireless SDAC units to collectively make up a sensor system capable of persistent, adaptive, and autonomous behavior. These systems are base on the evaluation of scenarios and existing systems covering various domains. This paper presents a promising view of sensor network characteristics, which will eventually yield smart (intelligent collectives) network arrays of SDAC sensing units generally applicable to multiple related domains. This paper will also discuss and evaluate the demonstration system developed to test the concepts related to SDAC systems.

An energy-efficient and secure hybrid algorithm for wireless sensor networks using a mobile data collector

NASA Astrophysics Data System (ADS)

Dayananda, Karanam Ravichandran; Straub, Jeremy

2017-05-01

This paper proposes a new hybrid algorithm for security, which incorporates both distributed and hierarchal approaches. It uses a mobile data collector (MDC) to collect information in order to save energy of sensor nodes in a wireless sensor network (WSN) as, in most networks, these sensor nodes have limited energy. Wireless sensor networks are prone to security problems because, among other things, it is possible to use a rogue sensor node to eavesdrop on or alter the information being transmitted. To prevent this, this paper introduces a security algorithm for MDC-based WSNs. A key use of this algorithm is to protect the confidentiality of the information sent by the sensor nodes. The sensor nodes are deployed in a random fashion and form group structures called clusters. Each cluster has a cluster head. The cluster head collects data from the other nodes using the time-division multiple access protocol. The sensor nodes send their data to the cluster head for transmission to the base station node for further processing. The MDC acts as an intermediate node between the cluster head and base station. The MDC, using its dynamic acyclic graph path, collects the data from the cluster head and sends it to base station. This approach is useful for applications including warfighting, intelligent building and medicine. To assess the proposed system, the paper presents a comparison of its performance with other approaches and algorithms that can be used for similar purposes.

Server rack for improved data center management

DOEpatents

Bermudez Rodriguez, Sergio A.; Hamann, Hendrik F.; Wehle, Hans-Dieter

2018-01-09

Methods and systems for data center management include collecting sensor data from one or more sensors in a rack; determining a location and identifying information for each asset in the rack using a set of asset tags associated with respective assets; communicating the sensor and asset location to a communication module; receiving an instruction from the communication module; and executing the received instruction to change a property of the rack.

Underwater (UW) Unexploded Ordnance (UXO) Multi-Sensor Data Base (MSDB) Collection

DTIC Science & Technology

2009-07-01

11 FIGURE 6 RTG SENSOR. FOUR SENSOR TRIADS ARE SHOWN, EACH WITH A 3-AXIS FLUXGATE MAGNETOMETER ...used by RTG to measure the gradients. Each triad includes a 3-axis fluxgate magnetometer and a set of feedback coils. The outputs of three triad...each with a 3-axis fluxgate magnetometer (internal, not clearly visible) and a set of 3 feedback coils. The upper triad 3-axis magnetometer

Human Movement Detection and Idengification Using Pyroelectric Infrared Sensors

PubMed Central

Yun, Jaeseok; Lee, Sang-Shin

2014-01-01

Pyroelectric infrared (PIR) sensors are widely used as a presence trigger, but the analog output of PIR sensors depends on several other aspects, including the distance of the body from the PIR sensor, the direction and speed of movement, the body shape and gait. In this paper, we present an empirical study of human movement detection and idengification using a set of PIR sensors. We have developed a data collection module having two pairs of PIR sensors orthogonally aligned and modified Fresnel lenses. We have placed three PIR-based modules in a hallway for monitoring people; one module on the ceiling; two modules on opposite walls facing each other. We have collected a data set from eight subjects when walking in three different conditions: two directions (back and forth), three distance intervals (close to one wall sensor, in the middle, close to the other wall sensor) and three speed levels (slow, moderate, fast). We have used two types of feature sets: a raw data set and a reduced feature set composed of amplitude and time to peaks; and passage duration extracted from each PIR sensor. We have performed classification analysis with well-known machine learning algorithms, including instance-based learning and support vector machine. Our findings show that with the raw data set captured from a single PIR sensor of each of the three modules, we could achieve more than 92% accuracy in classifying the direction and speed of movement, the distance interval and idengifying subjects. We could also achieve more than 94% accuracy in classifying the direction, speed and distance and idengifying subjects using the reduced feature set extracted from two pairs of PIR sensors of each of the three modules. PMID:24803195

Wearable Sensors; Applications, design and implementation

NASA Astrophysics Data System (ADS)

Mukhopadhyay, Subhas Chandra; Islam, Tarikul

2017-12-01

With the ability to monitor a vast range of physiological parameters, combined with wireless technology, wireless sensor networks and the Internet of Things, wearable sensors are revolutionising the field of digital health monitoring. In addition to applications in health monitoring, such technology is being used to monitor the state of our living environment and even the quality of our foods and the wellbeing of livestock. Written for scientists, engineers and practitioners by an international collection of authors, this book reviews the fundamentals of wearable sensors, their function, design, fabrication and implementation. Their application and advanced aspects including interface electronics and signal processing for easy interpretation of data, data transmission, data networking, data security, and privacy are also included.

Automatically augmenting lifelog events using pervasively generated content from millions of people.

PubMed

Doherty, Aiden R; Smeaton, Alan F

2010-01-01

In sensor research we take advantage of additional contextual sensor information to disambiguate potentially erroneous sensor readings or to make better informed decisions on a single sensor's output. This use of additional information reinforces, validates, semantically enriches, and augments sensed data. Lifelog data is challenging to augment, as it tracks one's life with many images including the places they go, making it non-trivial to find associated sources of information. We investigate realising the goal of pervasive user-generated content based on sensors, by augmenting passive visual lifelogs with "Web 2.0" content collected by millions of other individuals.

Scaleable wireless web-enabled sensor networks

NASA Astrophysics Data System (ADS)

Townsend, Christopher P.; Hamel, Michael J.; Sonntag, Peter A.; Trutor, B.; Arms, Steven W.

2002-06-01

Our goal was to develop a long life, low cost, scalable wireless sensing network, which collects and distributes data from a wide variety of sensors over the internet. Time division multiple access was employed with RF transmitter nodes (each w/unique16 bit address) to communicate digital data to a single receiver (range 1/3 mile). One thousand five channel nodes can communicate to one receiver (30 minute update). Current draw (sleep) is 20 microamps, allowing 5 year battery life w/one 3.6 volt Li-Ion AA size battery. The network nodes include sensor excitation (AC or DC), multiplexer, instrumentation amplifier, 16 bit A/D converter, microprocessor, and RF link. They are compatible with thermocouples, strain gauges, load/torque transducers, inductive/capacitive sensors. The receiver (418 MHz) includes a single board computer (SBC) with Ethernet capability, internet file transfer protocols (XML/HTML), and data storage. The receiver detects data from specific nodes, performs error checking, records the data. The web server interrogates the SBC (from Microsoft's Internet Explorer or Netscape's Navigator) to distribute data. This system can collect data from thousands of remote sensors on a smart structure, and be shared by an unlimited number of users.

Trade-off analysis of modes of data handling for earth resources (ERS), volume 1

NASA Technical Reports Server (NTRS)

1975-01-01

Data handling requirements are reviewed for earth observation missions along with likely technology advances. Parametric techniques for synthesizing potential systems are developed. Major tasks include: (1) review of the sensors under development and extensions of or improvements in these sensors; (2) development of mission models for missions spanning land, ocean, and atmosphere observations; (3) summary of data handling requirements including the frequency of coverage, timeliness of dissemination, and geographic relationships between points of collection and points of dissemination; (4) review of data routing to establish ways of getting data from the collection point to the user; (5) on-board data processing; (6) communications link; and (7) ground data processing. A detailed synthesis of three specific missions is included.

Crowd-Sourcing Seismic Data for Education and Research Opportunities with the Quake-Catcher Network

NASA Astrophysics Data System (ADS)

Sumy, D. F.; DeGroot, R. M.; Benthien, M. L.; Cochran, E. S.; Taber, J. J.

2016-12-01

The Quake Catcher Network (QCN; quakecatcher.net) uses low cost micro-electro-mechanical system (MEMS) sensors hosted by volunteers to collect seismic data. Volunteers use accelerometers internal to laptop computers, phones, tablets or small (the size of a matchbox) MEMS sensors plugged into desktop computers using a USB connector to collect scientifically useful data. Data are collected and sent to a central server using the Berkeley Open Infrastructure for Network Computing (BOINC) distributed computing software. Since 2008, sensors installed in museums, schools, offices, and residences have collected thousands of earthquake records, including the 2010 M8.8 Maule, Chile, the 2010 M7.1 Darfield, New Zealand, and 2015 M7.8 Gorkha, Nepal earthquakes. In 2016, the QCN in the United States transitioned to the Incorporated Research Institutions for Seismology (IRIS) Consortium and the Southern California Earthquake Center (SCEC), which are facilities funded through the National Science Foundation and the United States Geological Survey, respectively. The transition has allowed for an influx of new ideas and new education related efforts, which include focused installations in several school districts in southern California, on Native American reservations in North Dakota, and in the most seismically active state in the contiguous U.S. - Oklahoma. We present and describe these recent educational opportunities, and highlight how QCN has engaged a wide sector of the public in scientific data collection, particularly through the QCN-EPIcenter Network and NASA Mars InSight teacher programs. QCN provides the public with information and insight into how seismic data are collected, and how researchers use these data to better understand and characterize seismic activity. Lastly, we describe how students use data recorded by QCN sensors installed in their classrooms to explore and investigate felt earthquakes, and look towards the bright future of the network.

Intelligent sensor and controller framework for the power grid

DOEpatents

Akyol, Bora A.; Haack, Jereme Nathan; Craig, Jr., Philip Allen; Tews, Cody William; Kulkarni, Anand V.; Carpenter, Brandon J.; Maiden, Wendy M.; Ciraci, Selim

2015-07-28

Disclosed below are representative embodiments of methods, apparatus, and systems for monitoring and using data in an electric power grid. For example, one disclosed embodiment comprises a sensor for measuring an electrical characteristic of a power line, electrical generator, or electrical device; a network interface; a processor; and one or more computer-readable storage media storing computer-executable instructions. In this embodiment, the computer-executable instructions include instructions for implementing an authorization and authentication module for validating a software agent received at the network interface; instructions for implementing one or more agent execution environments for executing agent code that is included with the software agent and that causes data from the sensor to be collected; and instructions for implementing an agent packaging and instantiation module for storing the collected data in a data container of the software agent and for transmitting the software agent, along with the stored data, to a next destination.

Intelligent sensor and controller framework for the power grid

DOE Office of Scientific and Technical Information (OSTI.GOV)

Akyol, Bora A.; Haack, Jereme Nathan; Craig, Jr., Philip Allen

Disclosed below are representative embodiments of methods, apparatus, and systems for monitoring and using data in an electric power grid. For example, one disclosed embodiment comprises a sensor for measuring an electrical characteristic of a power line, electrical generator, or electrical device; a network interface; a processor; and one or more computer-readable storage media storing computer-executable instructions. In this embodiment, the computer-executable instructions include instructions for implementing an authorization and authentication module for validating a software agent received at the network interface; instructions for implementing one or more agent execution environments for executing agent code that is included with themore » software agent and that causes data from the sensor to be collected; and instructions for implementing an agent packaging and instantiation module for storing the collected data in a data container of the software agent and for transmitting the software agent, along with the stored data, to a next destination.« less

"Data like a movie instead of a photo” - continuous water sensor data collection, 2015 Lake MI CSMI

EPA Science Inventory

During the 2015 Lake Michigan CSMI effort we collected continuous undulating tow and autonomous glider data including conductivity, temperature, depth, fluorescence, and backscatter across the northern half of Lake Michigan. During the same period, we also collected discreet vert...

Explosive Infrasonic Events: Sensor Comparison Experiment (SCE)

DOE Office of Scientific and Technical Information (OSTI.GOV)

Schnurr, J. M.; Garces, M.; Rodgers, A. J.

SCE (sensor comparison experiment) 1 through 4 consists of a series of four controlled above-ground explosions designed to provide new data for overpressure propagation. Infrasound data were collected by LLNL iPhones and other sensors. Origin times, locations HOB, and yields are not being released at this time and are therefore not included in this report. This preliminary report will be updated as access to additional data changes, or instrument responses are determined.

Quantifying the Influence of Near-Surface Water-Energy Budgets on Soil Thermal Properties Using a Network of Coupled Meteorological and Vadose Zone Instrument Arrays in Indiana, USA

NASA Astrophysics Data System (ADS)

Naylor, S.; Gustin, A. R.; Ellett, K. M.

2012-12-01

Weather stations that collect reliable, sustained meteorological data sets are becoming more widely distributed because of advances in both instrumentation and data server technology. However, sites collecting soil moisture and soil temperature data remain sparse with even fewer locations where complete meteorological data are collected in conjunction with soil data. Thanks to the advent of sensors that collect continuous in-situ thermal properties data for soils, we have gone a step further and incorporated thermal properties measurements as part of hydrologic instrument arrays in central and northern Indiana. The coupled approach provides insights into the variability of soil thermal conductivity and diffusivity attributable to geologic and climatological controls for various hydrogeologic settings. These data are collected to facilitate the optimization of ground-source heat pumps (GSHPs) in the glaciated Midwest by establishing publicly available data that can be used to parameterize system design models. A network of six monitoring sites was developed in Indiana. Sensors that determine thermal conductivity and diffusivity using radial differential temperature measurements around a heating wire were installed at 1.2 meters below ground surface— a typical depth for horizontal GSHP systems. Each site also includes standard meteorological sensors for calculating reference evapotranspiration following the methods by the Food and Agriculture Organization (FAO) of the United Nations. Vadose zone instrumentation includes time domain reflectometry soil-moisture and temperature sensors installed at 0.3-meter depth intervals down to a 1.8-meter depth, in addition to matric potential sensors at 0.15, 0.3, 0.6, and 1.2 meters. Cores collected at 0.3-meter intervals were analyzed in a laboratory for grain size distribution, bulk density, thermal conductivity, and thermal diffusivity. Our work includes developing methods for calibrating thermal properties sensors based on known standards and comparing measurements from transient line heat source devices. Transform equations have been developed to correct in-situ measurements of thermal conductivity and comparing these results with soil moisture data indicates that thermal conductivity can increase by as much as 25 percent during wetting front propagation. Thermal dryout curves have also been modeled based on laboratory conductivity data collected from core samples to verify field measurements, and alternatively, temperature profile data are used to calibrate near-surface temperature gradient models. We compare data collected across various spatial scales to assess the potential for upscaling near-surface thermal regimes based on available soils data. A long-term goal of the monitoring effort is to establish continuous data sets that determine the effect of climate variability on soil thermal properties such that expected ranges in thermal conductivity can be used to determine optimal ground-coupling loop lengths for GSHP systems.

Turbine rotor disk health monitoring assessment based on sensor technology and spin tests data.

PubMed

Abdul-Aziz, Ali; Woike, Mark

2013-01-01

The paper focuses on presenting data obtained from spin test experiments of a turbine engine like rotor disk and assessing their correlation to the development of a structural health monitoring and fault detection system. The data were obtained under various operating conditions such as the rotor disk being artificially induced with and without a notch and rotated at a rotational speed of up to 10,000 rpm under balanced and imbalanced state. The data collected included blade tip clearance, blade tip timing measurements, and shaft displacements. Two different sensor technologies were employed in the testing: microwave and capacitive sensors, respectively. The experimental tests were conducted at the NASA Glenn Research Center's Rotordynamics Laboratory using a high precision spin system. Disk flaw observations and related assessments from the collected data for both sensors are reported and discussed.

Radiometric characterization of Landsat Collection 1 products

USGS Publications Warehouse

Micijevic, Esad; Haque, Md. Obaidul; Mishra, Nischal

2017-01-01

Landsat data in the U.S. Geological Survey (USGS) archive are being reprocessed to generate a tiered collection of consistently geolocated and radiometrically calibrated products that are suitable for time series analyses. With the implementation of the collection management, no major updates will be made to calibration of the Landsat sensors within a collection. Only calibration parameters needed to maintain the established calibration trends without an effect on derived environmental records will be regularly updated, while all other changes will be deferred to a new collection. This first collection, Collection 1, incorporates various radiometric calibration updates to all Landsat sensors including absolute and relative gains for Landsat 8 Operational Land Imager (OLI), stray light correction for Landsat 8 Thermal Infrared Sensor (TIRS), absolute gains for Landsat 4 and 5 Thematic Mappers (TM), recalibration of Landsat 1-5 Multispectral Scanners (MSS) to ensure radiometric consistency among different formats of archived MSS data, and a transfer of Landsat 8 OLI reflectance based calibration to all previous Landsat sensors. While all OLI/TIRS, ETM+ and majority of TM data have already been reprocessed to Collection 1, a completion of MSS and remaining TM data reprocessing is expected by the end of this year. It is important to note that, although still available for download from the USGS web pages, the products generated using the Pre-Collection processing do not benefit from the latest radiometric calibration updates. In this paper, we are assessing radiometry of solar reflective bands in Landsat Collection 1 products through analysis of trends in on-board calibrator and pseudo invariant site (PICS) responses.

Radiometric characterization of Landsat Collection 1 products

NASA Astrophysics Data System (ADS)

Micijevic, Esad; Haque, Md. Obaidul; Mishra, Nischal

2017-09-01

Landsat data in the U.S. Geological Survey (USGS) archive are being reprocessed to generate a tiered collection of consistently geolocated and radiometrically calibrated products that are suitable for time series analyses. With the implementation of the collection management, no major updates will be made to calibration of the Landsat sensors within a collection. Only calibration parameters needed to maintain the established calibration trends without an effect on derived environmental records will be regularly updated, while all other changes will be deferred to a new collection. This first collection, Collection 1, incorporates various radiometric calibration updates to all Landsat sensors including absolute and relative gains for Landsat 8 Operational Land Imager (OLI), stray light correction for Landsat 8 Thermal Infrared Sensor (TIRS), absolute gains for Landsat 4 and 5 Thematic Mappers (TM), recalibration of Landsat 1-5 Multispectral Scanners (MSS) to ensure radiometric consistency among different formats of archived MSS data, and a transfer of Landsat 8 OLI reflectance based calibration to all previous Landsat sensors. While all OLI/TIRS, ETM+ and majority of TM data have already been reprocessed to Collection 1, a completion of MSS and remaining TM data reprocessing is expected by the end of this year. It is important to note that, although still available for download from the USGS web pages, the products generated using the Pre-Collection processing do not benefit from the latest radiometric calibration updates. In this paper, we are assessing radiometry of solar reflective bands in Landsat Collection 1 products through analysis of trends in on-board calibrator and pseudo invariant site (PICS) responses.

Spatio-temporal interpolation of soil moisture in 3D+T using automated sensor network data

NASA Astrophysics Data System (ADS)

Gasch, C.; Hengl, T.; Magney, T. S.; Brown, D. J.; Gräler, B.

2014-12-01

Soil sensor networks provide frequent in situ measurements of dynamic soil properties at fixed locations, producing data in 2- or 3-dimensions and through time (2D+T and 3D+T). Spatio-temporal interpolation of 3D+T point data produces continuous estimates that can then be used for prediction at unsampled times and locations, as input for process models, and can simply aid in visualization of properties through space and time. Regression-kriging with 3D and 2D+T data has successfully been implemented, but currently the field of geostatistics lacks an analytical framework for modeling 3D+T data. Our objective is to develop robust 3D+T models for mapping dynamic soil data that has been collected with high spatial and temporal resolution. For this analysis, we use data collected from a sensor network installed on the R.J. Cook Agronomy Farm (CAF), a 37-ha Long-Term Agro-Ecosystem Research (LTAR) site in Pullman, WA. For five years, the sensors have collected hourly measurements of soil volumetric water content at 42 locations and five depths. The CAF dataset also includes a digital elevation model and derivatives, a soil unit description map, crop rotations, electromagnetic induction surveys, daily meteorological data, and seasonal satellite imagery. The soil-water sensor data, combined with the spatial and temporal covariates, provide an ideal dataset for developing 3D+T models. The presentation will include preliminary results and address main implementation strategies.

Clip-on wireless wearable microwave sensor for ambulatory cardiac monitoring.

PubMed

Fletcher, Richard R; Kulkarni, Sarang

2010-01-01

We present a new type of non-contact sensor for use in ambulatory cardiac monitoring. The sensor operation is based on a microwave Doppler technique; however, instead of detecting the heart activity from a distance, the sensor is placed on the patient's chest over the clothing. The microwave sensor directly measures heart movement rather than electrical activity, and is thus complementary to ECG. The primary advantages of the microwave sensor includes small size, light weight, low power, low-cost, and the ability to operate through clothing. We present a sample sensor design that incorporates a 2.4 GHz Doppler circuit, integrated microstrip patch antenna, and microntroller with 12-bit ADC data sampling. The prototype sensor also includes a wireless data link for sending data to a remote PC or mobile phone. Sample data is shown for several subjects and compared to data from a commercial portable ECG device. Data collected from the microwave sensor exhibits a significant amount of features, indicating possible use as a tool for monitoring heart mechanics and detection of abnormalities such as fibrillation and akinesia.

The IRIS Data Management Center: An international "network of networks", providing open, automated access to geographically distributed sensors of geophysical and environmental data.

NASA Astrophysics Data System (ADS)

Benson, R. B.; Ahern, T. K.; Trabant, C.

2006-12-01

The IRIS Data Management System has long supported international collaboration for seismology by both deploying a global network of seismometers and creating and maintaining an open and accessible archive in Seattle, WA, known as the Data Management Center (DMC). With sensors distributed on a global scale spanning more than 30 years of digital data, the DMC provides a rich repository of observations across broad time and space domains. Primary seismological data types include strong motion and broadband seismometers, conventional and superconducting gravimeters, tilt and creep meters, GPS measurements, along with other similar sensors that record accurate and calibrated ground motion. What may not be as well understood is the volume of environmental data that accompanies typical seismological data these days. This poster will review the types of time-series data that are currently being collected, how they are collected, and made freely available for download at the IRIS DMC. Environmental sensor data that is often co-located with geophysical data sensors include temperature, barometric pressure, wind direction and speed, humidity, insolation, rain gauge, and sometimes hydrological data like water current, level, temperature and depth. As the primary archival institution of the International Federation of Digital Seismograph Networks (FDSN), the IRIS DMC collects approximately 13,600 channels of real-time data from 69 different networks, from close to 1600 individual stations, currently averaging 10Tb per year in total. A major contribution to the IRIS archive currently is the EarthScope project data, a ten-year science undertaking that is collecting data from a high-resolution, multi-variate sensor network. Data types include magnetotelluric, high-sample rate seismics from a borehole drilled into the San Andreas fault (SAFOD) and various types of strain data from the Plate Boundary Observatory (PBO). In addition to the DMC, data centers located in other countries are networked seamlessly, and are providing access for researchers to these data from national networks around the world utilizing the IRIS developed Data Handling Interface (DHI) system. This poster will highlight some of the DHI enabled clients that allow geophysical information to be directly transferred to the clients. This ability allows one to construct a virtual network of data centers providing the illusion of a single virtual observatory. Furthermore, some of the features that will be shown include direct connections to MATLAB and the ability to access globally distributed sensor data in real time. We encourage discussion and participation from network operators who would like to leverage existing technology, as well as enabling collaboration.

A Review of Artificial Lateral Line in Sensor Fabrication and Bionic Applications for Robot Fish.

PubMed

Liu, Guijie; Wang, Anyi; Wang, Xinbao; Liu, Peng

2016-01-01

Lateral line is a system of sense organs that can aid fishes to maneuver in a dark environment. Artificial lateral line (ALL) imitates the structure of lateral line in fishes and provides invaluable means for underwater-sensing technology and robot fish control. This paper reviews ALL, including sensor fabrication and applications to robot fish. The biophysics of lateral line are first introduced to enhance the understanding of lateral line structure and function. The design and fabrication of an ALL sensor on the basis of various sensing principles are then presented. ALL systems are collections of sensors that include carrier and control circuit. Their structure and hydrodynamic detection are reviewed. Finally, further research trends and existing problems of ALL are discussed.

Method and system for gathering a library of response patterns for sensor arrays

DOEpatents

Zaromb, Solomon

1992-01-01

A method of gathering a library of response patterns for one or more sensor arrays used in the detection and identification of chemical components in a fluid includes the steps of feeding samples of fluid with time-spaced separation of known components to the sensor arrays arranged in parallel or series configurations. Modifying elements such as heating filaments of differing materials operated at differing temperatures are included in the configurations to duplicate operational modes designed into the portable detection systems with which the calibrated sensor arrays are to be used. The response patterns from the known components are collected into a library held in the memory of a microprocessor for comparison with the response patterns of unknown components.

Inexpensive, Low Power, Open-Source Data Logging in the Field

NASA Astrophysics Data System (ADS)

Sandell, C. T.; Wickert, A. D.

2016-12-01

Collecting a robust data set of environmental conditions with commercial equipment is often cost prohibitive. I present the ALog, a general-purpose, inexpensive, low-power, open-source data logger that has proven its durability on long-term deployments in the harsh conditions of high altitude glaciers and humid river deltas. The ALog was developed to fill the need for a capable, rugged, easy-to-use, inexpensive, open-source hardware targeted at long-term remote deployment in nearly any environment. Building on the popular Arduino platform, the hardware features a high-precision clock, full size SD card slot for high-volume data storage, screw terminals, six analog inputs, two digital inputs, one digital interrupt, 3.3V and 5V power outputs, and SPI and I2C communication capability. The design is focused on extremely low power consumption allowing the Alog to be deployed for years on a single set of common alkaline batteries. The power efficiency of the Alog eliminates the difficulties associated with field power collection including additional hardware and installation costs, dependence on weather conditions, possible equipment failure, and the transport of bulky/heavy equipment to a remote site. Battery power increases suitable data collection sites (too shaded for photovoltaics) and allows for low profile installation options (including underground). The ALog has gone through continuous development with over four years of successful data collection in hydrologic field research. Over this time, software support for a wide range of sensors has been made available such as ultrasonic rangefinders (for water level, snow accumulation and glacial melt), temperature sensors (air and groundwater), humidity sensors, pyranometers, inclinometers, rain gauges, soil moisture and water potential sensors, resistance-based tools to measure frost heave, and cameras that trigger on events. The software developed for use with the ALog allows simple integration of established commercial sensors, including example implementation code so users with limited programming knowledge can get up and running with ease. All development files including design schematics, circuit board layouts, and source code files are open-source to further eliminate barriers to its use and allow community development contribution.

Electromagnetic sensors for general lightning application

NASA Technical Reports Server (NTRS)

Baum, C. E.; Breen, E. L.; Onell, J. P.; Moore, C. B.; Sower, G. D.

1980-01-01

Electromagnetic sensors for general lightning applications in measuring environment are discussed as well as system response to the environment. This includes electric and magnetic fields, surface current and charge densities, and currents on conductors. Many EMP sensors are directly applicable to lightning measurements, but there are some special cases of lightning measurements involving direct strikes which require special design considerations for the sensors. The sensors and instrumentation used by NMIMT in collecting data on lightning at South Baldy peak in central New Mexico during the 1978 and 1979 lightning seasons are also discussed. The Langmuir Laboratory facilities and details of the underground shielded instrumentation room and recording equipment are presented.

An Energy Efficient MAC Protocol for Multi-Hop Swallowable Body Sensor Networks

PubMed Central

Lin, Lin; Yang, Chengfeng; Wong, Kai Juan; Yan, Hao; Shen, Junwen; Phee, Soo Jay

2014-01-01

Swallowable body sensor networks (BSNs) are composed of sensors which are swallowed by patients and send the collected data to the outside coordinator. These sensors are energy constraint and the batteries are difficult to be replaced. The medium access control (MAC) protocol plays an important role in energy management. This paper investigates an energy efficient MAC protocol design for swallowable BSNs. Multi-hop communication is analyzed and proved more energy efficient than single-hop communication within the human body when the circuitry power is low. Based on this result, a centrally controlled time slotting schedule is proposed. The major workload is shifted from the sensors to the coordinator. The coordinator collects the path-loss map and calculates the schedules, including routing, slot assignment and transmission power. Sensor nodes follow the schedules to send data in a multi-hop way. The proposed protocol is compared with the IEEE 802.15.6 protocol in terms of energy consumption. The results show that it is more energy efficient than IEEE 802.15.6 for swallowable BSN scenarios. PMID:25330049

Instrumentation Automation for Concrete Structures: Report 2, Automation Hardware and Retrofitting Techniques, and Report 3, Available Data Collection and Reduction Software

DTIC Science & Technology

1987-06-01

commercial products. · OP -- Typical cutout at a plumbiinc location where an automated monitoring system has bv :• installed. The sensor used with the...This report provides a description of commercially available sensors , instruments, and ADP equipment that may be selected to fully automate...automated. The automated plumbline monitoring system includes up to twelve sensors , repeaters, a system controller, and a printer. The system may

Contributions of the SDR Task Network tool to Calibration and Validation of the NPOESS Preparatory Project instruments

NASA Astrophysics Data System (ADS)

Feeley, J.; Zajic, J.; Metcalf, A.; Baucom, T.

2009-12-01

The National Polar-orbiting Operational Environmental Satellite System (NPOESS) Preparatory Project (NPP) Calibration and Validation (Cal/Val) team is planning post-launch activities to calibrate the NPP sensors and validate Sensor Data Records (SDRs). The IPO has developed a web-based data collection and visualization tool in order to effectively collect, coordinate, and manage the calibration and validation tasks for the OMPS, ATMS, CrIS, and VIIRS instruments. This tool is accessible to the multi-institutional Cal/Val teams consisting of the Prime Contractor and Government Cal/Val leads along with the NASA NPP Mission team, and is used for mission planning and identification/resolution of conflicts between sensor activities. Visualization techniques aid in displaying task dependencies, including prerequisites and exit criteria, allowing for the identification of a critical path. This presentation will highlight how the information is collected, displayed, and used to coordinate the diverse instrument calibration/validation teams.

Low Cost Multi-Sensor Robot Laser Scanning System and its Accuracy Investigations for Indoor Mapping Application

NASA Astrophysics Data System (ADS)

Chen, C.; Zou, X.; Tian, M.; Li, J.; Wu, W.; Song, Y.; Dai, W.; Yang, B.

2017-11-01

In order to solve the automation of 3D indoor mapping task, a low cost multi-sensor robot laser scanning system is proposed in this paper. The multiple-sensor robot laser scanning system includes a panorama camera, a laser scanner, and an inertial measurement unit and etc., which are calibrated and synchronized together to achieve simultaneously collection of 3D indoor data. Experiments are undertaken in a typical indoor scene and the data generated by the proposed system are compared with ground truth data collected by a TLS scanner showing an accuracy of 99.2% below 0.25 meter, which explains the applicability and precision of the system in indoor mapping applications.

Ram-air sample collection device for a chemical warfare agent sensor

DOEpatents

Megerle, Clifford A.; Adkins, Douglas R.; Frye-Mason, Gregory C.

2002-01-01

In a surface acoustic wave sensor mounted within a body, the sensor having a surface acoustic wave array detector and a micro-fabricated sample preconcentrator exposed on a surface of the body, an apparatus for collecting air for the sensor, comprising a housing operatively arranged to mount atop the body, the housing including a multi-stage channel having an inlet and an outlet, the channel having a first stage having a first height and width proximate the inlet, a second stage having a second lower height and width proximate the micro-fabricated sample preconcentrator, a third stage having a still lower third height and width proximate the surface acoustic wave array detector, and a fourth stage having a fourth height and width proximate the outlet, where the fourth height and width are substantially the same as the first height and width.

System and Method for RFID-Enabled Information Collection

NASA Technical Reports Server (NTRS)

Fink, Patrick W. (Inventor); Kennedy, Timothy F. (Inventor); Lin, Gregory Y. (Inventor); Ngo, Phong H. (Inventor); Byerly, Diane (Inventor)

2016-01-01

Methods, apparatuses and systems for radio frequency identification (RFID)-enabled information collection are disclosed, including an enclosure, a collector coupled to the enclosure, an interrogator, a processor, and one or more RFID field sensors, each having an individual identification, disposed within the enclosure. In operation, the interrogator transmits an incident signal to the collector, causing the collector to generate an electromagnetic field within the enclosure. The electromagnetic field is affected by one or more influences. RFID sensors respond to the electromagnetic field by transmitting reflected signals containing the individual identifications of the responding RFID sensors to the interrogator. The interrogator receives the reflected signals, measures one or more returned signal strength indications ("RSSI") of the reflected signals and sends the RSSI measurements and identification of the responding RFID sensors to the processor to determine one or more facts about the influences. Other embodiments are also described.

Turbine Rotor Disk Health Monitoring Assessment Based on Sensor Technology and Spin Tests Data

PubMed Central

2013-01-01

The paper focuses on presenting data obtained from spin test experiments of a turbine engine like rotor disk and assessing their correlation to the development of a structural health monitoring and fault detection system. The data were obtained under various operating conditions such as the rotor disk being artificially induced with and without a notch and rotated at a rotational speed of up to 10,000 rpm under balanced and imbalanced state. The data collected included blade tip clearance, blade tip timing measurements, and shaft displacements. Two different sensor technologies were employed in the testing: microwave and capacitive sensors, respectively. The experimental tests were conducted at the NASA Glenn Research Center's Rotordynamics Laboratory using a high precision spin system. Disk flaw observations and related assessments from the collected data for both sensors are reported and discussed. PMID:23844396

The Design of an Autonomous Underwater Vehicle for Water Quality Monitoring

NASA Astrophysics Data System (ADS)

Li, Yulong; Liu, Rong; Liu, Shujin

2018-01-01

This paper describes the development of a civilian-used autonomous underwater vehicle (AUV) for water quality monitoring at reservoirs and watercourses that can obtain realtime visual and locational information. The mechanical design was completed with CAD software Solidworks. Four thrusters—two horizontal and two vertical—on board enable the vehicle to surge, heave, yaw, and pitch. A specialized water sample collection compartment is designed to perform water collection at target locations. The vehicle has a central controller—STM32—and a sub-coordinate controller—Arduino MEGA 2560—that coordinates multiple sensors including an inertial sensor, ultrasonic sensors, etc. Global Navigation Satellite System (GNSS) and the inertial sensor enable the vehicle’s localization. Remote operators monitor and control the vehicle via a host computer system. Operators choose either semi-autonomous mode in which they set target locations or manual mode. The experimental results show that the vehicle is able to perform well in either mode.

A deployment of fine-grained sensor network and empirical analysis of urban temperature.

PubMed

Thepvilojanapong, Niwat; Ono, Takahiro; Tobe, Yoshito

2010-01-01

Temperature in an urban area exhibits a complicated pattern due to complexity of infrastructure. Despite geographical proximity, structures of a group of buildings and streets affect changes in temperature. To investigate the pattern of fine-grained distribution of temperature, we installed a densely distributed sensor network called UScan. In this paper, we describe the system architecture of UScan as well as experience learned from installing 200 sensors in downtown Tokyo. The field experiment of UScan system operated for two months to collect long-term urban temperature data. To analyze the collected data in an efficient manner, we propose a lightweight clustering methodology to study the correlation between the pattern of temperature and various environmental factors including the amount of sunshine, the width of streets, and the existence of trees. The analysis reveals meaningful results and asserts the necessity of fine-grained deployment of sensors in an urban area.

Design of polarization imaging system based on CIS and FPGA

NASA Astrophysics Data System (ADS)

Zeng, Yan-an; Liu, Li-gang; Yang, Kun-tao; Chang, Da-ding

2008-02-01

As polarization is an important characteristic of light, polarization image detecting is a new image detecting technology of combining polarimetric and image processing technology. Contrasting traditional image detecting in ray radiation, polarization image detecting could acquire a lot of very important information which traditional image detecting couldn't. Polarization image detecting will be widely used in civilian field and military field. As polarization image detecting could resolve some problem which couldn't be resolved by traditional image detecting, it has been researched widely around the world. The paper introduces polarization image detecting in physical theory at first, then especially introduces image collecting and polarization image process based on CIS (CMOS image sensor) and FPGA. There are two parts including hardware and software for polarization imaging system. The part of hardware include drive module of CMOS image sensor, VGA display module, SRAM access module and the real-time image data collecting system based on FPGA. The circuit diagram and PCB was designed. Stokes vector and polarization angle computing method are analyzed in the part of software. The float multiply of Stokes vector is optimized into just shift and addition operation. The result of the experiment shows that real time image collecting system could collect and display image data from CMOS image sensor in real-time.

A feedback-based secure path approach for wireless sensor network data collection.

PubMed

Mao, Yuxin; Wei, Guiyi

2010-01-01

The unattended nature of wireless sensor networks makes them very vulnerable to malicious attacks. Therefore, how to preserve secure data collection is an important issue to wireless sensor networks. In this paper, we propose a novel approach of secure data collection for wireless sensor networks. We explore secret sharing and multipath routing to achieve secure data collection in wireless sensor network with compromised nodes. We present a novel tracing-feedback mechanism, which makes full use of the routing functionality of wireless sensor networks, to improve the quality of data collection. The major advantage of the approach is that the secure paths are constructed as a by-product of data collection. The process of secure routing causes little overhead to the sensor nodes in the network. Compared with existing works, the algorithms of the proposed approach are easy to implement and execute in resource-constrained wireless sensor networks. According to the result of a simulation experiment, the performance of the approach is better than the recent approaches with a similar purpose.

A Wearable Real-Time and Non-Invasive Thoracic Cavity Monitoring System

NASA Astrophysics Data System (ADS)

Salman, Safa

A surgery-free on-body monitoring system is proposed to evaluate the dielectric constant of internal body tissues (especially lung and heart) and effectively determine irregularities in real-time. The proposed surgery-free on-body monitoring system includes a sensor, a post-processing technique, and an automated data collection circuit. Data are automatically collected from the sensor electrodes and then post processed to extract the electrical properties of the underlying biological tissue(s). To demonstrate the imaging concept, planar and wrap-around sensors are devised. These sensors are designed to detect changes in the dielectric constant of inner tissues (lung and heart). The planar sensor focuses on a single organ while the wrap-around sensors allows for imaging of the thoracic cavity's cross section. Moreover, post-processing techniques are proposed to complement sensors for a more complete on-body monitoring system. The idea behind the post-processing technique is to suppress interference from the outer layers (skin, fat, muscle, and bone). The sensors and post-processing techniques yield high signal (from the inner layers) to noise (from the outer layers) ratio. Additionally, data collection circuits are proposed for a more robust and stand-alone system. The circuit design aims to sequentially activate each port of the sensor and portions of the propagating signal are to be received at all passive ports in the form of a voltage at the probes. The voltages are converted to scattering parameters which are then used in the post-processing technique to obtain epsilonr. The concept of wearability is also considered through the use of electrically conductive fibers (E-fibers). These fibers show matching performance to that of copper, especially at low frequencies making them a viable substitute. For the cases considered, the proposed sensors show promising results in recovering the permittivity of deep tissues with a maximum error of 13.5%. These sensors provide a way for a new class of medical sensors through accuracy improvements and avoidance of inverse scattering techniques.

Deforestation and Secondary Growth in Rondonia, Brazil from SIR-C SAR and Landsat.SPOT data

NASA Technical Reports Server (NTRS)

Rignot, Eric; Salas, William A.; Skole, David L.

1996-01-01

Covers problems with existing data collected with high-resolution optical sensors. They say active microwave sensors could complement other sensors in getting through things like cloud cover. They analyzed SIR-C data in combination with Landsat TM data, a 9-year time series of SPOT XS data, and a preliminary field survey. They report findings and draw conclusions, including that SARs operating at long radar wavelengths, with both like and cross-polarizations, are needed for tropical deforestation studies.

Sensor Technologies for Intelligent Transportation Systems

PubMed Central

Guerrero-Ibáñez, Juan; Zeadally, Sherali

2018-01-01

Modern society faces serious problems with transportation systems, including but not limited to traffic congestion, safety, and pollution. Information communication technologies have gained increasing attention and importance in modern transportation systems. Automotive manufacturers are developing in-vehicle sensors and their applications in different areas including safety, traffic management, and infotainment. Government institutions are implementing roadside infrastructures such as cameras and sensors to collect data about environmental and traffic conditions. By seamlessly integrating vehicles and sensing devices, their sensing and communication capabilities can be leveraged to achieve smart and intelligent transportation systems. We discuss how sensor technology can be integrated with the transportation infrastructure to achieve a sustainable Intelligent Transportation System (ITS) and how safety, traffic control and infotainment applications can benefit from multiple sensors deployed in different elements of an ITS. Finally, we discuss some of the challenges that need to be addressed to enable a fully operational and cooperative ITS environment. PMID:29659524

Sensor Technologies for Intelligent Transportation Systems.

PubMed

Guerrero-Ibáñez, Juan; Zeadally, Sherali; Contreras-Castillo, Juan

2018-04-16

Modern society faces serious problems with transportation systems, including but not limited to traffic congestion, safety, and pollution. Information communication technologies have gained increasing attention and importance in modern transportation systems. Automotive manufacturers are developing in-vehicle sensors and their applications in different areas including safety, traffic management, and infotainment. Government institutions are implementing roadside infrastructures such as cameras and sensors to collect data about environmental and traffic conditions. By seamlessly integrating vehicles and sensing devices, their sensing and communication capabilities can be leveraged to achieve smart and intelligent transportation systems. We discuss how sensor technology can be integrated with the transportation infrastructure to achieve a sustainable Intelligent Transportation System (ITS) and how safety, traffic control and infotainment applications can benefit from multiple sensors deployed in different elements of an ITS. Finally, we discuss some of the challenges that need to be addressed to enable a fully operational and cooperative ITS environment.

A Review of Artificial Lateral Line in Sensor Fabrication and Bionic Applications for Robot Fish

PubMed Central

Wang, Anyi; Wang, Xinbao; Liu, Peng

2016-01-01

Lateral line is a system of sense organs that can aid fishes to maneuver in a dark environment. Artificial lateral line (ALL) imitates the structure of lateral line in fishes and provides invaluable means for underwater-sensing technology and robot fish control. This paper reviews ALL, including sensor fabrication and applications to robot fish. The biophysics of lateral line are first introduced to enhance the understanding of lateral line structure and function. The design and fabrication of an ALL sensor on the basis of various sensing principles are then presented. ALL systems are collections of sensors that include carrier and control circuit. Their structure and hydrodynamic detection are reviewed. Finally, further research trends and existing problems of ALL are discussed. PMID:28115825

Invitation to a forum: architecting operational `next generation' earth monitoring satellites based on best modeling, existing sensor capabilities, with constellation efficiencies to secure trusted datasets for the next 20 years

NASA Astrophysics Data System (ADS)

Helmuth, Douglas B.; Bell, Raymond M.; Grant, David A.; Lentz, Christopher A.

2012-09-01

Architecting the operational Next Generation of earth monitoring satellites based on matured climate modeling, reuse of existing sensor & satellite capabilities, attention to affordability and evolutionary improvements integrated with constellation efficiencies - becomes our collective goal for an open architectural design forum. Understanding the earth's climate and collecting requisite signatures over the next 30 years is a shared mandate by many of the world's governments. But there remains a daunting challenge to bridge scientific missions to 'operational' systems that truly support the demands of decision makers, scientific investigators and global users' requirements for trusted data. In this paper we will suggest an architectural structure that takes advantage of current earth modeling examples including cross-model verification and a first order set of critical climate parameters and metrics; that in turn, are matched up with existing space borne collection capabilities and sensors. The tools used and the frameworks offered are designed to allow collaborative overlays by other stakeholders nominating different critical parameters and their own treaded connections to existing international collection experience. These aggregate design suggestions will be held up to group review and prioritized as potential constellation solutions including incremental and spiral developments - including cost benefits and organizational opportunities. This Part IV effort is focused on being an inclusive 'Next Gen Constellation' design discussion and is the natural extension to earlier papers.

Low-Cost Air Quality Monitoring Tools: From Research to Practice (A Workshop Summary)

PubMed Central

Griswold, William G.; RS, Abhijit; Johnston, Jill E.; Herting, Megan M.; Thorson, Jacob; Collier-Oxandale, Ashley; Hannigan, Michael

2017-01-01

In May 2017, a two-day workshop was held in Los Angeles (California, U.S.A.) to gather practitioners who work with low-cost sensors used to make air quality measurements. The community of practice included individuals from academia, industry, non-profit groups, community-based organizations, and regulatory agencies. The group gathered to share knowledge developed from a variety of pilot projects in hopes of advancing the collective knowledge about how best to use low-cost air quality sensors. Panel discussion topics included: (1) best practices for deployment and calibration of low-cost sensor systems, (2) data standardization efforts and database design, (3) advances in sensor calibration, data management, and data analysis and visualization, and (4) lessons learned from research/community partnerships to encourage purposeful use of sensors and create change/action. Panel discussions summarized knowledge advances and project successes while also highlighting the questions, unresolved issues, and technological limitations that still remain within the low-cost air quality sensor arena. PMID:29143775

Student-Built High-Altitude Balloon Payload with Sensor Array and Flight Computer

NASA Astrophysics Data System (ADS)

Jeffery, Russell; Slaton, William

A payload was designed for a high-altitude weather balloon. The flight controller consisted of a Raspberry Pi running a Python 3.4 program to collect and store data. The entire payload was designed to be versatile and easy to modify so that it could be repurposed for other projects: The code was written with the expectation that more sensors and other functionality would be added later, and a Raspberry Pi was chosen as the processor because of its versatility, its active support community, and its ability to interface easily with sensors, servos, and other such hardware. For this project, extensive use was made of the Python 3.4 libraries gps3, PiCamera, and RPi.GPIO to collect data from a GPS breakout board, a Raspberry Pi camera, a geiger counter, two thermocouples, and a pressure sensor. The data collected clearly shows that pressure and temperature decrease as altitude increases, while β-radiation and γ-radiation increase as altitude increases. These trends in the data follow those predicted by theoretical calculations made for comparison. This payload was developed in such a way that future students could easily alter it to include additional sensors, biological experiments, and additional error monitoring and management. Arkansas Space Grant Consortium (ASGC) Workforce Development Grant.

Modeling Charge Collection in Detector Arrays

NASA Technical Reports Server (NTRS)

Hardage, Donna (Technical Monitor); Pickel, J. C.

2003-01-01

A detector array charge collection model has been developed for use as an engineering tool to aid in the design of optical sensor missions for operation in the space radiation environment. This model is an enhancement of the prototype array charge collection model that was developed for the Next Generation Space Telescope (NGST) program. The primary enhancements were accounting for drift-assisted diffusion by Monte Carlo modeling techniques and implementing the modeling approaches in a windows-based code. The modeling is concerned with integrated charge collection within discrete pixels in the focal plane array (FPA), with high fidelity spatial resolution. It is applicable to all detector geometries including monolithc charge coupled devices (CCDs), Active Pixel Sensors (APS) and hybrid FPA geometries based on a detector array bump-bonded to a readout integrated circuit (ROIC).

A Feedback-Based Secure Path Approach for Wireless Sensor Network Data Collection

PubMed Central

Mao, Yuxin; Wei, Guiyi

2010-01-01

The unattended nature of wireless sensor networks makes them very vulnerable to malicious attacks. Therefore, how to preserve secure data collection is an important issue to wireless sensor networks. In this paper, we propose a novel approach of secure data collection for wireless sensor networks. We explore secret sharing and multipath routing to achieve secure data collection in wireless sensor network with compromised nodes. We present a novel tracing-feedback mechanism, which makes full use of the routing functionality of wireless sensor networks, to improve the quality of data collection. The major advantage of the approach is that the secure paths are constructed as a by-product of data collection. The process of secure routing causes little overhead to the sensor nodes in the network. Compared with existing works, the algorithms of the proposed approach are easy to implement and execute in resource-constrained wireless sensor networks. According to the result of a simulation experiment, the performance of the approach is better than the recent approaches with a similar purpose. PMID:22163424

Cellular telephone-based radiation sensor and wide-area detection network

DOEpatents

Craig, William W [Pittsburg, CA; Labov, Simon E [Berkeley, CA

2006-12-12

A network of radiation detection instruments, each having a small solid state radiation sensor module integrated into a cellular phone for providing radiation detection data and analysis directly to a user. The sensor module includes a solid-state crystal bonded to an ASIC readout providing a low cost, low power, light weight compact instrument to detect and measure radiation energies in the local ambient radiation field. In particular, the photon energy, time of event, and location of the detection instrument at the time of detection is recorded for real time transmission to a central data collection/analysis system. The collected data from the entire network of radiation detection instruments are combined by intelligent correlation/analysis algorithms which map the background radiation and detect, identify and track radiation anomalies in the region.

Multi-phenomenology Observation Network Evaluation Tool'' (MONET)

NASA Astrophysics Data System (ADS)

Oltrogge, D.; North, P.; Vallado, D.

2014-09-01

Evaluating overall performance of an SSA "system-of-systems" observational network collecting against thousands of Resident Space Objects (RSO) is very difficult for typical tasking or scheduling-based analysis tools. This is further complicated by networks that have a wide variety of sensor types and phenomena, to include optical, radar and passive RF types, each having unique resource, ops tempo, competing customer and detectability constraints. We present details of the Multi-phenomenology Observation Network Evaluation Tool (MONET), which circumvents these difficulties by assessing the ideal performance of such a network via a digitized supply-vs-demand approach. Cells of each sensors supply time are distributed among RSO targets of interest to determine the average performance of the network against that set of RSO targets. Orbit Determination heuristics are invoked to represent observation quantity and geometry notionally required to obtain the desired orbit estimation quality. To feed this approach, we derive the detectability and collection rate performance of optical, radar and passive RF sensor physical and performance characteristics. We then prioritize the selected RSO targets according to object size, active/inactive status, orbit regime, and/or other considerations. Finally, the OD-derived tracking demands of each RSO of interest are levied against remaining sensor supply until either (a) all sensor time is exhausted; or (b) the list of RSO targets is exhausted. The outputs from MONET include overall network performance metrics delineated by sensor type, objects and orbits tracked, along with likely orbit accuracies which might result from the conglomerate network tracking.

Wearable PPG sensor based alertness scoring system.

PubMed

Dey, Jishnu; Bhowmik, Tanmoy; Sahoo, Saswata; Tiwari, Vijay Narayan

2017-07-01

Quantifying mental alertness in today's world is important as it enables the person to adopt lifestyle changes for better work efficiency. Miniaturized sensors in wearable devices have facilitated detection/monitoring of mental alertness. Photoplethysmography (PPG) sensors through Heart Rate Variability (HRV) offer one such opportunity by providing information about one's daily alertness levels without requiring any manual interference from the user. In this paper, a smartwatch based alertness estimation system is proposed. Data collected from PPG sensor of smartwatch is processed and fed to machine learning based model to get a continuous alertness score. Utility functions are designed based on statistical analysis to give a quality score on different stages of alertness such as awake, long sleep and short duration power nap. An intelligent data collection approach is proposed in collaboration with the motion sensor in the smartwatch to reduce battery drainage. Overall, our proposed wearable based system provides a detailed analysis of alertness over a period in a systematic and optimized manner. We were able to achieve an accuracy of 80.1% for sleep/awake classification along with alertness score. This opens up the possibility for quantifying alertness levels using a single PPG sensor for better management of health related activities including sleep.

Human activity discrimination for maritime application

NASA Astrophysics Data System (ADS)

Boettcher, Evelyn; Deaver, Dawne M.; Krapels, Keith

2008-04-01

The US Army RDECOM CERDEC Night Vision and Electronic Sensors Directorate (NVESD) is investigating how motion affects the target acquisition model (NVThermIP) sensor performance estimates. This paper looks specifically at estimating sensor performance for the task of discriminating human activities on watercraft, and was sponsored by the Office of Naval Research (ONR). Traditionally, sensor models were calibrated using still images. While that approach is sufficient for static targets, video allows one to use motion cues to aid in discerning the type of human activity more quickly and accurately. This, in turn, will affect estimated sensor performance and these effects are measured in order to calibrate current target acquisition models for this task. The study employed an eleven alternative forced choice (11AFC) human perception experiment to measure the task difficulty of discriminating unique human activities on watercrafts. A mid-wave infrared camera was used to collect video at night. A description of the construction of this experiment is given, including: the data collection, image processing, perception testing and how contrast was defined for video. These results are applicable to evaluate sensor field performance for Anti-Terrorism and Force Protection (AT/FP) tasks for the U.S. Navy.

High throughput field plant phenotyping facility at University of Nebraska-Lincoln and the first year experience

NASA Astrophysics Data System (ADS)

Ge, Y.; Bai, G.; Irmak, S.; Awada, T.; Stoerger, V.; Graef, G.; Scoby, D.; Schnable, J.

2017-12-01

University of Nebraska - Lincoln's high throughput field plant phenotyping facility is a cable robot based system built on a 1-ac field. The sensor platform is tethered with eight cables via four poles at the corners of the field for its precise control and positioning. The sensor modules on the platform include a 4-band RGB-NIR camera, a thermal infrared camera, a 3D LiDAR, VNIR spectrometers, and environmental sensors. These sensors are used to collect multifaceted physiological, structural and chemical properties of plants from the field plots. A subsurface drip irrigation system is established in this field which allows a controlled amount of water and fertilizers to be delivered to individual plots. An extensive soil moisture sensor network is also established to monitor soil water status, and serve as a feedback loop for irrigation scheduling. In the first year of operation, the field is planted maize and soybean. Weekly ground truth data were collected from the plots to validate image and sensor data from the phenotyping system. This presentation will provide an overview of this state-of-the-art field plant phenotyping facility, and present preliminary data from the first year operation of the system.

Prototype of a low cost multiparameter probe

NASA Astrophysics Data System (ADS)

Koski, K.; Schwingle, R.; Pullin, M.

2010-12-01

Commercial multi-parameter probes provide accurate, high-resolution temporal data collection of a variety of water quality parameters, but their cost (>5,000) prohibits more than a few sampling locations. We present a design and prototype for a low cost (<250) probe. The cost of the probe is ~5% of commercially available probes, allowing for data collection from ~20 times more sampling points in a field location. The probe is constructed from a single-board microcontroller, a commercially available temperature sensor, a conductivity sensor, and a fabricated optical rhodamine sensor. Using a secure digital (SD) memory card, the probe can record over a month of data at a user specified interval. Construction, calibration, field deployment and data retrieval can be accomplished by a skilled undergraduate. Initial deployment will take place as part of a tracer test in the Valles Caldera National Preserve in northern New Mexico. Future work includes: addition of commercial ion selective electrodes (pH, bromide, nitrate, and others); construction of optically based sensors (chlorophyll, dissolved oxygen, and others); wireless networking between the sensors; and reduction of biofouling.

Multimodal Wireless Sensor Network-Based Ambient Assisted Living in Real Homes with Multiple Residents

PubMed Central

Tunca, Can; Alemdar, Hande; Ertan, Halil; Incel, Ozlem Durmaz; Ersoy, Cem

2014-01-01

Human activity recognition and behavior monitoring in a home setting using wireless sensor networks (WSNs) provide a great potential for ambient assisted living (AAL) applications, ranging from health and wellbeing monitoring to resource consumption monitoring. However, due to the limitations of the sensor devices, challenges in wireless communication and the challenges in processing large amounts of sensor data in order to recognize complex human activities, WSN-based AAL systems are not effectively integrated in the home environment. Additionally, given the variety of sensor types and activities, selecting the most suitable set of sensors in the deployment is an important task. In order to investigate and propose solutions to such challenges, we introduce a WSN-based multimodal AAL system compatible for homes with multiple residents. Particularly, we focus on the details of the system architecture, including the challenges of sensor selection, deployment, networking and data collection and provide guidelines for the design and deployment of an effective AAL system. We also present the details of the field study we conducted, using the systems deployed in two different real home environments with multiple residents. With these systems, we are able to collect ambient sensor data from multiple homes. This data can be used to assess the wellbeing of the residents and identify deviations from everyday routines, which may be indicators of health problems. Finally, in order to elaborate on the possible applications of the proposed AAL system and to exemplify directions for processing the collected data, we provide the results of several human activity inference experiments, along with examples on how such results could be interpreted. We believe that the experiences shared in this work will contribute towards accelerating the acceptance of WSN-based AAL systems in the home setting. PMID:24887044

Multimodal wireless sensor network-based ambient assisted living in real homes with multiple residents.

PubMed

Tunca, Can; Alemdar, Hande; Ertan, Halil; Incel, Ozlem Durmaz; Ersoy, Cem

2014-05-30

Human activity recognition and behavior monitoring in a home setting using wireless sensor networks (WSNs) provide a great potential for ambient assisted living (AAL) applications, ranging from health and wellbeing monitoring to resource consumption monitoring. However, due to the limitations of the sensor devices, challenges in wireless communication and the challenges in processing large amounts of sensor data in order to recognize complex human activities, WSN-based AAL systems are not effectively integrated in the home environment. Additionally, given the variety of sensor types and activities, selecting the most suitable set of sensors in the deployment is an important task. In order to investigate and propose solutions to such challenges, we introduce a WSN-based multimodal AAL system compatible for homes with multiple residents. Particularly, we focus on the details of the system architecture, including the challenges of sensor selection, deployment, networking and data collection and provide guidelines for the design and deployment of an effective AAL system. We also present the details of the field study we conducted, using the systems deployed in two different real home environments with multiple residents. With these systems, we are able to collect ambient sensor data from multiple homes. This data can be used to assess the wellbeing of the residents and identify deviations from everyday routines, which may be indicators of health problems. Finally, in order to elaborate on the possible applications of the proposed AAL system and to exemplify directions for processing the collected data, we provide the results of several human activity inference experiments, along with examples on how such results could be interpreted. We believe that the experiences shared in this work will contribute towards accelerating the acceptance of WSN-based AAL systems in the home setting.

A cloud-based information repository for bridge monitoring applications

NASA Astrophysics Data System (ADS)

Jeong, Seongwoon; Zhang, Yilan; Hou, Rui; Lynch, Jerome P.; Sohn, Hoon; Law, Kincho H.

2016-04-01

This paper describes an information repository to support bridge monitoring applications on a cloud computing platform. Bridge monitoring, with instrumentation of sensors in particular, collects significant amount of data. In addition to sensor data, a wide variety of information such as bridge geometry, analysis model and sensor description need to be stored. Data management plays an important role to facilitate data utilization and data sharing. While bridge information modeling (BrIM) technologies and standards have been proposed and they provide a means to enable integration and facilitate interoperability, current BrIM standards support mostly the information about bridge geometry. In this study, we extend the BrIM schema to include analysis models and sensor information. Specifically, using the OpenBrIM standards as the base, we draw on CSI Bridge, a commercial software widely used for bridge analysis and design, and SensorML, a standard schema for sensor definition, to define the data entities necessary for bridge monitoring applications. NoSQL database systems are employed for data repository. Cloud service infrastructure is deployed to enhance scalability, flexibility and accessibility of the data management system. The data model and systems are tested using the bridge model and the sensor data collected at the Telegraph Road Bridge, Monroe, Michigan.

Charge collection and field profile studies of heavily irradiated strip sensors for the ATLAS inner tracker upgrade

NASA Astrophysics Data System (ADS)

Hara, K.; Allport, P. P.; Baca, M.; Broughton, J.; Chisholm, A.; Nikolopoulos, K.; Pyatt, S.; Thomas, J. P.; Wilson, J. A.; Kierstead, J.; Kuczewski, P.; Lynn, D.; Arratia, M.; Hommels, L. B. A.; Ullan, M.; Bloch, I.; Gregor, I. M.; Tackmann, K.; Trofimov, A.; Yildirim, E.; Hauser, M.; Jakobs, K.; Kuehn, S.; Mahboubi, K.; Mori, R.; Parzefall, U.; Clark, A.; Ferrere, D.; Gonzalez Sevilla, S.; Ashby, J.; Blue, A.; Bates, R.; Buttar, C.; Doherty, F.; McMullen, T.; McEwan, F.; O'Shea, V.; Kamada, S.; Yamamura, K.; Ikegami, Y.; Nakamura, K.; Takubo, Y.; Unno, Y.; Takashima, R.; Chilingarov, A.; Fox, H.; Affolder, A. A.; Casse, G.; Dervan, P.; Forshaw, D.; Greenall, A.; Wonsak, S.; Wormald, M.; Cindro, V.; Kramberger, G.; Mandić, I.; Mikuž, M.; Gorelov, I.; Hoeferkamp, M.; Palni, P.; Seidel, S.; Taylor, A.; Toms, K.; Wang, R.; Hessey, N. P.; Valencic, N.; Hanagaki, K.; Dolezal, Z.; Kodys, P.; Bohm, J.; Mikestikova, M.; Bevan, A.; Beck, G.; Milke, C.; Domingo, M.; Fadeyev, V.; Galloway, Z.; Hibbard-Lubow, D.; Liang, Z.; Sadrozinski, H. F.-W.; Seiden, A.; To, K.; French, R.; Hodgson, P.; Marin-Reyes, H.; Parker, K.; Jinnouchi, O.; Hara, K.; Sato, K.; Sato, K.; Hagihara, M.; Iwabuchi, S.; Bernabeu, J.; Civera, J. V.; Garcia, C.; Lacasta, C.; Marti i. Garcia, S.; Rodriguez, D.; Santoyo, D.; Solaz, C.; Soldevila, U.

2016-09-01

The ATLAS group has evaluated the charge collection in silicon microstrip sensors irradiated up to a fluence of 1 ×1016 neq/cm2, exceeding the maximum of 1.6 ×1015 neq/cm2 expected for the strip tracker during the high luminosity LHC (HL-LHC) period including a safety factor of 2. The ATLAS12, n+-on-p type sensor, which is fabricated by Hamamatsu Photonics (HPK) on float zone (FZ) substrates, is the latest barrel sensor prototype. The charge collection from the irradiated 1×1 cm2 barrel test sensors has been evaluated systematically using penetrating β-rays and an Alibava readout system. The data obtained at different measurement sites are compared with each other and with the results obtained from the previous ATLAS07 design. The results are very consistent, in particular, when the deposit charge is normalized by the sensor's active thickness derived from the edge transient current technique (edge-TCT) measurements. The measurements obtained using β-rays are verified to be consistent with the measurements using an electron beam. The edge-TCT is also effective for evaluating the field profiles across the depth. The differences between the irradiated ATLAS07 and ATLAS12 samples have been examined along with the differences among the samples irradiated with different radiation sources: neutrons, protons, and pions. The studies of the bulk properties of the devices show that the devices can yield a sufficiently large signal for the expected fluence range in the HL-LHC, thereby acting as precision tracking sensors.

Progress toward a cosmic dust collection facility on space station

NASA Technical Reports Server (NTRS)

Mackinnon, Ian D. R. (Editor); Carey, William C. (Editor)

1987-01-01

Scientific and programmatic progress toward the development of a cosmic dust collection facility (CDCF) for the proposed space station is documented. Topics addressed include: trajectory sensor concepts; trajectory accuracy and orbital evolution; CDCF pointing direction; development of capture devices; analytical techniques; programmatic progress; flight opportunities; and facility development.

Using diurnal temperature signals to infer vertical groundwater-surface water exchange

USGS Publications Warehouse

Irvine, Dylan J.; Briggs, Martin A.; Lautz, Laura K.; Gordon, Ryan P.; McKenzie, Jeffrey M.; Cartwright, Ian

2017-01-01

Heat is a powerful tracer to quantify fluid exchange between surface water and groundwater. Temperature time series can be used to estimate pore water fluid flux, and techniques can be employed to extend these estimates to produce detailed plan-view flux maps. Key advantages of heat tracing include cost-effective sensors and ease of data collection and interpretation, without the need for expensive and time-consuming laboratory analyses or induced tracers. While the collection of temperature data in saturated sediments is relatively straightforward, several factors influence the reliability of flux estimates that are based on time series analysis (diurnal signals) of recorded temperatures. Sensor resolution and deployment are particularly important in obtaining robust flux estimates in upwelling conditions. Also, processing temperature time series data involves a sequence of complex steps, including filtering temperature signals, selection of appropriate thermal parameters, and selection of the optimal analytical solution for modeling. This review provides a synthesis of heat tracing using diurnal temperature oscillations, including details on optimal sensor selection and deployment, data processing, model parameterization, and an overview of computing tools available. Recent advances in diurnal temperature methods also provide the opportunity to determine local saturated thermal diffusivity, which can improve the accuracy of fluid flux modeling and sensor spacing, which is related to streambed scour and deposition. These parameters can also be used to determine the reliability of flux estimates from the use of heat as a tracer.

Real-time monitoring of ubiquitous wireless ECG sensor node for medical care using ZigBee

NASA Astrophysics Data System (ADS)

Vijayalakshmi, S. R.; Muruganand, S.

2012-01-01

Sensor networks have the potential to impact many aspects of medical care greatly. By outfitting patients with wireless, wearable vital sign sensors, collecting detailed real-time data on physiological status can be greatly simplified. In this article, we propose the system architecture for smart sensor platform based on advanced wireless sensor networks. An emerging application for wireless sensor networks involves their use in medical care. In hospitals or clinics, outfitting every patient with tiny, wearable wireless vital sign sensors would allow doctors, nurses and other caregivers to continuously monitor the status of their patients. In an emergency or disaster scenario, the same technology would enable medics to more effectively care for a large number of casualties. First responders could receive immediate notifications on any changes in patient status, such as respiratory failure or cardiac arrest. Wireless sensor network is a set of small, autonomous devices, working together to solve different problems. It is a relatively new technology, experiencing true expansion in the past decade. People have realised that integration of small and cheap microcontrollers with sensors can result in the production of extremely useful devices, which can be used as an integral part of the sensor nets. These devices are called sensor nodes. Today, sensor nets are used in agriculture, ecology and tourism, but medicine is the area where they certainly meet the greatest potential. This article presents a medical smart sensor node platform. This article proposes a wireless two-lead EKG. These devices collect heart rate and EKG data and relay it over a short-range (300 m) wireless network to any number of receiving devices, including PDAs, laptops or ambulance-based terminals.

GPS compound eye attitude and navigation sensor and method

NASA Technical Reports Server (NTRS)

Quinn, David A. (Inventor)

2003-01-01

The present invention is a GPS system for navigation and attitude determination, comprising a sensor array including a convex hemispherical mounting structure having a plurality of mounting surfaces, and a plurality of antennas mounted to the mounting surfaces for receiving signals from space vehicles of a GPS constellation. The present invention also includes a receiver for collecting the signals and making navigation and attitude determinations. In an alternate embodiment the present invention may include two opposing convex hemispherical mounting structures, each of the mounting structures having a plurality of mounting surfaces, and a plurality of antennas mounted to the mounting surfaces.

A Review of Wearable Sensor Systems for Monitoring Body Movements of Neonates

PubMed Central

Chen, Hongyu; Xue, Mengru; Mei, Zhenning; Bambang Oetomo, Sidarto; Chen, Wei

2016-01-01

Characteristics of physical movements are indicative of infants’ neuro-motor development and brain dysfunction. For instance, infant seizure, a clinical signal of brain dysfunction, could be identified and predicted by monitoring its physical movements. With the advance of wearable sensor technology, including the miniaturization of sensors, and the increasing broad application of micro- and nanotechnology, and smart fabrics in wearable sensor systems, it is now possible to collect, store, and process multimodal signal data of infant movements in a more efficient, more comfortable, and non-intrusive way. This review aims to depict the state-of-the-art of wearable sensor systems for infant movement monitoring. We also discuss its clinical significance and the aspect of system design. PMID:27983664

Gas Main Sensor and Communications Network System

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hagen Schempf

Automatika, Inc. was contracted by the Department of Energy (DOE) and with co-funding from the Northeast Gas Association (NGA), to develop an in-pipe natural gas prototype measurement and wireless communications system for assessing and monitoring distribution networks. This projected was completed in April 2006, and culminated in the installation of more than 2 dozen GasNet nodes in both low- and high-pressure cast-iron and steel mains owned by multiple utilities in the northeastern US. Utilities are currently logging data (off-line) and monitoring data in real time from single and multiple networked sensors over cellular networks and collecting data using wireless bluetoothmore » PDA systems. The system was designed to be modular, using in-pipe sensor-wands capable of measuring, flow, pressure, temperature, water-content and vibration. Internal antennae allowed for the use of the pipe-internals as a waveguide for setting up a sensor network to collect data from multiple nodes simultaneously. Sensor nodes were designed to be installed with low- and no-blow techniques and tools. Using a multi-drop bus technique with a custom protocol, all electronics were designed to be buriable and allow for on-board data-collection (SD-card), wireless relaying and cellular network forwarding. Installation options afforded by the design included direct-burial and external polemounted variants. Power was provided by one or more batteries, direct AC-power (Class I Div.2) and solar-array. The utilities are currently in a data-collection phase and intend to use the collected (and processed) data to make capital improvement decisions, compare it to Stoner model predictions and evaluate the use of such a system for future expansion, technology-improvement and commercialization starting later in 2006.« less

Travel Mode Detection with Varying Smartphone Data Collection Frequencies

PubMed Central

Shafique, Muhammad Awais; Hato, Eiji

2016-01-01

Smartphones are becoming increasingly popular day-by-day. Modern smartphones are more than just calling devices. They incorporate a number of high-end sensors that provide many new dimensions to smartphone experience. The use of smartphones, however, can be extended from the usual telecommunication field to applications in other specialized fields including transportation. Sensors embedded in the smartphones like GPS, accelerometer and gyroscope can collect data passively, which in turn can be processed to infer the travel mode of the smartphone user. This will solve most of the shortcomings associated with conventional travel survey methods including biased response, no response, erroneous time recording, etc. The current study uses the sensors’ data collected by smartphones to extract nine features for classification. Variables including data frequency, moving window size and proportion of data to be used for training, are dealt with to achieve better results. Random forest is used to classify the smartphone data among six modes. An overall accuracy of 99.96% is achieved, with no mode less than 99.8% for data collected at 10 Hz frequency. The accuracy is observed to decrease with decrease in data frequency, but at the same time the computation time also decreases. PMID:27213380

Advances in detection of diffuse seafloor venting using structured light imaging.

NASA Astrophysics Data System (ADS)

Smart, C.; Roman, C.; Carey, S.

2016-12-01

Systematic, remote detection and high resolution mapping of low temperature diffuse hydrothermal venting is inefficient and not currently tractable using traditional remotely operated vehicle (ROV) mounted sensors. Preliminary results for hydrothermal vent detection using a structured light laser sensor were presented in 2011 and published in 2013 (Smart) with continual advancements occurring in the interim. As the structured light laser passes over active venting, the projected laser line effectively blurs due to the associated turbulence and density anomalies in the vent fluid. The degree laser disturbance is captured by a camera collecting images of the laser line at 20 Hz. Advancements in the detection of the laser and fluid interaction have included extensive normalization of the collected laser data and the implementation of a support vector machine algorithm to develop a classification routine. The image data collected over a hydrothermal vent field is then labeled as seafloor, bacteria or a location of venting. The results can then be correlated with stereo images, bathymetry and backscatter data. This sensor is a component of an ROV mounted imaging suite which also includes stereo cameras and a multibeam sonar system. Originally developed for bathymetric mapping, the structured light laser sensor, and other imaging suite components, are capable of creating visual and bathymetric maps with centimeter level resolution. Surveys are completed in a standard mowing the lawn pattern completing a 30m x 30m survey with centimeter level resolution in under an hour. Resulting co-registered data includes, multibeam and structured light laser bathymetry and backscatter, stereo images and vent detection. This system allows for efficient exploration of areas with diffuse and small point source hydrothermal venting increasing the effectiveness of scientific sampling and observation. Recent vent detection results collected during the 2013-2015 E/V Nautilus seasons will be presented. Smart, C. J. and Roman, C. and Carey, S. N. (2013) Detection of diffuse seafloor venting using structured light imaging, Geochemistry, Geophysics, Geosystems, 14, 4743-4757

Evaluation of High-Temporal-Resolution Bedload Sensors for Tracking Channel Bed Movement and Transport Thresholds in Forested Mountain Headwater Catchments.

NASA Astrophysics Data System (ADS)

Martin, S.; Conklin, M. H.; Bales, R. C.

2014-12-01

High temporal resolution data is required to take channel bed movement data beyond time integrated changes between measurements where many of the subtleties of bedload movement patterns are often missed. This study used continuous bedload scour sensors (flexible, fluid-filled pans connected to a pressure transducer) to collect high temporal resolution, long term bedload movement data for 4 high elevation (1500-1800 m) Sierra Nevada headwater streams draining 1 km2 catchments and to investigate the physical channel characteristics under which they perform best. Data collected by the scour sensors were used to investigate the disturbance and recovery patterns of these streams, to relate the observed patterns to channel bed stability, and to evaluate whether the channel bed is acting as a sediment source, sink, or storage across various temporal scales. Finally, attempts are made to identify discharge thresholds for bed movement from scour sensor and discharge data and to compare these threshold values to observed changes in the channel bed. Bedload scour data, turbidity data, and stream discharge data were collected at 15 minute intervals for (WY 2011 to WY 2014), including both above average (2011) and below average (2012, 2013, 2014) water years. Bedload scour sensors were found to have a relatively high (60%) failure rate in these systems. In addition, they required in situ calibrations as the factory and laboratory calibrations did not translate well to the field deployments. Data from the working sensors, showed patterns of abrupt channel bed disturbance (scour and/or fill) on an hour to day temporal scale followed by gradual recovery on a day to month scale back to a stable equilibrium bed surface elevation. These observed patterns suggest the bed acts as a short term source or sink for sediment, but is roughly sediment neutral over longer time periods implying the changes in bed elevation are reflective of fluctuations in storage rather than a true source or sink. Overall, these sensors show promise for collecting continuous data for high gradient, forested, mountain streams. Additional benefits include their relatively low cost both monetarily (under $1000) and in labor compared to traditional methods as well as not requiring the trade-off between temporal resolution and length of study that traditional methods do.

Innovative solutions in monitoring systems in flood protection

NASA Astrophysics Data System (ADS)

Sekuła, Klaudia; Połeć, Marzena; Borecka, Aleksandra

2018-02-01

The article presents the possibilities of ISMOP - IT System of Levee Monitoring. This system is able to collecting data from the reference and experimental control and measurement network. The experimental levee is build in a 1:1 scale and located in the village of Czernichow, near Cracow. The innovation is the utilization of a series of sensors monitoring the changes in the body of levee. It can be done by comparing the results of numerical simulations with results from installed two groups of sensors: reference sensors and experimental sensors. The reference control and measurement sensors create network based on pore pressure and temperature sensors. Additionally, it contains the fiber-optic technology. The second network include design experimental sensors, constructed for the development of solutions that can be used in existing flood embankments. The results are important to create the comprehensive and inexpensive monitoring system, which could be helpful for state authorities and local governments in flood protection.

Workflow-Oriented Cyberinfrastructure for Sensor Data Analytics

NASA Astrophysics Data System (ADS)

Orcutt, J. A.; Rajasekar, A.; Moore, R. W.; Vernon, F.

2015-12-01

Sensor streams comprise an increasingly large part of Earth Science data. Analytics based on sensor data require an easy way to perform operations such as acquisition, conversion to physical units, metadata linking, sensor fusion, analysis and visualization on distributed sensor streams. Furthermore, embedding real-time sensor data into scientific workflows is of growing interest. We have implemented a scalable networked architecture that can be used to dynamically access packets of data in a stream from multiple sensors, and perform synthesis and analysis across a distributed network. Our system is based on the integrated Rule Oriented Data System (irods.org), which accesses sensor data from the Antelope Real Time Data System (brtt.com), and provides virtualized access to collections of data streams. We integrate real-time data streaming from different sources, collected for different purposes, on different time and spatial scales, and sensed by different methods. iRODS, noted for its policy-oriented data management, brings to sensor processing features and facilities such as single sign-on, third party access control lists ( ACLs), location transparency, logical resource naming, and server-side modeling capabilities while reducing the burden on sensor network operators. Rich integrated metadata support also makes it straightforward to discover data streams of interest and maintain data provenance. The workflow support in iRODS readily integrates sensor processing into any analytical pipeline. The system is developed as part of the NSF-funded Datanet Federation Consortium (datafed.org). APIs for selecting, opening, reaping and closing sensor streams are provided, along with other helper functions to associate metadata and convert sensor packets into NetCDF and JSON formats. Near real-time sensor data including seismic sensors, environmental sensors, LIDAR and video streams are available through this interface. A system for archiving sensor data and metadata in NetCDF format has been implemented and will be demonstrated at AGU.

Sensor Alerting Capability

NASA Astrophysics Data System (ADS)

Henriksson, Jakob; Bermudez, Luis; Satapathy, Goutam

2013-04-01

There is a large amount of sensor data generated today by various sensors, from in-situ buoys to mobile underwater gliders. Providing sensor data to the users through standardized services, language and data model is the promise of OGC's Sensor Web Enablement (SWE) initiative. As the amount of data grows it is becoming difficult for data providers, planners and managers to ensure reliability of data and services and to monitor critical data changes. Intelligent Automation Inc. (IAI) is developing a net-centric alerting capability to address these issues. The capability is built on Sensor Observation Services (SOSs), which is used to collect and monitor sensor data. The alerts can be configured at the service level and at the sensor data level. For example it can alert for irregular data delivery events or a geo-temporal statistic of sensor data crossing a preset threshold. The capability provides multiple delivery mechanisms and protocols, including traditional techniques such as email and RSS. With this capability decision makers can monitor their assets and data streams, correct failures or be alerted about a coming phenomena.

Low cost infrared and near infrared sensors for UAVs

NASA Astrophysics Data System (ADS)

Aden, S. T.; Bialas, J. P.; Champion, Z.; Levin, E.; McCarty, J. L.

2014-11-01

Thermal remote sensing has a wide range of applications, though the extent of its use is inhibited by cost. Robotic and computer components are now widely available to consumers on a scale that makes thermal data a readily accessible resource. In this project, thermal imagery collected via a lightweight remote sensing Unmanned Aerial Vehicle (UAV) was used to create a surface temperature map for the purpose of providing wildland firefighting crews with a cost-effective and time-saving resource. The UAV system proved to be flexible, allowing for customized sensor packages to be designed that could include visible or infrared cameras, GPS, temperature sensors, and rangefinders, in addition to many data management options. Altogether, such a UAV system could be used to rapidly collect thermal and aerial data, with a geographic accuracy of less than one meter.

On-board Data Mining

NASA Astrophysics Data System (ADS)

Tanner, Steve; Stein, Cara; Graves, Sara J.

Networks of remote sensors are becoming more common as technology improves and costs decline. In the past, a remote sensor was usually a device that collected data to be retrieved at a later time by some other mechanism. This collected data were usually processed well after the fact at a computer greatly removed from the in situ sensing location. This has begun to change as sensor technology, on-board processing, and network communication capabilities have increased and their prices have dropped. There has been an explosion in the number of sensors and sensing devices, not just around the world, but literally throughout the solar system. These sensors are not only becoming vastly more sophisticated, accurate, and detailed in the data they gather but they are also becoming cheaper, lighter, and smaller. At the same time, engineers have developed improved methods to embed computing systems, memory, storage, and communication capabilities into the platforms that host these sensors. Now, it is not unusual to see large networks of sensors working in cooperation with one another. Nor does it seem strange to see the autonomous operation of sensorbased systems, from space-based satellites to smart vacuum cleaners that keep our homes clean and robotic toys that help to entertain and educate our children. But access to sensor data and computing power is only part of the story. For all the power of these systems, there are still substantial limits to what they can accomplish. These include the well-known limits to current Artificial Intelligence capabilities and our limited ability to program the abstract concepts, goals, and improvisation needed for fully autonomous systems. But it also includes much more basic engineering problems such as lack of adequate power, communications bandwidth, and memory, as well as problems with the geolocation and real-time georeferencing required to integrate data from multiple sensors to be used together.

Fiber optic strain and temperature sensor for power plant applications

NASA Astrophysics Data System (ADS)

Narendran, Nadarajah; Weiss, Joseph M.

1996-01-01

The applicability of fiber-optic strain and temperature sensors to monitor power plant structures was evaluated on a super-heated steam pipe operating at 1000 degree(s)F at the Tennessee Valley Authority power plant in Kingston, Tennessee. The potential applications of these fiber-optic sensors include health monitoring of high-temperature structures such as boilers, tube headers, and steam pipes, as well as many other power plant structures exposed to less severe environments. The sensor selected for this application is based on a white-light interferometric technique. The key features of this sensor include its ability for absolute measurements that are not affected by light loss along the fiber cable due to, for example, microbending effects and coupler loss, its compatibility with off-the-shelf fiber-optic components, and its low cost. The glass fiber-optic strain sensors were packaged in a rugged metal housing and were spot welded to the high-temperature steam pipe. Another set of gages was placed inside a thermowell for steam temperature measurement. Data collected during a routine start-up is very encouraging and the details are presented in this manuscript.

Net-Centric Sensors and Data Sources (N-CSDS) GEODSS Sidecar

NASA Astrophysics Data System (ADS)

Richmond, D.

2012-09-01

Vast amounts of Space Situational Sensor data is collected each day on closed, legacy systems. Massachusetts Institute of Technology Lincoln Laboratory (MIT/LL) developed a Net-Centric approach to expose this data under the Extended Space Sensors Architecture (ESSA) Advanced Concept Technology Demonstration (ACTD). The Net-Centric Sensors and Data Sources (N-CSDS) Ground-based Electro Optical Deep Space Surveillance (GEODSS) Sidecar is the next generation that moves the ESSA ACTD engineering tools to an operational baseline. The N-CSDS GEODSS sidecar high level architecture will be presented, highlighting the features that supports deployment at multiple diverse sensor sites. Other key items that will be covered include: 1) The Web Browser interface to perform searches of historical data 2) The capabilities of the deployed Web Services and example service request/responses 3) Example data and potential user applications will be highlighted 4) Specifics regarding the process to gain access to the N-CSDS GEODSS sensor data in near real time 5) Current status and future deployment plans (Including plans for deployment to the Maui GEODSS Site)

Multi-optical mine detection: results from a field trial

NASA Astrophysics Data System (ADS)

Letalick, Dietmar; Tolt, Gustav; Sjökvist, Stefan K.; Nyberg, Sten; Grönwall, Christina; Andersson, Pierre; Linderhed, Anna; Forssell, Göran; Larsson, Håkan; Uppsäll, Magnus

2006-05-01

As a part of the Swedish mine detection project MOMS, an initial field trial was conducted at the Swedish EOD and Demining Centre (SWEDEC). The purpose was to collect data on surface-laid mines, UXO, submunitions, IED's, and background with a variety of optical sensors, for further use in the project. Three terrain types were covered: forest, gravel road, and an area which had recovered after total removal of all vegetation some years before. The sensors used in the field trial included UV, VIS, and NIR sensors as well as thermal, multi-spectral, and hyper-spectral sensors, 3-D laser radar and polarization sensors. Some of the sensors were mounted on an aerial work platform, while others were placed on tripods on the ground. This paper describes the field trial and the presents some initial results obtained from the subsequent analysis.

Opportunistic Mobility Support for Resource Constrained Sensor Devices in Smart Cities

PubMed Central

Granlund, Daniel; Holmlund, Patrik; Åhlund, Christer

2015-01-01

A multitude of wireless sensor devices and technologies are being developed and deployed in cities all over the world. Sensor applications in city environments may include highly mobile installations that span large areas which necessitates sensor mobility support. This paper presents and validates two mechanisms for supporting sensor mobility between different administrative domains. Firstly, EAP-Swift, an Extensible Authentication Protocol (EAP)-based sensor authentication protocol is proposed that enables light-weight sensor authentication and key generation. Secondly, a mechanism for handoffs between wireless sensor gateways is proposed. We validate both mechanisms in a real-life study that was conducted in a smart city environment with several fixed sensors and moving gateways. We conduct similar experiments in an industry-based anechoic Long Term Evolution (LTE) chamber with an ideal radio environment. Further, we validate our results collected from the smart city environment against the results produced under ideal conditions to establish best and real-life case scenarios. Our results clearly validate that our proposed mechanisms can facilitate efficient sensor authentication and handoffs while sensors are roaming in a smart city environment. PMID:25738767

Opportunistic mobility support for resource constrained sensor devices in smart cities.

PubMed

Granlund, Daniel; Holmlund, Patrik; Åhlund, Christer

2015-03-02

A multitude of wireless sensor devices and technologies are being developed and deployed in cities all over the world. Sensor applications in city environments may include highly mobile installations that span large areas which necessitates sensor mobility support. This paper presents and validates two mechanisms for supporting sensor mobility between different administrative domains. Firstly, EAP-Swift, an Extensible Authentication Protocol (EAP)-based sensor authentication protocol is proposed that enables light-weight sensor authentication and key generation. Secondly, a mechanism for handoffs between wireless sensor gateways is proposed. We validate both mechanisms in a real-life study that was conducted in a smart city environment with several fixed sensors and moving gateways. We conduct similar experiments in an industry-based anechoic Long Term Evolution (LTE) chamber with an ideal radio environment. Further, we validate our results collected from the smart city environment against the results produced under ideal conditions to establish best and real-life case scenarios. Our results clearly validate that our proposed mechanisms can facilitate efficient sensor authentication and handoffs while sensors are roaming in a smart city environment.

Point Cloud Generation from sUAS-Mounted iPhone Imagery: Performance Analysis

NASA Astrophysics Data System (ADS)

Ladai, A. D.; Miller, J.

2014-11-01

The rapidly growing use of sUAS technology and fast sensor developments continuously inspire mapping professionals to experiment with low-cost airborne systems. Smartphones has all the sensors used in modern airborne surveying systems, including GPS, IMU, camera, etc. Of course, the performance level of the sensors differs by orders, yet it is intriguing to assess the potential of using inexpensive sensors installed on sUAS systems for topographic applications. This paper focuses on the quality analysis of point clouds generated based on overlapping images acquired by an iPhone 5s mounted on a sUAS platform. To support the investigation, test data was acquired over an area with complex topography and varying vegetation. In addition, extensive ground control, including GCPs and transects were collected with GSP and traditional geodetic surveying methods. The statistical and visual analysis is based on a comparison of the UAS data and reference dataset. The results with the evaluation provide a realistic measure of data acquisition system performance. The paper also gives a recommendation for data processing workflow to achieve the best quality of the final products: the digital terrain model and orthophoto mosaic. After a successful data collection the main question is always the reliability and the accuracy of the georeferenced data.

Incorporating Target Priorities in the Sensor Tasking Reward Function

NASA Astrophysics Data System (ADS)

Gehly, S.; Bennett, J.

2016-09-01

Orbital debris tracking poses many challenges, most fundamentally the need to track a large number of objects from a limited number of sensors. The use of information theoretic sensor allocation provides a means to efficiently collect data on the multitarget system. An additional need of the community is the ability to specify target priorities, driven both by user needs and environmental factors such as collision warnings. This research develops a method to incorporate target priorities in the sensor tasking reward function, allowing for several applications in different tasking modes such as catalog maintenance, calibration, and collision monitoring. A set of numerical studies is included to demonstrate the functionality of the method.

Aerothermal Assment Of The Expert Flap In The SCIROCCO Wind Tunnel

NASA Astrophysics Data System (ADS)

Walpot, L.; Di Clemente, M.; Vos, J.; Etchells, J.; Trifoni, E.; Thoemel, J.; Gavira, J.

2011-05-01

In the frame of the “In-Flight Test Measurement Techniques for Aerothermodynamics” activity of the EXPERT Program, the EXPERT Instrumented Open Flap Assembly experiment has the objective to verify the design/sensor integration and validate the CFD tools. Ground based measurements were made in Europe’s largest high enthalpy plasma facility, Scirocco in Italy. Two EXPERT flaps of the flight article, instrumented with 14 thermocouples, 5 pressure ports, a pyrometer and an IR camera mounted in the cavity instrumented flap will collect in-flight data. During the Scirocco experiment, an EXPERT flap model identical to the flight article was mounted at 45 deg on a holder including cavity and was subjected to a hot plasma flow at an enthalpy up to 11MJ/kg at a stagnation pressure of 7 bar. The test model sports the same pressure sensors as the flight article. Hypersonic state-of-the-art codes were then be used to perform code-to-code and wind tunnel-to-code comparisons, including thermal response of the flap as collected during the tests by the sensors and camera.

Unmanned Aerial Vehicles for High-Throughput Phenotyping and Agronomic Research

PubMed Central

Shi, Yeyin; Thomasson, J. Alex; Murray, Seth C.; Pugh, N. Ace; Rooney, William L.; Shafian, Sanaz; Rajan, Nithya; Rouze, Gregory; Morgan, Cristine L. S.; Neely, Haly L.; Rana, Aman; Bagavathiannan, Muthu V.; Henrickson, James; Bowden, Ezekiel; Valasek, John; Olsenholler, Jeff; Bishop, Michael P.; Sheridan, Ryan; Putman, Eric B.; Popescu, Sorin; Burks, Travis; Cope, Dale; Ibrahim, Amir; McCutchen, Billy F.; Baltensperger, David D.; Avant, Robert V.; Vidrine, Misty; Yang, Chenghai

2016-01-01

Advances in automation and data science have led agriculturists to seek real-time, high-quality, high-volume crop data to accelerate crop improvement through breeding and to optimize agronomic practices. Breeders have recently gained massive data-collection capability in genome sequencing of plants. Faster phenotypic trait data collection and analysis relative to genetic data leads to faster and better selections in crop improvement. Furthermore, faster and higher-resolution crop data collection leads to greater capability for scientists and growers to improve precision-agriculture practices on increasingly larger farms; e.g., site-specific application of water and nutrients. Unmanned aerial vehicles (UAVs) have recently gained traction as agricultural data collection systems. Using UAVs for agricultural remote sensing is an innovative technology that differs from traditional remote sensing in more ways than strictly higher-resolution images; it provides many new and unique possibilities, as well as new and unique challenges. Herein we report on processes and lessons learned from year 1—the summer 2015 and winter 2016 growing seasons–of a large multidisciplinary project evaluating UAV images across a range of breeding and agronomic research trials on a large research farm. Included are team and project planning, UAV and sensor selection and integration, and data collection and analysis workflow. The study involved many crops and both breeding plots and agronomic fields. The project’s goal was to develop methods for UAVs to collect high-quality, high-volume crop data with fast turnaround time to field scientists. The project included five teams: Administration, Flight Operations, Sensors, Data Management, and Field Research. Four case studies involving multiple crops in breeding and agronomic applications add practical descriptive detail. Lessons learned include critical information on sensors, air vehicles, and configuration parameters for both. As the first and most comprehensive project of its kind to date, these lessons are particularly salient to researchers embarking on agricultural research with UAVs. PMID:27472222

International Space Station Data Collection for Disaster Response

NASA Technical Reports Server (NTRS)

Stefanov, William L.; Evans, Cynthia A.

2015-01-01

Remotely sensed data acquired by orbital sensor systems has emerged as a vital tool to identify the extent of damage resulting from a natural disaster, as well as providing near-real time mapping support to response efforts on the ground and humanitarian aid efforts. The International Space Station (ISS) is a unique terrestrial remote sensing platform for acquiring disaster response imagery. Unlike automated remote-sensing platforms it has a human crew; is equipped with both internal and externally-mounted remote sensing instruments; and has an inclined, low-Earth orbit that provides variable views and lighting (day and night) over 95 percent of the inhabited surface of the Earth. As such, it provides a useful complement to autonomous sensor systems in higher altitude polar orbits. NASA remote sensing assets on the station began collecting International Disaster Charter (IDC) response data in May 2012. The initial NASA ISS sensor systems responding to IDC activations included the ISS Agricultural Camera (ISSAC), mounted in the Window Observational Research Facility (WORF); the Crew Earth Observations (CEO) Facility, where the crew collects imagery using off-the-shelf handheld digital cameras; and the Hyperspectral Imager for the Coastal Ocean (HICO), a visible to near-infrared system mounted externally on the Japan Experiment Module Exposed Facility. The ISSAC completed its primary mission in January 2013. It was replaced by the very high resolution ISS SERVIR Environmental Research and Visualization System (ISERV) Pathfinder, a visible-wavelength digital camera, telescope, and pointing system. Since the start of IDC response in 2012 there have been 108 IDC activations; NASA sensor systems have collected data for thirty-two of these events. Of the successful data collections, eight involved two or more ISS sensor systems responding to the same event. Data has also been collected by International Partners in response to natural disasters, most notably JAXA and Roscosmos/Energia through the Urugan program.

Mixed Traffic Information Collection System based on Pressure Sensor

NASA Astrophysics Data System (ADS)

Liao, Wenzhe; Liu, Mingsheng; Meng, Qingli

The traffic information collection is the base of Intelligent Traffic.At present, there exist mixed traffic situation in urban road in China. This paper researched and implemented a system through collecting the vehicle and bicycle mixed traffic flow parameters based on pressure sensor. According to information collection requirements, we selected pressure sensor, designed the data collection, storage and other hardware circuitries and information processing software. The experiment shows that the system can meet the demand of traffic information collection in the actual.

Optimization of Thermal Neutron Converter in SiC Sensors for Spectral Radiation Measurements

DOE Office of Scientific and Technical Information (OSTI.GOV)

Krolikowski, Igor; Cetnar, Jerzy; Issa, Fatima

2015-07-01

Optimization of the neutron converter in SiC sensors is presented. The sensors are used for spectral radiation measurements of thermal and fast neutrons and optionally gamma ray at elevated temperature in harsh radiation environment. The neutron converter, which is based on 10B, allows to detect thermal neutrons by means of neutron capture reaction. Two construction of the sensors were used to measure radiation in experiments. Sensor responses collected in experiments have been reproduced by the computer tool created by authors, it allows to validate the tool. The tool creates the response matrix function describing the characteristic of the sensors andmore » it was used for detailed analyses of the sensor responses. Obtained results help to optimize the neutron converter in order to increase thermal neutron detection. Several enhanced construction of the sensors, which includes the neutron converter based on {sup 10}B or {sup 6}Li, were proposed. (authors)« less

Unmanned Aerial System (UAS)-based phenotyping of soybean using multi-sensor data fusion and extreme learning machine

NASA Astrophysics Data System (ADS)

Maimaitijiang, Maitiniyazi; Ghulam, Abduwasit; Sidike, Paheding; Hartling, Sean; Maimaitiyiming, Matthew; Peterson, Kyle; Shavers, Ethan; Fishman, Jack; Peterson, Jim; Kadam, Suhas; Burken, Joel; Fritschi, Felix

2017-12-01

Estimating crop biophysical and biochemical parameters with high accuracy at low-cost is imperative for high-throughput phenotyping in precision agriculture. Although fusion of data from multiple sensors is a common application in remote sensing, less is known on the contribution of low-cost RGB, multispectral and thermal sensors to rapid crop phenotyping. This is due to the fact that (1) simultaneous collection of multi-sensor data using satellites are rare and (2) multi-sensor data collected during a single flight have not been accessible until recent developments in Unmanned Aerial Systems (UASs) and UAS-friendly sensors that allow efficient information fusion. The objective of this study was to evaluate the power of high spatial resolution RGB, multispectral and thermal data fusion to estimate soybean (Glycine max) biochemical parameters including chlorophyll content and nitrogen concentration, and biophysical parameters including Leaf Area Index (LAI), above ground fresh and dry biomass. Multiple low-cost sensors integrated on UASs were used to collect RGB, multispectral, and thermal images throughout the growing season at a site established near Columbia, Missouri, USA. From these images, vegetation indices were extracted, a Crop Surface Model (CSM) was advanced, and a model to extract the vegetation fraction was developed. Then, spectral indices/features were combined to model and predict crop biophysical and biochemical parameters using Partial Least Squares Regression (PLSR), Support Vector Regression (SVR), and Extreme Learning Machine based Regression (ELR) techniques. Results showed that: (1) For biochemical variable estimation, multispectral and thermal data fusion provided the best estimate for nitrogen concentration and chlorophyll (Chl) a content (RMSE of 9.9% and 17.1%, respectively) and RGB color information based indices and multispectral data fusion exhibited the largest RMSE 22.6%; the highest accuracy for Chl a + b content estimation was obtained by fusion of information from all three sensors with an RMSE of 11.6%. (2) Among the plant biophysical variables, LAI was best predicted by RGB and thermal data fusion while multispectral and thermal data fusion was found to be best for biomass estimation. (3) For estimation of the above mentioned plant traits of soybean from multi-sensor data fusion, ELR yields promising results compared to PLSR and SVR in this study. This research indicates that fusion of low-cost multiple sensor data within a machine learning framework can provide relatively accurate estimation of plant traits and provide valuable insight for high spatial precision in agriculture and plant stress assessment.

Fingerprint enhancement using a multispectral sensor

NASA Astrophysics Data System (ADS)

Rowe, Robert K.; Nixon, Kristin A.

2005-03-01

The level of performance of a biometric fingerprint sensor is critically dependent on the quality of the fingerprint images. One of the most common types of optical fingerprint sensors relies on the phenomenon of total internal reflectance (TIR) to generate an image. Under ideal conditions, a TIR fingerprint sensor can produce high-contrast fingerprint images with excellent feature definition. However, images produced by the same sensor under conditions that include dry skin, dirt on the skin, and marginal contact between the finger and the sensor, are likely to be severely degraded. This paper discusses the use of multispectral sensing as a means to collect additional images with new information about the fingerprint that can significantly augment the system performance under both normal and adverse sample conditions. In the context of this paper, "multispectral sensing" is used to broadly denote a collection of images taken under different illumination conditions: different polarizations, different illumination/detection configurations, as well as different wavelength illumination. Results from three small studies using an early-stage prototype of the multispectral-TIR (MTIR) sensor are presented along with results from the corresponding TIR data. The first experiment produced data from 9 people, 4 fingers from each person and 3 measurements per finger under "normal" conditions. The second experiment provided results from a study performed to test the relative performance of TIR and MTIR images when taken under extreme dry and dirty conditions. The third experiment examined the case where the area of contact between the finger and sensor is greatly reduced.

A Radiosonde Using a Humidity Sensor Array with a Platinum Resistance Heater and Multi-Sensor Data Fusion

PubMed Central

Shi, Yunbo; Luo, Yi; Zhao, Wenjie; Shang, Chunxue; Wang, Yadong; Chen, Yinsheng

2013-01-01

This paper describes the design and implementation of a radiosonde which can measure the meteorological temperature, humidity, pressure, and other atmospheric data. The system is composed of a CPU, microwave module, temperature sensor, pressure sensor and humidity sensor array. In order to effectively solve the humidity sensor condensation problem due to the low temperatures in the high altitude environment, a capacitive humidity sensor including four humidity sensors to collect meteorological humidity and a platinum resistance heater was developed using micro-electro-mechanical-system (MEMS) technology. A platinum resistance wire with 99.999% purity and 0.023 mm in diameter was used to obtain the meteorological temperature. A multi-sensor data fusion technique was applied to process the atmospheric data. Static and dynamic experimental results show that the designed humidity sensor with platinum resistance heater can effectively tackle the sensor condensation problem, shorten response times and enhance sensitivity. The humidity sensor array can improve measurement accuracy and obtain a reliable initial meteorological humidity data, while the multi-sensor data fusion technique eliminates the uncertainty in the measurement. The radiosonde can accurately reflect the meteorological changes. PMID:23857263

A radiosonde using a humidity sensor array with a platinum resistance heater and multi-sensor data fusion.

PubMed

Shi, Yunbo; Luo, Yi; Zhao, Wenjie; Shang, Chunxue; Wang, Yadong; Chen, Yinsheng

2013-07-12

This paper describes the design and implementation of a radiosonde which can measure the meteorological temperature, humidity, pressure, and other atmospheric data. The system is composed of a CPU, microwave module, temperature sensor, pressure sensor and humidity sensor array. In order to effectively solve the humidity sensor condensation problem due to the low temperatures in the high altitude environment, a capacitive humidity sensor including four humidity sensors to collect meteorological humidity and a platinum resistance heater was developed using micro-electro-mechanical-system (MEMS) technology. A platinum resistance wire with 99.999% purity and 0.023 mm in diameter was used to obtain the meteorological temperature. A multi-sensor data fusion technique was applied to process the atmospheric data. Static and dynamic experimental results show that the designed humidity sensor with platinum resistance heater can effectively tackle the sensor condensation problem, shorten response times and enhance sensitivity. The humidity sensor array can improve measurement accuracy and obtain a reliable initial meteorological humidity data, while the multi-sensor data fusion technique eliminates the uncertainty in the measurement. The radiosonde can accurately reflect the meteorological changes.

Evaluation of Software Simulation of Road Weather Information System.

DOT National Transportation Integrated Search

2016-09-01

A road weather information system (RWIS) is a combination of technologies that collects, transmits, models, and disseminates weather and road condition information. Sensors measure a range of weatherrelated conditions, including pavement temperatur...

Systems and methods for analyzing building operations sensor data

DOEpatents

Mezic, Igor; Eisenhower, Bryan A.

2015-05-26

Systems and methods are disclosed for analyzing building sensor information and decomposing the information therein to a more manageable and more useful form. Certain embodiments integrate energy-based and spectral-based analysis methods with parameter sampling and uncertainty/sensitivity analysis to achieve a more comprehensive perspective of building behavior. The results of this analysis may be presented to a user via a plurality of visualizations and/or used to automatically adjust certain building operations. In certain embodiments, advanced spectral techniques, including Koopman-based operations, are employed to discern features from the collected building sensor data.

Design of self-contained sensor for monitoring of deep-sea offshore platform

NASA Astrophysics Data System (ADS)

Song, Yang; Yu, Yan; Zhang, Chunwei; Dong, Weijie; Ou, Jinping

2013-04-01

Offshore platform, which is the base of the production and living in the sea, is the most important infrastructure for developing oil and gas resources. At present, there are almost 6500 offshore platforms servicing in the 53 countries' sea areas around the world, creating great wealth for the world. In general, offshore platforms may work for 20 years, however, offshore platforms are expensive, complex, bulky, and so many of them are on extended active duty. Because of offshore platforms servicing in the harsh marine environment for a long time, the marine environment have a great impact on the offshore platforms. Besides, with the impact and erosion of seawater, and material aging, the offshore platform is possible to be in unexpected situations when a badly sudden situation happens. Therefore, it is of great significance to monitor the marine environment and offshore platforms. The self-contained sensor for deep-sea offshore platform with its unique design, can not only effectively extend the working time of the sensor with the capability of converting vibration energy to electrical energy, but also simultaneously collect the data of acceleration, inclination, temperature and humidity of the deep sea, so that we can achieve the purpose of monitoring offshore platforms through analyzing the collected data. The self-contained sensor for monitoring of deep-sea offshore platform includes sensing unit, data collecting and storage unit, the energy supply unit. The sensing unit with multi-variables, consists of an accelerometer LIS344ALH, an inclinometer SCA103T and a temperature and humidity sensor SHT11; the data collecting and storage unit includes the MSP430 low-power MCU, large capacity memory, clock circuit and the communication interface, the communication interface includes USB interface, serial ports and wireless interface; in addition, the energy supply unit, converting vibration to electrical energy to power the overall system, includes the electromagnetic generator, voltage multiplier circuit and a super capacitor which can withstand virtually unlimited number of charge-discharge cycles. When the seawater impacts on offshore platforms to produce vibration, electromagnetic generator converts vibration to electrical energy, its output(~ 1 V 50 Hz AC) is stepped up and rectified by a voltage multiplier circuit, and the energy is stored in a super capacitor. It is controlled by the MSP430 that monitors the voltage level on the super capacitor. The super capacitor charges the Li-ion battery when the voltage on the super capacitor reaches a threshold, then the whole process of energy supply is completed. The self-contained sensor for deep-sea offshore platform has good application prospects and practical value with small size, low power, being easy to install, converting vibration energy to supply power and high detection accuracy.

Using Diurnal Temperature Signals to Infer Vertical Groundwater-Surface Water Exchange.

PubMed

Irvine, Dylan J; Briggs, Martin A; Lautz, Laura K; Gordon, Ryan P; McKenzie, Jeffrey M; Cartwright, Ian

2017-01-01

Heat is a powerful tracer to quantify fluid exchange between surface water and groundwater. Temperature time series can be used to estimate pore water fluid flux, and techniques can be employed to extend these estimates to produce detailed plan-view flux maps. Key advantages of heat tracing include cost-effective sensors and ease of data collection and interpretation, without the need for expensive and time-consuming laboratory analyses or induced tracers. While the collection of temperature data in saturated sediments is relatively straightforward, several factors influence the reliability of flux estimates that are based on time series analysis (diurnal signals) of recorded temperatures. Sensor resolution and deployment are particularly important in obtaining robust flux estimates in upwelling conditions. Also, processing temperature time series data involves a sequence of complex steps, including filtering temperature signals, selection of appropriate thermal parameters, and selection of the optimal analytical solution for modeling. This review provides a synthesis of heat tracing using diurnal temperature oscillations, including details on optimal sensor selection and deployment, data processing, model parameterization, and an overview of computing tools available. Recent advances in diurnal temperature methods also provide the opportunity to determine local saturated thermal diffusivity, which can improve the accuracy of fluid flux modeling and sensor spacing, which is related to streambed scour and deposition. These parameters can also be used to determine the reliability of flux estimates from the use of heat as a tracer. © 2016, National Ground Water Association.

HYDICE postflight data processing

NASA Astrophysics Data System (ADS)

Aldrich, William S.; Kappus, Mary E.; Resmini, Ronald G.; Mitchell, Peter A.

1996-06-01

The hyperspectral digital imagery collection experiment (HYDICE) sensor records instrument counts for scene data, in-flight spectral and radiometric calibration sequences, and dark current levels onto an AMPEX DCRsi data tape. Following flight, the HYDICE ground data processing subsystem (GDPS) transforms selected scene data from digital numbers (DN) to calibrated radiance levels at the sensor aperture. This processing includes: dark current correction, spectral and radiometric calibration, conversion to radiance, and replacement of bad detector elements. A description of the algorithms for post-flight data processing is presented. A brief analysis of the original radiometric calibration procedure is given, along with a description of the development of the modified procedure currently used. Example data collected during the 1995 flight season, but uncorrected and processed, are shown to demonstrate the removal of apparent sensor artifacts (e.g., non-uniformities in detector response over the array) as a result of this transformation.

The geographic applications program of the U. S. Geological Survey

USGS Publications Warehouse

Gerlach, Arch C.

1969-01-01

The fundamental objective of modern Geography is to improve man's level of living through a better understanding of man-environment inter actions. Related goals of the USGS program for applications of remote sensor data to Geographical research are: (1) the analysis and improvement of land use, with special emphasis on urban problems; and (2) more effective use of the total available energy budget, including insolation, mineral fuels, atomic energy, human resources, and mental energy, all of which are integrated into man-environment interactions. The collection of data through remote sensors in air craft and spacecraft is financed largely by funds from NASA, and is part of the much broader EROS Program of the Department of the Interior. Results to date have achieved much toward the identification of remote sensor signatures for Earth features and human activities, and toward evaluation of instruments for collecting essential information.

UAV-Assisted Dynamic Clustering of Wireless Sensor Networks for Crop Health Monitoring

PubMed Central

Ammad Uddin, Mohammad; Mansour, Ali; Le Jeune, Denis; Ayaz, Mohammad; Aggoune, el-Hadi M.

2018-01-01

In this study, a crop health monitoring system is developed by using state of the art technologies including wireless sensors and Unmanned Aerial Vehicles (UAVs). Conventionally data is collected from sensor nodes either by fixed base stations or mobile sinks. Mobile sinks are considered a better choice nowadays due to their improved network coverage and energy utilization. Usually, the mobile sink is used in two ways: either it goes for random walk to find the scattered nodes and collect data, or follows a pre-defined path established by the ground network/clusters. Neither of these options is suitable in our scenario due to the factors like dynamic data collection, the strict targeted area required to be scanned, unavailability of a large number of nodes, dynamic path of the UAV, and most importantly, none of these are known in advance. The contribution of this paper is the formation of dynamic runtime clusters of field sensors by considering the above mentioned factors. Furthermore a mechanism (Bayesian classifier) is defined to select best node as cluster head. The proposed system is validated through simulation results, lab and infield experiments using concept devices. The obtained results are encouraging, especially in terms of deployment time, energy, efficiency, throughput and ease of use. PMID:29439496

A Targeted Approach to Ligament Balancing Using Kinetic Sensors.

PubMed

Gustke, Kenneth A; Golladay, Gregory J; Roche, Martin W; Elson, Leah C; Anderson, Christopher R

2017-07-01

Currently, soft-tissue imbalance contributes to several of the foremost reasons for revision following primary TKA, including instability, stiffness, and aseptic loosening. In order to decrease the incidence of soft-tissue imbalance, intraoperative sensors were developed to provide real-time, quantitative load data within the knee. This study examines the intraoperative data of a group of multicenter patients to determine how targeted ligament releases affect intra-articular loading, and to understand which types of releases are necessary to achieve quantified ligament balance. A group of 129 patients received sensor-assisted TKA, as part of a multicenter study. Medial and lateral loading data were collected pre-release, during any sequential releases, and post-release. All data were collected at 10°, 45°, and 90° during range of motion testing. Ligament release type, release technique type, and resultant loading were collected. Loading across the joint decreased, overall, and became more symmetrical after releases were performed. On average, between 2 and 3 corrections were made (up to 8) in order to achieve ligament balance. The ligament release type and subsequent quantified change in loading were in agreement with historical, qualified sources. Objective data from sensor output may assist surgeons in decreasing loading variability and, thereby, decreasing ligament imbalance and its associated complications. Copyright © 2017 Elsevier Inc. All rights reserved.

Estimation of Temporal Gait Parameters Using a Wearable Microphone-Sensor-Based System

PubMed Central

Wang, Cheng; Wang, Xiangdong; Long, Zhou; Yuan, Jing; Qian, Yueliang; Li, Jintao

2016-01-01

Most existing wearable gait analysis methods focus on the analysis of data obtained from inertial sensors. This paper proposes a novel, low-cost, wireless and wearable gait analysis system which uses microphone sensors to collect footstep sound signals during walking. This is the first time a microphone sensor is used as a wearable gait analysis device as far as we know. Based on this system, a gait analysis algorithm for estimating the temporal parameters of gait is presented. The algorithm fully uses the fusion of two feet footstep sound signals and includes three stages: footstep detection, heel-strike event and toe-on event detection, and calculation of gait temporal parameters. Experimental results show that with a total of 240 data sequences and 1732 steps collected using three different gait data collection strategies from 15 healthy subjects, the proposed system achieves an average 0.955 F1-measure for footstep detection, an average 94.52% accuracy rate for heel-strike detection and 94.25% accuracy rate for toe-on detection. Using these detection results, nine temporal related gait parameters are calculated and these parameters are consistent with their corresponding normal gait temporal parameters and labeled data calculation results. The results verify the effectiveness of our proposed system and algorithm for temporal gait parameter estimation. PMID:27999321

UAV-Assisted Dynamic Clustering of Wireless Sensor Networks for Crop Health Monitoring.

PubMed

Uddin, Mohammad Ammad; Mansour, Ali; Jeune, Denis Le; Ayaz, Mohammad; Aggoune, El-Hadi M

2018-02-11

In this study, a crop health monitoring system is developed by using state of the art technologies including wireless sensors and Unmanned Aerial Vehicles (UAVs). Conventionally data is collected from sensor nodes either by fixed base stations or mobile sinks. Mobile sinks are considered a better choice nowadays due to their improved network coverage and energy utilization. Usually, the mobile sink is used in two ways: either it goes for random walk to find the scattered nodes and collect data, or follows a pre-defined path established by the ground network/clusters. Neither of these options is suitable in our scenario due to the factors like dynamic data collection, the strict targeted area required to be scanned, unavailability of a large number of nodes, dynamic path of the UAV, and most importantly, none of these are known in advance. The contribution of this paper is the formation of dynamic runtime clusters of field sensors by considering the above mentioned factors. Furthermore a mechanism (Bayesian classifier) is defined to select best node as cluster head. The proposed system is validated through simulation results, lab and infield experiments using concept devices. The obtained results are encouraging, especially in terms of deployment time, energy, efficiency, throughput and ease of use.

Dataset from chemical gas sensor array in turbulent wind tunnel.

PubMed

Fonollosa, Jordi; Rodríguez-Luján, Irene; Trincavelli, Marco; Huerta, Ramón

2015-06-01

The dataset includes the acquired time series of a chemical detection platform exposed to different gas conditions in a turbulent wind tunnel. The chemo-sensory elements were sampling directly the environment. In contrast to traditional approaches that include measurement chambers, open sampling systems are sensitive to dispersion mechanisms of gaseous chemical analytes, namely diffusion, turbulence, and advection, making the identification and monitoring of chemical substances more challenging. The sensing platform included 72 metal-oxide gas sensors that were positioned at 6 different locations of the wind tunnel. At each location, 10 distinct chemical gases were released in the wind tunnel, the sensors were evaluated at 5 different operating temperatures, and 3 different wind speeds were generated in the wind tunnel to induce different levels of turbulence. Moreover, each configuration was repeated 20 times, yielding a dataset of 18,000 measurements. The dataset was collected over a period of 16 months. The data is related to "On the performance of gas sensor arrays in open sampling systems using Inhibitory Support Vector Machines", by Vergara et al.[1]. The dataset can be accessed publicly at the UCI repository upon citation of [1]: http://archive.ics.uci.edu/ml/datasets/Gas+sensor+arrays+in+open+sampling+settings.

Hybrid architecture for building secure sensor networks

NASA Astrophysics Data System (ADS)

Owens, Ken R., Jr.; Watkins, Steve E.

2012-04-01

Sensor networks have various communication and security architectural concerns. Three approaches are defined to address these concerns for sensor networks. The first area is the utilization of new computing architectures that leverage embedded virtualization software on the sensor. Deploying a small, embedded virtualization operating system on the sensor nodes that is designed to communicate to low-cost cloud computing infrastructure in the network is the foundation to delivering low-cost, secure sensor networks. The second area focuses on securing the sensor. Sensor security components include developing an identification scheme, and leveraging authentication algorithms and protocols that address security assurance within the physical, communication network, and application layers. This function will primarily be accomplished through encrypting the communication channel and integrating sensor network firewall and intrusion detection/prevention components to the sensor network architecture. Hence, sensor networks will be able to maintain high levels of security. The third area addresses the real-time and high priority nature of the data that sensor networks collect. This function requires that a quality-of-service (QoS) definition and algorithm be developed for delivering the right data at the right time. A hybrid architecture is proposed that combines software and hardware features to handle network traffic with diverse QoS requirements.

Evaluation of the performance of irradiated silicon strip sensors for the forward detector of the ATLAS Inner Tracker Upgrade

NASA Astrophysics Data System (ADS)

Mori, R.; Allport, P. P.; Baca, M.; Broughton, J.; Chisholm, A.; Nikolopoulos, K.; Pyatt, S.; Thomas, J. P.; Wilson, J. A.; Kierstead, J.; Kuczewski, P.; Lynn, D.; Arratia-Munoz, M. I.; Hommels, L. B. A.; Ullan, M.; Fleta, C.; Fernandez-Tejero, J.; Bloch, I.; Gregor, I. M.; Lohwasser, K.; Poley, L.; Tackmann, K.; Trofimov, A.; Yildirim, E.; Hauser, M.; Jakobs, K.; Kuehn, S.; Mahboubi, K.; Parzefall, U.; Clark, A.; Ferrere, D.; Sevilla, S. Gonzalez; Ashby, J.; Blue, A.; Bates, R.; Buttar, C.; Doherty, F.; McMullen, T.; McEwan, F.; O'Shea, V.; Kamada, S.; Yamamura, K.; Ikegami, Y.; Nakamura, K.; Takubo, Y.; Unno, Y.; Takashima, R.; Chilingarov, A.; Fox, H.; Affolder, A. A.; Casse, G.; Dervan, P.; Forshaw, D.; Greenall, A.; Wonsak, S.; Wormald, M.; Cindro, V.; Kramberger, G.; Mandić, I.; Mikuž, M.; Gorelov, I.; Hoeferkamp, M.; Palni, P.; Seidel, S.; Taylor, A.; Toms, K.; Wang, R.; Hessey, N. P.; Valencic, N.; Hanagaki, K.; Dolezal, Z.; Kodys, P.; Bohm, J.; Stastny, J.; Mikestikova, M.; Bevan, A.; Beck, G.; Milke, C.; Domingo, M.; Fadeyev, V.; Galloway, Z.; Hibbard-Lubow, D.; Liang, Z.; Sadrozinski, H. F.-W.; Seiden, A.; To, K.; French, R.; Hodgson, P.; Marin-Reyes, H.; Parker, K.; Jinnouchi, O.; Hara, K.; Sato, K.; Sato, K.; Hagihara, M.; Iwabuchi, S.; Bernabeu, J.; Civera, J. V.; Garcia, C.; Lacasta, C.; Garcia, S. Marti i.; Rodriguez, D.; Santoyo, D.; Solaz, C.; Soldevila, U.

2016-09-01

The upgrade to the High-Luminosity LHC foreseen in about ten years represents a great challenge for the ATLAS inner tracker and the silicon strip sensors in the forward region. Several strip sensor designs were developed by the ATLAS collaboration and fabricated by Hamamatsu in order to maintain enough performance in terms of charge collection efficiency and its uniformity throughout the active region. Of particular attention, in the case of a stereo-strip sensor, is the area near the sensor edge where shorter strips were ganged to the complete ones. In this work the electrical and charge collection test results on irradiated miniature sensors with forward geometry are presented. Results from charge collection efficiency measurements show that at the maximum expected fluence, the collected charge is roughly halved with respect to the one obtained prior to irradiation. Laser measurements show a good signal uniformity over the sensor. Ganged strips have a similar efficiency as standard strips.

Signal system data mining

DOT National Transportation Integrated Search

2000-09-01

Intelligent transportation systems (ITS) include large numbers of traffic sensors that collect enormous quantities of data. The data provided by ITS is necessary for advanced forms of control, however basic forms of control, primarily time-of-day (TO...

Feasibility of large-scale deployment of multiple wearable sensors in Parkinson's disease

PubMed Central

Hahn, Tim; Evers, Luc J. W.; de Vries, Nienke M.; Cohen, Eli; Afek, Michal; Bataille, Lauren; Daeschler, Margaret; Claes, Kasper; Boroojerdi, Babak; Terricabras, Dolors; Little, Max A.; Baldus, Heribert; Bloem, Bastiaan R.; Faber, Marjan J.

2017-01-01

Wearable devices can capture objective day-to-day data about Parkinson’s Disease (PD). This study aims to assess the feasibility of implementing wearable technology to collect data from multiple sensors during the daily lives of PD patients. The Parkinson@home study is an observational, two-cohort (North America, NAM; The Netherlands, NL) study. To recruit participants, different strategies were used between sites. Main enrolment criteria were self-reported diagnosis of PD, possession of a smartphone and age≥18 years. Participants used the Fox Wearable Companion app on a smartwatch and smartphone for a minimum of 6 weeks (NAM) or 13 weeks (NL). Sensor-derived measures estimated information about movement. Additionally, medication intake and symptoms were collected via self-reports in the app. A total of 953 participants were included (NL: 304, NAM: 649). Enrolment rate was 88% in the NL (n = 304) and 51% (n = 649) in NAM. Overall, 84% (n = 805) of participants contributed sensor data. Participants were compliant for 68% (16.3 hours/participant/day) of the study period in NL and for 62% (14.8 hours/participant/day) in NAM. Daily accelerometer data collection decreased 23% in the NL after 13 weeks, and 27% in NAM after 6 weeks. Data contribution was not affected by demographics, clinical characteristics or attitude towards technology, but was by the platform usability score in the NL (χ2 (2) = 32.014, p<0.001), and self-reported depression in NAM (χ2(2) = 6.397, p = .04). The Parkinson@home study shows that it is feasible to collect objective data using multiple wearable sensors in PD during daily life in a large cohort. PMID:29261709

Investigating energy-saving potentials in the cloud.

PubMed

Lee, Da-Sheng

2014-02-20

Collecting webpage messages can serve as a sensor for investigating the energy-saving potential of buildings. Focusing on stores, a cloud sensor system is developed to collect data and determine their energy-saving potential. The owner of a store under investigation must register online, report the store address, area, and the customer ID number on the electric meter. The cloud sensor system automatically surveys the energy usage records by connecting to the power company website and calculating the energy use index (EUI) of the store. Other data includes the chain store check, company capital, location price, and the influence of weather conditions on the store; even the exposure frequency of store under investigation may impact the energy usage collected online. After collecting data from numerous stores, a multi-dimensional data array is constructed to determine energy-saving potential by identifying stores with similarity conditions. Similarity conditions refer to analyzed results that indicate that two stores have similar capital, business scale, weather conditions, and exposure frequency on web. Calculating the EUI difference or pure technical efficiency of stores, the energy-saving potential is determined. In this study, a real case study is performed. An 8-dimensional (8D) data array is constructed by surveying web data related to 67 stores. Then, this study investigated the savings potential of the 33 stores, using a site visit, and employed the cloud sensor system to determine the saving potential. The case study results show good agreement between the data obtained by the site visit and the cloud investigation, with errors within 4.17%. Among 33 the samples, eight stores have low saving potentials of less than 5%. The developed sensor on the cloud successfully identifies them as having low saving potential and avoids wasting money on the site visit.

Investigating Energy-Saving Potentials in the Cloud

PubMed Central

Lee, Da-Sheng

2014-01-01

Collecting webpage messages can serve as a sensor for investigating the energy-saving potential of buildings. Focusing on stores, a cloud sensor system is developed to collect data and determine their energy-saving potential. The owner of a store under investigation must register online, report the store address, area, and the customer ID number on the electric meter. The cloud sensor system automatically surveys the energy usage records by connecting to the power company website and calculating the energy use index (EUI) of the store. Other data includes the chain store check, company capital, location price, and the influence of weather conditions on the store; even the exposure frequency of store under investigation may impact the energy usage collected online. After collecting data from numerous stores, a multi-dimensional data array is constructed to determine energy-saving potential by identifying stores with similarity conditions. Similarity conditions refer to analyzed results that indicate that two stores have similar capital, business scale, weather conditions, and exposure frequency on web. Calculating the EUI difference or pure technical efficiency of stores, the energy-saving potential is determined. In this study, a real case study is performed. An 8-dimensional (8D) data array is constructed by surveying web data related to 67 stores. Then, this study investigated the savings potential of the 33 stores, using a site visit, and employed the cloud sensor system to determine the saving potential. The case study results show good agreement between the data obtained by the site visit and the cloud investigation, with errors within 4.17%. Among 33 the samples, eight stores have low saving potentials of less than 5%. The developed sensor on the cloud successfully identifies them as having low saving potential and avoids wasting money on the site visit. PMID:24561405

UXO Discrimination Using Vehicle Towed and Man Portable Sensor Data Collected at Camp Beale, California

DTIC Science & Technology

2011-11-01

UXO Discrimination Using Vehicle Towed and Man Portable Sensor Data Collected at Camp Beale, California Len Pasion , Laurens Beran, Stephen Billings...PORTABLE SENSOR DATA COLLECTED AT CAMP BEALE, CALIFORNIA LEN PASION Sky Research 112A 2386 East Mall Vancouver, BC V6T1Z3 CANADA (604) 221

Early detection and evaluation of waste through sensorized containers for a collection monitoring application.

PubMed

Rovetta, Alberto; Xiumin, Fan; Vicentini, Federico; Minghua, Zhu; Giusti, Alessandro; Qichang, He

2009-12-01

The present study describes a novel application for use in the monitoring of municipal solid waste, based on distributed sensor technology and geographical information systems. Original field testing and evaluation of the application were carried out in Pudong, Shanghai (PR China). The local waste management system in Pudong features particular requirements related to the rapidly increasing rate of waste production. In view of the fact that collected waste is currently deployed to landfills or to incineration plants within the context investigated, the key aspects to be taken into account in waste collection procedures include monitoring of the overall amount of waste produced, quantitative measurement of the waste present at each collection point and identification of classes of material present in the collected waste. The case study described herein focuses particularly on the above mentioned aspects, proposing the implementation of a network of sensorized waste containers linked to a data management system. Containers used were equipped with a set of sensors mounted onto standard waste bins. The design, implementation and validation procedures applied are subsequently described. The main aim to be achieved by data collection and evaluation was to provide for feasibility analysis of the final device. Data pertaining to the content of waste containers, sampled and processed by means of devices validated on two purpose-designed prototypes, were therefore uploaded to a central monitoring server using GPRS connection. The data monitoring and management modules are integrated into an existing application used by local municipal authorities. A field test campaign was performed in the Pudong area. The system was evaluated in terms of real data flow from the network nodes (containers) as well as in terms of optimization functions, such as collection vehicle routing and scheduling. The most important outcomes obtained were related to calculations of waste weight and volume. The latter data were subsequently used as parameters for the routing optimization of collection trucks and material density evaluation.

Balancing energy consumption with hybrid clustering and routing strategy in wireless sensor networks.

PubMed

Xu, Zhezhuang; Chen, Liquan; Liu, Ting; Cao, Lianyang; Chen, Cailian

2015-10-20

Multi-hop data collection in wireless sensor networks (WSNs) is a challenge issue due to the limited energy resource and transmission range of wireless sensors. The hybrid clustering and routing (HCR) strategy has provided an effective solution, which can generate a connected and efficient cluster-based topology for multi-hop data collection in WSNs. However, it suffers from imbalanced energy consumption, which results in the poor performance of the network lifetime. In this paper, we evaluate the energy consumption of HCR and discover an important result: the imbalanced energy consumption generally appears in gradient k = 1, i.e., the nodes that can communicate with the sink directly. Based on this observation, we propose a new protocol called HCR-1, which includes the adaptive relay selection and tunable cost functions to balance the energy consumption. The guideline of setting the parameters in HCR-1 is provided based on simulations. The analytical and numerical results prove that, with minor modification of the topology in Sensors 2015, 15 26584 gradient k = 1, the HCR-1 protocol effectively balances the energy consumption and prolongs the network lifetime.

Biomimetic approaches for engineered organ chips and skin electronics for in vitro diagnostics

NASA Astrophysics Data System (ADS)

Suh, Kahp-Yang; Pang, Changhyun; Jang, Kyung-Jin; Kim, Hong Nam; Jiao, Alex; Hwang, Nathaniel S.; Kim, Min Sung; Kang, Do-Hyun; Kim, Deok-Ho

2012-10-01

Two kinds of biomimetic systems including engineered organ chip and flexible electronic sensor are presented. First, in vivo, renal tubular epithelial cells are exposed to luminal fluid shear stress (FSS) and a transepithelial osmotic gradient. In this study, we used a simple collecting-duct-on-a-chip to investigate the role of an altered luminal microenvironment in the translocation of aquaporin-2 (AQP2) and the reorganization of actin cytoskeleton (F-actin) in primary cultured inner medullary collecting duct (IMCD) cells of rat kidney. We demonstrate that several factors (i.e., luminal FSS, hormonal stimulation, transepithelial osmotic gradient) collectively exert a profound effect on the AQP2 trafficking in the collecting ducts, which is associated with actin cytoskeletal reorganization. Furthermore, with this kidney-mimicking chip, renal toxicity of cisplatin was tested under static and fluidic conditions, suggesting the physiological relevancy of fluidic environment compared to static culture. Second, we present a simple architecture for a flexible and highly sensitive strain sensor that enables the detection of pressure, shear and torsion. The device is based on two interlocked arrays of high-aspect-ratio Pt-coated polymeric nanofibres that are supported on thin polydimethylsiloxane layers. When different sensing stimuli are applied, the degree of interconnection and the electrical resistance of the sensor changes in a reversible, directional manner with specific, discernible strain-gauge factors. We show that the sensor can be used to monitor signals ranging from human heartbeats to the impact of a bouncing water droplet on a superhydrophobic surface.

On securing wireless sensor network--novel authentication scheme against DOS attacks.

PubMed

Raja, K Nirmal; Beno, M Marsaline

2014-10-01

Wireless sensor networks are generally deployed for collecting data from various environments. Several applications specific sensor network cryptography algorithms have been proposed in research. However WSN's has many constrictions, including low computation capability, less memory, limited energy resources, vulnerability to physical capture, which enforce unique security challenges needs to make a lot of improvements. This paper presents a novel security mechanism and algorithm for wireless sensor network security and also an application of this algorithm. The proposed scheme is given to strong authentication against Denial of Service Attacks (DOS). The scheme is simulated using network simulator2 (NS2). Then this scheme is analyzed based on the network packet delivery ratio and found that throughput has improved.

Piezoresistive Pressure Sensor Based on Synergistical Innerconnect Polyvinyl Alcohol Nanowires/Wrinkled Graphene Film.

PubMed

Liu, Weijie; Liu, Nishuang; Yue, Yang; Rao, Jiangyu; Cheng, Feng; Su, Jun; Liu, Zhitian; Gao, Yihua

2018-04-01

Piezoresistive sensor is a promising pressure sensor due to its attractive advantages including uncomplicated signal collection, simple manufacture, economical and practical characteristics. Here, a flexible and highly sensitive pressure sensor based on wrinkled graphene film (WGF)/innerconnected polyvinyl alcohol (PVA) nanowires/interdigital electrodes is fabricated. Due to the synergistic effect between WGF and innerconnected PVA nanowires, the as-prepared pressure sensor realizes a high sensitivity of 28.34 kPa -1 . In addition, the device is able to discern lightweight rice about 22.4 mg (≈2.24 Pa) and shows excellent durability and reliability after 6000 repeated loading and unloading cycles. What is more, the device can detect subtle pulse beat and monitor various human movement behaviors in real-time. © 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

CPAC: Energy-Efficient Data Collection through Adaptive Selection of Compression Algorithms for Sensor Networks

PubMed Central

Lee, HyungJune; Kim, HyunSeok; Chang, Ik Joon

2014-01-01

We propose a technique to optimize the energy efficiency of data collection in sensor networks by exploiting a selective data compression. To achieve such an aim, we need to make optimal decisions regarding two aspects: (1) which sensor nodes should execute compression; and (2) which compression algorithm should be used by the selected sensor nodes. We formulate this problem into binary integer programs, which provide an energy-optimal solution under the given latency constraint. Our simulation results show that the optimization algorithm significantly reduces the overall network-wide energy consumption for data collection. In the environment having a stationary sink from stationary sensor nodes, the optimized data collection shows 47% energy savings compared to the state-of-the-art collection protocol (CTP). More importantly, we demonstrate that our optimized data collection provides the best performance in an intermittent network under high interference. In such networks, we found that the selective compression for frequent packet retransmissions saves up to 55% energy compared to the best known protocol. PMID:24721763

Rapid-response Sensor Networks Leveraging Open Standards and the Internet of Things

NASA Astrophysics Data System (ADS)

Bermudez, L. E.; Lieberman, J. E.; Lewis, L.; Botts, M.; Liang, S.

2016-12-01

New sensor technologies provide an unparalleled capability to collect large numbers of diverse observations about the world around us. Networks of such sensors are especially effective for capturing and analyzing unexpected, fast moving events if they can be deployed with a minimum of time, effort, and cost. A rapid-response sensing and processing capability is extremely important in quickly unfolding events not only to collect data for future research.but also to support response efforts that may be needed by providing up-to-date knowledge of the situation. A recent pilot activity coordinated by the Open Geospatial Consortium combined Sensor Web Enablement (SWE) standards with Internet of Things (IoT) practices to understand better how to set up rapid-response sensor networks in comparable event situations involving accidents or disasters. The networks included weather and environmental sensors, georeferenced UAV and PTZ imagery collectors, and observations from "citizen sensors", as well as virtual observations generated by predictive models. A key feature of each "SWE-IoT" network was one or more Sensor Hubs that connected local, often proprietary sensor device protocols to a common set of standard SWE data types and standard Web interfaces on an IP-based internetwork. This IoT approach provided direct, common, interoperable access to all sensor readings from anywhere on the internetwork of sensors, Hubs, and applications. Sensor Hubs also supported an automated discovery protocol in which activated Hubs registered themselves with a canonical catalog service. As each sensor (wireless or wired) was activated within range of an authorized Hub, it registered itself with that Hub, which in turn registered the sensor and its capabilities with the catalog. Sensor Hub functions were implemented in a range of component types, from personal devices such as smartphones and Raspberry Pi's to full cloud-based sensor services platforms. Connected into a network "constellation" the Hubs also enabled reliable exchange and persistence of sensor data in constrained communications environments. Pilot results are being documented in public OGC engineering reports and are feeding into improved standards to support SWE-IoT networks for a range of domains and applications.

A uniform energy consumption algorithm for wireless sensor and actuator networks based on dynamic polling point selection.

PubMed

Li, Shuo; Peng, Jun; Liu, Weirong; Zhu, Zhengfa; Lin, Kuo-Chi

2013-12-19

Recent research has indicated that using the mobility of the actuator in wireless sensor and actuator networks (WSANs) to achieve mobile data collection can greatly increase the sensor network lifetime. However, mobile data collection may result in unacceptable collection delays in the network if the path of the actuator is too long. Because real-time network applications require meeting data collection delay constraints, planning the path of the actuator is a very important issue to balance the prolongation of the network lifetime and the reduction of the data collection delay. In this paper, a multi-hop routing mobile data collection algorithm is proposed based on dynamic polling point selection with delay constraints to address this issue. The algorithm can actively update the selection of the actuator's polling points according to the sensor nodes' residual energies and their locations while also considering the collection delay constraint. It also dynamically constructs the multi-hop routing trees rooted by these polling points to balance the sensor node energy consumption and the extension of the network lifetime. The effectiveness of the algorithm is validated by simulation.

Multisensor speech input

NASA Astrophysics Data System (ADS)

Viswanathan, V. R.; Karnofsky, K. F.; Stevens, K. N.; Alakel, M. N.

1983-12-01

The use of multiple sensors to transduce speech was investigated. A data base of speech and noise was collected from a number of transducers located on and around the head of the speaker. The transducers included pressure, first order gradient, second order gradient microphones and an accelerometer. The effort analyzed this data and evaluated the performance of a multiple sensor configuration. The conclusion was: multiple transducer configurations can provide a signal containing more useable speech information than that provided by a microphone.

Development and Validation of a UAV Based System for Air Pollution Measurements

PubMed Central

Villa, Tommaso Francesco; Salimi, Farhad; Morton, Kye; Morawska, Lidia; Gonzalez, Felipe

2016-01-01

Air quality data collection near pollution sources is difficult, particularly when sites are complex, have physical barriers, or are themselves moving. Small Unmanned Aerial Vehicles (UAVs) offer new approaches to air pollution and atmospheric studies. However, there are a number of critical design decisions which need to be made to enable representative data collection, in particular the location of the air sampler or air sensor intake. The aim of this research was to establish the best mounting point for four gas sensors and a Particle Number Concentration (PNC) monitor, onboard a hexacopter, so to develop a UAV system capable of measuring point source emissions. The research included two different tests: (1) evaluate the air flow behavior of a hexacopter, its downwash and upwash effect, by measuring air speed along three axes to determine the location where the sensors should be mounted; (2) evaluate the use of gas sensors for CO2, CO, NO2 and NO, and the PNC monitor (DISCmini) to assess the efficiency and performance of the UAV based system by measuring emissions from a diesel engine. The air speed behavior map produced by test 1 shows the best mounting point for the sensors to be alongside the UAV. This position is less affected by the propeller downwash effect. Test 2 results demonstrated that the UAV propellers cause a dispersion effect shown by the decrease of gas and PN concentration measured in real time. A Linear Regression model was used to estimate how the sensor position, relative to the UAV center, affects pollutant concentration measurements when the propellers are turned on. This research establishes guidelines on how to develop a UAV system to measure point source emissions. Such research should be undertaken before any UAV system is developed for real world data collection. PMID:28009820

Development and Validation of a UAV Based System for Air Pollution Measurements.

PubMed

Villa, Tommaso Francesco; Salimi, Farhad; Morton, Kye; Morawska, Lidia; Gonzalez, Felipe

2016-12-21

Air quality data collection near pollution sources is difficult, particularly when sites are complex, have physical barriers, or are themselves moving. Small Unmanned Aerial Vehicles (UAVs) offer new approaches to air pollution and atmospheric studies. However, there are a number of critical design decisions which need to be made to enable representative data collection, in particular the location of the air sampler or air sensor intake. The aim of this research was to establish the best mounting point for four gas sensors and a Particle Number Concentration (PNC) monitor, onboard a hexacopter, so to develop a UAV system capable of measuring point source emissions. The research included two different tests: (1) evaluate the air flow behavior of a hexacopter, its downwash and upwash effect, by measuring air speed along three axes to determine the location where the sensors should be mounted; (2) evaluate the use of gas sensors for CO₂, CO, NO₂ and NO, and the PNC monitor (DISCmini) to assess the efficiency and performance of the UAV based system by measuring emissions from a diesel engine. The air speed behavior map produced by test 1 shows the best mounting point for the sensors to be alongside the UAV. This position is less affected by the propeller downwash effect. Test 2 results demonstrated that the UAV propellers cause a dispersion effect shown by the decrease of gas and PN concentration measured in real time. A Linear Regression model was used to estimate how the sensor position, relative to the UAV center, affects pollutant concentration measurements when the propellers are turned on. This research establishes guidelines on how to develop a UAV system to measure point source emissions. Such research should be undertaken before any UAV system is developed for real world data collection.

Needs for Robotic Assessments of Nuclear Disasters

DOE Office of Scientific and Technical Information (OSTI.GOV)

Victor Walker; Derek Wadsworth

Following the nuclear disaster at the Fukushima nuclear reactor plant in Japan, the need for systems which can assist in dynamic high-radiation environments such as nuclear incidents has become more apparent. The INL participated in delivering robotic technologies to Japan and has identified key components which are needed for success and obstacles to their deployment. In addition, we are proposing new work and methods to improve assessments and reactions to such events in the future. Robotics needs in disaster situations include phases such as: Assessment, Remediation, and Recovery Our particular interest is in the initial assessment activities. In assessment wemore » need collection of environmental parameters, determination of conditions, and physical sample collection. Each phase would require key tools and efforts to develop. This includes study of necessary sensors and their deployment methods, the effects of radiation on sensors and deployment, and the development of training and execution systems.« less

Experimental studies in natural groundwater recharge dynamics: Assessment of recent advances in instrumentation

USGS Publications Warehouse

Sophocleous, M.; Perry, C.A.

1984-01-01

To quantify and model the natural groundwater-recharge process, two sites in south-central Kansas, U.S.A., were instrumented with various modern sensors and data microloggers. The atmospheric-boundary layer and the unsaturated and saturated soil zones were monitored as a unified regime. Data from the various sensors were collected using microloggers in combination with magnetic-cassette tape, graphical and digital recorders, analog paper-tape recorders, and direct observations to evaluate and automate data collection and processing. Atmospheric sensors included an anemometer, a tipping-bucket raingage, an air-temperature thermistor, a relative-humidity probe, a net radiometer, and a barometric-pressure transducer. Sensors in the unsaturated zone consisted of soil-temperature thermocouples, tensiometers coupled with pressure transducers and dial gages, gypsum blocks, and a neutron moisture probe operated by an observer. The saturated-zone sensors consisted of a water-level pressure transducer, a conventional float gage connected to a variable potentiometer, soil thermocouples, and a number of multiple-depth piezometers. Evaluation of the operation of these sensors and recorders indicated that certain types of equipment such as pressure transducers are very sensitive to environmental conditions. Extraordinary steps had to be taken to protect some of the equipment, whereas other equipment seemed to be reliable under all conditions. Based on such experiences, a number of suggestions aimed at improving such investigations are outlined. ?? 1984.

Next generation sensing platforms for extended deployments in large-scale, multidisciplinary, adaptive sampling and observational networks

NASA Astrophysics Data System (ADS)

Cross, J. N.; Meinig, C.; Mordy, C. W.; Lawrence-Slavas, N.; Cokelet, E. D.; Jenkins, R.; Tabisola, H. M.; Stabeno, P. J.

2016-12-01

New autonomous sensors have dramatically increased the resolution and accuracy of oceanographic data collection, enabling rapid sampling over extremely fine scales. Innovative new autonomous platofrms like floats, gliders, drones, and crawling moorings leverage the full potential of these new sensors by extending spatiotemporal reach across varied environments. During 2015 and 2016, The Innovative Technology for Arctic Exploration Program at the Pacific Marine Environmental Laboratory tested several new types of fully autonomous platforms with increased speed, durability, and power and payload capacity designed to deliver cutting-edge ecosystem assessment sensors to remote or inaccessible environments. The Expendable Ice-Tracking (EXIT) gloat developed by the NOAA Pacific Marine Environmental Laboratory (PMEL) is moored near bottom during the ice-free season and released on an autonomous timer beneath the ice during the following winter. The float collects a rapid profile during ascent, and continues to collect critical, poorly-accessible under-ice data until melt, when data is transmitted via satellite. The autonomous Oculus sub-surface glider developed by the University of Washington and PMEL has a large power and payload capacity and an enhanced buoyancy engine. This 'coastal truck' is designed for the rapid water column ascent required by optical imaging systems. The Saildrone is a solar and wind powered ocean unmanned surface vessel (USV) developed by Saildrone, Inc. in partnership with PMEL. This large-payload (200 lbs), fast (1-7 kts), durable (46 kts winds) platform was equipped with 15 sensors designed for ecosystem assessment during 2016, including passive and active acoustic systems specially redesigned for autonomous vehicle deployments. The senors deployed on these platforms achieved rigorous accuracy and precision standards. These innovative platforms provide new sampling capabilities and cost efficiencies in high-resolution sensor deployment, including reconnaissance for annual fisheries and marine mammal surveys; better linkages between sustained observing platforms; and adaptive deployments that can easily target anomalies as they arise.

Radiometric calibration updates to the Landsat collection

USGS Publications Warehouse

Micijevic, Esad; Haque, Md. Obaidul; Mishra, Nischal

2016-01-01

The Landsat Project is planning to implement a new collection management strategy for Landsat products generated at the U.S. Geological Survey (USGS) Earth Resources Observation and Science (EROS) Center. The goal of the initiative is to identify a collection of consistently geolocated and radiometrically calibrated images across the entire Landsat archive that is readily suitable for time-series analyses. In order to perform an accurate land change analysis, the data from all Landsat sensors must be on the same radiometric scale. Landsat 7 Enhanced Thematic Mapper Plus (ETM+) is calibrated to a radiance standard and all previous sensors are cross-calibrated to its radiometric scale. Landsat 8 Operational Land Imager (OLI) is calibrated to both radiance and reflectance standards independently. The Landsat 8 OLI reflectance calibration is considered to be most accurate. To improve radiometric calibration accuracy of historical data, Landsat 1-7 sensors also need to be cross-calibrated to the OLI reflectance scale. Results of that effort, as well as other calibration updates including the absolute and relative radiometric calibration and saturated pixel replacement for Landsat 8 OLI and absolute calibration for Landsat 4 and 5 Thematic Mappers (TM), will be implemented into Landsat products during the archive reprocessing campaign planned within the new collection management strategy. This paper reports on the planned radiometric calibration updates to the solar reflective bands of the new Landsat collection.

Designing an End-to-End System for Data Storage, Analysis, and Visualization for an Urban Environmental Observatory

NASA Astrophysics Data System (ADS)

McGuire, M. P.; Welty, C.; Gangopadhyay, A.; Karabatis, G.; Chen, Z.

2006-05-01

The urban environment is formed by complex interactions between natural and human dominated systems, the study of which requires the collection and analysis of very large datasets that span many disciplines. Recent advances in sensor technology and automated data collection have improved the ability to monitor urban environmental systems and are making the idea of an urban environmental observatory a reality. This in turn has created a number of potential challenges in data management and analysis. We present the design of an end-to-end system to store, analyze, and visualize data from a prototype urban environmental observatory based at the Baltimore Ecosystem Study, a National Science Foundation Long Term Ecological Research site (BES LTER). We first present an object-relational design of an operational database to store high resolution spatial datasets as well as data from sensor networks, archived data from the BES LTER, data from external sources such as USGS NWIS, EPA Storet, and metadata. The second component of the system design includes a spatiotemporal data warehouse consisting of a data staging plan and a multidimensional data model designed for the spatiotemporal analysis of monitoring data. The system design also includes applications for multi-resolution exploratory data analysis, multi-resolution data mining, and spatiotemporal visualization based on the spatiotemporal data warehouse. Also the system design includes interfaces with water quality models such as HSPF, SWMM, and SWAT, and applications for real-time sensor network visualization, data discovery, data download, QA/QC, and backup and recovery, all of which are based on the operational database. The system design includes both internet and workstation-based interfaces. Finally we present the design of a laboratory for spatiotemporal analysis and visualization as well as real-time monitoring of the sensor network.

Distributed data collection and supervision based on web sensor

NASA Astrophysics Data System (ADS)

He, Pengju; Dai, Guanzhong; Fu, Lei; Li, Xiangjun

2006-11-01

As a node in Internet/Intranet, web sensor has been promoted in recent years and wildly applied in remote manufactory, workshop measurement and control field. However, the conventional scheme can only support HTTP protocol, and the remote users supervise and control the collected data published by web in the standard browser because of the limited resource of the microprocessor in the sensor; moreover, only one node of data acquirement can be supervised and controlled in one instant therefore the requirement of centralized remote supervision, control and data process can not be satisfied in some fields. In this paper, the centralized remote supervision, control and data process by the web sensor are proposed and implemented by the principle of device driver program. The useless information of the every collected web page embedded in the sensor is filtered and the useful data is transmitted to the real-time database in the workstation, and different filter algorithms are designed for different sensors possessing independent web pages. Every sensor node has its own filter program of web, called "web data collection driver program", the collecting details are shielded, and the supervision, control and configuration software can be implemented by the call of web data collection driver program just like the use of the I/O driver program. The proposed technology can be applied in the data acquirement where relative low real-time is required.

Low-Cost, Distributed Environmental Monitors for Factory Worker Health

PubMed Central

Thomas, Geb W.; Sousan, Sinan; Tatum, Marcus; Liu, Xiaoxing; Zuidema, Christopher; Fitzpatrick, Mitchell; Koehler, Kirsten A.; Peters, Thomas M.

2018-01-01

An integrated network of environmental monitors was developed to continuously measure several airborne hazards in a manufacturing facility. The monitors integrated low-cost sensors to measure particulate matter, carbon monoxide, ozone and nitrogen dioxide, noise, temperature and humidity. The monitors were developed and tested in situ for three months in several overlapping deployments, before a full cohort of 40 was deployed in a heavy vehicle manufacturing facility for a year of data collection. The monitors collect data from each sensor and report them to a central database every 5 min. The work includes an experimental validation of the particle, gas and noise monitors. The R2 for the particle sensor ranges between 0.98 and 0.99 for particle mass densities up to 300 μg/m3. The R2 for the carbon monoxide sensor is 0.99 for concentrations up to 15 ppm. The R2 for the oxidizing gas sensor is 0.98 over the sensitive range from 20 to 180 ppb. The noise monitor is precise within 1% between 65 and 95 dBA. This work demonstrates the capability of distributed monitoring as a means to examine exposure variability in both space and time, building an important preliminary step towards a new approach for workplace hazard monitoring. PMID:29751534

Electric-field sensors for bullet detection systems

NASA Astrophysics Data System (ADS)

Vinci, Stephen; Hull, David; Ghionea, Simon; Ludwig, William; Deligeorges, Socrates; Gudmundsson, Thorkell; Noras, Maciej

2014-06-01

Research and experimental trials have shown that electric-field (E-field) sensors are effective at detecting charged projectiles. E-field sensors can likely complement traditional acoustic sensors, and help provide a more robust and effective solution for bullet detection and tracking. By far, the acoustic sensor is the most prevalent technology in use today for hostile fire defeat systems due to compact size and low cost, yet they come with a number of challenges that include multipath, reverberant environments, false positives and low signal-to-noise. Studies have shown that these systems can benefit from additional sensor modalities such as E-field sensors. However, E-field sensors are a newer technology that is relatively untested beyond basic experimental trials; this technology has not been deployed in any fielded systems. The U.S. Army Research Laboratory (ARL) has conducted live-fire experiments at Aberdeen Proving Grounds (APG) to collect data from E-field sensors. Three types of E-field sensors were included in these experiments: (a) an electric potential gradiometer manufactured by Quasar Federal Systems (QFS), (b) electric charge induction, or "D-dot" sensors designed and built by the Army Research Lab (ARL), and (c) a varactor based E-field sensor prototype designed by University of North Carolina-Charlotte (UNCC). Sensors were placed in strategic locations near the bullet trajectories, and their data were recorded. We analyzed the performance of each E-field sensor type in regard to small-arms bullet detection capability. The most recent experiment in October 2013 allowed demonstration of improved versions of the varactor and D-dot sensor types. Results of new real-time analysis hardware employing detection algorithms were also tested. The algorithms were used to process the raw data streams to determine when bullet detections occurred. Performance among the sensor types and algorithm effectiveness were compared to estimates from acoustics signatures and known ground truth. Results, techniques and configurations that might work best for a given sensor platform are discussed.

Applying Sensor-Based Technology to Improve Construction Safety Management.

PubMed

Zhang, Mingyuan; Cao, Tianzhuo; Zhao, Xuefeng

2017-08-11

Construction sites are dynamic and complicated systems. The movement and interaction of people, goods and energy make construction safety management extremely difficult. Due to the ever-increasing amount of information, traditional construction safety management has operated under difficult circumstances. As an effective way to collect, identify and process information, sensor-based technology is deemed to provide new generation of methods for advancing construction safety management. It makes the real-time construction safety management with high efficiency and accuracy a reality and provides a solid foundation for facilitating its modernization, and informatization. Nowadays, various sensor-based technologies have been adopted for construction safety management, including locating sensor-based technology, vision-based sensing and wireless sensor networks. This paper provides a systematic and comprehensive review of previous studies in this field to acknowledge useful findings, identify the research gaps and point out future research directions.

Applying Sensor-Based Technology to Improve Construction Safety Management

PubMed Central

Zhang, Mingyuan; Cao, Tianzhuo; Zhao, Xuefeng

2017-01-01

Construction sites are dynamic and complicated systems. The movement and interaction of people, goods and energy make construction safety management extremely difficult. Due to the ever-increasing amount of information, traditional construction safety management has operated under difficult circumstances. As an effective way to collect, identify and process information, sensor-based technology is deemed to provide new generation of methods for advancing construction safety management. It makes the real-time construction safety management with high efficiency and accuracy a reality and provides a solid foundation for facilitating its modernization, and informatization. Nowadays, various sensor-based technologies have been adopted for construction safety management, including locating sensor-based technology, vision-based sensing and wireless sensor networks. This paper provides a systematic and comprehensive review of previous studies in this field to acknowledge useful findings, identify the research gaps and point out future research directions. PMID:28800061

Virtual Sensor Web Architecture

NASA Astrophysics Data System (ADS)

Bose, P.; Zimdars, A.; Hurlburt, N.; Doug, S.

2006-12-01

NASA envisions the development of smart sensor webs, intelligent and integrated observation network that harness distributed sensing assets, their associated continuous and complex data sets, and predictive observation processing mechanisms for timely, collaborative hazard mitigation and enhanced science productivity and reliability. This paper presents Virtual Sensor Web Infrastructure for Collaborative Science (VSICS) Architecture for sustained coordination of (numerical and distributed) model-based processing, closed-loop resource allocation, and observation planning. VSICS's key ideas include i) rich descriptions of sensors as services based on semantic markup languages like OWL and SensorML; ii) service-oriented workflow composition and repair for simple and ensemble models; event-driven workflow execution based on event-based and distributed workflow management mechanisms; and iii) development of autonomous model interaction management capabilities providing closed-loop control of collection resources driven by competing targeted observation needs. We present results from initial work on collaborative science processing involving distributed services (COSEC framework) that is being extended to create VSICS.

A Real-Time De-Noising Algorithm for E-Noses in a Wireless Sensor Network

PubMed Central

Qu, Jianfeng; Chai, Yi; Yang, Simon X.

2009-01-01

A wireless e-nose network system is developed for the special purpose of monitoring odorant gases and accurately estimating odor strength in and around livestock farms. This system is to simultaneously acquire accurate odor strength values remotely at various locations, where each node is an e-nose that includes four metal-oxide semiconductor (MOS) gas sensors. A modified Kalman filtering technique is proposed for collecting raw data and de-noising based on the output noise characteristics of those gas sensors. The measurement noise variance is obtained in real time by data analysis using the proposed slip windows average method. The optimal system noise variance of the filter is obtained by using the experiments data. The Kalman filter theory on how to acquire MOS gas sensors data is discussed. Simulation results demonstrate that the proposed method can adjust the Kalman filter parameters and significantly reduce the noise from the gas sensors. PMID:22399946

Using Passive Sensing to Estimate Relative Energy Expenditure for Eldercare Monitoring

PubMed Central

2012-01-01

This paper describes ongoing work in analyzing sensor data logged in the homes of seniors. An estimation of relative energy expenditure is computed using motion density from passive infrared motion sensors mounted in the environment. We introduce a new algorithm for detecting visitors in the home using motion sensor data and a set of fuzzy rules. The visitor algorithm, as well as a previous algorithm for identifying time-away-from-home (TAFH), are used to filter the logged motion sensor data. Thus, the energy expenditure estimate uses data collected only when the resident is home alone. Case studies are included from TigerPlace, an Aging in Place community, to illustrate how the relative energy expenditure estimate can be used to track health conditions over time. PMID:25266777

Calibration, Sensor Model Improvements and Uncertainty Budget of the Airborne Imaging Spectrometer APEX

NASA Astrophysics Data System (ADS)

Hueni, A.

2015-12-01

ESA's Airborne Imaging Spectrometer APEX (Airborne Prism Experiment) was developed under the PRODEX (PROgramme de Développement d'EXpériences scientifiques) program by a Swiss-Belgian consortium and entered its operational phase at the end of 2010 (Schaepman et al., 2015). Work on the sensor model has been carried out extensively within the framework of European Metrology Research Program as part of the Metrology for Earth Observation and Climate (MetEOC and MetEOC2). The focus has been to improve laboratory calibration procedures in order to reduce uncertainties, to establish a laboratory uncertainty budget and to upgrade the sensor model to compensate for sensor specific biases. The updated sensor model relies largely on data collected during dedicated characterisation experiments in the APEX calibration home base but includes airborne data as well where the simulation of environmental conditions in the given laboratory setup was not feasible. The additions to the model deal with artefacts caused by environmental changes and electronic features, namely the impact of ambient air pressure changes on the radiometry in combination with dichroic coatings, influences of external air temperatures and consequently instrument baffle temperatures on the radiometry, and electronic anomalies causing radiometric errors in the four shortwave infrared detector readout blocks. Many of these resolved issues might be expected to be present in other imaging spectrometers to some degree or in some variation. Consequently, the work clearly shows the difficulties of extending a laboratory-based uncertainty to data collected under in-flight conditions. The results are hence not only of interest to the calibration scientist but also to the spectroscopy end user, in particular when commercial sensor systems are used for data collection and relevant sensor characteristic information tends to be sparse. Schaepman, et al, 2015. Advanced radiometry measurements and Earth science applications with the Airborne Prism Experiment (APEX). RSE, 158, 207-219.

Low-Cost Radar Sensors for Personnel Detection and Tracking in Urban Areas

DTIC Science & Technology

2007-01-31

progress on the reserach grant "Low-Cost Radar Sensors for Personnel Detection and Tracking in Urban Areas" during the period 1 May 2005 - 31 December...the DOA of target i with respect to the array boresight is given by: O 1sin-1 -/- fD)--F2(. )(1) where d is the spacing between the elements and A, is...wall. A large database was collected for different parameter spaces including number of humans, types of movements, wall types and radar polarization

Data acquisition for a real time fault monitoring and diagnosis knowledge-based system for space power system

NASA Technical Reports Server (NTRS)

Wilhite, Larry D.; Lee, S. C.; Lollar, Louis F.

1989-01-01

The design and implementation of the real-time data acquisition and processing system employed in the AMPERES project is described, including effective data structures for efficient storage and flexible manipulation of the data by the knowledge-based system (KBS), the interprocess communication mechanism required between the data acquisition system and the KBS, and the appropriate data acquisition protocols for collecting data from the sensors. Sensor data are categorized as critical or noncritical data on the basis of the inherent frequencies of the signals and the diagnostic requirements reflected in their values. The critical data set contains 30 analog values and 42 digital values and is collected every 10 ms. The noncritical data set contains 240 analog values and is collected every second. The collected critical and noncritical data are stored in separate circular buffers. Buffers are created in shared memory to enable other processes, i.e., the fault monitoring and diagnosis process and the user interface process, to freely access the data sets.

Scalable sensor management for automated fusion and tactical reconnaissance

NASA Astrophysics Data System (ADS)

Walls, Thomas J.; Wilson, Michael L.; Partridge, Darin C.; Haws, Jonathan R.; Jensen, Mark D.; Johnson, Troy R.; Petersen, Brad D.; Sullivan, Stephanie W.

2013-05-01

The capabilities of tactical intelligence, surveillance, and reconnaissance (ISR) payloads are expanding from single sensor imagers to integrated systems-of-systems architectures. Increasingly, these systems-of-systems include multiple sensing modalities that can act as force multipliers for the intelligence analyst. Currently, the separate sensing modalities operate largely independent of one another, providing a selection of operating modes but not an integrated intelligence product. We describe here a Sensor Management System (SMS) designed to provide a small, compact processing unit capable of managing multiple collaborative sensor systems on-board an aircraft. Its purpose is to increase sensor cooperation and collaboration to achieve intelligent data collection and exploitation. The SMS architecture is designed to be largely sensor and data agnostic and provide flexible networked access for both data providers and data consumers. It supports pre-planned and ad-hoc missions, with provisions for on-demand tasking and updates from users connected via data links. Management of sensors and user agents takes place over standard network protocols such that any number and combination of sensors and user agents, either on the local network or connected via data link, can register with the SMS at any time during the mission. The SMS provides control over sensor data collection to handle logging and routing of data products to subscribing user agents. It also supports the addition of algorithmic data processing agents for feature/target extraction and provides for subsequent cueing from one sensor to another. The SMS architecture was designed to scale from a small UAV carrying a limited number of payloads to an aircraft carrying a large number of payloads. The SMS system is STANAG 4575 compliant as a removable memory module (RMM) and can act as a vehicle specific module (VSM) to provide STANAG 4586 compliance (level-3 interoperability) to a non-compliant sensor system. The SMS architecture will be described and results from several flight tests and simulations will be shown.

A Uniform Energy Consumption Algorithm for Wireless Sensor and Actuator Networks Based on Dynamic Polling Point Selection

PubMed Central

Li, Shuo; Peng, Jun; Liu, Weirong; Zhu, Zhengfa; Lin, Kuo-Chi

2014-01-01

Recent research has indicated that using the mobility of the actuator in wireless sensor and actuator networks (WSANs) to achieve mobile data collection can greatly increase the sensor network lifetime. However, mobile data collection may result in unacceptable collection delays in the network if the path of the actuator is too long. Because real-time network applications require meeting data collection delay constraints, planning the path of the actuator is a very important issue to balance the prolongation of the network lifetime and the reduction of the data collection delay. In this paper, a multi-hop routing mobile data collection algorithm is proposed based on dynamic polling point selection with delay constraints to address this issue. The algorithm can actively update the selection of the actuator's polling points according to the sensor nodes' residual energies and their locations while also considering the collection delay constraint. It also dynamically constructs the multi-hop routing trees rooted by these polling points to balance the sensor node energy consumption and the extension of the network lifetime. The effectiveness of the algorithm is validated by simulation. PMID:24451455

Study on an agricultural environment monitoring server system using Wireless Sensor Networks.

PubMed

Hwang, Jeonghwan; Shin, Changsun; Yoe, Hyun

2010-01-01

This paper proposes an agricultural environment monitoring server system for monitoring information concerning an outdoors agricultural production environment utilizing Wireless Sensor Network (WSN) technology. The proposed agricultural environment monitoring server system collects environmental and soil information on the outdoors through WSN-based environmental and soil sensors, collects image information through CCTVs, and collects location information using GPS modules. This collected information is converted into a database through the agricultural environment monitoring server consisting of a sensor manager, which manages information collected from the WSN sensors, an image information manager, which manages image information collected from CCTVs, and a GPS manager, which processes location information of the agricultural environment monitoring server system, and provides it to producers. In addition, a solar cell-based power supply is implemented for the server system so that it could be used in agricultural environments with insufficient power infrastructure. This agricultural environment monitoring server system could even monitor the environmental information on the outdoors remotely, and it could be expected that the use of such a system could contribute to increasing crop yields and improving quality in the agricultural field by supporting the decision making of crop producers through analysis of the collected information.

Lightning Instrumentation at KSC

NASA Technical Reports Server (NTRS)

Colon, Jose L.; Eng, D.

2003-01-01

This report summarizes lightning phenomena with a brief explanation of lightning generation and lightning activity as related to KSC. An analysis of the instrumentation used at launching Pads 39 A&B for measurements of lightning effects is included with alternatives and recommendations to improve the protection system and upgrade the actual instrumentation system. An architecture for a new data collection system to replace the present one is also included. A novel architecture to obtain lightning current information from several sensors using only one high speed recording channel while monitoring all sensors to replace the actual manual lightning current recorders and a novel device for the protection system are described.

Bidirectional QoS support for novelty detection applications based on hierarchical wireless sensor network model

NASA Astrophysics Data System (ADS)

Edwards, Mark; Hu, Fei; Kumar, Sunil

2004-10-01

The research on the Novelty Detection System (NDS) (called as VENUS) at the authors' universities has generated exciting results. For example, we can detect an abnormal behavior (such as cars thefts from the parking lot) from a series of video frames based on the cognitively motivated theory of habituation. In this paper, we would like to describe the implementation strategies of lower layer protocols for using large-scale Wireless Sensor Networks (WSN) to NDS with Quality-of-Service (QoS) support. Wireless data collection framework, consisting of small and low-power sensor nodes, provides an alternative mechanism to observe the physical world, by using various types of sensing capabilities that include images (and even videos using Panoptos), sound and basic physical measurements such as temperature. We do not want to lose any 'data query command' packets (in the downstream direction: sink-to-sensors) or have any bit-errors in them since they are so important to the whole sensor network. In the upstream direction (sensors-to-sink), we may tolerate the loss of some sensing data packets. But the 'interested' sensing flow should be assigned a higher priority in terms of multi-hop path choice, network bandwidth allocation, and sensing data packet generation frequency (we hope to generate more sensing data packet for that novel event in the specified network area). The focus of this paper is to investigate MAC-level Quality of Service (QoS) issue in Wireless Sensor Networks (WSN) for Novelty Detection applications. Although QoS has been widely studied in other types of networks including wired Internet, general ad hoc networks and mobile cellular networks, we argue that QoS in WSN has its own characteristics. In wired Internet, the main QoS parameters include delay, jitter and bandwidth. In mobile cellular networks, two most common QoS metrics are: handoff call dropping probability and new call blocking probability. Since the main task of WSN is to detect and report events, the most important QoS parameters should include sensing data packet transmission reliability, lifetime extension degree from sensor sleeping control, event detection latency, congestion reduction level through removal of redundant sensing data. In this paper, we will focus on the following bi-directional QoS topics: (1) Downstream (sink-to-sensor) QoS: Reliable data query command forwarding to particular sensor(s). In other words, we do not want to lose the query command packets; (2) Upstream (sensor-to-sink) QoS: transmission of sensed data with priority control. The more interested data that can help in novelty detection should be transmitted on an optimal path with higher reliability. We propose the use of Differentiated Data Collection. Due to the large-scale nature and resource constraints of typical wireless sensor networks, such as limited energy, small memory (typically RAM < 4K bytes) and short communication range, the above problems become even more challenging. Besides QoS support issue, we will also describe our low-energy Sensing Data Transmission network Architecture. Our research results show the scalability and energy-efficiency of our proposed WSN QoS schemes.

BIOTEX--biosensing textiles for personalised healthcare management.

PubMed

Coyle, Shirley; Lau, King-Tong; Moyna, Niall; O'Gorman, Donal; Diamond, Dermot; Di Francesco, Fabio; Costanzo, Daniele; Salvo, Pietro; Trivella, Maria Giovanna; De Rossi, Danilo Emilio; Taccini, Nicola; Paradiso, Rita; Porchet, Jacque-André; Ridolfi, Andrea; Luprano, Jean; Chuzel, Cyril; Lanier, Thierry; Revol-Cavalier, Frdéric; Schoumacker, Sébastien; Mourier, Véronique; Chartier, Isabelle; Convert, Reynald; De-Moncuit, Henri; Bini, Christina

2010-03-01

Textile-based sensors offer an unobtrusive method of continually monitoring physiological parameters during daily activities. Chemical analysis of body fluids, noninvasively, is a novel and exciting area of personalized wearable healthcare systems. BIOTEX was an EU-funded project that aimed to develop textile sensors to measure physiological parameters and the chemical composition of body fluids, with a particular interest in sweat. A wearable sensing system has been developed that integrates a textile-based fluid handling system for sample collection and transport with a number of sensors including sodium, conductivity, and pH sensors. Sensors for sweat rate, ECG, respiration, and blood oxygenation were also developed. For the first time, it has been possible to monitor a number of physiological parameters together with sweat composition in real time. This has been carried out via a network of wearable sensors distributed around the body of a subject user. This has huge implications for the field of sports and human performance and opens a whole new field of research in the clinical setting.

Evaluation of Candidate Millimeter Wave Sensors for Synthetic Vision

NASA Technical Reports Server (NTRS)

Alexander, Neal T.; Hudson, Brian H.; Echard, Jim D.

1994-01-01

The goal of the Synthetic Vision Technology Demonstration Program was to demonstrate and document the capabilities of current technologies to achieve safe aircraft landing, take off, and ground operation in very low visibility conditions. Two of the major thrusts of the program were (1) sensor evaluation in measured weather conditions on a tower overlooking an unused airfield and (2) flight testing of sensor and pilot performance via a prototype system. The presentation first briefly addresses the overall technology thrusts and goals of the program and provides a summary of MMW sensor tower-test and flight-test data collection efforts. Data analysis and calibration procedures for both the tower tests and flight tests are presented. The remainder of the presentation addresses the MMW sensor flight-test evaluation results, including the processing approach for determination of various performance metrics (e.g., contrast, sharpness, and variability). The variation of the very important contrast metric in adverse weather conditions is described. Design trade-off considerations for Synthetic Vision MMW sensors are presented.

On the importance of telemetric temperature sensor location during intraperitoneal implantation in rats.

PubMed

Chapon, P A; Bulla, J; Gauthier, A; Moussay, S

2014-04-01

This study aims to assess the thermal homogeneity of the intraperitoneal (IP) cavity and the relevance of using a fixed telemetric temperature sensor at a given location in studying rodents. Ten rats were intraperitoneally implanted with three Jonah® capsules each; after assessing the accuracy and reliability of the sensors. Two capsules were attached, one to the right iliac fossa (RIF) and the other to the left hypochondrium (LH), and another was placed between the intestines but not attached (Free). In the ex vivo condition, the differences between sensors and reference values remained in the range of ±0.1. In the in vivo condition, each sensor enabled the observation of temperature patterns. However, sensor location affected mean and median temperature values while the rats were moving freely. Indeed, temperature data collected in the LH were 0.1 significantly higher than those collected in the RIF and temperature data collected in the LH were 0.11 significantly higher than those collected with the Free capsules. In in vivo conditions, intra-sensor variability of temperature data was not affected by sensor location. Taking into account sensor accuracy, similar intra-sensor variability, and mean differences observed between the three locations, the impact of sensor location within the IP cavity could be considered negligible. In in vivo conditions, temperature differences between locations regularly exceeded ±0.2 and reached up to 2.5. These extreme values could be explained by behavioral factors such as food or water intake. Finally, considering the good thermal homogeneity of the IP cavity and possible adverse consequences of sensor attachment, it seems better to let sensors range free within the cavity.

Design of QoS-Aware Multi-Level MAC-Layer for Wireless Body Area Network.

PubMed

Hu, Long; Zhang, Yin; Feng, Dakui; Hassan, Mohammad Mehedi; Alelaiwi, Abdulhameed; Alamri, Atif

2015-12-01

With the advances in wearable computing and various wireless technologies, there is an increasing trend to outsource body signals from wireless body area network (WBAN) to outside world including cyber space, healthcare big data clouds, etc. Since the environmental and physiological data collected by multimodal sensors have different importance, the provisioning of quality of service (QoS) for the sensory data in WBAN is a critical issue. This paper proposes multiple level-based QoS design at WBAN media access control layer in terms of user level, data level and time level. In the proposed QoS provisioning scheme, different users have different priorities, various sensory data collected by different sensor nodes have different importance, while data priority for the same sensor node varies over time. The experimental results show that the proposed multi-level based QoS provisioning solution in WBAN yields better performance for meeting QoS requirements of personalized healthcare applications while achieving energy saving.

Ionospheric Variability as Observed by the CTECS and CORISS Sensors

NASA Astrophysics Data System (ADS)

Bishop, R. L.; Redding, M.; Straus, P. R.

2013-12-01

The Compact Total Electron Content Sensor (CTECS) is a GPS radio occultation instrument designed for cubesat platforms that utilizes a COTS receiver, modified firmware, and a custom designed antenna. CTECS was placed on the Pico Satellite Solar Cell Testbed 2 (PSSC2) nanosat that was installed on the Space Shuttle Atlantis (STS-135). PSSC2 was successfully released from the shuttle on 20 July 2011 near 380 km altitude. Because of attitude control and power issues, only 13.5 hours of data was collected during its approximately 5-month mission life. The C/NOFS Occultation Receiver for Ionospheric Sensing and Specification (CORISS) GPS radio occultation sensor on the C/NOFS satellite has collected data nearly continuously from May 2008 to June 2013. Both CTECS and CORISS obtain Total Electron Content and scintillation data. In this presentation the CTECS data is first validated against CORISS and available ground-based observations. Then combining the CTECS and CORISS data, low and mid latitude ionospheric variability including scintillation events is presented.

The NASA Smart Probe Project for real-time multiple microsensor tissue recognition

NASA Technical Reports Server (NTRS)

Andrews, Russell J.; Mah, Robert W.

2003-01-01

BACKGROUND: Remote surgery requires automated sensors, effectors and sensor-effector communication. The NASA Smart Probe Project has focused on the sensor aspect. METHODS: The NASA Smart Probe uses neural networks and data from multiple microsensors for a unique tissue signature in real time. Animal and human trials use several probe configurations: (1) 8-microsensor probe (2.5 mm in diameter) for rodent studies (normal and subcutaneous mammary tumor tissues), and (2) 21-gauge needle probe with 3 spectroscopic fibers and an impedance microelectrode for breast cancer diagnosis in humans. Multisensor data are collected in real time (update 100 times/s) using PCs. RESULTS: Human data (collected by NASA licensee BioLuminate) from 15 women undergoing breast biopsy distinguished normal tissue from both benign tumors and breast carcinoma. Tumor margins and necrosis are rapidly detected. CONCLUSION: Real-time tissue identification is achievable. Potential applications, including probes incorporating nanoelectrode arrays, are presented. Copyright 2003 S. Karger AG, Basel.

SensorKit: An End-to-End Solution for Environmental Sensor Networking

NASA Astrophysics Data System (ADS)

Silva, F.; Graham, E.; Deschon, A.; Lam, Y.; Goldman, J.; Wroclawski, J.; Kaiser, W.; Benzel, T.

2008-12-01

Modern day sensor network technology has shown great promise to transform environmental data collection. However, despite the promise, these systems have remained the purview of the engineers and computer scientists who design them rather than a useful tool for the environmental scientists who need them. SensorKit is conceived of as a way to make wireless sensor networks accessible to The People: it is an advanced, powerful tool for sensor data collection that does not require advanced technological know-how. We are aiming to make wireless sensor networks for environmental science as simple as setting up a standard home computer network by providing simple, tested configurations of commercially-available hardware, free and easy-to-use software, and step-by-step tutorials. We designed and built SensorKit using a simplicity-through-sophistication approach, supplying users a powerful sensor to database end-to-end system with a simple and intuitive user interface. Our objective in building SensorKit was to make the prospect of using environmental sensor networks as simple as possible. We built SensorKit from off the shelf hardware components, using the Compact RIO platform from National Instruments for data acquisition due to its modular architecture and flexibility to support a large number of sensor types. In SensorKit, we support various types of analog, digital and networked sensors. Our modular software architecture allows us to abstract sensor details and provide users a common way to acquire data and to command different types of sensors. SensorKit is built on top of the Sensor Processing and Acquisition Network (SPAN), a modular framework for acquiring data in the field, moving it reliably to the scientist institution, and storing it in an easily-accessible database. SPAN allows real-time access to the data in the field by providing various options for long haul communication, such as cellular and satellite links. Our system also features reliable data storage and transmission, using a custody transfer mechanism that ensures data is retained until successful delivery to the scientist can be confirmed. The ability for the scientist to communicate in real-time with the sensor network in the field enables remote sensor reconfiguration and system health and status monitoring. We use a spiral approach of design, test, deploy and revise, and, by going to the field frequently and getting feedback from field scientists, we have been able to include additional functionality that is useful to the scientist while ensuring SensorKit remains intuitive to operate. Users can configure, control, and monitor SensorKit using a number of tools we have developed. An intuitive user interface running on a desktop or laptop allows scientists to setup the system, add and configure sensors, and specify when and how the data will be collected. We also have a mobile version of our interface that runs on a PDA and lets scientists calibrate sensors and "tune" the system while in the field, allowing for data validation before leaving the field and returning to the research lab. SensorKit also features SensorBase, an intuitive user interface built on top of a standard SQL database, which allows scientists to store and share their data with other researchers. SensorKit has been used for diverse scientific applications and deployed throughout the world: from studying mercury cycling in rice paddies in China, to ecological research in the neotropical rainforests of Costa Rica, to monitoring the contamination of salt lakes in Argentina.

On-demand information retrieval in sensor networks with localised query and energy-balanced data collection.

PubMed

Teng, Rui; Zhang, Bing

2011-01-01

On-demand information retrieval enables users to query and collect up-to-date sensing information from sensor nodes. Since high energy efficiency is required in a sensor network, it is desirable to disseminate query messages with small traffic overhead and to collect sensing data with low energy consumption. However, on-demand query messages are generally forwarded to sensor nodes in network-wide broadcasts, which create large traffic overhead. In addition, since on-demand information retrieval may introduce intermittent and spatial data collections, the construction and maintenance of conventional aggregation structures such as clusters and chains will be at high cost. In this paper, we propose an on-demand information retrieval approach that exploits the name resolution of data queries according to the attribute and location of each sensor node. The proposed approach localises each query dissemination and enable localised data collection with maximised aggregation. To illustrate the effectiveness of the proposed approach, an analytical model that describes the criteria of sink proxy selection is provided. The evaluation results reveal that the proposed scheme significantly reduces energy consumption and improves the balance of energy consumption among sensor nodes by alleviating heavy traffic near the sink.

Towards a cross-platform software framework to support end-to-end hydrometeorological sensor network deployment

NASA Astrophysics Data System (ADS)

Celicourt, P.; Sam, R.; Piasecki, M.

2016-12-01

Global phenomena such as climate change and large scale environmental degradation require the collection of accurate environmental data at detailed spatial and temporal scales from which knowledge and actionable insights can be derived using data science methods. Despite significant advances in sensor network technologies, sensors and sensor network deployment remains a labor-intensive, time consuming, cumbersome and expensive task. These factors demonstrate why environmental data collection remains a challenge especially in developing countries where technical infrastructure, expertise and pecuniary resources are scarce. In addition, they also demonstrate the reason why dense and long-term environmental data collection has been historically quite difficult. Moreover, hydrometeorological data collection efforts usually overlook the (critically important) inclusion of a standards-based system for storing, managing, organizing, indexing, documenting and sharing sensor data. We are developing a cross-platform software framework using the Python programming language that will allow us to develop a low cost end-to-end (from sensor to publication) system for hydrometeorological conditions monitoring. The software framework contains provision for sensor, sensor platforms, calibration and network protocols description, sensor programming, data storage, data publication and visualization and more importantly data retrieval in a desired unit system. It is being tested on the Raspberry Pi microcomputer as end node and a laptop PC as the base station in a wireless setting.

A spatiotemporal analysis of hydrological patterns based on a wireless sensor network system

NASA Astrophysics Data System (ADS)

Plaza, F.; Slater, T. A.; Zhong, X.; Li, Y.; Liang, Y.; Liang, X.

2017-12-01

Understanding complicated spatiotemporal patterns of eco-hydrological variables at a small scale plays a profound role in improving predictability of high resolution distributed hydrological models. However, accurate and continuous monitoring of these complex patterns has become one of the main challenges in the environmental sciences. Wireless sensor networks (WSNs) have emerged as one of the most widespread potential solutions to achieve this. This study presents a spatiotemporal analysis of hydrological patterns (e.g., soil moisture, soil water potential, soil temperature and transpiration) based on observational data collected from a dense multi-hop wireless sensor network (WSN) in a steep-forested testbed located in Southwestern Pennsylvania, USA. At this WSN testbed with an approximate area of 3000 m2, environmental variables are collected from over 240 sensors that are connected to more than 100 heterogeneous motes. The sensors include the soil moisture of EC-5, soil temperature and soil water potential of MPS-1 and MPS-2, and sap flow sensors constructed in house. The motes consist of MICAz, IRIS and TelosB. In addition, several data loggers have been installed along the site to provide a comparative reference to the WSN measurements for the purpose of checking the WSN data quality. The edaphic properties monitored by the WSN sensors show strong agreement with the data logger measurements. Moreover, sap flow measurements, scaled to tree stand transpiration, are found to be reasonable. This study also investigates the feasibility and roles that these sensor measurements play in improving the performance of high-resolution distributed hydrological models. In particular, we explore this using a modified version of the Distributed Hydrological Soil Vegetation Model (DHSVM).

Ground-based sensors for the SR-71 sonic boom propagation experiment

NASA Technical Reports Server (NTRS)

Norris, Stephen R.; Haering, Edward A., Jr.; Murray, James E.

1995-01-01

This paper describes ground-level measurements of sonic boom signatures made as part of the SR-71 sonic boom propagation experiment recently completed at NASA Dryden Flight Research Center, Edwards, California. Ground level measurements were the final stage of this experiment which also included airborne measurements at near and intermediate distances from an SR-71 research aircraft. Three types of sensors were deployed to three station locations near the aircraft ground track. Pressure data were collected for flight conditions from Mach 1.25 to Mach 1.60 at altitudes from 30,000 to 48,000 ft. Ground-level measurement techniques, comparisons of data sets from different ground sensors, and sensor system strengths and weaknesses are discussed. The well-known N-wave structure dominated the sonic boom signatures generated by the SR-71 aircraft at most of these conditions. Variations in boom shape caused by atmospheric turbulence, focusing effects, or both were observed for several flights. Peak pressure and boom event duration showed some dependence on aircraft gross weight. The sonic boom signatures collected in this experiment are being compiled in a data base for distribution in support of the High Speed Research Program.

a Preliminary Investigation on Comparison and Transformation of SENTINEL-2 MSI and Landsat 8 Oli

NASA Astrophysics Data System (ADS)

Chen, F.; Lou, S.; Fan, Q.; Li, J.; Wang, C.; Claverie, M.

2018-05-01

A PRELIMINARY INVESTIGATION ON COMPARISON AND TRANSFORMATION OF SENTINEL-2 MSI AND LANDSAT 8 OLI Timely and accurate earth observation with short revisit interval is usually necessary, especially for emergency response. Currently, several new generation sensors provided with similar channel characteristics have been operated onboard different satellite platforms, including Sentinel-2 and Landsat 8. Joint use of the observations by different sensors offers an opportunity to meet the demands for emergency requirements. For example, through the combination of Landsat and Sentinel-2 data, the land can be observed every 2-3 days at medium spatial resolution. However, differences are expected in radiometric values (e.g., channel reflectance) of the corresponding channels between two sensors. Spectral response function (SRF) is taken as an important aspect of sensor settings. Accordingly, between-sensor differences due to SRFs variation need to be quantified and compensated. The comparison of SRFs shows difference (more or less) in channel settings between Sentinel-2 Multi-Spectral Instrument (MSI) and Landsat 8 Operational Land Imager (OLI). Effect of the difference in SRF on corresponding values between MSI and OLI was investigated, mainly in terms of channel reflectance and several derived spectral indices. Spectra samples from ASTER Spectral Library Version 2.0 and Hyperion data archives were used in obtaining channel reflectance simulation of MSI and OLI. Preliminary results show that MSI and OLI are well comparable in several channels with small relative discrepancy (< 5 %), including the Costal Aerosol channel, a NIR (855-875 nm) channel, the SWIR channels, and the Cirrus channel. Meanwhile, for channels covering Blue, Green, Red, and NIR (785-900 nm), the between-sensor differences are significantly presented. Compared with the difference in reflectance of each individual channel, the difference in derived spectral index is more significant. In addition, effectiveness of linear transformation model is not ensured when the target belongs to another spectra collection. If an improper transformation model is selected, the between-sensor discrepancy will even largely increase. In conclusion, improvement in between-sensor consistency is possibly a challenge, through linear transformation based on model(s) generated from other spectra collections.

Using a Novel Optical Sensor to Characterize Methane Ebullition Processes

NASA Astrophysics Data System (ADS)

Delwiche, K.; Hemond, H.; Senft-Grupp, S.

2015-12-01

We have built a novel bubble size sensor that is rugged, economical to build, and capable of accurately measuring methane bubble sizes in aquatic environments over long deployment periods. Accurate knowledge of methane bubble size is important to calculating atmospheric methane emissions from in-land waters. By routing bubbles past pairs of optical detectors, the sensor accurately measures bubbles sizes for bubbles between 0.01 mL and 1 mL, with slightly reduced accuracy for bubbles from 1 mL to 1.5 mL. The sensor can handle flow rates up to approximately 3 bubbles per second. Optional sensor attachments include a gas collection chamber for methane sampling and volume verification, and a detachable extension funnel to customize the quantity of intercepted bubbles. Additional features include a data-cable running from the deployed sensor to a custom surface buoy, allowing us to download data without disturbing on-going bubble measurements. We have successfully deployed numerous sensors in Upper Mystic Lake at depths down to 18 m, 1 m above the sediment. The resulting data gives us bubble size distributions and the precise timing of bubbling events over a period of several months. In addition to allowing us to characterize typical bubble size distributions, this data allows us to draw important conclusions about temporal variations in bubble sizes, as well as bubble dissolution rates within the water column.

Physiological sensor signals classification for healthcare using sensor data fusion and case-based reasoning.

PubMed

Begum, Shahina; Barua, Shaibal; Ahmed, Mobyen Uddin

2014-07-03

Today, clinicians often do diagnosis and classification of diseases based on information collected from several physiological sensor signals. However, sensor signal could easily be vulnerable to uncertain noises or interferences and due to large individual variations sensitivity to different physiological sensors could also vary. Therefore, multiple sensor signal fusion is valuable to provide more robust and reliable decision. This paper demonstrates a physiological sensor signal classification approach using sensor signal fusion and case-based reasoning. The proposed approach has been evaluated to classify Stressed or Relaxed individuals using sensor data fusion. Physiological sensor signals i.e., Heart Rate (HR), Finger Temperature (FT), Respiration Rate (RR), Carbon dioxide (CO2) and Oxygen Saturation (SpO2) are collected during the data collection phase. Here, sensor fusion has been done in two different ways: (i) decision-level fusion using features extracted through traditional approaches; and (ii) data-level fusion using features extracted by means of Multivariate Multiscale Entropy (MMSE). Case-Based Reasoning (CBR) is applied for the classification of the signals. The experimental result shows that the proposed system could classify Stressed or Relaxed individual 87.5% accurately compare to an expert in the domain. So, it shows promising result in the psychophysiological domain and could be possible to adapt this approach to other relevant healthcare systems.

Design and initial testing of a piezoelectric sensor to quantify aeolian sand transport

NASA Astrophysics Data System (ADS)

Raygosa-Barahona, Ruben; Ruiz-Martinez, Gabriel; Mariño-Tapia, Ismael; Heyser-Ojeda, Emilio

2016-09-01

This paper describes a sensor for measuring the mass flux of aeolian sand transport based on a low-cost piezo-electric transducer. The device is able to measure time series of aeolian sand transport. Maximum fluxes of 27 mg per second can be achieved. The design includes a sand trap, an electronic amplifier circuit and an embedded system for data collection. A field test was performed, where the basis for signal interpretation and the corresponding measurements of aeolian sand transport are presented. The sensor successfully measures fluxes driven by sea breezes of 10 ms-1, showing the importance of this process for dune-building in the region.

A data management and publication workflow for a large-scale, heterogeneous sensor network.

PubMed

Jones, Amber Spackman; Horsburgh, Jeffery S; Reeder, Stephanie L; Ramírez, Maurier; Caraballo, Juan

2015-06-01

It is common for hydrology researchers to collect data using in situ sensors at high frequencies, for extended durations, and with spatial distributions that produce data volumes requiring infrastructure for data storage, management, and sharing. The availability and utility of these data in addressing scientific questions related to water availability, water quality, and natural disasters relies on effective cyberinfrastructure that facilitates transformation of raw sensor data into usable data products. It also depends on the ability of researchers to share and access the data in useable formats. In this paper, we describe a data management and publication workflow and software tools for research groups and sites conducting long-term monitoring using in situ sensors. Functionality includes the ability to track monitoring equipment inventory and events related to field maintenance. Linking this information to the observational data is imperative in ensuring the quality of sensor-based data products. We present these tools in the context of a case study for the innovative Urban Transitions and Aridregion Hydrosustainability (iUTAH) sensor network. The iUTAH monitoring network includes sensors at aquatic and terrestrial sites for continuous monitoring of common meteorological variables, snow accumulation and melt, soil moisture, surface water flow, and surface water quality. We present the overall workflow we have developed for effectively transferring data from field monitoring sites to ultimate end-users and describe the software tools we have deployed for storing, managing, and sharing the sensor data. These tools are all open source and available for others to use.

Got Point Clouds: Characterizing Canopy Structure With Active and Passive Sensors

NASA Astrophysics Data System (ADS)

Popescu, S. C.; Malambo, L.; Sheridan, R.; Putman, E.; Murray, S.; Rooney, W.; Rajan, N.

2016-12-01

Unmanned Aerial Systems (UAS) provide the means to acquire highly customized aerial data at local scale with a multitude of sensors. UAS allow us to obtain affordably repeated observations of canopy structure for agricultural and natural resources applications by using passive optical sensors, such as cameras and photogrammetric techniques, and active sensors, such as lidar (Light Detection and Ranging). The objectives of this presentation are to: (1) offer a brief overview of UAS used for agriculture and natural resources studies, (2) describe experiences in conducting agriculture phenotyping and forest vegetation measurements, and (3) give details on the methodology developed for image and lidar data processing for characterizing the three dimensional structure of plant canopies. The UAS types used for this purpose included rotary platforms, such as quadcopters, hexacopters, and octocopters, with a payload capacity of up to 19 lbs. The sensors that collected data over two crop seasons include multispectral cameras in the visible color spectrum and near infrared, and UAS-lidar. For ground reference data we used terrestrial lidar scanners and field measurements. Results comparing UAS and terrestrial measurements show high correlation and open new areas of scientific investigation of crop canopies previously not possible with affordable techniques.

Field Demonstration of Multi-Sensor Technology for Condition Assessment of Wastewater Collection Systems (Abstract)

EPA Science Inventory

The purpose of the field demonstration program is to gather technically reliable cost and performance information on selected condition assessment technologies under defined field conditions. The selected technologies include zoom camera, focused electrode leak location (FELL), ...

Calibration of automatic performance measures - speed and volume data: volume 2, evaluation of the accuracy of approach volume counts and speeds collected by microwave sensors.

DOT National Transportation Integrated Search

2016-05-01

This study evaluated the accuracy of approach volumes and free flow approach speeds collected by the Wavetronix : SmartSensor Advance sensor for the Signal Performance Metrics system of the Utah Department of Transportation (UDOT), : using the field ...

Effective Sensor Selection and Data Anomaly Detection for Condition Monitoring of Aircraft Engines

PubMed Central

Liu, Liansheng; Liu, Datong; Zhang, Yujie; Peng, Yu

2016-01-01

In a complex system, condition monitoring (CM) can collect the system working status. The condition is mainly sensed by the pre-deployed sensors in/on the system. Most existing works study how to utilize the condition information to predict the upcoming anomalies, faults, or failures. There is also some research which focuses on the faults or anomalies of the sensing element (i.e., sensor) to enhance the system reliability. However, existing approaches ignore the correlation between sensor selecting strategy and data anomaly detection, which can also improve the system reliability. To address this issue, we study a new scheme which includes sensor selection strategy and data anomaly detection by utilizing information theory and Gaussian Process Regression (GPR). The sensors that are more appropriate for the system CM are first selected. Then, mutual information is utilized to weight the correlation among different sensors. The anomaly detection is carried out by using the correlation of sensor data. The sensor data sets that are utilized to carry out the evaluation are provided by National Aeronautics and Space Administration (NASA) Ames Research Center and have been used as Prognostics and Health Management (PHM) challenge data in 2008. By comparing the two different sensor selection strategies, the effectiveness of selection method on data anomaly detection is proved. PMID:27136561

Effective Sensor Selection and Data Anomaly Detection for Condition Monitoring of Aircraft Engines.

PubMed

Liu, Liansheng; Liu, Datong; Zhang, Yujie; Peng, Yu

2016-04-29

In a complex system, condition monitoring (CM) can collect the system working status. The condition is mainly sensed by the pre-deployed sensors in/on the system. Most existing works study how to utilize the condition information to predict the upcoming anomalies, faults, or failures. There is also some research which focuses on the faults or anomalies of the sensing element (i.e., sensor) to enhance the system reliability. However, existing approaches ignore the correlation between sensor selecting strategy and data anomaly detection, which can also improve the system reliability. To address this issue, we study a new scheme which includes sensor selection strategy and data anomaly detection by utilizing information theory and Gaussian Process Regression (GPR). The sensors that are more appropriate for the system CM are first selected. Then, mutual information is utilized to weight the correlation among different sensors. The anomaly detection is carried out by using the correlation of sensor data. The sensor data sets that are utilized to carry out the evaluation are provided by National Aeronautics and Space Administration (NASA) Ames Research Center and have been used as Prognostics and Health Management (PHM) challenge data in 2008. By comparing the two different sensor selection strategies, the effectiveness of selection method on data anomaly detection is proved.

DECAF - Density Estimation for Cetaceans from Passive Acoustic Fixed Sensors

DTIC Science & Technology

2007-01-01

including the time for reviewing instructions, searching existing data sources, gathering and maintaining the data needed, and completing and reviewing...penalty for failing to comply with a collection of information if it does not display a currently valid OMB control number. 1. REPORT DATE 2007 2. REPORT...as far as possible to leverage data that have already been collected, and classification and localization methods that have already been developed

Balancing Science Objectives and Operational Constraints: A Mission Planner's Challenge

NASA Technical Reports Server (NTRS)

Weldy, Michelle

1996-01-01

The Air Force minute sensor technology integration (MSTI-3) satellite's primary mission is to characterize Earth's atmospheric background clutter. MSTI-3 will use three cameras for data collection, a mid-wave infrared imager, a short wave infrared imager, and a visible imaging spectrometer. Mission science objectives call for the collection of over 2 million images within the one year mission life. In addition, operational constraints limit camera usage to four operations of twenty minutes per day, with no more than 10,000 data and calibrating images collected per day. To balance the operational constraints and science objectives, the mission planning team has designed a planning process to e event schedules and sensor operation timelines. Each set of constraints, including spacecraft performance capabilities, the camera filters, the geographical regions, and the spacecraft-Sun-Earth geometries of interest, and remote tracking station deconflictions has been accounted for in this methodology. To aid in this process, the mission planning team is building a series of tools from commercial off-the-shelf software. These include the mission manifest which builds a daily schedule of events, and the MSTI Scene Simulator which helps build geometrically correct scans. These tools provide an efficient, responsive, and highly flexible architecture that maximizes data collection while minimizing mission planning time.

Meteorological data for selected sites along the Colorado River Corridor, Arizona, 2011-13

USGS Publications Warehouse

Caster, Joshua J.; Dealy, Timothy P.; Andrews, Timothy; Fairley, Helen C.; East, Amy E.; Sankey, Joel B.

2014-01-01

This report presents data from 14 automated weather stations collected as part of an ongoing monitoring program within the Grand Canyon National Park and Glen Canyon Recreation Area along the Colorado River Corridor in Arizona. Weather data presented in this document include precipitation, wind speed, maximum wind gusts, wind direction, barometric pressure, relative humidity, and air temperature collected by the Grand Canyon Monitoring and Research Center at 4-minute intervals between January 1, 2011, and December 31, 2013, using automated weather stations consisting of a data logger and a weather transmitter equipped with a piezoelectric sensor, ultrasonic transducers, and capacitive thermal and pressure sensors. Data collection was discontinuous because of station additions, station removals, changes in permits, and equipment failure. A large volume of data was collected for each station. These data are part of a larger research effort focused on physical processes affecting landscapes and archaeological-site stability in the Colorado River Corridor—both natural processes (including meteorological events) and those related to the Glen Canyon Dam operations. Meteorological conditions during the study interval were warmer and drier than is typical, due to ongoing drought conditions during the time period studied. The El Niño/Southern Oscillation was primarily in a neutral state during the reporting period.

Emergency Response Fire-Imaging UAS Missions over the Southern California Wildfire Disaster

NASA Technical Reports Server (NTRS)

DelFrate, John H.

2008-01-01

Objectives include: Demonstrate capabilities of UAS to overfly and collect sensor data on widespread fires throughout Western US. Demonstrate long-endurance mission capabilities (20-hours+). Image multiple fires (greater than 4 fires per mission), to showcase extendable mission configuration and ability to either linger over key fires or station over disparate regional fires. Demonstrate new UAV-compatible, autonomous sensor for improved thermal characterization of fires. Provide automated, on-board, terrain and geo-rectified sensor imagery over OTH satcom links to national fire personnel and Incident commanders. Deliver real-time imagery (within 10-minutes of acquisition). Demonstrate capabilities of OTS technologies (GoogleEarth) to serve and display mission-critical sensor data, coincident with other pertinent data elements to facilitate information processing (WX data, ground asset data, other satellite data, R/T video, flight track info, etc).

Emergency Response Fire-Imaging UAS Missions over the Southern California Wildfire Disaster

NASA Technical Reports Server (NTRS)

Cobleigh, Brent R.

2007-01-01

Objectives include: Demonstrate capabilities of UAS to overfly and collect sensor data on widespread fires throughout Western US. Demonstrate long-endurance mission capabilities (20-hours+). Image multiple fires (greater than 4 fires per mission), to showcase extendable mission configuration and ability to either linger over key fires or station over disparate regional fires. Demonstrate new UAV-compatible, autonomous sensor for improved thermal characterization of fires. Provide automated, on-board, terrain and geo-rectified sensor imagery over OTH satcom links to national fire personnel and Incident commanders. Deliver real-time imagery (within 10-minutes of acquisition). Demonstrate capabilities of OTS technologies (GoogleEarth) to serve and display mission-critical sensor data, coincident with other pertinent data elements to facilitate information processing (WX data, ground asset data, other satellite data, R/T video, flight track info, etc).

Tablet PC Enabled Body Sensor System for Rural Telehealth Applications

PubMed Central

Panicker, Nitha V.; Kumar, A. Sukesh

2016-01-01

Telehealth systems benefit from the rapid growth of mobile communication technology for measuring physiological signals. Development and validation of a tablet PC enabled noninvasive body sensor system for rural telehealth application are discussed in this paper. This system includes real time continuous collection of physiological parameters (blood pressure, pulse rate, and temperature) and fall detection of a patient with the help of a body sensor unit and wireless transmission of the acquired information to a tablet PC handled by the medical staff in a Primary Health Center (PHC). Abnormal conditions are automatically identified and alert messages are given to the medical officer in real time. Clinical validation is performed in a real environment and found to be successful. Bland-Altman analysis is carried out to validate the wrist blood pressure sensor used. The system works well for all measurements. PMID:26884757

Accuracy of different sensors for the estimation of pollutant concentrations (total suspended solids, total and dissolved chemical oxygen demand) in wastewater and stormwater.

PubMed

Lepot, Mathieu; Aubin, Jean-Baptiste; Bertrand-Krajewski, Jean-Luc

2013-01-01

Many field investigations have used continuous sensors (turbidimeters and/or ultraviolet (UV)-visible spectrophotometers) to estimate with a short time step pollutant concentrations in sewer systems. Few, if any, publications compare the performance of various sensors for the same set of samples. Different surrogate sensors (turbidity sensors, UV-visible spectrophotometer, pH meter, conductivity meter and microwave sensor) were tested to link concentrations of total suspended solids (TSS), total and dissolved chemical oxygen demand (COD), and sensors' outputs. In the combined sewer at the inlet of a wastewater treatment plant, 94 samples were collected during dry weather, 44 samples were collected during wet weather, and 165 samples were collected under both dry and wet weather conditions. From these samples, triplicate standard laboratory analyses were performed and corresponding sensors outputs were recorded. Two outlier detection methods were developed, based, respectively, on the Mahalanobis and Euclidean distances. Several hundred regression models were tested, and the best ones (according to the root mean square error criterion) are presented in order of decreasing performance. No sensor appears as the best one for all three investigated pollutants.

Multi-sensor Cloud Retrieval Simulator and Remote Sensing from Model Parameters . Pt. 1; Synthetic Sensor Radiance Formulation; [Synthetic Sensor Radiance Formulation

NASA Technical Reports Server (NTRS)

Wind, G.; DaSilva, A. M.; Norris, P. M.; Platnick, S.

2013-01-01

In this paper we describe a general procedure for calculating synthetic sensor radiances from variable output from a global atmospheric forecast model. In order to take proper account of the discrepancies between model resolution and sensor footprint, the algorithm takes explicit account of the model subgrid variability, in particular its description of the probability density function of total water (vapor and cloud condensate.) The simulated sensor radiances are then substituted into an operational remote sensing algorithm processing chain to produce a variety of remote sensing products that would normally be produced from actual sensor output. This output can then be used for a wide variety of purposes such as model parameter verification, remote sensing algorithm validation, testing of new retrieval methods and future sensor studies.We show a specific implementation using the GEOS-5 model, the MODIS instrument and the MODIS Adaptive Processing System (MODAPS) Data Collection 5.1 operational remote sensing cloud algorithm processing chain (including the cloud mask, cloud top properties and cloud optical and microphysical properties products). We focus on clouds because they are very important to model development and improvement.

Real-Time Classification of Patients with Balance Disorders vs. Normal Subjects Using a Low-Cost Small Wireless Wearable Gait Sensor.

PubMed

Nukala, Bhargava Teja; Nakano, Taro; Rodriguez, Amanda; Tsay, Jerry; Lopez, Jerry; Nguyen, Tam Q; Zupancic, Steven; Lie, Donald Y C

2016-11-29

Gait analysis using wearable wireless sensors can be an economical, convenient and effective way to provide diagnostic and clinical information for various health-related issues. In this work, our custom designed low-cost wireless gait analysis sensor that contains a basic inertial measurement unit (IMU) was used to collect the gait data for four patients diagnosed with balance disorders and additionally three normal subjects, each performing the Dynamic Gait Index (DGI) tests while wearing the custom wireless gait analysis sensor (WGAS). The small WGAS includes a tri-axial accelerometer integrated circuit (IC), two gyroscopes ICs and a Texas Instruments (TI) MSP430 microcontroller and is worn by each subject at the T4 position during the DGI tests. The raw gait data are wirelessly transmitted from the WGAS to a near-by PC for real-time gait data collection and analysis. In order to perform successful classification of patients vs. normal subjects, we used several different classification algorithms, such as the back propagation artificial neural network (BP-ANN), support vector machine (SVM), k -nearest neighbors (KNN) and binary decision trees (BDT), based on features extracted from the raw gait data of the gyroscopes and accelerometers. When the range was used as the input feature, the overall classification accuracy obtained is 100% with BP-ANN, 98% with SVM, 96% with KNN and 94% using BDT. Similar high classification accuracy results were also achieved when the standard deviation or other values were used as input features to these classifiers. These results show that gait data collected from our very low-cost wearable wireless gait sensor can effectively differentiate patients with balance disorders from normal subjects in real time using various classifiers, the success of which may eventually lead to accurate and objective diagnosis of abnormal human gaits and their underlying etiologies in the future, as more patient data are being collected.

Tropospheric Airborne Meteorological Data Reporting (TAMDAR) Sensor Development

NASA Technical Reports Server (NTRS)

Daniels, Taumi S.; Tsoucalas, George; Anderson, Mark; Mulally, Daniel; Moninger, William; Mamrosh, Richard

2004-01-01

One of the recommendations of the National Aviation Weather Program Council was to expand and institutionalize the generation, dissemination, and use of automated pilot reports (PIREPS) to the full spectrum of the aviation community, including general aviation. In response to this and other similar recommendations, NASA initiated cooperative research into the development of an electronic pilot reporting capability (Daniels 2002). The ultimate goal is to develop a small low-cost sensor, collect useful meteorological observations below 25,000 ft., downlink the data in near real time, and use the data to improve weather forecasts. Primary users of the data include pilots, who are one targeted audience for the improved weather information that will result from the TAMDAR data. The weather data will be disseminated and used to improve aviation safety by providing pilots with enhanced weather situational awareness. In addition, the data will be used to improve the accuracy and timeliness of weather forecasts. Other users include air traffic controllers, flight service stations, and airline weather centers. Additionally, the meteorological data collected by TAMDAR is expected to have a significant positive impact on forecast accuracy for ground based applications.

A modular optical sensor

NASA Astrophysics Data System (ADS)

Conklin, John Albert

This dissertation presents the design of a modular, fiber-optic sensor and the results obtained from testing the modular sensor. The modular fiber-optic sensor is constructed in such manner that the sensor diaphragm can be replaced with different configurations to detect numerous physical phenomena. Additionally, different fiber-optic detection systems can be attached to the sensor. Initially, the modular sensor was developed to be used by university of students to investigate realistic optical sensors and detection systems to prepare for advance studies of micro-optical mechanical systems (MOMS). The design accomplishes this by doing two things. First, the design significantly lowers the costs associated with studying optical sensors by modularizing the sensor design. Second, the sensor broadens the number of physical phenomena that students can apply optical sensing techniques to in a fiber optics sensor course. The dissertation is divided into seven chapters covering the historical development of fiber-optic sensors, a theoretical overview of fiber-optic sensors, the design, fabrication, and the testing of the modular sensor developed in the course of this work. Chapter 1 discusses, in detail, how this dissertation is organized and states the purpose of the dissertation. Chapter 2 presents an historical overview of the development of optical fibers, optical pressure sensors, and fibers, optical pressure sensors, and optical microphones. Chapter 3 reviews the theory of multi-fiber optic detection systems, optical microphones, and pressure sensors. Chapter 4 presents the design details of the modular, optical sensor. Chapter 5 delves into how the modular sensor is fabricated and how the detection systems are constructed. Chapter 6 presents the data collected from the microphone and pressure sensor configurations of the modular sensor. Finally, Chapter 7 discusses the data collected and draws conclusions about the design based on the data collected. Chapter 7 also presents future work needed to expand the functionality and utility of the modular sensor.

International Space Station Data Collection for Disaster Response

NASA Technical Reports Server (NTRS)

Stefanov, William L.; Evans, Cynthia A..

2014-01-01

Natural disasters - including such events as tropical storms, earthquakes, floods, volcanic eruptions, and wildfires -effect hundreds of millions of people worldwide, and also cause billions of dollars (USD) in damage to the global economy. Remotely sensed data acquired by orbital sensor systems has emerged as a vital tool to identify the extent of damage resulting from a natural disaster, as well as providing near-real time mapping support to response efforts on the ground and humanitarian aid efforts. The International Space Station (ISS) is a unique terrestrial remote sensing platform for acquiring disaster response imagery. Unlike automated remote-sensing platforms it has a human crew; is equipped with both internal and externally-mounted remote sensing instruments; and has an inclined, low-Earth orbit that provides variable views and lighting (day and night) over 95 percent of the inhabited surface of the Earth. As such, it provides a useful complement to free-flyer based, sun-synchronous sensor systems in higher altitude polar orbits. While several nations have well-developed terrestrial remote sensing programs and assets for data collection, many developing nations do not have ready access to such resources. The International Charter, Space and Major Disasters (also known as the "International Disaster Charter", or IDC; http://www.disasterscharter.org/home) addresses this disparity. It is an agreement between agencies of several countries to provide - on a best-effort basis - remotely sensed data of natural disasters to requesting countries in support of disaster response. The lead US agency for interaction with the IDC is the United States Geological Survey (USGS); when an IDC request or "activation" is received, the USGS notifies the science teams for NASA instruments with targeting information for data collection. In the case of the ISS, the Earth Sciences and Remote Sensing (ESRS) Unit, part of the Astromaterials Research and Exploration Science Directorate and supporting the ISS Program Science Office at NASA's Johnson Space Center, receives notification from the USGS and coordinates targeting and data collection with the NASA ISS sensor teams. If data is collected, it is passed back to the USGS for posting on their Hazards Data Distribution System and made available for download. The ISS International Partners (CSA, ESA, JAXA, Roscosmos/Energia) have their own procedures for independently supporting IDC activations using their assets on ISS, and there is currently no joint coordination with NASA ISS sensor teams. Following completion of ISS assembly, NASA remote sensing assets began collecting IDC response data in May 2012. The initial NASA ISS sensor systems available to respond to IDC activations included the ISS Agricultural Camera (ISSAC), an internal multispectral visible-near infrared wavelength system mounted in the Window Observational Research Facility, or WORF; the Crew Earth Observations (CEO) Facility, where the crew collects imagery through Station windows using off-the-shelf handheld digital visible-wavelength cameras; and the Hyperspectral Imager for the Coastal Oceans (HICO), a visible to near-infrared system mounted externally on the Japan Experiment Module Exposed Facility. The ISSAC completed its primary mission and was removed from the WORF in January 2013. It was replaced by the very high resolution ISS SERVIR Environmental Research and Visualization System (ISERV) Pathfinder, a visible-wavelength digital camera, telescope, and pointing system. Since the start of IDC response by NASA sensors on the ISS in May 2012 and as of this report, there have been eighty IDC activations; NASA sensor systems have collected data for twenty-three of these events. Of the twenty-three successful data collections, five involved 2 or more ISS sensor systems responding to the same event. Data has also been collected by International Partners in response to natural disasters, most notably JAXA and Roscosmos/Energia through the Urugan program. Data collected in response to IDC activations is delivered by the ISS sensor teams to the ESRS for quality review and transfer to the USGS, where it is ingested into the Hazards Data Distribution System, or HDDS (https://hdds.usgs.gov/hdds2/; figure 1). This system allows the local agencies that issued the IDC activation request to review and download data. The data is then used to develop secondary products useful for humanitarian response such as flood maps. As of this report, approximately 1000 images collected by NASA ISS sensor systems have been downloaded from the HDDS, indicating that the ISS has assumed a valuable role in disaster response efforts. The ISS is also a unique platform in that it will have multiple users over its lifetime, and that no single remote sensing system has a permanent internal or external berth. This scheduled turnover provides for development of new remote sensing capabilities relevant to disaster response -as well as both research and applied science-and represents a significant contribution to continuance and enhancement of the NASA mission to investigate changes on our home planet.

A 100 Mfps image sensor for biological applications

NASA Astrophysics Data System (ADS)

Etoh, T. Goji; Shimonomura, Kazuhiro; Nguyen, Anh Quang; Takehara, Kosei; Kamakura, Yoshinari; Goetschalckx, Paul; Haspeslagh, Luc; De Moor, Piet; Dao, Vu Truong Son; Nguyen, Hoang Dung; Hayashi, Naoki; Mitsui, Yo; Inumaru, Hideo

2018-02-01

Two ultrahigh-speed CCD image sensors with different characteristics were fabricated for applications to advanced scientific measurement apparatuses. The sensors are BSI MCG (Backside-illuminated Multi-Collection-Gate) image sensors with multiple collection gates around the center of the front side of each pixel, placed like petals of a flower. One has five collection gates and one drain gate at the center, which can capture consecutive five frames at 100 Mfps with the pixel count of about 600 kpixels (512 x 576 x 2 pixels). In-pixel signal accumulation is possible for repetitive image capture of reproducible events. The target application is FLIM. The other is equipped with four collection gates each connected to an in-situ CCD memory with 305 elements, which enables capture of 1,220 (4 x 305) consecutive images at 50 Mfps. The CCD memory is folded and looped with the first element connected to the last element, which also makes possible the in-pixel signal accumulation. The sensor is a small test sensor with 32 x 32 pixels. The target applications are imaging TOF MS, pulse neutron tomography and dynamic PSP. The paper also briefly explains an expression of the temporal resolution of silicon image sensors theoretically derived by the authors in 2017. It is shown that the image sensor designed based on the theoretical analysis achieves imaging of consecutive frames at the frame interval of 50 ps.

Cellular telephone-based radiation detection instrument

DOEpatents

Craig, William W [Pittsburg, CA; Labov, Simon E [Berkeley, CA

2011-06-14

A network of radiation detection instruments, each having a small solid state radiation sensor module integrated into a cellular phone for providing radiation detection data and analysis directly to a user. The sensor module includes a solid-state crystal bonded to an ASIC readout providing a low cost, low power, light weight compact instrument to detect and measure radiation energies in the local ambient radiation field. In particular, the photon energy, time of event, and location of the detection instrument at the time of detection is recorded for real time transmission to a central data collection/analysis system. The collected data from the entire network of radiation detection instruments are combined by intelligent correlation/analysis algorithms which map the background radiation and detect, identify and track radiation anomalies in the region.

Cellular telephone-based wide-area radiation detection network

DOEpatents

Craig, William W [Pittsburg, CA; Labov, Simon E [Berkeley, CA

2009-06-09

A network of radiation detection instruments, each having a small solid state radiation sensor module integrated into a cellular phone for providing radiation detection data and analysis directly to a user. The sensor module includes a solid-state crystal bonded to an ASIC readout providing a low cost, low power, light weight compact instrument to detect and measure radiation energies in the local ambient radiation field. In particular, the photon energy, time of event, and location of the detection instrument at the time of detection is recorded for real time transmission to a central data collection/analysis system. The collected data from the entire network of radiation detection instruments are combined by intelligent correlation/analysis algorithms which map the background radiation and detect, identify and track radiation anomalies in the region.

Data mining tools for the support of traffic signal timing plan development in arterial networks

DOT National Transportation Integrated Search

2001-05-01

Intelligent transportation systems (ITS) include large numbers of traffic sensors that collect enormous quantities of data. The data provided by ITS is necessary for advanced forms of control; however, basic forms of control, primarily time-of-day (T...

Monitoring system including an electronic sensor platform and an interrogation transceiver

DOEpatents

Kinzel, Robert L.; Sheets, Larry R.

2003-09-23

A wireless monitoring system suitable for a wide range of remote data collection applications. The system includes at least one Electronic Sensor Platform (ESP), an Interrogator Transceiver (IT) and a general purpose host computer. The ESP functions as a remote data collector from a number of digital and analog sensors located therein. The host computer provides for data logging, testing, demonstration, installation checkout, and troubleshooting of the system. The IT transmits signals from one or more ESP's to the host computer to the ESP's. The IT host computer may be powered by a common power supply, and each ESP is individually powered by a battery. This monitoring system has an extremely low power consumption which allows remote operation of the ESP for long periods; provides authenticated message traffic over a wireless network; utilizes state-of-health and tamper sensors to ensure that the ESP is secure and undamaged; has robust housing of the ESP suitable for use in radiation environments; and is low in cost. With one base station (host computer and interrogator transceiver), multiple ESP's may be controlled at a single monitoring site.

Produce documents and media information. [on lightning

NASA Technical Reports Server (NTRS)

Alzmann, Melanie A.; Miller, G.A.

1994-01-01

Lightning data and information were collected from the United States, Germany, France, Brazil, China, and Australia for the dual purposes of compiling a global lightning data base and producing publications on the Marshall Space Flight Center's lightning program. Research covers the history of lightning, the characteristics of a storm, types of lightningdischarges, observations from airplanes and spacecraft, the future fole of planes and spacecraft in lightning studies, lightning detection networks, and the relationships between lightning and rainfall. Descriptions of the Optical Transient Dectector, the Lightning Imaging Sensor, and the Lightning Mapper Sensor are included.

Long term performance stability of silicon sensors

NASA Astrophysics Data System (ADS)

Mori, R.; Betancourt, C.; Kühn, S.; Hauser, M.; Messmer, I.; Hasenfratz, A.; Thomas, M.; Lohwasser, K.; Parzefall, U.; Jakobs, K.

2015-10-01

The HL-LHC investigations on silicon particle sensor performance are carried out with the intention to reproduce the harsh environments foreseen, but usually in individual short measurements. Recently, several groups have observed a decrease in the charge collection of silicon strip sensors after several days, in particular on sensors showing charge multiplication. This phenomenon has been explained with a surface effect, the increase of charge sharing due to the increment of positive charge in the silicon oxide coming from the source used for charge collection measurements. Observing a similar behaviour in other sensors for which we can exclude this surface effect, we propose and investigate alternative explanations, namely trapping related effects (change of polarization) and annealing related effects. Several n-on-p strip sensors, as-processed and irradiated with protons and neutrons up to 5 ×1015neq /cm2, have been subjected to charge collection efficiency measurements for several days, while parameters like the impedance have been monitored. The probable stressing conditions have been changed in an attempt to recover the collected charge in case of a decrease. The results show that for the investigated sensors the effect of charge sharing induced by a radioactive source is not important, and a main detrimental factor is due to very high voltage, while at lower voltages the performance is stable.

An efficient management system for wireless sensor networks.

PubMed

Ma, Yi-Wei; Chen, Jiann-Liang; Huang, Yueh-Min; Lee, Mei-Yu

2010-01-01

Wireless sensor networks have garnered considerable attention recently. Networks typically have many sensor nodes, and are used in commercial, medical, scientific, and military applications for sensing and monitoring the physical world. Many researchers have attempted to improve wireless sensor network management efficiency. A Simple Network Management Protocol (SNMP)-based sensor network management system was developed that is a convenient and effective way for managers to monitor and control sensor network operations. This paper proposes a novel WSNManagement system that can show the connections stated of relationships among sensor nodes and can be used for monitoring, collecting, and analyzing information obtained by wireless sensor networks. The proposed network management system uses collected information for system configuration. The function of performance analysis facilitates convenient management of sensors. Experimental results show that the proposed method enhances the alive rate of an overall sensor node system, reduces the packet lost rate by roughly 5%, and reduces delay time by roughly 0.2 seconds. Performance analysis demonstrates that the proposed system is effective for wireless sensor network management.

Importance of the spatial data and the sensor web in the ubiquitous computing area

NASA Astrophysics Data System (ADS)

Akçit, Nuhcan; Tomur, Emrah; Karslıoǧlu, Mahmut O.

2014-08-01

Spatial data has become a critical issue in recent years. In the past years, nearly more than three quarters of databases, were related directly or indirectly to locations referring to physical features, which constitute the relevant aspects. Spatial data is necessary to identify or calculate the relationships between spatial objects when using spatial operators in programs or portals. Originally, calculations were conducted using Geographic Information System (GIS) programs on local computers. Subsequently, through the Internet, they formed a geospatial web, which is integrated into a discoverable collection of geographically related web standards and key features, and constitutes a global network of geospatial data that employs the World Wide Web to process textual data. In addition, the geospatial web is used to gather spatial data producers, resources, and users. Standards also constitute a critical dimension in further globalizing the idea of the geospatial web. The sensor web is an example of the real time service that the geospatial web can provide. Sensors around the world collect numerous types of data. The sensor web is a type of sensor network that is used for visualizing, calculating, and analyzing collected sensor data. Today, people use smart devices and systems more frequently because of the evolution of technology and have more than one mobile device. The considerable number of sensors and different types of data that are positioned around the world have driven the production of interoperable and platform-independent sensor web portals. The focus of such production has been on further developing the idea of an interoperable and interdependent sensor web of all devices that share and collect information. The other pivotal idea consists of encouraging people to use and send data voluntarily for numerous purposes with the some level of credibility. The principal goal is to connect mobile and non-mobile device in the sensor web platform together to operate for serving and collecting information from people.

Fiber Optic Strain Sensor for Planetary Gear Diagnostics

NASA Technical Reports Server (NTRS)

Kiddy, Jason S.; Lewicki, David G.; LaBerge, Kelsen E.; Ehinger, Ryan T.; Fetty, Jason

2011-01-01

This paper presents a new sensing approach for helicopter damage detection in the planetary stage of a helicopter transmission based on a fiber optic strain sensor array. Complete helicopter transmission damage detection has proven itself a difficult task due to the complex geometry of the planetary reduction stage. The crowded and complex nature of the gearbox interior does not allow for attachment of sensors within the rotating frame. Hence, traditional vibration-based diagnostics are instead based on measurements from externally mounted sensors, typically accelerometers, fixed to the gearbox exterior. However, this type of sensor is susceptible to a number of external disturbances that can corrupt the data, leading to false positives or missed detection of potentially catastrophic faults. Fiber optic strain sensors represent an appealing alternative to the accelerometer. Their small size and multiplexibility allows for potentially greater sensing resolution and accuracy, as well as redundancy, when employed as an array of sensors. The work presented in this paper is focused on the detection of gear damage in the planetary stage of a helicopter transmission using a fiber optic strain sensor band. The sensor band includes an array of 13 strain sensors, and is mounted on the ring gear of a Bell Helicopter OH-58C transmission. Data collected from the sensor array is compared to accelerometer data, and the damage detection results are presented

Maximum Data Collection Rate Routing Protocol Based on Topology Control for Rechargeable Wireless Sensor Networks

PubMed Central

Lin, Haifeng; Bai, Di; Gao, Demin; Liu, Yunfei

2016-01-01

In Rechargeable Wireless Sensor Networks (R-WSNs), in order to achieve the maximum data collection rate it is critical that sensors operate in very low duty cycles because of the sporadic availability of energy. A sensor has to stay in a dormant state in most of the time in order to recharge the battery and use the energy prudently. In addition, a sensor cannot always conserve energy if a network is able to harvest excessive energy from the environment due to its limited storage capacity. Therefore, energy exploitation and energy saving have to be traded off depending on distinct application scenarios. Since higher data collection rate or maximum data collection rate is the ultimate objective for sensor deployment, surplus energy of a node can be utilized for strengthening packet delivery efficiency and improving the data generating rate in R-WSNs. In this work, we propose an algorithm based on data aggregation to compute an upper data generation rate by maximizing it as an optimization problem for a network, which is formulated as a linear programming problem. Subsequently, a dual problem by introducing Lagrange multipliers is constructed, and subgradient algorithms are used to solve it in a distributed manner. At the same time, a topology controlling scheme is adopted for improving the network’s performance. Through extensive simulation and experiments, we demonstrate that our algorithm is efficient at maximizing the data collection rate in rechargeable wireless sensor networks. PMID:27483282

Maximum Data Collection Rate Routing Protocol Based on Topology Control for Rechargeable Wireless Sensor Networks.

PubMed

Lin, Haifeng; Bai, Di; Gao, Demin; Liu, Yunfei

2016-07-30

In Rechargeable Wireless Sensor Networks (R-WSNs), in order to achieve the maximum data collection rate it is critical that sensors operate in very low duty cycles because of the sporadic availability of energy. A sensor has to stay in a dormant state in most of the time in order to recharge the battery and use the energy prudently. In addition, a sensor cannot always conserve energy if a network is able to harvest excessive energy from the environment due to its limited storage capacity. Therefore, energy exploitation and energy saving have to be traded off depending on distinct application scenarios. Since higher data collection rate or maximum data collection rate is the ultimate objective for sensor deployment, surplus energy of a node can be utilized for strengthening packet delivery efficiency and improving the data generating rate in R-WSNs. In this work, we propose an algorithm based on data aggregation to compute an upper data generation rate by maximizing it as an optimization problem for a network, which is formulated as a linear programming problem. Subsequently, a dual problem by introducing Lagrange multipliers is constructed, and subgradient algorithms are used to solve it in a distributed manner. At the same time, a topology controlling scheme is adopted for improving the network's performance. Through extensive simulation and experiments, we demonstrate that our algorithm is efficient at maximizing the data collection rate in rechargeable wireless sensor networks.

Evaluating Several Hundred Predictors for Suspended Particulate Matter in the Northern Gulf of Mexico Using Inherent and Apparent Optical Properties & Considering Their Applicability for Use With Bathymetric Lidar Surveys

NASA Astrophysics Data System (ADS)

Epps, S. A.

2017-12-01

Suspended particulate matter (SPM) is an important agent in generating marine light conditions which in turn have strong influences on biogeochemical systems. SPM also behaves as a vehicle for contaminant migration and is of interest to the estimation of bulk material transport in the marine environment. The measurement of inherent optical properties (IOPs) and apparent optical properties (AOPs) is becoming increasingly important in the prediction of SPM concentration. To more fully utilize data generated in bathymetric lidar surveys, modern systems such as CZMIL (the Coastal Zone Mapping Imaging LIDAR) include a hyperspectral sensor to collect data necessary for remote sensing reflectance (Rrs), an AOP. Some IOPs can be estimated can be estimated from Rrs. Additionally, a bathymetric lidar return signal contains both absorption and backscattering components (IOPs) at 532 nm which may be utilized for SPM prediction. This research utilizes IOP measurements using AC-9, AC-S, BB-9, and LISST-100X-B sensors deployed in the Northern Gulf of Mexico concurrent with SPM collection via filtration. Concomitant Rrs values were collected using a hand held hyperspectral sensor. Several hundred linearly regressed single-parameter estimates are created to predict SPM concentration using the IOPs attenuation, total scatter, backscatter, absorption and significant amalgamations thereof. Multiple wavelengths of light are analyzed for each IOP or IOP combination. Consideration is given to the suitability of each IOP type to SPM concentration prediction. Several criteria are assessed to winnow out the best predictors. These include sensor, data, and environmental limitations. The quantitative analyses of this research assist to identify the best types of IOPs (and wavelengths) for SPM prediction. Rrs at multiple wavelengths is also considered for SPM prediction. This research is focused on the functionality of IOP and AOP based SPM concentration predictions made available from the data products of bathymetric lidar surveys. It has applications for researchers with interest in IOPs, AOPs and SPM. There are also implications for monitoring estuarine, coastal, and offshore environments using bathymetric lidar and in-situ optical sensor suites to estimate SPM.

Characterization of thin irradiated epitaxial silicon sensors for the CMS phase II pixel upgrade

NASA Astrophysics Data System (ADS)

Centis Vignali, M.

2015-02-01

The high-luminosity upgrade of the Large Hadron Collider foreseen for 2023 resulted on the decision to replace the tracker system of the CMS experiment. The innermost layer of the new pixel detector will experience fluences in the order of phieq ≈ 1016 cm-2 and a dose of ≈ 5 MGy after an integrated luminosity of 3000 fb-1. Several materials and designs are under investigation in order to build a detector that can withstand such high fluences. Thin planar silicon sensors are good candidates to achieve this goal since the degradation of the signal produced by traversing particles is less severe than for thicker devices. A study has been carried out in order to characterize highly irradiated planar epitaxial silicon sensors with an active thickness of 100 μm. The investigation includes pad diodes and strip detectors irradiated up to a fluence of phieq = 1.3 × 1016 cm-2, and 3 × 1015 cm-2, respectively. The electrical properties of diodes have been characterized using laboratory measurements, while measurements have been carried out at the DESY II test beam facility to characterize the charge collection of the strip detectors. A beam telescope has been used to determine precisely the impact position of beam particles on the sensor. This allows the unbiased extraction of the charge deposited in the strip sensor and good identification of the noise. In this paper, the results obtained for p-bulk sensors are shown. The charge collection efficiency of the strip sensors is 90% at 1000 V after a fluence of phieq = 3 × 1015 cm-2. The irradiated diodes show charge multiplication effects. The impact of the threshold applied to a detector on its efficiency is also discussed.

Stand alone, low current measurements on possible sensing platforms via Arduino Uno microcontroller with modified commercially available sensors

NASA Astrophysics Data System (ADS)

Tanner, Meghan; Henson, Gabriel; Senevirathne, Indrajith

Advent of cost-effective solid-state sensors has spurred an immense interest in microcontrollers, in particular Arduino microcontrollers. These include serious engineering and physical science applications due to their versatility and robustness. An Arduino microcontroller coupled with a commercially available sensor has been used to methodically measure, record, and explore low currents, low voltages, and corresponding dissipated power towards assessing secondary physical properties in a select set of engineered systems. System was assembled via breadboard, wire, and simple soldering with an Arduino Uno with ATmega328P microcontroller connected to a PC. The microcontroller was programmed with Arduino software while the bootloader was used to upload the code. High-side measurement INA169 current shunt monitor was used to measure corresponding low to ultra-low currents and voltages. A collection of measurements was obtained via the sensor and was compared with measurements from standardized devices to assess reliability and uncertainty. Some sensors were modified/hacked to improve the sensitivity of the measurements.

Sensor Webs: Autonomous Rapid Response to Monitor Transient Science Events

NASA Technical Reports Server (NTRS)

Mandl, Dan; Grosvenor, Sandra; Frye, Stu; Sherwood, Robert; Chien, Steve; Davies, Ashley; Cichy, Ben; Ingram, Mary Ann; Langley, John; Miranda, Felix

2005-01-01

To better understand how physical phenomena, such as volcanic eruptions, evolve over time, multiple sensor observations over the duration of the event are required. Using sensor web approaches that integrate original detections by in-situ sensors and global-coverage, lower-resolution, on-orbit assets with automated rapid response observations from high resolution sensors, more observations of significant events can be made with increased temporal, spatial, and spectral resolution. This paper describes experiments using Earth Observing 1 (EO-1) along with other space and ground assets to implement progressive mission autonomy to identify, locate and image with high resolution instruments phenomena such as wildfires, volcanoes, floods and ice breakup. The software that plans, schedules and controls the various satellite assets are used to form ad hoc constellations which enable collaborative autonomous image collections triggered by transient phenomena. This software is both flight and ground based and works in concert to run all of the required assets cohesively and includes software that is model-based, artificial intelligence software.

Evaporometer | A Wireless Mesh of Open-Source Rainfall/Evaporation Gauge and Sensor Suite for In Situ Near-Real-Time Environmental Data

NASA Astrophysics Data System (ADS)

Kwon, M.; Lopez Alcala, J. M.; DeBell, T. C.; Udell, C.; Selker, J. S.

2017-12-01

Access to in situ near real-time environmental sensor data in remote locations provides invaluable utility in the fields of agricultural and environmental sciences. For studies where data needs to be gathered frequently, it could be costly and dangerous to take numerous trips into the field to collect this information and to inspect multitudes of distributed devices to ensure proper operation. One solution is to develop remote sensors capable of transmitting data and status updates (like battery level) over long distances from unserviced locations to a receiver hub to be accessed in near real-time online. The Openly Published Environmental Sensing Lab at Oregon State University (OPEnS Lab) produced a low-cost Open Source environmental sensing station called the Evaporometer that collects data at precisely timed intervals including rainfall amount, rate of evaporation, temperature, humidity and light (IR and Visible spectra), while CO2 and other sensors are also being evaluated for inclusion. This project focuses on the development and deployment of the prototype Evaporometer in HJ Andrew's Experimental Forest located in Blue River Oregon. The Evaporometer was designed for efficiency and succeeds in systematically collecting environmental data in hard to reach places over long periods of time. A real time clock interrupt enables the device to enter and exit "sleep mode", allowing Evaporometers to remain in the field over long periods of time and controlling the how frequently data should be collected. A load cell measures the weight of collected water in a container. This container is tightly packed with a fiberglass wick, which draws water from the bottom to the surface for efficient evaporation. A siphon has been designed into the container to prevent any possible water overflow situations and lost collected rainfall. All data collection and transmission processes are handled by an Adafruit Feather development board equipped with a long range, low power wireless (LoRa) radio that sends encrypted data via 900MHz ISM band. This data can be transmitted up to 20km to a receiver hub with an internet connection, and uploaded directly to Google cloud storage or other online data services for convenience.

Active Multimodal Sensor System for Target Recognition and Tracking

PubMed Central

Zhang, Guirong; Zou, Zhaofan; Liu, Ziyue; Mao, Jiansen

2017-01-01

High accuracy target recognition and tracking systems using a single sensor or a passive multisensor set are susceptible to external interferences and exhibit environmental dependencies. These difficulties stem mainly from limitations to the available imaging frequency bands, and a general lack of coherent diversity of the available target-related data. This paper proposes an active multimodal sensor system for target recognition and tracking, consisting of a visible, an infrared, and a hyperspectral sensor. The system makes full use of its multisensor information collection abilities; furthermore, it can actively control different sensors to collect additional data, according to the needs of the real-time target recognition and tracking processes. This level of integration between hardware collection control and data processing is experimentally shown to effectively improve the accuracy and robustness of the target recognition and tracking system. PMID:28657609

Resistive flex sensors: a survey

NASA Astrophysics Data System (ADS)

Saggio, Giovanni; Riillo, Francesco; Sbernini, Laura; Quitadamo, Lucia Rita

2016-01-01

Resistive flex sensors can be used to measure bending or flexing with relatively little effort and a relatively low budget. Their lightness, compactness, robustness, measurement effectiveness and low power consumption make these sensors useful for manifold applications in diverse fields. Here, we provide a comprehensive survey of resistive flex sensors, taking into account their working principles, manufacturing aspects, electrical characteristics and equivalent models, useful front-end conditioning circuitry, and physic-bio-chemical aspects. Particular effort is devoted to reporting on and analyzing several applications of resistive flex sensors, related to the measurement of body position and motion, and to the implementation of artificial devices. In relation to the human body, we consider the utilization of resistive flex sensors for the measurement of physical activity and for the development of interaction/interface devices driven by human gestures. Concerning artificial devices, we deal with applications related to the automotive field, robots, orthosis and prosthesis, musical instruments and measuring tools. The presented literature is collected from different sources, including bibliographic databases, company press releases, patents, master’s theses and PhD theses.

An Amplitude-Based Estimation Method for International Space Station (ISS) Leak Detection and Localization Using Acoustic Sensor Networks

NASA Technical Reports Server (NTRS)

Tian, Jialin; Madaras, Eric I.

2009-01-01

The development of a robust and efficient leak detection and localization system within a space station environment presents a unique challenge. A plausible approach includes the implementation of an acoustic sensor network system that can successfully detect the presence of a leak and determine the location of the leak source. Traditional acoustic detection and localization schemes rely on the phase and amplitude information collected by the sensor array system. Furthermore, the acoustic source signals are assumed to be airborne and far-field. Likewise, there are similar applications in sonar. In solids, there are specialized methods for locating events that are used in geology and in acoustic emission testing that involve sensor arrays and depend on a discernable phase front to the received signal. These methods are ineffective if applied to a sensor detection system within the space station environment. In the case of acoustic signal location, there are significant baffling and structural impediments to the sound path and the source could be in the near-field of a sensor in this particular setting.

Predicting Functional Independence Measure Scores During Rehabilitation with Wearable Inertial Sensors

PubMed Central

Sprint, Gina; Cook, Diane J.; Weeks, Douglas L.; Borisov, Vladimir

2016-01-01

Evaluating patient progress and making discharge decisions regarding inpatient medical rehabilitation rely upon standard clinical assessments administered by trained clinicians. Wearable inertial sensors can offer more objective measures of patient movement and progress. We undertook a study to investigate the contribution of wearable sensor data to predict discharge functional independence measure (FIM) scores for 20 patients at an inpatient rehabilitation facility. The FIM utilizes a 7-point ordinal scale to measure patient independence while performing several activities of daily living, such as walking, grooming, and bathing. Wearable inertial sensor data were collected from ecological ambulatory tasks at two time points mid-stay during inpatient rehabilitation. Machine learning algorithms were trained with sensor-derived features and clinical information obtained from medical records at admission to the inpatient facility. While models trained only with clinical features predicted discharge scores well, we were able to achieve an even higher level of prediction accuracy when also including the wearable sensor-derived features. Correlations as high as 0.97 for leave-one-out cross validation predicting discharge FIM motor scores are reported. PMID:27054054

Complete Scene Recovery and Terrain Classification in Textured Terrain Meshes

PubMed Central

Song, Wei; Cho, Kyungeun; Um, Kyhyun; Won, Chee Sun; Sim, Sungdae

2012-01-01

Terrain classification allows a mobile robot to create an annotated map of its local environment from the three-dimensional (3D) and two-dimensional (2D) datasets collected by its array of sensors, including a GPS receiver, gyroscope, video camera, and range sensor. However, parts of objects that are outside the measurement range of the range sensor will not be detected. To overcome this problem, this paper describes an edge estimation method for complete scene recovery and complete terrain reconstruction. Here, the Gibbs-Markov random field is used to segment the ground from 2D videos and 3D point clouds. Further, a masking method is proposed to classify buildings and trees in a terrain mesh. PMID:23112653

Chalcogenide glass sensors for bio-molecule detection

NASA Astrophysics Data System (ADS)

Lucas, Pierre; Coleman, Garrett J.; Cantoni, Christopher; Jiang, Shibin; Luo, Tao; Bureau, Bruno; Boussard-Pledel, Catherine; Troles, Johann; Yang, Zhiyong

2017-02-01

Chalcogenide glasses constitute the only class of materials that remain fully amorphous while exhibiting broad optical transparency over the full infrared region from 2-20 microns. As such, they can be shaped into complex optical elements while retaining a clear optical window that encompass the vibrational signals of virtually any molecules. Chalcogenide glasses are therefore ideal materials for designing biological and chemical sensors based on vibrational spectroscopy. In this paper we review the properties of these glasses and the corresponding design of optical elements for bio-chemical sensing. Amorphous chalcogenides offer a very wide compositional landscape that permit to tune their physical properties to match specific demands for the production of optical devices. This includes tailoring the infrared window over specific ranges of wavelength such as the long-wave infrared region to capture important vibrational signal including the "signature region" of micro-organisms or the bending mode of CO2 molecules. Additionally, compositional engineering enables tuning the viscosity-temperature dependence of the glass melt in order to control the rheological properties that are fundamental to the production of glass elements. Indeed, exquisite control of the viscosity is key to the fabrication process of many optical elements such as fiber drawing, lens molding, surface embossing or reflow of microresonators. Optimal control of these properties then enables the design and fabrication of optimized infrared sensors such as Fiber Evanescent Wave Spectroscopy (FEWS) sensors, Whispering Gallery Modes (WGM) micro-resonator sensors, nanostructured surfaces for integrated optics and surface-enhanced processes, or lens molding for focused collection of infrared signals. Many of these sensor designs can be adapted to collect and monitor the vibrational signal of live microorganisms to study their metabolism in controlled environmental conditions. Further materials engineering enable the design of opto-electrophoretic sensors that permit simultaneous capture and detection of hazardous bio-molecules such as bacteria, virus and proteins using a conducting glass that serves as both an electrode and an optical elements. Upon adequate spectral analysis such as Principal Component Analysis (PCA) or Partial Least Square (PLS) regression these devices enable highly selective identification of hazardous microorganism such as different strains of bacteria and food pathogens.

Development and Characteristics of a Mobile, Semi-Autonomous Floating Platform for in situ Lake Measurements

NASA Astrophysics Data System (ADS)

Barry, D.; Lemmin, U.; Le Dantec, N.; Zulliger, L.; Rusterholz, M.; Bolay, M.; Rossier, J.; Kangur, K.

2013-12-01

In the development of sustainable management strategies of lakes more insight into their physical, chemical and ecological dynamics is needed. Field data obtained from various types of sensors with adequate spatial and temporal sampling rate are essential to understand better the processes that govern fluxes and pathways of water masses and transported compounds, whether for model validation or for monitoring purposes. One advantage of unmanned platforms is that they limit the disturbances typically affecting the quality of data collected on small vessels, including perturbations caused by movements of onboard crew. We have developed a mobile, semi-autonomous floating platform with 8 h power autonomy using a 5 m long by 2.5 m wide catamaran. Our approach focused on modularity and high payload capacity in order to accommodate a large number of sensors both in terms of electronic (power and data) and mechanical constraints of integration. Software architecture and onboard electronics use National Instruments technology to simplify and standardize integration of sensors, actuators and communication. Piecewise-movable deck sections allow optimizing platform stability depending on the payload. The entire system is controlled by a remote computer located on an accompanying vessel and connected via a wireless link with a range of over 1 km. Real-time transmission of GPS-stamped measurements allows immediate modifications in the survey plan if needed. The displacement of the platform is semi-autonomous, with the options of either autopilot mode following a pre-planned course specified by waypoints or remote manual control from the accompanying vessel. Maintenance of permanent control over the platform displacement is required for safety reasons with respect to other users of the lake. Currently, the sensor payload comprises an array of fast temperature probes, a bottom-tracking ADCP and atmospheric sensors including a radiometer. A towed CTD with additional water quality sensors operated from a remotely controlled winch is presently being integrated. Field tests have shown that the platform is reliable, capable of collecting long transects of 2D lake and collocated atmospheric boundary layer data and adaptable to integrate new sensors.

New Window on the Universe.

ERIC Educational Resources Information Center

Reynolds, Ronald F.

1984-01-01

Describes the basic components of a space telescope that will be launched during a 1986 space shuttle mission. These components include a wide field/planetary camera, faint object spectroscope, high-resolution spectrograph, high-speed photometer, faint object camera, and fine guidance sensors. Data to be collected from these instruments are…

Acquisition and management of continuous data streams for crop water management

USDA-ARS?s Scientific Manuscript database

Wireless sensor network systems for decision support in crop water management offer many advantages including larger spatial coverage and multiple types of data input. However, collection and management of multiple and continuous data streams for near real-time post analysis can be problematic. Thi...

Design and implementation of a bluetooth-based band-aid pulse rate sensor

NASA Astrophysics Data System (ADS)

Kumar, Prashanth S.; Oh, Sechang; Rai, Pratyush; Kwon, Hyeokjun; Banerjee, Nilanjan; Varadan, Vijay K.

2011-04-01

Remote patient monitoring systems capable of collecting vital patient data such as blood pressure readings, Electrocardiograph (ECG) waveforms, and heart rate can obviate the need for repeated visits to the hospital. Moreover, such systems that continuously monitor the human physiology can provide valuable data to prognosticate the onset of critical health problems. The key to such remote health diagnostics is the design of minimally intrusive, low cost sensors that do not impede a patient's quotidian life but at the same time collect reliable noise free data. To this end, in this paper, we design and implement a Bluetooth-based wireless sensor system with a disposable sensor element and a reusable wireless component that can be worn as a "band-aid". The sensor is a piezoelectric polymer film placed on the wrist in proximity to the radial artery. The band-aid sized sensor allows non-intrusive monitoring of the pulsatile flow of blood in the artery. The sensor, using the Bluetooth module, can communicate with any Bluetooth enabled computer, mobile phone, or PDA. The data collected from the patient can be remotely viewed and analyzed by a physician.

A custom multi-modal sensor suite and data analysis pipeline for aerial field phenotyping

NASA Astrophysics Data System (ADS)

Bartlett, Paul W.; Coblenz, Lauren; Sherwin, Gary; Stambler, Adam; van der Meer, Andries

2017-05-01

Our group has developed a custom, multi-modal sensor suite and data analysis pipeline to phenotype crops in the field using unpiloted aircraft systems (UAS). This approach to high-throughput field phenotyping is part of a research initiative intending to markedly accelerate the breeding process for refined energy sorghum varieties. To date, single rotor and multirotor helicopters, roughly 14 kg in total weight, are being employed to provide sensor coverage over multiple hectaresized fields in tens of minutes. The quick, autonomous operations allow for complete field coverage at consistent plant and lighting conditions, with low operating costs. The sensor suite collects data simultaneously from six sensors and registers it for fusion and analysis. High resolution color imagery targets color and geometric phenotypes, along with lidar measurements. Long-wave infrared imagery targets temperature phenomena and plant stress. Hyperspectral visible and near-infrared imagery targets phenotypes such as biomass and chlorophyll content, as well as novel, predictive spectral signatures. Onboard spectrometers and careful laboratory and in-field calibration techniques aim to increase the physical validity of the sensor data throughout and across growing seasons. Off-line processing of data creates basic products such as image maps and digital elevation models. Derived data products include phenotype charts, statistics, and trends. The outcome of this work is a set of commercially available phenotyping technologies, including sensor suites, a fully integrated phenotyping UAS, and data analysis software. Effort is also underway to transition these technologies to farm management users by way of streamlined, lower cost sensor packages and intuitive software interfaces.

US-Korea collaborative research for bridge monitoring test beds

NASA Astrophysics Data System (ADS)

Yun, C. B.; Sohn, H.; Lee, J. J.; Park, S.; Wang, M. L.; Zhang, Y. F.; Lynch, J. P.

2010-04-01

This paper presents an interim report on an international collaborative research project between the United States and Korea that fundamentally addresses the challenges associated with integrating structural health monitoring (SHM) system components into a comprehensive system for bridges. The objective of the project is to integrate and validate cutting-edge sensors and SHM methods under development for monitoring the long-term performance and structural integrity of highway bridges. A variety of new sensor and monitoring technologies have been selected for integration including wireless sensors, EM stress sensors and piezoelectric active sensors. Using these sensors as building blocks, the first phase of the study focuses on the design of a comprehensive SHM system that is deployed upon a series of highway bridges in Korea. With permanently installed SHM systems in place, the second phase of the study provides open access to the bridges and response data continuously collected as an internal test-bed for SHM. Currently, basic facilities including Internet lines have been constructed on the test-beds, and the participants carried out tests on bridges on the test road section owned by the Korea Expressway Corporation (KEC) with their own measurement and monitoring systems in the local area network environment. The participants were able to access and control their measurement systems by using Remote Desktop in Windows XP through Internet. Researchers interested in this test-bed are encouraged to join in the collaborative research.

Systems and Methods for RFID-Enabled Pressure Sensing Apparatus

NASA Technical Reports Server (NTRS)

Kennedy, Timothy F. (Inventor); Lin, Gregory Y. (Inventor); Ngo, Phong H. (Inventor); Fink, Patrick W. (Inventor)

2017-01-01

Methods, apparatuses and systems for radio frequency identification (RFID)-enabled information collection are disclosed, including an enclosure, a collector coupled to the enclosure, an interrogator, a processor, and one or more RFID field sensors, each having an individual identification, disposed within the enclosure. In operation, the interrogator transmits an incident signal to the collector, causing the collector to generate an electromagnetic field within the enclosure. The electromagnetic field is affected by one or more influences. RFID sensors respond to the electromagnetic field by transmitting reflected signals containing the individual identifications of the responding RFID sensors to the interrogator. The interrogator receives the reflected signals, measures one or more returned signal strength indications ("RSSI") of the reflected signals and sends the RSSI measurements and identification of the responding RFID sensors to the processor to determine one or more facts about the influences. Other embodiments are also described.

Systems and Methods for RFID-Enabled Dispenser

NASA Technical Reports Server (NTRS)

Fink, Patrick W. (Inventor); Kennedy, Timothy F. (Inventor); Lin, Gregory Y. (Inventor); Ngo, Phong H. (Inventor); Byerly, Diane (Inventor)

2015-01-01

Methods, apparatuses and systems for radio frequency identification (RFID)-enabled information collection are disclosed, including an enclosure, a collector coupled to the enclosure, an interrogator, a processor, and one or more RFID field sensors, each having an individual identification, disposed within the enclosure. In operation, the interrogator transmits an incident signal to the collector, causing the collector to generate an electromagnetic field within the enclosure. The electromagnetic field is affected by one or more influences. RFID sensors respond to the electromagnetic field by transmitting reflected signals containing the individual identifications of the responding RFID sensors to the interrogator. The interrogator receives the reflected signals, measures one or more returned signal strength indications ("RSSI") of the reflected signals and sends the RSSI measurements and identification of the responding RFID sensors to the processor to determine one or more facts about the influences. Other embodiments are also described.

Systems and Methods for RFID-Enabled Pressure Sensing Apparatus

NASA Technical Reports Server (NTRS)

Lin, Gregory Y. (Inventor); Ngo, Phong H. (Inventor); Kennedy, Timothy F. (Inventor); Fink, Patrick W. (Inventor)

2016-01-01

Methods, apparatuses and systems for radio frequency identification (RFID)-enabled information collection are disclosed, including an enclosure, a collector coupled to the enclosure, an interrogator, a processor, and one or more RFID field sensors, each having an individual identification, disposed within the enclosure. In operation, the interrogator transmits an incident signal to the collector, causing the collector to generate an electromagnetic field within the enclosure. The electromagnetic field is affected by one or more influences. RFID sensors respond to the electromagnetic field by transmitting reflected signals containing the individual identifications of the responding RFID sensors to the interrogator. The interrogator receives the reflected signals, measures one or more returned signal strength indications ("RSSI") of the reflected signals and sends the RSSI measurements and identification of the responding RFID sensors to the processor to determine one or more facts about the influences. Other embodiments are also described.

Design a New Strategy Based on Nanoparticle-Enhanced Chemiluminescence Sensor Array for Biothiols Discrimination

NASA Astrophysics Data System (ADS)

Shahrajabian, Maryam; Hormozi-Nezhad, M. Reza

2016-08-01

Array-based sensor is an interesting approach that suggests an alternative to expensive analytical methods. In this work, we introduce a novel, simple, and sensitive nanoparticle-based chemiluminescence (CL) sensor array for discrimination of biothiols (e.g., cysteine, glutathione and glutathione disulfide). The proposed CL sensor array is based on the CL efficiencies of four types of enhanced nanoparticle-based CL systems. The intensity of CL was altered to varying degrees upon interaction with biothiols, producing unique CL response patterns. These distinct CL response patterns were collected as “fingerprints” and were then identified through chemometric methods, including linear discriminant analysis (LDA) and hierarchical cluster analysis (HCA). The developed array was able to successfully differentiate between cysteine, glutathione and glutathione disulfide in a wide concentration range. Moreover, it was applied to distinguish among the above analytes in human plasma.

Dual Roadside Seismic Sensor for Moving Road Vehicle Detection and Characterization

PubMed Central

Wang, Hua; Quan, Wei; Wang, Yinhai; Miller, Gregory R.

2014-01-01

This paper presents a method for using a dual roadside seismic sensor to detect moving vehicles on roadway by installing them on a road shoulder. Seismic signals are split into fixed time intervals in recording. In each interval, the time delay of arrival (TDOA) is estimated using a generalized cross-correlation approach with phase transform (GCC-PHAT). Various kinds of vehicle characterization information, including vehicle speed, axle spacing, detection of both vehicle axles and moving direction, can also be extracted from the collected seismic signals as demonstrated in this paper. The error of both vehicle speed and axle spacing detected by this approach has been shown to be less than 20% through the field tests conducted on an urban street in Seattle. Compared to most existing sensors, this new design of dual seismic sensor is cost effective, easy to install, and effective in gathering information for various traffic management applications. PMID:24526304

Method and apparatus for sampling low-yield wells

DOEpatents

Last, George V.; Lanigan, David C.

2003-04-15

An apparatus and method for collecting a sample from a low-yield well or perched aquifer includes a pump and a controller responsive to water level sensors for filling a sample reservoir. The controller activates the pump to fill the reservoir when the water level in the well reaches a high level as indicated by the sensor. The controller deactivates the pump when the water level reaches a lower level as indicated by the sensors. The pump continuously activates and deactivates the pump until the sample reservoir is filled with a desired volume, as indicated by a reservoir sensor. At the beginning of each activation cycle, the controller optionally can select to purge an initial quantity of water prior to filling the sample reservoir. The reservoir can be substantially devoid of air and the pump is a low volumetric flow rate pump. Both the pump and the reservoir can be located either inside or outside the well.

Test and Evaluation of Fiber Optic Sensors for High-Radiation Space Nuclear Power Applications

DOE Office of Scientific and Technical Information (OSTI.GOV)

Klemer, Daniel; Fielder, Robert S.; Stinson-Bagby, Kelly L.

2004-07-01

Fiber optic sensors can be used to measure a number of parameters, including temperature, strain, pressure and flow, for instrumentation and control of space nuclear power systems. In the past, this technology has often been rejected for use in such a high-radiation environment based on early experiments that revealed a number of degradation phenomena, including radiation-induced fiber attenuation, or 'graying', and Fiber Bragg Grating (FBG) fading and wavelength shift. However, this paper reports the results of recent experimental testing that demonstrates readability of fiber optic sensors to extremely high levels of neutron and gamma radiation. Both distributed Fiber Bragg Gratingmore » (FBG) sensors and single-point Extrinsic Fabry Perot Interferometer (EFPI) sensors were continuously monitored over a 2-month period, during which they were exposed to combined neutron and gamma radiation in both in-core and ex-core positions within a nuclear reactor. Total exposure reached approximately 2 x 10{sup 19} cm{sup -2} fast neutron (E > 1 MeV) fluence and 8.7 x 10{sup 8} Gy gamma for in-core sensors. FBG sensors were interrogated using a standard Luna Innovations FBG measurement system, which is based on optical frequency-domain reflectometer (OFDR) technology. Approximately 74% of the 19 FBG sensors located at the core centerline in the in-core position exhibited sufficient signal-to-noise ratio (SNR) to remain readable even after receiving the maximum dose. EFPI sensors were spectrally interrogated using a broadband probe source operating in the 830 nm wavelength region. While these single-point sensors failed early in the test, important additional fiber spectral transmission data was collected, which indicates that interrogation of EFPI sensors in alternate wavelength regions may allow significant improvement in sensor longevity for operation in high-radiation environments. This work was funded through a Small Business Innovative Research (SBIR) contract with the Nasa Glenn Research Center. (authors)« less

Multi-Source Cooperative Data Collection with a Mobile Sink for the Wireless Sensor Network.

PubMed

Han, Changcai; Yang, Jinsheng

2017-10-30

The multi-source cooperation integrating distributed low-density parity-check codes is investigated to jointly collect data from multiple sensor nodes to the mobile sink in the wireless sensor network. The one-round and two-round cooperative data collection schemes are proposed according to the moving trajectories of the sink node. Specifically, two sparse cooperation models are firstly formed based on geographical locations of sensor source nodes, the impairment of inter-node wireless channels and moving trajectories of the mobile sink. Then, distributed low-density parity-check codes are devised to match the directed graphs and cooperation matrices related with the cooperation models. In the proposed schemes, each source node has quite low complexity attributed to the sparse cooperation and the distributed processing. Simulation results reveal that the proposed cooperative data collection schemes obtain significant bit error rate performance and the two-round cooperation exhibits better performance compared with the one-round scheme. The performance can be further improved when more source nodes participate in the sparse cooperation. For the two-round data collection schemes, the performance is evaluated for the wireless sensor networks with different moving trajectories and the variant data sizes.

Multi-Source Cooperative Data Collection with a Mobile Sink for the Wireless Sensor Network

PubMed Central

Han, Changcai; Yang, Jinsheng

2017-01-01

The multi-source cooperation integrating distributed low-density parity-check codes is investigated to jointly collect data from multiple sensor nodes to the mobile sink in the wireless sensor network. The one-round and two-round cooperative data collection schemes are proposed according to the moving trajectories of the sink node. Specifically, two sparse cooperation models are firstly formed based on geographical locations of sensor source nodes, the impairment of inter-node wireless channels and moving trajectories of the mobile sink. Then, distributed low-density parity-check codes are devised to match the directed graphs and cooperation matrices related with the cooperation models. In the proposed schemes, each source node has quite low complexity attributed to the sparse cooperation and the distributed processing. Simulation results reveal that the proposed cooperative data collection schemes obtain significant bit error rate performance and the two-round cooperation exhibits better performance compared with the one-round scheme. The performance can be further improved when more source nodes participate in the sparse cooperation. For the two-round data collection schemes, the performance is evaluated for the wireless sensor networks with different moving trajectories and the variant data sizes. PMID:29084155

Sensing in the collaborative Internet of Things.

PubMed

Borges Neto, João B; Silva, Thiago H; Assunção, Renato Martins; Mini, Raquel A F; Loureiro, Antonio A F

2015-03-19

We are entering a new era of computing technology, the era of Internet of Things (IoT). An important element for this popularization is the large use of off-the-shelf sensors. Most of those sensors will be deployed by different owners, generally common users, creating what we call the Collaborative IoT. This collaborative IoT helps to increase considerably the amount and availability of collected data for different purposes, creating new interesting opportunities, but also several challenges. For example, it is very challenging to search for and select a desired sensor or a group of sensors when there is no description about the provided sensed data or when it is imprecise. Given that, in this work we characterize the properties of the sensed data in the Internet of Things, mainly the sensed data contributed by several sources, including sensors from common users. We conclude that, in order to safely use data available in the IoT, we need a filtering process to increase the data reliability. In this direction, we propose a new simple and powerful approach that helps to select reliable sensors. We tested our method for different types of sensed data, and the results reveal the effectiveness in the correct selection of sensor data.

An intelligent surveillance platform for large metropolitan areas with dense sensor deployment.

PubMed

Fernández, Jorge; Calavia, Lorena; Baladrón, Carlos; Aguiar, Javier M; Carro, Belén; Sánchez-Esguevillas, Antonio; Alonso-López, Jesus A; Smilansky, Zeev

2013-06-07

This paper presents an intelligent surveillance platform based on the usage of large numbers of inexpensive sensors designed and developed inside the European Eureka Celtic project HuSIMS. With the aim of maximizing the number of deployable units while keeping monetary and resource/bandwidth costs at a minimum, the surveillance platform is based on the usage of inexpensive visual sensors which apply efficient motion detection and tracking algorithms to transform the video signal in a set of motion parameters. In order to automate the analysis of the myriad of data streams generated by the visual sensors, the platform's control center includes an alarm detection engine which comprises three components applying three different Artificial Intelligence strategies in parallel. These strategies are generic, domain-independent approaches which are able to operate in several domains (traffic surveillance, vandalism prevention, perimeter security, etc.). The architecture is completed with a versatile communication network which facilitates data collection from the visual sensors and alarm and video stream distribution towards the emergency teams. The resulting surveillance system is extremely suitable for its deployment in metropolitan areas, smart cities, and large facilities, mainly because cheap visual sensors and autonomous alarm detection facilitate dense sensor network deployments for wide and detailed coverage.

Equivalent Sensor Radiance Generation and Remote Sensing from Model Parameters. Part 1; Equivalent Sensor Radiance Formulation

NASA Technical Reports Server (NTRS)

Wind, Galina; DaSilva, Arlindo M.; Norris, Peter M.; Platnick, Steven E.

2013-01-01

In this paper we describe a general procedure for calculating equivalent sensor radiances from variables output from a global atmospheric forecast model. In order to take proper account of the discrepancies between model resolution and sensor footprint the algorithm takes explicit account of the model subgrid variability, in particular its description of the probably density function of total water (vapor and cloud condensate.) The equivalent sensor radiances are then substituted into an operational remote sensing algorithm processing chain to produce a variety of remote sensing products that would normally be produced from actual sensor output. This output can then be used for a wide variety of purposes such as model parameter verification, remote sensing algorithm validation, testing of new retrieval methods and future sensor studies. We show a specific implementation using the GEOS-5 model, the MODIS instrument and the MODIS Adaptive Processing System (MODAPS) Data Collection 5.1 operational remote sensing cloud algorithm processing chain (including the cloud mask, cloud top properties and cloud optical and microphysical properties products.) We focus on clouds and cloud/aerosol interactions, because they are very important to model development and improvement.

Assessing the Performance of LVIS Waveform Lidar Topography and Canopy Structure Measurements in Gabon

NASA Astrophysics Data System (ADS)

Hofton, M. A.; Blair, J. B.; Rabine, D.; Brooks, C.; Cornejo, H.; Story, S.

2016-12-01

In February-March 2016, NASA's Land, Vegetation and Ice Sensor (LVIS) was used to image sub-canopy topography, canopy topography and structure at several sites in Gabon. Data were collected as part of the NASA and ESA Afrisar Campaign, a joint remote sensing mission involving multiple airborne and ground-based data collection activities that support the calibration and validation of future spaceborne missions, particularly GEDI, NISAR and BIOMASS, as well as other investigations. LVIS is a wide-swath, medium-footprint, waveform recording laser altimeter (lidar) sensor that can collect contiguous data within a 2 km-wide swath using 20m wide footprints from 10km altitude. For the Gabon deployment, the sensor was mounted in the NASA Langley King Air aircraft and flown at 8 km altitude over five, 70x15km-wide areas and along multiple country-wide transects. Data products include footprint-level canopy height, ground topography and canopy metrics, as well as vertically and horizontally-geolocated lidar return waveforms that enable end users to produce additional georeferenced data products as needed. We present a summary of the data products from the campaign, as well as a performance assessment of the ground and canopy structure data using available airborne and ground based data. Uses of the data include the simulation of GEDI-like data and the derivation of canopy height and profile metric algorithms for implementation in GEDI level2 products, as well as to improve our understanding of ground-finding errors in dense vegetation environments from waveform lidar.

Advances in Measuring the Apparent Optical Properties (AOPs) of Optically Complex Waters

NASA Technical Reports Server (NTRS)

Morrow, John H.; Hooker, Stanford B.; Booth, Charles R.; Bernhard, Germar; Lind, Randall N.; Brown, James W.

2010-01-01

This report documents new technology used to measure the apparent optical properties (AOPs) of optically complex waters. The principal objective is to be prepared for the launch of next-generation ocean color satellites with the most capable commercial off-the-shelf (COTS) instrumentation. An enhanced COTS radiometer was the starting point for designing and testing the new sensors. The follow-on steps were to apply the lessons learned towards a new in-water profiler based on a kite-shaped backplane for mounting the light sensors. The next level of sophistication involved evaluating new radiometers emerging from a development activity based on so-called microradiometers. The exploitation of microradiometers resulted in an in-water profiling system, which includes a sensor networking capability to control ancillary sensors like a shadowband or global positioning system (GPS) device. A principal advantage of microradiometers is their flexibility in producing, interconnecting, and maintaining instruments. The full problem set for collecting sea-truth data--whether in coastal waters or the open ocean-- involves other aspects of data collection that were improved for instruments measuring both AOPs and inherent optical properties (IOPs), if the uncertainty budget is to be minimized. New capabilities associated with deploying solar references were developed as well as a compact solution for recovering in-water instrument systems from small boats.

Development of the Chemical Exposure Monitor with Indoor Positioning (CEMWIP) for Workplace VOC Surveys

PubMed Central

Brown, KK; Shaw, PB; Mead, KR; Kovein, RJ; Voorhees, RT; Brandes, AR

2016-01-01

The purpose of this project was to research and develop a direct-reading exposure assessment method that combined a real-time location system with a wireless direct-reading personal chemical sensor. The personal chemical sensor was a photoionization device for detecting volatile organic compounds. The combined system was calibrated and tested against the same four standard gas concentrations and calibrated at one standard location and tested at four locations that included the standard locations. Data were wirelessly collected from the chemical sensor every 1.4 seconds, for volatile organic compounds concentration, location, temperature, humidity, and time. Regression analysis of the photo-ionization device voltage response against calibration gases showed the chemical sensor had a limit of detection of 0.2 ppm. The real-time location system was accurate to 13 cm ± 6 cm (standard deviation) in an open area and to 57 cm ± 31 cm in a closed room where the radio frequency has to penetrate drywall-finished walls. The streaming data were collected and graphically displayed as a three-dimensional hazard map for assessment of peak exposure with location. A real-time personal exposure assessment device with indoor positioning was practical and provided new knowledge on direct reading exposure assessment methods. PMID:26786234

Development of the chemical exposure monitor with indoor positioning (CEMWIP) for workplace VOC surveys.

PubMed

Brown, K K; Shaw, P B; Mead, K R; Kovein, R J; Voorhees, R T; Brandes, A R

2016-01-01

The purpose of this article was to research and develop a direct-reading exposure assessment method that combined a real-time location system with a wireless direct-reading personal chemical sensor. The personal chemical sensor was a photoionization device for detecting volatile organic compounds. The combined system was calibrated and tested against the same four standard gas concentrations and calibrated at one standard location and tested at four locations that included the standard locations. Data were wirelessly collected from the chemical sensor every 1.4 sec, for volatile organic compounds concentration, location, temperature, humidity, and time. Regression analysis of the photo-ionization device voltage response against calibration gases showed the chemical sensor had a limit of detection of 0.2 ppm. The real-time location system was accurate to 13 cm ± 6 cm (standard deviation) in an open area and to 57 cm ± 31 cm in a closed room where the radio frequency has to penetrate drywall-finished walls. The streaming data were collected and graphically displayed as a three-dimensional hazard map for assessment of peak exposure with location. A real-time personal exposure assessment device with indoor positioning was practical and provided new knowledge on direct reading exposure assessment methods.

cStress: Towards a Gold Standard for Continuous Stress Assessment in the Mobile Environment

PubMed Central

Hovsepian, Karen; al’Absi, Mustafa; Ertin, Emre; Kamarck, Thomas; Nakajima, Motohiro; Kumar, Santosh

2015-01-01

Recent advances in mobile health have produced several new models for inferring stress from wearable sensors. But, the lack of a gold standard is a major hurdle in making clinical use of continuous stress measurements derived from wearable sensors. In this paper, we present a stress model (called cStress) that has been carefully developed with attention to every step of computational modeling including data collection, screening, cleaning, filtering, feature computation, normalization, and model training. More importantly, cStress was trained using data collected from a rigorous lab study with 21 participants and validated on two independently collected data sets — in a lab study on 26 participants and in a week-long field study with 20 participants. In testing, the model obtains a recall of 89% and a false positive rate of 5% on lab data. On field data, the model is able to predict each instantaneous self-report with an accuracy of 72%. PMID:26543926

Radiation detection and wireless networked early warning

NASA Astrophysics Data System (ADS)

Burns, David A.; Litz, Marc S.; Carroll, James J.; Katsis, Dimosthenis

2012-06-01

We have designed a compact, wireless, GPS-enabled array of inexpensive radiation sensors based on scintillation counting. Each sensor has a scintillator, photomultiplier tube, and pulse-counting circuit that includes a comparator, digital potentiometer and microcontroller. This design provides a high level of sensitivity and reliability. A 0.2 m2 PV panel powers each sensor providing a maintenance-free 24/7 energy source. The sensor can be mounted within a roadway light-post and monitor radiological activity along transport routes. Each sensor wirelessly transmits real-time data (as counts per second) up to 2 miles with a XBee radio module, and the data is received by a XBee receive-module on a computer. Data collection software logs the information from all sensors and provides real-time identification of radiation events. Measurements performed to-date demonstrate the ability of a sensor to detect a 20 μCi source at 3.5 meters when packaged with a PVT (plastic) scintillator, and 7 meters for a sensor with a CsI crystal (more expensive but ~5 times more sensitive). It is calculated that the sensor-architecture can detect sources moving as fast as 130 km/h based on the current data rate and statistical bounds of 3-sigma threshold detection. The sensor array is suitable for identifying and tracking a radiation threat from a dirty bomb along roadways.

Semi-automated based ground-truthing GUI for airborne imagery

NASA Astrophysics Data System (ADS)

Phan, Chung; Lydic, Rich; Moore, Tim; Trang, Anh; Agarwal, Sanjeev; Tiwari, Spandan

2005-06-01

Over the past several years, an enormous amount of airborne imagery consisting of various formats has been collected and will continue into the future to support airborne mine/minefield detection processes, improve algorithm development, and aid in imaging sensor development. The ground-truthing of imagery is a very essential part of the algorithm development process to help validate the detection performance of the sensor and improving algorithm techniques. The GUI (Graphical User Interface) called SemiTruth was developed using Matlab software incorporating signal processing, image processing, and statistics toolboxes to aid in ground-truthing imagery. The semi-automated ground-truthing GUI is made possible with the current data collection method, that is including UTM/GPS (Universal Transverse Mercator/Global Positioning System) coordinate measurements for the mine target and fiducial locations on the given minefield layout to support in identification of the targets on the raw imagery. This semi-automated ground-truthing effort has developed by the US Army RDECOM CERDEC Night Vision and Electronic Sensors Directorate (NVESD), Countermine Division, Airborne Application Branch with some support by the University of Missouri-Rolla.

Typical effects of laser dazzling CCD camera

NASA Astrophysics Data System (ADS)

Zhang, Zhen; Zhang, Jianmin; Shao, Bibo; Cheng, Deyan; Ye, Xisheng; Feng, Guobin

2015-05-01

In this article, an overview of laser dazzling effect to buried channel CCD camera is given. The CCDs are sorted into staring and scanning types. The former includes the frame transfer and interline transfer types. The latter includes linear and time delay integration types. All CCDs must perform four primary tasks in generating an image, which are called charge generation, charge collection, charge transfer and charge measurement. In camera, the lenses are needed to input the optical signal to the CCD sensors, in which the techniques for erasing stray light are used. And the electron circuits are needed to process the output signal of CCD, in which many electronic techniques are used. The dazzling effects are the conjunct result of light distribution distortion and charge distribution distortion, which respectively derive from the lens and the sensor. Strictly speaking, in lens, the light distribution is not distorted. In general, the lens are so well designed and fabricated that its stray light can be neglected. But the laser is of much enough intensity to make its stray light obvious. In CCD image sensors, laser can induce a so large electrons generation. Charges transfer inefficiency and charges blooming will cause the distortion of the charge distribution. Commonly, the largest signal outputted from CCD sensor is restricted by capability of the collection well of CCD, and can't go beyond the dynamic range for the subsequent electron circuits maintaining normal work. So the signal is not distorted in the post-processing circuits. But some techniques in the circuit can make some dazzling effects present different phenomenon in final image.

Communications for unattended sensor networks

NASA Astrophysics Data System (ADS)

Nemeroff, Jay L.; Angelini, Paul; Orpilla, Mont; Garcia, Luis; DiPierro, Stefano

2004-07-01

The future model of the US Army's Future Combat Systems (FCS) and the Future Force reflects a combat force that utilizes lighter armor protection than the current standard. Survival on the future battlefield will be increased by the use of advanced situational awareness provided by unattended tactical and urban sensors that detect, identify, and track enemy targets and threats. Successful implementation of these critical sensor fields requires the development of advanced sensors, sensor and data-fusion processors, and a specialized communications network. To ensure warfighter and asset survivability, the communications must be capable of near real-time dissemination of the sensor data using robust, secure, stealthy, and jam resistant links so that the proper and decisive action can be taken. Communications will be provided to a wide-array of mission-specific sensors that are capable of processing data from acoustic, magnetic, seismic, and/or Chemical, Biological, Radiological, and Nuclear (CBRN) sensors. Other, more powerful, sensor node configurations will be capable of fusing sensor data and intelligently collect and process data images from infrared or visual imaging cameras. The radio waveform and networking protocols being developed under the Soldier Level Integrated Communications Environment (SLICE) Soldier Radio Waveform (SRW) and the Networked Sensors for the Future Force Advanced Technology Demonstration are part of an effort to develop a common waveform family which will operate across multiple tactical domains including dismounted soldiers, ground sensor, munitions, missiles and robotics. These waveform technologies will ultimately be transitioned to the JTRS library, specifically the Cluster 5 requirement.

Study on intelligent processing system of man-machine interactive garment frame model

NASA Astrophysics Data System (ADS)

Chen, Shuwang; Yin, Xiaowei; Chang, Ruijiang; Pan, Peiyun; Wang, Xuedi; Shi, Shuze; Wei, Zhongqian

2018-05-01

A man-machine interactive garment frame model intelligent processing system is studied in this paper. The system consists of several sensor device, voice processing module, mechanical parts and data centralized acquisition devices. The sensor device is used to collect information on the environment changes brought by the body near the clothes frame model, the data collection device is used to collect the information of the environment change induced by the sensor device, voice processing module is used for speech recognition of nonspecific person to achieve human-machine interaction, mechanical moving parts are used to make corresponding mechanical responses to the information processed by data collection device.it is connected with data acquisition device by a means of one-way connection. There is a one-way connection between sensor device and data collection device, two-way connection between data acquisition device and voice processing module. The data collection device is one-way connection with mechanical movement parts. The intelligent processing system can judge whether it needs to interact with the customer, realize the man-machine interaction instead of the current rigid frame model.

Collecting and distributing wearable sensor data: an embedded personal area network to local area network gateway server.

PubMed

Neuhaeuser, Jakob; D'Angelo, Lorenzo T

2013-01-01

The goal of the concept and of the device presented in this contribution is to be able to collect sensor data from wearable sensors directly, automatically and wirelessly and to make them available over a wired local area network. Several concepts in e-health and telemedicine make use of portable and wearable sensors to collect movement or activity data. Usually these data are either collected via a wireless personal area network or using a connection to the user's smartphone. However, users might not carry smartphones on them while inside a residential building such as a nursing home or a hospital, but also within their home. Also, in such areas the use of other wireless communication technologies might be limited. The presented system is an embedded server which can be deployed in several rooms in order to ensure live data collection in bigger buildings. Also, the collection of data batches recorded out of range, as soon as a connection is established, is also possible. Both, the system concept and the realization are presented.

Delivering customized apps, multimedia and NASA data to libraries and their patrons

NASA Astrophysics Data System (ADS)

Harold, J. B.; Dusenbery, P.; Holland, A.; LaConte, K.; Johnson, A.; Randall, C.; Fitzhugh, G.

2017-12-01

With funding through NASA's Science Mission Directorate, the NASA @ My Library project has been working with the public library community to enhance the STEM literacy of library patrons throughout the nation. One element of the project is to disseminate a variety of materials to 75 partner libraries in order to support their implementation of hands-on, NASA related STEM activities for their patrons. These materials range from very low tech (UV beads) to high tech (a 4.5" Orion Dobsonian telescope), and include an 8" tablet. This tablet provides us with a wide range of possibilities for delivering NASA content. Besides NASA multimedia and real-time spacecraft data, the tablets can be used for interactive activities, including public apps as well as apps specifically designed for this program, such as a green screen app that incorporates NASA imagery as part of a larger storytelling activity. The tablets also include a full sensor suite (magnetometer, light sensor, accelerometer, etc.), allowing us to develop library activities that use the tablet as a measuring device - detecting magnetism in a "Meteorite or Wrong" activity, or using the light sensor as a transit device. The tablet is centrally managed and includes a "kiosk mode", allowing the libraries to use it in either a locked down or conventional mode. The management system also allows us to create a curated collection of apps and multimedia, push out updated software, and collect analytics data on how the tablet is being used. In this presentation we will discuss the library pre-survey that guided our tablet development process, as well as our lessons learned to date, including the practicality and effectiveness of deploying tablets at this scale, their ability to support NASA specific STEM efforts, and what we have learned about library usage.

Cloud Absorption Radiometer Autonomous Navigation System - CANS

NASA Technical Reports Server (NTRS)

Kahle, Duncan; Gatebe, Charles; McCune, Bill; Hellwig, Dustan

2013-01-01

CAR (cloud absorption radiometer) acquires spatial reference data from host aircraft navigation systems. This poses various problems during CAR data reduction, including navigation data format, accuracy of position data, accuracy of airframe inertial data, and navigation data rate. Incorporating its own navigation system, which included GPS (Global Positioning System), roll axis inertia and rates, and three axis acceleration, CANS expedites data reduction and increases the accuracy of the CAR end data product. CANS provides a self-contained navigation system for the CAR, using inertial reference and GPS positional information. The intent of the software application was to correct the sensor with respect to aircraft roll in real time based upon inputs from a precision navigation sensor. In addition, the navigation information (including GPS position), attitude data, and sensor position details are all streamed to a remote system for recording and later analysis. CANS comprises a commercially available inertial navigation system with integral GPS capability (Attitude Heading Reference System AHRS) integrated into the CAR support structure and data system. The unit is attached to the bottom of the tripod support structure. The related GPS antenna is located on the P-3 radome immediately above the CAR. The AHRS unit provides a RS-232 data stream containing global position and inertial attitude and velocity data to the CAR, which is recorded concurrently with the CAR data. This independence from aircraft navigation input provides for position and inertial state data that accounts for very small changes in aircraft attitude and position, sensed at the CAR location as opposed to aircraft state sensors typically installed close to the aircraft center of gravity. More accurate positional data enables quicker CAR data reduction with better resolution. The CANS software operates in two modes: initialization/calibration and operational. In the initialization/calibration mode, the software aligns the precision navigation sensors and initializes the communications interfaces with the sensor and the remote computing system. It also monitors the navigation data state for quality and ensures that the system maintains the required fidelity for attitude and positional information. In the operational mode, the software runs at 12.5 Hz and gathers the required navigation/attitude data, computes the required sensor correction values, and then commands the sensor to the required roll correction. In this manner, the sensor will stay very near to vertical at all times, greatly improving the resulting collected data and imagery. CANS greatly improves quality of resulting imagery and data collected. In addition, the software component of the system outputs a concisely formatted, high-speed data stream that can be used for further science data processing. This precision, time-stamped data also can benefit other instruments on the same aircraft platform by providing extra information from the mission flight.

Communication Needs Assessment for Distributed Turbine Engine Control (Postprint)

DTIC Science & Technology

2008-07-01

and implementation, and enable new opportunities for performance optimization and increased awareness about system health. The transition from a...must be integrated into the communication network.10 These could include new sensors, actuators, or even complex subsystems for more advanced...No. 0704-0188 The public reporting burden for this collection of information is estimated to average 1 hour per response, including the time for

Using Machine Learning to Increase Research Efficiency: A New Approach in Environmental Sciences

USDA-ARS?s Scientific Manuscript database

Data collection has evolved from tedious in-person fieldwork to automatic data gathering from multiple sensor remotely. Scientist in environmental sciences have not fully exploited this data deluge, including legacy and new data, because the traditional scientific method is focused on small, high qu...

Space trajectory calculation based on G-sensor

NASA Astrophysics Data System (ADS)

Xu, Biya; Zhan, Yinwei; Shao, Yang

2017-08-01

At present, without full use of the mobile phone around us, most of the research in human body posture recognition field is use camera or portable acceleration sensor to collect data. In this paper, G-sensor built-in mobile phone is use to collect data. After processing data with the way of moving average filter and acceleration integral, joint point's space three-dimensional coordinates can be abtained accurately.

Sensor Fish Communicator

DOE Office of Scientific and Technical Information (OSTI.GOV)

The Sensor Fish collects information that can be used to evaluate conditions encountered by juvenile salmonids and other fish as they pass through hydroelectric dams on their way to the ocean. Sensor Fish are deployed in turbines, spillways, and sluiceways and measure changes in pressure, angular rate of change, and linear acceleration during passage. The software is need to make Sensor Fish fully functional and easy to use. Sensor Fish Communicator (SFC) links to Sensor Fish, allowing users to control data collection settings and download data. It may also be used to convert native raw data (.raw2) files into Commamore » Separated Variable (.csv) files and plot the results. The multiple capabilities of the SFC allow hardware communication, data conversion, and data plotting with one application.« less

Opportunistic Sensor Data Collection with Bluetooth Low Energy

PubMed Central

Aguilar, Sergio; Vidal, Rafael; Gomez, Carles

2017-01-01

Bluetooth Low Energy (BLE) has gained very high momentum, as witnessed by its widespread presence in smartphones, wearables and other consumer electronics devices. This fact can be leveraged to carry out opportunistic sensor data collection (OSDC) in scenarios where a sensor node cannot communicate with infrastructure nodes. In such cases, a mobile entity (e.g., a pedestrian or a vehicle) equipped with a BLE-enabled device can collect the data obtained by the sensor node when both are within direct communication range. In this paper, we characterize, both analytically and experimentally, the performance and trade-offs of BLE as a technology for OSDC, for the two main identified approaches, and considering the impact of its most crucial configuration parameters. Results show that a BLE sensor node running on a coin cell battery can achieve a lifetime beyond one year while transferring around 10 Mbit/day, in realistic OSDC scenarios. PMID:28124987

Opportunistic Sensor Data Collection with Bluetooth Low Energy.

PubMed

Aguilar, Sergio; Vidal, Rafael; Gomez, Carles

2017-01-23

Bluetooth Low Energy (BLE) has gained very high momentum, as witnessed by its widespread presence in smartphones, wearables and other consumer electronics devices. This fact can be leveraged to carry out opportunistic sensor data collection (OSDC) in scenarios where a sensor node cannot communicate with infrastructure nodes. In such cases, a mobile entity (e.g., a pedestrian or a vehicle) equipped with a BLE-enabled device can collect the data obtained by the sensor node when both are within direct communication range. In this paper, we characterize, both analytically and experimentally, the performance and trade-offs of BLE as a technology for OSDC, for the two main identified approaches, and considering the impact of its most crucial configuration parameters. Results show that a BLE sensor node running on a coin cell battery can achieve a lifetime beyond one year while transferring around 10 Mbit/day, in realistic OSDC scenarios.

Recent developments in sensing methods for eutrophying nutrients with a focus on automation for environmental applications.

PubMed

Duffy, G; Regan, F

2017-11-20

The demand for autonomous sensors for unattended, continuous nutrient monitoring in water is rapidly growing with the increasing need for more frequent and widespread environmental pollution monitoring. Legislative bodies, local authorities and industries all require frequent water quality monitoring, however, this is time and labour intensive, and an expensive undertaking. Autonomous sensors allow for frequent, unattended data collection. While this solves the time and labour intensive aspects of water monitoring, sensors can be very expensive. Development of low-cost sensors is essential to realise the concept of Internet of Things (IoT). However there is much work yet to be done in this field. This article reviews current literature on the research and development efforts towards deployable autonomous sensors for phosphorus (in the form of phosphate) and nitrogen (in the form of nitrate), with a focus on analytical performance and cost considerations. Additionally, some recent sensing approaches that could be automated in the future are included, along with an overview of approaches to monitoring both nutrients. These approaches are compared with standard laboratory methods and also with commercially available sensors for both phosphate and nitrate. Application of nutrient sensors in agriculture is discussed as an example of how sensor networks can provide improvements in decision making.

Experimenting with an Evolving Ground/Space-based Software Architecture to Enable Sensor Webs

NASA Technical Reports Server (NTRS)

mandl, Daniel; Frye, Stuart

2005-01-01

A series of ongoing experiments are being conducted at the NASA Goddard Space Flight Center to explore integrated ground and space-based software architectures enabling sensor webs. A sensor web, as defined by Steve Talabac at NASA Goddard Space Flight Center(GSFC), is a coherent set of distributed nodes interconnected by a communications fabric, that collectively behave as a single, dynamically adaptive, observing system. The nodes can be comprised of satellites, ground instruments, computing nodes etc. Sensor web capability requires autonomous management of constellation resources. This becomes progressively more important as more and more satellites share resource, such as communication channels and ground station,s while automatically coordinating their activities. There have been five ongoing activities which include an effort to standardize a set of middleware. This paper will describe one set of activities using the Earth Observing 1 satellite, which used a variety of ground and flight software along with other satellites and ground sensors to prototype a sensor web. This activity allowed us to explore where the difficulties that occur in the assembly of sensor webs given today s technology. We will present an overview of the software system architecture, some key experiments and lessons learned to facilitate better sensor webs in the future.

Wireless sensor network for monitoring soil moisture and weather conditions

USDA-ARS?s Scientific Manuscript database

A wireless sensor network (WSN) was developed and deployed in three fields to monitor soil water status and collect weather data for irrigation scheduling. The WSN consists of soil-water sensors, weather sensors, wireless data loggers, and a wireless modem. Soil-water sensors were installed at three...

Intelligent On-Board Processing in the Sensor Web

NASA Astrophysics Data System (ADS)

Tanner, S.

2005-12-01

Most existing sensing systems are designed as passive, independent observers. They are rarely aware of the phenomena they observe, and are even less likely to be aware of what other sensors are observing within the same environment. Increasingly, intelligent processing of sensor data is taking place in real-time, using computing resources on-board the sensor or the platform itself. One can imagine a sensor network consisting of intelligent and autonomous space-borne, airborne, and ground-based sensors. These sensors will act independently of one another, yet each will be capable of both publishing and receiving sensor information, observations, and alerts among other sensors in the network. Furthermore, these sensors will be capable of acting upon this information, perhaps altering acquisition properties of their instruments, changing the location of their platform, or updating processing strategies for their own observations to provide responsive information or additional alerts. Such autonomous and intelligent sensor networking capabilities provide significant benefits for collections of heterogeneous sensors within any environment. They are crucial for multi-sensor observations and surveillance, where real-time communication with external components and users may be inhibited, and the environment may be hostile. In all environments, mission automation and communication capabilities among disparate sensors will enable quicker response to interesting, rare, or unexpected events. Additionally, an intelligent network of heterogeneous sensors provides the advantage that all of the sensors can benefit from the unique capabilities of each sensor in the network. The University of Alabama in Huntsville (UAH) is developing a unique approach to data processing, integration and mining through the use of the Adaptive On-Board Data Processing (AODP) framework. AODP is a key foundation technology for autonomous internetworking capabilities to support situational awareness by sensors and their on-board processes. The two primary research areas for this project are (1) the on-board processing and communications framework itself, and (2) data mining algorithms targeted to the needs and constraints of the on-board environment. The team is leveraging its experience in on-board processing, data mining, custom data processing, and sensor network design. Several unique UAH-developed technologies are employed in the AODP project, including EVE, an EnVironmEnt for on-board processing, and the data mining tools included in the Algorithm Development and Mining (ADaM) toolkit.

Sensor-centric calibration and characterization of the VIIRS Ocean Color bands using Suomi NPP operational data

NASA Astrophysics Data System (ADS)

Pratt, P.

2012-12-01

Ocean color bands on VIIRS span the visible spectrum and include two NIR bands. There are sixteen detectors per band and two HAM (Half-angle mirror) sides giving a total of thirty two independent systems. For each scan, thirty two hundred pixels are collected and each has a fixed specific optical path and a dynamic position relative to the earth geoid. For a given calibration target where scene variation is minimized, sensor characteristics can be observed. This gives insight into the performance and calibration of the instrument from a sensor-centric perspective. Calibration of the blue bands is especially challenging since there are few blue targets on land. An ocean region called the South Pacific Gyre (SPG) was chosen for its known stability and large area to serve as a calibration target for this investigation. Thousands of pixels from every granule that views the SPG are collected daily through an automated system and tabulated along with the detector, HAM and scan position. These are then collated and organized in a sensor-centric set of tables. The data are then analyzed by slicing by each variable and then plotted in a number of ways over time. Trends in the data show that the VIIRS sensor is largely behaving as expected according to heritage data and also reveals weaknesses where additional characterization of the sensor is possible. This work by Northrop Grumman NPP CalVal Team is supporting the VIIRS on-orbit calibration and validation teams for the sensor and ocean color as well as providing scientists interested in performing ground truth with results that show which detectors and scan angles are the most reliable over time. This novel approach offers a comprehensive sensor-centric on-orbit characterization of the VIIRS instrument on the NASA Suomi NPP mission.

Viral vectors for gene modification of plants as chem/bio sensors.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Manginell, Monica; Harper, Jason C.; Arango, Dulce C.

2006-11-01

Chemical or biological sensors that are specific, sensitive, and robust allowing intelligence gathering for verification of nuclear non-proliferation treaty compliance and detouring production of weapons of mass destruction are sorely needed. Although much progress has been made in the area of biosensors, improvements in sensor lifetime, robustness, and device packaging are required before these devices become widely used. Current chemical and biological detection and identification techniques require less-than-covert sample collection followed by transport to a laboratory for analysis. In addition to being expensive and time consuming, results can often be inconclusive due to compromised sample integrity during collection and transport.more » We report here a demonstration of a plant based sensor technology which utilizes mature and seedling plants as chemical sensors. One can envision genetically modifying native plants at a site of interest that can report the presence of specific toxins or chemicals. In this one year project we used a developed inducible expression system to show the feasibility of plant sensors. The vector was designed as a safe, non-infectious vector which could be used to invade, replicate, and introduce foreign genes into mature host plants that then allow the plant to sense chem/bio agents. The genes introduced through the vector included a reporter gene that encodes for green fluorescent protein (GFP) and a gene that encodes for a mammalian receptor that recognizes a chemical agent. Specifically, GFP was induced by the presence of 17-{beta}-Estradiol (estrogen). Detection of fluorescence indicated the presence of the target chemical agent. Since the sensor is a plant, costly device packaging development or manufacturing of the sensor were not required. Additionally, the biological recognition and reporting elements are maintained in a living, natural environment and therefore do not suffer from lifetime disadvantages typical of most biosensing platforms. Detection of the chem/bio agent reporter (GFP) can be detected only at a specific wavelength.« less

Cyber security and data collection approaches for smartphone sensor systems

NASA Astrophysics Data System (ADS)

Turner, Hamilton; White, Jules

2012-06-01

In recent years the ubiquity and resources provided by smartphone devices have encouraged scientists to explore using these devices as remote sensing nodes. In addition, the United States Department of Defense has stated a mission of increasing persistent intelligence, surveillance, and reconnaissance capabilities or U.S. units. This paper presents a method of enabling large-scale, long-term smartphone-powered data collection. Key solutions discussed include the ability to directly allow domain experts to define and refine smartphone applications for data collection, technical advancements that allow rapid dissemination of a smartphone data collection application, and an algorithm for preserving the locational privacy of participating users.

A perception and manipulation system for collecting rock samples

NASA Technical Reports Server (NTRS)

Choi, T.; Delingette, H.; Deluise, M.; Hsin, Y.; Hebert, M.; Ikeuchi, Katsushi

1991-01-01

An important part of a planetary exploration mission is to collect and analyze surface samples. As part of the Carnegie Mellon University Ambler Project, researchers are investigating techniques for collecting samples using a robot arm and a range sensor. The aim of this work is to make the sample collection operation fully autonomous. Described here are the components of the experimental system, including a perception module that extracts objects of interest from range images and produces models of their shapes, and a manipulation module that enables the system to pick up the objects identified by the perception module. The system was tested on a small testbed using natural terrain.

A Multi-Sensor Aerogeophysical Study of Afghanistan

DTIC Science & Technology

2007-01-01

magnetometer coupled with an Applied Physics 539 3-axis fluxgate mag- netometer for compensation of the aircraft field; • an Applanix DSS 301 digital...survey. DATA COlleCTION AND PROCeSSINg Photogrammetry More than 65,000 high-resolution photogram- metric images were collected using an Applanix Digital...HSI L-Band Polarimetric Imaging Radar KGPS Dual Gravity Meters Common Sensor Bomb-bay Pallet Applanix DSS Camera Sensor Suite • Magnetometer • Gravity

The Sensor Test for Orion RelNav Risk Mitigation Development Test Objective

NASA Technical Reports Server (NTRS)

Christian, John A.; Hinkel, Heather; Maguire, Sean

2011-01-01

The Sensor Test for Orion Relative-Navigation Risk Mitigation (STORRM) Development Test Objective (DTO) ew aboard the Space Shuttle Endeavour on STS-134, and was designed to characterize the performance of the ash LIDAR being developed for the Orion. This ash LIDAR, called the Vision Navigation Sensor (VNS), will be the primary navigation instrument used by the Orion vehicle during rendezvous, proximity operations, and docking. This paper provides an overview of the STORRM test objectives and the concept of operations. It continues with a description of the STORRM's major hardware compo nents, which include the VNS and the docking camera. Next, an overview of crew and analyst training activities will describe how the STORRM team prepared for flight. Then an overview of how insight data collection and analysis actually went is presented. Key ndings and results from this project are summarized, including a description of "truth" data. Finally, the paper concludes with lessons learned from the STORRM DTO.

An Ultrasonic Sampler and Sensor Platform for In-Situ Astrobiological Exploration

NASA Technical Reports Server (NTRS)

Bar-Cohen, Yoaz E.; Bao, X.; Chang, Z.; Sherrit, S.

2003-01-01

The search for existing or past life in the Universe is one of the most important objectives of NASA's mission. In support of this objective, ultrasonic based mechanisms are currently being developed at JPL to allow probing and sampling rocks as well as perform as a sensor platform for in-situ astrobiological analysis. The technology is based on the novel Ultrasonic/Sonic Driller/Corer (USDC), which requires low axial force, thereby overcoming one of the major limitations of planetary sampling in low gravity using conventional drills. The USDC was demonstrated to: 1) drill ice and various rocks including granite, diorite, basalt and limestone, 2) not require bit sharpening, and 3) operate at high and low temperatures. The capabilities that are being investigated including probing the ground to select sampling sites, collecting various forms of samples, and hosting sensors for measuring chemical/physical properties. A series of modifications of the USDC basic configuration were implemented leading an ultrasonic abrasion tool (URAT), Ultrasonic Gopher for deep Drilling, and the lab-on-a-drill.

Wireless Integrated Microelectronic Vacuum Sensor System

NASA Technical Reports Server (NTRS)

Krug, Eric; Philpot, Brian; Trott, Aaron; Lawrence, Shaun

2013-01-01

NASA Stennis Space Center's (SSC's) large rocket engine test facility requires the use of liquid propellants, including the use of cryogenic fluids like liquid hydrogen as fuel, and liquid oxygen as an oxidizer (gases which have been liquefied at very low temperatures). These fluids require special handling, storage, and transfer technology. The biggest problem associated with transferring cryogenic liquids is product loss due to heat transfer. Vacuum jacketed piping is specifically designed to maintain high thermal efficiency so that cryogenic liquids can be transferred with minimal heat transfer. A vacuum jacketed pipe is essentially two pipes in one. There is an inner carrier pipe, in which the cryogenic liquid is actually transferred, and an outer jacket pipe that supports and seals the vacuum insulation, forming the "vacuum jacket." The integrity of the vacuum jacketed transmission lines that transfer the cryogenic fluid from delivery barges to the test stand must be maintained prior to and during engine testing. To monitor the vacuum in these vacuum jacketed transmission lines, vacuum gauge readings are used. At SSC, vacuum gauge measurements are done on a manual rotation basis with two technicians, each using a handheld instrument. Manual collection of vacuum data is labor intensive and uses valuable personnel time. Additionally, there are times when personnel cannot collect the data in a timely fashion (i.e., when a leak is detected, measurements must be taken more often). Additionally, distribution of this data to all interested parties can be cumbersome. To simplify the vacuum-gauge data collection process, automate the data collection, and decrease the labor costs associated with acquiring these measurements, an automated system that monitors the existing gauges was developed by Invocon, Inc. For this project, Invocon developed a Wireless Integrated Microelectronic Vacuum Sensor System (WIMVSS) that provides the ability to gather vacuum-gauge measurements automatically and wirelessly, in near-real time - using a low-maintenance, lowpower sensor mesh network. The WIMVSS operates by using a self-configuring mesh network of wireless sensor units. Mesh networking is a type of networking where each sensor or node can capture and disseminate its own data, but also serve as a relay to receive and transmit data from other sensors. Each sensor node can synchronize with adjacent sensors, and propagate data from one sensor to the next, until the destination is reached. In this case, the destination is a Network Interface Unit (NIU). The WIMVSS sensors are mounted on the existing vacuum gauges. Information gathered by the sensors is sent to the NIU. Because of the mesh networking, if a sensor cannot directly send the data to the NIU, it can be propagated through the network of sensors. The NIU requires antenna access to the sensor units, AC power, and an Ethernet connection. The NIU bridges the sensor network to a WIMVSS server via an Ethernet connection. The server is configured with a database, a Web server, and proprietary interface software that makes it possible for the vacuum measurements from vacuum jacketed fluid lines to be saved, retrieved, and then displayed from any Web-enabled PC that has access to the Internet. Authorized users can then simply access the data from any PC with Internet connection. Commands can also be sent directly from the Web interface for control and maintenance of the sensor network. The technology enabled by the WIMVSS decreases labor required for gathering vacuum measurements, increases access to vacuum data by making it available on any computer with access to the Internet, increases the frequency with which data points can be acquired for evaluating the system, and decreases the recurring cost of the sensors by using off-the-shelf components and integrating these with heritage vacuum gauges.

SWE-based Observation Data Delivery from the Instrument to the User - Sensor Web Technology in the NeXOS Project

NASA Astrophysics Data System (ADS)

Jirka, Simon; del Rio, Joaquin; Toma, Daniel; Martinez, Enoc; Delory, Eric; Pearlman, Jay; Rieke, Matthes; Stasch, Christoph

2017-04-01

The rapidly evolving technology for building Web-based (spatial) information infrastructures and Sensor Webs, there are new opportunities to improve the process how ocean data is collected and managed. A central element in this development is the suite of Sensor Web Enablement (SWE) standards specified by the Open Geospatial Consortium (OGC). This framework of standards comprises on the one hand data models as well as formats for measurement data (ISO/OGC Observations and Measurement, O&M) and metadata describing measurement processes and sensors (OGC Sensor Model Language, SensorML). On the other hand the SWE standards comprise (Web service) interface specifications for pull-based access to observation data (OGC Sensor Observation Service, SOS) and for controlling or configuring sensors (OGC Sensor Planning Service, SPS). Also within the European INSPIRE framework the SWE standards play an important role as the SOS is the recommended download service interface for O&M-encoded observation data sets. In the context of the EU-funded Oceans of Tomorrow initiative the NeXOS (Next generation, Cost-effective, Compact, Multifunctional Web Enabled Ocean Sensor Systems Empowering Marine, Maritime and Fisheries Management) project is developing a new generation of in-situ sensors that make use of the SWE standards to facilitate the data publication process and the integration into Web based information infrastructures. This includes the development of a dedicated firmware for instruments and sensor platforms (SEISI, Smart Electronic Interface for Sensors and Instruments) maintained by the Universitat Politècnica de Catalunya (UPC). Among other features, SEISI makes use of OGC SWE standards such OGC-PUCK, to enable a plug-and-play mechanism for sensors based on SensorML encoded metadata. Thus, if a new instrument is attached to a SEISI-based platform, it automatically configures the connection to these instruments, automatically generated data files compliant with the ISO/OGC Observations and Measurements standard and initiates the data transmission into the NeXOS Sensor Web infrastructure. Besides these platform-related developments, NeXOS has realised the full path of data transmission from the sensor to the end user application. The conceptual architecture design is implemented by a series of open source SWE software packages provided by 52°North. This comprises especially different SWE server components (i.e. OGC Sensor Observation Service), tools for data visualisation (e.g. the 52°North Helgoland SOS viewer), and an editor for providing SensorML-based metadata (52°North smle). As a result, NeXOS has demonstrated how the SWE standards help to improve marine observation data collection. Within this presentation, we will present the experiences and findings of the NeXOS project and will provide recommendation for future work directions.

Aircraft scatterometer observations of soil moisture on rangeland watersheds

NASA Technical Reports Server (NTRS)

Jackson, T. J.; Oneill, P. E.

1983-01-01

Extensive studies conducted by several researchers using truck-mounted active microwave sensors have shown the sensitivity of these sensors to soil moisture variations. The logical extension of these results is the evaluation of similar systems at lower resolutions typical of operational systems. Data collected during a series of aircraft flights in 1978 and 1980 over four rangeland watersheds located near Chickasha, Oklahoma, were analyzed in this study. These data included scatterometer measurements made at 1.6 and 4.75 GHz using a NASA aircraft and ground observations of soil moisture for a wide range of moisture conditions. Data were analyzed for consistency and compared to previous truck and aircraft results. Results indicate that the sensor system is capable of providing consistent estimates of soil moisture under the conditions tested.

Characterization of chromium compensated GaAs as an X-ray sensor material for charge-integrating pixel array detectors

NASA Astrophysics Data System (ADS)

Becker, J.; Tate, M. W.; Shanks, K. S.; Philipp, H. T.; Weiss, J. T.; Purohit, P.; Chamberlain, D.; Gruner, S. M.

2018-01-01

We studied the properties of chromium compensated GaAs when coupled to charge integrating ASICs as a function of detector temperature, applied bias and X-ray tube energy. The material is a photoresistor and can be biased to collect either electrons or holes by the pixel circuitry. Both are studied here. Previous studies have shown substantial hole trapping. This trapping and other sensor properties give rise to several non-ideal effects which include an extended point spread function, variations in the effective pixel size, and rate dependent offset shifts. The magnitude of these effects varies with temperature and bias, mandating good temperature uniformity in the sensor and very good temperature stabilization, as well as a carefully selected bias voltage.

Improving control and estimation for distributed parameter systems utilizing mobile actuator-sensor network.

PubMed

Mu, Wenying; Cui, Baotong; Li, Wen; Jiang, Zhengxian

2014-07-01

This paper proposes a scheme for non-collocated moving actuating and sensing devices which is unitized for improving performance in distributed parameter systems. By Lyapunov stability theorem, each moving actuator/sensor agent velocity is obtained. To enhance state estimation of a spatially distributes process, two kinds of filters with consensus terms which penalize the disagreement of the estimates are considered. Both filters can result in the well-posedness of the collective dynamics of state errors and can converge to the plant state. Numerical simulations demonstrate that the effectiveness of such a moving actuator-sensor network in enhancing system performance and the consensus filters converge faster to the plant state when consensus terms are included. Copyright © 2014 ISA. Published by Elsevier Ltd. All rights reserved.

Observations of Gas Emissions from Cascade Range Volcanoes (USA) using a Portable Real-Time Sensor Package and Evacuated Flasks

NASA Astrophysics Data System (ADS)

Kelly, P. J.; Werner, C. A.; Evans, W.; Ingebritsen, S.; Tucker, D.

2012-12-01

Degassing from most Cascade Range Volcanoes, USA, is characterized by low-temperature hydrothermal emissions. It is important to monitor these emissions as part of a comprehensive monitoring strategy yet access is often difficult and most features are sampled by the USGS only once per year at best. In an effort to increase the sampling frequency of major gas species and in preparation for building permanent, autonomous units, we built a portable sensor package capable of measuring H2O, CO2, SO2, and H2S in volcanic gas plumes. Here we compare results from the portable sensor package with gas analyses from direct samples obtained using a titanium tube and evacuated glass flasks collected at the same time. The sensor package is housed in a small, rugged case, weighs 5 kg, and includes sensors for measuring H2O (0-16 parts per thousand), CO2 (0-5000 ppmv), SO2 (0-100 ppm), and H2S (0-20 ppm) gases. Additional temperature and pressure sensors, a micro air pump, datalogger, and an internal battery are also incorporated. H2O and CO2 are measured using an infrared spectrometer (Licor 840) and sulfur-containing gases are measured using electrochemical sensors equipped with filters to mitigate cross-sensitivities. Data are collected at a 1 Hz sampling rate and can be recorded and displayed in real-time using a netbook computer or can be saved to the onboard datalogger. The data display includes timeseries of H2O, CO2, SO2, and H2S mixing ratios, the four-component bulk composition of the plume, and automated calculation of gas ratios commonly used in volcanic gas monitoring, such as H2O/CO2, CO2/SO2, and CO2/H2S . In the Cascade Range, the sensor package has been tested at Mt. Baker, Mt. St. Helens, Mt. Hood, and in Lassen Volcanic National Park. In each case, the instrument was placed 5 to 30 meters from the fumarole or fumarole field and emissions were sampled for 5 to 30 minutes. No SO2 was detected at any location. At Mt. Hood the sensor package yielded average CO2/H2S ratios from 10 to 16 in fumarole plumes versus flask CO2/H2S ratios (n = 2) of 13 and 16 on 9 July 2011, and on 28 July 2012 the sensor package yielded an average CO2/H2S ratio of 12 versus flask ratios (n = 2) of 13 (both sets of flask samples obtained in the Crater Rock area). At Mt. Baker, the sensor package yielded average CO2/H2S ratios from 19 to 22 whereas flask ratios (n = 3) were higher, from 25 to 32 (both fumarole-plume and flask samples obtained in the Sherman Crater area) on 22 July 2011. The mismatch falls slightly outside expected analytical uncertainty for the sensor package (about 20% relative for CO2/H2S ratios). However, flask samples collected in Sherman Crater in 2006 and 2007 (n = 5) yielded CO2/H2S ratios from 18 to 29, which nearly spans the range of observations in 2011. Therefore, one explanation for the small mismatch between the results of the sensor package and direct samples is that the sensor package measures bulk plume compositions that may integrate emissions from several chemically distinct fumaroles and the direct samples better represent the composition of discrete vents. Overall, the sensor package and evacuated flask data show good agreement and demonstrate that the real-time technique is a viable means for monitoring major volcanic gas species.

Soil Moisture Estimation Using Hyperspectral SWIR Imagery

NASA Astrophysics Data System (ADS)

Lewis, D.

2007-12-01

The U.S. Geological Survey (USGS) is engaged with the U.S. Department of Agriculture's (USDA) Agricultural Research Service (ARS) and the University of Georgia's National Environmentally Sound Production Agriculture Laboratory (NESPAL) both in Tifton, Georgia, USA, to develop transformations for medium and high resolution remotely sensed images to generate moisture indicators for soil. The Institute for Technology Development (ITD) is located at the Stennis Space Center in southern Mississippi and has developed hyperspectral sensor systems that, when mounted in aircraft, collect electromagnetic reflectance data of the terrain. The sensor suite consists of sensors for three different sections of the electromagnetic spectrum; the Ultra-Violet (UV), Visible/Near InfraRed (VNIR) and Short Wave InfraRed (SWIR). The USDA/ ARS' Southeast Watershed Research Laboratory has probes that measure and record soil moisture. Data taken from the ITD SWIR sensor and the USDA/ARS soil moisture meters were analyzed to study the informatics relationships between SWIR data and measured soil moisture. The geographic locations of 29 soil moisture meters provided by the USDA/ARS are in the vicinity of Tifton, Georgia. Using USGS Digital Ortho Quads (DOQ), flightlines were drawn over the 29 soil moisture meters. The SWIR sensor was installed into an aircraft. The coordinates for the flightlines were also loaded into the navigational system of the aircraft. This airborne platform was used to collect the data over these flightlines. In order to prepare the data set for analysis, standard preprocessing was performed. These standard processes included sensor calibration, spectral subsetting, and atmospheric calibration. All 60 bands of the SWIR data were collected for each line in the image data, 15 bands of which were stripped from the data set leaving 45 bands of information in the wavelength range of 906 to 1705 nanometers. All the image files were calibrated using the regression equations generated by using radiometer data collected over calibration tarps. Regions of Interest (ROI) were drawn over the image data set corresponding with the location of the soil moisture meters. Scripts written in ENVI's Interactive Data Language (IDL) were developed to extract the spectra from each of the processed hyperspectral image data over each soil moisture meter from its corresponding ROI. The informatics relationship between soil moisture and SWIR spectra was identified by using the resulting data set.

The International Space Station: New Capabilities for Disaster Response and Humanitarian Aid

NASA Technical Reports Server (NTRS)

Stefanov, William

2012-01-01

The International Space Station (ISS) has been acquiring Earth imagery since 2000, primarily in the form of astronaut photography using hand-held film and digital cameras. Recent additions of more sophisticated multispectral and hyperspectral sensor systems have expanded both the capabilities and relevance of the ISS to basic research, applied Earth science, and development of new sensor technologies. Funding opportunities established within NASA, the US National Laboratories and the international partner organizations have generated instrument proposals that will further enhance these capabilities. With both internal and external sensor location options, and the availability of both automated and human-tended operational environments, the ISS is a unique platform within the constellation of Earth-observing satellites currently in orbit. Current progress and challenges associated with development of ISS terrestrial remote sensing capabilities in the area of disaster response and support of relief efforts will be presented. The ISS orbit allows for imaging of the Earth's surface at varying times of day and night, providing opportunities for data collection over approximately 95% of the populated regions. These opportunities are distinct from--yet augment--the data collection windows for the majority of sensors on polar-orbiting satellites. In addition to this potential for "being in the right place at the right time" to collect critical information on an evolving disaster, the presence of a human crew also allows for immediate recognition of an event from orbit, notification of relevant organizations on the ground, and re-tasking of available remote sensing resources to support humanitarian response and relief efforts. Challenges to establishing an integrated response capability are both technical (coordination of sensor targeting and data collection, rapid downlink and posting of data to a central accessible hub, timely generation and distribution of relevant data products) and operational (notification and engagement of sensor support teams, international partner agency sanction of astronaut support activities). To better collaborate on common issues and strengthen applications, including using the data to support disaster response, we established an ISS Program Science Forum Working Group for Earth Observations comprised of representatives from the international partner agencies. This international forum welcomes input and support from relevant United Nations task groups regarding our disaster response and humanitarian aid to enable development of the ISS capabilities in this area for greatest value to the international community.

Fabrication and characterization of resonant SOI micromechanical silicon sensors based on DRIE micromachining, freestanding release process and silicon direct bonding

NASA Astrophysics Data System (ADS)

Gigan, Olivier; Chen, Hua; Robert, Olivier; Renard, Stephane; Marty, Frederic

2002-11-01

This paper is dedicated to the fabrication and technological aspect of a silicon microresonator sensor. The entire project includes the fabrication processes, the system modelling/simulation, and the electronic interface. The mechanical model of such resonator is presented including description of frequency stability and Hysterises behaviour of the electrostatically driven resonator. Numeric model and FEM simulations are used to simulate the system dynamic behaviour. The complete fabrication process is based on standard microelectronics technology with specific MEMS technological steps. The key steps are described: micromachining on SOI by Deep Reactive Ion Etching (DRIE), specific release processes to prevent sticking (resist and HF-vapour release process) and collective vacuum encapsulation by Silicon Direct Bonding (SDB). The complete process has been validated and prototypes have been fabricated. The ASIC was designed to interface the sensor and to control the vibration amplitude. This electronic was simulated and designed to work up to 200°C and implemented in a standard 0.6μ CMOS technology. Characterizations of sensor prototypes are done both mechanically and electrostatically. These measurements showed good agreements with theory and FEM simulations.

Integrated monitoring of wind plant systems

NASA Astrophysics Data System (ADS)

Whelan, Matthew J.; Janoyan, Kerop D.; Qiu, Tong

2008-03-01

Wind power is a renewable source of energy that is quickly gaining acceptance by many. Advanced sensor technologies have currently focused solely on improving wind turbine rotor aerodynamics and increasing of the efficiency of the blade design and concentration. Alternatively, potential improvements in wind plant efficiency may be realized through reduction of reactionary losses of kinetic energy to the structural and substructural systems supporting the turbine mechanics. Investigation of the complete dynamic structural response of the wind plant is proposed using a large-scale, high-rate wireless sensor network. The wireless network enables sensors to be placed across the sizable structure, including the rotating blades, without consideration of cabling issues and the economic burden associated with large spools of measurement cables. A large array of multi-axis accelerometers is utilized to evaluate the modal properties of the system as well as individual members and would enable long-term structural condition monitoring of the wind turbine as well. Additionally, environmental parameters, including wind speed, temperature, and humidity, are wirelessly collected for correlation. Such a wireless system could be integrated with electrical monitoring sensors and actuators and incorporated into a remote multi-turbine centralized plant monitoring and control system.

Coordinating an Autonomous Earth-Observing Sensorweb

NASA Technical Reports Server (NTRS)

Sherwood, Robert; Cichy, Benjamin; Tran, Daniel; Chien, Steve; Rabideau, Gregg; Davies, Ashley; Castano, Rebecca; frye, Stuart; Mandl, Dan; Shulman, Seth;

Monitoring human health behaviour in one's living environment: a technological review.

PubMed

Lowe, Shane A; Ólaighin, Gearóid

2014-02-01

The electronic monitoring of human health behaviour using computer techniques has been an active research area for the past few decades. A wide array of different approaches have been investigated using various technologies including inertial sensors, Global Positioning System, smart homes, Radio Frequency IDentification and others. It is only in recent years that research has turned towards a sensor fusion approach using several different technologies in single systems or devices. These systems allow for an increased volume of data to be collected and for activity data to be better used as measures of behaviour. This change may be due to decreasing hardware costs, smaller sensors, increased power efficiency or increases in portability. This paper is intended to act as a reference for the design of multi-sensor behaviour monitoring systems. The range of technologies that have been used in isolation for behaviour monitoring both in research and commercial devices are reviewed and discussed. Filtering, range, sensitivity, usability and other considerations of different technologies are discussed. A brief overview of commercially available activity monitors and their technology is also included. Copyright © 2013 IPEM. Published by Elsevier Ltd. All rights reserved.

Test/QA Plan for Verification of Nitrate Sensors for Groundwater Remediation Monitoring

EPA Science Inventory

A submersible nitrate sensor is capable of collecting in-situ measurements of dissolved nitrate concentrations in groundwater. Although several types of nitrate sensors currently exist, this verification test will focus on submersible sensors equipped with a nitrate-specific ion...

Sinkhole Avoidance Routing in Wireless Sensor Networks

DTIC Science & Technology

2011-05-09

sensor network consists of individual sensor nodes that work cooperatively to collect and communicate environmental data. In a surveillance role, a WSN...Wireless sensor networks, or WSNs, are an emerging commercial technology that may have practical applications on the modern battlefield. A wireless

Implementation of a multi-modal mobile sensor system for surface and subsurface assessment of roadways

NASA Astrophysics Data System (ADS)

Wang, Ming; Birken, Ralf; Shahini Shamsabadi, Salar

2015-03-01

There are more than 4 million miles of roads and 600,000 bridges in the United States alone. On-going investments are required to maintain the physical and operational quality of these assets to ensure public's safety and prosperity of the economy. Planning efficient maintenance and repair (M&R) operations must be armed with a meticulous pavement inspection method that is non-disruptive, is affordable and requires minimum manual effort. The Versatile Onboard Traffic Embedded Roaming Sensors (VOTERS) project developed a technology able to cost- effectively monitor the condition of roadway systems to plan for the right repairs, in the right place, at the right time. VOTERS technology consists of an affordable, lightweight package of multi-modal sensor systems including acoustic, optical, electromagnetic, and GPS sensors. Vehicles outfitted with this technology would be capable of collecting information on a variety of pavement-related characteristics at both surface and subsurface levels as they are driven. By correlating the sensors' outputs with the positioning data collected in tight time synchronization, a GIS-based control center attaches a spatial component to all the sensors' measurements and delivers multiple ratings of the pavement every meter. These spatially indexed ratings are then leveraged by VOTERS decision making modules to plan the optimum M&R operations and predict the future budget needs. In 2014, VOTERS inspection results were validated by comparing them to the outputs of recent professionally done condition surveys of a local engineering firm for 300 miles of Massachusetts roads. Success of the VOTERS project portrays rapid, intelligent, and comprehensive evaluation of tomorrow's transportation infrastructure to increase public's safety, vitalize the economy, and deter catastrophic failures.

Field Tests of Real-time In-situ Dissolved CO2 Monitoring for CO2 Leakage Detection in Groundwater

NASA Astrophysics Data System (ADS)

Yang, C.; Zou, Y.; Delgado, J.; Guzman, N.; Pinedo, J.

2016-12-01

Groundwater monitoring for detecting CO2 leakage relies on groundwater sampling from water wells drilled into aquifers. Usually groundwater samples are required be collected periodically in field and analyzed in the laboratory. Obviously groundwater sampling is labor and cost-intensive for long-term monitoring of large areas. Potential damage and contamination of water samples during the sampling process can degrade accuracy, and intermittent monitoring may miss changes in the geochemical parameters of groundwater, and therefore signs of CO2 leakage. Real-time in-situ monitoring of geochemical parameters with chemical sensors may play an important role for CO2 leakage detection in groundwater at a geological carbon sequestration site. This study presents field demonstration of a real-time in situ monitoring system capable of covering large areas for detection of low levels of dissolved CO2 in groundwater and reliably differentiating natural variations of dissolved CO2 concentration from small changes resulting from leakage. The sand-alone system includes fully distributed fiber optic sensors for carbon dioxide detection with a unique sensor technology developed by Intelligent Optical Systems. The systems were deployed to the two research sites: the Brackenridge Field Laboratory where the aquifer is shallow at depths of 10-20 ft below surface and the Devine site where the aquifer is much deeper at depths of 140 to 150 ft. Groundwater samples were periodically collected from the water wells which were installed with the chemical sensors and further compared to the measurements of the chemical sensors. Our study shows that geochemical monitoring of dissolved CO2 with fiber optic sensors could provide reliable CO2 leakage signal detection in groundwater as long as CO2 leakage signals are stronger than background noises at the monitoring locations.

Autonomous Sensors for Large Scale Data Collection

NASA Astrophysics Data System (ADS)

Noto, J.; Kerr, R.; Riccobono, J.; Kapali, S.; Migliozzi, M. A.; Goenka, C.

2017-12-01

Presented here is a novel implementation of a "Doppler imager" which remotely measures winds and temperatures of the neutral background atmosphere at ionospheric altitudes of 87-300Km and possibly above. Incorporating both recent optical manufacturing developments, modern network awareness and the application of machine learning techniques for intelligent self-monitoring and data classification. This system achieves cost savings in manufacturing, deployment and lifetime operating costs. Deployed in both ground and space-based modalities, this cost-disruptive technology will allow computer models of, ionospheric variability and other space weather models to operate with higher precision. Other sensors can be folded into the data collection and analysis architecture easily creating autonomous virtual observatories. A prototype version of this sensor has recently been deployed in Trivandrum India for the Indian Government. This Doppler imager is capable of operation, even within the restricted CubeSat environment. The CubeSat bus offers a very challenging environment, even for small instruments. The lack of SWaP and the challenging thermal environment demand development of a new generation of instruments; the Doppler imager presented is well suited to this environment. Concurrent with this CubeSat development is the development and construction of ground based arrays of inexpensive sensors using the proposed technology. This instrument could be flown inexpensively on one or more CubeSats to provide valuable data to space weather forecasters and ionospheric scientists. Arrays of magnetometers have been deployed for the last 20 years [Alabi, 2005]. Other examples of ground based arrays include an array of white-light all sky imagers (THEMIS) deployed across Canada [Donovan et al., 2006], oceans sensors on buoys [McPhaden et al., 2010], and arrays of seismic sensors [Schweitzer et al., 2002]. A comparable array of Doppler imagers can be constructed and deployed on the ground, to compliment the CubeSat data.

Integrating Sensor-Collected Intelligence

DTIC Science & Technology

2008-11-01

collecting, processing, data storage and fusion, and the dissemination of information collected by Intelligence, Surveillance, and Reconnaissance (ISR...Grid – Bandwidth Expansion (GIG-BE) program) to provide the capability to transfer data from sensors to accessible storage and satellite and airborne...based ISR is much more fragile. There was a purposeful drawdown of these systems following the Cold War and modernization programs were planned to

Development of analysis techniques for remote sensing of vegetation resources

NASA Technical Reports Server (NTRS)

Draeger, W. C.

1972-01-01

Various data handling and analysis techniques are summarized for evaluation of ERTS-A and supporting high flight imagery. These evaluations are concerned with remote sensors applied to wildland and agricultural vegetation resource inventory problems. Monitoring California's annual grassland, automatic texture analysis, agricultural ground data collection techniques, and spectral measurements are included.

A Method of Reducing Random Drift in the Combined Signal of an Array of Inertial Sensors

DTIC Science & Technology

2015-09-30

stability of the collective output, Bayard et al, US Patent 6,882,964. The prior art methods rely upon the use of Kalman filtering and averaging...including scale-factor errors, quantization effects, temperature effects, random drift, and additive noise. A comprehensive account of all of these

"Probeware" on Increase in Schools' Science Labs

ERIC Educational Resources Information Center

Trotter, Andrew

2008-01-01

Though the term, "probeware" may not be a household word, it has grown more familiar to science educators over the past decade, as a new generation of high-tech instruments for collecting and analyzing data from the physical world have been introduced into school science labs. Today, those tools include digital scientific probes or sensors that…

A Comparison of Video-Based and Interaction-Based Affect Detectors in Physics Playground

ERIC Educational Resources Information Center

Kai, Shiming; Paquette, Luc; Baker, Ryan S.; Bosch, Nigel; D'Mello, Sidney; Ocumpaugh, Jaclyn; Shute, Valerie; Ventura, Matthew

2015-01-01

Increased attention to the relationships between affect and learning has led to the development of machine-learned models that are able to identify students' affective states in computerized learning environments. Data for these affect detectors have been collected from multiple modalities including physical sensors, dialogue logs, and logs of…

Wide area sensor network

NASA Astrophysics Data System (ADS)

Mukhopadhyay, Sanjoy; Nix, Tricia; Junker, Robert; Brentano, Josef; Khona, Dhiren

2006-05-01

The technical concept for this project has existed since the Chernobyl accident in 1986. A host of Eastern European nations have developed countrywide grid of sensors to monitor airborne radiation. The objective is to build a radiological sensor network for real-time monitoring of environmental radiation levels in order to provide data for warning, and consequentially the assessment of a nuclear event. A network of radiation measuring equipment consisting of gamma, neutron, alpha, and beta counters would be distributed over a large area (preferably on fire station roof tops) and connected by a wireless network to the emergency response center. The networks would be deployed in urban environments and would supply first responders and federal augmentation teams (including those from the U.S. Departments of Energy, Defense, Justice, and Homeland Security) with detailed, accurate information regarding the transport of radioactive environmental contaminants, so the agencies can provide a safe and effective response. A networked sensor capability would be developed, with fixed sensors deployed at key locations and in sufficient numbers, to provide adequate coverage for early warning, and input to post-event emergency response. An overall system description and specification will be provided, including detector characteristics, communication protocols, infrastructure and maintenance requirements, and operation procedures. The system/network can be designed for a specifically identified urban area, or for a general urban area scalable to cities of specified size. Data collected via the network will be transmitted directly to the appropriate emergency response center and shared with multiple agencies via the Internet or an Intranet. The data collected will be managed using commercial off - the - shelf Geographical Information System (GIS). The data will be stored in a database and the GIS software will aid in analysis and management of the data. Unique features of the system include each node being assigned a health-effect based risk factor. By connecting the nodes on a particular measured isopleth one can define the plume accurately. Radon counts will be provided and used to calculate the alpha counts. The radiological data collected will also be of value under routine conditions, in the absence of a radiological threat, to provide a detailed map of radiation background in the urban environment and complement predictive models of radiation transport. The data can be transferred to the National Atmospheric Release Advisory Center (NARAC) to augment its predictive model, thereby increasing its fidelity. Initially, as a proof of concept, a few nodes will be built for the purpose of demonstrating the concept.

Small Body GN and C Research Report: G-SAMPLE - An In-Flight Dynamical Method for Identifying Sample Mass [External Release Version

NASA Technical Reports Server (NTRS)

Carson, John M., III; Bayard, David S.

2006-01-01

G-SAMPLE is an in-flight dynamical method for use by sample collection missions to identify the presence and quantity of collected sample material. The G-SAMPLE method implements a maximum-likelihood estimator to identify the collected sample mass, based on onboard force sensor measurements, thruster firings, and a dynamics model of the spacecraft. With G-SAMPLE, sample mass identification becomes a computation rather than an extra hardware requirement; the added cost of cameras or other sensors for sample mass detection is avoided. Realistic simulation examples are provided for a spacecraft configuration with a sample collection device mounted on the end of an extended boom. In one representative example, a 1000 gram sample mass is estimated to within 110 grams (95% confidence) under realistic assumptions of thruster profile error, spacecraft parameter uncertainty, and sensor noise. For convenience to future mission design, an overall sample-mass estimation error budget is developed to approximate the effect of model uncertainty, sensor noise, data rate, and thrust profile error on the expected estimate of collected sample mass.

An Assessment of the Icing Blade and the SEA Multi-Element Sensor for Liquid Water Content Calibration of the NASA GRC Icing Research Tunnel

NASA Technical Reports Server (NTRS)

Steen, Laura E.; Ide, Robert F.; Van Zante, Judith Foss

2017-01-01

The Icing Research Tunnel at NASA Glenn has recently switched to from using the Icing Blade to using the SEA Multi-Element Sensor (also known as the multi-wire) for its calibration of cloud liquid water content. In order to perform this transition, tests were completed to compare the Multi-Element Sensor to the Icing Blade, particularly with respect to liquid water content, airspeed, and drop size. The two instruments were found to compare well for the majority of Appendix C conditions. However, it was discovered that the Icing Blade under-measures when the conditions approach the Ludlam Limit. This paper also describes data processing procedures for the Multi-Element Sensor in the IRT, including collection efficiency corrections, mounting underneath a splitter plate, and correcting for a jump in the compensation wire power. Further data is presented to describe the repeatability of the IRT with the Multi-Element sensor, health-monitoring checks for the instrument, and a sensing-element configuration comparison.

Sensing in the Collaborative Internet of Things

PubMed Central

Borges Neto, João B.; Silva, Thiago H.; Assunção, Renato Martins; Mini, Raquel A. F.; Loureiro, Antonio A. F.

2015-01-01

We are entering a new era of computing technology, the era of Internet of Things (IoT). An important element for this popularization is the large use of off-the-shelf sensors. Most of those sensors will be deployed by different owners, generally common users, creating what we call the Collaborative IoT. This collaborative IoT helps to increase considerably the amount and availability of collected data for different purposes, creating new interesting opportunities, but also several challenges. For example, it is very challenging to search for and select a desired sensor or a group of sensors when there is no description about the provided sensed data or when it is imprecise. Given that, in this work we characterize the properties of the sensed data in the Internet of Things, mainly the sensed data contributed by several sources, including sensors from common users. We conclude that, in order to safely use data available in the IoT, we need a filtering process to increase the data reliability. In this direction, we propose a new simple and powerful approach that helps to select reliable sensors. We tested our method for different types of sensed data, and the results reveal the effectiveness in the correct selection of sensor data. PMID:25808766

An Intelligent Surveillance Platform for Large Metropolitan Areas with Dense Sensor Deployment

PubMed Central

Fernández, Jorge; Calavia, Lorena; Baladrón, Carlos; Aguiar, Javier M.; Carro, Belén; Sánchez-Esguevillas, Antonio; Alonso-López, Jesus A.; Smilansky, Zeev

2013-01-01

This paper presents an intelligent surveillance platform based on the usage of large numbers of inexpensive sensors designed and developed inside the European Eureka Celtic project HuSIMS. With the aim of maximizing the number of deployable units while keeping monetary and resource/bandwidth costs at a minimum, the surveillance platform is based on the usage of inexpensive visual sensors which apply efficient motion detection and tracking algorithms to transform the video signal in a set of motion parameters. In order to automate the analysis of the myriad of data streams generated by the visual sensors, the platform's control center includes an alarm detection engine which comprises three components applying three different Artificial Intelligence strategies in parallel. These strategies are generic, domain-independent approaches which are able to operate in several domains (traffic surveillance, vandalism prevention, perimeter security, etc.). The architecture is completed with a versatile communication network which facilitates data collection from the visual sensors and alarm and video stream distribution towards the emergency teams. The resulting surveillance system is extremely suitable for its deployment in metropolitan areas, smart cities, and large facilities, mainly because cheap visual sensors and autonomous alarm detection facilitate dense sensor network deployments for wide and detailed coverage. PMID:23748169

A Networked Sensor System for the Analysis of Plot-Scale Hydrology.

PubMed

Villalba, German; Plaza, Fernando; Zhong, Xiaoyang; Davis, Tyler W; Navarro, Miguel; Li, Yimei; Slater, Thomas A; Liang, Yao; Liang, Xu

2017-03-20

This study presents the latest updates to the Audubon Society of Western Pennsylvania (ASWP) testbed, a $50,000 USD, 104-node outdoor multi-hop wireless sensor network (WSN). The network collects environmental data from over 240 sensors, including the EC-5, MPS-1 and MPS-2 soil moisture and soil water potential sensors and self-made sap flow sensors, across a heterogeneous deployment comprised of MICAz, IRIS and TelosB wireless motes. A low-cost sensor board and software driver was developed for communicating with the analog and digital sensors. Innovative techniques (e.g., balanced energy efficient routing and heterogeneous over-the-air mote reprogramming) maintained high success rates (>96%) and enabled effective software updating, throughout the large-scale heterogeneous WSN. The edaphic properties monitored by the network showed strong agreement with data logger measurements and were fitted to pedotransfer functions for estimating local soil hydraulic properties. Furthermore, sap flow measurements, scaled to tree stand transpiration, were found to be at or below potential evapotranspiration estimates. While outdoor WSNs still present numerous challenges, the ASWP testbed proves to be an effective and (relatively) low-cost environmental monitoring solution and represents a step towards developing a platform for monitoring and quantifying statistically relevant environmental parameters from large-scale network deployments.

A Networked Sensor System for the Analysis of Plot-Scale Hydrology

PubMed Central

Villalba, German; Plaza, Fernando; Zhong, Xiaoyang; Davis, Tyler W.; Navarro, Miguel; Li, Yimei; Slater, Thomas A.; Liang, Yao; Liang, Xu

2017-01-01

This study presents the latest updates to the Audubon Society of Western Pennsylvania (ASWP) testbed, a $50,000 USD, 104-node outdoor multi-hop wireless sensor network (WSN). The network collects environmental data from over 240 sensors, including the EC-5, MPS-1 and MPS-2 soil moisture and soil water potential sensors and self-made sap flow sensors, across a heterogeneous deployment comprised of MICAz, IRIS and TelosB wireless motes. A low-cost sensor board and software driver was developed for communicating with the analog and digital sensors. Innovative techniques (e.g., balanced energy efficient routing and heterogeneous over-the-air mote reprogramming) maintained high success rates (>96%) and enabled effective software updating, throughout the large-scale heterogeneous WSN. The edaphic properties monitored by the network showed strong agreement with data logger measurements and were fitted to pedotransfer functions for estimating local soil hydraulic properties. Furthermore, sap flow measurements, scaled to tree stand transpiration, were found to be at or below potential evapotranspiration estimates. While outdoor WSNs still present numerous challenges, the ASWP testbed proves to be an effective and (relatively) low-cost environmental monitoring solution and represents a step towards developing a platform for monitoring and quantifying statistically relevant environmental parameters from large-scale network deployments. PMID:28335534

Ground-based radiometric calibration of the Landsat 8 Operational Land Imager (OLI) using in situ techniques

NASA Astrophysics Data System (ADS)

Czapla-Myers, J.

2013-12-01

Landsat 8 was successfully launched from Vandenberg Air Force Base in California on 11 February 2013, and was placed into the orbit previously occupied by Landsat 5. Landsat 8 is the latest platform in the 40-year history of the Landsat series of satellites, and it contains two instruments that operate in the solar-reflective and the thermal infrared regimes. The Operational Land Imager (OLI) is a pushbroom sensor that contains eight multispectral bands ranging from 400-2300 nm, and one panchromatic band. The spatial resolution of the multispectral bands is 30 m, which is similar to previous Landsat sensors, and the panchromatic band has a 15-m spatial resolution, which is also similar to previous Landsat sensors. The 12-bit radiometric resolution of OLI improves upon the 8-bit resolution of the Enhanced Thematic Mapper Plus (ETM+) onboard Landsat 7. An important requirement for the Landsat program is the long-term radiometric continuity of its sensors. Ground-based vicarious techniques have been used for over 20 years to determine the absolute radiometric calibration of sensors that encompass a wide variety of spectral and spatial characteristics. This work presents the early radiometric calibration results of Landsat 8 OLI that were obtained using the traditional reflectance-based approach. University of Arizona personnel used five sites in Arizona, California, and Nevada to collect ground-based data. In addition, a unique set of in situ data were collected in March 2013, when Landsat 7 and Landsat 8 were observing the same site within minutes of each other. The tandem overfly schedule occurred while Landsat 8 was shifting to the WRS-2 orbital grid, and lasted only a few days. The ground-based data also include results obtained using the University of Arizona's Radiometric Calibration Test Site (RadCaTS), which is an automated suite of instruments located at Railroad Valley, Nevada. The results presented in this work include a comparison to the L1T at-sensor spectral radiance and the top-of-atmosphere reflectance, both of which are standard products available from the US Geological Survey.

Mechanisms for Prolonging Network Lifetime in Wireless Sensor Networks

ERIC Educational Resources Information Center

Yang, Yinying

2010-01-01

Sensors are used to monitor and control the physical environment. A Wireless Sensor Network (WSN) is composed of a large number of sensor nodes that are densely deployed either inside the phenomenon or very close to it [18][5]. Sensor nodes measure various parameters of the environment and transmit data collected to one or more sinks, using…

Integrating Social Media and Mobile Sensor Data for Clinical Decision Support: Concept and Requirements.

PubMed

Denecke, Kerstin

2016-01-01

Social media are increasingly used by individuals for the purpose of collecting data and reporting on the personal health status, on health issues, symptoms and experiences with treatments. Beyond, fitness trackers are more used by individuals to monitor their fitness and health. The health data that is becoming available due to these developments could provide a valuable source for continuous health monitoring, prevention of unexpected health events and clinical decision making since it gives insights into behavior and life habits. However, an integration of the data is challenging. This paper aims triggering the discussion about this current topic. We present a concept for integrating social media data with mobile sensor data and clinical data using digital patient modelling. Further, we collect requirements and challenges for a possible realization of the concept. Challenges include the data volume, reliability and semantic interoperability.

Adaptive Remote-Sensing Techniques Implementing Swarms of Mobile Agents

DOE Office of Scientific and Technical Information (OSTI.GOV)

Asher, R.B.; Cameron, S.M.; Loubriel, G.M.

1998-11-25

In many situations, stand-off remote-sensing and hazard-interdiction techniques over realistic operational areas are often impractical "and difficult to characterize. An alternative approach is to implement an adap- tively deployable array of sensitive agent-specific devices. Our group has been studying the collective be- havior of an autonomous, multi-agent system applied to chedbio detection and related emerging threat applications, The current physics-based models we are using coordinate a sensor array for mukivanate sig- nal optimization and coverage as re,alized by a swarm of robots or mobile vehicles. These intelligent control systems integrate'glob"ally operating decision-making systems and locally cooperative learning neural net- worksmore » to enhance re+-timp operational responses to dynarnical environments examples of which include obstacle avoidance, res~onding to prevailing wind patterns, and overcoming other natural obscurants or in- terferences. Collectively',tkensor nefirons with simple properties, interacting according to basic community rules, can accomplish complex interconnecting functions such as generalization, error correction, pattern recognition, sensor fusion, and localization. Neural nets provide a greater degree of robusmess and fault tolerance than conventional systems in that minor variations or imperfections do not impair performance. The robotic platforms would be equipped with sensor devices that perform opticaI detection of biologicais in combination with multivariate chemical analysis tools based on genetic and neural network algorithms, laser-diode LIDAR analysis, ultra-wideband short-pulsed transmitting and receiving antennas, thermal im- a:ing sensors, and optical Communication technology providing robust data throughput pathways. Mission scenarios under consideration include ground penetrating radar (GPR) for detection of underground struc- tures, airborne systems, and plume migration and mitigation. We will describe our research in these areas anti give a status report on our progress.« less

Summary of suspended-sediment concentration data, San Francisco Bay, California, water year 2010

USGS Publications Warehouse

Buchanan, Paul A.; Morgan, Tara L.

2014-01-01

Suspended-sediment concentration data were collected by the U.S. Geological Survey in San Francisco Bay during water year 2010 (October 1, 2009–September 30, 2010). Turbidity sensors and water samples were used to monitor suspended-sediment concentration at two sites in Suisun Bay, one site in San Pablo Bay, three sites in Central San Francisco Bay, and one site in South San Francisco Bay. Sensors were positioned at two depths at most sites to help define the vertical variability of suspended sediments. Water samples were collected periodically and analyzed for concentrations of suspended sediment. The results of the analyses were used to calibrate the output of the turbidity sensors so that a record of suspended-sediment concentrations could be computed. This report presents the data-collection methods used and summarizes, in graphs, the suspended-sediment concentration data collected from October 2009 through September 2010. Calibration curves and plots of the processed data for each sensor also are presented.

Vision-Based Traffic Data Collection Sensor for Automotive Applications

PubMed Central

Llorca, David F.; Sánchez, Sergio; Ocaña, Manuel; Sotelo, Miguel. A.

2010-01-01

This paper presents a complete vision sensor onboard a moving vehicle which collects the traffic data in its local area in daytime conditions. The sensor comprises a rear looking and a forward looking camera. Thus, a representative description of the traffic conditions in the local area of the host vehicle can be computed. The proposed sensor detects the number of vehicles (traffic load), their relative positions and their relative velocities in a four-stage process: lane detection, candidates selection, vehicles classification and tracking. Absolute velocities (average road speed) and global positioning are obtained after combining the outputs provided by the vision sensor with the data supplied by the CAN Bus and a GPS sensor. The presented experiments are promising in terms of detection performance and accuracy in order to be validated for applications in the context of the automotive industry. PMID:22315572

Vision-based traffic data collection sensor for automotive applications.

PubMed

Llorca, David F; Sánchez, Sergio; Ocaña, Manuel; Sotelo, Miguel A

2010-01-01

This paper presents a complete vision sensor onboard a moving vehicle which collects the traffic data in its local area in daytime conditions. The sensor comprises a rear looking and a forward looking camera. Thus, a representative description of the traffic conditions in the local area of the host vehicle can be computed. The proposed sensor detects the number of vehicles (traffic load), their relative positions and their relative velocities in a four-stage process: lane detection, candidates selection, vehicles classification and tracking. Absolute velocities (average road speed) and global positioning are obtained after combining the outputs provided by the vision sensor with the data supplied by the CAN Bus and a GPS sensor. The presented experiments are promising in terms of detection performance and accuracy in order to be validated for applications in the context of the automotive industry.

Airborne agent concentration analysis

DOEpatents

Gelbard, Fred

2004-02-03

A method and system for inferring airborne contaminant concentrations in rooms without contaminant sensors, based on data collected by contaminant sensors in other rooms of a building, using known airflow interconnectivity data. The method solves a least squares problem that minimizes the difference between measured and predicted contaminant sensor concentrations with respect to an unknown contaminant release time. Solutions are constrained to providing non-negative initial contaminant concentrations in all rooms. The method can be used to identify a near-optimal distribution of sensors within the building, when then number of available sensors is less than the total number of rooms. This is achieved by having a system-sensor matrix that is non-singular, and by selecting that distribution which yields the lowest condition number of all the distributions considered. The method can predict one or more contaminant initial release points from the collected data.

Introduction to the Special Issue on "State-of-the-Art Sensor Technology in Japan 2015".

PubMed

Tokumitsu, Masahiro; Ishida, Yoshiteru

2016-08-23

This Special Issue, "State-of-the-Art Sensor Technology in Japan 2015", collected papers on different kinds of sensing technology: fundamental technology for intelligent sensors, information processing for monitoring humans, and information processing for adaptive and survivable sensor systems.[...].

Inexpensive Open-Source Data Logging in the Field

NASA Astrophysics Data System (ADS)

Wickert, A. D.

2013-12-01

I present a general-purpose open-source field-capable data logger, which provides a mechanism to develop dense networks of inexpensive environmental sensors. This data logger was developed as a low-power variant of the Arduino open-source development system, and is named the ALog ("Arduino Logger") BottleLogger (it is slim enough to fit inside a Nalgene water bottle) version 1.0. It features an integrated high-precision real-time clock, SD card slot for high-volume data storage, and integrated power switching. The ALog can interface with sensors via six analog/digital pins, two digital pins, and one digital interrupt pin that can read event-based inputs, such as those from a tipping-bucket rain gauge. We have successfully tested the ALog BottleLogger with ultrasonic rangefinders (for water stage and snow accumulation and melt), temperature sensors, tipping-bucket rain gauges, soil moisture and water potential sensors, resistance-based tools to measure frost heave, and cameras that it triggers based on events. The source code for the ALog, including functions to interface with a a range of commercially-available sensors, is provided as an Arduino C++ library with example implementations. All schematics, circuit board layouts, and source code files are open-source and freely available under GNU GPL v3.0 and Creative Commons Attribution-ShareAlike 3.0 Unported licenses. Through this work, we hope to foster a community-driven movement to collect field environmental data on a budget that permits citizen-scientists and researchers from low-income countries to collect the same high-quality data as researchers in wealthy countries. These data can provide information about global change to managers, governments, scientists, and interested citizens worldwide. Watertight box with ALog BottleLogger data logger on the left and battery pack with 3 D cells on the right. Data can be collected for 3-5 years on one set of batteries.

High-voltage pixel sensors for ATLAS upgrade

NASA Astrophysics Data System (ADS)

Perić, I.; Kreidl, C.; Fischer, P.; Bompard, F.; Breugnon, P.; Clemens, J.-C.; Fougeron, D.; Liu, J.; Pangaud, P.; Rozanov, A.; Barbero, M.; Feigl, S.; Capeans, M.; Ferrere, D.; Pernegger, H.; Ristic, B.; Muenstermann, D.; Gonzalez Sevilla, S.; La Rosa, A.; Miucci, A.; Nessi, M.; Iacobucci, G.; Backhaus, M.; Hügging, Fabian; Krüger, H.; Hemperek, T.; Obermann, T.; Wermes, N.; Garcia-Sciveres, M.; Quadt, A.; Weingarten, J.; George, M.; Grosse-Knetter, J.; Rieger, J.; Bates, R.; Blue, A.; Buttar, C.; Hynds, D.

2014-11-01

The high-voltage (HV-) CMOS pixel sensors offer several good properties: a fast charge collection by drift, the possibility to implement relatively complex CMOS in-pixel electronics and the compatibility with commercial processes. The sensor element is a deep n-well diode in a p-type substrate. The n-well contains CMOS pixel electronics. The main charge collection mechanism is drift in a shallow, high field region, which leads to a fast charge collection and a high radiation tolerance. We are currently evaluating the use of the high-voltage detectors implemented in 180 nm HV-CMOS technology for the high-luminosity ATLAS upgrade. Our approach is replacing the existing pixel and strip sensors with the CMOS sensors while keeping the presently used readout ASICs. By intelligence we mean the ability of the sensor to recognize a particle hit and generate the address information. In this way we could benefit from the advantages of the HV sensor technology such as lower cost, lower mass, lower operating voltage, smaller pitch, smaller clusters at high incidence angles. Additionally we expect to achieve a radiation hardness necessary for ATLAS upgrade. In order to test the concept, we have designed two HV-CMOS prototypes that can be readout in two ways: using pixel and strip readout chips. In the case of the pixel readout, the connection between HV-CMOS sensor and the readout ASIC can be established capacitively.

The Drifter Platform for Measurements in Small Rivers

NASA Astrophysics Data System (ADS)

Kruger, A.; Niemeier, J. J.; Ceynar, D. L.

2011-12-01

Researchers at The University of Iowa have been developing a small, inexpensive floating sensor platform to enable a variety of measurements in small rivers. The platform, dubbed "drifters" consists of a PVC housing and small inflatable rubber tube, data collection electronics, and several sensors. Upon release at strategic locations and times in a river network, drifters interrogate their GPS modules for position, time, and velocity. Researchers then collect the drifters and download and analyze position and velocity data. While our primary interest is to observe river network surface water flows, drifters have the broader application of serving as instrumentation platforms for other sensors such a temperature and turbidity. The drifters are structured as follows. A temperature-compensated MEMS clock provides accurate time information. A GPS disciplines this clock and provides georeference information. A low-power microcontroller orchestrates the data collection on the drifter. The standard sensor configuration of the drifter incorporates the GPS, air- and water temperature sensors, a water turbidity sensor, and an accelerometer. The microcontroller stores the collected data on a high-capacity, non-volatile Flash memory card. Each drifter has a bar code sticker, a small RFID tag, and a unique electronic ID embedded in the electronics. These allow us to manage a fleet of drifters and the data they collect. Each drifter has contact information in case a drifter is lost, and an inexpensive short-range radio and a beeper. These allow for determining the locations of the drifters at the conclusion of an experiment as follows. The microcontroller periodically turns on the receiver and listens for the instruction to turn on the beeper. The beeper, when activated, generates a piercing sound that helps operators locate the drifter. The microcontroller also blinks a super bright LED. Two AA-size alkaline batteries typically power the system. The maximum data collection period is dependent on the number of sensors a user activates, the type of battery utilized (alkaline, lithium, NiMH, etc.), the sample rate, and ranges from 12-72 hours. We have collected several data sets in Iowa.

Internet of Things Platform for Smart Farming: Experiences and Lessons Learnt.

PubMed

Jayaraman, Prem Prakash; Yavari, Ali; Georgakopoulos, Dimitrios; Morshed, Ahsan; Zaslavsky, Arkady

2016-11-09

Improving farm productivity is essential for increasing farm profitability and meeting the rapidly growing demand for food that is fuelled by rapid population growth across the world. Farm productivity can be increased by understanding and forecasting crop performance in a variety of environmental conditions. Crop recommendation is currently based on data collected in field-based agricultural studies that capture crop performance under a variety of conditions (e.g., soil quality and environmental conditions). However, crop performance data collection is currently slow, as such crop studies are often undertaken in remote and distributed locations, and such data are typically collected manually. Furthermore, the quality of manually collected crop performance data is very low, because it does not take into account earlier conditions that have not been observed by the human operators but is essential to filter out collected data that will lead to invalid conclusions (e.g., solar radiation readings in the afternoon after even a short rain or overcast in the morning are invalid, and should not be used in assessing crop performance). Emerging Internet of Things (IoT) technologies, such as IoT devices (e.g., wireless sensor networks, network-connected weather stations, cameras, and smart phones) can be used to collate vast amount of environmental and crop performance data, ranging from time series data from sensors, to spatial data from cameras, to human observations collected and recorded via mobile smart phone applications. Such data can then be analysed to filter out invalid data and compute personalised crop recommendations for any specific farm. In this paper, we present the design of SmartFarmNet, an IoT-based platform that can automate the collection of environmental, soil, fertilisation, and irrigation data; automatically correlate such data and filter-out invalid data from the perspective of assessing crop performance; and compute crop forecasts and personalised crop recommendations for any particular farm. SmartFarmNet can integrate virtually any IoT device, including commercially available sensors, cameras, weather stations, etc., and store their data in the cloud for performance analysis and recommendations. An evaluation of the SmartFarmNet platform and our experiences and lessons learnt in developing this system concludes the paper. SmartFarmNet is the first and currently largest system in the world (in terms of the number of sensors attached, crops assessed, and users it supports) that provides crop performance analysis and recommendations.

Feasibility of Deploying Inhaler Sensors to Identify the Impacts of Environmental Triggers and Built Environment Factors on Asthma Short-Acting Bronchodilator Use.

PubMed

Su, Jason G; Barrett, Meredith A; Henderson, Kelly; Humblet, Olivier; Smith, Ted; Sublett, James W; Nesbitt, LaQuandra; Hogg, Chris; Van Sickle, David; Sublett, James L

2017-02-01

Epidemiological asthma research has relied upon self-reported symptoms or healthcare utilization data, and used the residential address as the primary location for exposure. These data sources can be temporally limited, spatially aggregated, subjective, and burdensome for the patient to collect. First, we aimed to test the feasibility of collecting rescue inhaler use data in space-time using electronic sensors. Second, we aimed to evaluate whether these data have the potential to identify environmental triggers and built environment factors associated with rescue inhaler use and to determine whether these findings would be consistent with the existing literature. We utilized zero-truncated negative binomial models to identify triggers associated with inhaler use, and implemented three sensitivity analyses to validate our findings. Electronic sensors fitted on metered dose inhalers tracked 5,660 rescue inhaler use events in space and time for 140 participants from 13 June 2012 to 28 February 2014. We found that the inhaler sensors were feasible in passively collecting objective rescue inhaler use data. We identified several environmental triggers with a positive and significant association with inhaler use, including: AQI, PM10, weed pollen, and mold. Conversely, the spatial distribution of tree cover demonstrated a negative and significant association with inhaler use. Utilizing a sensor to capture the signal of rescue inhaler use in space-time offered a passive and objective signal of asthma activity. This approach enabled detailed analyses to identify environmental triggers and built environment factors that are associated with asthma symptoms beyond the residential address. The application of these new technologies has the potential to improve our surveillance and understanding of asthma. Citation: Su JG, Barrett MA, Henderson K, Humblet O, Smith T, Sublett JW, Nesbitt L, Hogg C, Van Sickle D, Sublett JL. 2017. Feasibility of deploying inhaler sensors to identify the impacts of environmental triggers and built environment factors on asthma short-acting bronchodilator use. Environ Health Perspect 125:254-261; http://dx.doi.org/10.1289/EHP266.

The Impacts of Attitudes and Engagement on Electronic Word of Mouth (eWOM) of Mobile Sensor Computing Applications.

PubMed

Zhao, Yu; Liu, Yide; Lai, Ivan K W; Zhang, Hongfeng; Zhang, Yi

2016-03-18

As one of the latest revolutions in networking technology, social networks allow users to keep connected and exchange information. Driven by the rapid wireless technology development and diffusion of mobile devices, social networks experienced a tremendous change based on mobile sensor computing. More and more mobile sensor network applications have appeared with the emergence of a huge amount of users. Therefore, an in-depth discussion on the human-computer interaction (HCI) issues of mobile sensor computing is required. The target of this study is to extend the discussions on HCI by examining the relationships of users' compound attitudes (i.e., affective attitudes, cognitive attitude), engagement and electronic word of mouth (eWOM) behaviors in the context of mobile sensor computing. A conceptual model is developed, based on which, 313 valid questionnaires are collected. The research discusses the level of impact on the eWOM of mobile sensor computing by considering user-technology issues, including the compound attitude and engagement, which can bring valuable discussions on the HCI of mobile sensor computing in further study. Besides, we find that user engagement plays a mediating role between the user's compound attitudes and eWOM. The research result can also help the mobile sensor computing industry to develop effective strategies and build strong consumer user-product (brand) relationships.

Design of autonomous sensor nodes for remote soil monitoring in tropical banana plantation

NASA Astrophysics Data System (ADS)

Tiausas, Francis Jerome G.; Co, Jerelyn; Macalinao, Marc Joseph M.; Guico, Maria Leonora; Monje, Jose Claro; Oppus, Carlos

2017-09-01

Determining the effect of Fusarium oxysporum f. sp. cubense Tropical Race 4 on various soil parameters is essential in modeling and predicting its occurrence in banana plantations. One way to fulfill this is through a sensor network that will continuously and automatically monitor environmental conditions at suspect locations for an extended period of time. A wireless sensor network was developed specifically for this purpose. This sensor network is capable of measuring soil acidity, moisture, temperature, and conductivity. The designed prototype made use of off-the-shelf Parrot Flower Power soil sensor, pH sensor, Bluno Beetle, battery, and 3D-printed materials, catering specifically to the conditions of tropical banana plantations with consideration for sensor node size, communication, and power. Sensor nodes were tested on both simulated tropical environments and on an actual banana plantation in San Jose, General Santos City, Philippines. Challenges were resolved through iterative design and development of prototypes. Several tests including temperature and weather resilience, and structural stress tests were done to validate the design. Findings showed that the WSN nodes developed for this purpose are resilient to high tropical temperatures for up to 12 hours of continuous exposure, are able to withstand compressive forces of up to 8880.6 N, and can reliably collect data automatically from the area 47.96% of the time at an hourly frequency under actual field conditions.

Fast Measurement and Reconstruction of Large Workpieces with Freeform Surfaces by Combining Local Scanning and Global Position Data

PubMed Central

Chen, Zhe; Zhang, Fumin; Qu, Xinghua; Liang, Baoqiu

2015-01-01

In this paper, we propose a new approach for the measurement and reconstruction of large workpieces with freeform surfaces. The system consists of a handheld laser scanning sensor and a position sensor. The laser scanning sensor is used to acquire the surface and geometry information, and the position sensor is utilized to unify the scanning sensors into a global coordinate system. The measurement process includes data collection, multi-sensor data fusion and surface reconstruction. With the multi-sensor data fusion, errors accumulated during the image alignment and registration process are minimized, and the measuring precision is significantly improved. After the dense accurate acquisition of the three-dimensional (3-D) coordinates, the surface is reconstructed using a commercial software piece, based on the Non-Uniform Rational B-Splines (NURBS) surface. The system has been evaluated, both qualitatively and quantitatively, using reference measurements provided by a commercial laser scanning sensor. The method has been applied for the reconstruction of a large gear rim and the accuracy is up to 0.0963 mm. The results prove that this new combined method is promising for measuring and reconstructing the large-scale objects with complex surface geometry. Compared with reported methods of large-scale shape measurement, it owns high freedom in motion, high precision and high measurement speed in a wide measurement range. PMID:26091396

The Impacts of Attitudes and Engagement on Electronic Word of Mouth (eWOM) of Mobile Sensor Computing Applications

PubMed Central

Zhao, Yu; Liu, Yide; Lai, Ivan K. W.; Zhang, Hongfeng; Zhang, Yi

2016-01-01

As one of the latest revolutions in networking technology, social networks allow users to keep connected and exchange information. Driven by the rapid wireless technology development and diffusion of mobile devices, social networks experienced a tremendous change based on mobile sensor computing. More and more mobile sensor network applications have appeared with the emergence of a huge amount of users. Therefore, an in-depth discussion on the human–computer interaction (HCI) issues of mobile sensor computing is required. The target of this study is to extend the discussions on HCI by examining the relationships of users’ compound attitudes (i.e., affective attitudes, cognitive attitude), engagement and electronic word of mouth (eWOM) behaviors in the context of mobile sensor computing. A conceptual model is developed, based on which, 313 valid questionnaires are collected. The research discusses the level of impact on the eWOM of mobile sensor computing by considering user-technology issues, including the compound attitude and engagement, which can bring valuable discussions on the HCI of mobile sensor computing in further study. Besides, we find that user engagement plays a mediating role between the user’s compound attitudes and eWOM. The research result can also help the mobile sensor computing industry to develop effective strategies and build strong consumer user—product (brand) relationships. PMID:26999155

Motor vehicle fuel analyzer

DOEpatents

Hoffheins, B.S.; Lauf, R.J.

1997-08-05

A gas detecting system is described for classifying the type of liquid fuel in a container or tank. The system includes a plurality of semiconductor gas sensors, each of which differs from the other in its response to various organic vapors. The system includes a means of processing the responses of the plurality of sensors such that the responses to any particular organic substance or mixture is sufficiently distinctive to constitute a recognizable ``signature``. The signature of known substances are collected and divided into two classes based on some other known characteristic of the substances. A pattern recognition system classifies the signature of an unknown substance with reference to the two user-defined classes, thereby classifying the unknown substance with regard to the characteristic of interest, such as its suitability for a particular use. 14 figs.

Motor vehicle fuel analyzer

DOEpatents

Hoffheins, Barbara S.; Lauf, Robert J.

1997-01-01

A gas detecting system for classifying the type of liquid fuel in a container or tank. The system includes a plurality of semiconductor gas sensors, each of which differs from the other in its response to various organic vapors. The system includes a means of processing the responses of the plurality of sensors such that the responses to any particular organic substance or mixture is sufficiently distinctive to constitute a recognizable "signature". The signature of known substances are collected and divided into two classes based on some other known characteristic of the substances. A pattern recognition system classifies the signature of an unknown substance with reference to the two user-defined classes, thereby classifying the unknown substance with regard to the characteristic of interest, such as its suitability for a particular use.

An adaptive distributed data aggregation based on RCPC for wireless sensor networks

NASA Astrophysics Data System (ADS)

Hua, Guogang; Chen, Chang Wen

2006-05-01

One of the most important design issues in wireless sensor networks is energy efficiency. Data aggregation has significant impact on the energy efficiency of the wireless sensor networks. With massive deployment of sensor nodes and limited energy supply, data aggregation has been considered as an essential paradigm for data collection in sensor networks. Recently, distributed source coding has been demonstrated to possess several advantages in data aggregation for wireless sensor networks. Distributed source coding is able to encode sensor data with lower bit rate without direct communication among sensor nodes. To ensure reliable and high throughput transmission with the aggregated data, we proposed in this research a progressive transmission and decoding of Rate-Compatible Punctured Convolutional (RCPC) coded data aggregation with distributed source coding. Our proposed 1/2 RSC codes with Viterbi algorithm for distributed source coding are able to guarantee that, even without any correlation between the data, the decoder can always decode the data correctly without wasting energy. The proposed approach achieves two aspects in adaptive data aggregation for wireless sensor networks. First, the RCPC coding facilitates adaptive compression corresponding to the correlation of the sensor data. When the data correlation is high, higher compression ration can be achieved. Otherwise, lower compression ratio will be achieved. Second, the data aggregation is adaptively accumulated. There is no waste of energy in the transmission; even there is no correlation among the data, the energy consumed is at the same level as raw data collection. Experimental results have shown that the proposed distributed data aggregation based on RCPC is able to achieve high throughput and low energy consumption data collection for wireless sensor networks

Use of remotely reporting electronic sensors for assessing use of water filters and cookstoves in Rwanda.

PubMed

Thomas, Evan A; Barstow, Christina K; Rosa, Ghislaine; Majorin, Fiona; Clasen, Thomas

2013-01-01

Remotely reporting electronic sensors offer the potential to reduce bias in monitoring use of environmental health interventions. In the context of a five-month randomized controlled trial of household water filters and improved cookstoves in rural Rwanda, we collected data from intervention households on product compliance using (i) monthly surveys and direct observations by community health workers and environmental health officers, and (ii) sensor-equipped filters and cookstoves deployed for about two weeks in each household. The adoption rate interpreted by the sensors varied from the household reporting: 90.5% of households reported primarily using the intervention stove, while the sensors interpreted 73.2% use, and 96.5% of households reported using the intervention filter regularly, while the sensors interpreted no more than 90.2%. The sensor-collected data estimated use to be lower than conventionally collected data both for water filters (approximately 36% less water volume per day) and cookstoves (approximately 40% fewer uses per week). An evaluation of intrahousehold consistency in use suggests that households are not using their filters or stoves on an exclusive basis, and may be both drinking untreated water at times and using other stoves ("stove-stacking"). These results provide additional evidence that surveys and direct observation may exaggerate compliance with household-based environmental interventions.

Flexible Workflow Software enables the Management of an Increased Volume and Heterogeneity of Sensors, and evolves with the Expansion of Complex Ocean Observatory Infrastructures.

NASA Astrophysics Data System (ADS)

Tomlin, M. C.; Jenkyns, R.

2015-12-01

Ocean Networks Canada (ONC) collects data from observatories in the northeast Pacific, Salish Sea, Arctic Ocean, Atlantic Ocean, and land-based sites in British Columbia. Data are streamed, collected autonomously, or transmitted via satellite from a variety of instruments. The Software Engineering group at ONC develops and maintains Oceans 2.0, an in-house software system that acquires and archives data from sensors, and makes data available to scientists, the public, government and non-government agencies. The Oceans 2.0 workflow tool was developed by ONC to manage a large volume of tasks and processes required for instrument installation, recovery and maintenance activities. Since 2013, the workflow tool has supported 70 expeditions and grown to include 30 different workflow processes for the increasing complexity of infrastructures at ONC. The workflow tool strives to keep pace with an increasing heterogeneity of sensors, connections and environments by supporting versioning of existing workflows, and allowing the creation of new processes and tasks. Despite challenges in training and gaining mutual support from multidisciplinary teams, the workflow tool has become invaluable in project management in an innovative setting. It provides a collective place to contribute to ONC's diverse projects and expeditions and encourages more repeatable processes, while promoting interactions between the multidisciplinary teams who manage various aspects of instrument development and the data they produce. The workflow tool inspires documentation of terminologies and procedures, and effectively links to other tools at ONC such as JIRA, Alfresco and Wiki. Motivated by growing sensor schemes, modes of collecting data, archiving, and data distribution at ONC, the workflow tool ensures that infrastructure is managed completely from instrument purchase to data distribution. It integrates all areas of expertise and helps fulfill ONC's mandate to offer quality data to users.

Advances in Small Remotely Piloted Aircraft Communications and Remote Sensing in Maritime Environments including the Arctic

NASA Astrophysics Data System (ADS)

McGillivary, P. A.; Borges de Sousa, J.; Wackowski, S.; Walker, G.

2011-12-01

Small remotely piloted aircraft have recently been used for maritime remote sensing, including launch and retrieval operations from land, ships and sea ice. Such aircraft can also function to collect and communicate data from other ocean observing system platforms including moorings, tagged animals, drifters, autonomous surface vessels (ASVs), and autonomous underwater vessels (AUVs). The use of small remotely piloted aircraft (or UASs, unmanned aerial systems) with a combination of these capabilities will be required to monitor the vast areas of the open ocean, as well as in harsh high-latitude ecosystems. Indeed, these aircraft are a key component of planned high latitude maritime domain awareness environmental data collection capabilities, including use of visible, IR and hyperspectral sensors, as well as lidar, meteorological sensors, and interferometric synthetic aperture radars (ISARs). We here first describe at-sea demonstrations of improved reliability and bandwidth of communications from ocean sensors on autonomous underwater vehicles to autonomous surface vessels, and then via remotely piloted aircraft to shore, ships and manned aircraft using Delay and Disruption Tolerant (DTN) communication protocols. DTN enables data exchange in communications-challenged environments, such as remote regions of the ocean including high latitudes where low satellite angles and auroral disturbances can be problematic. DTN provides a network architecture and application interface structured around optionally-reliable asynchronous message forwarding, with limited expectations of end-to-end connectivity and node resources. This communications method enables aircraft and surface vessels to function as data mules to move data between physically disparate nodes. We provide examples of the uses of this communication protocol for environmental data collection and data distribution with a variety of different remotely piloted aircraft in a coastal ocean environment. Next, we highlight use in the arctic of two different small remotely piloted aircraft (ScanEagle and RAVEN) for remote sensing of ice and ocean conditions as well as surveys of marine mammals. Finally, we explain how these can be used in future networked environments with DTN support not only for the collection of ocean and ice data for maritime domain awareness, but also for monitoring oil spill dynamics in high latitude environments, including spills in and under sea ice. The networked operation of heterogeneous air and ocean vehicle systems using DTN communications methods can provide unprecedented levels of spatial-temporal sampling resolution important to improving arctic remote sensing and maritime domain awareness capabilities.

Localization of short-range acoustic and seismic wideband sources: Algorithms and experiments

NASA Astrophysics Data System (ADS)

Stafsudd, J. Z.; Asgari, S.; Hudson, R.; Yao, K.; Taciroglu, E.

2008-04-01

We consider the determination of the location (source localization) of a disturbance source which emits acoustic and/or seismic signals. We devise an enhanced approximate maximum-likelihood (AML) algorithm to process data collected at acoustic sensors (microphones) belonging to an array of, non-collocated but otherwise identical, sensors. The approximate maximum-likelihood algorithm exploits the time-delay-of-arrival of acoustic signals at different sensors, and yields the source location. For processing the seismic signals, we investigate two distinct algorithms, both of which process data collected at a single measurement station comprising a triaxial accelerometer, to determine direction-of-arrival. The direction-of-arrivals determined at each sensor station are then combined using a weighted least-squares approach for source localization. The first of the direction-of-arrival estimation algorithms is based on the spectral decomposition of the covariance matrix, while the second is based on surface wave analysis. Both of the seismic source localization algorithms have their roots in seismology; and covariance matrix analysis had been successfully employed in applications where the source and the sensors (array) are typically separated by planetary distances (i.e., hundreds to thousands of kilometers). Here, we focus on very-short distances (e.g., less than one hundred meters) instead, with an outlook to applications in multi-modal surveillance, including target detection, tracking, and zone intrusion. We demonstrate the utility of the aforementioned algorithms through a series of open-field tests wherein we successfully localize wideband acoustic and/or seismic sources. We also investigate a basic strategy for fusion of results yielded by acoustic and seismic arrays.

System for Suppressing Vibration in Turbomachine Components

NASA Technical Reports Server (NTRS)

Morrison, Carlos R. (Inventor); Provenza, Andrew J. (Inventor); Choi, Benjamin B. (Inventor); Bakhle, Milind A. (Inventor); Min, James B (Inventor); Stefko, George L. (Inventor); Kussmann, John A (Inventor); Fougere, Alan J (Inventor)

2013-01-01

Disclosed is a system for suppressing vibration and noise mitigation in structures such as blades in turbomachinery. The system includes flexible piezoelectric patches which are secured on or imbedded in turbomachinery blades which, in one embodiment, comprises eight (8) fan blades. The system further includes a capacitor plate coupler and a power transfer apparatus, which may both be arranged into one assembly, that respectively transfer data and power. Each of the capacitive plate coupler and power transfer apparatus is configured so that one part is attached to a fixed member while another part is attached to a rotatable member with an air gap there between. The system still further includes a processor that has 16 channels, eight of which serve as sensor channels, and the remaining eight, serving as actuation channels. The processor collects and analyzes the sensor signals and, in turn, outputs corrective signals for vibration/noise suppression of the turbine blades.

Electrostatic thin film chemical and biological sensor

DOE Office of Scientific and Technical Information (OSTI.GOV)

Prelas, Mark A.; Ghosh, Tushar K.; Tompson, Jr., Robert V.

A chemical and biological agent sensor includes an electrostatic thin film supported by a substrate. The film includes an electrostatic charged surface to attract predetermined biological and chemical agents of interest. A charge collector associated with said electrostatic thin film collects charge associated with surface defects in the electrostatic film induced by the predetermined biological and chemical agents of interest. A preferred sensing system includes a charge based deep level transient spectroscopy system to read out charges from the film and match responses to data sets regarding the agents of interest. A method for sensing biological and chemical agents includesmore » providing a thin sensing film having a predetermined electrostatic charge. The film is exposed to an environment suspected of containing the biological and chemical agents. Quantum surface effects on the film are measured. Biological and/or chemical agents can be detected, identified and quantified based on the measured quantum surface effects.« less

DOE Office of Scientific and Technical Information (OSTI.GOV)

Leary, T.J.; Lamb, A.

The Department of Energy`s Office of Arms Control and Non-Proliferation (NN-20) has developed a suite of airborne remote sensing systems that simultaneously collect coincident data from a US Navy P-3 aircraft. The primary objective of the Airborne Multisensor Pod System (AMPS) Program is {open_quotes}to collect multisensor data that can be used for data research, both to reduce interpretation problems associated with data overload and to develop information products more complete than can be obtained from any single sensor.{close_quotes} The sensors are housed in wing-mounted pods and include: a Ku-Band Synthetic Aperture Radar; a CASI Hyperspectral Imager; a Daedalus 3600 Airbornemore » Multispectral Scanner; a Wild Heerbrugg RC-30 motion compensated large format camera; various high resolution, light intensified and thermal video cameras; and several experimental sensors (e.g. the Portable Hyperspectral Imager of Low-Light Spectroscopy (PHILLS)). Over the past year or so, the Coastal Marine Resource Assessment (CAMRA) group at the Florida Department of Environmental Protection`s Marine Research Institute (FMRI) has been working with the Department of Energy through the Naval Research Laboratory to develop applications and products from existing data. Considerable effort has been spent identifying image formats integration parameters. 2 refs., 3 figs., 2 tabs.« less

Heart rate and sentiment experimental data with common timeline.

PubMed

Salamon, Jaromír; Mouček, Roman

2017-12-01

Sentiment extraction and analysis using spoken utterances or written corpora as well as collection and analysis of human heart rate data using sensors are commonly used techniques and methods. On the other hand, these have been not combined yet. The collected data can be used e.g. to investigate the mutual dependence of human physical and emotional activity. The paper describes the procedure of parallel acquisition of heart rate sensor data and tweets expressing sentiment and difficulties related to this procedure. The obtained datasets are described in detail and further discussed to provide as much information as possible for subsequent analyses and conclusions. Analyses and conclusions are not included in this paper. The presented experiment and provided datasets serve as the first basis for further studies where all four presented data sources can be used independently, combined in a reasonable way or used all together. For instance, when the data is used all together, performing studies comparing human sensor data, acquired noninvasively from the surface of the human body and considered as more objective, and human written data expressing the sentiment, which is at least partly cognitively interpreted and thus considered as more subjective, could be beneficial.

Virtualization of event sources in wireless sensor networks for the internet of things.

PubMed

Lucas Martínez, Néstor; Martínez, José-Fernán; Hernández Díaz, Vicente

2014-12-01

Wireless Sensor Networks (WSNs) are generally used to collect information from the environment. The gathered data are delivered mainly to sinks or gateways that become the endpoints where applications can retrieve and process such data. However, applications would also expect from a WSN an event-driven operational model, so that they can be notified whenever occur some specific environmental changes instead of continuously analyzing the data provided periodically. In either operational model, WSNs represent a collection of interconnected objects, as outlined by the Internet of Things. Additionally, in order to fulfill the Internet of Things principles, Wireless Sensor Networks must have a virtual representation that allows indirect access to their resources, a model that should also include the virtualization of event sources in a WSN. Thus, in this paper a model for a virtual representation of event sources in a WSN is proposed. They are modeled as internet resources that are accessible by any internet application, following an Internet of Things approach. The model has been tested in a real implementation where a WSN has been deployed in an open neighborhood environment. Different event sources have been identified in the proposed scenario, and they have been represented following the proposed model.

Saving energy for the data collection point in WBAN network

NASA Astrophysics Data System (ADS)

Nguyen-Duc, Toan; Kamioka, Eiji

2017-11-01

Wireless sensor networking (WSN) has been rapidly developed and become essential in various domains including health care systems. Such systems use WSN to collect real-time medical sensed data, aiming at improving the patient safety. For instance, patients suffered from adverse events, i.e., cardiac or respiratory arrests, are monitored so as to prevent them from getting harm. Sensors are placed on, in or near the patients' body to continuously collect sensing data such as the electrocardiograms, blood oxygenation, breathing, and heart rate. In this case, the sensors form a subcategory of WSN called wireless body area network (WBAN). In WBAN, sensing data are sent to one or more data collection points called personal server (PS). The role of PS is important since it forwards sensed data, to a medical server via a Bluetooth/WLAN connection in real time to support storage of information and real-time diagnosis, the device can also issue a notification of an emergency status. Since PS is a battery-based device, when its battery is empty, it will disconnect the sensed medical data with the rest network. To best of our knowledge, very few studies that focus on saving energy for the PS. To this end, this work investigates the trade-off between energy consumption for wireless communication and the amount of sensing data. An energy consumption model for wireless communication has been proposed based on direct measurement using real testbed. According to our findings, it is possible to save energy for the PS by selecting suitable wireless technology to be used based on the amount of data to be transmitted.

The Pilatus Unmanned Aircraft System for Lower Atmospheric Research

NASA Technical Reports Server (NTRS)

de Boer, Gijs; Palo, Scott; Argrow, Brian; LoDolce, Gabriel; Mack, James; Gao, Ru-shan; Telg, Hagen; Trussel, Cameron; Fromm, Joshua; Long, Charles N.;

Enhanced RGB-D Mapping Method for Detailed 3D Indoor and Outdoor Modeling

PubMed Central

Tang, Shengjun; Zhu, Qing; Chen, Wu; Darwish, Walid; Wu, Bo; Hu, Han; Chen, Min

2016-01-01

RGB-D sensors (sensors with RGB camera and Depth camera) are novel sensing systems that capture RGB images along with pixel-wise depth information. Although they are widely used in various applications, RGB-D sensors have significant drawbacks including limited measurement ranges (e.g., within 3 m) and errors in depth measurement increase with distance from the sensor with respect to 3D dense mapping. In this paper, we present a novel approach to geometrically integrate the depth scene and RGB scene to enlarge the measurement distance of RGB-D sensors and enrich the details of model generated from depth images. First, precise calibration for RGB-D Sensors is introduced. In addition to the calibration of internal and external parameters for both, IR camera and RGB camera, the relative pose between RGB camera and IR camera is also calibrated. Second, to ensure poses accuracy of RGB images, a refined false features matches rejection method is introduced by combining the depth information and initial camera poses between frames of the RGB-D sensor. Then, a global optimization model is used to improve the accuracy of the camera pose, decreasing the inconsistencies between the depth frames in advance. In order to eliminate the geometric inconsistencies between RGB scene and depth scene, the scale ambiguity problem encountered during the pose estimation with RGB image sequences can be resolved by integrating the depth and visual information and a robust rigid-transformation recovery method is developed to register RGB scene to depth scene. The benefit of the proposed joint optimization method is firstly evaluated with the publicly available benchmark datasets collected with Kinect. Then, the proposed method is examined by tests with two sets of datasets collected in both outside and inside environments. The experimental results demonstrate the feasibility and robustness of the proposed method. PMID:27690028

Enhanced RGB-D Mapping Method for Detailed 3D Indoor and Outdoor Modeling.

PubMed

Tang, Shengjun; Zhu, Qing; Chen, Wu; Darwish, Walid; Wu, Bo; Hu, Han; Chen, Min

2016-09-27

RGB-D sensors (sensors with RGB camera and Depth camera) are novel sensing systems that capture RGB images along with pixel-wise depth information. Although they are widely used in various applications, RGB-D sensors have significant drawbacks including limited measurement ranges (e.g., within 3 m) and errors in depth measurement increase with distance from the sensor with respect to 3D dense mapping. In this paper, we present a novel approach to geometrically integrate the depth scene and RGB scene to enlarge the measurement distance of RGB-D sensors and enrich the details of model generated from depth images. First, precise calibration for RGB-D Sensors is introduced. In addition to the calibration of internal and external parameters for both, IR camera and RGB camera, the relative pose between RGB camera and IR camera is also calibrated. Second, to ensure poses accuracy of RGB images, a refined false features matches rejection method is introduced by combining the depth information and initial camera poses between frames of the RGB-D sensor. Then, a global optimization model is used to improve the accuracy of the camera pose, decreasing the inconsistencies between the depth frames in advance. In order to eliminate the geometric inconsistencies between RGB scene and depth scene, the scale ambiguity problem encountered during the pose estimation with RGB image sequences can be resolved by integrating the depth and visual information and a robust rigid-transformation recovery method is developed to register RGB scene to depth scene. The benefit of the proposed joint optimization method is firstly evaluated with the publicly available benchmark datasets collected with Kinect. Then, the proposed method is examined by tests with two sets of datasets collected in both outside and inside environments. The experimental results demonstrate the feasibility and robustness of the proposed method.

The pilatus unmanned aircraft system for lower atmospheric research

NASA Astrophysics Data System (ADS)

de Boer, G.; Palo, S.; Argrow, B.; LoDolce, G.; Mack, J.; Gao, R.-S.; Telg, H.; Trussel, C.; Fromm, J.; Long, C. N.; Bland, G.; Maslanik, J.; Schmid, B.; Hock, T.

2015-11-01

This paper presents details of the University of Colorado (CU) Pilatus unmanned research aircraft, assembled to provide measurements of aerosols, radiation and thermodynamics in the lower troposphere. This aircraft has a wingspan of 3.2 m and a maximum take off weight of 25 kg and is powered by an electric motor to reduce engine exhaust and concerns about carburetor icing. It carries instrumentation to make measurements of broadband up- and downwelling shortwave and longwave radiation, aerosol particle size distribution, atmospheric temperature, relative humidity and pressure and to collect video of flights for subsequent analysis of atmospheric conditions during flight. In order to make the shortwave radiation measurements, care was taken to carefully position a high-quality compact inertial measurement unit (IMU) and characterize the attitude of the aircraft and it's orientation to the upward looking radiation sensor. Using measurements from both of these sensors, a correction is applied to the raw radiometer measurements to correct for aircraft attitude and sensor tilt relative to the sun. The data acquisition system was designed from scratch based on a set of key driving requirements to accommodate the variety of sensors deployed. Initial test flights completed in Colorado provide promising results with measurements from the radiation sensors agreeing with those from a nearby surface site. Additionally, estimates of surface albedo from onboard sensors were consistent with local surface conditions, including melting snow and bright runway surface. Aerosol size distributions collected are internally consistent and have previously been shown to agree well with larger, surface-based instrumentation. Finally the atmospheric state measurements evolve as expected, with the near-surface atmosphere warming over time as the day goes on, and the atmospheric relative humidity decreasing with increased temperature. No directional bias on measured temperature, as might be expected due to uneven heating of the sensor housing over the course of a racetrack pattern, was detected. The results from these flights indicate that the CU Pilatus platform is capable of performing research grade lower tropospheric measurement missions.

The Pilatus unmanned aircraft system for lower atmospheric research

NASA Astrophysics Data System (ADS)

de Boer, Gijs; Palo, Scott; Argrow, Brian; LoDolce, Gabriel; Mack, James; Gao, Ru-Shan; Telg, Hagen; Trussel, Cameron; Fromm, Joshua; Long, Charles N.; Bland, Geoff; Maslanik, James; Schmid, Beat; Hock, Terry

2016-04-01

This paper presents details of the University of Colorado (CU) "Pilatus" unmanned research aircraft, assembled to provide measurements of aerosols, radiation and thermodynamics in the lower troposphere. This aircraft has a wingspan of 3.2 m and a maximum take-off weight of 25 kg, and it is powered by an electric motor to reduce engine exhaust and concerns about carburetor icing. It carries instrumentation to make measurements of broadband up- and downwelling shortwave and longwave radiation, aerosol particle size distribution, atmospheric temperature, relative humidity and pressure and to collect video of flights for subsequent analysis of atmospheric conditions during flight. In order to make the shortwave radiation measurements, care was taken to carefully position a high-quality compact inertial measurement unit (IMU) and characterize the attitude of the aircraft and its orientation to the upward-looking radiation sensor. Using measurements from both of these sensors, a correction is applied to the raw radiometer measurements to correct for aircraft attitude and sensor tilt relative to the sun. The data acquisition system was designed from scratch based on a set of key driving requirements to accommodate the variety of sensors deployed. Initial test flights completed in Colorado provide promising results with measurements from the radiation sensors agreeing with those from a nearby surface site. Additionally, estimates of surface albedo from onboard sensors were consistent with local surface conditions, including melting snow and bright runway surface. Aerosol size distributions collected are internally consistent and have previously been shown to agree well with larger, surface-based instrumentation. Finally the atmospheric state measurements evolve as expected, with the near-surface atmosphere warming over time as the day goes on, and the atmospheric relative humidity decreasing with increased temperature. No directional bias on measured temperature, as might be expected due to uneven heating of the sensor housing over the course of a racetrack pattern, was detected. The results from these flights indicate that the CU Pilatus platform is capable of performing research-grade lower tropospheric measurement missions.

Multifunctional Web Enabled Ocean Sensor Systems for the Monitoring of a Changing Ocean

NASA Astrophysics Data System (ADS)

Pearlman, Jay; Castro, Ayoze; Corrandino, Luigi; del Rio, Joaquin; Delory, Eric; Garello, Rene; Heuermann, Rudinger; Martinez, Enoc; Pearlman, Francoise; Rolin, Jean-Francois; Toma, Daniel; Waldmann, Christoph; Zielinski, Oliver

2016-04-01

As stated in the 2010 "Ostend Declaration", a major challenge in the coming years is the development of a truly integrated and sustainably funded European Ocean Observing System for supporting major policy initiatives such as the Integrated Maritime Policy and the Marine Strategy Framework Directive. This will be achieved with more long-term measurements of key parameters supported by a new generation of sensors whose costs and reliability will enable broad and consistent observations. Within the NeXOS project, a framework including new sensors capabilities and interface software has been put together that embraces the key technical aspects needed to improve the temporal and spatial coverage, resolution and quality of marine observations. The developments include new, low-cost, compact and integrated sensors with multiple functionalities that will allow for the measurements useful for a number of objectives, ranging from more precise monitoring and modeling of the marine environment to an improved assessment of fisheries. The project is entering its third year and will be demonstrating initial capabilities of optical and acoustic sensor prototypes that will become available for a number of platforms. For fisheries management, there is also a series of sensors that support an Ecosystem Approach to Fisheries (EAF). The greatest capabilities for comprehensive operations will occur when these sensors can be integrated into a multisensory capability on a single platform or multiply interconnected and coordinated platforms. Within NeXOS the full processing steps starting from the sensor signal all the way up to distributing collected environmental information will be encapsulated into standardized new state of the art Smart Sensor Interface and Web components to provide both improved integration and a flexible interface for scientists to control sensor operation. The use of the OGC SWE (Sensor Web Enablement) set of standards like OGC PUCK and SensorML at the instrument to platform integration phase will provide standard mechanisms for a truly plug'n'work connection. Through this, NeXOS Instruments will maintain within themselves specific information about how a platform (buoy controller, AUV controller, Observatory controller) has to configure and communicate with the instrument without the platform needing previous knowledge about the instrument. This mechanism is now being evaluated in real platforms like a Slocum Glider from Teledyne Web research, SeaExplorer Glider from Alseamar, Provor Float from NKE, and others including non commercial platforms like Obsea seafloor cabled observatory. The latest developments in the NeXOS sensors and the integration into an observation system will be discussed, addressing demonstration plans both for a variety of platforms and scientific objectives supporting marine management.

GEOS-3 phase B ground truth summary

NASA Technical Reports Server (NTRS)

Parsons, C. L.; Goodman, L. R.

1975-01-01

Ground truth data collected during the experiment systems calibration and evaluation phase of the Geodynamics experimental Ocean Satellite (GEOS-3) experiment are summarized. Both National Weather Service analyses and aircraft sensor data are included. The data are structured to facilitate the use of the various data products in calibrating the GEOS-3 radar altimeter and in assessing the altimeter's sensitivity to geophysical phenomena. Brief statements are made concerning the quality and completeness of the included data.

An Integrated System for Wildlife Sensing

DTIC Science & Technology

2014-08-14

design requirement. “Sensor Controller” software. A custom Sensor Controller application was developed for the Android device in order to collect...and log readings from that device’s sensors. “Camera Controller” software. A custom Camera Controller application was developed for the Android device...into 2 separate Android applications (Figure 4). The Sensor Controller logs readings periodically from the Android device’s organic sensors, and

Overview of the 2015 Algodones Sand Dunes field campaign to support sensor intercalibration

NASA Astrophysics Data System (ADS)

McCorkel, Joel; Bachmann, Charles M.; Coburn, Craig; Gerace, Aaron; Leigh, Larry; Czapla-Myers, Jeff; Helder, Dennis; Cook, Bruce

2018-01-01

Several sites from around the world are being used operationally and are suitable for vicarious calibration of space-borne imaging platforms. However, due to the proximity of these sites (e.g., Libya 4), a rigorous characterization of the landscape is not feasible, limiting their utility for sensor intercalibration efforts. Due to its accessibility and similarities to Libya 4, the Algodones Sand Dunes System in California, USA, was identified as a potentially attractive intercalibration site for space-borne, reflective instruments such as Landsat. In March 2015, a 4-day field campaign was conducted to develop an initial characterization of Algodones with a primary goal of assessing its intercalibration potential. Five organizations from the US and Canada collaborated to collect both active and passive airborne image data, spatial and temporal measurements of spectral bidirectional reflectance distribution function, and in-situ sand samples from several locations across the Algodones system. The collection activities conducted to support the campaign goal is summarized, including a summary of all instrumentation used, the data collected, and the experiments performed in an effort to characterize the Algodones site.

Calibration and Validation of the National Ecological Observatory Network's Airborne Imaging Spectrometers

NASA Astrophysics Data System (ADS)

Leisso, N.

2015-12-01

The National Ecological Observatory Network (NEON) is being constructed by the National Science Foundation and is slated for completion in 2017. NEON is designed to collect data to improve the understanding of changes in observed ecosystems. The observatory will produce data products on a variety of spatial and temporal scales collected from individual sites strategically located across the U.S. including Alaska, Hawaii, and Puerto Rico. Data sources include standardized terrestrial, instrumental, and aquatic observation systems in addition to three airborne remote sensing observation systems installed into leased Twin Otter aircraft. The Airborne Observation Platforms (AOP) are designed to collect 3-band aerial imagery, waveform and discrete LiDAR, and high-fidelity imaging spectroscopy data over the NEON sites annually at or near peak-greenness. The NEON Imaging Spectrometer (NIS) is a Visible and Shortwave Infrared (VSWIR) sensor designed by NASA JPL for ecological applications. Spectroscopic data is collected at 5-nm intervals across the solar-reflective spectral region (380-nm to 2500-nm) in a 34-degree FOV swath. A key uncertainty driver to the derived remote sensing NEON data products is the calibration of the imaging spectrometers. In addition, the calibration and accuracy of the higher-level data product algorithms is essential to the overall NEON mission to detect changes in the collected ecosystems over the 30-year expected lifetime. The typical calibration workflow of the NIS consists of the characterizing the focal plane, spectral calibration, and radiometric calibration. Laboratory spectral calibration is based on well-defined emission lines in conjunction with a scanning monochromator to define the individual spectral response functions. The radiometric calibration is NIST traceable and transferred to the NIS with an integrating sphere calibrated through the use of transfer radiometers. The laboratory calibration is monitored and maintained through the use of an On-Board Calibration (OBC) system. Recent advances in the understanding of the NIS sensor that have led to improvements in the overall calibration accuracy are reported. In addition, the NIS calibration and data products are compared to Earth-observing satellite sensors.

BOUSSOLE: A Joint CNRS-INSU, ESA, CNES, and NASA Ocean Color Calibration and Validation Activity

NASA Technical Reports Server (NTRS)

Antoine, David; Chami, Malik; Claustre, Herve; d'Ortenzio, Fabrizio; Morel, Andre; Becu, Guislain; Gentili, Bernard; Louis, Francis; Ras, Josephine; Roussier, Emmanuel;

A Tool for the Automated Collection of Space Utilization Data: Three Dimensional Space Utilization Monitor

NASA Technical Reports Server (NTRS)

Vos, Gordon A.; Fink, Patrick; Ngo, Phong H.; Morency, Richard; Simon, Cory; Williams, Robert E.; Perez, Lance C.

2015-01-01

Space Human Factors and Habitability (SHFH) Element within the Human Research Program (HRP), in collaboration with the Behavioral Health and Performance (BHP) Element, is conducting research regarding Net Habitable Volume (NHV), the internal volume within a spacecraft or habitat that is available to crew for required activities, as well as layout and accommodations within that volume. NASA is looking for innovative methods to unobtrusively collect NHV data without impacting crew time. Data required includes metrics such as location and orientation of crew, volume used to complete tasks, internal translation paths, flow of work, and task completion times. In less constrained environments methods for collecting such data exist yet many are obtrusive and require significant post-processing. Example technologies used in terrestrial settings include infrared (IR) retro-reflective marker based motion capture, GPS sensor tracking, inertial tracking, and multiple camera filmography. However due to constraints of space operations many such methods are infeasible, such as inertial tracking systems which typically rely upon a gravity vector to normalize sensor readings, and traditional IR systems which are large and require extensive calibration. However multiple technologies have not yet been applied to space operations for these explicit purposes. Two of these include 3-Dimensional Radio Frequency Identification Real-Time Localization Systems (3D RFID-RTLS) and depth imaging systems which allow for 3D motion capture and volumetric scanning (such as those using IR-depth cameras like the Microsoft Kinect or Light Detection and Ranging / Light-Radar systems, referred to as LIDAR).

A sensor simulation framework for the testing and evaluation of external hazard monitors and integrated alerting and notification functions

NASA Astrophysics Data System (ADS)

Uijt de Haag, Maarten; Venable, Kyle; Bezawada, Rajesh; Adami, Tony; Vadlamani, Ananth K.

2009-05-01

This paper discusses a sensor simulator/synthesizer framework that can be used to test and evaluate various sensor integration strategies for the implementation of an External Hazard Monitor (EHM) and Integrated Alerting and Notification (IAN) function as part of NASA's Integrated Intelligent Flight Deck (IIFD) project. The IIFD project under the NASA's Aviation Safety program "pursues technologies related to the flight deck that ensure crew workload and situational awareness are both safely optimized and adapted to the future operational environment as envisioned by NextGen." Within the simulation framework, various inputs to the IIFD and its subsystems, the EHM and IAN, are simulated, synthesized from actual collected data, or played back from actual flight test sensor data. Sensors and avionics included in this framework are TCAS, ADS-B, Forward-Looking Infrared, Vision cameras, GPS, Inertial navigators, EGPWS, Laser Detection and Ranging sensors, altimeters, communication links with ATC, and weather radar. The framework is implemented in Simulink, a modeling language developed by The Mathworks. This modeling language allows for test and evaluation of various sensor and communication link configurations as well as the inclusion of feedback from the pilot on the performance of the aircraft. Specifically, this paper addresses the architecture of the simulator, the sensor model interfaces, the timing and database (environment) aspects of the sensor models, the user interface of the modeling environment, and the various avionics implementations.

Identifying Objective Physiological Markers and Modifiable Behaviors for Self-Reported Stress and Mental Health Status Using Wearable Sensors and Mobile Phones: Observational Study.

PubMed

Sano, Akane; Taylor, Sara; McHill, Andrew W; Phillips, Andrew Jk; Barger, Laura K; Klerman, Elizabeth; Picard, Rosalind

2018-06-08

Wearable and mobile devices that capture multimodal data have the potential to identify risk factors for high stress and poor mental health and to provide information to improve health and well-being. We developed new tools that provide objective physiological and behavioral measures using wearable sensors and mobile phones, together with methods that improve their data integrity. The aim of this study was to examine, using machine learning, how accurately these measures could identify conditions of self-reported high stress and poor mental health and which of the underlying modalities and measures were most accurate in identifying those conditions. We designed and conducted the 1-month SNAPSHOT study that investigated how daily behaviors and social networks influence self-reported stress, mood, and other health or well-being-related factors. We collected over 145,000 hours of data from 201 college students (age: 18-25 years, male:female=1.8:1) at one university, all recruited within self-identified social groups. Each student filled out standardized pre- and postquestionnaires on stress and mental health; during the month, each student completed twice-daily electronic diaries (e-diaries), wore two wrist-based sensors that recorded continuous physical activity and autonomic physiology, and installed an app on their mobile phone that recorded phone usage and geolocation patterns. We developed tools to make data collection more efficient, including data-check systems for sensor and mobile phone data and an e-diary administrative module for study investigators to locate possible errors in the e-diaries and communicate with participants to correct their entries promptly, which reduced the time taken to clean e-diary data by 69%. We constructed features and applied machine learning to the multimodal data to identify factors associated with self-reported poststudy stress and mental health, including behaviors that can be possibly modified by the individual to improve these measures. We identified the physiological sensor, phone, mobility, and modifiable behavior features that were best predictors for stress and mental health classification. In general, wearable sensor features showed better classification performance than mobile phone or modifiable behavior features. Wearable sensor features, including skin conductance and temperature, reached 78.3% (148/189) accuracy for classifying students into high or low stress groups and 87% (41/47) accuracy for classifying high or low mental health groups. Modifiable behavior features, including number of naps, studying duration, calls, mobility patterns, and phone-screen-on time, reached 73.5% (139/189) accuracy for stress classification and 79% (37/47) accuracy for mental health classification. New semiautomated tools improved the efficiency of long-term ambulatory data collection from wearable and mobile devices. Applying machine learning to the resulting data revealed a set of both objective features and modifiable behavioral features that could classify self-reported high or low stress and mental health groups in a college student population better than previous studies and showed new insights into digital phenotyping. ©Akane Sano, Sara Taylor, Andrew W McHill, Andrew JK Phillips, Laura K Barger, Elizabeth Klerman, Rosalind Picard. Originally published in the Journal of Medical Internet Research (http://www.jmir.org), 08.06.2018.

Flexible DCP interface. [signal conditioning system for use with Kansas environmental sensors

NASA Technical Reports Server (NTRS)

Kanemasu, E. T. (Principal Investigator); Schimmelpfenning, H.

1974-01-01

The author has identified the following significant results. A user of an ERTS data collection system must supply the sensors and signal conditioning interface. The electronic interface must be compatible with the NASA-furnished data collection platform (DCP). A universal signal conditioning system for use with a wide range of environmental sensors is described. The interface is environmentally and electronically compatible with the DCP and has operated satisfactorily for a complete winter wheat growing season in Kansas.

Hydrologic Monitoring in the Deep Subsurface to Support Repository Performance

NASA Astrophysics Data System (ADS)

Hubbell, J. M.; Heath, G. L.; Scott, C. L.

2007-12-01

The INL has installed and operated several vadose and ground water monitoring systems in arid and humid sites to depths of about 200m. Some of these systems have been in continuous operation for over 12 years. It is important that the systems be physically robust, simple, yet versatile enough that it can operate for extended time periods with little or no maintenance. Monitoring instruments are frequently installed and run to characterize the site, collect data during site operation, and continue to run for long-term stewardship, necessitating sensors that can be maintained or serviced. Sensors are carefully chosen based on the perceived data requirements over the life of the site. An emphasis is given on direct measurements such as tensiometers (portable and advanced), neutron probe, drain gauge, temperature, wells or sampling for fluids and gases. Other complementary data can include using TDR/capacitance, radiation detectors, and larger scale geophysical techniques (3-d resistivity and EM) for volumetric measurements. Commercially available instruments may have to be modified for their use at greater depths, to allow multiple instruments in a single borehole or to perform the intended monitoring function. Access tubes (some open at the bottom) can be placed to allow insertion of multiple sensors (radiation, neutron and portable sensors/samplers), future drilling/sampling and to install new instruments at a later time. The installation techniques and backfill materials must be chosen and the measurement technique tested to ensure representative data collection for the parameters of interest. The data collection system can be linked to climatic data (precipitation, barometric pressure, snow depth, runoff, surface water sources) that may influence the site's subsurface hydrology. The instruments are then connected to a real-time automated data collection system that collect, stores, and provides access to the data. These systems have been developed that allow easy access, automatic data quality checks with notification, processing, and presentation of the data in real time through the web. The systems can be designed to manipulate/test the system remotely. Data from several sites will be presented showing that continuous monitoring is necessary to detect rapid changes in the deep vadose zone and ground water at fractured rock sites.

Earth resources research data facility R and D file. Volume 1: Documentary data

NASA Technical Reports Server (NTRS)

1971-01-01

Cumulative listings of the R and D file data are presented. All Earth Resources Program information available at the Manned Spacecraft Center is in Vol. 1. Sensor data collected during flights over NASA test sites and from missions flown by subcontractors supporting the Earth Resources Survey Program are included in Vol. 2.

Small pixel cross-talk MTF and its impact on MWIR sensor performance

NASA Astrophysics Data System (ADS)

Goss, Tristan M.; Willers, Cornelius J.

2017-05-01

As pixel sizes reduce in the development of modern High Definition (HD) Mid Wave Infrared (MWIR) detectors the interpixel cross-talk becomes increasingly difficult to regulate. The diffusion lengths required to achieve the quantum efficiency and sensitivity of MWIR detectors are typically longer than the pixel pitch dimension, and the probability of inter-pixel cross-talk increases as the pixel pitch/diffusion length fraction decreases. Inter-pixel cross-talk is most conveniently quantified by the focal plane array sampling Modulation Transfer Function (MTF). Cross-talk MTF will reduce the ideal sinc square pixel MTF that is commonly used when modelling sensor performance. However, cross-talk MTF data is not always readily available from detector suppliers, and since the origins of inter-pixel cross-talk are uniquely device and manufacturing process specific, no generic MTF models appear to satisfy the needs of the sensor designers and analysts. In this paper cross-talk MTF data has been collected from recent publications and the development for a generic cross-talk MTF model to fit this data is investigated. The resulting cross-talk MTF model is then included in a MWIR sensor model and the impact on sensor performance is evaluated in terms of the National Imagery Interoperability Rating Scale's (NIIRS) General Image Quality Equation (GIQE) metric for a range of fnumber/ detector pitch Fλ/d configurations and operating environments. By applying non-linear boost transfer functions in the signal processing chain, the contrast losses due to cross-talk may be compensated for. Boost transfer functions, however, also reduce the signal to noise ratio of the sensor. In this paper boost function limits are investigated and included in the sensor performance assessments.

Low Frequency Radar Sensor Observations of Tropical Forests in the Panama Canal Area

NASA Technical Reports Server (NTRS)

Imhoff, M. L.; Lawrence, W.; Condit, R.; Wright, J.; Johnson, P.; Hyer, J.; May, L.; Carson, S.; Smith, David E. (Technical Monitor)

2000-01-01

A synthetic aperture radar sensor operating in 5 bands between 80 and 120 MHz was flown over forested areas in the canal zone of the Republic of Panama in an experiment to measure biomass in heavy tropical forests. The sensor is a pulse coherent SAR flown on a small aircraft and oriented straight down. The doppler history is processed to collect data on the ground in rectangular cells of varying size over a range of incidence angles fore and aft of nadir (+45 to - 45 degrees). Sensor data consists of 5 frequency bands with 20 incidence angles per band. Sensor data for over 12+ sites were collected with forest stands having biomass densities ranging from 50 to 300 tons/ha dry above ground biomass. Results are shown exploring the biomass saturation thresholds using these frequencies, the system design is explained, and preliminary attempts at data visualization using this unique sensor design are described.

Branch-Based Centralized Data Collection for Smart Grids Using Wireless Sensor Networks

PubMed Central

Kim, Kwangsoo; Jin, Seong-il

2015-01-01

A smart grid is one of the most important applications in smart cities. In a smart grid, a smart meter acts as a sensor node in a sensor network, and a central device collects power usage from every smart meter. This paper focuses on a centralized data collection problem of how to collect every power usage from every meter without collisions in an environment in which the time synchronization among smart meters is not guaranteed. To solve the problem, we divide a tree that a sensor network constructs into several branches. A conflict-free query schedule is generated based on the branches. Each power usage is collected according to the schedule. The proposed method has important features: shortening query processing time and avoiding collisions between a query and query responses. We evaluate this method using the ns-2 simulator. The experimental results show that this method can achieve both collision avoidance and fast query processing at the same time. The success rate of data collection at a sink node executing this method is 100%. Its running time is about 35 percent faster than that of the round-robin method, and its memory size is reduced to about 10% of that of the depth-first search method. PMID:26007734

Branch-based centralized data collection for smart grids using wireless sensor networks.

PubMed

Kim, Kwangsoo; Jin, Seong-il

2015-05-21

A smart grid is one of the most important applications in smart cities. In a smart grid, a smart meter acts as a sensor node in a sensor network, and a central device collects power usage from every smart meter. This paper focuses on a centralized data collection problem of how to collect every power usage from every meter without collisions in an environment in which the time synchronization among smart meters is not guaranteed. To solve the problem, we divide a tree that a sensor network constructs into several branches. A conflict-free query schedule is generated based on the branches. Each power usage is collected according to the schedule. The proposed method has important features: shortening query processing time and avoiding collisions between a query and query responses. We evaluate this method using the ns-2 simulator. The experimental results show that this method can achieve both collision avoidance and fast query processing at the same time. The success rate of data collection at a sink node executing this method is 100%. Its running time is about 35 percent faster than that of the round-robin method, and its memory size is reduced to about 10% of that of the depth-first search method.

Trustworthy data collection from implantable medical devices via high-speed security implementation based on IEEE 1363.

PubMed

Hu, Fei; Hao, Qi; Lukowiak, Marcin; Sun, Qingquan; Wilhelm, Kyle; Radziszowski, Stanisław; Wu, Yao

2010-11-01

Implantable medical devices (IMDs) have played an important role in many medical fields. Any failure in IMDs operations could cause serious consequences and it is important to protect the IMDs access from unauthenticated access. This study investigates secure IMD data collection within a telehealthcare [mobile health (m-health)] network. We use medical sensors carried by patients to securely access IMD data and perform secure sensor-to-sensor communications between patients to relay the IMD data to a remote doctor's server. To meet the requirements on low computational complexity, we choose N-th degree truncated polynomial ring (NTRU)-based encryption/decryption to secure IMD-sensor and sensor-sensor communications. An extended matryoshkas model is developed to estimate direct/indirect trust relationship among sensors. An NTRU hardware implementation in very large integrated circuit hardware description language is studied based on industry Standard IEEE 1363 to increase the speed of key generation. The performance analysis results demonstrate the security robustness of the proposed IMD data access trust model.

A Spacecraft Housekeeping System-on-Chip in a Radiation Hardened Structured ASIC

NASA Technical Reports Server (NTRS)

Suarez, George; DuMonthier, Jeffrey J.; Sheikh, Salman S.; Powell, Wesley A.; King, Robyn L.

2012-01-01

Housekeeping systems are essential to health monitoring of spacecraft and instruments. Typically, sensors are distributed across various sub-systems and data is collected using components such as analog-to-digital converters, analog multiplexers and amplifiers. In most cases programmable devices are used to implement the data acquisition control and storage, and the interface to higher level systems. Such discrete implementations require additional size, weight, power and interconnect complexity versus an integrated circuit solution, as well as the qualification of multiple parts. Although commercial devices are readily available, they are not suitable for space applications due the radiation tolerance and qualification requirements. The Housekeeping System-o n-A-Chip (HKSOC) is a low power, radiation hardened integrated solution suitable for spacecraft and instrument control and data collection. A prototype has been designed and includes a wide variety of functions including a 16-channel analog front-end for driving and reading sensors, analog-to-digital and digital-to-analog converters, on-chip temperature sensor, power supply current sense circuits, general purpose comparators and amplifiers, a 32-bit processor, digital I/O, pulse-width modulation (PWM) generators, timers and I2C master and slave serial interfaces. In addition, the device can operate in a bypass mode where the processor is disabled and external logic is used to control the analog and mixed signal functions. The device is suitable for stand-alone or distributed systems where multiple chips can be deployed across different sub-systems as intelligent nodes with computing and processing capabilities.

International Space Station Instmments Collect Imagery of Natural Disasters

NASA Technical Reports Server (NTRS)

Evans, C. A.; Stefanov, W. L.

2013-01-01

A new focus for utilization of the International Space Station (ISS) is conducting basic and applied research that directly benefits Earth's citizenry. In the Earth Sciences, one such activity is collecting remotely sensed imagery of disaster areas and making those data immediately available through the USGS Hazards Data Distribution System, especially in response to activations of the International Charter for Space and Major Disasters (known informally as the "International Disaster Charter", or IDC). The ISS, together with other NASA orbital sensor assets, responds to IDC activations following notification by the USGS. Most of the activations are due to natural hazard events, including large floods, impacts of tropical systems, major fires, and volcanic eruptions and earthquakes. Through the ISS Program Science Office, we coordinate with ISS instrument teams for image acquisition using several imaging systems. As of 1 August 2013, we have successfully contributed imagery data in support of 14 Disaster Charter Activations, including regions in both Haiti and the east coast of the US impacted by Hurricane Sandy; flooding events in Russia, Mozambique, India, Germany and western Africa; and forest fires in Algeria and Ecuador. ISS-based sensors contributing data include the Hyperspectral Imager for the Coastal Ocean (HICO), the ISERV (ISS SERVIR Environmental Research and Visualization System) Pathfinder camera mounted in the US Window Observational Research Facility (WORF), the ISS Agricultural Camera (ISSAC), formerly operating from the WORF, and high resolution handheld camera photography collected by crew members (Crew Earth Observations). When orbital parameters and operations support data collection, ISS-based imagery adds to the resources available to disaster response teams and contributes to the publicdomain record of these events for later analyses.

NeXOS, developing and evaluating a new generation of insitu ocean observation systems.

NASA Astrophysics Data System (ADS)

Delory, Eric; del Rio, Joaquin; Golmen, Lars; Roar Hareide, Nils; Pearlman, Jay; Rolin, Jean-Francois; Waldmann, Christoph; Zielinski, Oliver

2017-04-01

Ocean biological, chemical or physical processes occur over widely varying scales in space and time: from micro- to kilometer scales, from less than seconds to centuries. While space systems supply important data and information, insitu data is necessary for comprehensive modeling and forecasting of ocean dynamics. Yet, collection of in-situ observation on these scales is inherently challenging and remains generally difficult and costly in time and resources. This paper address the innovations and significant developments for a new generation of insitu sensors in FP7 European Union project "Next generation, Cost- effective, Compact, Multifunctional Web Enabled Ocean Sensor Systems Empowering Marine, Maritime and Fisheries Management" or "NeXOS" for short. Optical and acoustics sensors are the focus of NeXOS but NeXOS moves beyond just sensors as systems that simultaneously address multiple objectives and applications are becoming increasingly important. Thus NeXOS takes a perspective of both sensors and sensor systems with significant advantages over existing observing capabilities via the implementation of innovations such as multiplatform integration, greater reliability through better antifouling management and greater sensor and data interoperability through use of OGC standards. This presentation will address the sensor system development and field-testing of the new NeXOS sensor systems. This is being done on multiple platforms including profiling floats, gliders, ships, buoys and subsea stations. The implementation of a data system based on SWE and PUCK furthers interoperability across measurements and platforms. This presentation will review the sensor system capabilities, the status of field tests and recommendations for long-term ocean monitoring.

Usage of Wireless Sensor Networks in a service based spatial data infrastructure for Landslide Monitoring and Early Warning

NASA Astrophysics Data System (ADS)

Arnhardt, C.; Fernandez-Steeger, T. M.; Walter, K.; Kallash, A.; Niemeyer, F.; Azzam, R.; Bill, R.

2007-12-01

The joint project Sensor based Landslide Early Warning System (SLEWS) aims at a systematic development of a prototyping alarm- and early warning system for the detection of mass movements by application of an ad hoc wireless sensor network (WSN). Next to the development of suitable sensor setups, sensor fusion and network fusion are applied to enhance data quality and reduce false alarm rates. Of special interest is the data retrieval, processing and visualization in GI-Systems. Therefore a suitable serviced based Spatial Data Infrastructure (SDI) will be developed with respect to existing and upcoming Open Geospatial Consortium (OGC) standards.The application of WSN provides a cheap and easy to set up solution for special monitoring and data gathering in large areas. Measurement data from different low-cost transducers for deformation observation (acceleration, displacement, tilting) is collected by distributed sensor nodes (motes), which interact separately and connect each other in a self-organizing manner. Data are collected and aggregated at the beacon (transmission station) and further operations like data pre-processing and compression can be performed. The WSN concept provides next to energy efficiency, miniaturization, real-time monitoring and remote operation, but also new monitoring strategies like sensor and network fusion. Since not only single sensors can be integrated at single motes either cross-validation or redundant sensor setups are possible to enhance data quality. The planned monitoring and information system will include a mobile infrastructure (information technologies and communication components) as well as methods and models to estimate surface deformation parameters (positioning systems). The measurements result in heterogeneous observation sets that have to be integrated in a common adjustment and filtering approach. Reliable real-time information will be obtained using a range of sensor input and algorithms, from which early warnings and prognosis may be derived. Implementation of sensor algorithms is an important task to form the business logic. This will be represented in self-contained web-based processing services (WPS). In the future different types of sensor networks can communicate via an infrastructure of OGC services using an interoperable way by standardized protocols as the Sensor Markup Language (SensorML) and Observations & Measurements Schema (O&M). Synchronous and asynchronous information services as the Sensor Alert Service (SAS) and the Web Notification Services (WNS) will provide defined users and user groups with time-critical readings from the observation site. Techniques using services for visualizing mapping data (WMS), meta data (CSW), vector (WFS) and raster data (WCS) will range from high detailed expert based output to fuzzy graphical warning elements.The expected results will be an advancement regarding classical alarm and early warning systems as the WSN are free scalable, extensible and easy to install.

Injury Risk Assessment of Extravehicular Mobility Unit (EMU) Phase VI and Series 4000 Gloves During Extravehicular Activity (EVA) Hand Manipulation Tasks

NASA Technical Reports Server (NTRS)

Kilby, Melissa

2015-01-01

Functional Extravehicular Mobility Units (EMUs) with high precision gloves are essential for the success of Extravehicular Activity (EVA). Previous research done at NASA has shown that total strength capabilities and performance are reduced when wearing a pressurized EMU. The goal of this project was to characterize the human-space suit glove interaction and assess the risk of injury during common EVA hand manipulation tasks, including pushing, pinching and gripping objects. A custom third generation sensor garment was designed to incorporate a combination of sensors, including force sensitive resistors, strain gauge sensors, and shear force sensors. The combination of sensors was used to measure the forces acting on the finger nails, finger pads, finger tips, as well as the knuckle joints. In addition to measuring the forces, data was collected on the temperature, humidity, skin conductance, and blood perfusion of the hands. Testing compared both the Phase VI and Series 4000 glove against an ungloved condition. The ungloved test was performed wearing the sensor garment only. The project outcomes identified critical landmarks that experienced higher workloads and are more likely to suffer injuries. These critical landmarks varied as a function of space suit glove and task performed. The results showed that less forces were acting on the hands while wearing the Phase VI glove as compared to wearing the Series 4000 glove. Based on our findings, the engineering division can utilize these methods for optimizing the current space suit glove and designing next generation gloves to prevent injuries and optimize hand mobility and comfort.

Applications of optical sensors for high-frequency water-quality monitoring and research

USGS Publications Warehouse

Pellerin, Brian

2015-01-01

The recent commercial availability of in-situ optical sensors, together with new techniques for data collection and analysis, provides the opportunity to monitor a wide range of water-quality constituents over time scales during which environmental conditions actually change. Traditional approaches for data collection (daily to monthly discrete samples) are often limited by high sample collection, processing, and analytical costs, difficult site access, and logistical challenges, particularly for long-term sampling at a large number of sites. Optical sensors that continuously measure constituents in the environment by absorbance or fluorescence properties (Figure 1) have had a long history of use in oceanography for measuring highly resolved concentrations and fluxes of organic matter, nutrients, and algal material. However, much of the work using commercially-available optical sensors in rivers and streams has taken place in only the last few years. Figure 1. [NOT SHOWN] Optical sensor technology is now sufficiently developed to warrant broader application for research and monitoring in coastal and freshwater systems, and the United States Geological Survey (a U.S. science agency) is now using these sensors in a variety of research and monitoring programs to better understand water quality in-situ and in real-time. Examples are numerous and range from the applications of nitrate sensors for calculating loads to estuaries susceptible to hypoxia (Pellerin et al., 2014) to the use of fluorometers to estimate methymercury fluxes (Bergamaschi et al., 2011) and disinfection byproduct formation (Carpenter et al., 2013). Transmitting these data in real-time provides information that can be used for early trend detection, help identify monitoring gaps critical for water management, and provide science-based decision support across a range of issues related to water quality, freshwater ecosystems, and human health. Despite the value of these sensors, collecting data that meet high-quality standards requires investment in and adherence to tested and established methods and protocols for sensor operation and data management (Pellerin et al., 2013). For example, optical sensor measurements can be strongly influenced by a variety of matrix effects, including water temperature, inner filtering from highly colored water, and scattering of light by suspended particles (Downing et al., 2012). Characterizing and correcting sensors for these effects – as well as the continued development of common methodologies and protocols for sensor use – will be critical to ensuring comparable measurements across sites and over time. In addition, collaborative efforts such as the Nutrient Sensor Challenge (www.nutrients-challenge.org) will continue to accelerate the development, production and use of affordable, reliable and accurate sensors for a range of environments. REFERENCES Bergamaschi .B.A., Fleck J.A., Downing B.D., Boss E., Pellerin B.A., Ganju N.K., Schoellhamer D.H., Byington A.A., Heim W.A., Stephenson M., Fujii R. (2011), Methyl mercury dynamics in a tidal wetland quantified using in situ optical measurements. Limnology and Oceanography, 56(4): 1355-1371. Carpenter K.D., Kraus T.E.C., Goldman J.H., Saraceno J., Downing B.D., Bergamaschi B.A., McGhee G., Triplett T. (2013), Sources and Characteristics of Organic Matter in the Clackamas River, Oregon, Related to the Formation of Disinfection By-products in Treated Drinking Water: U.S. Geological Survey Scientific Investigations Report 2013–5001, 78 p. Downing .B.D., Pellerin B.A., Bergamaschi B.A., Saraceno J., Kraus T.E.K. (2012), Seeing the light: The effects of particles, temperature and inner filtering on in situ CDOM fluorescence in rivers and streams. Limnology and Oceanography: Methods, 10: 767-775. Pellerin B.A., Bergamaschi B.A., Downing B.D., Saraceno J., Garrett J.D., Olsen L.D. (2013), Optical Techniques for the Determination of Nitrate in En

Imaging Radar in the Mojave Desert-Death Valley Region

NASA Technical Reports Server (NTRS)

Farr, Tom G.

2001-01-01

The Mojave Desert-Death Valley region has had a long history as a test bed for remote sensing techniques. Along with visible-near infrared and thermal IR sensors, imaging radars have flown and orbited over the area since the 1970's, yielding new insights into the geologic applications of these technologies. More recently, radar interferometry has been used to derive digital topographic maps of the area, supplementing the USGS 7.5' digital quadrangles currently available for nearly the entire area. As for their shorter-wavelength brethren, imaging radars were tested early in their civilian history in the Mojave Desert-Death Valley region because it contains a variety of surface types in a small area without the confounding effects of vegetation. The earliest imaging radars to be flown over the region included military tests of short-wavelength (3 cm) X-band sensors. Later, the Jet Propulsion Laboratory began its development of imaging radars with an airborne sensor, followed by the Seasat orbital radar in 1978. These systems were L-band (25 cm). Following Seasat, JPL embarked upon a series of Space Shuttle Imaging Radars: SIRA (1981), SIR-B (1984), and SIR-C (1994). The most recent in the series was the most capable radar sensor flown in space and acquired large numbers of data swaths in a variety of test areas around the world. The Mojave Desert-Death Valley region was one of those test areas, and was covered very well with 3 wavelengths, multiple polarizations, and at multiple angles. At the same time, the JPL aircraft radar program continued improving and collecting data over the Mojave Desert Death Valley region. Now called AIRSAR, the system includes 3 bands (P-band, 67 cm; L-band, 25 cm; C-band, 5 cm). Each band can collect all possible polarizations in a mode called polarimetry. In addition, AIRSAR can be operated in the TOPSAR mode wherein 2 antennas collect data interferometrically, yielding a digital elevation model (DEM). Both L-band and C-band can be operated in this way, with horizontal resolution of about 5 m and vertical errors less than 2 m. The findings and developments of these earlier investigations are discussed.

Neutron detection apparatus and method

DOE Office of Scientific and Technical Information (OSTI.GOV)

Derzon, Mark S.; Borek, III, Theodore T.

An apparatus for neutron detection is provided. The apparatus comprises a sensor medium in electrical contact with an electrode arrangement conformed to collect radiation-generated charge from the sensor medium. The sensor medium comprises a borazine and/or a borazine-based polymer.

AOI [3]: Smart Refractory Sensor Systems for Wireless Monitoring of Temperature, Health, and Degradation of Slagging Gasifiers

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sabolsky, Edward M.; Bhattacharyya, Debangsu; Graham, David

The objective of the work was to develop refractory “smart bricks”, which would contain embedded temperature, strain/stress, and spallation sensors throughout the volume of high-chromia (-Cr2O3) refractory brick. The proposed work included work to interconnect the sensors to the reactor exterior, where the sensor signals may be processed by low-power electronics and transmitted wirelessly to a central processing hub. The data processing and wireless transmitter hardware was specifically designed to be isolated (with low power consumption) and to be adaptable to future implementation of energy-harvesting strategies for extended life. Finally, the collected data was incorporated into a model to estimatemore » refractory degradation, a technique that could help monitor the health of the refractory in real-time. The long-term goal of this program was to demonstrate high-temperature, wireless sensor arrays for in situ three-dimensional (3-D) refractory monitoring or mapping for slagging gasification systems. The research was in collaboration with HarbisonWalker International (HWI) Technology Center in West Mifflin, PA. HWI is a leading developer and manufacturer of ceramic refractory products for high-temperature applications. The work completed focused on the following areas: 1) Investigation of the chemical stability, microstructural evolution, grain growth kinetics, degree of homogeneity (quantitative image analysis), and electrical properties of refractory oxide-silicide composites at temperatures between 750-1450ºC; 2) Fabrication of silicide-alumina composite and oxide thermocouples and thermistor preforms and the development of techniques to embed them into high-chromia refractory bricks to form “smart bricks”; 3) Utilization of commercial off-the-shelf discrete components to prototype circuits for interfacing between smart brick sensors and the wireless sensor network. The prototypes were then used to design an integrated circuit for thermistor, thermocouple, and capacitive-based smart brick sensor interfacing; 4) Interfacing of the smart bricks with embedded sensors with wireless motes thus yielding a complete signal chain. This end-to-end data collection system was tested on a furnace heated to 1350 °C; 5) Development of a slag penetration model and a nonlinear unknown input filter for the data from the embedded sensors for estimating temperature and extent of slag penetration.« less

Non-traditional Sensor Tasking for SSA: A Case Study

NASA Astrophysics Data System (ADS)

Herz, A.; Herz, E.; Center, K.; Martinez, I.; Favero, N.; Clark, C.; Therien, W.; Jeffries, M.

Industry has recognized that maintaining SSA of the orbital environment going forward is too challenging for the government alone. Consequently there are a significant number of commercial activities in various stages of development standing-up novel sensors and sensor networks to assist in SSA gathering and dissemination. Use of these systems will allow government and military operators to focus on the most sensitive space control issues while allocating routine or lower priority data gathering responsibility to the commercial side. The fact that there will be multiple (perhaps many) commercial sensor capabilities available in this new operational model begets a common access solution. Absent a central access point to assert data needs, optimized use of all commercial sensor resources is not possible and the opportunity for coordinated collections satisfying overarching SSA-elevating objectives is lost. Orbit Logic is maturing its Heimdall Web system - an architecture facilitating “data requestor” perspectives (allowing government operations centers to assert SSA data gathering objectives) and “sensor operator” perspectives (through which multiple sensors of varying phenomenology and capability are integrated via machine -machine interfaces). When requestors submit their needs, Heimdall’s planning engine determines tasking schedules across all sensors, optimizing their use via an SSA-specific figure-of-merit. ExoAnalytic was a key partner in refining the sensor operator interfaces, working with Orbit Logic through specific details of sensor tasking schedule delivery and the return of observation data. Scant preparation on both sides preceded several integration exercises (walk-then-run style), which culminated in successful demonstration of the ability to supply optimized schedules for routine public catalog data collection – then adapt sensor tasking schedules in real-time upon receipt of urgent data collection requests. This paper will provide a narrative of the joint integration process - detailing decision points, compromises, and results obtained on the road toward a set of interoperability standards for commercial sensor accommodation.

Sensor Web Dynamic Measurement Techniques and Adaptive Observing Strategies

NASA Technical Reports Server (NTRS)

Talabac, Stephen J.

2004-01-01

Sensor Web observing systems may have the potential to significantly improve our ability to monitor, understand, and predict the evolution of rapidly evolving, transient, or variable environmental features and events. This improvement will come about by integrating novel data collection techniques, new or improved instruments, emerging communications technologies and protocols, sensor mark-up languages, and interoperable planning and scheduling systems. In contrast to today's observing systems, "event-driven" sensor webs will synthesize real- or near-real time measurements and information from other platforms and then react by reconfiguring the platforms and instruments to invoke new measurement modes and adaptive observation strategies. Similarly, "model-driven" sensor webs will utilize environmental prediction models to initiate targeted sensor measurements or to use a new observing strategy. The sensor web concept contrasts with today's data collection techniques and observing system operations concepts where independent measurements are made by remote sensing and in situ platforms that do not share, and therefore cannot act upon, potentially useful complementary sensor measurement data and platform state information. This presentation describes NASA's view of event-driven and model-driven Sensor Webs and highlights several research and development activities at the Goddard Space Flight Center.

New Flexible Silicone-Based EEG Dry Sensor Material Compositions Exhibiting Improvements in Lifespan, Conductivity, and Reliability.

PubMed

Yu, Yi-Hsin; Chen, Shih-Hsun; Chang, Che-Lun; Lin, Chin-Teng; Hairston, W David; Mrozek, Randy A

2016-10-31

This study investigates alternative material compositions for flexible silicone-based dry electroencephalography (EEG) electrodes to improve the performance lifespan while maintaining high-fidelity transmission of EEG signals. Electrode materials were fabricated with varying concentrations of silver-coated silica and silver flakes to evaluate their electrical, mechanical, and EEG transmission performance. Scanning electron microscope (SEM) analysis of the initial electrode development identified some weak points in the sensors' construction, including particle pull-out and ablation of the silver coating on the silica filler. The newly-developed sensor materials achieved significant improvement in EEG measurements while maintaining the advantages of previous silicone-based electrodes, including flexibility and non-toxicity. The experimental results indicated that the proposed electrodes maintained suitable performance even after exposure to temperature fluctuations, 85% relative humidity, and enhanced corrosion conditions demonstrating improvements in the environmental stability. Fabricated flat (forehead) and acicular (hairy sites) electrodes composed of the optimum identified formulation exhibited low impedance and reliable EEG measurement; some initial human experiments demonstrate the feasibility of using these silicone-based electrodes for typical lab data collection applications.

The accuracy and efficacy of real-time continuous glucose monitoring sensor in Chinese diabetes patients: a multicenter study.

PubMed

Zhou, Jian; Lv, Xiaofeng; Mu, Yiming; Wang, Xianling; Li, Jing; Zhang, Xingguang; Wu, Jinxiao; Bao, Yuqian; Jia, Weiping

2012-08-01

The purpose of this multicenter study was to investigate the accuracy of a real-time continuous glucose monitoring sensor in Chinese diabetes patients. In total, 48 patients with type 1 or 2 diabetes from three centers in China were included in the study. The MiniMed Paradigm(®) 722 insulin pump (Medtronic, Northridge, CA) was used to monitor the real-time continuous changes of blood glucose levels for three successive days. Venous blood of the subjects was randomly collected every 15 min for seven consecutive hours on the day when the subjects were wearing the sensor. Reference values were provided by the YSI(®) 2300 STAT PLUS™ glucose and lactate analyzer (YSI Life Sciences, Yellow Springs, OH). In total, 1,317 paired YSI-sensor values were collected from the 48 patients. Of the sensor readings, 88.3% (95% confidence interval, 0.84-0.92) were within±20% of the YSI values, and 95.7% were within±30% of the YSI values. Clarke and consensus error grid analyses showed that the ratios of the YSI-sensor values in Zone A to the values in Zone B were 99.1% and 99.9%, respectively. Continuous error grid analysis showed that the ratios of the YSI-sensor values in the region of accurate reading, benign errors, and erroneous reading were 96.4%, 1.8%, and 1.8%, respectively. The mean absolute relative difference (ARD) for all subjects was 10.4%, and the median ARD was 7.8%. Bland-Altman analysis detected a mean blood glucose level of 3.84 mg/dL. Trend analysis revealed that 86.1% of the difference of the rates of change between the YSI values and the sensor readings occurred within the range of 1 mg/dL/min. The Paradigm insulin pump has high accuracy in both monitoring the real-time continuous changes and predicting the trend of changes in blood glucose level. However, actual clinical manifestations should be taken into account for diagnosis of hypoglycemia.

Optimal UAS Assignments and Trajectories for Persistent Surveillance and Data Collection from a Wireless Sensor Network

DTIC Science & Technology

2015-12-24

minimizing a weighted sum ofthe time and control effort needed to collect sensor data. This problem formulation is a modified traveling salesman ...29 2.5 The Shortest Path Problem . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 30 2.5.1 Traveling Salesman Problem ...48 3.3.1 Initial Guess by Traveling Salesman Problem Solution

MODIS Cloud Microphysics Product (MOD_PR06OD) Data Collection 6 Updates

NASA Technical Reports Server (NTRS)

Wind, Gala; Platnick, Steven; King, Michael D.

2014-01-01

The MODIS Cloud Optical and Microphysical Product (MOD_PR060D) for Data Collection 6 has entered full scale production. Aqua reprocessing is almost completed and Terra reprocessing will begin shortly. Unlike previous collections, the CHIMAERA code base allows for simultaneous processing for multiple sensors and the operational CHIMAERA 6.0.76 stream is also available for VIIRS and SEVIRI sensors and for our E-MAS airborne platform.

Sensor Fusion for Nuclear Proliferation Activity Monitoring

DOE Office of Scientific and Technical Information (OSTI.GOV)

Adel Ghanem, Ph D

2007-03-30

The objective of Phase 1 of this STTR project is to demonstrate a Proof-of-Concept (PoC) of the Geo-Rad system that integrates a location-aware SmartTag (made by ZonTrak) and a radiation detector (developed by LLNL). It also includes the ability to transmit the collected radiation data and location information to the ZonTrak server (ZonService). The collected data is further transmitted to a central server at LLNL (the Fusion Server) to be processed in conjunction with overhead imagery to generate location estimates of nuclear proliferation and radiation sources.

Developing hydrological monitoring networks with Arduino

NASA Astrophysics Data System (ADS)

Buytaert, Wouter; Vega, Andres; Villacis, Marcos; Moulds, Simon

2015-04-01

The open source hardware platform Arduino is very cost-effective and versatile for the development of sensor networks. Here we report on experiments on the use of Arduino-related technologies to develop and implement hydrological monitoring networks. Arduino Uno boards were coupled to a variety of commercially available hydrological sensors and programmed for automatic data collection. Tested sensors include water level, temperature, humidity, radiation, and precipitation. Our experiments show that most of the tested analogue sensors are quite straightforward to couple to Arduino based data loggers, especially if the electronic characteristics of the sensor are available. However, some sensors have internal digital interfaces, which are more challenging to connect. Lastly, tipping bucket rain gauges prove the most challenging because of the very specific methodology, i.e. registration of bucket tips instead of measurements at regular intervals. The typically low data generation rate of hydrological instruments is very compatible with available technologies for wireless data transmission. Mesh networks such as Xbee prove very convenient and robust for dispersed networks, while wifi is also an option for shorter distances and particular topographies. Lastly, the GSM shield of the Arduino can be used to transfer data to centralized databases. In regions where no mobile internet (i.e. 3G) connection is available, data transmission via text messages may be an option, depending on the bandwidth requirements.

On-Line Temperature Estimation for Noisy Thermal Sensors Using a Smoothing Filter-Based Kalman Predictor

PubMed Central

Li, Zhi; Wei, Henglu; Zhou, Wei; Duan, Zhemin

2018-01-01

Dynamic thermal management (DTM) mechanisms utilize embedded thermal sensors to collect fine-grained temperature information for monitoring the real-time thermal behavior of multi-core processors. However, embedded thermal sensors are very susceptible to a variety of sources of noise, including environmental uncertainty and process variation. This causes the discrepancies between actual temperatures and those observed by on-chip thermal sensors, which seriously affect the efficiency of DTM. In this paper, a smoothing filter-based Kalman prediction technique is proposed to accurately estimate the temperatures from noisy sensor readings. For the multi-sensor estimation scenario, the spatial correlations among different sensor locations are exploited. On this basis, a multi-sensor synergistic calibration algorithm (known as MSSCA) is proposed to improve the simultaneous prediction accuracy of multiple sensors. Moreover, an infrared imaging-based temperature measurement technique is also proposed to capture the thermal traces of an advanced micro devices (AMD) quad-core processor in real time. The acquired real temperature data are used to evaluate our prediction performance. Simulation shows that the proposed synergistic calibration scheme can reduce the root-mean-square error (RMSE) by 1.2 ∘C and increase the signal-to-noise ratio (SNR) by 15.8 dB (with a very small average runtime overhead) compared with assuming the thermal sensor readings to be ideal. Additionally, the average false alarm rate (FAR) of the corrected sensor temperature readings can be reduced by 28.6%. These results clearly demonstrate that if our approach is used to perform temperature estimation, the response mechanisms of DTM can be triggered to adjust the voltages, frequencies, and cooling fan speeds at more appropriate times. PMID:29393862

On-Line Temperature Estimation for Noisy Thermal Sensors Using a Smoothing Filter-Based Kalman Predictor.

PubMed

Li, Xin; Ou, Xingtao; Li, Zhi; Wei, Henglu; Zhou, Wei; Duan, Zhemin

2018-02-02

Dynamic thermal management (DTM) mechanisms utilize embedded thermal sensors to collect fine-grained temperature information for monitoring the real-time thermal behavior of multi-core processors. However, embedded thermal sensors are very susceptible to a variety of sources of noise, including environmental uncertainty and process variation. This causes the discrepancies between actual temperatures and those observed by on-chip thermal sensors, which seriously affect the efficiency of DTM. In this paper, a smoothing filter-based Kalman prediction technique is proposed to accurately estimate the temperatures from noisy sensor readings. For the multi-sensor estimation scenario, the spatial correlations among different sensor locations are exploited. On this basis, a multi-sensor synergistic calibration algorithm (known as MSSCA) is proposed to improve the simultaneous prediction accuracy of multiple sensors. Moreover, an infrared imaging-based temperature measurement technique is also proposed to capture the thermal traces of an advanced micro devices (AMD) quad-core processor in real time. The acquired real temperature data are used to evaluate our prediction performance. Simulation shows that the proposed synergistic calibration scheme can reduce the root-mean-square error (RMSE) by 1.2 ∘ C and increase the signal-to-noise ratio (SNR) by 15.8 dB (with a very small average runtime overhead) compared with assuming the thermal sensor readings to be ideal. Additionally, the average false alarm rate (FAR) of the corrected sensor temperature readings can be reduced by 28.6%. These results clearly demonstrate that if our approach is used to perform temperature estimation, the response mechanisms of DTM can be triggered to adjust the voltages, frequencies, and cooling fan speeds at more appropriate times.

Fiber optic laser-induced breakdown spectroscopy sensor for molten material analysis

DOEpatents

Zhang, Hansheng; Rai, Awadesh K.; Singh, Jagdish P.; Yueh, Fang-Yu

2004-07-13

A fiber optic laser-induced breakdown spectroscopy (LIBS) sensor, including a laser light source, a harmonic separator for directing the laser light, a dichroic mirror for reflecting the laser light, a coupling lens for coupling the laser light at an input of a multimode optical fiber, a connector for coupling the laser light from an output of the multimode optical fiber to an input of a high temperature holder, such as a holder made of stainless steel, and a detector portion for receiving emission signal and analyzing LIBS intensities. In one variation, the multimode optical fiber has silica core and silica cladding. The holder includes optical lenses for collimating and focusing the laser light in a molten alloy to produce a plasma, and for collecting and transmitting an emission signal to the multimode optical fiber.

Real-Time Wireless Data Acquisition System

NASA Technical Reports Server (NTRS)

Valencia, Emilio J.; Perotti, Jose; Lucena, Angel; Mata, Carlos

2007-01-01

Current and future aerospace requirements demand the creation of a new breed of sensing devices, with emphasis on reduced weight, power consumption, and physical size. This new generation of sensors must possess a high degree of intelligence to provide critical data efficiently and in real-time. Intelligence will include self-calibration, self-health assessment, and pre-processing of raw data at the sensor level. Most of these features are already incorporated in the Wireless Sensors Network (SensorNet(TradeMark)), developed by the Instrumentation Group at Kennedy Space Center (KSC). A system based on the SensorNet(TradeMark) architecture consists of data collection point(s) called Central Stations (CS) and intelligent sensors called Remote Stations (RS) where one or more CSs can be accommodated depending on the specific application. The CS's major function is to establish communications with the Remote Stations and to poll each RS for data and health information. The CS also collects, stores and distributes these data to the appropriate systems requiring the information. The system has the ability to perform point-to-point, multi-point and relay mode communications with an autonomous self-diagnosis of each communications link. Upon detection of a communication failure, the system automatically reconfigures to establish new communication paths. These communication paths are automatically and autonomously selected as the best paths by the system based on the existing operating environment. The data acquisition system currently under development at KSC consists of the SensorNet(TradeMark) wireless sensors as the remote stations and the central station called the Radio Frequency Health Node (RFHN). The RFF1N is the central station which remotely communicates with the SensorNet(TradeMark) sensors to control them and to receive data. The system's salient feature is the ability to provide deterministic sensor data with accurate time stamps for both time critical and non-time critical applications. Current wireless standards such as Zigbee(TradeMark) and Bluetooth(Registered TradeMark) do not have these capabilities and can not meet the needs that are provided by the SensorNet technology. Additionally, the system has the ability to automatically reconfigure the wireless communication link to a secondary frequency if interference is encountered and can autonomously search for a sensor that was perceived to be lost using the relay capabilities of the sensors and the secondary frequency. The RFHN and the SensorNet designs are based on modular architectures that allow for future increases in capability and the ability to expand or upgrade with relative ease. The RFHN and SensorNet sensors .can also perform data processing which forms a distributed processing architecture allowing the system to pass along information rather than just sending "raw data points" to the next higher level system. With a relatively small size, weight and power consumption, this system has the potential for both spacecraft and aircraft applications as well as ground applications that require time critical data.

Nonlinear estimation for arrays of chemical sensors

NASA Astrophysics Data System (ADS)

Yosinski, Jason; Paffenroth, Randy

2010-04-01

Reliable detection of hazardous materials is a fundamental requirement of any national security program. Such materials can take a wide range of forms including metals, radioisotopes, volatile organic compounds, and biological contaminants. In particular, detection of hazardous materials in highly challenging conditions - such as in cluttered ambient environments, where complex collections of analytes are present, and with sensors lacking specificity for the analytes of interest - is an important part of a robust security infrastructure. Sophisticated single sensor systems provide good specificity for a limited set of analytes but often have cumbersome hardware and environmental requirements. On the other hand, simple, broadly responsive sensors are easily fabricated and efficiently deployed, but such sensors individually have neither the specificity nor the selectivity to address analyte differentiation in challenging environments. However, arrays of broadly responsive sensors can provide much of the sensitivity and selectivity of sophisticated sensors but without the substantial hardware overhead. Unfortunately, arrays of simple sensors are not without their challenges - the selectivity of such arrays can only be realized if the data is first distilled using highly advanced signal processing algorithms. In this paper we will demonstrate how the use of powerful estimation algorithms, based on those commonly used within the target tracking community, can be extended to the chemical detection arena. Herein our focus is on algorithms that not only provide accurate estimates of the mixture of analytes in a sample, but also provide robust measures of ambiguity, such as covariances.

The EO-1 hyperion and advanced land imager sensors for use in tundra classification studies within the Upper Kuparuk River Basin, Alaska

NASA Astrophysics Data System (ADS)

Hall-Brown, Mary

The heterogeneity of Arctic vegetation can make land cover classification vey difficult when using medium to small resolution imagery (Schneider et al., 2009; Muller et al., 1999). Using high radiometric and spatial resolution imagery, such as the SPOT 5 and IKONOS satellites, have helped arctic land cover classification accuracies rise into the 80 and 90 percentiles (Allard, 2003; Stine et al., 2010; Muller et al., 1999). However, those increases usually come at a high price. High resolution imagery is very expensive and can often add tens of thousands of dollars onto the cost of the research. The EO-1 satellite launched in 2002 carries two sensors that have high specral and/or high spatial resolutions and can be an acceptable compromise between the resolution versus cost issues. The Hyperion is a hyperspectral sensor with the capability of collecting 242 spectral bands of information. The Advanced Land Imager (ALI) is an advanced multispectral sensor whose spatial resolution can be sharpened to 10 meters. This dissertation compares the accuracies of arctic land cover classifications produced by the Hyperion and ALI sensors to the classification accuracies produced by the Systeme Pour l' Observation de le Terre (SPOT), the Landsat Thematic Mapper (TM) and the Landsat Enhanced Thematic Mapper Plus (ETM+) sensors. Hyperion and ALI images from August 2004 were collected over the Upper Kuparuk River Basin, Alaska. Image processing included the stepwise discriminant analysis of pixels that were positively classified from coinciding ground control points, geometric and radiometric correction, and principle component analysis. Finally, stratified random sampling was used to perform accuracy assessments on satellite derived land cover classifications. Accuracy was estimated from an error matrix (confusion matrix) that provided the overall, producer's and user's accuracies. This research found that while the Hyperion sensor produced classfication accuracies that were equivalent to the TM and ETM+ sensor (approximately 78%), the Hyperion could not obtain the accuracy of the SPOT 5 HRV sensor. However, the land cover classifications derived from the ALI sensor exceeded most classification accuracies derived from the TM and ETM+ senors and were even comparable to most SPOT 5 HRV classifications (87%). With the deactivation of the Landsat series satellites, the monitoring of remote locations such as in the Arctic on an uninterupted basis thoughout the world is in jeopardy. The utilization of the Hyperion and ALI sensors are a way to keep that endeavor operational. By keeping the ALI sensor active at all times, uninterupted observation of the entire Earth can be accomplished. Keeping the Hyperion sensor as a "tasked" sensor can provide scientists with additional imagery and options for their studies without overburdening storage issues.

Optimizing qPlus sensor assemblies for simultaneous scanning tunneling and noncontact atomic force microscopy operation based on finite element method analysis

DOE PAGES

Dagdeviren, Omur E.; Schwarz, Udo D.

2017-03-20

Quartz tuning forks that have a probe tip attached to the end of one of its prongs while the other prong is arrested to a holder (“qPlus” configuration) have gained considerable popularity in recent years for high-resolution atomic force microscopy imaging. The small size of the tuning forks and the complexity of the sensor architecture, however, often impede predictions on how variations in the execution of the individual assembly steps affect the performance of the completed sensor. Extending an earlier study that provided numerical analysis of qPlus-style setups without tips, this work quantifies the influence of tip attachment on themore » operational characteristics of the sensor. The results using finite element modeling show in particular that for setups that include a metallic tip that is connected via a separate wire to enable the simultaneous collection of local forces and tunneling currents, the exact realization of this wire connection has a major effect on sensor properties such as spring constant, quality factor, resonance frequency, and its deviation from an ideal vertical oscillation.« less

Optimizing qPlus sensor assemblies for simultaneous scanning tunneling and noncontact atomic force microscopy operation based on finite element method analysis

DOE Office of Scientific and Technical Information (OSTI.GOV)

Dagdeviren, Omur E.; Schwarz, Udo D.

Quartz tuning forks that have a probe tip attached to the end of one of its prongs while the other prong is arrested to a holder (“qPlus” configuration) have gained considerable popularity in recent years for high-resolution atomic force microscopy imaging. The small size of the tuning forks and the complexity of the sensor architecture, however, often impede predictions on how variations in the execution of the individual assembly steps affect the performance of the completed sensor. Extending an earlier study that provided numerical analysis of qPlus-style setups without tips, this work quantifies the influence of tip attachment on themore » operational characteristics of the sensor. The results using finite element modeling show in particular that for setups that include a metallic tip that is connected via a separate wire to enable the simultaneous collection of local forces and tunneling currents, the exact realization of this wire connection has a major effect on sensor properties such as spring constant, quality factor, resonance frequency, and its deviation from an ideal vertical oscillation.« less

Localization of a continuous CO2 leak from an isotropic flat-surface structure using acoustic emission detection and near-field beamforming techniques

NASA Astrophysics Data System (ADS)

Yan, Yong; Cui, Xiwang; Guo, Miao; Han, Xiaojuan

2016-11-01

Seal capacity is of great importance for the safety operation of pressurized vessels. It is crucial to locate the leak hole timely and accurately for reasons of safety and maintenance. This paper presents the principle and application of a linear acoustic emission sensor array and a near-field beamforming technique to identify the location of a continuous CO2 leak from an isotropic flat-surface structure on a pressurized vessel in the carbon capture and storage system. Acoustic signals generated by the leak hole are collected using a linear high-frequency sensor array. Time-frequency analysis and a narrow-band filtering technique are deployed to extract effective information about the leak. The impacts of various factors on the performance of the localization technique are simulated, compared and discussed, including the number of sensors, distance between the leak hole and sensor array and spacing between adjacent sensors. Experiments were carried out on a laboratory-scale test rig to assess the effectiveness and operability of the proposed method. The results obtained suggest that the proposed method is capable of providing accurate and reliable localization of a continuous CO2 leak.

End-To-End performance test of the LINC-NIRVANA Wavefront-Sensor system.

NASA Astrophysics Data System (ADS)

Berwein, Juergen; Bertram, Thomas; Conrad, Al; Briegel, Florian; Kittmann, Frank; Zhang, Xiangyu; Mohr, Lars

2011-09-01

LINC-NIRVANA is an imaging Fizeau interferometer, for use in near infrared wavelengths, being built for the Large Binocular Telescope. Multi-conjugate adaptive optics (MCAO) increases the sky coverage and the field of view over which diffraction limited images can be obtained. For its MCAO implementation, Linc-Nirvana utilizes four total wavefront sensors; each of the two beams is corrected by both a ground-layer wavefront sensor (GWS) and a high-layer wavefront sensor (HWS). The GWS controls the adaptive secondary deformable mirror (DM), which is based on an DSP slope computing unit. Whereas the HWS controls an internal DM via computations provided by an off-the-shelf multi-core Linux system. Using wavefront sensor data collected from a prior lab experiment, we have shown via simulation that the Linux based system is sufficient to operate at 1kHz, with jitter well below the needs of the final system. Based on that setup we tested the end-to-end performance and latency through all parts of the system which includes the camera, the wavefront controller, and the deformable mirror. We will present our loop control structure and the results of those performance tests.

Investigation of hydrologic and biogeochemical controls on arsenic mobilization using distributed sensing at a field site in Munshiganj, Bangladesh

NASA Astrophysics Data System (ADS)

Ramanathan, N.; Estrin, D.; Harmon, T.; Harvey, C.; Jay, J.; Kohler, E.; Rothenberg, S.

2006-12-01

The presence of arsenic in the groundwater has led to the largest environmental poisoning in history; tens of millions of people in the Ganges Delta continue to drink groundwater that is dangerously contaminated with arsenic. A current working hypothesis is that arsenic is mobilized in the near surface environment where sediments are weathered by seasonal changes in the redox state that drive a cycle of pyrite oxidation and iron oxide reduction. In order to test the supporting hypothesis that subsurface geochemical changes may be induced by agricultural activity, we deployed 42 wirelessly networked ion-selective electrodes, including calcium, ammonium, nitrate, ORP, chloride, carbonate, and pH in a rice paddy in the Munshiganj district of Bangladesh in January of 2006. Each sensor was connected to an MDA300 sensor board and Mica2 wireless transceiver and computational device. Over a period of 11 days, we observed clear diel, and diurnal trends in 4 of the electrodes (calcium, ammonium, chloride and carbonate). The trends may be due to hydrological changes, or geochemical changes induced either by photosynthesis in the overlying water (which then infiltrated to the depth of the sensors) or in the root zone of rice plants. While the spatiotemporally dense measurements from wireless sensor networks enable scientists to ask new questions and elucidate complex relationships in heterogeneous physical environments such as soil, there are many practical issues to address in order to collect data usable for scientific purposes. For example, in response to a stream of faults in one of our sensor network deployments, we designed Sympathy to enable users to find and fix problems impacting the quantity of data collected in the field. Sympathy detects packet loss experienced at the base station and systematically assigns blame to faulty components in the network for remediation, replacing the prior policy of ad-hoc node rebooting and battery replacements. Sympathy has been deployed in many habitat monitoring sensor networks. While using Sympathy at our Bangladesh field site we received 80% of the sensor data expected at the base station, upon returning, post-deployment analysis revealed that 42% of these sensor data were potentially faulty. Due to the remote location of the deployment, we were unable to go back and validate the questionable segments of the data set, forcing us to discard potentially interesting information. In addition to being undesirable, this response is often avoidable as well. Even simple actions such as checking sensor connections and quickly validating sensors in the field could have increased our confidence in the quality of the data, minimizing doubts that data observations were simply caused by badly behaving hardware. To improve data quality, we have designed a system called Confidence, which continuously monitors data collected at a base-station to identify faulty data and notify the user in the field of actions they can take to validate the data or remediate the sensor fault. Augmenting a sensor network deployment with Confidence and Sympathy enables users in the identification and remediation of faults impacting the quality and quantity of data respectively.

Delay-tolerant mobile network protocol for rice field monitoring using wireless sensor networks

NASA Astrophysics Data System (ADS)

Guitton, Alexandre; Andres, Frédéric; Cardoso, Jarbas Lopes; Kawtrakul, Asanee; Barbin, Silvio E.

2015-10-01

The monitoring of rice fields can improve productivity by helping farmers throughout the rice cultivation cycle, on various issues: when to harvest, when to treat the crops against disease, when to increase the water level, how to share observations and decisions made in a collaborative way, etc. In this paper, we propose an architecture to monitor a rice field by a wireless sensor network. Our architecture is based on static sensor nodes forming a disconnected network, and mobile nodes communicating with the sensor nodes in a delay-tolerant manner. The data collected by the static sensor nodes are transmitted to mobile nodes, which in turn transmit them to a gateway, connected to a database, for further analysis. We focus on the related architecture, as well as on the energy-efficient protocols intended to perform the data collection.

NASA Sea Ice and Snow Validation Program for the DMSP SSM/I: NASA DC-8 flight report

NASA Technical Reports Server (NTRS)

Cavalieri, D. J.

1988-01-01

In June 1987 a new microwave sensor called the Special Sensor Microwave Imager (SSM/I) was launched as part of the Defense Meteorological Satellite Program (DMSP). In recognition of the importance of this sensor to the polar research community, NASA developed a program to acquire the data, to convert the data into sea ice parameters, and finally to validate and archive both the SSM/I radiances and the derived sea ice parameters. Central to NASA's sea ice validation program was a series of SSM/I aircraft underflights with the NASA DC-8 airborne Laboratory. The mission (the Arctic '88 Sea Ice Mission) was completed in March 1988. This report summarizes the mission and includes a summary of aircraft instrumentation, coordination with participating Navy aircraft, flight objectives, flight plans, data collected, SSM/I orbits for each day during the mission, and lists several piggyback experiments supported during this mission.

Cuffless Blood Pressure Estimation Based on Data-Oriented Continuous Health Monitoring System

PubMed Central

Kawanaka, Haruki; Oguri, Koji

2017-01-01

Measuring blood pressure continuously helps monitor health and also prevent lifestyle related diseases to extend the expectancy of healthy life. Blood pressure, which is nowadays used for monitoring patient, is one of the most useful indexes for prevention of lifestyle related diseases such as hypertension. However, continuously monitoring the blood pressure is unrealistic because of discomfort caused by the tightening of a cuff belt. We have earlier researched the data-oriented blood pressure estimation without using a cuff. Remarkably, our blood pressure estimation method only uses a photoplethysmograph sensor. Therefore, the application is flexible for sensor locations and measuring situations. In this paper, we describe the implementation of our estimation method, the launch of a cloud system which can collect and manage blood pressure data measured by a wristwatch-type photoplethysmograph sensor, and the construction of our applications to visualize life-log data including the time-series data of blood pressure. PMID:28523074

Results From the First 118 GHz Passive Microwave Observations Over Antarctica

NASA Astrophysics Data System (ADS)

McAllister, R.; Gallaher, D. W.; Gasiewski, A. J.; Periasamy, L.; Belter, R.; Hurowitz, M.; Hosack, W.; Sanders, B. T.

2017-12-01

Cooperation between the University of Colorado (Center for Environmental Technology, National Snow and Ice Data Center, and Colorado Space Grant Consortium) and the private corporation Orbital Micro Systems (OMS) has resulted in a highly miniturized passive microwave sensor. This sensor was successfully flown over Antarctica in onboard NASA's DC-8 in Operation Ice Bridge (OIB) in October / November of 2016. Data was collected from the "MiniRad" 8 channel miniaturized microwave sensor, which operated as both a sounder and an imager. The non-calibrated observation included both high and low altitude observations over clouds, sea, ice, ice sheets, and mountains as well as terrain around Tierra del Fuego. Sample results and their significance will be discussed. The instrument is in a form factor suitable for deployment in cubesats and will be launched into orbit next year. Commercial deployments by OMS in a constellation configuration will shortly follow.

Game Theory for Wireless Sensor Networks: A Survey

PubMed Central

Shi, Hai-Yan; Wang, Wan-Liang; Kwok, Ngai-Ming; Chen, Sheng-Yong

2012-01-01

Game theory (GT) is a mathematical method that describes the phenomenon of conflict and cooperation between intelligent rational decision-makers. In particular, the theory has been proven very useful in the design of wireless sensor networks (WSNs). This article surveys the recent developments and findings of GT, its applications in WSNs, and provides the community a general view of this vibrant research area. We first introduce the typical formulation of GT in the WSN application domain. The roles of GT are described that include routing protocol design, topology control, power control and energy saving, packet forwarding, data collection, spectrum allocation, bandwidth allocation, quality of service control, coverage optimization, WSN security, and other sensor management tasks. Then, three variations of game theory are described, namely, the cooperative, non-cooperative, and repeated schemes. Finally, existing problems and future trends are identified for researchers and engineers in the field. PMID:23012533

Biomedical sensing analyzer (BSA) for mobile-health (mHealth)-LTE.

PubMed

Adibi, Sasan

2014-01-01

The rapid expansion of mobile-based systems, the capabilities of smartphone devices, as well as the radio access and cellular network technologies are the wind beneath the wing of mobile health (mHealth). In this paper, the concept of biomedical sensing analyzer (BSA) is presented, which is a novel framework, devised for sensor-based mHealth applications. The BSA is capable of formulating the Quality of Service (QoS) measurements in an end-to-end sense, covering the entire communication path (wearable sensors, link-technology, smartphone, cell-towers, mobile-cloud, and the end-users). The characterization and formulation of BSA depend on a number of factors, including the deployment of application-specific biomedical sensors, generic link-technologies, collection, aggregation, and prioritization of mHealth data, cellular network based on the Long-Term Evolution (LTE) access technology, and extensive multidimensional delay analyses. The results are studied and analyzed in a LabView 8.5 programming environment.

Smart garments for safety improvement of emergency/disaster operators.

PubMed

Curone, Davide; Dudnik, Gabriela; Loriga, Giannicola; Luprano, Jean; Magenes, Giovanni; Paradiso, Rita; Tognetti, Alessandro; Bonfiglio, Annalisa

2007-01-01

The main purpose of the European project ProeTEX is to develop equipment to improve safety, coordination and efficiency of emergency disaster intervention personnel like fire-fighters or civil protection rescuers. The equipment consists of a new generation of "smart" garments, integrating wearable sensors which will allow monitoring physiological parameters, position and activity of the user, as like as environmental variables of the operating field in which rescuers are working: both commercial and newly developed textile and fibre based sensors will be included. The garments will also contain an electronic box to process data collected by the sensors and a communication system enabling the transmission of data to the other rescuers and to a monitoring station. Also a "smart" victim patch will be developed: a wearable garment which will allow monitoring physiological parameters of injured civilians involved in disasters, with the aim of optimizing their survival management.

Estimation of Energy Expenditure Using a Patch-Type Sensor Module with an Incremental Radial Basis Function Neural Network

PubMed Central

Li, Meina; Kwak, Keun-Chang; Kim, Youn Tae

2016-01-01

Conventionally, indirect calorimetry has been used to estimate oxygen consumption in an effort to accurately measure human body energy expenditure. However, calorimetry requires the subject to wear a mask that is neither convenient nor comfortable. The purpose of our study is to develop a patch-type sensor module with an embedded incremental radial basis function neural network (RBFNN) for estimating the energy expenditure. The sensor module contains one ECG electrode and a three-axis accelerometer, and can perform real-time heart rate (HR) and movement index (MI) monitoring. The embedded incremental network includes linear regression (LR) and RBFNN based on context-based fuzzy c-means (CFCM) clustering. This incremental network is constructed by building a collection of information granules through CFCM clustering that is guided by the distribution of error of the linear part of the LR model. PMID:27669249

Virtual Observatory and Distributed Data Mining

NASA Astrophysics Data System (ADS)

Borne, Kirk D.

2012-03-01

New modes of discovery are enabled by the growth of data and computational resources (i.e., cyberinfrastructure) in the sciences. This cyberinfrastructure includes structured databases, virtual observatories (distributed data, as described in Section 20.2.1 of this chapter), high-performance computing (petascale machines), distributed computing (e.g., the Grid, the Cloud, and peer-to-peer networks), intelligent search and discovery tools, and innovative visualization environments. Data streams from experiments, sensors, and simulations are increasingly complex and growing in volume. This is true in most sciences, including astronomy, climate simulations, Earth observing systems, remote sensing data collections, and sensor networks. At the same time, we see an emerging confluence of new technologies and approaches to science, most clearly visible in the growing synergism of the four modes of scientific discovery: sensors-modeling-computing-data (Eastman et al. 2005). This has been driven by numerous developments, including the information explosion, development of large-array sensors, acceleration in high-performance computing (HPC) power, advances in algorithms, and efficient modeling techniques. Among these, the most extreme is the growth in new data. Specifically, the acquisition of data in all scientific disciplines is rapidly accelerating and causing a data glut (Bell et al. 2007). It has been estimated that data volumes double every year—for example, the NCSA (National Center for Supercomputing Applications) reported that their users cumulatively generated one petabyte of data over the first 19 years of NCSA operation, but they then generated their next one petabyte in the next year alone, and the data production has been growing by almost 100% each year after that (Butler 2008). The NCSA example is just one of many demonstrations of the exponential (annual data-doubling) growth in scientific data collections. In general, this putative data-doubling is an inevitable result of several compounding factors: the proliferation of data-generating devices, sensors, projects, and enterprises; the 18-month doubling of the digital capacity of these microprocessor-based sensors and devices (commonly referred to as "Moore’s law"); the move to digital for nearly all forms of information; the increase in human-generated data (both unstructured information on the web and structured data from experiments, models, and simulation); and the ever-expanding capability of higher density media to hold greater volumes of data (i.e., data production expands to fill the available storage space). These factors are consequently producing an exponential data growth rate, which will soon (if not already) become an insurmountable technical challenge even with the great advances in computation and algorithms. This technical challenge is compounded by the ever-increasing geographic dispersion of important data sources—the data collections are not stored uniformly at a single location, or with a single data model, or in uniform formats and modalities (e.g., images, databases, structured and unstructured files, and XML data sets)—the data are in fact large, distributed, heterogeneous, and complex. The greatest scientific research challenge with these massive distributed data collections is consequently extracting all of the rich information and knowledge content contained therein, thus requiring new approaches to scientific research. This emerging data-intensive and data-oriented approach to scientific research is sometimes called discovery informatics or X-informatics (where X can be any science, such as bio, geo, astro, chem, eco, or anything; Agresti 2003; Gray 2003; Borne 2010). This data-oriented approach to science is now recognized by some (e.g., Mahootian and Eastman 2009; Hey et al. 2009) as the fourth paradigm of research, following (historically) experiment/observation, modeling/analysis, and computational science.

Real-Time Field Data Acquisition and Remote Sensor Reconfiguration Using Scientific Workflows

NASA Astrophysics Data System (ADS)

Silva, F.; Mehta, G.; Vahi, K.; Deelman, E.

2010-12-01

Despite many technological advances, field data acquisition still consists of several manual and laborious steps. Once sensors and data loggers are deployed in the field, scientists often have to periodically return to their study sites in order to collect their data. Even when field deployments have a way to communicate and transmit data back to the laboratory (e.g. by using a satellite or a cellular modem), data analysis still requires several repetitive steps. Because data often needs to be processed and inspected manually, there is usually a significant time delay between data collection and analysis. As a result, sensor failures that could be detected almost in real-time are not noted for weeks or months. Finally, sensor reconfiguration as a result of interesting events in the field is still done manually, making rapid response nearly impossible and causing important data to be missed. By working closely with scientists from different application domains, we identified several tasks that, if automated, could greatly improve the way field data is collected, processed, and distributed. Our goals are to enable real-time data collection and validation, automate sensor reconfiguration in response to interest events in the field, and allow scientists to easily automate their data processing. We began our design by employing the Sensor Processing and Acquisition Network (SPAN) architecture. SPAN uses an embedded processor in the field to coordinate sensor data acquisition from analog and digital sensors by interfacing with different types of devices and data loggers. SPAN is also able to interact with various types of communication devices in order to provide real-time communication to and from field sites. We use the Pegasus Workflow Management System (Pegasus WMS) to coordinate data collection and control sensors and deployments in the field. Because scientific workflows can be used to automate multi-step, repetitive tasks, scientists can create simple workflows to download sensor data, perform basic QA/QC, and identify events of interest as well as sensor and data logger failures almost in real-time. As a result of this automation, scientists can quickly be notified (e.g. via e-mail or SMS) so that important events are not missed. In addition, Pegasus WMS has the ability to abstract the execution environment of where programs run. By placing a Pegasus WMS agent inside an embedded processor in the field, we allow scientists to ship simple computational models to the field, enabling remote data processing at the field site. As an example, scientists can send an image processing algorithm to the field so that the embedded processor can analyze images, thus reducing the bandwidth necessary for communication. In addition, when real-time communication to the laboratory is not possible, scientists can create simple computational models that can be run on sensor nodes autonomously, monitoring sensor data and making adjustments without any human intervention. We believe our system lowers the bar for the adoption of reconfigurable sensor networks by field scientists. In this poster, we will show how this technology can be used to provide not only data acquisition, but also real-time data validation and sensor reconfiguration.

IBE-Lite: a lightweight identity-based cryptography for body sensor networks.

PubMed

Tan, Chiu C; Wang, Haodong; Zhong, Sheng; Li, Qun

2009-11-01

A body sensor network (BSN) is a network of sensors deployed on a person's body for health care monitoring. Since the sensors collect personal medical data, security and privacy are important components in a BSN. In this paper, we developed IBE-Lite, a lightweight identity-based encryption suitable for sensors in a BSN. We present protocols based on IBE-Lite that balance security and privacy with accessibility and perform evaluation using experiments conducted on commercially available sensors.

Characteristic vector analysis of inflection ratio spectra: New technique for analysis of ocean color data

NASA Technical Reports Server (NTRS)

Grew, G. W.

1985-01-01

Characteristic vector analysis applied to inflection ratio spectra is a new approach to analyzing spectral data. The technique applied to remote data collected with the multichannel ocean color sensor (MOCS), a passive sensor, simultaneously maps the distribution of two different phytopigments, chlorophyll alpha and phycoerythrin, the ocean. The data set presented is from a series of warm core ring missions conducted during 1982. The data compare favorably with a theoretical model and with data collected on the same mission by an active sensor, the airborne oceanographic lidar (AOL).

Achieving Passive Localization with Traffic Light Schedules in Urban Road Sensor Networks

PubMed Central

Niu, Qiang; Yang, Xu; Gao, Shouwan; Chen, Pengpeng; Chan, Shibing

2016-01-01

Localization is crucial for the monitoring applications of cities, such as road monitoring, environment surveillance, vehicle tracking, etc. In urban road sensor networks, sensors are often sparely deployed due to the hardware cost. Under this sparse deployment, sensors cannot communicate with each other via ranging hardware or one-hop connectivity, rendering the existing localization solutions ineffective. To address this issue, this paper proposes a novel Traffic Lights Schedule-based localization algorithm (TLS), which is built on the fact that vehicles move through the intersection with a known traffic light schedule. We can first obtain the law by binary vehicle detection time stamps and describe the law as a matrix, called a detection matrix. At the same time, we can also use the known traffic light information to construct the matrices, which can be formed as a collection called a known matrix collection. The detection matrix is then matched in the known matrix collection for identifying where sensors are located on urban roads. We evaluate our algorithm by extensive simulation. The results show that the localization accuracy of intersection sensors can reach more than 90%. In addition, we compare it with a state-of-the-art algorithm and prove that it has a wider operational region. PMID:27735871

DOE Office of Scientific and Technical Information (OSTI.GOV)

Joe, Paul; Scott, Bill; Doyle, Chris

Abstract—An innovative monitoring network was implemented to support the operational and science programs for the Vancouver 2010 Winter Olympics. It consisted of in situ weather stations on custom-designed platforms. The sensors included an HMP45C for temperature, humidity and pressure, a tipping bucket rain gauge, an acoustic snow depth sensor, a Pluvio 1 precipitation gauge and an anemometer placed at gauge height and at 10 m height. Modifications to commercial automated precipitation gauges were necessary for the heavy snowfall conditions. Advanced or emerging technologies were deployed to support scientific and nowcasting studies into precipitation intensity, typing, visibility and wind. The sensorsmore » included an FD12P visibility and precipitation sensor, a precipitation occurrence sensing system (POSS) present weather sensor, a Hotplate precipitation sensor and a Parsivel disdrometer. Data were collected at 1 min sampling intervals. A Doppler weather radar was deployed in a valley location and provided critical detailed low-level data. An X-band dual-polarized radar was deployed by the National Oceanic and Atmospheric Administration to monitor Vancouver and Cypress Mountain. Three remote sensing stations for vertical profiling were established. At the base of Whistler Mountain, a micro-rain radar, a 22-channel radiometer, a ceilometer, a Parsivel and a POSS were installed. At the base of Cypress Mountain, a micro-rain radar, a ceilometer, a low cost rain sensor (LCR by ATTEX) and a POSS were installed. At Squamish, a wind profiler and a POSS were installed. Weather sensors were mounted on the Whistler Village Gondola and on the Peak to Peak gondola. Sites were established along the Whistler Mountain slope and at other key locations. The combination of sites and instruments formed a comprehensive network to provide observations appropriate for nowcasting in winter complex terrain and investigate precipitation, visibility and wind processes. The contribution provides a detailed description of the network, their sensors, the innovations and some examples.« less

Artifact Noise Removal Techniques on Seismocardiogram Using Two Tri-Axial Accelerometers

PubMed Central

Luu, Loc; Dinh, Anh

2018-01-01

The aim of this study is on the investigation of motion noise removal techniques using two-accelerometer sensor system and various placements of the sensors on gentle movement and walking of the patients. A Wi-Fi based data acquisition system and a framework on Matlab are developed to collect and process data while the subjects are in motion. The tests include eight volunteers who have no record of heart disease. The walking and running data on the subjects are analyzed to find the minimal-noise bandwidth of the SCG signal. This bandwidth is used to design filters in the motion noise removal techniques and peak signal detection. There are two main techniques of combining signals from the two sensors to mitigate the motion artifact: analog processing and digital processing. The analog processing comprises analog circuits performing adding or subtracting functions and bandpass filter to remove artifact noises before entering the data acquisition system. The digital processing processes all the data using combinations of total acceleration and z-axis only acceleration. The two techniques are tested on three placements of accelerometer sensors including horizontal, vertical, and diagonal on gentle motion and walking. In general, the total acceleration and z-axis acceleration are the best techniques to deal with gentle motion on all sensor placements which improve average systolic signal-noise-ratio (SNR) around 2 times and average diastolic SNR around 3 times comparing to traditional methods using only one accelerometer. With walking motion, ADDER and z-axis acceleration are the best techniques on all placements of the sensors on the body which enhance about 7 times of average systolic SNR and about 11 times of average diastolic SNR comparing to only one accelerometer method. Among the sensor placements, the performance of horizontal placement of the sensors is outstanding comparing with other positions on all motions. PMID:29614821

Fast fingerprint database maintenance for indoor positioning based on UGV SLAM.

PubMed

Tang, Jian; Chen, Yuwei; Chen, Liang; Liu, Jingbin; Hyyppä, Juha; Kukko, Antero; Kaartinen, Harri; Hyyppä, Hannu; Chen, Ruizhi

2015-03-04

Indoor positioning technology has become more and more important in the last two decades. Utilizing Received Signal Strength Indicator (RSSI) fingerprints of Signals of OPportunity (SOP) is a promising alternative navigation solution. However, as the RSSIs vary during operation due to their physical nature and are easily affected by the environmental change, one challenge of the indoor fingerprinting method is maintaining the RSSI fingerprint database in a timely and effective manner. In this paper, a solution for rapidly updating the fingerprint database is presented, based on a self-developed Unmanned Ground Vehicles (UGV) platform NAVIS. Several SOP sensors were installed on NAVIS for collecting indoor fingerprint information, including a digital compass collecting magnetic field intensity, a light sensor collecting light intensity, and a smartphone which collects the access point number and RSSIs of the pre-installed WiFi network. The NAVIS platform generates a map of the indoor environment and collects the SOPs during processing of the mapping, and then the SOP fingerprint database is interpolated and updated in real time. Field tests were carried out to evaluate the effectiveness and efficiency of the proposed method. The results showed that the fingerprint databases can be quickly created and updated with a higher sampling frequency (5Hz) and denser reference points compared with traditional methods, and the indoor map can be generated without prior information. Moreover, environmental changes could also be detected quickly for fingerprint indoor positioning.

Evaluation of the Radar Stage Sensor manufactured by Forest Technology Systems—Results of laboratory and field testing

USGS Publications Warehouse

Kunkle, Gerald A.

2018-01-31

Two identical Radar Stage Sensors from Forest Technology Systems were evaluated to determine if they are suitable for U.S. Geological Survey (USGS) hydrologic data collection. The sensors were evaluated in laboratory conditions to evaluate the distance accuracy of the sensor over the manufacturer’s specified operating temperatures and distance to water ranges. Laboratory results were compared to the manufacturer’s accuracy specification of ±0.007 foot (ft) and the USGS Office of Surface Water (OSW) policy requirement that water-level sensors have a measurement uncertainty of no more than 0.01 ft or 0.20 percent of the indicated reading. Both of the sensors tested were within the OSW policy requirement in both laboratory tests and within the manufacturer’s specification in the distance to water test over tested distances from 3 to 15 ft. In the temperature chamber test, both sensors were within the manufacturer’s specification for more than 90 percent of the data points collected over a temperature range of –40 to +60 degrees Celsius at a fixed distance of 8 ft. One sensor was subjected to an SDI-12 communication test, which it passed. A field test was conducted on one sensor at a USGS field site near Landon, Mississippi, from February 5 to March 29, 2016. Water-level measurements made by the radar during the field test were in agreement with those made by the Sutron Accubar Constant Flow Bubble Gauge.Upon the manufacturer’s release of updated firmware version 1.09, additional SDI-12 and temperature testing was performed to evaluate added SDI-12 functions and verify that performance was unaffected by the update. At this time, an Axiom data logger is required to perform a firmware update on this sensor. The data confirmed the results of the original test. Based on the test results, the Radar Stage Sensor is a suitable choice for USGS hydrologic data collection.

We have "born digital" - now what about "born semantic"?

NASA Astrophysics Data System (ADS)

Leadbetter, Adam; Fredericks, Janet

2014-05-01

The phrase "born-digital" refers to those materials which originate in a digital form. In Earth and Space Sciences, this is now very much the norm for data: analogue to digital converters sit on instrument boards and produce a digital record of the observed environment. While much effort has been put in to creating and curating these digital data, there has been little work on using semantic mark up of data from the point of collection - what we term 'born semantic'. In this presentation we report on two efforts to expand this area: Qartod-to-OGC (Q2O) and SenseOCEAN. These projects have taken a common approach to 'born semantic': create or reuse appropriate controlled vocabularies, published to World Wide Web Commission (W3C) standards use standards from the Open Geospatial Consortium's Sensor Web Enablement (SWE) initiative to describe instrument setup, deployment and/or outputs using terms from those controlled vocabularies embed URLs from the controlled vocabularies within the SWE documents in a "Linked Data" conformant approach Q2O developed best practices examples of SensorML descriptions of Original Equipment Manufacturers' metadata (model characteristics, capabilities, manufacturer contact, etc ...) set-up and deployment SensorML files; and data centre process-lineage using registered vocabularies to describe terms (including input, output, processes, parameters, quality control flags) One Q2O use case, the Martha's Vineyard Coastal Observatory ADCP Waves instance, uses SensorML and registered vocabularies to fully describe the process of computing wave parameters from sensed properties, including quality control tests and associated results. The European Commission Framework Programme 7 project SenseOCEAN draws together world leading marine sensor developers to create a highly integrated multifunction and cost-effective in situ marine biogeochemical sensor system. This project will provide a quantum leap in the ability to measure crucial biogeochemical parameters. Innovations will be combined with state of the art sensor technology to produce a modular sensor system that can be deployed on many platforms. The sensor descriptions are being profiled in SensorML and the controlled vocabularies are being repurposed from those used within the European Commission SeaDataNet project and published on the community standard NERC Vocabulary Server.

Using phone sensors and an artificial neural network to detect gait changes during drinking episodes in the natural environment.

PubMed

Suffoletto, Brian; Gharani, Pedram; Chung, Tammy; Karimi, Hassan

2018-02-01

Phone sensors could be useful in assessing changes in gait that occur with alcohol consumption. This study determined (1) feasibility of collecting gait-related data during drinking occasions in the natural environment, and (2) how gait-related features measured by phone sensors relate to estimated blood alcohol concentration (eBAC). Ten young adult heavy drinkers were prompted to complete a 5-step gait task every hour from 8pm to 12am over four consecutive weekends. We collected 3-axis accelerometer, gyroscope, and magnetometer data from phone sensors, and computed 24 gait-related features using a sliding window technique. eBAC levels were calculated at each time point based on Ecological Momentary Assessment (EMA) of alcohol use. We used an artificial neural network model to analyze associations between sensor features and eBACs in training (70% of the data) and validation and test (30% of the data) datasets. We analyzed 128 data points where both eBAC and gait-related sensor data were captured, either when not drinking (n=60), while eBAC was ascending (n=55) or eBAC was descending (n=13). 21 data points were captured at times when the eBAC was greater than the legal limit (0.08mg/dl). Using a Bayesian regularized neural network, gait-related phone sensor features showed a high correlation with eBAC (Pearson's r>0.9), and >95% of estimated eBAC would fall between -0.012 and +0.012 of actual eBAC. It is feasible to collect gait-related data from smartphone sensors during drinking occasions in the natural environment. Sensor-based features can be used to infer gait changes associated with elevated blood alcohol content. Copyright © 2017 Elsevier B.V. All rights reserved.

The Localized Discovery and Recovery for Query Packet Losses in Wireless Sensor Networks with Distributed Detector Clusters

PubMed Central

Teng, Rui; Leibnitz, Kenji; Miura, Ryu

2013-01-01

An essential application of wireless sensor networks is to successfully respond to user queries. Query packet losses occur in the query dissemination due to wireless communication problems such as interference, multipath fading, packet collisions, etc. The losses of query messages at sensor nodes result in the failure of sensor nodes reporting the requested data. Hence, the reliable and successful dissemination of query messages to sensor nodes is a non-trivial problem. The target of this paper is to enable highly successful query delivery to sensor nodes by localized and energy-efficient discovery, and recovery of query losses. We adopt local and collective cooperation among sensor nodes to increase the success rate of distributed discoveries and recoveries. To enable the scalability in the operations of discoveries and recoveries, we employ a distributed name resolution mechanism at each sensor node to allow sensor nodes to self-detect the correlated queries and query losses, and then efficiently locally respond to the query losses. We prove that the collective discovery of query losses has a high impact on the success of query dissemination and reveal that scalability can be achieved by using the proposed approach. We further study the novel features of the cooperation and competition in the collective recovery at PHY and MAC layers, and show that the appropriate number of detectors can achieve optimal successful recovery rate. We evaluate the proposed approach with both mathematical analyses and computer simulations. The proposed approach enables a high rate of successful delivery of query messages and it results in short route lengths to recover from query losses. The proposed approach is scalable and operates in a fully distributed manner. PMID:23748172

Chemical and mineralogical data and processing methods management system prototype with application to study of the North Caucasus Blybsky Metamorphic Complexes metamorphism PT-condition

NASA Astrophysics Data System (ADS)

Ivanov, Stanislav; Kamzolkin, Vladimir; Konilov, Aleksandr; Aleshin, Igor

2014-05-01

There are many various methods of assessing the conditions of rocks formation based on determining the composition of the constituent minerals. Our objective was to create a universal tool for processing mineral's chemical analysis results and solving geothermobarometry problems by creating a database of existing sensors and providing a user-friendly standard interface. Similar computer assisted tools are based upon large collection of sensors (geothermometers and geobarometers) are known, for example, the project TPF (Konilov A.N., 1999) - text-based sensor collection tool written in PASCAL. The application contained more than 350 different sensors and has been used widely in petrochemical studies (see A.N. Konilov , A.A. Grafchikov, V.I. Fonarev 2010 for review). Our prototype uses the TPF project concept and is designed with modern application development techniques, which allows better flexibility. Main components of the designed system are 3 connected datasets: sensors collection (geothermometers, geobarometers, oxygen geobarometers, etc.), petrochemical data and modeling results. All data is maintained by special management and visualization tools and resides in sql database. System utilities allow user to import and export data in various file formats, edit records and plot graphs. Sensors database contains up to date collections of known methods. New sensors may be added by user. Measured database should be filled in by researcher. User friendly interface allows access to all available data and sensors, automates routine work, reduces the risk of common user mistakes and simplifies information exchange between research groups. We use prototype to evaluate peak pressure during the formation of garnet-amphibolite apoeclogites, gneisses and schists Blybsky metamorphic complex of the Front Range of the Northern Caucasus. In particular, our estimation of formation pressure range (18 ± 4 kbar) agrees on independent research results. The reported study was partially supported by RFBR, research project No. 14-05-00615.

Recent Advances in Bathymetric Surveying of Continental Shelf Regions Using Autonomous Vehicles

NASA Astrophysics Data System (ADS)

Holland, K. T.; Calantoni, J.; Slocum, D.

2016-02-01

Obtaining bathymetric observations within the continental shelf in areas closer to the shore is often time consuming and dangerous, especially when uncharted shoals and rocks present safety concerns to survey ships and launches. However, surveys in these regions are critically important to numerical simulation of oceanographic processes, as bathymetry serves as the bottom boundary condition in operational forecasting models. We will present recent progress in bathymetric surveying using both traditional vessels retrofitted for autonomous operations and relatively inexpensive, small team deployable, Autonomous Underwater Vehicles (AUV). Both systems include either high-resolution multibeam echo sounders or interferometric sidescan sonar sensors with integrated inertial navigation system capabilities consistent with present commercial-grade survey operations. The advantages and limitations of these two configurations employing both unmanned and autonomous strategies are compared using results from several recent survey operations. We will demonstrate how sensor data collected from unmanned platforms can augment or even replace traditional data collection technologies. Oceanographic observations (e.g., sound speed, temperature and currents) collected simultaneously with bathymetry using autonomous technologies provide additional opportunities for advanced data assimilation in numerical forecasts. Discussion focuses on our vision for unmanned and autonomous systems working in conjunction with manned or in-situ systems to optimally and simultaneously collect data in environmentally hostile or difficult to reach areas.

Airborne Remote Earth Sensing (ARES) Program: an operational airborne MWIR imaging spectrometer and applications

NASA Astrophysics Data System (ADS)

Bishop, Kevin D.; Diestel, Michael J.

1996-11-01

Since 1993, the Airborne Remote Earth Sensing (ARES) Program has collected a wide variety of mid-wave infrared hyperspectral data on an interesting assortment of atmospheric, geologic, urban and chemical emission/absorption features. Flown in NASA's high altitude WB-57F aircraft, the ARES sensor is a 75 channel cryo-cooled prism spectrometer covering the 2 - 6 micrometers spectral region, and is capable of up or down-looking measurements over a wide range of collection geometries. Sensor characteristics, pointing capabilities, and overall performance are discussed. Highlights from some of the recent data collections, such as the 1993 and 95 thermal mapping of the active lava flow areas from the Kilauea volcano; the 1993 collection of the direct solar specular reflection off high altitude (ice) cloud layers over West Texas; upper atmospheric H2O vapor sounding using the 6 micrometers solar absorption spectra; Sulfur Dioxide detection from a coal burning power plant in Page, AZ (SO2 in emission) and from the Pu'u O'o vent of the Kilauea volcano (SO2 in absorption); and MWIR imagery from various terrestrial and urban background scenes, including West Los Angeles, and the Capitol area of Washington, D.C. Supporting spectral analysis and radiometric modeling are presented.

hydropower biological evaluation tools

DOE Office of Scientific and Technical Information (OSTI.GOV)

This software is a set of analytical tools to evaluate the physical and biological performance of existing, refurbished, or newly installed conventional hydro-turbines nationwide where fish passage is a regulatory concern. The current version is based on information collected by the Sensor Fish. Future version will include other technologies. The tool set includes data acquisition, data processing, and biological response tools with applications to various turbine designs and other passage alternatives. The associated database is centralized, and can be accessed remotely. We have demonstrated its use for various applications including both turbines and spillways

A robotic approach to mapping post-eruptive volcanic fissure conduits

NASA Astrophysics Data System (ADS)

Parcheta, Carolyn E.; Pavlov, Catherine A.; Wiltsie, Nicholas; Carpenter, Kalind C.; Nash, Jeremy; Parness, Aaron; Mitchell, Karl L.

2016-06-01

VolcanoBot was developed to map volcanic vents and their underlying conduit systems, which are rarely preserved and generally inaccessible to human exploration. It uses a PrimeSense Carmine 1.09 sensor for mapping and carries an IR temperature sensor, analog distance sensor, and an inertial measurement unit (IMU) inside a protective shell. The first field test succeeded in collecting valuable scientific data but revealed several needed improvements, including more rugged cable connections and mechanical couplers, increased ground clearance, and higher-torque motors for uphill mobility. The second field test significantly improved on all of these aspects but it traded electrical ruggedness for reduced data collection speed. Data collected by the VolcanoBots, while intermittent, yield the first insights into the cm-scale geometry of volcanic fissures at depths of up to 25 m. VolcanoBot was deployed at the 1969 Mauna Ulu fissure system on Kīlauea volcano in Hawai'i. It collected first-of-its-kind data from inside the fissure system. We hypothesized that 1) fissure sinuosity should decrease with depth, 2) irregularity should be persistent with depth, 3) any blockages in the conduit should occur at the narrowest points, and 4) the fissure should narrow with depth until it is too narrow for VolcanoBot to pass or is plugged with solidified lava. Our field campaigns did not span enough lateral or vertical area to test sinuosity. The preliminary data indicate that 1) there were many irregularities along fissures at depth, 2) blockages occurred, but not at obviously narrow locations, and 3) the conduit width remained a consistent 0.4-0.5 m for most of the upper 10 m that we analyzed.

Understanding the role of contrasting urban contexts in healthy aging: an international cohort study using wearable sensor devices (the CURHA study protocol).

PubMed

Kestens, Yan; Chaix, Basile; Gerber, Philippe; Desprès, Michel; Gauvin, Lise; Klein, Olivier; Klein, Sylvain; Köppen, Bernhard; Lord, Sébastien; Naud, Alexandre; Payette, Hélène; Richard, Lucie; Rondier, Pierre; Shareck, Martine; Sueur, Cédric; Thierry, Benoit; Vallée, Julie; Wasfi, Rania

2016-05-05

Given the challenges of aging populations, calls have been issued for more sustainable urban re-development and implementation of local solutions to address global environmental and healthy aging issues. However, few studies have considered older adults' daily mobility to better understand how local built and social environments may contribute to healthy aging. Meanwhile, wearable sensors and interactive map-based applications offer novel means for gathering information on people's mobility, levels of physical activity, or social network structure. Combining such data with classical questionnaires on well-being, physical activity, perceived environments and qualitative assessment of experience of places opens new opportunities to assess the complex interplay between individuals and environments. In line with current gaps and novel analytical capabilities, this research proposes an international research agenda to collect and analyse detailed data on daily mobility, social networks and health outcomes among older adults using interactive web-based questionnaires and wearable sensors. Our study resorts to a battery of innovative data collection methods including use of a novel multisensor device for collection of location and physical activity, interactive map-based questionnaires on regular destinations and social networks, and qualitative assessment of experience of places. This rich data will allow advanced quantitative and qualitative analyses in the aim to disentangle the complex people-environment interactions linking urban local contexts to healthy aging, with a focus on active living, social networks and participation, and well-being. This project will generate evidence about what characteristics of urban environments relate to active mobility, social participation, and well-being, three important dimensions of healthy aging. It also sets the basis for an international research agenda on built environment and healthy aging based on a shared and comprehensive data collection protocol.

Feasibility Study of Inexpensive Thermal Sensors and Small Uas Deployment for Living Human Detection in Rescue Missions Application Scenarios

NASA Astrophysics Data System (ADS)

Levin, E.; Zarnowski, A.; McCarty, J. L.; Bialas, J.; Banaszek, A.; Banaszek, S.

2016-06-01

Significant efforts are invested by rescue agencies worldwide to save human lives during natural and man-made emergency situations including those that happen in wilderness locations. These emergency situations include but not limited to: accidents with alpinists, mountainous skiers, people hiking and lost in remote areas. Sometimes in a rescue operation hundreds of first responders are involved to save a single human life. There are two critical issues where geospatial imaging can be a very useful asset in rescue operations support: 1) human detection and 2) confirming a fact that detected a human being is alive. International group of researchers from the Unites States and Poland collaborated on a pilot research project devoted to identify a feasibility of use for the human detection and alive-human state confirmation small unmanned aerial vehicles (SUAVs) and inexpensive forward looking infrared (FLIR) sensors. Equipment price for both research teams was below 8,000 including 3DR quadrotor UAV and Lepton longwave infrared (LWIR) imager which costs around 250 (for the US team); DJI Inspire 1 UAS with commercial Tamarisc-320 thermal camera (for the Polish team). Specifically both collaborating groups performed independent experiments in the USA and Poland and shared imaging data of on the ground and airborne electro-optical and FLIR sensor imaging collected. In these experiments dead bodies were emulated by use of medical training dummies. Real humans were placed nearby as live human subjects. Electro-optical imagery was used for the research in optimal human detection algorithms. Furthermore, given the fact that a dead human body after several hours has a temperature of the surrounding environment our experiments were challenged by the SUAS data optimization, i.e., distance from SUAV to object so that the FLIR sensor is still capable to distinguish temperature differences between a dummy and a real human. Our experiments indicated feasibility of use SUAVs and small thermal sensors for the human detection scenarios described above. Differences in temperatures were collected by deployed imaging acquisition platform are interpretable on FLIR images visually. Moreover, we applied ENVI image processing functions for calibration and numerical estimations of such a temperature differences. There are more potential system functionalities such as voice messages from rescue teams and even distant medication delivery for the victims of described emergencies. This paper describes experiments, processing results, and future research in more details.

Large Scale Environmental Monitoring through Integration of Sensor and Mesh Networks.

PubMed

Jurdak, Raja; Nafaa, Abdelhamid; Barbirato, Alessio

2008-11-24

Monitoring outdoor environments through networks of wireless sensors has received interest for collecting physical and chemical samples at high spatial and temporal scales. A central challenge to environmental monitoring applications of sensor networks is the short communication range of the sensor nodes, which increases the complexity and cost of monitoring commodities that are located in geographically spread areas. To address this issue, we propose a new communication architecture that integrates sensor networks with medium range wireless mesh networks, and provides users with an advanced web portal for managing sensed information in an integrated manner. Our architecture adopts a holistic approach targeted at improving the user experience by optimizing the system performance for handling data that originates at the sensors, traverses the mesh network, and resides at the server for user consumption. This holistic approach enables users to set high level policies that can adapt the resolution of information collected at the sensors, set the preferred performance targets for their application, and run a wide range of queries and analysis on both real-time and historical data. All system components and processes will be described in this paper.

Data collection framework for energy efficient privacy preservation in wireless sensor networks having many-to-many structures.

PubMed

Bahşi, Hayretdin; Levi, Albert

2010-01-01

Wireless sensor networks (WSNs) generally have a many-to-one structure so that event information flows from sensors to a unique sink. In recent WSN applications, many-to-many structures evolved due to the need for conveying collected event information to multiple sinks. Privacy preserved data collection models in the literature do not solve the problems of WSN applications in which network has multiple un-trusted sinks with different level of privacy requirements. This study proposes a data collection framework bases on k-anonymity for preventing record disclosure of collected event information in WSNs. Proposed method takes the anonymity requirements of multiple sinks into consideration by providing different levels of privacy for each destination sink. Attributes, which may identify an event owner, are generalized or encrypted in order to meet the different anonymity requirements of sinks at the same anonymized output. If the same output is formed, it can be multicasted to all sinks. The other trivial solution is to produce different anonymized outputs for each sink and send them to related sinks. Multicasting is an energy efficient data sending alternative for some sensor nodes. Since minimization of energy consumption is an important design criteria for WSNs, multicasting the same event information to multiple sinks reduces the energy consumption of overall network.

Real-time stress monitoring of highway bridges with a secured wireless sensor network.

DOT National Transportation Integrated Search

2011-12-01

"This collaborative research aims to develop a real-time stress monitoring system for highway bridges with a secured wireless sensor network. The near term goal is to collect wireless sensor data under different traffic patterns from local highway br...

A triboelectric motion sensor in wearable body sensor network for human activity recognition.

PubMed

Hui Huang; Xian Li; Ye Sun

2016-08-01

The goal of this study is to design a novel triboelectric motion sensor in wearable body sensor network for human activity recognition. Physical activity recognition is widely used in well-being management, medical diagnosis and rehabilitation. Other than traditional accelerometers, we design a novel wearable sensor system based on triboelectrification. The triboelectric motion sensor can be easily attached to human body and collect motion signals caused by physical activities. The experiments are conducted to collect five common activity data: sitting and standing, walking, climbing upstairs, downstairs, and running. The k-Nearest Neighbor (kNN) clustering algorithm is adopted to recognize these activities and validate the feasibility of this new approach. The results show that our system can perform physical activity recognition with a successful rate over 80% for walking, sitting and standing. The triboelectric structure can also be used as an energy harvester for motion harvesting due to its high output voltage in random low-frequency motion.

Ubiquitous healthcare computing with SEnsor Grid Enhancement with Data Management System (SEGEDMA).

PubMed

Preve, Nikolaos

2011-12-01

Wireless Sensor Network (WSN) can be deployed to monitor the health of patients suffering from critical diseases. Also a wireless network consisting of biomedical sensors can be implanted into the patient's body and can monitor the patients' conditions. These sensor devices, apart from having an enormous capability of collecting data from their physical surroundings, are also resource constraint in nature with a limited processing and communication ability. Therefore we have to integrate them with the Grid technology in order to process and store the collected data by the sensor nodes. In this paper, we proposed the SEnsor Grid Enhancement Data Management system, called SEGEDMA ensuring the integration of different network technologies and the continuous data access to system users. The main contribution of this work is to achieve the interoperability of both technologies through a novel network architecture ensuring also the interoperability of Open Geospatial Consortium (OGC) and HL7 standards. According to the results, SEGEDMA can be applied successfully in a decentralized healthcare environment.

Landsat and Thermal Infrared Imaging

NASA Technical Reports Server (NTRS)

Arvidson, Terry; Barsi, Julia; Jhabvala, Murzy; Reuter, Dennis

2012-01-01

The purpose of this chapter is to describe the collection of thermal images by Landsat sensors already on orbit and to introduce the new thermal sensor to be launched in 2013. The chapter describes the thematic mapper (TM) and enhanced thematic mapper plus (ETM+) sensors, the calibration of their thermal bands, and the design and prelaunch calibration of the new thermal infrared sensor (TIRS).

Wireless Sensor Network Radio Power Management and Simulation Models

DTIC Science & Technology

2010-01-01

The Open Electrical & Electronic Engineering Journal, 2010, 4, 21-31 21 1874-1290/10 2010 Bentham Open Open Access Wireless Sensor Network Radio...Air Force Institute of Technology, Wright-Patterson AFB, OH, USA Abstract: Wireless sensor networks (WSNs) create a new frontier in collecting and...consumption. Keywords: Wireless sensor network , power management, energy-efficiency, medium access control (MAC), simulation pa- rameters. 1

Berkeley Sensor Database, an Implementation of CUAHSI's ODM for the Keck HydroWatch Wireless Sensor Network

NASA Astrophysics Data System (ADS)

Ogle, G.; Bode, C.; Fung, I.

2010-12-01

The Keck HydroWatch Project is a multidisciplinary project devoted to understanding how water interacts with atmosphere, vegetation, soil, and fractured bedrock. It is experimenting with novel techniques to monitor and trace water pathways through these mediums, including developing an intensive wireless sensor network, in the Angelo Coast Range and Sagehen Reserves in California. The sensor time-series data is being supplemented with periodic campaigns experimenting with sampling and tracing techniques, including water chemistry, stable isotope analysis, electrical resistivity tomography (ERT), and neutron probes. Mechanistic and statistical modeling is being performed with these datasets. One goal of the HydroWatch project is to prototype technologies for intensive sampling that can be upscaled to the watershed scale. The Berkeley Sensor Database was designed to manage the large volumes of heterogeneous data coming from this sensor network. This system is based on the Observations Data Model (ODM) developed by the Consortium of Universities for the Advancement of Hydrologic Science, Inc. (CUAHSI). Due to need for the use of open-source software, UC Berkeley ported the ODM to a LAMP system (Linux, Apache, MySQL, Perl). As of August 2010, the Berkeley Sensor Database contains 33 million measurements from 1200 devices, with several thousand new measurements being added each hour. Data for this research is being collected from a wide variety of equipment. Some of this equipment is experimental and subject to constant modification, others are industry standards. Well pressure transducers, sap flow sensors, experimental microclimate motes, standard weather stations, and multiple rock and soil moisture sensors are some examples. While the Hydrologic Information System (HIS) and the ODM are optimized for data interoperability, they are not focused on facility management and data quality control which occur at a complex research site. In this presentation, we describe our implementation of the ODM, the modifications we made to the ODM schema to include incident reports, concepts of 'stations', reuse and moving of equipment, and NASA data quality levels. The HydroWatch researchers' data use vary radically, so we implemented a number of different accessors to the data, from real-time graphing during storms to direct SQL queries for automated analysis to full data dumps for heavy statistical modeling.

Top/bottom multisensor remote sensing of Arctic sea ice

NASA Technical Reports Server (NTRS)

Comiso, J. C.; Wadhams, P.; Krabill, W. B.; Swift, R. N.; Crawford, J. P.

1991-01-01

Results are presented on the Aircraft/Submarine Sea Ice Project experiment carried out in May 1987 to investigate concurrently the top and the bottom features of the Arctic sea-ice cover. Data were collected nearly simultaneously by instruments aboard two aircraft and a submarine, which included passive and active (SAR) microwave sensors, upward looking and sidescan sonars, a lidar profilometer, and an IR sensor. The results described fall into two classes of correlations: (1) quantitative correlations between profiles, such as ice draft (sonar), ice elevation (laser), SAR backscatter along the track line, and passive microwave brightness temperatures; and (2) qualitative and semiquantitative correlations between corresponding areas of imagery (i.e., passive microwave, AR, and sidescan sonar).

Intelligent electrical outlet for collective load control

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lentine, Anthony L.; Ford, Justin R.; Spires, Shannon V.

Various technologies described herein pertain to an electrical outlet that autonomously manages loads in a microgrid. The electrical outlet can provide autonomous load control in response to variations in electrical power generation supply in the microgrid. The electrical outlet includes a receptacle, a sensor operably coupled to the receptacle, and an actuator configured to selectively actuate the receptacle. The sensor measures electrical parameters at the receptacle. Further, a processor autonomously controls the actuator based at least in part on the electrical parameters measured at the receptacle, electrical parameters from one or more disparate electrical outlets in the microgrid, and amore » supply of generated electric power in the microgrid at a given time.« less

BOREAS Level-3b Landsat TM Imagery: At-sensor Radiances in BSQ Format

NASA Technical Reports Server (NTRS)

Hall, Forrest G. (Editor); Nickeson, Jaime; Knapp, David; Newcomer, Jeffrey A.; Cihlar, Josef

2000-01-01

For BOREAS, the level-3b Landsat TM data, along with the other remotely sensed images, were collected in order to provide spatially extensive information over the primary study areas. This information includes radiant energy, detailed land cover, and biophysical parameter maps such as FPAR and LAI. Although very similar in content to the level-3a Landsat TM products, the level-3b images were created to provide users with a directly usable at-sensor radiance image. Geographically, the level-3b images cover the BOREAS NSA and SSA. Temporally, the images cover the period of 22-Jun-1984 to 09-Jul-1996. The images are available in binary, image format files.

Evaluation of Measurements Collected with Multi-Parameter Continuous Water-Quality Monitors in Selected Illinois Streams, 2001-03

USGS Publications Warehouse

Groschen, George E.; King, Robin B.

2005-01-01

Eight streams, representing a wide range of environmental and water-quality conditions across Illinois, were monitored from July 2001 to October 2003 for five water-quality parameters as part of a pilot study by the U.S. Geological Survey (USGS) in cooperation with the Illinois Environmental Protection Agency (IEPA). Continuous recording multi-parameter water-quality monitors were installed to collect data on water temperature, dissolved-oxygen concentrations, specific conductivity, pH, and turbidity. The monitors were near USGS streamflow-gaging stations where stage and streamflow are continuously recorded. During the study period, the data collected for these five parameters generally met the data-quality objectives established by the USGS and IEPA at all eight stations. A similar pilot study during this period for measurement of chlorophyll concentrations failed to achieve the data-quality objectives. Of all the sensors used, the temperature sensors provided the most accurate and reliable measurements (generally within ?5 percent of a calibrated thermometer reading). Signal adjustments and calibration of all other sensors are dependent upon an accurate and precise temperature measurement. The dissolved-oxygen sensors were the next most reliable during the study and were responsive to changing conditions and accurate at all eight stations. Specific conductivity was the third most accurate and reliable measurement collected from the multi-parameter monitors. Specific conductivity at the eight stations varied widely-from less than 40 microsiemens (?S) at Rayse Creek near Waltonville to greater than 3,500 ?S at Salt Creek at Western Springs. In individual streams, specific conductivity often changed quickly (greater than 25 percent in less than 3 hours) and the sensors generally provided good to excellent record of these variations at all stations. The widest range of specific-conductivity measurements was in Salt Creek at Western Springs in the Greater Chicago metropolitan area. Unlike temperature, dissolved oxygen, and specific conductivity that have been typically measured over a wide range of historical streamflow conditions in many streams, there are few historical turbidity data and the full range of turbidity values is not well known for many streams. Because proposed regional criteria for turbidity in regional streams are based on upper 25th percentiles of concentration in reference streams, accurate determination of the distribution of turbidity in monitored streams is important. Digital data from all five sensors were recorded within each of the eight sondes deployed in the streams and in automated data recorders in the nearby streamflow-gaging houses at each station. The data recorded on each sonde were retrieved to a field laptop computer at each station visit. The feasibility of transmitting these data in near-real time to a central processing point for dissemination on the World-Wide Web was tested successfully. Data collected at all eight stations indicate that a number of factors affect the dissolved-oxygen concentration in the streams and rivers monitored. These factors include: temperature, biological activity, nutrient runoff, and weather (storm runoff). During brief periods usually in late summer, dissolved-oxygen concentrations in half or more of the eight streams and rivers monitored were below the 5 milligrams per liter minimum established by the Illinois Pollution Control Board to protect aquatic life. Because the streams monitored represent a wide range in water-quality and environmental conditions, including diffuse (non-point) runoff and wastewater-effluent contributions, this result indicates that deleterious low dissolved-oxygen concentrations during late summer may be widespread in Illinois streams.

Wide-area littoral discreet observation: success at the tactical edge

NASA Astrophysics Data System (ADS)

Toth, Susan; Hughes, William; Ladas, Andrew

2012-06-01

In June 2011, the United States Army Research Laboratory (ARL) participated in Empire Challenge 2011 (EC-11). EC-11 was United States Joint Forces Command's (USJFCOM) annual live, joint and coalition intelligence, surveillance and reconnaissance (ISR) interoperability demonstration under the sponsorship of the Under Secretary of Defense for Intelligence (USD/I). EC-11 consisted of a series of ISR interoperability events, using a combination of modeling & simulation, laboratory and live-fly events. Wide-area Littoral Discreet Observation (WALDO) was ARL's maritime/littoral capability. WALDO met a USD(I) directive that EC-11 have a maritime component and WALDO was the primary player in the maritime scenario conducted at Camp Lejeune, North Carolina. The WALDO effort demonstrated the utility of a networked layered sensor array deployed in a maritime littoral environment, focusing on maritime surveillance targeting counter-drug, counter-piracy and suspect activity in a littoral or riverine environment. In addition to an embedded analytical capability, the sensor array and control infrastructure consisted of the Oriole acoustic sensor, iScout unattended ground sensor (UGS), OmniSense UGS, the Compact Radar and the Universal Distributed Management System (UDMS), which included the Proxy Skyraider, an optionally manned aircraft mounting both wide and narrow FOV EO/IR imaging sensors. The capability seeded a littoral area with riverine and unattended sensors in order to demonstrate the utility of a Wide Area Sensor (WAS) capability in a littoral environment focused on maritime surveillance activities. The sensors provided a cue for WAS placement/orbit. A narrow field of view sensor would be used to focus on more discreet activities within the WAS footprint. Additionally, the capability experimented with novel WAS orbits to determine if there are more optimal orbits for WAS collection in a littoral environment. The demonstration objectives for WALDO at EC-11 were: * Demonstrate a networked, layered, multi-modal sensor array deployed in a maritime littoral environment, focusing on maritime surveillance targeting counter-drug, counter-piracy and suspect activity * Assess the utility of a Wide Area Surveillance (WAS) sensor in a littoral environment focused on maritime surveillance activities * Demonstrate the effectiveness of using UGS sensors to cue WAS sensor tasking * Employ a narrow field of view full motion video (FMV) sensor package that is collocated with the WAS to conduct more discrete observation of potential items of interest when queued by near-real-time data from UGS or observers * Couple the ARL Oriole sensor with other modality UGS networks in a ground layer ISR capability, and incorporate data collected from aerial sensors with a GEOINT base layer to form a fused product * Swarm multiple aerial or naval platforms to prosecute single or multiple targets * Track fast moving surface vessels in littoral areas * Disseminate time sensitive, high value data to the users at the tactical edge In short we sought to answer the following question: how do you layer, control and display disparate sensors and sensor modalities in such a way as to facilitate appropriate sensor cross-cue, data integration, and analyst control to effectively monitor activity in a littoral (or novel) environment?

Satellite Observation Systems for Polar Climate Change Studies

NASA Technical Reports Server (NTRS)

Comiso, Josefino C.

2012-01-01

The key observational tools for detecting large scale changes of various parameters in the polar regions have been satellite sensors. The sensors include passive and active satellite systems in the visible, infrared and microwave frequencies. The monitoring started with Tiros and Nimbus research satellites series in the 1970s but during the period, not much data was stored digitally because of limitations and cost of the needed storage systems. Continuous global data came about starting with the launch of ocean color, passive microwave, and thermal infrared sensors on board Nimbus-7 and Synthetic Aperture Radar, Radar Altimeter and Scatterometer on board SeaSat satellite both launched in 1978. The Nimbus-7 lasted longer than expected and provided about 9 years of useful data while SeaSat quit working after 3 months but provided very useful data that became the baseline for follow-up systems with similar capabilities. Over the years, many new sensors were launched, some from Japan Aeronautics and Space Agency (JAXA), some from the European Space Agency (ESA) and more recently, from RuSSia, China, Korea, Canada and India. For polar studies, among the most useful sensors has been the passive microwave sensor which provides day/night and almost all weather observation of the surface. The sensor provide sea surface temperature, precipitation, wind, water vapor and sea ice concentration data that have been very useful in monitoring the climate of the region. More than 30 years of such data are now available, starting with the Scanning Multichannel Microwave Radiometer (SMMR) on board the Nimbus-7, the Special Scanning Microwave/Imager (SSM/I) on board a Defense Meteorological Satellite Program (DMSP) and the Advanced Microwave Scanning Radiometer on board the EOS/ Aqua satellite. The techniques that have been developed to derive geophysical parameters from data provided by these and other sensors and associated instrumental and algorithm errors and validation techniques will be discussed. An important issue is the organization and storage of hundreds of terabytes of data collected by even just a few of these satellite sensors. Advances in mass storage and computer technology have made it possible to overcome many of the collection and archival problems and the availability of comprehensive satellite data sets put together by NASA's Earth Observing System project will be discussed.

Temperature and Humidity Calibration of a Low-Cost Wireless Dust Sensor for Real-Time Monitoring.

PubMed

Hojaiji, Hannaneh; Kalantarian, Haik; Bui, Alex A T; King, Christine E; Sarrafzadeh, Majid

2017-03-01

This paper introduces the design, calibration, and validation of a low-cost portable sensor for the real-time measurement of dust particles within the environment. The proposed design consists of low hardware cost and calibration based on temperature and humidity sensing to achieve accurate processing of airborne dust density. Using commercial particulate matter sensors, a highly accurate air quality monitoring sensor was designed and calibrated using real world variations in humidity and temperature for indoor and outdoor applications. Furthermore, to provide a low-cost secure solution for real-time data transfer and monitoring, an onboard Bluetooth module with AES data encryption protocol was implemented. The wireless sensor was tested against a Dylos DC1100 Pro Air Quality Monitor, as well as an Alphasense OPC-N2 optical air quality monitoring sensor for accuracy. The sensor was also tested for reliability by comparing the sensor to an exact copy of itself under indoor and outdoor conditions. It was found that accurate measurements under real-world humid and temperature varying and dynamically changing conditions were achievable using the proposed sensor when compared to the commercially available sensors. In addition to accurate and reliable sensing, this sensor was designed to be wearable and perform real-time data collection and transmission, making it easy to collect and analyze data for air quality monitoring and real-time feedback in remote health monitoring applications. Thus, the proposed device achieves high quality measurements at lower-cost solutions than commercially available wireless sensors for air quality.

Development of wireless sensor network for landslide monitoring system

NASA Astrophysics Data System (ADS)

Suryadi; Puranto, Prabowo; Adinanta, Hendra; Tohari, Adrin; Priambodo, Purnomo S.

2017-05-01

A wireless sensor network has been developed to monitor soil movement of some observed areas periodically. The system consists of four nodes and one gateway which installed on a scope area of 0.2 Km2. Each of nodehastwo types of sensor,an inclinometer and an extensometer. An inclinometer sensor is used to measure the tilt of a structure while anextensometer sensor is used to measure the displacement of soil movement. Each of nodeisalso supported by awireless communication device, a solar power supply unit, and a microcontroller unit called sensor module. In this system, there is also gateway module as a main communication system consistinga wireless communication device, power supply unit, and rain gauge to measure the rainfall intensity of the observed area. Each sensor of inclinometer and extensometer isconnected to the sensor module in wiring system but sensor module iscommunicating with gateway in a wireless system. Those four nodes are alsoconnectedeach other in a wireless system collecting the data from inclinometer and extensometer sensors. Module Gateway istransmitting the instruction code to each sensor module one by one and collecting the data from them. Gateway module is an important part to communicate with not only sensor modules but also to the server. This wireless system wasdesigned toreducethe electric consumption powered by 80 WP solar panel and 55Ah battery. This system has been implemented in Pangalengan, Bandung, which has high intensity of rainfall and it can be seen on the website.

Gas sensor protection device and method

DOE Office of Scientific and Technical Information (OSTI.GOV)

Boyd, David; Magera, Craig

A gas sensor includes a sensor housing and a sensing element located within the sensor housing. The sensing element has a distal end and defines an axis. The gas sensor also includes a sensor protection device coupled to the sensor housing and at least partially surrounding the distal end of the sensing element. The sensor protection device includes a first member coupled to the housing, the first member having a generally rectangular cross-sectional shape in a plane perpendicular to the axis. The first member includes a gas inlet and a gas outlet. The sensor protection device also includes a secondmore » member coupled to the housing.« less

Tropospheric Airborne Meteorological Data Reporting (TAMDAR) Sensor Validation and Verification on National Oceanographic and Atmospheric Administration (NOAA) Lockheed WP-3D Aircraft

NASA Technical Reports Server (NTRS)

Tsoucalas, George; Daniels, Taumi S.; Zysko, Jan; Anderson, Mark V.; Mulally, Daniel J.

2010-01-01

As part of the National Aeronautics and Space Administration's Aviation Safety and Security Program, the Tropospheric Airborne Meteorological Data Reporting project (TAMDAR) developed a low-cost sensor for aircraft flying in the lower troposphere. This activity was a joint effort with support from Federal Aviation Administration, National Oceanic and Atmospheric Administration, and industry. This paper reports the TAMDAR sensor performance validation and verification, as flown on board NOAA Lockheed WP-3D aircraft. These flight tests were conducted to assess the performance of the TAMDAR sensor for measurements of temperature, relative humidity, and wind parameters. The ultimate goal was to develop a small low-cost sensor, collect useful meteorological data, downlink the data in near real time, and use the data to improve weather forecasts. The envisioned system will initially be used on regional and package carrier aircraft. The ultimate users of the data are National Centers for Environmental Prediction forecast modelers. Other users include air traffic controllers, flight service stations, and airline weather centers. NASA worked with an industry partner to develop the sensor. Prototype sensors were subjected to numerous tests in ground and flight facilities. As a result of these earlier tests, many design improvements were made to the sensor. The results of tests on a final version of the sensor are the subject of this report. The sensor is capable of measuring temperature, relative humidity, pressure, and icing. It can compute pressure altitude, indicated air speed, true air speed, ice presence, wind speed and direction, and eddy dissipation rate. Summary results from the flight test are presented along with corroborative data from aircraft instruments.

Ballistocardiogaphic studies with acceleration and electromechanical film sensors.

PubMed

Alametsä, J; Värri, A; Viik, J; Hyttinen, J; Palomäki, A

2009-11-01

The purpose of this research is to demonstrate and compare the utilization of electromechanical film (EMFi) and two acceleration sensors, ADXL202 and MXA2500U, for ballistocardiographic (BCG) and pulse transit time (PTT) studies. We have constructed a mobile physiological measurement station including amplifiers and a data collection system to record the previously mentioned signals and an electrocardiogram signal. Various versions of the measuring systems used in BCG studies in the past are also presented and evaluated. We have showed the ability of the EMFi sensor to define the elastic properties of the cardiovascular system and to ensure the functionality of the proposed instrumentation in different physiological loading conditions, before and after exercise and sauna bath. The EMFi sensor provided a BCG signal of good quality in the study of the human heart and function of the cardiovascular system with different measurement configurations. EMFi BCG measurements provided accurate and repeatable results for the different components of the heart cycle. In multiple-channel EMFi measurements, the carotid and limb pulse signals acquired were detailed and distinctive, allowing accurate PTT measurements. Changes in blood pressure were clearly observed and easily determined with EMFi sensor strips in pulse wave velocity (PWV) measurements. In conclusion, the configuration of the constructed device provided reliable measurements of the electrocardiogram, BCG, heart sound, and carotid and ankle pulse wave signals. Attached EMFi sensor strips on the neck and limbs yield completely new applications of the EMFi sensors aside from the conventional seat and supine recordings. Higher sensitivity, ease of utilization, and minimum discomfort of the EMFi sensor compared with acceleration sensors strengthen the status of the EMFi sensor for accurate and reliable BCG and PWV measurements, providing novel evaluation of the elastic properties of the cardiovascular system.

NASA 2007 Western States Fire Missions (WSFM)

NASA Technical Reports Server (NTRS)

Posada, Herman A.

2008-01-01

This presentation describes the objectives of the 2007 Western States Fire Mission (WSFM), which included demonstrating capabilities of the Ikhana unmanned aerial system (UAS) to overfly and collect sensor data on widespread fires throughout the Western United States, demonstrating long-endurance (20+ hours) mission capabilities, and delivering real-time imagery within 10 minutes of acquisition. Additionally, the operations concept, operational zones, and landing sites are highlighted. Provisions of the certificate of authorization are also addressed. Imagery obtained from the WSFM are included.

Acousto-ultrasonic system for the inspection of composite armored vehicles

NASA Astrophysics Data System (ADS)

Godinez, Valery F.; Carlos, Mark F.; Delamere, Michael; Hoch, William; Fotopoulos, Christos; Dai, Weiming; Raju, Basavaraju B.

2001-04-01

In this paper the design and implementation of a unique acousto-ultrasonics system for the inspection of composite armored vehicles is discussed. The system includes a multi-sensor probe with a position-tracking device mounted on a computer controlled scanning bridge. The system also includes an arbitrary waveform generator with a multiplexer and a multi-channel acoustic emission board capable of simultaneously collecting and processing up to four acoustic signals in real time. C-scans of an armored vehicle panel with defects are presented.

Internet of Things Platform for Smart Farming: Experiences and Lessons Learnt

PubMed Central

Jayaraman, Prem Prakash; Yavari, Ali; Georgakopoulos, Dimitrios; Morshed, Ahsan; Zaslavsky, Arkady

2016-01-01

Improving farm productivity is essential for increasing farm profitability and meeting the rapidly growing demand for food that is fuelled by rapid population growth across the world. Farm productivity can be increased by understanding and forecasting crop performance in a variety of environmental conditions. Crop recommendation is currently based on data collected in field-based agricultural studies that capture crop performance under a variety of conditions (e.g., soil quality and environmental conditions). However, crop performance data collection is currently slow, as such crop studies are often undertaken in remote and distributed locations, and such data are typically collected manually. Furthermore, the quality of manually collected crop performance data is very low, because it does not take into account earlier conditions that have not been observed by the human operators but is essential to filter out collected data that will lead to invalid conclusions (e.g., solar radiation readings in the afternoon after even a short rain or overcast in the morning are invalid, and should not be used in assessing crop performance). Emerging Internet of Things (IoT) technologies, such as IoT devices (e.g., wireless sensor networks, network-connected weather stations, cameras, and smart phones) can be used to collate vast amount of environmental and crop performance data, ranging from time series data from sensors, to spatial data from cameras, to human observations collected and recorded via mobile smart phone applications. Such data can then be analysed to filter out invalid data and compute personalised crop recommendations for any specific farm. In this paper, we present the design of SmartFarmNet, an IoT-based platform that can automate the collection of environmental, soil, fertilisation, and irrigation data; automatically correlate such data and filter-out invalid data from the perspective of assessing crop performance; and compute crop forecasts and personalised crop recommendations for any particular farm. SmartFarmNet can integrate virtually any IoT device, including commercially available sensors, cameras, weather stations, etc., and store their data in the cloud for performance analysis and recommendations. An evaluation of the SmartFarmNet platform and our experiences and lessons learnt in developing this system concludes the paper. SmartFarmNet is the first and currently largest system in the world (in terms of the number of sensors attached, crops assessed, and users it supports) that provides crop performance analysis and recommendations. PMID:27834862

Secure Intra-Body Wireless Communications (SIWiC) System Project

NASA Technical Reports Server (NTRS)

Ahmad, Aftab; Doggett, Terrence P.

2011-01-01

SIWiC System is a project to investigate, design and implement future wireless networks of implantable sensors in the body. This futuristic project is designed to make use of the emerging and yet-to-emerge technologies, including ultra-wide band (UWB) for wireless communications, smart implantable sensors, ultra low power networking protocols, security and privacy for bandwidth and power deficient devices and quantum computing. Progress in each of these fronts is hindered by the needs of breakthrough. But, as we will see in this paper, these major challenges are being met or will be met in near future. SIWiC system is a network of in-situ wireless devices that are implanted to coordinate sensed data inside the body, such as symptoms monitoring collected internally, or biometric data collected of an outside object from within the intra-body network. One node has the capability of communicating outside the body to send data or alarm to a relevant authority, e.g., a remote physician.

Advanced LWIR hyperspectral sensor for on-the-move proximal detection of liquid/solid contaminants on surfaces

NASA Astrophysics Data System (ADS)

Giblin, Jay P.; Dixon, John; Dupuis, Julia R.; Cosofret, Bogdan R.; Marinelli, William J.

2017-05-01

Sensor technologies capable of detecting low vapor pressure liquid surface contaminants, as well as solids, in a noncontact fashion while on-the-move continues to be an important need for the U.S. Army. In this paper, we discuss the development of a long-wave infrared (LWIR, 8-10.5 μm) spatial heterodyne spectrometer coupled with an LWIR illuminator and an automated detection algorithm for detection of surface contaminants from a moving vehicle. The system is designed to detect surface contaminants by repetitively collecting LWIR reflectance spectra of the ground. Detection and identification of surface contaminants is based on spectral correlation of the measured LWIR ground reflectance spectra with high fidelity library spectra and the system's cumulative binary detection response from the sampled ground. We present the concepts of the detection algorithm through a discussion of the system signal model. In addition, we present reflectance spectra of surfaces contaminated with a liquid CWA simulant, triethyl phosphate (TEP), and a solid simulant, acetaminophen acquired while the sensor was stationary and on-the-move. Surfaces included CARC painted steel, asphalt, concrete, and sand. The data collected was analyzed to determine the probability of detecting 800 μm diameter contaminant particles at a 0.5 g/m2 areal density with the SHSCAD traversing a surface.

Virtualization of Event Sources in Wireless Sensor Networks for the Internet of Things

PubMed Central

Martínez, Néstor Lucas; Martínez, José-Fernán; Díaz, Vicente Hernández

2014-01-01

Wireless Sensor Networks (WSNs) are generally used to collect information from the environment. The gathered data are delivered mainly to sinks or gateways that become the endpoints where applications can retrieve and process such data. However, applications would also expect from a WSN an event-driven operational model, so that they can be notified whenever occur some specific environmental changes instead of continuously analyzing the data provided periodically. In either operational model, WSNs represent a collection of interconnected objects, as outlined by the Internet of Things. Additionally, in order to fulfill the Internet of Things principles, Wireless Sensor Networks must have a virtual representation that allows indirect access to their resources, a model that should also include the virtualization of event sources in a WSN. Thus, in this paper a model for a virtual representation of event sources in a WSN is proposed. They are modeled as internet resources that are accessible by any internet application, following an Internet of Things approach. The model has been tested in a real implementation where a WSN has been deployed in an open neighborhood environment. Different event sources have been identified in the proposed scenario, and they have been represented following the proposed model. PMID:25470489

Water-level fluctuations, water temperatures, and tilts in sandbars -6.5R, 43.1L, and 172.3L, Grand Canyon, Arizona, 1990-93

USGS Publications Warehouse

Carpenter, Michael C.; Crosswhite, Jason A.; Carruth, R.L.

1995-01-01

Rill erosion, slumping, and fissuring develop on seepage faces of many sandbars along the Colorado River in the Grand Canyon at low river stage. Three sandbars were instrumented with sensors for continual monitoring of stage, pore pressure, ground-water temperature, and tilt to determine the relation between ground-water flow and sandbar deformation. Data were collected from October 1990 to July 1993 at sandbar -6.5R, which had 17 pore- pressure sensors, 1 stage sensor, 19 temperature sensors, and 8 tilt sensors. Data were collected from April 1991 to March 1993 at sandbar 172.3L, which had 15 pore-pressure sensors, 1 stage sensor, 29 temperature sensors, and 10 tilt sensors. Atten- uation of water-level fluctuation from the zone of fluctuating river stage to the back of the sandbars ranged from 70 percent at sandbar -6.5R to 40 percent for sandbars 43.1L and 172.3L. Shallow tilt occurred at sandbar 43.1L from July 7 to August 10, 1991. Tilt occurred at sandbar 172.3L on May 7-8, June 18-19, and September 1-2, 1991; July 3 and 31, 1992; January 12, 14, 20-21, and 31, 1993; and February 21 and 24, 1993.

Geospace Science from Ground-based Magnetometer Arrays: Advances in Sensors, Data Collection, and Data Integration

NASA Astrophysics Data System (ADS)

Mann, Ian; Chi, Peter

2016-07-01

Networks of ground-based magnetometers now provide the basis for the diagnosis of magnetic disturbances associated with solar wind-magnetosphere-ionosphere coupling on a truly global scale. Advances in sensor and digitisation technologies offer increases in sensitivity in fluxgate, induction coil, and new micro-sensor technologies - including the promise of hybrid sensors. Similarly, advances in remote connectivity provide the capacity for truly real-time monitoring of global dynamics at cadences sufficient for monitoring and in many cases resolving system level spatio-temporal ambiguities especially in combination with conjugate satellite measurements. A wide variety of the plasmaphysical processes active in driving geospace dynamics can be monitored based on the response of the electrical current system, including those associated with changes in global convection, magnetospheric substorms and nightside tail flows, as well as due to solar wind changes in both dynamic pressure and in response to rotations of the direction of the IMF. Significantly, any changes to the dynamical system must be communicated by the propagation of long-period Alfven and/or compressional waves. These wave populations hence provide diagnostics for not only the energy transport by the wave fields themselves, but also provide a mechanism for diagnosing the structure of the background plasma medium through which the waves propagate. Ultra-low frequency (ULF) waves are especially significant in offering a monitor for mass density profiles, often invisible to particle detectors because of their very low energy, through the application of a variety of magneto-seismology and cross-phase techniques. Renewed scientific interest in the plasma waves associated with near-Earth substorm dynamics, including magnetosphere-ionosphere coupling at substorm onset and their relation to magnetotail flows, as well the importance of global scale ultra-low frequency waves for the energisation, transport, acceleration, and loss of electrons in the radiation belts promise high profile science returns. Integrated, global scale data products also have potential importance and application for real-time monitoring of the space weather threats to electrical power grids from geomagnetically induced currents. Such data exploitation increasingly relies on the collaborations between multiple national magnetometer arrays to generate single data products with common file format and data properties. We review advances in geospace science which can be delivered by networks of ground-based magnetometers - in terms of advances in sensors, data collection, and data integration - including through collaborations within the Ultra-Large Terrestrial International Magnetometer Array (ULTIMA) consortium.

Smart home in a box: usability study for a large scale self-installation of smart home technologies.

PubMed

Hu, Yang; Tilke, Dominique; Adams, Taylor; Crandall, Aaron S; Cook, Diane J; Schmitter-Edgecombe, Maureen

2016-07-01

This study evaluates the ability of users to self-install a smart home in a box (SHiB) intended for use by a senior population. SHiB is a ubiquitous system, developed by the Washington State University Center for Advanced Studies in Adaptive Systems (CASAS). Participants involved in this study are from the greater Palouse region of Washington State, and there are 13 participants in the study with an average age of 69.23. The SHiB package, which included several different types of components to collect and transmit sensor data, was given to participants to self-install. After installation of the SHiB, the participants were visited by researchers for a check of the installation. The researchers evaluated how well the sensors were installed and asked the resident questions about the installation process to help improve the SHiB design. The results indicate strengths and weaknesses of the SHiB design. Indoor motion tracking sensors are installed with high success rate, low installation success rate was found for door sensors and setting up the Internet server.

Smart home in a box: usability study for a large scale self-installation of smart home technologies

PubMed Central

Hu, Yang; Tilke, Dominique; Adams, Taylor; Crandall, Aaron S.; Schmitter-Edgecombe, Maureen

2017-01-01

This study evaluates the ability of users to self-install a smart home in a box (SHiB) intended for use by a senior population. SHiB is a ubiquitous system, developed by the Washington State University Center for Advanced Studies in Adaptive Systems (CASAS). Participants involved in this study are from the greater Palouse region of Washington State, and there are 13 participants in the study with an average age of 69.23. The SHiB package, which included several different types of components to collect and transmit sensor data, was given to participants to self-install. After installation of the SHiB, the participants were visited by researchers for a check of the installation. The researchers evaluated how well the sensors were installed and asked the resident questions about the installation process to help improve the SHiB design. The results indicate strengths and weaknesses of the SHiB design. Indoor motion tracking sensors are installed with high success rate, low installation success rate was found for door sensors and setting up the Internet server. PMID:28936390

Autonomous Triggering of in situ Sensors on Kilauea Volcano, HI, from Eruption Detection by the EO-1 Spacecraft: Design and Operational Scenario.

NASA Astrophysics Data System (ADS)

Boudreau, K.; Cecava, J. R.; Behar, A.; Davies, A. G.; Tran, D. Q.; Abtahi, A. A.; Pieri, D. C.; Jpl Volcano Sensor Web Team, A

2007-12-01

Response time in acquiring sensor data in volcanic emergencies can be greatly improved through use of autonomous systems. For instance, ground-based observations and data processing applications of the JPL Volcano Sensor Web have promptly triggered spacecraft observations [e.g., 1]. The reverse command and information flow path can also be useful, using autonomous analysis of spacecraft data to trigger in situ sensors. In this demonstration project, SO2 sensors have been incorporated into expendable "Volcano Monitor" capsules to be placed downwind of the Pu'U 'O'o vent of Kilauea volcano, Hawai'i. In nominal (low) power conservation mode, data from these sensors are collected and transmitted every hour to the Volcano Sensor Web through the Iridium Satellite Network. If SO2 readings exceed a predetermined threshold, the modem within the Volcano Monitor sends an alert to the Sensor Web, triggering a request for prompt Earth Observing-1 ( EO-1) spacecraft data acquisition. During pre-defined "critical events" as perceived by multiple sensors (which could include both in situ and spaceborne devices), however, the Sensor Web can order the SO2 sensors within the Volcano Monitor to increase their sampling frequency to once per minute (high power "burst mode"). Autonomous control of the sensors' sampling frequency enables the Sensor Web to monitor and respond to rapidly evolving conditions before and during an eruption, and allows near real-time compilation and dissemination of these data to the scientific community. Reference: [1] Davies et al., (2006) Eos, 87, (1), 1&5. This work was performed at the Jet Propulsion Laboratory-California Institute of Technology, under contract to NASA. Support was provided by the NASA AIST program, the Idaho Space Grant Consortium, and the New Mexico Space Grant Program. We thank the personnel of the USGS Hawaiian Volcano Observatory for their invaluable assistance.

Optical techniques for the determination of nitrate in environmental waters: Guidelines for instrument selection, operation, deployment, maintenance, quality assurance, and data reporting

USGS Publications Warehouse

Pellerin, Brian A.; Bergamaschi, Brian A.; Downing, Bryan D.; Saraceno, John Franco; Garrett, Jessica D.; Olsen, Lisa D.

2013-01-01

The recent commercial availability of in situ optical sensors, together with new techniques for data collection and analysis, provides the opportunity to monitor a wide range of water-quality constituents on time scales in which environmental conditions actually change. Of particular interest is the application of ultraviolet (UV) photometers for in situ determination of nitrate concentrations in rivers and streams. The variety of UV nitrate sensors currently available differ in several important ways related to instrument design that affect the accuracy of their nitrate concentration measurements in different types of natural waters. This report provides information about selection and use of UV nitrate sensors by the U.S. Geological Survey to facilitate the collection of high-quality data across studies, sites, and instrument types. For those in need of technical background and information about sensor selection, this report addresses the operating principles, key features and sensor design, sensor characterization techniques and typical interferences, and approaches for sensor deployment. For those needing information about maintaining sensor performance in the field, key sections in this report address maintenance and calibration protocols, quality-assurance techniques, and data formats and reporting. Although the focus of this report is UV nitrate sensors, many of the principles can be applied to other in situ optical sensors for water-quality studies.

Global dust sources detection using MODIS Deep Blue Collection 6 aerosol products

NASA Astrophysics Data System (ADS)

Pérez García-Pando, C.; Ginoux, P. A.

2015-12-01

Our understanding of the global dust cycle is limited by a dearth of information about dust sources, especially small-scale features which could account for a large fraction of global emissions. Remote sensing sensors are the most useful tool to locate dust sources. These sensors include microwaves, visible channels, and lidar. On the global scale, major dust source regions have been identified using polar orbiting satellite instruments. The MODIS Deep Blue algorithm has been particularly useful to detect small-scale sources such as floodplains, alluvial fans, rivers, and wadis , as well as to identify anthropogenic sources from agriculture. The recent release of Collection 6 MODIS aerosol products allows to extend dust source detection to the entire land surfaces, which is quite useful to identify mid to high latitude dust sources and detect not only dust from agriculture but fugitive dust from transport and industrial activities. This presentation will overview the advantages and drawbacks of using MODIS Deep Blue for dust detection, compare to other instruments (polar orbiting and geostationary). The results of Collection 6 with a new dust screening will be compared against AERONET. Applications to long range transport of anthropogenic dust will be presented.

Infrared imagery acquisition process supporting simulation and real image training

NASA Astrophysics Data System (ADS)

O'Connor, John

2012-05-01

The increasing use of infrared sensors requires development of advanced infrared training and simulation tools to meet current Warfighter needs. In order to prepare the force, a challenge exists for training and simulation images to be both realistic and consistent with each other to be effective and avoid negative training. The US Army Night Vision and Electronic Sensors Directorate has corrected this deficiency by developing and implementing infrared image collection methods that meet the needs of both real image trainers and real-time simulations. The author presents innovative methods for collection of high-fidelity digital infrared images and the associated equipment and environmental standards. The collected images are the foundation for US Army, and USMC Recognition of Combat Vehicles (ROC-V) real image combat ID training and also support simulations including the Night Vision Image Generator and Synthetic Environment Core. The characteristics, consistency, and quality of these images have contributed to the success of these and other programs. To date, this method has been employed to generate signature sets for over 350 vehicles. The needs of future physics-based simulations will also be met by this data. NVESD's ROC-V image database will support the development of training and simulation capabilities as Warfighter needs evolve.

An intelligent tool for activity data collection.

PubMed

Sarkar, A M Jehad

2011-01-01

Activity recognition systems using simple and ubiquitous sensors require a large variety of real-world sensor data for not only evaluating their performance but also training the systems for better functioning. However, a tremendous amount of effort is required to setup an environment for collecting such data. For example, expertise and resources are needed to design and install the sensors, controllers, network components, and middleware just to perform basic data collections. It is therefore desirable to have a data collection method that is inexpensive, flexible, user-friendly, and capable of providing large and diverse activity datasets. In this paper, we propose an intelligent activity data collection tool which has the ability to provide such datasets inexpensively without physically deploying the testbeds. It can be used as an inexpensive and alternative technique to collect human activity data. The tool provides a set of web interfaces to create a web-based activity data collection environment. It also provides a web-based experience sampling tool to take the user's activity input. The tool generates an activity log using its activity knowledge and the user-given inputs. The activity knowledge is mined from the web. We have performed two experiments to validate the tool's performance in producing reliable datasets.

Prototyping sensor network system for automatic vital signs collection. Evaluation of a location based automated assignment of measured vital signs to patients.

PubMed

Kuroda, T; Noma, H; Naito, C; Tada, M; Yamanaka, H; Takemura, T; Nin, K; Yoshihara, H

2013-01-01

Development of a clinical sensor network system that automatically collects vital sign and its supplemental data, and evaluation the effect of automatic vital sensor value assignment to patients based on locations of sensors. The sensor network estimates the data-source, a target patient, from the position of a vital sign sensor obtained from a newly developed proximity sensing system. The proximity sensing system estimates the positions of the devices using a Bluetooth inquiry process. Using Bluetooth access points and the positioning system newly developed in this project, the sensor network collects vital sign and its 4W (who, where, what, and when) supplemental data from any Bluetooth ready vital sign sensors such as Continua-ready devices. The prototype was evaluated in a pseudo clinical setting at Kyoto University Hospital using a cyclic paired comparison and statistical analysis. The result of the cyclic paired analysis shows the subjects evaluated the proposed system is more effective and safer than POCS as well as paper-based operation. It halves the times for vital signs input and eliminates input errors. On the other hand, the prototype failed in its position estimation for 12.6% of all attempts, and the nurses overlooked half of the errors. A detailed investigation clears that an advanced interface to show the system's "confidence", i.e. the probability of estimation error, must be effective to reduce the oversights. This paper proposed a clinical sensor network system that relieves nurses from vital signs input tasks. The result clearly shows that the proposed system increases the efficiency and safety of the nursing process both subjectively and objectively. It is a step toward new generation of point of nursing care systems where sensors take over the tasks of data input from the nurses.

Integrating a High Resolution Optically Pumped Magnetometer with a Multi-Rotor UAV towards 3-D Magnetic Gradiometry

NASA Astrophysics Data System (ADS)

Braun, A.; Walter, C. A.; Parvar, K.

2016-12-01

The current platforms for collecting magnetic data include dense coverage, but low resolution traditional airborne surveys, and high resolution, but low coverage terrestrial surveys. Both platforms leave a critical observation gap between the ground surface and approximately 100m above ground elevation, which can be navigated efficiently by new technologies, such as Unmanned Aerial Vehicles (UAVs). Specifically, multi rotor UAV platforms provide the ability to sense the magnetic field in a full 3-D tensor, which increases the quality of data collected over other current platform types. Payload requirements and target requirements must be balanced to fully exploit the 3-D magnetic tensor. This study outlines the integration of a GEM Systems Cesium Vapour UAV Magnetometer, a Lightware SF-11 Laser Altimeter and a uBlox EVK-7P GPS module with a DJI s900 Multi Rotor UAV. The Cesium Magnetometer is suspended beneath the UAV platform by a cable of varying length. A set of surveys was carried out to optimize the sensor orientation, sensor cable length beneath the UAV and data collection methods of the GEM Systems Cesium Vapour UAV Magnetometer when mounted on the DJI s900. The target for these surveys is a 12 inch steam pipeline located approximately 2 feet below the ground surface. A systematic variation of cable length, sensor orientation and inclination was conducted. The data collected from the UAV magnetometer was compared to a terrestrial survey conducted with the GEM GST-19 Proton Procession Magnetometer at the same elevation, which also served a reference station. This allowed for a cross examination between the UAV system and a proven industry standard for magnetic field data collection. The surveys resulted in optimizing the above parameters based on minimizing instrument error and ensuring reliable data acquisition. The results demonstrate that optimizing the UAV magnetometer survey can yield to industry standard measurements.

In-network Coding for Resilient Sensor Data Storage and Efficient Data Mule Collection

NASA Astrophysics Data System (ADS)

Albano, Michele; Gao, Jie

In a sensor network of n nodes in which k of them have sensed interesting data, we perform in-network erasure coding such that each node stores a linear combination of all the network data with random coefficients. This scheme greatly improves data resilience to node failures: as long as there are k nodes that survive an attack, all the data produced in the sensor network can be recovered with high probability. The in-network coding storage scheme also improves data collection rate by mobile mules and allows for easy scheduling of data mules.

Research on a Denial of Service (DoS) Detection System Based on Global Interdependent Behaviors in a Sensor Network Environment

PubMed Central

Song, Jae-gu; Jung, Sungmo; Kim, Jong Hyun; Seo, Dong Il; Kim, Seoksoo

2010-01-01

This research suggests a Denial of Service (DoS) detection method based on the collection of interdependent behavior data in a sensor network environment. In order to collect the interdependent behavior data, we use a base station to analyze traffic and behaviors among nodes and introduce methods of detecting changes in the environment with precursor symptoms. The study presents a DoS Detection System based on Global Interdependent Behaviors and shows the result of detecting a sensor carrying out DoS attacks through the test-bed. PMID:22163475

Global Lightning Climatology from the Tropical Rainfall Measuring Mission (TRMM), Lightning Imaging Sensor (LIS) and the Optical Transient Detector (OTD)

NASA Technical Reports Server (NTRS)

Cecil, Daniel J.; Buechler, Dennis E.; Blakeslee, Richard J.

2015-01-01

The Tropical Rainfall Measuring Mission (TRMM) Lightning Imaging Sensor (LIS) has been collecting observations of total lightning in the global tropics and subtropics (roughly 38 deg S - 38 deg N) since December 1997. A similar instrument, the Optical Transient Detector, operated from 1995-2000 on another low earth orbit satellite that also saw high latitudes. Lightning data from these instruments have been used to create gridded climatologies and time series of lightning flash rate. These include a 0.5 deg resolution global annual climatology, and lower resolution products describing the annual cycle and the diurnal cycle. These products are updated annually. Results from the update through 2013 will be shown at the conference. The gridded products are publicly available for download. Descriptions of how each product can be used will be discussed, including strengths, weaknesses, and caveats about the smoothing and sampling used in various products.

Non-Intrusive Sensor for In-Situ Measurement of Recession Rate of Ablative and Eroding Materials

NASA Technical Reports Server (NTRS)

Papadopoulos, George (Inventor); Tiliakos, Nicholas (Inventor); Thomson, Clint (Inventor); Benel, Gabriel (Inventor)

2014-01-01

A non-intrusive sensor for in-situ measurement of recession rate of heat shield ablatives. An ultrasonic wave source is carried in the housing. A microphone is also carried in the housing, for collecting the reflected ultrasonic waves from an interface surface of the ablative material. A time phasing control circuit is also included for time-phasing the ultrasonic wave source so that the waves reflected from the interface surface of the ablative material focus on the microphone, to maximize the acoustic pressure detected by the microphone and to mitigate acoustic velocity variation effects through the material through a de-coupling process that involves a software algorithm. A software circuit for computing the location off of which the ultrasonic waves scattered to focus back at the microphone is also included, so that the recession rate of the heat shield ablative may be monitored in real-time through the scan-focus approach.

Method and apparatus for shape and end position determination using an optical fiber

NASA Technical Reports Server (NTRS)

Moore, Jason P. (Inventor)

2010-01-01

A method of determining the shape of an unbound optical fiber includes collecting strain data along a length of the fiber, calculating curvature and bending direction data of the fiber using the strain data, curve-fitting the curvature and bending direction data to derive curvature and bending direction functions, calculating a torsion function using the bending direction function, and determining the 3D shape from the curvature, bending direction, and torsion functions. An apparatus for determining the 3D shape of the fiber includes a fiber optic cable unbound with respect to a protective sleeve, strain sensors positioned along the cable, and a controller in communication with the sensors. The controller has an algorithm for determining a 3D shape and end position of the fiber by calculating a set of curvature and bending direction data, deriving curvature, bending, and torsion functions, and solving Frenet-Serret equations using these functions.

The Nimbus 4 data catalog. Volume 8: Data orbits 5206-10,120, 1 May 1971 - 30 April 1972

NASA Technical Reports Server (NTRS)

1972-01-01

Data from various instruments onboard the Nimbus 4 are presented, including the image dissector camera system, the temperature-humidity infrared radiometer, infrared interferometer spectrometer, and monitor of ultraviolet solar energy experiments. This data was collected from 1 May 1971 to 30 Apr. 1972. Orbital elements and daily sensor data are presented in tabular form.

Power throttling of collections of computing elements

DOEpatents

Bellofatto, Ralph E [Ridgefield, CT; Coteus, Paul W [Yorktown Heights, NY; Crumley, Paul G [Yorktown Heights, NY; Gara, Alan G [Mount Kidsco, NY; Giampapa, Mark E [Irvington, NY; Gooding,; Thomas, M [Rochester, MN; Haring, Rudolf A [Cortlandt Manor, NY; Megerian, Mark G [Rochester, MN; Ohmacht, Martin [Yorktown Heights, NY; Reed, Don D [Mantorville, MN; Swetz, Richard A [Mahopac, NY; Takken, Todd [Brewster, NY

2011-08-16

An apparatus and method for controlling power usage in a computer includes a plurality of computers communicating with a local control device, and a power source supplying power to the local control device and the computer. A plurality of sensors communicate with the computer for ascertaining power usage of the computer, and a system control device communicates with the computer for controlling power usage of the computer.

DataPlus™ - a revolutionary applications generator for DOS hand-held computers

Treesearch

David Dean; Linda Dean

2000-01-01

DataPlus allows the user to easily design data collection templates for DOS-based hand-held computers that mimic clipboard data sheets. The user designs and tests the application on the desktop PC and then transfers it to a DOS field computer. Other features include: error checking, missing data checks, and sensor input from RS-232 devices such as bar code wands,...

The Pilatus unmanned aircraft system for lower atmospheric research

DOE PAGES

de Boer, Gijs; Palo, Scott; Argrow, Brian; ...

2016-04-28

This study presents details of the University of Colorado (CU) “Pilatus” unmanned research aircraft, assembled to provide measurements of aerosols, radiation and thermodynamics in the lower troposphere. This aircraft has a wingspan of 3.2 m and a maximum take-off weight of 25 kg, and it is powered by an electric motor to reduce engine exhaust and concerns about carburetor icing. It carries instrumentation to make measurements of broadband up- and downwelling shortwave and longwave radiation, aerosol particle size distribution, atmospheric temperature, relative humidity and pressure and to collect video of flights for subsequent analysis of atmospheric conditions during flight. Inmore » order to make the shortwave radiation measurements, care was taken to carefully position a high-quality compact inertial measurement unit (IMU) and characterize the attitude of the aircraft and its orientation to the upward-looking radiation sensor. Using measurements from both of these sensors, a correction is applied to the raw radiometer measurements to correct for aircraft attitude and sensor tilt relative to the sun. The data acquisition system was designed from scratch based on a set of key driving requirements to accommodate the variety of sensors deployed. Initial test flights completed in Colorado provide promising results with measurements from the radiation sensors agreeing with those from a nearby surface site. Additionally, estimates of surface albedo from onboard sensors were consistent with local surface conditions, including melting snow and bright runway surface. Aerosol size distributions collected are internally consistent and have previously been shown to agree well with larger, surface-based instrumentation. Finally the atmospheric state measurements evolve as expected, with the near-surface atmosphere warming over time as the day goes on, and the atmospheric relative humidity decreasing with increased temperature. No directional bias on measured temperature, as might be expected due to uneven heating of the sensor housing over the course of a racetrack pattern, was detected. The results from these flights indicate that the CU Pilatus platform is capable of performing research-grade lower tropospheric measurement missions.« less

The Pilatus unmanned aircraft system for lower atmospheric research

DOE Office of Scientific and Technical Information (OSTI.GOV)

de Boer, Gijs; Palo, Scott; Argrow, Brian

This study presents details of the University of Colorado (CU) “Pilatus” unmanned research aircraft, assembled to provide measurements of aerosols, radiation and thermodynamics in the lower troposphere. This aircraft has a wingspan of 3.2 m and a maximum take-off weight of 25 kg, and it is powered by an electric motor to reduce engine exhaust and concerns about carburetor icing. It carries instrumentation to make measurements of broadband up- and downwelling shortwave and longwave radiation, aerosol particle size distribution, atmospheric temperature, relative humidity and pressure and to collect video of flights for subsequent analysis of atmospheric conditions during flight. Inmore » order to make the shortwave radiation measurements, care was taken to carefully position a high-quality compact inertial measurement unit (IMU) and characterize the attitude of the aircraft and its orientation to the upward-looking radiation sensor. Using measurements from both of these sensors, a correction is applied to the raw radiometer measurements to correct for aircraft attitude and sensor tilt relative to the sun. The data acquisition system was designed from scratch based on a set of key driving requirements to accommodate the variety of sensors deployed. Initial test flights completed in Colorado provide promising results with measurements from the radiation sensors agreeing with those from a nearby surface site. Additionally, estimates of surface albedo from onboard sensors were consistent with local surface conditions, including melting snow and bright runway surface. Aerosol size distributions collected are internally consistent and have previously been shown to agree well with larger, surface-based instrumentation. Finally the atmospheric state measurements evolve as expected, with the near-surface atmosphere warming over time as the day goes on, and the atmospheric relative humidity decreasing with increased temperature. No directional bias on measured temperature, as might be expected due to uneven heating of the sensor housing over the course of a racetrack pattern, was detected. The results from these flights indicate that the CU Pilatus platform is capable of performing research-grade lower tropospheric measurement missions.« less

Synthetic Training Data Generation for Activity Monitoring and Behavior Analysis

NASA Astrophysics Data System (ADS)

Monekosso, Dorothy; Remagnino, Paolo

This paper describes a data generator that produces synthetic data to simulate observations from an array of environment monitoring sensors. The overall goal of our work is to monitor the well-being of one occupant in a home. Sensors are embedded in a smart home to unobtrusively record environmental parameters. Based on the sensor observations, behavior analysis and modeling are performed. However behavior analysis and modeling require large data sets to be collected over long periods of time to achieve the level of accuracy expected. A data generator - was developed based on initial data i.e. data collected over periods lasting weeks to facilitate concurrent data collection and development of algorithms. The data generator is based on statistical inference techniques. Variation is introduced into the data using perturbation models.

Mars Climate Orbiter

NASA Technical Reports Server (NTRS)

1998-01-01

The purpose of this mission is to study the climate history and the water distribution of Mars. Beautiful panoramic views of the shuttle on the launch pad, engine ignition, Rocket launch, and the separation and burnout of the Solid Rocket Boosters are shown. The footage also includes an animation of the mission. Detailed views of the path that the Orbiter traversed were shown. Once the Orbiter lands on the surface of Mars, it will dig a six to eight inch hole and collect samples from the planets' surface. The animation also included the prospective return of the Orbiter to Earth over the desert of Utah. The remote sensor on the Orbiter helps in finding the exact location of the Orbiter so that scientists may collect the sample and analyze it.

Portable remote laser sensor for methane leak detection

NASA Technical Reports Server (NTRS)

Grant, W. B.; Hinkley, E. D., Jr. (Inventor)

1984-01-01

A portable laser system for remote detection of methane gas leaks and concentrations is disclosed. The system transmitter includes first and second lasers, tuned respectively to a wavelength coincident with a strong absorption line of methane and a reference wavelength which is weakly absorbed by methane gas. The system receiver includes a spherical mirror for collecting the reflected laser radiation and focusing the collected radiation through a narrowband optical filter onto an optial detector. The filter is tuned to the wavelength of the two lasers, and rejects background noise. The output of the optical detector is processed by a lock-in detector synchronized to the chopper, and which measures the difference between the first wavelength signal and the reference wavelength signal.

The Wave Glider°: A New Autonomous Surface Vehicle to Augment MBARI's Growing Fleet of Ocean Observing Systems

NASA Astrophysics Data System (ADS)

Tougher, B. B.

2011-12-01

Monterey Bay Aquarium Research Institute's (MBARI) evolving fleet of ocean observing systems has made it possible to collect information and data about a wide variety of ocean parameters, enabling researchers to better understand marine ecosystems. In collaboration with Liquid Robotics Inc, the designer of the Wave Glider autonomous surface vehicle (ASV), MBARI is adding a new capability to its suite of ocean observing tools. This new technology will augment MBARI research programs that use satellites, ships, moorings, drifters, autonomous underwater vehicles (AUVs) and remotely operated vehicles (ROVs) to improve data collection of temporally and spatially variable oceanographic features. The Wave Glider ASV derives its propulsion from wave energy, while sensors and communications are powered through the use of two solar panels and batteries, enabling it to remain at sea indefinitely. Wave Gliders are remotely controlled via real-time Iridium burst communications, which also permit real-time data telemetry. MBARI has developed Ocean Acidification (OA) moorings to continuously monitor the chemical and physical changes occurring in the ocean as a result of increased levels of atmospheric carbon dioxide (CO2). The moorings are spatially restricted by being anchored to the seafloor, so during the summer of 2011 the ocean acidification sensor suite designed for moorings was integrated into a Wave Glider ASV to increase both temporal and spatial ocean observation capabilities. The OA sensor package enables the measurement of parameters essential to better understanding the changing acidity of the ocean, specifically pCO2, pH, oxygen, salinity and temperature. The Wave Glider will also be equipped with a meteorological sensor suite that will measure air temperature, air pressure, and wind speed and direction. The OA sensor integration into a Wave Glider was part of MBARI's 2011 summer internship program. This project involved designing a new layout for the OA sensors within a Wave Glider aft payload dry box. The Wave Glider OA sensor suite includes the addition of a pCO2 standard tank not included within the current OA moorings. Communication links between MBARI electronics and Liquid Robotics Control and Communications were successfully established in the laboratory, however further steps to fully integrate and test the OA system into a Wave Glider ASV are still needed. In the future these ASVs will provide platforms for additional surface and subsurface instrumentation, particularly with MBARI's upcoming Controlled, Agile, and Novel, Observing Network (CANON) projects. The integration of the OA sensor package into a Wave Glider ASV will make it possible to continuously monitor the marine environment during adverse weather conditions which are often difficult to document but scientifically important.

Semantic Support for Complex Ecosystem Research Environments

NASA Astrophysics Data System (ADS)

Klawonn, M.; McGuinness, D. L.; Pinheiro, P.; Santos, H. O.; Chastain, K.

2015-12-01

As ecosystems come under increasing stresses from diverse sources, there is growing interest in research efforts aimed at monitoring, modeling, and improving understanding of ecosystems and protection options. We aimed to provide a semantic infrastructure capable of representing data initially related to one large aquatic ecosystem research effort - the Jefferson project at Lake George. This effort includes significant historical observational data, extensive sensor-based monitoring data, experimental data, as well as model and simulation data covering topics including lake circulation, watershed runoff, lake biome food webs, etc. The initial measurement representation has been centered on monitoring data and related provenance. We developed a human-aware sensor network ontology (HASNetO) that leverages existing ontologies (PROV-O, OBOE, VSTO*) in support of measurement annotations. We explicitly support the human-aware aspects of human sensor deployment and collection activity to help capture key provenance that often is lacking. Our foundational ontology has since been generalized into a family of ontologies and used to create our human-aware data collection infrastructure that now supports the integration of measurement data along with simulation data. Interestingly, we have also utilized the same infrastructure to work with partners who have some more specific needs for specifying the environmental conditions where measurements occur, for example, knowing that an air temperature is not an external air temperature, but of the air temperature when windows are shut and curtains are open. We have also leveraged the same infrastructure to work with partners more interested in modeling smart cities with data feeds more related to people, mobility, environment, and living. We will introduce our human-aware data collection infrastructure, and demonstrate how it uses HASNetO and its supporting SOLR-based search platform to support data integration and semantic browsing. Further we will present learnings from its use in three relatively diverse large ecosystem research efforts and highlight some benefits and challenges related to our semantically-enhanced foundation.

Evaluation of Three State-of-the-Art Classifiers for Recognition of Activities of Daily Living from Smart Home Ambient Data

PubMed Central

Nef, Tobias; Urwyler, Prabitha; Büchler, Marcel; Tarnanas, Ioannis; Stucki, Reto; Cazzoli, Dario; Müri, René; Mosimann, Urs

2012-01-01

Smart homes for the aging population have recently started attracting the attention of the research community. The “health state” of smart homes is comprised of many different levels; starting with the physical health of citizens, it also includes longer-term health norms and outcomes, as well as the arena of positive behavior changes. One of the problems of interest is to monitor the activities of daily living (ADL) of the elderly, aiming at their protection and well-being. For this purpose, we installed passive infrared (PIR) sensors to detect motion in a specific area inside a smart apartment and used them to collect a set of ADL. In a novel approach, we describe a technology that allows the ground truth collected in one smart home to train activity recognition systems for other smart homes. We asked the users to label all instances of all ADL only once and subsequently applied data mining techniques to cluster in-home sensor firings. Each cluster would therefore represent the instances of the same activity. Once the clusters were associated to their corresponding activities, our system was able to recognize future activities. To improve the activity recognition accuracy, our system preprocessed raw sensor data by identifying overlapping activities. To evaluate the recognition performance from a 200-day dataset, we implemented three different active learning classification algorithms and compared their performance: naive Bayesian (NB), support vector machine (SVM) and random forest (RF). Based on our results, the RF classifier recognized activities with an average specificity of 96.53%, a sensitivity of 68.49%, a precision of 74.41% and an F-measure of 71.33%, outperforming both the NB and SVM classifiers. Further clustering markedly improved the results of the RF classifier. An activity recognition system based on PIR sensors in conjunction with a clustering classification approach was able to detect ADL from datasets collected from different homes. Thus, our PIR-based smart home technology could improve care and provide valuable information to better understand the functioning of our societies, as well as to inform both individual and collective action in a smart city scenario. PMID:26007727

Evaluation of Three State-of-the-Art Classifiers for Recognition of Activities of Daily Living from Smart Home Ambient Data.

PubMed

Nef, Tobias; Urwyler, Prabitha; Büchler, Marcel; Tarnanas, Ioannis; Stucki, Reto; Cazzoli, Dario; Müri, René; Mosimann, Urs

2015-05-21

Smart homes for the aging population have recently started attracting the attention of the research community. The "health state" of smart homes is comprised of many different levels; starting with the physical health of citizens, it also includes longer-term health norms and outcomes, as well as the arena of positive behavior changes. One of the problems of interest is to monitor the activities of daily living (ADL) of the elderly, aiming at their protection and well-being. For this purpose, we installed passive infrared (PIR) sensors to detect motion in a specific area inside a smart apartment and used them to collect a set of ADL. In a novel approach, we describe a technology that allows the ground truth collected in one smart home to train activity recognition systems for other smart homes. We asked the users to label all instances of all ADL only once and subsequently applied data mining techniques to cluster in-home sensor firings. Each cluster would therefore represent the instances of the same activity. Once the clusters were associated to their corresponding activities, our system was able to recognize future activities. To improve the activity recognition accuracy, our system preprocessed raw sensor data by identifying overlapping activities. To evaluate the recognition performance from a 200-day dataset, we implemented three different active learning classification algorithms and compared their performance: naive Bayesian (NB), support vector machine (SVM) and random forest (RF). Based on our results, the RF classifier recognized activities with an average specificity of 96.53%, a sensitivity of 68.49%, a precision of 74.41% and an F-measure of 71.33%, outperforming both the NB and SVM classifiers. Further clustering markedly improved the results of the RF classifier. An activity recognition system based on PIR sensors in conjunction with a clustering classification approach was able to detect ADL from datasets collected from different homes. Thus, our PIR-based smart home technology could improve care and provide valuable information to better understand the functioning of our societies, as well as to inform both individual and collective action in a smart city scenario.

Barriers to the Adoption of Wearable Sensors in the Workplace: A Survey of Occupational Safety and Health Professionals.

PubMed

Schall, Mark C; Sesek, Richard F; Cavuoto, Lora A

2018-05-01

To gather information on the (a) types of wearable sensors, particularly personal activity monitors, currently used by occupational safety and health (OSH) professionals; (b) potential benefits of using such technologies in the workplace; and (c) perceived barriers preventing the widespread adoption of wearable sensors in industry. Wearable sensors are increasingly being promoted as a means to improve employee health and well-being, and there is mounting evidence supporting their use as exposure assessment and personal health tools. Despite this, many workplaces have been hesitant to adopt these technologies. An electronic survey was emailed to 28,428 registered members of the American Society of Safety Engineers (ASSE) and 1,302 professionals certified by the Board of Certification in Professional Ergonomics (BCPE). A total of 952 valid responses were returned. Over half of respondents described being in favor of using wearable sensors to track OSH-related risk factors and relevant exposure metrics at their respective workplaces. However, barriers including concerns regarding employee privacy/confidentiality of collected data, employee compliance, sensor durability, the cost/benefit ratio of using wearables, and good manufacturing practice requirements were described as challenges precluding adoption. The broad adoption of wearable technologies appears to depend largely on the scientific community's ability to successfully address the identified barriers. Investigators may use the information provided to develop research studies that better address OSH practitioner concerns and help technology developers operationalize wearable sensors to improve employee health and well-being.

A Practical Application Combining Wireless Sensor Networks and Internet of Things: Safety Management System for Tower Crane Groups

PubMed Central

Zhong, Dexing; Lv, Hongqiang; Han, Jiuqiang; Wei, Quanrui

2014-01-01

The so-called Internet of Things (IoT) has attracted increasing attention in the field of computer and information science. In this paper, a specific application of IoT, named Safety Management System for Tower Crane Groups (SMS-TC), is proposed for use in the construction industry field. The operating status of each tower crane was detected by a set of customized sensors, including horizontal and vertical position sensors for the trolley, angle sensors for the jib and load, tilt and wind speed sensors for the tower body. The sensor data is collected and processed by the Tower Crane Safety Terminal Equipment (TC-STE) installed in the driver's operating room. Wireless communication between each TC-STE and the Local Monitoring Terminal (LMT) at the ground worksite were fulfilled through a Zigbee wireless network. LMT can share the status information of the whole group with each TC-STE, while the LMT records the real-time data and reports it to the Remote Supervision Platform (RSP) through General Packet Radio Service (GPRS). Based on the global status data of the whole group, an anti-collision algorithm was executed in each TC-STE to ensure the safety of each tower crane during construction. Remote supervision can be fulfilled using our client software installed on a personal computer (PC) or smartphone. SMS-TC could be considered as a promising practical application that combines a Wireless Sensor Network with the Internet of Things. PMID:25196106

A practical application combining wireless sensor networks and Internet of Things: Safety Management System for Tower Crane Groups.

PubMed

Zhong, Dexing; Lv, Hongqiang; Han, Jiuqiang; Wei, Quanrui

2014-07-30

The so-called Internet of Things (IoT) has attracted increasing attention in the field of computer and information science. In this paper, a specific application of IoT, named Safety Management System for Tower Crane Groups (SMS-TC), is proposed for use in the construction industry field. The operating status of each tower crane was detected by a set of customized sensors, including horizontal and vertical position sensors for the trolley, angle sensors for the jib and load, tilt and wind speed sensors for the tower body. The sensor data is collected and processed by the Tower Crane Safety Terminal Equipment (TC-STE) installed in the driver's operating room. Wireless communication between each TC-STE and the Local Monitoring Terminal (LMT) at the ground worksite were fulfilled through a Zigbee wireless network. LMT can share the status information of the whole group with each TC-STE, while the LMT records the real-time data and reports it to the Remote Supervision Platform (RSP) through General Packet Radio Service (GPRS). Based on the global status data of the whole group, an anti-collision algorithm was executed in each TC-STE to ensure the safety of each tower crane during construction. Remote supervision can be fulfilled using our client software installed on a personal computer (PC) or smartphone. SMS-TC could be considered as a promising practical application that combines a Wireless Sensor Network with the Internet of Things.

Managed traffic evacuation using distributed sensor processing

NASA Astrophysics Data System (ADS)

Ramuhalli, Pradeep; Biswas, Subir

2005-05-01

This paper presents an integrated sensor network and distributed event processing architecture for managed in-building traffic evacuation during natural and human-caused disasters, including earthquakes, fire and biological/chemical terrorist attacks. The proposed wireless sensor network protocols and distributed event processing mechanisms offer a new distributed paradigm for improving reliability in building evacuation and disaster management. The networking component of the system is constructed using distributed wireless sensors for measuring environmental parameters such as temperature, humidity, and detecting unusual events such as smoke, structural failures, vibration, biological/chemical or nuclear agents. Distributed event processing algorithms will be executed by these sensor nodes to detect the propagation pattern of the disaster and to measure the concentration and activity of human traffic in different parts of the building. Based on this information, dynamic evacuation decisions are taken for maximizing the evacuation speed and minimizing unwanted incidents such as human exposure to harmful agents and stampedes near exits. A set of audio-visual indicators and actuators are used for aiding the automated evacuation process. In this paper we develop integrated protocols, algorithms and their simulation models for the proposed sensor networking and the distributed event processing framework. Also, efficient harnessing of the individually low, but collectively massive, processing abilities of the sensor nodes is a powerful concept behind our proposed distributed event processing algorithms. Results obtained through simulation in this paper are used for a detailed characterization of the proposed evacuation management system and its associated algorithmic components.

Australian Space Situational Awareness Capability Demonstrations

NASA Astrophysics Data System (ADS)

Morreale, B.; Bessell, T.; Rutten, M.; Cheung, B.

Australia is increasing its contribution to the global space situational awareness (SSA) problem by committing to acquire and operate SSA sensors. Over the last year, a series of collaborative SSA experiments have been undertaken to demonstrate the capabilities of Australian sensors. These experiments aimed to demonstrate how existing Australian sensors could perform in a surveillance of space role, prove passive radar’s capability to observe low earth orbit (LEO) satellites and perform SSA handoffs to optical sensors. The trials established a data sharing and communications protocol that bridged defence, academia, and industry partners. Geographically dispersed optical assets, including the Falcon telescope in Canberra, Raven telescopes in Exmouth (Western Australia) and Defence Science and Technology (DST) Telescopes in Adelaide (South Australia) collected on LEO satellites and established cueing protocols. The Murchison Widefield Array (MWA) located in Western Australia, demonstrated the capability of passive radar as an SSA asset after successfully observing LEO satellites based on reflected terrestrial radio signals. The combination of radar and optical SSA assets allows for the exploitation of each sensors unique advantages and locations across the Australian continent. This paper outlines the capabilities and diversity of Australian optical and radar sensors as demonstrated by field trials in 2016 and 2017. It suggests future potential for harnessing novel radar and optical integration techniques to supplement high-value assets such as the Space Surveillance Telescope as part of the Space Surveillance Network.

Defect-Repairable Latent Feature Extraction of Driving Behavior via a Deep Sparse Autoencoder

PubMed Central

Taniguchi, Tadahiro; Takenaka, Kazuhito; Bando, Takashi

2018-01-01

Data representing driving behavior, as measured by various sensors installed in a vehicle, are collected as multi-dimensional sensor time-series data. These data often include redundant information, e.g., both the speed of wheels and the engine speed represent the velocity of the vehicle. Redundant information can be expected to complicate the data analysis, e.g., more factors need to be analyzed; even varying the levels of redundancy can influence the results of the analysis. We assume that the measured multi-dimensional sensor time-series data of driving behavior are generated from low-dimensional data shared by the many types of one-dimensional data of which multi-dimensional time-series data are composed. Meanwhile, sensor time-series data may be defective because of sensor failure. Therefore, another important function is to reduce the negative effect of defective data when extracting low-dimensional time-series data. This study proposes a defect-repairable feature extraction method based on a deep sparse autoencoder (DSAE) to extract low-dimensional time-series data. In the experiments, we show that DSAE provides high-performance latent feature extraction for driving behavior, even for defective sensor time-series data. In addition, we show that the negative effect of defects on the driving behavior segmentation task could be reduced using the latent features extracted by DSAE. PMID:29462931

Passive wireless sensor systems can recognize activites of daily living.

PubMed

Urwyler, Prabitha; Stucki, Reto; Muri, Rene; Mosimann, Urs P; Nef, Tobias

2015-08-01

The ability to determine what activity of daily living a person performs is of interest in many application domains. It is possible to determine the physical and cognitive capabilities of the elderly by inferring what activities they perform in their houses. Our primary aim was to establish a proof of concept that a wireless sensor system can monitor and record physical activity and these data can be modeled to predict activities of daily living. The secondary aim was to determine the optimal placement of the sensor boxes for detecting activities in a room. A wireless sensor system was set up in a laboratory kitchen. The ten healthy participants were requested to make tea following a defined sequence of tasks. Data were collected from the eight wireless sensor boxes placed in specific places in the test kitchen and analyzed to detect the sequences of tasks performed by the participants. These sequence of tasks were trained and tested using the Markov Model. Data analysis focused on the reliability of the system and the integrity of the collected data. The sequence of tasks were successfully recognized for all subjects and the averaged data pattern of tasks sequences between the subjects had a high correlation. Analysis of the data collected indicates that sensors placed in different locations are capable of recognizing activities, with the movement detection sensor contributing the most to detection of tasks. The central top of the room with no obstruction of view was considered to be the best location to record data for activity detection. Wireless sensor systems show much promise as easily deployable to monitor and recognize activities of daily living.

A Systematic Method of Integrating BIM and Sensor Technology for Sustainable Construction Design

NASA Astrophysics Data System (ADS)

Liu, Zhen; Deng, Zhiyu

2017-10-01

Building Information Modeling (BIM) has received lots of attention of construction field, and sensor technology was applied in construction data collection. This paper developed a method to integrate BIM and sensor technology for sustainable construction design. A brief literature review was conducted to clarify the current development of BIM and sensor technology; then a systematic method for integrating BIM and sensor technology to realize sustainable construction design was put forward; finally a brief discussion and conclusion was given.

Design and implementation of PAVEMON: A GIS web-based pavement monitoring system based on large amounts of heterogeneous sensors data

NASA Astrophysics Data System (ADS)

Shahini Shamsabadi, Salar

A web-based PAVEment MONitoring system, PAVEMON, is a GIS oriented platform for accommodating, representing, and leveraging data from a multi-modal mobile sensor system. Stated sensor system consists of acoustic, optical, electromagnetic, and GPS sensors and is capable of producing as much as 1 Terabyte of data per day. Multi-channel raw sensor data (microphone, accelerometer, tire pressure sensor, video) and processed results (road profile, crack density, international roughness index, micro texture depth, etc.) are outputs of this sensor system. By correlating the sensor measurements and positioning data collected in tight time synchronization, PAVEMON attaches a spatial component to all the datasets. These spatially indexed outputs are placed into an Oracle database which integrates seamlessly with PAVEMON's web-based system. The web-based system of PAVEMON consists of two major modules: 1) a GIS module for visualizing and spatial analysis of pavement condition information layers, and 2) a decision-support module for managing maintenance and repair (Mℝ) activities and predicting future budget needs. PAVEMON weaves together sensor data with third-party climate and traffic information from the National Oceanic and Atmospheric Administration (NOAA) and Long Term Pavement Performance (LTPP) databases for an organized data driven approach to conduct pavement management activities. PAVEMON deals with heterogeneous and redundant observations by fusing them for jointly-derived higher-confidence results. A prominent example of the fusion algorithms developed within PAVEMON is a data fusion algorithm used for estimating the overall pavement conditions in terms of ASTM's Pavement Condition Index (PCI). PAVEMON predicts PCI by undertaking a statistical fusion approach and selecting a subset of all the sensor measurements. Other fusion algorithms include noise-removal algorithms to remove false negatives in the sensor data in addition to fusion algorithms developed for identifying features on the road. PAVEMON offers an ideal research and monitoring platform for rapid, intelligent and comprehensive evaluation of tomorrow's transportation infrastructure based on up-to-date data from heterogeneous sensor systems.

Feasibility testing of a home-based sensor system to monitor mobility and daily activities in Korean American older adults.

PubMed

Chung, Jane; Demiris, George; Thompson, Hilaire J; Chen, Ke-Yu; Burr, Robert; Patel, Shwetak; Fogarty, James

2017-03-01

This study aimed to test feasibility of a home-based sensor system that is designed to assess mobility and daily activity patterns among Korean American older adults (KAOAs; n = 6) and explore sensor technology acceptance among participants. Home-based sensors have the potential to support older adults' desire to remain at home as long as possible. Despite a growing interest in using home-based sensors for older adults, there have been no documented attempts to apply this type of technology to a group of ethnic minority older adults. The study employed descriptive, quantitative and qualitative approaches. The system was deployed for 2 months in four homes of KAOAs. Study procedures included (i) sensor-based data collection, (ii) self-report mobility instruments, (iii) activity logs and (iv) interviews. To explore changes in activity patterns, line graphs and sequence plots were applied to data obtained from a set of sensors. General linear models (GLMs) were used for motion in each space of the home to examine how much variability of activities is explained by several time variables. Sensor data had natural fluctuation over time. Different 24-hr patterns were observed across homes. The GLM estimates showed that effect sizes of the time variables vary across individuals. A hydro sensor deployed in one participant's bathroom inferred various water usage activities. Overall, sensors were acceptable for all participants, despite some privacy concerns. Study findings demonstrate that sensor technology applications could be successfully used longitudinally in a minority population of older adults that is not often targeted as an end-user group for the use of innovative technologies. The use of home-based sensors provides nurses with a useful tool to detect deviations from normal patterns and to achieve proactive care for some groups of older adults. © 2016 John Wiley & Sons Ltd.

A Tool for the Automated Collection of Space Utilization Data: Three Dimensional Space Utilization Monitor

NASA Technical Reports Server (NTRS)

Vos, Gordon A.; Fink, Patrick; Ngo, Phong H.; Morency, Richard; Simon, Cory; Williams, Robert E.; Perez, Lance C.

2017-01-01

Space Human Factors and Habitability (SHFH) Element within the Human Research Program (HRP) and the Behavioral Health and Performance (BHP) Element are conducting research regarding Net Habitable Volume (NHV), the internal volume within a spacecraft or habitat that is available to crew for required activities, as well as layout and accommodations within the volume. NASA needs methods to unobtrusively collect NHV data without impacting crew time. Data required includes metrics such as location and orientation of crew, volume used to complete tasks, internal translation paths, flow of work, and task completion times. In less constrained environments methods exist yet many are obtrusive and require significant post-processing. ?Examplesused in terrestrial settings include infrared (IR) retro-reflective marker based motion capture, GPS sensor tracking, inertial tracking, and multi-camera methods ?Due to constraints of space operations many such methods are infeasible. Inertial tracking systems typically rely upon a gravity vector to normalize sensor readings,and traditional IR systems are large and require extensive calibration. ?However, multiple technologies have not been applied to space operations for these purposes. Two of these include: 3D Radio Frequency Identification Real-Time Localization Systems (3D RFID-RTLS) ?Depth imaging systems which allow for 3D motion capture and volumetric scanning (such as those using IR-depth cameras like the Microsoft Kinect or Light Detection and Ranging / Light-Radar systems, referred to as LIDAR)

A Platform to Build Mobile Health Apps: The Personal Health Intervention Toolkit (PHIT).

PubMed

Eckhoff, Randall Peter; Kizakevich, Paul Nicholas; Bakalov, Vesselina; Zhang, Yuying; Bryant, Stephanie Patrice; Hobbs, Maria Ann

2015-06-01

Personal Health Intervention Toolkit (PHIT) is an advanced cross-platform software framework targeted at personal self-help research on mobile devices. Following the subjective and objective measurement, assessment, and plan methodology for health assessment and intervention recommendations, the PHIT platform lets researchers quickly build mobile health research Android and iOS apps. They can (1) create complex data-collection instruments using a simple extensible markup language (XML) schema; (2) use Bluetooth wireless sensors; (3) create targeted self-help interventions based on collected data via XML-coded logic; (4) facilitate cross-study reuse from the library of existing instruments and interventions such as stress, anxiety, sleep quality, and substance abuse; and (5) monitor longitudinal intervention studies via daily upload to a Web-based dashboard portal. For physiological data, Bluetooth sensors collect real-time data with on-device processing. For example, using the BinarHeartSensor, the PHIT platform processes the heart rate data into heart rate variability measures, and plots these data as time-series waveforms. Subjective data instruments are user data-entry screens, comprising a series of forms with validation and processing logic. The PHIT instrument library consists of over 70 reusable instruments for various domains including cognitive, environmental, psychiatric, psychosocial, and substance abuse. Many are standardized instruments, such as the Alcohol Use Disorder Identification Test, Patient Health Questionnaire-8, and Post-Traumatic Stress Disorder Checklist. Autonomous instruments such as battery and global positioning system location support continuous background data collection. All data are acquired using a schedule appropriate to the app's deployment. The PHIT intelligent virtual advisor (iVA) is an expert system logic layer, which analyzes the data in real time on the device. This data analysis results in a tailored app of interventions and other data-collection instruments. For example, if a user anxiety score exceeds a threshold, the iVA might add a meditation intervention to the task list in order to teach the user how to relax, and schedule a reassessment using the anxiety instrument 2 weeks later to re-evaluate. If the anxiety score exceeds a higher threshold, then an advisory to seek professional help would be displayed. Using the easy-to-use PHIT scripting language, the researcher can program new instruments, the iVA, and interventions to their domain-specific needs. The iVA, instruments, and interventions are defined via XML files, which facilities rapid app development and deployment. The PHIT Web-based dashboard portal provides the researcher access to all the uploaded data. After a secure login, the data can be filtered by criteria such as study, protocol, domain, and user. Data can also be exported into a comma-delimited file for further processing. The PHIT framework has proven to be an extensible, reconfigurable technology that facilitates mobile data collection and health intervention research. Additional plans include instrument development in other domains, additional health sensors, and a text messaging notification system.

A Platform to Build Mobile Health Apps: The Personal Health Intervention Toolkit (PHIT)

PubMed Central

2015-01-01

Personal Health Intervention Toolkit (PHIT) is an advanced cross-platform software framework targeted at personal self-help research on mobile devices. Following the subjective and objective measurement, assessment, and plan methodology for health assessment and intervention recommendations, the PHIT platform lets researchers quickly build mobile health research Android and iOS apps. They can (1) create complex data-collection instruments using a simple extensible markup language (XML) schema; (2) use Bluetooth wireless sensors; (3) create targeted self-help interventions based on collected data via XML-coded logic; (4) facilitate cross-study reuse from the library of existing instruments and interventions such as stress, anxiety, sleep quality, and substance abuse; and (5) monitor longitudinal intervention studies via daily upload to a Web-based dashboard portal. For physiological data, Bluetooth sensors collect real-time data with on-device processing. For example, using the BinarHeartSensor, the PHIT platform processes the heart rate data into heart rate variability measures, and plots these data as time-series waveforms. Subjective data instruments are user data-entry screens, comprising a series of forms with validation and processing logic. The PHIT instrument library consists of over 70 reusable instruments for various domains including cognitive, environmental, psychiatric, psychosocial, and substance abuse. Many are standardized instruments, such as the Alcohol Use Disorder Identification Test, Patient Health Questionnaire-8, and Post-Traumatic Stress Disorder Checklist. Autonomous instruments such as battery and global positioning system location support continuous background data collection. All data are acquired using a schedule appropriate to the app’s deployment. The PHIT intelligent virtual advisor (iVA) is an expert system logic layer, which analyzes the data in real time on the device. This data analysis results in a tailored app of interventions and other data-collection instruments. For example, if a user anxiety score exceeds a threshold, the iVA might add a meditation intervention to the task list in order to teach the user how to relax, and schedule a reassessment using the anxiety instrument 2 weeks later to re-evaluate. If the anxiety score exceeds a higher threshold, then an advisory to seek professional help would be displayed. Using the easy-to-use PHIT scripting language, the researcher can program new instruments, the iVA, and interventions to their domain-specific needs. The iVA, instruments, and interventions are defined via XML files, which facilities rapid app development and deployment. The PHIT Web-based dashboard portal provides the researcher access to all the uploaded data. After a secure login, the data can be filtered by criteria such as study, protocol, domain, and user. Data can also be exported into a comma-delimited file for further processing. The PHIT framework has proven to be an extensible, reconfigurable technology that facilitates mobile data collection and health intervention research. Additional plans include instrument development in other domains, additional health sensors, and a text messaging notification system. PMID:26033047

Self-localization of wireless sensor networks using self-organizing maps

NASA Astrophysics Data System (ADS)

Ertin, Emre; Priddy, Kevin L.

2005-03-01

Recently there has been a renewed interest in the notion of deploying large numbers of networked sensors for applications ranging from environmental monitoring to surveillance. In a typical scenario a number of sensors are distributed in a region of interest. Each sensor is equipped with sensing, processing and communication capabilities. The information gathered from the sensors can be used to detect, track and classify objects of interest. For a number of locations the sensors location is crucial in interpreting the data collected from those sensors. Scalability requirements dictate sensor nodes that are inexpensive devices without a dedicated localization hardware such as GPS. Therefore the network has to rely on information collected within the network to self-localize. In the literature a number of algorithms has been proposed for network localization which uses measurements informative of range, angle, proximity between nodes. Recent work by Patwari and Hero relies on sensor data without explicit range estimates. The assumption is that the correlation structure in the data is a monotone function of the intersensor distances. In this paper we propose a new method based on unsupervised learning techniques to extract location information from the sensor data itself. We consider a grid consisting of virtual nodes and try to fit grid in the actual sensor network data using the method of self organizing maps. Then known sensor network geometry can be used to rotate and scale the grid to a global coordinate system. Finally, we illustrate how the virtual nodes location information can be used to track a target.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Herman, R.; O’Brien, S.

Using our own prototype sensor arrays that were deployed to collect microclimate data, we were able to visualize distinct differences in temperature, wind speed, and humidity over very small ranges of distance. We collected data across four polygons within the Barrow Environmental Observatory site. Our prototype microclimate arrays were based on an Arduino microcontroller, DS18B20 temperature sensors, DHT11 relative humidity/temperature sensors, and Vernier anemometers. Data were obtained in a small grid pattern with four sensors spaced 60 cm apart along the x-axis, and moved at 60 cm increments along a y-line across a polygon. Overlaying bird nest location with suchmore » data has allowed us to better answer our research question, “How do Arctic birds choose where to nest to maximize fitness in harsh Arctic environments?”« less

Quantifying multi-dimensional attributes of human activities at various geographic scales based on smartphone tracking.

PubMed

Zhou, Xiaolu; Li, Dongying

2018-05-09

Advancement in location-aware technologies, and information and communication technology in the past decades has furthered our knowledge of the interaction between human activities and the built environment. An increasing number of studies have collected data regarding individual activities to better understand how the environment shapes human behavior. Despite this growing interest, some challenges exist in collecting and processing individual's activity data, e.g., capturing people's precise environmental contexts and analyzing data at multiple spatial scales. In this study, we propose and implement an innovative system that integrates smartphone-based step tracking with an app and the sequential tile scan techniques to collect and process activity data. We apply the OpenStreetMap tile system to aggregate positioning points at various scales. We also propose duration, step and probability surfaces to quantify the multi-dimensional attributes of activities. Results show that, by running the app in the background, smartphones can measure multi-dimensional attributes of human activities, including space, duration, step, and location uncertainty at various spatial scales. By coordinating Global Positioning System (GPS) sensor with accelerometer sensor, this app can save battery which otherwise would be drained by GPS sensor quickly. Based on a test dataset, we were able to detect the recreational center and sports center as the space where the user was most active, among other places visited. The methods provide techniques to address key issues in analyzing human activity data. The system can support future studies on behavioral and health consequences related to individual's environmental exposure.

Determination of mandibular border and functional movement protocols using an electromagnetic articulograph (EMA).

PubMed

Fuentes, Ramon; Navarro, Pablo; Curiqueo, Aldo; Ottone, Nicolas E

2015-01-01

The electromagnetic articulograph (EMA) is a device that can collect movement data by positioning sensors at multiple points, measuring displacements of the structure in real time, as well as the acoustics and mechanics of speech using a microphone connected to the measurement system. The aim of this study is to describe protocols for the generation, measurement and visualization of mandibular border and functional movements in the three spatial planes (frontal, sagittal and horizontal) using the EMA. The EMA has transmitter coils that determine magnetic fields to collect information about movements from sensors located on different structures (tongue, palate, mouth, incisors, skin, etc.) and in every direction in an area of 300 mm. After measurement with the EMA, the information is transferred to a computer and read with the Visartico software to visualize the recording of the mandibular movements registered by the EMA. The sensors placed in the space between the three axes XYZ are observed, and then the plots created from the mandibular movements included in the corresponding protocol can be visualized, enabling interpretation of these data. Four protocols for the obtaining of images of the opening and closing mandibular movements were defined and developed, as well as border movements in the frontal, sagittal and horizontal planes, managing to accurately reproduce Posselt's diagram and Gothic arch on the latter two axes. Measurements with the EMA will allow more exact data to be collected in relation to the mandibular clinical physiology and morphology, which will permit more accurate diagnoses and application of more precise and adjusted treatments in the future.

Data Collection for Disaster Response from the International Space Station

NASA Astrophysics Data System (ADS)

Stefanov, W. L.; Evans, C. A.

2015-04-01

Remotely sensed data acquired by orbital sensor systems has emerged as a vital tool to identify the extent of damage resulting from a natural disaster, as well as providing near-real time mapping support to response efforts on the ground and humanitarian aid efforts. The International Space Station (ISS) is a unique terrestrial remote sensing platform for acquiring disaster response imagery. Unlike automated remote-sensing platforms it has a human crew; is equipped with both internal and externally-mounted remote sensing instruments; and has an inclined, low-Earth orbit that provides variable views and lighting (day and night) over 90 percent of the inhabited surface of the Earth. As such, it provides a useful complement to autonomous sensor systems in higher altitude polar orbits. NASA remote sensing assets on the station began collecting International Charter, Space and Major Disasters, also known informally as the International Disaster Charter (IDC) response data in May 2012. Since the start of IDC response in 2012, and as of late March 2015, there have been 123 IDC activations; NASA sensor systems have collected data for thirty-four of these events. Of the successful data collections, eight involved two or more ISS sensor systems responding to the same event. Data has also been collected by International Partners in response to natural disasters, most notably JAXA and Roscosmos/Energia through the Urugan program.