An Interoperable Architecture for Air Pollution Early Warning System Based on Sensor Web

NASA Astrophysics Data System (ADS)

Samadzadegan, F.; Zahmatkesh, H.; Saber, M.; Ghazi khanlou, H. J.

2013-09-01

Environmental monitoring systems deal with time-sensitive issues which require quick responses in emergency situations. Handling the sensor observations in near real-time and obtaining valuable information is challenging issues in these systems from a technical and scientific point of view. The ever-increasing population growth in urban areas has caused certain problems in developing countries, which has direct or indirect impact on human life. One of applicable solution for controlling and managing air quality by considering real time and update air quality information gathered by spatially distributed sensors in mega cities, using sensor web technology for developing monitoring and early warning systems. Urban air quality monitoring systems using functionalities of geospatial information system as a platform for analysing, processing, and visualization of data in combination with Sensor Web for supporting decision support systems in disaster management and emergency situations. This system uses Sensor Web Enablement (SWE) framework of the Open Geospatial Consortium (OGC), which offers a standard framework that allows the integration of sensors and sensor data into spatial data infrastructures. SWE framework introduces standards for services to access sensor data and discover events from sensor data streams as well as definition set of standards for the description of sensors and the encoding of measurements. The presented system provides capabilities to collect, transfer, share, process air quality sensor data and disseminate air quality status in real-time. It is possible to overcome interoperability challenges by using standard framework. In a routine scenario, air quality data measured by in-situ sensors are communicated to central station where data is analysed and processed. The extracted air quality status is processed for discovering emergency situations, and if necessary air quality reports are sent to the authorities. This research proposed an architecture to represent how integrate air quality sensor data stream into geospatial data infrastructure to present an interoperable air quality monitoring system for supporting disaster management systems by real time information. Developed system tested on Tehran air pollution sensors for calculating Air Quality Index (AQI) for CO pollutant and subsequently notifying registered users in emergency cases by sending warning E-mails. Air quality monitoring portal used to retrieving and visualize sensor observation through interoperable framework. This system provides capabilities to retrieve SOS observation using WPS in a cascaded service chaining pattern for monitoring trend of timely sensor observation.

A Web service-based architecture for real-time hydrologic sensor networks

NASA Astrophysics Data System (ADS)

Wong, B. P.; Zhao, Y.; Kerkez, B.

2014-12-01

Recent advances in web services and cloud computing provide new means by which to process and respond to real-time data. This is particularly true of platforms built for the Internet of Things (IoT). These enterprise-scale platforms have been designed to exploit the IP-connectivity of sensors and actuators, providing a robust means by which to route real-time data feeds and respond to events of interest. While powerful and scalable, these platforms have yet to be adopted by the hydrologic community, where the value of real-time data impacts both scientists and decision makers. We discuss the use of one such IoT platform for the purpose of large-scale hydrologic measurements, showing how rapid deployment and ease-of-use allows scientists to focus on their experiment rather than software development. The platform is hardware agnostic, requiring only IP-connectivity of field devices to capture, store, process, and visualize data in real-time. We demonstrate the benefits of real-time data through a real-world use case by showing how our architecture enables the remote control of sensor nodes, thereby permitting the nodes to adaptively change sampling strategies to capture major hydrologic events of interest.

Real-time sensor validation and fusion for distributed autonomous sensors

NASA Astrophysics Data System (ADS)

Yuan, Xiaojing; Li, Xiangshang; Buckles, Bill P.

2004-04-01

Multi-sensor data fusion has found widespread applications in industrial and research sectors. The purpose of real time multi-sensor data fusion is to dynamically estimate an improved system model from a set of different data sources, i.e., sensors. This paper presented a systematic and unified real time sensor validation and fusion framework (RTSVFF) based on distributed autonomous sensors. The RTSVFF is an open architecture which consists of four layers - the transaction layer, the process fusion layer, the control layer, and the planning layer. This paradigm facilitates distribution of intelligence to the sensor level and sharing of information among sensors, controllers, and other devices in the system. The openness of the architecture also provides a platform to test different sensor validation and fusion algorithms and thus facilitates the selection of near optimal algorithms for specific sensor fusion application. In the version of the model presented in this paper, confidence weighted averaging is employed to address the dynamic system state issue noted above. The state is computed using an adaptive estimator and dynamic validation curve for numeric data fusion and a robust diagnostic map for decision level qualitative fusion. The framework is then applied to automatic monitoring of a gas-turbine engine, including a performance comparison of the proposed real-time sensor fusion algorithms and a traditional numerical weighted average.

A multiprocessing architecture for real-time monitoring

NASA Technical Reports Server (NTRS)

Schmidt, James L.; Kao, Simon M.; Read, Jackson Y.; Weitzenkamp, Scott M.; Laffey, Thomas J.

1988-01-01

A multitasking architecture for performing real-time monitoring and analysis using knowledge-based problem solving techniques is described. To handle asynchronous inputs and perform in real time, the system consists of three or more distributed processes which run concurrently and communicate via a message passing scheme. The Data Management Process acquires, compresses, and routes the incoming sensor data to other processes. The Inference Process consists of a high performance inference engine that performs a real-time analysis on the state and health of the physical system. The I/O Process receives sensor data from the Data Management Process and status messages and recommendations from the Inference Process, updates its graphical displays in real time, and acts as the interface to the console operator. The distributed architecture has been interfaced to an actual spacecraft (NASA's Hubble Space Telescope) and is able to process the incoming telemetry in real-time (i.e., several hundred data changes per second). The system is being used in two locations for different purposes: (1) in Sunnyville, California at the Space Telescope Test Control Center it is used in the preflight testing of the vehicle; and (2) in Greenbelt, Maryland at NASA/Goddard it is being used on an experimental basis in flight operations for health and safety monitoring.

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.

Digital Image Processing Overview For Helmet Mounted Displays

NASA Astrophysics Data System (ADS)

Parise, Michael J.

1989-09-01

Digital image processing provides a means to manipulate an image and presents a user with a variety of display formats that are not available in the analog image processing environment. When performed in real time and presented on a Helmet Mounted Display, system capability and flexibility are greatly enhanced. The information content of a display can be increased by the addition of real time insets and static windows from secondary sensor sources, near real time 3-D imaging from a single sensor can be achieved, graphical information can be added, and enhancement techniques can be employed. Such increased functionality is generating a considerable amount of interest in the military and commercial markets. This paper discusses some of these image processing techniques and their applications.

FPGA-based real time processing of the Plenoptic Wavefront Sensor

NASA Astrophysics Data System (ADS)

Rodríguez-Ramos, L. F.; Marín, Y.; Díaz, J. J.; Piqueras, J.; García-Jiménez, J.; Rodríguez-Ramos, J. M.

The plenoptic wavefront sensor combines measurements at pupil and image planes in order to obtain simultaneously wavefront information from different points of view, being capable to sample the volume above the telescope to extract the tomographic information of the atmospheric turbulence. The advantages of this sensor are presented elsewhere at this conference (José M. Rodríguez-Ramos et al). This paper will concentrate in the processing required for pupil plane phase recovery, and its computation in real time using FPGAs (Field Programmable Gate Arrays). This technology eases the implementation of massive parallel processing and allows tailoring the system to the requirements, maintaining flexibility, speed and cost figures.

Sensors and systems for space applications: a methodology for developing fault detection, diagnosis, and recovery

NASA Astrophysics Data System (ADS)

Edwards, John L.; Beekman, Randy M.; Buchanan, David B.; Farner, Scott; Gershzohn, Gary R.; Khuzadi, Mbuyi; Mikula, D. F.; Nissen, Gerry; Peck, James; Taylor, Shaun

2007-04-01

Human space travel is inherently dangerous. Hazardous conditions will exist. Real time health monitoring of critical subsystems is essential for providing a safe abort timeline in the event of a catastrophic subsystem failure. In this paper, we discuss a practical and cost effective process for developing critical subsystem failure detection, diagnosis and response (FDDR). We also present the results of a real time health monitoring simulation of a propellant ullage pressurization subsystem failure. The health monitoring development process identifies hazards, isolates hazard causes, defines software partitioning requirements and quantifies software algorithm development. The process provides a means to establish the number and placement of sensors necessary to provide real time health monitoring. We discuss how health monitoring software tracks subsystem control commands, interprets off-nominal operational sensor data, predicts failure propagation timelines, corroborate failures predictions and formats failure protocol.

Synthetic Foveal Imaging Technology

NASA Technical Reports Server (NTRS)

Nikzad, Shouleh (Inventor); Monacos, Steve P. (Inventor); Hoenk, Michael E. (Inventor)

2013-01-01

Apparatuses and methods are disclosed that create a synthetic fovea in order to identify and highlight interesting portions of an image for further processing and rapid response. Synthetic foveal imaging implements a parallel processing architecture that uses reprogrammable logic to implement embedded, distributed, real-time foveal image processing from different sensor types while simultaneously allowing for lossless storage and retrieval of raw image data. Real-time, distributed, adaptive processing of multi-tap image sensors with coordinated processing hardware used for each output tap is enabled. In mosaic focal planes, a parallel-processing network can be implemented that treats the mosaic focal plane as a single ensemble rather than a set of isolated sensors. Various applications are enabled for imaging and robotic vision where processing and responding to enormous amounts of data quickly and efficiently is important.

FPGA-based Fused Smart Sensor for Real-Time Plant-Transpiration Dynamic Estimation

PubMed Central

Millan-Almaraz, Jesus Roberto; de Jesus Romero-Troncoso, Rene; Guevara-Gonzalez, Ramon Gerardo; Contreras-Medina, Luis Miguel; Carrillo-Serrano, Roberto Valentin; Osornio-Rios, Roque Alfredo; Duarte-Galvan, Carlos; Rios-Alcaraz, Miguel Angel; Torres-Pacheco, Irineo

2010-01-01

Plant transpiration is considered one of the most important physiological functions because it constitutes the plants evolving adaptation to exchange moisture with a dry atmosphere which can dehydrate or eventually kill the plant. Due to the importance of transpiration, accurate measurement methods are required; therefore, a smart sensor that fuses five primary sensors is proposed which can measure air temperature, leaf temperature, air relative humidity, plant out relative humidity and ambient light. A field programmable gate array based unit is used to perform signal processing algorithms as average decimation and infinite impulse response filters to the primary sensor readings in order to reduce the signal noise and improve its quality. Once the primary sensor readings are filtered, transpiration dynamics such as: transpiration, stomatal conductance, leaf-air-temperature-difference and vapor pressure deficit are calculated in real time by the smart sensor. This permits the user to observe different primary and calculated measurements at the same time and the relationship between these which is very useful in precision agriculture in the detection of abnormal conditions. Finally, transpiration related stress conditions can be detected in real time because of the use of online processing and embedded communications capabilities. PMID:22163656

Real-time motion artifacts compensation of ToF sensors data on GPU

NASA Astrophysics Data System (ADS)

Lefloch, Damien; Hoegg, Thomas; Kolb, Andreas

2013-05-01

Over the last decade, ToF sensors attracted many computer vision and graphics researchers. Nevertheless, ToF devices suffer from severe motion artifacts for dynamic scenes as well as low-resolution depth data which strongly justifies the importance of a valid correction. To counterbalance this effect, a pre-processing approach is introduced to greatly improve range image data on dynamic scenes. We first demonstrate the robustness of our approach using simulated data to finally validate our method using sensor range data. Our GPU-based processing pipeline enhances range data reliability in real-time.

Electrochemical Aptamer-Based Sensors for Rapid Point-of-Use Monitoring of the Mycotoxin Ochratoxin A Directly in a Food Stream.

PubMed

Somerson, Jacob; Plaxco, Kevin W

2018-04-15

The ability to measure the concentration of specific small molecules continuously and in real-time in complex sample streams would impact many areas of agriculture, food safety, and food production. Monitoring for mycotoxin taint in real time during food processing, for example, could improve public health. Towards this end, we describe here an inexpensive electrochemical DNA-based sensor that supports real-time monitor of the mycotoxin ochratoxin A in a flowing stream of foodstuffs.

IoGET: Internet of Geophysical and Environmental Things

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

Mudunuru, Maruti Kumar

The objective of this project is to provide novel and fast reduced-order models for onboard computation at sensor nodes for real-time analysis. The approach will require that LANL perform high-fidelity numerical simulations, construct simple reduced-order models (ROMs) using machine learning and signal processing algorithms, and use real-time data analysis for ROMs and compressive sensing at sensor nodes.

A customizable system for real-time image processing using the Blackfin DSProcessor and the MicroC/OS-II real-time kernel

NASA Astrophysics Data System (ADS)

Coffey, Stephen; Connell, Joseph

2005-06-01

This paper presents a development platform for real-time image processing based on the ADSP-BF533 Blackfin processor and the MicroC/OS-II real-time operating system (RTOS). MicroC/OS-II is a completely portable, ROMable, pre-emptive, real-time kernel. The Blackfin Digital Signal Processors (DSPs), incorporating the Analog Devices/Intel Micro Signal Architecture (MSA), are a broad family of 16-bit fixed-point products with a dual Multiply Accumulate (MAC) core. In addition, they have a rich instruction set with variable instruction length and both DSP and MCU functionality thus making them ideal for media based applications. Using the MicroC/OS-II for task scheduling and management, the proposed system can capture and process raw RGB data from any standard 8-bit greyscale image sensor in soft real-time and then display the processed result using a simple PC graphical user interface (GUI). Additionally, the GUI allows configuration of the image capture rate and the system and core DSP clock rates thereby allowing connectivity to a selection of image sensors and memory devices. The GUI also allows selection from a set of image processing algorithms based in the embedded operating system.

ROADNET: A Real-time Data Aware System for Earth, Oceanographic, and Environmental Applications

NASA Astrophysics Data System (ADS)

Vernon, F.; Hansen, T.; Lindquist, K.; Ludascher, B.; Orcutt, J.; Rajasekar, A.

2003-12-01

The Real-time Observatories, Application, and Data management Network (ROADNet) Program aims to develop an integrated, seamless, and transparent environmental information network that will deliver geophysical, oceanographic, hydrological, ecological, and physical data to a variety of users in real-time. ROADNet is a multidisciplinary, multinational partnership of researchers, policymakers, natural resource managers, educators, and students who aim to use the data to advance our understanding and management of coastal, ocean, riparian, and terrestrial Earth systems in Southern California, Mexico, and well off shore. To date, project activity and funding have focused on the design and deployment of network linkages and on the exploratory development of the real-time data management system. We are currently adapting powerful "Data Grid" technologies to the unique challenges associated with the management and manipulation of real-time data. Current "Grid" projects deal with static data files, and significant technical innovation is required to address fundamental problems of real-time data processing, integration, and distribution. The technologies developed through this research will create a system that dynamically adapt downstream processing, cataloging, and data access interfaces when sensors are added or removed from the system; provide for real-time processing and monitoring of data streams--detecting events, and triggering computations, sensor and logger modifications, and other actions; integrate heterogeneous data from multiple (signal) domains; and provide for large-scale archival and querying of "consolidated" data. The software tools which must be developed do not exist, although limited prototype systems are available. This research has implications for the success of large-scale NSF initiatives in the Earth sciences (EarthScope), ocean sciences (OOI- Ocean Observatories Initiative), biological sciences (NEON - National Ecological Observatory Network) and civil engineering (NEES - Network for Earthquake Engineering Simulation). Each of these large scale initiatives aims to collect real-time data from thousands of sensors, and each will require new technologies to process, manage, and communicate real-time multidisciplinary environmental data on regional, national, and global scales.

All-IP-Ethernet architecture for real-time sensor-fusion processing

NASA Astrophysics Data System (ADS)

Hiraki, Kei; Inaba, Mary; Tezuka, Hiroshi; Tomari, Hisanobu; Koizumi, Kenichi; Kondo, Shuya

2016-03-01

Serendipter is a device that distinguishes and selects very rare particles and cells from huge amount of population. We are currently designing and constructing information processing system for a Serendipter. The information processing system for Serendipter is a kind of sensor-fusion system but with much more difficulties: To fulfill these requirements, we adopt All IP based architecture: All IP-Ethernet based data processing system consists of (1) sensor/detector directly output data as IP-Ethernet packet stream, (2) single Ethernet/TCP/IP streams by a L2 100Gbps Ethernet switch, (3) An FPGA board with 100Gbps Ethernet I/F connected to the switch and a Xeon based server. Circuits in the FPGA include 100Gbps Ethernet MAC, buffers and preprocessing, and real-time Deep learning circuits using multi-layer neural networks. Proposed All-IP architecture solves existing problem to construct large-scale sensor-fusion systems.

Research on an autonomous vision-guided helicopter

NASA Technical Reports Server (NTRS)

Amidi, Omead; Mesaki, Yuji; Kanade, Takeo

1994-01-01

Integration of computer vision with on-board sensors to autonomously fly helicopters was researched. The key components developed were custom designed vision processing hardware and an indoor testbed. The custom designed hardware provided flexible integration of on-board sensors with real-time image processing resulting in a significant improvement in vision-based state estimation. The indoor testbed provided convenient calibrated experimentation in constructing real autonomous systems.

CHIMERA II - A real-time multiprocessing environment for sensor-based robot control

NASA Technical Reports Server (NTRS)

Stewart, David B.; Schmitz, Donald E.; Khosla, Pradeep K.

1989-01-01

A multiprocessing environment for a wide variety of sensor-based robot system, providing the flexibility, performance, and UNIX-compatible interface needed for fast development of real-time code is addressed. The requirements imposed on the design of a programming environment for sensor-based robotic control is outlined. The details of the current hardware configuration are presented, along with the details of the CHIMERA II software. Emphasis is placed on the kernel, low-level interboard communication, user interface, extended file system, user-definable and dynamically selectable real-time schedulers, remote process synchronization, and generalized interprocess communication. A possible implementation of a hierarchical control model, the NASA/NBS standard reference model for telerobot control system is demonstrated.

Real-time Medical Emergency Response System: Exploiting IoT and Big Data for Public Health.

PubMed

Rathore, M Mazhar; Ahmad, Awais; Paul, Anand; Wan, Jiafu; Zhang, Daqiang

2016-12-01

Healthy people are important for any nation's development. Use of the Internet of Things (IoT)-based body area networks (BANs) is increasing for continuous monitoring and medical healthcare in order to perform real-time actions in case of emergencies. However, in the case of monitoring the health of all citizens or people in a country, the millions of sensors attached to human bodies generate massive volume of heterogeneous data, called "Big Data." Processing Big Data and performing real-time actions in critical situations is a challenging task. Therefore, in order to address such issues, we propose a Real-time Medical Emergency Response System that involves IoT-based medical sensors deployed on the human body. Moreover, the proposed system consists of the data analysis building, called "Intelligent Building," depicted by the proposed layered architecture and implementation model, and it is responsible for analysis and decision-making. The data collected from millions of body-attached sensors is forwarded to Intelligent Building for processing and for performing necessary actions using various units such as collection, Hadoop Processing (HPU), and analysis and decision. The feasibility and efficiency of the proposed system are evaluated by implementing the system on Hadoop using an UBUNTU 14.04 LTS coreTMi5 machine. Various medical sensory datasets and real-time network traffic are considered for evaluating the efficiency of the system. The results show that the proposed system has the capability of efficiently processing WBAN sensory data from millions of users in order to perform real-time responses in case of emergencies.

A wireless sensor network for urban traffic characterization and trend monitoring.

PubMed

Fernández-Lozano, J J; Martín-Guzmán, Miguel; Martín-Ávila, Juan; García-Cerezo, A

2015-10-15

Sustainable mobility requires a better management of the available infrastructure resources. To achieve this goal, it is necessary to obtain accurate data about road usage, in particular in urban areas. Although a variety of sensor alternates for urban traffic exist, they usually require extensive investments in the form of construction works for installation, processing means, etc. Wireless Sensor Networks (WSN) are an alternative to acquire urban traffic data, allowing for flexible, easy deployment. Together with the use of the appropriate sensors, like Bluetooth identification, and associate processing, WSN can provide the means to obtain in real time data like the origin-destination matrix, a key tool for trend monitoring which previously required weeks or months to be completed. This paper presents a system based on WSN designed to characterize urban traffic, particularly traffic trend monitoring through the calculation of the origin-destination matrix in real time by using Bluetooth identification. Additional sensors are also available integrated in different types of nodes. Experiments in real conditions have been performed, both for separate sensors (Bluetooth, ultrasound and laser), and for the whole system, showing the feasibility of this approach.

Real-time fluorescence quenching-based detection of nitro-containing explosive vapours: what are the key processes?

PubMed

Shaw, P E; Burn, P L

2017-11-15

The detection of explosives continues to be a pressing global challenge with many potential technologies being pursued by the scientific research community. Luminescence-based detection of explosive vapours with an organic semiconductor has attracted much interest because of its potential for detectors that have high sensitivity, compact form factor, simple operation and low-cost. Despite the abundance of literature on novel sensor materials systems there are relatively few mechanistic studies targeted towards vapour-based sensing. In this Perspective, we will review the progress that has been made in understanding the processes that control the real-time luminescence quenching of thin films by analyte vapours. These are the non-radiative quenching process by which the sensor exciton decays, the analyte-sensor intermolecular binding interaction, and the diffusion process for the analyte vapours in the film. We comment on the contributions of each of these processes towards the sensing response and, in particular, the relative roles of analyte diffusion and exciton diffusion. While the latter has been historically judged to be one of, if not the primary, causes for the high sensitivity of many conjugated polymers to nitrated vapours, recent evidence suggests that long exciton diffusion lengths are unnecessary. The implications of these results on the development of sensor materials for real-time detection are discussed.

Real-time assessment of surface interactions with titanium passivation layer by surface plasmon resonance

PubMed Central

Hirata, Isao; Yoshida, Yasuhiro; Nagaoka, Noriyuki; Hiasa, Kyou; Abe, Yasuhiko; Maekawa, Kenji; Kuboki, Takuo; Akagawa, Yasumasa; Suzuki, Kazuomi; Van Meerbeek, Bart; Messersmith, Phillip B.; Okazaki, Masayuki

2011-01-01

The high corrosion resistance and strength-to-density ratio makes titanium widely used in major industry, but also in a gamut of medical applications. Here we report for the first time on our development of a titanium passivation layer sensor that makes use of surface plasmon resonance (SPR). The deposited titanium metal layer on the sensor was passivated in air, like titanium medical devices. Our ‘Ti-SPR sensor’ enables analysis of biomolecules interactions with the passivated surface of titanium in real time. As a proof of concept, corrosion of titanium passivation layer exposed to acid was monitored in real time. Also, the Ti-SPR sensor can accurately measure the time-dependence of protein adsorption onto titanium passivation layer with a sub-nanogram per square millimeter accuracy. Besides such SPR analyses, an SPR-imaging (SPRI) enables real-time assessment of chemical surface processes that occur simultaneously at ‘multiple independent spots’ on the Ti-SPR sensor, such as acid-corrosion or adhesion of cells. Our Ti-SPR sensor will therefore be very useful to study titanium-corrosion phenomena and biomolecular titanium-surface interactions with application in a broad range of industrial and biomedical fields. PMID:22154862

System Developed for Real-Time Blade-Flutter Monitoring in the Wind Tunnel

NASA Technical Reports Server (NTRS)

Kurkov, Anatole P.; Dhadwal, Harbans S.; Radzikowski, mark; Strukov, Dmitri

2005-01-01

A real-time system has been developed to monitor flutter vibrations in turbomachinery. The system is designed for continuous processing of blade tip timing data at a rate of 10 MB/sec. A USB 2.0 interface provides uninterrupted real-time processing of the data, and the blade-tip arrival times are measured with a 50-MHz oscillator and a 24-bit pipelined architecture counter. The input stage includes a glitch catcher, which reduces the probability of detecting a ghost blade to negligible levels. A graphical user interface provides online interrogation of any blade tip from any light probe sensor. Alternatively, data from all blades and all sensors can be superimposed into a single composite scatter plot displaying the vibration amplitude of each blade.

FAWKES Information Management for Space Situational Awareness

NASA Astrophysics Data System (ADS)

Spetka, S.; Ramseyer, G.; Tucker, S.

2010-09-01

Current space situational awareness assets can be fully utilized by managing their inputs and outputs in real time. Ideally, sensors are tasked to perform specific functions to maximize their effectiveness. Many sensors are capable of collecting more data than is needed for a particular purpose, leading to the potential to enhance a sensor’s utilization by allowing it to be re-tasked in real time when it is determined that sufficient data has been acquired to meet the first task’s requirements. In addition, understanding a situation involving fast-traveling objects in space may require inputs from more than one sensor, leading to a need for information sharing in real time. Observations that are not processed in real time may be archived to support forensic analysis for accidents and for long-term studies. Space Situational Awareness (SSA) requires an extremely robust distributed software platform to appropriately manage the collection and distribution for both real-time decision-making as well as for analysis. FAWKES is being developed as a Joint Space Operations Center (JSPOC) Mission System (JMS) compliant implementation of the AFRL Phoenix information management architecture. It implements a pub/sub/archive/query (PSAQ) approach to communications designed for high performance applications. FAWKES provides an easy to use, reliable interface for structuring parallel processing, and is particularly well suited to the requirements of SSA. In addition to supporting point-to-point communications, it offers an elegant and robust implementation of collective communications, to scatter, gather and reduce values. A query capability is also supported that enhances reliability. Archived messages can be queried to re-create a computation or to selectively retrieve previous publications. PSAQ processes express their role in a computation by subscribing to their inputs and by publishing their results. Sensors on the edge can subscribe to inputs by appropriately authorized users, allowing dynamic tasking capabilities. Previously, the publication of sensor data collected by mobile systems was demonstrated. Thumbnails of infrared imagery that were imaged in real time by an aircraft [1] were published over a grid. This airborne system subscribed to requests for and then published the requested detailed images. In another experiment a system employing video subscriptions [2] drove the analysis of live video streams, resulting in a published stream of processed video output. We are currently implementing an SSA system that uses FAWKES to deliver imagery from telescopes through a pipeline of processing steps that are performed on high performance computers. PSAQ facilitates the decomposition of a problem into components that can be distributed across processing assets from the smallest sensors in space to the largest high performance computing (HPC) centers, as well as the integration and distribution of the results, all in real time. FAWKES supports the real-time latency requirements demanded by all of these applications. It also enhances reliability by easily supporting redundant computation. This study shows how FAWKES/PSAQ is utilized in SSA applications, and presents performance results for latency and throughput that meet these needs.

Utilization of biosensors and chemical sensors for space applications

NASA Technical Reports Server (NTRS)

Bonting, S. L.

1992-01-01

There will be a need for a wide array of chemical sensors for biomedical experimentation and for the monitoring of water and air recycling processes on Space Station Freedom. The infrequent logistics flights of the Space Shuttle will necessitate onboard analysis. The advantages of biosensors and chemical sensors over conventional analysis onboard spacecraft are manifold. They require less crew time, space, and power. Sample treatment is not needed. Real time or near-real time monitoring is possible, in some cases on a continuous basis. Sensor signals in digitized form can be transmitted to the ground. Types and requirements for chemical sensors to be used in biomedical experimentation and monitoring of water recycling during long-term space missions are discussed.

Real-time synchronized multiple-sensor IR/EO scene generation utilizing the SGI Onyx2

NASA Astrophysics Data System (ADS)

Makar, Robert J.; O'Toole, Brian E.

1998-07-01

An approach to utilize the symmetric multiprocessing environment of the Silicon Graphics Inc.R (SGI) Onyx2TM has been developed to support the generation of IR/EO scenes in real-time. This development, supported by the Naval Air Warfare Center Aircraft Division (NAWC/AD), focuses on high frame rate hardware-in-the-loop testing of multiple sensor avionics systems. In the past, real-time IR/EO scene generators have been developed as custom architectures that were often expensive and difficult to maintain. Previous COTS scene generation systems, designed and optimized for visual simulation, could not be adapted for accurate IR/EO sensor stimulation. The new Onyx2 connection mesh architecture made it possible to develop a more economical system while maintaining the fidelity needed to stimulate actual sensors. An SGI based Real-time IR/EO Scene Simulator (RISS) system was developed to utilize the Onyx2's fast multiprocessing hardware to perform real-time IR/EO scene radiance calculations. During real-time scene simulation, the multiprocessors are used to update polygon vertex locations and compute radiometrically accurate floating point radiance values. The output of this process can be utilized to drive a variety of scene rendering engines. Recent advancements in COTS graphics systems, such as the Silicon Graphics InfiniteRealityR make a total COTS solution possible for some classes of sensors. This paper will discuss the critical technologies that apply to infrared scene generation and hardware-in-the-loop testing using SGI compatible hardware. Specifically, the application of RISS high-fidelity real-time radiance algorithms on the SGI Onyx2's multiprocessing hardware will be discussed. Also, issues relating to external real-time control of multiple synchronized scene generation channels will be addressed.

Monitoring in situ in real time of resin infusion for thermoset composite structures

NASA Astrophysics Data System (ADS)

Faci, A.; Wang, P.; Cochrane, C.; Koncar, V.

2017-10-01

The presented work investigates changes in electrical resistance of embedded sensory yarns as a method to monitor the resin flow front position and curing degree of resin during manufacturing of composite structures by vacuum infusion technology. The sensor concept is based on Piezo-resistive sensors integrated to the flax fabric, having almost identical propriety and dimensions as the flax threads used for the production of reinforcements. In the first time sensors have been characterized and first measures of the resin infusion have been realized in order to demonstrate the feasibility of the proposed approach. Then, the measures in real time were realized with fibrous sensors added to the flax fabric (green composites) to monitor the flow front of resin. A large amount of data recorded, filtered, examined, analysed and processed in order to understand and to optimize the infusion and polymerization process.

Advanced detection, isolation, and accommodation of sensor failures in turbofan engines: Real-time microcomputer implementation

NASA Technical Reports Server (NTRS)

Delaat, John C.; Merrill, Walter C.

1990-01-01

The objective of the Advanced Detection, Isolation, and Accommodation Program is to improve the overall demonstrated reliability of digital electronic control systems for turbine engines. For this purpose, an algorithm was developed which detects, isolates, and accommodates sensor failures by using analytical redundancy. The performance of this algorithm was evaluated on a real time engine simulation and was demonstrated on a full scale F100 turbofan engine. The real time implementation of the algorithm is described. The implementation used state-of-the-art microprocessor hardware and software, including parallel processing and high order language programming.

Real-time object tracking based on scale-invariant features employing bio-inspired hardware.

PubMed

Yasukawa, Shinsuke; Okuno, Hirotsugu; Ishii, Kazuo; Yagi, Tetsuya

2016-09-01

We developed a vision sensor system that performs a scale-invariant feature transform (SIFT) in real time. To apply the SIFT algorithm efficiently, we focus on a two-fold process performed by the visual system: whole-image parallel filtering and frequency-band parallel processing. The vision sensor system comprises an active pixel sensor, a metal-oxide semiconductor (MOS)-based resistive network, a field-programmable gate array (FPGA), and a digital computer. We employed the MOS-based resistive network for instantaneous spatial filtering and a configurable filter size. The FPGA is used to pipeline process the frequency-band signals. The proposed system was evaluated by tracking the feature points detected on an object in a video. Copyright © 2016 Elsevier Ltd. All rights reserved.

Real-Time and In-Flow Sensing Using a High Sensitivity Porous Silicon Microcavity-Based Sensor.

PubMed

Caroselli, Raffaele; Martín Sánchez, David; Ponce Alcántara, Salvador; Prats Quilez, Francisco; Torrijos Morán, Luis; García-Rupérez, Jaime

2017-12-05

Porous silicon seems to be an appropriate material platform for the development of high-sensitivity and low-cost optical sensors, as their porous nature increases the interaction with the target substances, and their fabrication process is very simple and inexpensive. In this paper, we present the experimental development of a porous silicon microcavity sensor and its use for real-time in-flow sensing application. A high-sensitivity configuration was designed and then fabricated, by electrochemically etching a silicon wafer. Refractive index sensing experiments were realized by flowing several dilutions with decreasing refractive indices, and measuring the spectral shift in real-time. The porous silicon microcavity sensor showed a very linear response over a wide refractive index range, with a sensitivity around 1000 nm/refractive index unit (RIU), which allowed us to directly detect refractive index variations in the 10 -7 RIU range.

A Wireless Sensor Network for Urban Traffic Characterization and Trend Monitoring

PubMed Central

Fernández-Lozano, J.J.; Martín-Guzmán, Miguel; Martín-Ávila, Juan; García-Cerezo, A.

2015-01-01

Sustainable mobility requires a better management of the available infrastructure resources. To achieve this goal, it is necessary to obtain accurate data about road usage, in particular in urban areas. Although a variety of sensor alternates for urban traffic exist, they usually require extensive investments in the form of construction works for installation, processing means, etc. Wireless Sensor Networks (WSN) are an alternative to acquire urban traffic data, allowing for flexible, easy deployment. Together with the use of the appropriate sensors, like Bluetooth identification, and associate processing, WSN can provide the means to obtain in real time data like the origin-destination matrix, a key tool for trend monitoring which previously required weeks or months to be completed. This paper presents a system based on WSN designed to characterize urban traffic, particularly traffic trend monitoring through the calculation of the origin-destination matrix in real time by using Bluetooth identification. Additional sensors are also available integrated in different types of nodes. Experiments in real conditions have been performed, both for separate sensors (Bluetooth, ultrasound and laser), and for the whole system, showing the feasibility of this approach. PMID:26501278

Sensor-based atomic layer deposition for rapid process learning and enhanced manufacturability

NASA Astrophysics Data System (ADS)

Lei, Wei

In the search for sensor based atomic layer deposition (ALD) process to accelerate process learning and enhance manufacturability, we have explored new reactor designs and applied in-situ process sensing to W and HfO 2 ALD processes. A novel wafer scale ALD reactor, which features fast gas switching, good process sensing compatibility and significant similarity to the real manufacturing environment, is constructed. The reactor has a unique movable reactor cap design that allows two possible operation modes: (1) steady-state flow with alternating gas species; or (2) fill-and-pump-out cycling of each gas, accelerating the pump-out by lifting the cap to employ the large chamber volume as ballast. Downstream quadrupole mass spectrometry (QMS) sampling is applied for in-situ process sensing of tungsten ALD process. The QMS reveals essential surface reaction dynamics through real-time signals associated with byproduct generation as well as precursor introduction and depletion for each ALD half cycle, which are then used for process learning and optimization. More subtle interactions such as imperfect surface saturation and reactant dose interaction are also directly observed by QMS, indicating that ALD process is more complicated than the suggested layer-by-layer growth. By integrating in real-time the byproduct QMS signals over each exposure and plotting it against process cycle number, the deposition kinetics on the wafer is directly measured. For continuous ALD runs, the total integrated byproduct QMS signal in each ALD run is also linear to ALD film thickness, and therefore can be used for ALD film thickness metrology. The in-situ process sensing is also applied to HfO2 ALD process that is carried out in a furnace type ALD reactor. Precursor dose end-point control is applied to precisely control the precursor dose in each half cycle. Multiple process sensors, including quartz crystal microbalance (QCM) and QMS are used to provide real time process information. The sensing results confirm the proposed surface reaction path and once again reveal the complexity of ALD processes. The impact of this work includes: (1) It explores new ALD reactor designs which enable the implementation of in-situ process sensors for rapid process learning and enhanced manufacturability; (2) It demonstrates in the first time that in-situ QMS can reveal detailed process dynamics and film growth kinetics in wafer-scale ALD process, and thus can be used for ALD film thickness metrology. (3) Based on results from two different processes carried out in two different reactors, it is clear that ALD is a more complicated process than normally believed or advertised, but real-time observation of the operational chemistries in ALD by in-situ sensors provides critical insight to the process and the basis for more effective process control for ALD applications.

Near real-time, on-the-move software PED using VPEF

NASA Astrophysics Data System (ADS)

Green, Kevin; Geyer, Chris; Burnette, Chris; Agarwal, Sanjeev; Swett, Bruce; Phan, Chung; Deterline, Diane

2015-05-01

The scope of the Micro-Cloud for Operational, Vehicle-Based EO-IR Reconnaissance System (MOVERS) development effort, managed by the Night Vision and Electronic Sensors Directorate (NVESD), is to develop, integrate, and demonstrate new sensor technologies and algorithms that improve improvised device/mine detection using efficient and effective exploitation and fusion of sensor data and target cues from existing and future Route Clearance Package (RCP) sensor systems. Unfortunately, the majority of forward looking Full Motion Video (FMV) and computer vision processing, exploitation, and dissemination (PED) algorithms are often developed using proprietary, incompatible software. This makes the insertion of new algorithms difficult due to the lack of standardized processing chains. In order to overcome these limitations, EOIR developed the Government off-the-shelf (GOTS) Video Processing and Exploitation Framework (VPEF) to be able to provide standardized interfaces (e.g., input/output video formats, sensor metadata, and detected objects) for exploitation software and to rapidly integrate and test computer vision algorithms. EOIR developed a vehicle-based computing framework within the MOVERS and integrated it with VPEF. VPEF was further enhanced for automated processing, detection, and publishing of detections in near real-time, thus improving the efficiency and effectiveness of RCP sensor systems.

Variable self-powered light detection CMOS chip with real-time adaptive tracking digital output based on a novel on-chip sensor.

PubMed

Wang, HongYi; Fan, Youyou; Lu, Zhijian; Luo, Tao; Fu, Houqiang; Song, Hongjiang; Zhao, Yuji; Christen, Jennifer Blain

2017-10-02

This paper provides a solution for a self-powered light direction detection with digitized output. Light direction sensors, energy harvesting photodiodes, real-time adaptive tracking digital output unit and other necessary circuits are integrated on a single chip based on a standard 0.18 µm CMOS process. Light direction sensors proposed have an accuracy of 1.8 degree over a 120 degree range. In order to improve the accuracy, a compensation circuit is presented for photodiodes' forward currents. The actual measurement precision of output is approximately 7 ENOB. Besides that, an adaptive under voltage protection circuit is designed for variable supply power which may undulate with temperature and process.

Real-Time Reconnaissance-A Systems Look At Advanced Technology

NASA Astrophysics Data System (ADS)

Lapp, Henry

1981-12-01

An important role for reconnaissance is the location and identification of targets in real time. Current technology has been compartmented into sensors, automatic target recognizers, data links, ground exploitation and finally dissemination. In the days of bring home film recce, this segmentation of functions was appropriate. With the current emphasis on real time decision making from outputs of high resolution sensors this thinking has to be re-analyzed. A total systems approach to data management must be employed using the constraints imposed by technology as well as the atmosphere, survivable flight profiles, and the human workload. This paper will analyze the target acquisition through exploitation tasks and discuss the current advanced development technology that are applicable. A philosophy of processing data to get information as early as possible in the data handling chain is examined in the context of ground exploitation and dissemination needs. Examples of how the various real time sensors (screeners and processors), jam resistant data links and near real time ground data handling systems fit into this scenario are discussed. Specific DoD programs will be used to illustrate the credibility of this integrated approach.

A Sensor System for Detection of Hull Surface Defects

PubMed Central

Navarro, Pedro; Iborra, Andrés; Fernández, Carlos; Sánchez, Pedro; Suardíaz, Juan

2010-01-01

This paper presents a sensor system for detecting defects in ship hull surfaces. The sensor was developed to enable a robotic system to perform grit blasting operations on ship hulls. To achieve this, the proposed sensor system captures images with the help of a camera and processes them in real time using a new defect detection method based on thresholding techniques. What makes this method different is its efficiency in the automatic detection of defects from images recorded in variable lighting conditions. The sensor system was tested under real conditions at a Spanish shipyard, with excellent results. PMID:22163590

Optimization of the HyPer sensor for robust real-time detection of hydrogen peroxide in the rice blast fungus.

PubMed

Huang, Kun; Caplan, Jeff; Sweigard, James A; Czymmek, Kirk J; Donofrio, Nicole M

2017-02-01

Reactive oxygen species (ROS) production and breakdown have been studied in detail in plant-pathogenic fungi, including the rice blast fungus, Magnaporthe oryzae; however, the examination of the dynamic process of ROS production in real time has proven to be challenging. We resynthesized an existing ROS sensor, called HyPer, to exhibit optimized codon bias for fungi, specifically Neurospora crassa, and used a combination of microscopy and plate reader assays to determine whether this construct could detect changes in fungal ROS during the plant infection process. Using confocal microscopy, we were able to visualize fluctuating ROS levels during the formation of an appressorium on an artificial hydrophobic surface, as well as during infection on host leaves. Using the plate reader, we were able to ascertain measurements of hydrogen peroxide (H 2 O 2 ) levels in conidia as detected by the MoHyPer sensor. Overall, by the optimization of codon usage for N. crassa and related fungal genomes, the MoHyPer sensor can be used as a robust, dynamic and powerful tool to both monitor and quantify H 2 O 2 dynamics in real time during important stages of the plant infection process. © 2016 BSPP AND JOHN WILEY & SONS LTD.

Assimilation of Real-Time Satellite And Human Sensor Networks for Modeling Natural Disasters

NASA Astrophysics Data System (ADS)

Aulov, O.; Halem, M.; Lary, D. J.

2011-12-01

We describe the development of underlying technologies needed to address the merging of a web of real time satellite sensor Web (SSW) and Human Sensor Web (HSW) needed to augment the US response to extreme events. As an initial prototyping step and use case scenario, we consider the development of two major system tools that can be transitioned from research to the responding operational agency for mitigating coastal oil spills. These tools consist of the capture of Situation Aware (SA) Social Media (SM) Data, and assimilation of the processed information into forecasting models to provide incident decision managers with interactive virtual spatial temporal animations superimposed with probabilistic data estimates. The system methodologies are equally applicable to the wider class of extreme events such as plume dispersions from volcanoes or massive fires, major floods, hurricane impacts, radioactive isotope dispersions from nuclear accidents, etc. A successful feasibility demonstration of this technology has been shown in the case of the Deepwater Horizon Oil Spill where Human Sensor Networks have been combined with a geophysical model to perform parameter assessments. Flickr images of beached oil were mined from the spill area, geolocated and timestamped and converted into geophysical data. This data was incorporated into General NOAA Operational Modeling Environment (GNOME), a Lagrangian forecast model that uses near real-time surface winds, ocean currents, and satellite shape profiles of oil to generate a forecast of plume movement. As a result, improved estimates of diffusive coefficients and rates of oil spill were determined. Current approaches for providing satellite derived oil distributions are collected from a satellite sensor web of operational and research sensors from many countries, and a manual analysis is performed by NESDIS. A real time SA HSW processing system based on geolocated SM data from sources such as Twitter, Flickr, YouTube etc., greatly supplements the current operational practice of sending out teams of humans to gather samples of tarballs reaching coastal locations. We show that ensemble Kalman filter assimilation of the combination of SM data with model forecast background data fields can minimize the false positive cases of satellite observations alone. Our future framework consists of two parts, a real time SA HSW processing system and an on-demand SSW processing system. HSW processing system uses a geolocated SM data to provide observations of coastal oil contact. SSW system is composed of selected instruments from NASA EOS, NPP and available Decadal Survey mission satellites along with other in situ data to form a real time regional oil spill observing system. We will automate the NESDIS manual process of providing oil spill maps by using Self Organizing Feature Map (SOFM) algorithm. We use the LETKF scheme for assimilating the satellite sensor web and HSW observations into the GNOME model to reduce the uncertainty of the observations. We intend to infuse these developments in an SOA implementation for execution of event driven model forecast assimilation cycles in a dedicated HPC cloud.

Fugitive Methane Gas Emission Monitoring in oil and gas industry

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

Klein, Levente

Identifying fugitive methane leaks allow optimization of the extraction process, can extend gas extraction equipment lifetime, and eliminate hazardous work conditions. We demonstrate a wireless sensor network based on cost effective and robust chemi-resistive methane sensors combined with real time analytics to identify leaks from 2 scfh to 10000 scfh. The chemi-resistive sensors were validated for sensitivity better than 1 ppm of methane plume detection. The real time chemical sensor and wind data is integrated into an inversion models to identify the location and the magnitude of the methane leak. This integrated solution can be deployed in outdoor environment formore » long term monitoring of chemical plumes.« less

High Resolution Near Real Time Image Processing and Support for MSSS Modernization

NASA Astrophysics Data System (ADS)

Duncan, R. B.; Sabol, C.; Borelli, K.; Spetka, S.; Addison, J.; Mallo, A.; Farnsworth, B.; Viloria, R.

2012-09-01

This paper describes image enhancement software applications engineering development work that has been performed in support of Maui Space Surveillance System (MSSS) Modernization. It also includes R&D and transition activity that has been performed over the past few years with the objective of providing increased space situational awareness (SSA) capabilities. This includes Air Force Research Laboratory (AFRL) use of an FY10 Dedicated High Performance Investment (DHPI) cluster award -- and our selection and planned use for an FY12 DHPI award. We provide an introduction to image processing of electro optical (EO) telescope sensors data; and a high resolution image enhancement and near real time processing and summary status overview. We then describe recent image enhancement applications development and support for MSSS Modernization, results to date, and end with a discussion of desired future development work and conclusions. Significant improvements to image processing enhancement have been realized over the past several years, including a key application that has realized more than a 10,000-times speedup compared to the original R&D code -- and a greater than 72-times speedup over the past few years. The latest version of this code maintains software efficiency for post-mission processing while providing optimization for image processing of data from a new EO sensor at MSSS. Additional work has also been performed to develop low latency, near real time processing of data that is collected by the ground-based sensor during overhead passes of space objects.

Digital seismo-acoustic signal processing aboard a wireless sensor platform

NASA Astrophysics Data System (ADS)

Marcillo, O.; Johnson, J. B.; Lorincz, K.; Werner-Allen, G.; Welsh, M.

2006-12-01

We are developing a low power, low-cost wireless sensor array to conduct real-time signal processing of earthquakes at active volcanoes. The sensor array, which integrates data from both seismic and acoustic sensors, is based on Moteiv TMote Sky wireless sensor nodes (www.moteiv.com). The nodes feature a Texas Instruments MSP430 microcontroller, 48 Kbytes of program memory, 10 Kbytes of static RAM, 1 Mbyte of external flash memory, and a 2.4-GHz Chipcon CC2420 IEEE 802.15.4 radio. The TMote Sky is programmed in TinyOS. Basic signal processing occurs on an array of three peripheral sensor nodes. These nodes are tied into a dedicated GPS receiver node, which is focused on time synchronization, and a central communications node, which handles data integration and additional processing. The sensor nodes incorporate dual 12-bit digitizers sampling a seismic sensor and a pressure transducer at 100 samples per second. The wireless capabilities of the system allow flexible array geometry, with a maximum aperture of 200m. We have already developed the digital signal processing routines on board the Moteiv Tmote sensor nodes. The developed routines accomplish Real-time Seismic-Amplitude Measurement (RSAM), Seismic Spectral- Amplitude Measurement (SSAM), and a user-configured Short Term Averaging / Long Term Averaging (STA LTA ratio), which is used to calculate first arrivals. The processed data from individual nodes are transmitted back to a central node, where additional processing may be performed. Such processing will include back azimuth determination and other wave field analyses. Future on-board signal processing will focus on event characterization utilizing pattern recognition and spectral characterization. The processed data is intended as low bandwidth information which can be transmitted periodically and at low cost through satellite telemetry to a web server. The processing is limited by the computational capabilities (RAM, ROM) of the nodes. Nevertheless, we envision this product to be a useful tool for assessing the state of unrest at remote volcanoes.

Embedding piezoresistive pressure sensors to obtain online pressure profiles inside fiber composite laminates.

PubMed

Moghaddam, Maryam Kahali; Breede, Arne; Brauner, Christian; Lang, Walter

2015-03-27

The production of large and complex parts using fiber composite materials is costly due to the frequent formation of voids, porosity and waste products. By embedding different types of sensors and monitoring the process in real time, the amount of wastage can be significantly reduced. This work focuses on developing a knowledge-based method to improve and ensure complete impregnation of the fibers before initiation of the resin cure. Piezoresistive and capacitive pressure sensors were embedded in fiber composite laminates to measure the real-time the pressure values inside the laminate. A change of pressure indicates resin infusion. The sensors were placed in the laminate and the resin was infused by vacuum. The embedded piezoresistive pressure sensors were able to track the vacuum pressure in the fiber composite laminate setup, as well as the arrival of the resin at the sensor. The pressure increase due to closing the resin inlet was also measured. In contrast, the capacitive type of sensor was found to be inappropriate for measuring these quantities. The following study demonstrates real-time monitoring of pressure changes inside the fiber composite laminate, which validate the use of Darcy's law in porous media to control the resin flow during infusion.

Miniaturized and Wireless Optical Neurotransmitter Sensor for Real-Time Monitoring of Dopamine in the Brain

PubMed Central

Kim, Min H.; Yoon, Hargsoon; Choi, Sang H.; Zhao, Fei; Kim, Jongsung; Song, Kyo D.; Lee, Uhn

2016-01-01

Real-time monitoring of extracellular neurotransmitter concentration offers great benefits for diagnosis and treatment of neurological disorders and diseases. This paper presents the study design and results of a miniaturized and wireless optical neurotransmitter sensor (MWONS) for real-time monitoring of brain dopamine concentration. MWONS is based on fluorescent sensing principles and comprises a microspectrometer unit, a microcontroller for data acquisition, and a Bluetooth wireless network for real-time monitoring. MWONS has a custom-designed application software that controls the operation parameters for excitation light sources, data acquisition, and signal processing. MWONS successfully demonstrated a measurement capability with a limit of detection down to a 100 nanomole dopamine concentration, and high selectivity to ascorbic acid (90:1) and uric acid (36:1). PMID:27834927

Miniaturized and Wireless Optical Neurotransmitter Sensor for Real-Time Monitoring of Dopamine in the Brain.

PubMed

Kim, Min H; Yoon, Hargsoon; Choi, Sang H; Zhao, Fei; Kim, Jongsung; Song, Kyo D; Lee, Uhn

2016-11-10

Real-time monitoring of extracellular neurotransmitter concentration offers great benefits for diagnosis and treatment of neurological disorders and diseases. This paper presents the study design and results of a miniaturized and wireless optical neurotransmitter sensor (MWONS) for real-time monitoring of brain dopamine concentration. MWONS is based on fluorescent sensing principles and comprises a microspectrometer unit, a microcontroller for data acquisition, and a Bluetooth wireless network for real-time monitoring. MWONS has a custom-designed application software that controls the operation parameters for excitation light sources, data acquisition, and signal processing. MWONS successfully demonstrated a measurement capability with a limit of detection down to a 100 nanomole dopamine concentration, and high selectivity to ascorbic acid (90:1) and uric acid (36:1).

Real-time improvement of continuous glucose monitoring accuracy: the smart sensor concept.

PubMed

Facchinetti, Andrea; Sparacino, Giovanni; Guerra, Stefania; Luijf, Yoeri M; DeVries, J Hans; Mader, Julia K; Ellmerer, Martin; Benesch, Carsten; Heinemann, Lutz; Bruttomesso, Daniela; Avogaro, Angelo; Cobelli, Claudio

2013-04-01

Reliability of continuous glucose monitoring (CGM) sensors is key in several applications. In this work we demonstrate that real-time algorithms can render CGM sensors smarter by reducing their uncertainty and inaccuracy and improving their ability to alert for hypo- and hyperglycemic events. The smart CGM (sCGM) sensor concept consists of a commercial CGM sensor whose output enters three software modules, able to work in real time, for denoising, enhancement, and prediction. These three software modules were recently presented in the CGM literature, and here we apply them to the Dexcom SEVEN Plus continuous glucose monitor. We assessed the performance of the sCGM on data collected in two trials, each containing 12 patients with type 1 diabetes. The denoising module improves the smoothness of the CGM time series by an average of ∼57%, the enhancement module reduces the mean absolute relative difference from 15.1 to 10.3%, increases by 12.6% the pairs of values falling in the A-zone of the Clarke error grid, and finally, the prediction module forecasts hypo- and hyperglycemic events an average of 14 min ahead of time. We have introduced and implemented the sCGM sensor concept. Analysis of data from 24 patients demonstrates that incorporation of suitable real-time signal processing algorithms for denoising, enhancement, and prediction can significantly improve the performance of CGM applications. This can be of great clinical impact for hypo- and hyperglycemic alert generation as well in artificial pancreas devices.

Real-time GIS data model and sensor web service platform for environmental data management.

PubMed

Gong, Jianya; Geng, Jing; Chen, Zeqiang

2015-01-09

Effective environmental data management is meaningful for human health. In the past, environmental data management involved developing a specific environmental data management system, but this method often lacks real-time data retrieving and sharing/interoperating capability. With the development of information technology, a Geospatial Service Web method is proposed that can be employed for environmental data management. The purpose of this study is to determine a method to realize environmental data management under the Geospatial Service Web framework. A real-time GIS (Geographic Information System) data model and a Sensor Web service platform to realize environmental data management under the Geospatial Service Web framework are proposed in this study. The real-time GIS data model manages real-time data. The Sensor Web service platform is applied to support the realization of the real-time GIS data model based on the Sensor Web technologies. To support the realization of the proposed real-time GIS data model, a Sensor Web service platform is implemented. Real-time environmental data, such as meteorological data, air quality data, soil moisture data, soil temperature data, and landslide data, are managed in the Sensor Web service platform. In addition, two use cases of real-time air quality monitoring and real-time soil moisture monitoring based on the real-time GIS data model in the Sensor Web service platform are realized and demonstrated. The total time efficiency of the two experiments is 3.7 s and 9.2 s. The experimental results show that the method integrating real-time GIS data model and Sensor Web Service Platform is an effective way to manage environmental data under the Geospatial Service Web framework.

Architecture For The Optimization Of A Machining Process In Real Time Through Rule-Based Expert System

NASA Astrophysics Data System (ADS)

Serrano, Rafael; González, Luis Carlos; Martín, Francisco Jesús

2009-11-01

Under the project SENSOR-IA which has had financial funding from the Order of Incentives to the Regional Technology Centers of the Counsil of Innovation, Science and Enterprise of Andalusia, an architecture for the optimization of a machining process in real time through rule-based expert system has been developed. The architecture consists of an acquisition system and sensor data processing engine (SATD) from an expert system (SE) rule-based which communicates with the SATD. The SE has been designed as an inference engine with an algorithm for effective action, using a modus ponens rule model of goal-oriented rules.The pilot test demonstrated that it is possible to govern in real time the machining process based on rules contained in a SE. The tests have been done with approximated rules. Future work includes an exhaustive collection of data with different tool materials and geometries in a database to extract more precise rules.

Real-time synchronization of wireless sensor network by 1-PPS signal

NASA Astrophysics Data System (ADS)

Giammarini, Marco; Pieralisi, Marco; Isidori, Daniela; Concettoni, Enrico; Cristalli, Cristina; Fioravanti, Matteo

2015-05-01

The use of wireless sensor networks with different nodes is desirable in a smart environment, because the network setting up and installation on preexisting structures can be done without a fixed cabled infrastructure. The flexibility of the monitoring system is fundamental where the use of a considerable quantity of cables could compromise the normal exercise, could affect the quality of acquired signal and finally increase the cost of the materials and installation. The network is composed of several intelligent "nodes", which acquires data from different kind of sensors, and then store or transmit them to a central elaboration unit. The synchronization of data acquisition is the core of the real-time wireless sensor network (WSN). In this paper, we present a comparison between different methods proposed by literature for the real-time acquisition in a WSN and finally we present our solution based on 1-Pulse-Per-Second (1-PPS) signal generated by GPS systems. The sensor node developed is a small-embedded system based on ARM microcontroller that manages the acquisition, the timing and the post-processing of the data. The communications between the sensors and the master based on IEEE 802.15.4 protocol and managed by dedicated software. Finally, we present the preliminary results obtained on a 3 floor building simulator with the wireless sensors system developed.

Real-Time Earthquake Intensity Estimation Using Streaming Data Analysis of Social and Physical Sensors

NASA Astrophysics Data System (ADS)

Kropivnitskaya, Yelena; Tiampo, Kristy F.; Qin, Jinhui; Bauer, Michael A.

2017-06-01

Earthquake intensity is one of the key components of the decision-making process for disaster response and emergency services. Accurate and rapid intensity calculations can help to reduce total loss and the number of casualties after an earthquake. Modern intensity assessment procedures handle a variety of information sources, which can be divided into two main categories. The first type of data is that derived from physical sensors, such as seismographs and accelerometers, while the second type consists of data obtained from social sensors, such as witness observations of the consequences of the earthquake itself. Estimation approaches using additional data sources or that combine sources from both data types tend to increase intensity uncertainty due to human factors and inadequate procedures for temporal and spatial estimation, resulting in precision errors in both time and space. Here we present a processing approach for the real-time analysis of streams of data from both source types. The physical sensor data is acquired from the U.S. Geological Survey (USGS) seismic network in California and the social sensor data is based on Twitter user observations. First, empirical relationships between tweet rate and observed Modified Mercalli Intensity (MMI) are developed using data from the M6.0 South Napa, CAF earthquake that occurred on August 24, 2014. Second, the streams of both data types are analyzed together in simulated real-time to produce one intensity map. The second implementation is based on IBM InfoSphere Streams, a cloud platform for real-time analytics of big data. To handle large processing workloads for data from various sources, it is deployed and run on a cloud-based cluster of virtual machines. We compare the quality and evolution of intensity maps from different data sources over 10-min time intervals immediately following the earthquake. Results from the joint analysis shows that it provides more complete coverage, with better accuracy and higher resolution over a larger area than either data source alone.

In-line monitoring of granule moisture in fluidized-bed dryers using microwave resonance technology.

PubMed

Buschmüller, Caroline; Wiedey, Wolfgang; Döscher, Claas; Dressler, Jochen; Breitkreutz, Jörg

2008-05-01

This is the first report on in-line moisture measurement of pharmaceutical products by microwave resonance technology. In order to meet the FDA's PAT approach, a microwave resonance sensor appropriate for pharmaceutical use was developed and implemented into two different fluidized-bed dryers. The novel sensor enables a continuous moisture measurement independent from the product density. Hence, for the first time precise real time determination of the moisture in pharmaceutical granules becomes possible. The qualification of the newly developed sensor was performed by drying placebo granules under experimental conditions and the validation using drug loaded granules under real process conditions. The results of the investigations show good correlations between water content of the granules determined by the microwave resonance sensor and both reference methods, loss on drying by infrared light exposure and Karl Fischer titration. Furthermore, a considerable time saving in the drying process was achieved through monitoring the residual water content continuously by microwave resonance technology instead of the formerly used discontinuous methods.

A generic FPGA-based detector readout and real-time image processing board

NASA Astrophysics Data System (ADS)

Sarpotdar, Mayuresh; Mathew, Joice; Safonova, Margarita; Murthy, Jayant

2016-07-01

For space-based astronomical observations, it is important to have a mechanism to capture the digital output from the standard detector for further on-board analysis and storage. We have developed a generic (application- wise) field-programmable gate array (FPGA) board to interface with an image sensor, a method to generate the clocks required to read the image data from the sensor, and a real-time image processor system (on-chip) which can be used for various image processing tasks. The FPGA board is applied as the image processor board in the Lunar Ultraviolet Cosmic Imager (LUCI) and a star sensor (StarSense) - instruments developed by our group. In this paper, we discuss the various design considerations for this board and its applications in the future balloon and possible space flights.

Minimizing Input-to-Output Latency in Virtual Environment

NASA Technical Reports Server (NTRS)

Adelstein, Bernard D.; Ellis, Stephen R.; Hill, Michael I.

2009-01-01

A method and apparatus were developed to minimize latency (time delay ) in virtual environment (VE) and other discrete- time computer-base d systems that require real-time display in response to sensor input s. Latency in such systems is due to the sum of the finite time requi red for information processing and communication within and between sensors, software, and displays.

Optical sensor for real-time weld defect detection

NASA Astrophysics Data System (ADS)

Ancona, Antonio; Maggipinto, Tommaso; Spagnolo, Vincenzo; Ferrara, Michele; Lugara, Pietro M.

2002-04-01

In this work we present an innovative optical sensor for on- line and non-intrusive welding process monitoring. It is based on the spectroscopic analysis of the optical VIS emission of the welding plasma plume generated in the laser- metal interaction zone. Plasma electron temperature has been measured for different chemical species composing the plume. Temperature signal evolution has been recorded and analyzed during several CO2-laser welding processes, under variable operating conditions. We have developed a suitable software able to real time detect a wide range of weld defects like crater formation, lack of fusion, excessive penetration, seam oxidation. The same spectroscopic approach has been applied for electric arc welding process monitoring. We assembled our optical sensor in a torch for manual Gas Tungsten Arc Welding procedures and tested the prototype in a manufacturing industry production line. Even in this case we found a clear correlation between the signal behavior and the welded joint quality.

Real-time DNA Amplification and Detection System Based on a CMOS Image Sensor.

PubMed

Wang, Tiantian; Devadhasan, Jasmine Pramila; Lee, Do Young; Kim, Sanghyo

2016-01-01

In the present study, we developed a polypropylene well-integrated complementary metal oxide semiconductor (CMOS) platform to perform the loop mediated isothermal amplification (LAMP) technique for real-time DNA amplification and detection simultaneously. An amplification-coupled detection system directly measures the photon number changes based on the generation of magnesium pyrophosphate and color changes. The photon number decreases during the amplification process. The CMOS image sensor observes the photons and converts into digital units with the aid of an analog-to-digital converter (ADC). In addition, UV-spectral studies, optical color intensity detection, pH analysis, and electrophoresis detection were carried out to prove the efficiency of the CMOS sensor based the LAMP system. Moreover, Clostridium perfringens was utilized as proof-of-concept detection for the new system. We anticipate that this CMOS image sensor-based LAMP method will enable the creation of cost-effective, label-free, optical, real-time and portable molecular diagnostic devices.

A Real-Time Thermal Self-Elimination Method for Static Mode Operated Freestanding Piezoresistive Microcantilever-Based Biosensors.

PubMed

Ku, Yu-Fu; Huang, Long-Sun; Yen, Yi-Kuang

2018-02-28

Here, we provide a method and apparatus for real-time compensation of the thermal effect of single free-standing piezoresistive microcantilever-based biosensors. The sensor chip contained an on-chip fixed piezoresistor that served as a temperature sensor, and a multilayer microcantilever with an embedded piezoresistor served as a biomolecular sensor. This method employed the calibrated relationship between the resistance and the temperature of piezoresistors to eliminate the thermal effect on the sensor, including the temperature coefficient of resistance (TCR) and bimorph effect. From experimental results, the method was verified to reduce the signal of thermal effect from 25.6 μV/°C to 0.3 μV/°C, which was approximately two orders of magnitude less than that before the processing of the thermal elimination method. Furthermore, the proposed approach and system successfully demonstrated its effective real-time thermal self-elimination on biomolecular detection without any thermostat device to control the environmental temperature. This method realizes the miniaturization of an overall measurement system of the sensor, which can be used to develop portable medical devices and microarray analysis platforms.

Real-time image processing for non-contact monitoring of dynamic displacements using smartphone technologies

NASA Astrophysics Data System (ADS)

Min, Jae-Hong; Gelo, Nikolas J.; Jo, Hongki

2016-04-01

The newly developed smartphone application, named RINO, in this study allows measuring absolute dynamic displacements and processing them in real time using state-of-the-art smartphone technologies, such as high-performance graphics processing unit (GPU), in addition to already powerful CPU and memories, embedded high-speed/ resolution camera, and open-source computer vision libraries. A carefully designed color-patterned target and user-adjustable crop filter enable accurate and fast image processing, allowing up to 240fps for complete displacement calculation and real-time display. The performances of the developed smartphone application are experimentally validated, showing comparable accuracy with those of conventional laser displacement sensor.

Floor Covering and Surface Identification for Assistive Mobile Robotic Real-Time Room Localization Application

PubMed Central

Gillham, Michael; Howells, Gareth; Spurgeon, Sarah; McElroy, Ben

2013-01-01

Assistive robotic applications require systems capable of interaction in the human world, a workspace which is highly dynamic and not always predictable. Mobile assistive devices face the additional and complex problem of when and if intervention should occur; therefore before any trajectory assistance is given, the robotic device must know where it is in real-time, without unnecessary disruption or delay to the user requirements. In this paper, we demonstrate a novel robust method for determining room identification from floor features in a real-time computational frame for autonomous and assistive robotics in the human environment. We utilize two inexpensive sensors: an optical mouse sensor for straightforward and rapid, texture or pattern sampling, and a four color photodiode light sensor for fast color determination. We show how data relating floor texture and color obtained from typical dynamic human environments, using these two sensors, compares favorably with data obtained from a standard webcam. We show that suitable data can be extracted from these two sensors at a rate 16 times faster than a standard webcam, and that these data are in a form which can be rapidly processed using readily available classification techniques, suitable for real-time system application. We achieved a 95% correct classification accuracy identifying 133 rooms' flooring from 35 classes, suitable for fast coarse global room localization application, boundary crossing detection, and additionally some degree of surface type identification. PMID:24351647

Floor covering and surface identification for assistive mobile robotic real-time room localization application.

PubMed

Gillham, Michael; Howells, Gareth; Spurgeon, Sarah; McElroy, Ben

2013-12-17

Assistive robotic applications require systems capable of interaction in the human world, a workspace which is highly dynamic and not always predictable. Mobile assistive devices face the additional and complex problem of when and if intervention should occur; therefore before any trajectory assistance is given, the robotic device must know where it is in real-time, without unnecessary disruption or delay to the user requirements. In this paper, we demonstrate a novel robust method for determining room identification from floor features in a real-time computational frame for autonomous and assistive robotics in the human environment. We utilize two inexpensive sensors: an optical mouse sensor for straightforward and rapid, texture or pattern sampling, and a four color photodiode light sensor for fast color determination. We show how data relating floor texture and color obtained from typical dynamic human environments, using these two sensors, compares favorably with data obtained from a standard webcam. We show that suitable data can be extracted from these two sensors at a rate 16 times faster than a standard webcam, and that these data are in a form which can be rapidly processed using readily available classification techniques, suitable for real-time system application. We achieved a 95% correct classification accuracy identifying 133 rooms' flooring from 35 classes, suitable for fast coarse global room localization application, boundary crossing detection, and additionally some degree of surface type identification.

Overview of the Smart Network Element Architecture and Recent Innovations

NASA Technical Reports Server (NTRS)

Perotti, Jose M.; Mata, Carlos T.; Oostdyk, Rebecca L.

2008-01-01

In industrial environments, system operators rely on the availability and accuracy of sensors to monitor processes and detect failures of components and/or processes. The sensors must be networked in such a way that their data is reported to a central human interface, where operators are tasked with making real-time decisions based on the state of the sensors and the components that are being monitored. Incorporating health management functions at this central location aids the operator by automating the decision-making process to suggest, and sometimes perform, the action required by current operating conditions. Integrated Systems Health Management (ISHM) aims to incorporate data from many sources, including real-time and historical data and user input, and extract information and knowledge from that data to diagnose failures and predict future failures of the system. By distributing health management processing to lower levels of the architecture, there is less bandwidth required for ISHM, enhanced data fusion, make systems and processes more robust, and improved resolution for the detection and isolation of failures in a system, subsystem, component, or process. The Smart Network Element (SNE) has been developed at NASA Kennedy Space Center to perform intelligent functions at sensors and actuators' level in support of ISHM.

Microfabricated Hydrogen Sensor Technology for Aerospace and Commercial Applications

NASA Technical Reports Server (NTRS)

Hunter, Gary W.; Bickford, R. L.; Jansa, E. D.; Makel, D. B.; Liu, C. C.; Wu, Q. H.; Powers, W. T.

1994-01-01

Leaks on the Space Shuttle while on the Launch Pad have generated interest in hydrogen leak monitoring technology. An effective leak monitoring system requires reliable hydrogen sensors, hardware, and software to monitor the sensors. The system should process the sensor outputs and provide real-time leak monitoring information to the operator. This paper discusses the progress in developing such a complete leak monitoring system. Advanced microfabricated hydrogen sensors are being fabricated at Case Western Reserve University (CWRU) and tested at NASA Lewis Research Center (LeRC) and Gencorp Aerojet (Aerojet). Changes in the hydrogen concentrations are detected using a PdAg on silicon Schottky diode structure. Sensor temperature control is achieved with a temperature sensor and heater fabricated onto the sensor chip. Results of the characterization of these sensors are presented. These sensors can detect low concentrations of hydrogen in inert environments with high sensitivity and quick response time. Aerojet is developing the hardware and software for a multipoint leak monitoring system designed to provide leak source and magnitude information in real time. The monitoring system processes data from the hydrogen sensors and presents the operator with a visual indication of the leak location and magnitude. Work has commenced on integrating the NASA LeRC-CWRU hydrogen sensors with the Aerojet designed monitoring system. Although the leak monitoring system was designed for hydrogen propulsion systems, the possible applications of this monitoring system are wide ranged. Possible commercialization of the system will also be discussed.

OPTICAL FIBER SENSOR TECHNOLOGIES FOR EFFICIENT AND ECONOMICAL OIL RECOVERY

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

Anbo Wang; Kristie L. Cooper; Gary R. Pickrell

2003-06-01

Efficient recovery of petroleum reserves from existing oil wells has been proven to be difficult due to the lack of robust instrumentation that can accurately and reliably monitor processes in the downhole environment. Commercially available sensors for measurement of pressure, temperature, and fluid flow exhibit shortened lifetimes in the harsh downhole conditions, which are characterized by high pressures (up to 20 kpsi), temperatures up to 250 C, and exposure to chemically reactive fluids. Development of robust sensors that deliver continuous, real-time data on reservoir performance and petroleum flow pathways will facilitate application of advanced recovery technologies, including horizontal and multilateralmore » wells. This is the final report for the four-year program ''Optical Fiber Sensor Technologies for Efficient and Economical Oil Recovery'', funded by the National Petroleum Technology Office of the U.S. Department of Energy, and performed by the Center for Photonics Technology of the Bradley Department of Electrical and Computer Engineering at Virginia Tech from October 1, 1999 to March 31, 2003. The main objective of this research program was to develop cost-effective, reliable optical fiber sensor instrumentation for real-time monitoring of various key parameters crucial to efficient and economical oil production. During the program, optical fiber sensors were demonstrated for the measurement of temperature, pressure, flow, and acoustic waves, including three successful field tests in the Chevron/Texaco oil fields in Coalinga, California, and at the world-class oil flow simulation facilities in Tulsa, Oklahoma. Research efforts included the design and fabrication of sensor probes, development of signal processing algorithms, construction of test systems, development and testing of strategies for the protection of optical fibers and sensors in the downhole environment, development of remote monitoring capabilities allowing real-time monitoring of the field test data from virtually anywhere in the world, and development of novel data processing techniques. Comprehensive testing was performed to systematically evaluate the performance of the fiber optic sensor systems in both lab and field environments.« less

Advances in Multi-Sensor Information Fusion: Theory and Applications 2017.

PubMed

Jin, Xue-Bo; Sun, Shuli; Wei, Hong; Yang, Feng-Bao

2018-04-11

The information fusion technique can integrate a large amount of data and knowledge representing the same real-world object and obtain a consistent, accurate, and useful representation of that object. The data may be independent or redundant, and can be obtained by different sensors at the same time or at different times. A suitable combination of investigative methods can substantially increase the profit of information in comparison with that from a single sensor. Multi-sensor information fusion has been a key issue in sensor research since the 1970s, and it has been applied in many fields. For example, manufacturing and process control industries can generate a lot of data, which have real, actionable business value. The fusion of these data can greatly improve productivity through digitization. The goal of this special issue is to report innovative ideas and solutions for multi-sensor information fusion in the emerging applications era, focusing on development, adoption, and applications.

Real-time Enhancement, Registration, and Fusion for a Multi-Sensor Enhanced Vision System

NASA Technical Reports Server (NTRS)

Hines, Glenn D.; Rahman, Zia-ur; Jobson, Daniel J.; Woodell, Glenn A.

2006-01-01

Over the last few years NASA Langley Research Center (LaRC) has been developing an Enhanced Vision System (EVS) to aid pilots while flying in poor visibility conditions. The EVS captures imagery using two infrared video cameras. The cameras are placed in an enclosure that is mounted and flown forward-looking underneath the NASA LaRC ARIES 757 aircraft. The data streams from the cameras are processed in real-time and displayed on monitors on-board the aircraft. With proper processing the camera system can provide better-than- human-observed imagery particularly during poor visibility conditions. However, to obtain this goal requires several different stages of processing including enhancement, registration, and fusion, and specialized processing hardware for real-time performance. We are using a real-time implementation of the Retinex algorithm for image enhancement, affine transformations for registration, and weighted sums to perform fusion. All of the algorithms are executed on a single TI DM642 digital signal processor (DSP) clocked at 720 MHz. The image processing components were added to the EVS system, tested, and demonstrated during flight tests in August and September of 2005. In this paper we briefly discuss the EVS image processing hardware and algorithms. We then discuss implementation issues and show examples of the results obtained during flight tests. Keywords: enhanced vision system, image enhancement, retinex, digital signal processing, sensor fusion

An Imaging Sensor-Aided Vision Navigation Approach that Uses a Geo-Referenced Image Database.

PubMed

Li, Yan; Hu, Qingwu; Wu, Meng; Gao, Yang

2016-01-28

In determining position and attitude, vision navigation via real-time image processing of data collected from imaging sensors is advanced without a high-performance global positioning system (GPS) and an inertial measurement unit (IMU). Vision navigation is widely used in indoor navigation, far space navigation, and multiple sensor-integrated mobile mapping. This paper proposes a novel vision navigation approach aided by imaging sensors and that uses a high-accuracy geo-referenced image database (GRID) for high-precision navigation of multiple sensor platforms in environments with poor GPS. First, the framework of GRID-aided vision navigation is developed with sequence images from land-based mobile mapping systems that integrate multiple sensors. Second, a highly efficient GRID storage management model is established based on the linear index of a road segment for fast image searches and retrieval. Third, a robust image matching algorithm is presented to search and match a real-time image with the GRID. Subsequently, the image matched with the real-time scene is considered to calculate the 3D navigation parameter of multiple sensor platforms. Experimental results show that the proposed approach retrieves images efficiently and has navigation accuracies of 1.2 m in a plane and 1.8 m in height under GPS loss in 5 min and within 1500 m.

An Imaging Sensor-Aided Vision Navigation Approach that Uses a Geo-Referenced Image Database

PubMed Central

Li, Yan; Hu, Qingwu; Wu, Meng; Gao, Yang

2016-01-01

In determining position and attitude, vision navigation via real-time image processing of data collected from imaging sensors is advanced without a high-performance global positioning system (GPS) and an inertial measurement unit (IMU). Vision navigation is widely used in indoor navigation, far space navigation, and multiple sensor-integrated mobile mapping. This paper proposes a novel vision navigation approach aided by imaging sensors and that uses a high-accuracy geo-referenced image database (GRID) for high-precision navigation of multiple sensor platforms in environments with poor GPS. First, the framework of GRID-aided vision navigation is developed with sequence images from land-based mobile mapping systems that integrate multiple sensors. Second, a highly efficient GRID storage management model is established based on the linear index of a road segment for fast image searches and retrieval. Third, a robust image matching algorithm is presented to search and match a real-time image with the GRID. Subsequently, the image matched with the real-time scene is considered to calculate the 3D navigation parameter of multiple sensor platforms. Experimental results show that the proposed approach retrieves images efficiently and has navigation accuracies of 1.2 m in a plane and 1.8 m in height under GPS loss in 5 min and within 1500 m. PMID:26828496

Embedding Piezoresistive Pressure Sensors to Obtain Online Pressure Profiles Inside Fiber Composite Laminates

PubMed Central

Kahali Moghaddam, Maryam; Breede, Arne; Brauner, Christian; Lang, Walter

2015-01-01

The production of large and complex parts using fiber composite materials is costly due to the frequent formation of voids, porosity and waste products. By embedding different types of sensors and monitoring the process in real time, the amount of wastage can be significantly reduced. This work focuses on developing a knowledge-based method to improve and ensure complete impregnation of the fibers before initiation of the resin cure. Piezoresistive and capacitive pressure sensors were embedded in fiber composite laminates to measure the real-time the pressure values inside the laminate. A change of pressure indicates resin infusion. The sensors were placed in the laminate and the resin was infused by vacuum. The embedded piezoresistive pressure sensors were able to track the vacuum pressure in the fiber composite laminate setup, as well as the arrival of the resin at the sensor. The pressure increase due to closing the resin inlet was also measured. In contrast, the capacitive type of sensor was found to be inappropriate for measuring these quantities. The following study demonstrates real-time monitoring of pressure changes inside the fiber composite laminate, which validate the use of Darcy’s law in porous media to control the resin flow during infusion. PMID:25825973

Frequency Domain Analysis of Sensor Data for Event Classification in Real-Time Robot Assisted Deburring

PubMed Central

Pappachan, Bobby K; Caesarendra, Wahyu; Tjahjowidodo, Tegoeh; Wijaya, Tomi

2017-01-01

Process monitoring using indirect methods relies on the usage of sensors. Using sensors to acquire vital process related information also presents itself with the problem of big data management and analysis. Due to uncertainty in the frequency of events occurring, a higher sampling rate is often used in real-time monitoring applications to increase the chances of capturing and understanding all possible events related to the process. Advanced signal processing methods are used to further decipher meaningful information from the acquired data. In this research work, power spectrum density (PSD) of sensor data acquired at sampling rates between 40–51.2 kHz was calculated and the corelation between PSD and completed number of cycles/passes is presented. Here, the progress in number of cycles/passes is the event this research work intends to classify and the algorithm used to compute PSD is Welch’s estimate method. A comparison between Welch’s estimate method and statistical methods is also discussed. A clear co-relation was observed using Welch’s estimate to classify the number of cycles/passes. The paper also succeeds in classifying vibration signal generated by the spindle from the vibration signal acquired during finishing process. PMID:28556809

System and method for cognitive processing for data fusion

NASA Technical Reports Server (NTRS)

Duong, Tuan A. (Inventor); Duong, Vu A. (Inventor)

2012-01-01

A system and method for cognitive processing of sensor data. A processor array receiving analog sensor data and having programmable interconnects, multiplication weights, and filters provides for adaptive learning in real-time. A static random access memory contains the programmable data for the processor array and the stored data is modified to provide for adaptive learning.

Real-Time Communication Support for Underwater Acoustic Sensor Networks †.

PubMed

Santos, Rodrigo; Orozco, Javier; Micheletto, Matias; Ochoa, Sergio F; Meseguer, Roc; Millan, Pere; Molina, And Carlos

2017-07-14

Underwater sensor networks represent an important and promising field of research due to the large diversity of underwater ubiquitous applications that can be supported by these networks, e.g., systems that deliver tsunami and oil spill warnings, or monitor submarine ecosystems. Most of these monitoring and warning systems require real-time communication in wide area networks that have a low density of nodes. The underwater communication medium involved in these networks is very harsh and imposes strong restrictions to the communication process. In this scenario, the real-time transmission of information is done mainly using acoustic signals, since the network nodes are not physically close. The features of the communication scenario and the requirements of the communication process represent major challenges for designers of both, communication protocols and monitoring and warning systems. The lack of models to represent these networks is the main stumbling block for the proliferation of underwater ubiquitous systems. This paper presents a real-time communication model for underwater acoustic sensor networks (UW-ASN) that are designed to cover wide areas with a low density of nodes, using any-to-any communication. This model is analytic, considers two solution approaches for scheduling the real-time messages, and provides a time-constraint analysis for the network performance. Using this model, the designers of protocols and underwater ubiquitous systems can quickly prototype and evaluate their solutions in an evolving way, in order to determine the best solution to the problem being addressed. The suitability of the proposal is illustrated with a case study that shows the performance of a UW-ASN under several initial conditions. This is the first analytic model for representing real-time communication in this type of network, and therefore, it opens the door for the development of underwater ubiquitous systems for several application scenarios.

Real-Time Communication Support for Underwater Acoustic Sensor Networks †

PubMed Central

Santos, Rodrigo; Orozco, Javier; Micheletto, Matias

2017-01-01

Underwater sensor networks represent an important and promising field of research due to the large diversity of underwater ubiquitous applications that can be supported by these networks, e.g., systems that deliver tsunami and oil spill warnings, or monitor submarine ecosystems. Most of these monitoring and warning systems require real-time communication in wide area networks that have a low density of nodes. The underwater communication medium involved in these networks is very harsh and imposes strong restrictions to the communication process. In this scenario, the real-time transmission of information is done mainly using acoustic signals, since the network nodes are not physically close. The features of the communication scenario and the requirements of the communication process represent major challenges for designers of both, communication protocols and monitoring and warning systems. The lack of models to represent these networks is the main stumbling block for the proliferation of underwater ubiquitous systems. This paper presents a real-time communication model for underwater acoustic sensor networks (UW-ASN) that are designed to cover wide areas with a low density of nodes, using any-to-any communication. This model is analytic, considers two solution approaches for scheduling the real-time messages, and provides a time-constraint analysis for the network performance. Using this model, the designers of protocols and underwater ubiquitous systems can quickly prototype and evaluate their solutions in an evolving way, in order to determine the best solution to the problem being addressed. The suitability of the proposal is illustrated with a case study that shows the performance of a UW-ASN under several initial conditions. This is the first analytic model for representing real-time communication in this type of network, and therefore, it opens the door for the development of underwater ubiquitous systems for several application scenarios. PMID:28708093

Real-time Graphics Processing Unit Based Fourier Domain Optical Coherence Tomography and Surgical Applications

NASA Astrophysics Data System (ADS)

Zhang, Kang

2011-12-01

In this dissertation, real-time Fourier domain optical coherence tomography (FD-OCT) capable of multi-dimensional micrometer-resolution imaging targeted specifically for microsurgical intervention applications was developed and studied. As a part of this work several ultra-high speed real-time FD-OCT imaging and sensing systems were proposed and developed. A real-time 4D (3D+time) OCT system platform using the graphics processing unit (GPU) to accelerate OCT signal processing, the imaging reconstruction, visualization, and volume rendering was developed. Several GPU based algorithms such as non-uniform fast Fourier transform (NUFFT), numerical dispersion compensation, and multi-GPU implementation were developed to improve the impulse response, SNR roll-off and stability of the system. Full-range complex-conjugate-free FD-OCT was also implemented on the GPU architecture to achieve doubled image range and improved SNR. These technologies overcome the imaging reconstruction and visualization bottlenecks widely exist in current ultra-high speed FD-OCT systems and open the way to interventional OCT imaging for applications in guided microsurgery. A hand-held common-path optical coherence tomography (CP-OCT) distance-sensor based microsurgical tool was developed and validated. Through real-time signal processing, edge detection and feed-back control, the tool was shown to be capable of track target surface and compensate motion. The micro-incision test using a phantom was performed using a CP-OCT-sensor integrated hand-held tool, which showed an incision error less than +/-5 microns, comparing to >100 microns error by free-hand incision. The CP-OCT distance sensor has also been utilized to enhance the accuracy and safety of optical nerve stimulation. Finally, several experiments were conducted to validate the system for surgical applications. One of them involved 4D OCT guided micro-manipulation using a phantom. Multiple volume renderings of one 3D data set were performed with different view angles to allow accurate monitoring of the micro-manipulation, and the user to clearly monitor tool-to-target spatial relation in real-time. The system was also validated by imaging multiple biological samples, such as human fingerprint, human cadaver head and small animals. Compared to conventional surgical microscopes, GPU-based real-time FD-OCT can provide the surgeons with a real-time comprehensive spatial view of the microsurgical region and accurate depth perception.

Laser vision seam tracking system based on image processing and continuous convolution operator tracker

NASA Astrophysics Data System (ADS)

Zou, Yanbiao; Chen, Tao

2018-06-01

To address the problem of low welding precision caused by the poor real-time tracking performance of common welding robots, a novel seam tracking system with excellent real-time tracking performance and high accuracy is designed based on the morphological image processing method and continuous convolution operator tracker (CCOT) object tracking algorithm. The system consists of a six-axis welding robot, a line laser sensor, and an industrial computer. This work also studies the measurement principle involved in the designed system. Through the CCOT algorithm, the weld feature points are determined in real time from the noise image during the welding process, and the 3D coordinate values of these points are obtained according to the measurement principle to control the movement of the robot and the torch in real time. Experimental results show that the sensor has a frequency of 50 Hz. The welding torch runs smoothly with a strong arc light and splash interference. Tracking error can reach ±0.2 mm, and the minimal distance between the laser stripe and the welding molten pool can reach 15 mm, which can significantly fulfill actual welding requirements.

A laser scanning confocal imaging-surface plasmon resonance system application in real time detection of antibody-antigen interaction

NASA Astrophysics Data System (ADS)

Zhang, H. Y.; Yang, L. Q.; Liu, W. M.

2011-12-01

The laser scanning confocal microscope (LSCM) offers several advantages over conventional optical microscopy, but most LSCM work is qualitative analysis and it is very hard to achieve quantitative detection directly with the changing of the fluorescent intensity. A new real time sensor system for the antibody-antigen interaction detection was built integrating with a LSCM and a wavelength-dependent surface plasmon resonance (SPR) sensor. The system was applied to detect the bonding process of human IgG and fluorescent-labeled affinity purified antibody in real time. The fluorescence images changing is well with that of SPR wavelengths in real time, and the trend of the resonance wavelength shift with the concentrations of antibody is similar to that of the fluorescent intensity changing. The results show that SPR makes up the short of quantificational analysis with LSCM with the high spatial resolution. The sensor system shows the merits of the of the LSCM and SPR synergetic application, which are of great importance for practical application in biosensor and life science for interesting local interaction.

Study on real-time images compounded using spatial light modulator

NASA Astrophysics Data System (ADS)

Xu, Jin; Chen, Zhebo; Ni, Xuxiang; Lu, Zukang

2007-01-01

Image compounded technology is often used on film and its facture. In common, image compounded use image processing arithmetic, get useful object, details, background or some other things from the images firstly, then compounding all these information into one image. When using this method, the film system needs a powerful processor, for the process function is very complex, we get the compounded image for a few time delay. In this paper, we introduce a new method of image real-time compounded, use this method, we can do image composite at the same time with movie shot. The whole system is made up of two camera-lens, spatial light modulator array and image sensor. In system, the spatial light modulator could be liquid crystal display (LCD), liquid crystal on silicon (LCoS), thin film transistor liquid crystal display (TFTLCD), Deformable Micro-mirror Device (DMD), and so on. Firstly, one camera-lens images the object on the spatial light modulator's panel, we call this camera-lens as first image lens. Secondly, we output an image to the panel of spatial light modulator. Then, the image of the object and image that output by spatial light modulator will be spatial compounded on the panel of spatial light modulator. Thirdly, the other camera-lens images the compounded image to the image sensor, and we call this camera-lens as second image lens. After these three steps, we will gain the compound images by image sensor. For the spatial light modulator could output the image continuously, then the image will be compounding continuously too, and the compounding procedure is completed in real-time. When using this method to compounding image, if we will put real object into invented background, we can output the invented background scene on the spatial light modulator, and the real object will be imaged by first image lens. Then, we get the compounded images by image sensor in real time. The same way, if we will put real background to an invented object, we can output the invented object on the spatial light modulator and the real background will be imaged by first image lens. Then, we can also get the compounded images by image sensor real time. Commonly, most spatial light modulator only can do modulate light intensity, so we can only do compounding BW images if use only one panel which without color filter. If we will get colorful compounded image, we need use the system like three spatial light modulator panel projection. In the paper, the system's optical system framework we will give out. In all experiment, the spatial light modulator used liquid crystal on silicon (LCoS). At the end of the paper, some original pictures and compounded pictures will be given on it. Although the system has a few shortcomings, we can conclude that, using this system to compounding images has no delay to do mathematic compounding process, it is a really real time images compounding system.

A high performance sensor for triaxial cutting force measurement in turning.

PubMed

Zhao, You; Zhao, Yulong; Liang, Songbo; Zhou, Guanwu

2015-04-03

This paper presents a high performance triaxial cutting force sensor with excellent accuracy, favorable natural frequency and acceptable cross-interference for high speed turning process. Octagonal ring is selected as sensitive element of the designed sensor, which is drawn inspiration from ring theory. A novel structure of two mutual-perpendicular octagonal rings is proposed and three Wheatstone full bridge circuits are specially organized in order to obtain triaxial cutting force components and restrain cross-interference. Firstly, the newly developed sensor is tested in static calibration; test results indicate that the sensor possesses outstanding accuracy in the range of 0.38%-0.83%. Secondly, impacting modal tests are conducted to identify the natural frequencies of the sensor in triaxial directions (i.e., 1147 Hz, 1122 Hz and 2035 Hz), which implies that the devised sensor can be used for cutting force measurement in a high speed lathe when the spindle speed does not exceed 17,205 rev/min in continuous cutting condition. Finally, an application of the sensor in turning process is operated to show its performance for real-time cutting force measurement; the measured cutting forces demonstrate a good accordance with the variation of cutting parameters. Thus, the developed sensor possesses perfect properties and it gains great potential for real-time cutting force measurement in turning.

A High Performance Sensor for Triaxial Cutting Force Measurement in Turning

PubMed Central

Zhao, You; Zhao, Yulong; Liang, Songbo; Zhou, Guanwu

2015-01-01

This paper presents a high performance triaxial cutting force sensor with excellent accuracy, favorable natural frequency and acceptable cross-interference for high speed turning process. Octagonal ring is selected as sensitive element of the designed sensor, which is drawn inspiration from ring theory. A novel structure of two mutual-perpendicular octagonal rings is proposed and three Wheatstone full bridge circuits are specially organized in order to obtain triaxial cutting force components and restrain cross-interference. Firstly, the newly developed sensor is tested in static calibration; test results indicate that the sensor possesses outstanding accuracy in the range of 0.38%–0.83%. Secondly, impacting modal tests are conducted to identify the natural frequencies of the sensor in triaxial directions (i.e., 1147 Hz, 1122 Hz and 2035 Hz), which implies that the devised sensor can be used for cutting force measurement in a high speed lathe when the spindle speed does not exceed 17,205 rev/min in continuous cutting condition. Finally, an application of the sensor in turning process is operated to show its performance for real-time cutting force measurement; the measured cutting forces demonstrate a good accordance with the variation of cutting parameters. Thus, the developed sensor possesses perfect properties and it gains great potential for real-time cutting force measurement in turning. PMID:25855035

Real-time image processing of TOF range images using a reconfigurable processor system

NASA Astrophysics Data System (ADS)

Hussmann, S.; Knoll, F.; Edeler, T.

2011-07-01

During the last years, Time-of-Flight sensors achieved a significant impact onto research fields in machine vision. In comparison to stereo vision system and laser range scanners they combine the advantages of active sensors providing accurate distance measurements and camera-based systems recording a 2D matrix at a high frame rate. Moreover low cost 3D imaging has the potential to open a wide field of additional applications and solutions in markets like consumer electronics, multimedia, digital photography, robotics and medical technologies. This paper focuses on the currently implemented 4-phase-shift algorithm in this type of sensors. The most time critical operation of the phase-shift algorithm is the arctangent function. In this paper a novel hardware implementation of the arctangent function using a reconfigurable processor system is presented and benchmarked against the state-of-the-art CORDIC arctangent algorithm. Experimental results show that the proposed algorithm is well suited for real-time processing of the range images of TOF cameras.

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

Sreedharan, Priya

The sudden release of toxic contaminants that reach indoor spaces can be hazardousto building occupants. To respond effectively, the contaminant release must be quicklydetected and characterized to determine unobserved parameters, such as release locationand strength. Characterizing the release requires solving an inverse problem. Designinga robust real-time sensor system that solves the inverse problem is challenging becausethe fate and transport of contaminants is complex, sensor information is limited andimperfect, and real-time estimation is computationally constrained.This dissertation uses a system-level approach, based on a Bayes Monte Carloframework, to develop sensor-system design concepts and methods. I describe threeinvestigations that explore complex relationships amongmore » sensors, network architecture,interpretation algorithms, and system performance. The investigations use data obtainedfrom tracer gas experiments conducted in a real building. The influence of individual sensor characteristics on the sensor-system performance for binary-type contaminant sensors is analyzed. Performance tradeoffs among sensor accuracy, threshold level and response time are identified; these attributes could not be inferred without a system-level analysis. For example, more accurate but slower sensors are found to outperform less accurate but faster sensors. Secondly, I investigate how the sensor-system performance can be understood in terms of contaminant transport processes and the model representation that is used to solve the inverse problem. The determination of release location and mass are shown to be related to and constrained by transport and mixing time scales. These time scales explain performance differences among different sensor networks. For example, the effect of longer sensor response times is comparably less for releases with longer mixing time scales. The third investigation explores how information fusion from heterogeneous sensors may improve the sensor-system performance and offset the need for more contaminant sensors. Physics- and algorithm-based frameworks are presented for selecting and fusing information from noncontaminant sensors. The frameworks are demonstrated with door-position sensors, which are found to be more useful in natural airflow conditions, but which cannot compensate for poor placement of contaminant sensors. The concepts and empirical findings have the potential to help in the design of sensor systems for more complex building systems. The research has broader relevance to additional environmental monitoring problems, fault detection and diagnostics, and system design.« less

A Real-Time Cardiac Arrhythmia Classification System with Wearable Sensor Networks

PubMed Central

Hu, Sheng; Wei, Hongxing; Chen, Youdong; Tan, Jindong

2012-01-01

Long term continuous monitoring of electrocardiogram (ECG) in a free living environment provides valuable information for prevention on the heart attack and other high risk diseases. This paper presents the design of a real-time wearable ECG monitoring system with associated cardiac arrhythmia classification algorithms. One of the striking advantages is that ECG analog front-end and on-node digital processing are designed to remove most of the noise and bias. In addition, the wearable sensor node is able to monitor the patient's ECG and motion signal in an unobstructive way. To realize the real-time medical analysis, the ECG is digitalized and transmitted to a smart phone via Bluetooth. On the smart phone, the ECG waveform is visualized and a novel layered hidden Markov model is seamlessly integrated to classify multiple cardiac arrhythmias in real time. Experimental results demonstrate that the clean and reliable ECG waveform can be captured in multiple stressed conditions and the real-time classification on cardiac arrhythmia is competent to other workbenches. PMID:23112746

Biomimetic machine vision system.

PubMed

Harman, William M; Barrett, Steven F; Wright, Cameron H G; Wilcox, Michael

2005-01-01

Real-time application of digital imaging for use in machine vision systems has proven to be prohibitive when used within control systems that employ low-power single processors without compromising the scope of vision or resolution of captured images. Development of a real-time machine analog vision system is the focus of research taking place at the University of Wyoming. This new vision system is based upon the biological vision system of the common house fly. Development of a single sensor is accomplished, representing a single facet of the fly's eye. This new sensor is then incorporated into an array of sensors capable of detecting objects and tracking motion in 2-D space. This system "preprocesses" incoming image data resulting in minimal data processing to determine the location of a target object. Due to the nature of the sensors in the array, hyperacuity is achieved thereby eliminating resolutions issues found in digital vision systems. In this paper, we will discuss the biological traits of the fly eye and the specific traits that led to the development of this machine vision system. We will also discuss the process of developing an analog based sensor that mimics the characteristics of interest in the biological vision system. This paper will conclude with a discussion of how an array of these sensors can be applied toward solving real-world machine vision issues.

Nanoparticle PEBBLE sensors in live cells and in vivo

PubMed Central

Smith, Ron

2009-01-01

Nanoparticle sensors have been developed for imaging and dynamic monitoring, in live cells and in vivo, of the molecular or ionic components, constructs, forces and dynamics, all in real time, during biological/chemical/physical processes. With their biocompatible small size and inert matrix, nanoparticle sensors have been successfully applied for non-invasive real-time measurements of analytes and fields in cells and rodents, with spatial, temporal, physical and chemical resolution. This review describes the diverse designs of nanoparticle sensors for ions and small molecules, physical fields and biological features, as well as the characterization, properties, and applications of these nanosensors to in vitro and in vivo measurements. Their floating as well as localization ability in biological media is captured by the acronym PEBBLE: photonic explorer for bioanalysis with biologically localized embedding. PMID:20098636

Real-time understanding of lignocellulosic bioethanol fermentation by Raman spectroscopy

PubMed Central

2013-01-01

Background A substantial barrier to commercialization of lignocellulosic ethanol production is a lack of process specific sensors and associated control strategies that are essential for economic viability. Current sensors and analytical techniques require lengthy offline analysis or are easily fouled in situ. Raman spectroscopy has the potential to continuously monitor fermentation reactants and products, maximizing efficiency and allowing for improved process control. Results In this paper we show that glucose and ethanol in a lignocellulosic fermentation can be accurately monitored by a 785 nm Raman spectroscopy instrument and novel immersion probe, even in the presence of an elevated background thought to be caused by lignin-derived compounds. Chemometric techniques were used to reduce the background before generating calibration models for glucose and ethanol concentration. The models show very good correlation between the real-time Raman spectra and the offline HPLC validation. Conclusions Our results show that the changing ethanol and glucose concentrations during lignocellulosic fermentation processes can be monitored in real-time, allowing for optimization and control of large scale bioconversion processes. PMID:23425590

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.

Comparison of turbulence mitigation algorithms

NASA Astrophysics Data System (ADS)

Kozacik, Stephen T.; Paolini, Aaron; Sherman, Ariel; Bonnett, James; Kelmelis, Eric

2017-07-01

When capturing imagery over long distances, atmospheric turbulence often degrades the data, especially when observation paths are close to the ground or in hot environments. These issues manifest as time-varying scintillation and warping effects that decrease the effective resolution of the sensor and reduce actionable intelligence. In recent years, several image processing approaches to turbulence mitigation have shown promise. Each of these algorithms has different computational requirements, usability demands, and degrees of independence from camera sensors. They also produce different degrees of enhancement when applied to turbulent imagery. Additionally, some of these algorithms are applicable to real-time operational scenarios while others may only be suitable for postprocessing workflows. EM Photonics has been developing image-processing-based turbulence mitigation technology since 2005. We will compare techniques from the literature with our commercially available, real-time, GPU-accelerated turbulence mitigation software. These comparisons will be made using real (not synthetic), experimentally obtained data for a variety of conditions, including varying optical hardware, imaging range, subjects, and turbulence conditions. Comparison metrics will include image quality, video latency, computational complexity, and potential for real-time operation. Additionally, we will present a technique for quantitatively comparing turbulence mitigation algorithms using real images of radial resolution targets.

Steel reinforcement corrosion detection with coaxial cable sensors

NASA Astrophysics Data System (ADS)

Muchaidze, Iana; Pommerenke, David; Chen, Genda

2011-04-01

Corrosion processes in the steel reinforced structures can result in structural deficiency and with time create a threat to human lives. Millions of dollars are lost each year because of corrosion. According to the U. S. Federal Highway Administration (FHWA) the average annual cost of corrosion in the infrastructure sector by the end of 2002 was estimated to be $22.6 billion. Timely remediation/retrofit and effective maintenance can extend the structure's live span for much less expense. Thus the considerable effort should be done to deploy corrosion monitoring techniques to have realistic information on the location and the severity of damage. Nowadays commercially available techniques for corrosion monitoring require costly equipment and certain interpretational skills. In addition, none of them is designed for the real time quality assessment. In this study the crack sensor developed at Missouri University of Science and Technology is proposed as a distributed sensor for real time corrosion monitoring. Implementation of this technology may ease the pressure on the bridge owners restrained with the federal budget by allowing the timely remediation with the minimal financial and labor expenses. The sensor is instrumented in such a way that the location of any discontinuity developed along its length can be easily detected. When the sensor is placed in immediate vicinity to the steel reinforcement it is subjected to the same chemical process as the steel reinforcement. And corrosion pitting is expected to develop on the sensor exactly at the same location as in the rebar. Thus it is expected to be an effective tool for active corrosion zones detection within reinforced concrete (RC) members. A series of laboratory tests were conducted to validate the effectiveness of the proposed methodology. Nine sensors were manufactured and placed in the artificially created corrosive environment and observed over the time. To induce accelerated corrosion 3% and 5% NaCL solutions were used. Based on the test results, the proposed/corrosion distributed sensor is capable of delivering fairly accurate information on the location of a discontinuity along the sensor caused by corrosion pitting. Forensic study was also conducted to validate the concept. In order to test the sensors in real live condition, 27 sensors were prepared to be placed into RC beams. The beams will be subjected to corrosive environment. After that the sensors will be monitored over the time for signs of corrosion.

A Real-Time Thermal Self-Elimination Method for Static Mode Operated Freestanding Piezoresistive Microcantilever-Based Biosensors

PubMed Central

Ku, Yu-Fu; Huang, Long-Sun

2018-01-01

Here, we provide a method and apparatus for real-time compensation of the thermal effect of single free-standing piezoresistive microcantilever-based biosensors. The sensor chip contained an on-chip fixed piezoresistor that served as a temperature sensor, and a multilayer microcantilever with an embedded piezoresistor served as a biomolecular sensor. This method employed the calibrated relationship between the resistance and the temperature of piezoresistors to eliminate the thermal effect on the sensor, including the temperature coefficient of resistance (TCR) and bimorph effect. From experimental results, the method was verified to reduce the signal of thermal effect from 25.6 μV/°C to 0.3 μV/°C, which was approximately two orders of magnitude less than that before the processing of the thermal elimination method. Furthermore, the proposed approach and system successfully demonstrated its effective real-time thermal self-elimination on biomolecular detection without any thermostat device to control the environmental temperature. This method realizes the miniaturization of an overall measurement system of the sensor, which can be used to develop portable medical devices and microarray analysis platforms. PMID:29495574

Revolutionize Situational Awareness in Emergencies

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

Hehlen, Markus Peter

This report describes an integrated system that provides real-time actionable information to first responders. LANL will integrate three technologies to form an advanced predictive real-time sensor network including compact chemical and wind sensor sin low cost rugged package for outdoor installation; flexible robust communication architecture linking sensors in near-real time to globally accessible servers; and the QUIC code which predicts contamination transport and dispersal in urban environments in near real time.

Role of optical computers in aeronautical control applications

NASA Technical Reports Server (NTRS)

Baumbick, R. J.

1981-01-01

The role that optical computers play in aircraft control is determined. The optical computer has the potential high speed capability required, especially for matrix/matrix operations. The optical computer also has the potential for handling nonlinear simulations in real time. They are also more compatible with fiber optic signal transmission. Optics also permit the use of passive sensors to measure process variables. No electrical energy need be supplied to the sensor. Complex interfacing between optical sensors and the optical computer is avoided if the optical sensor outputs can be directly processed by the optical computer.

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.

Evaluation of a newly developed mid-infrared sensor for real-time monitoring of yeast fermentations.

PubMed

Schalk, Robert; Geoerg, Daniel; Staubach, Jens; Raedle, Matthias; Methner, Frank-Juergen; Beuermann, Thomas

2017-05-01

A mid-infrared (MIR) sensor using the attenuated total reflection (ATR) technique has been developed for real-time monitoring in biotechnology. The MIR-ATR sensor consists of an IR emitter as light source, a zinc selenide ATR prism as boundary to the process, and four thermopile detectors, each equipped with an optical bandpass filter. The suitability of the sensor for practical application was tested during aerobic batch-fermentations of Saccharomyces cerevisiae by simultaneous monitoring of glucose and ethanol. The performance of the sensor was compared to a commercial Fourier transform mid-infrared (FT-MIR) spectrometer by on-line measurements in a bypass loop. Sensor and spectrometer were calibrated by multiple linear regression (MLR) in order to link the measured absorbance in the transmission ranges of the four optical sensor channels to the analyte concentrations. For reference analysis, high-performance liquid chromatography (HPLC) was applied. Process monitoring using the sensor yielded in standard errors of prediction (SEP) of 6.15 g/L and 1.36 g/L for glucose and ethanol. In the case of the FT-MIR spectrometer the corresponding SEP values were 4.34 g/L and 0.61 g/L, respectively. The advantages of optical multi-channel mid-infrared sensors in comparison to FT-MIR spectrometer setups are the compactness, easy process implementation and lower price. Copyright © 2016 The Society for Biotechnology, Japan. Published by Elsevier B.V. All rights reserved.

The Sensor Management for Applied Research Technologies (SMART) Project

NASA Technical Reports Server (NTRS)

Goodman, Michael; Jedlovec, Gary; Conover, Helen; Botts, Mike; Robin, Alex; Blakeslee, Richard; Hood, Robbie; Ingenthron, Susan; Li, Xiang; Maskey, Manil;

Sensor Management for Applied Research Technologies (SMART)-On Demand Modeling (ODM) Project

NASA Technical Reports Server (NTRS)

Goodman, M.; Blakeslee, R.; Hood, R.; Jedlovec, G.; Botts, M.; Li, X.

2006-01-01

NASA requires timely on-demand data and analysis capabilities to enable practical benefits of Earth science observations. However, a significant challenge exists in accessing and integrating data from multiple sensors or platforms to address Earth science problems because of the large data volumes, varying sensor scan characteristics, unique orbital coverage, and the steep learning curve associated with each sensor and data type. The development of sensor web capabilities to autonomously process these data streams (whether real-time or archived) provides an opportunity to overcome these obstacles and facilitate the integration and synthesis of Earth science data and weather model output. A three year project, entitled Sensor Management for Applied Research Technologies (SMART) - On Demand Modeling (ODM), will develop and demonstrate the readiness of Open Geospatial Consortium (OGC) Sensor Web Enablement (SWE) capabilities that integrate both Earth observations and forecast model output into new data acquisition and assimilation strategies. The advancement of SWE-enabled systems (i.e., use of SensorML, sensor planning services - SPS, sensor observation services - SOS, sensor alert services - SAS and common observation model protocols) will have practical and efficient uses in the Earth science community for enhanced data set generation, real-time data assimilation with operational applications, and for autonomous sensor tasking for unique data collection.

Color sensor and neural processor on one chip

NASA Astrophysics Data System (ADS)

Fiesler, Emile; Campbell, Shannon R.; Kempem, Lother; Duong, Tuan A.

1998-10-01

Low-cost, compact, and robust color sensor that can operate in real-time under various environmental conditions can benefit many applications, including quality control, chemical sensing, food production, medical diagnostics, energy conservation, monitoring of hazardous waste, and recycling. Unfortunately, existing color sensor are either bulky and expensive or do not provide the required speed and accuracy. In this publication we describe the design of an accurate real-time color classification sensor, together with preprocessing and a subsequent neural network processor integrated on a single complementary metal oxide semiconductor (CMOS) integrated circuit. This one-chip sensor and information processor will be low in cost, robust, and mass-producible using standard commercial CMOS processes. The performance of the chip and the feasibility of its manufacturing is proven through computer simulations based on CMOS hardware parameters. Comparisons with competing methodologies show a significantly higher performance for our device.

Novel Real-Time Temperature Diagnosis of Conventional Hot-Embossing Process Using an Ultrasonic Transducer

PubMed Central

Cheng, Chin-Chi; Yang, Sen-Yeu; Lee, Dasheng

2014-01-01

This paper presents an integrated high temperature ultrasonic transducer (HTUT) on a sensor insert and its application for real-time diagnostics of the conventional hot embossing process to fabricate V-cut patterns. The sensor was directly deposited onto the sensor insert of the hot embossing mold by using a sol-gel spray technique. It could operate at temperatures higher than 400 °C and uses an ultrasonic pulse-echo technique. The ultrasonic velocity could indicate the three statuses of the hot embossing process and also evaluate the replication of V-cut patterns on a plastic plate under various processing conditions. The progression of the process, including mold closure, plastic plate softening, cooling and plate detachment inside the mold, was clearly observed using ultrasound. For an ultrasonic velocity range from 2197.4 to 2435.9 m/s, the height of the V-cut pattern decreased from 23.0 to 3.2 μm linearly, with a ratio of −0.078 μm/(m/s). The incompleteness of the replication of the V-cut patterns could be indirectly observed by the ultrasonic signals. This study demonstrates the effectiveness of the ultrasonic sensors and technology for diagnosing the replicating condition of microstructures during the conventional hot embossing process. PMID:25330051

Overlay improvements using a real time machine learning algorithm

NASA Astrophysics Data System (ADS)

Schmitt-Weaver, Emil; Kubis, Michael; Henke, Wolfgang; Slotboom, Daan; Hoogenboom, Tom; Mulkens, Jan; Coogans, Martyn; ten Berge, Peter; Verkleij, Dick; van de Mast, Frank

2014-04-01

While semiconductor manufacturing is moving towards the 14nm node using immersion lithography, the overlay requirements are tightened to below 5nm. Next to improvements in the immersion scanner platform, enhancements in the overlay optimization and process control are needed to enable these low overlay numbers. Whereas conventional overlay control methods address wafer and lot variation autonomously with wafer pre exposure alignment metrology and post exposure overlay metrology, we see a need to reduce these variations by correlating more of the TWINSCAN system's sensor data directly to the post exposure YieldStar metrology in time. In this paper we will present the results of a study on applying a real time control algorithm based on machine learning technology. Machine learning methods use context and TWINSCAN system sensor data paired with post exposure YieldStar metrology to recognize generic behavior and train the control system to anticipate on this generic behavior. Specific for this study, the data concerns immersion scanner context, sensor data and on-wafer measured overlay data. By making the link between the scanner data and the wafer data we are able to establish a real time relationship. The result is an inline controller that accounts for small changes in scanner hardware performance in time while picking up subtle lot to lot and wafer to wafer deviations introduced by wafer processing.

Parallel Processing Systems for Passive Ranging During Helicopter Flight

NASA Technical Reports Server (NTRS)

Sridhar, Bavavar; Suorsa, Raymond E.; Showman, Robert D. (Technical Monitor)

1994-01-01

The complexity of rotorcraft missions involving operations close to the ground result in high pilot workload. In order to allow a pilot time to perform mission-oriented tasks, sensor-aiding and automation of some of the guidance and control functions are highly desirable. Images from an electro-optical sensor provide a covert way of detecting objects in the flight path of a low-flying helicopter. Passive ranging consists of processing a sequence of images using techniques based on optical low computation and recursive estimation. The passive ranging algorithm has to extract obstacle information from imagery at rates varying from five to thirty or more frames per second depending on the helicopter speed. We have implemented and tested the passive ranging algorithm off-line using helicopter-collected images. However, the real-time data and computation requirements of the algorithm are beyond the capability of any off-the-shelf microprocessor or digital signal processor. This paper describes the computational requirements of the algorithm and uses parallel processing technology to meet these requirements. Various issues in the selection of a parallel processing architecture are discussed and four different computer architectures are evaluated regarding their suitability to process the algorithm in real-time. Based on this evaluation, we conclude that real-time passive ranging is a realistic goal and can be achieved with a short time.

Laser beam welding quality monitoring system based in high-speed (10 kHz) uncooled MWIR imaging sensors

NASA Astrophysics Data System (ADS)

Linares, Rodrigo; Vergara, German; Gutiérrez, Raúl; Fernández, Carlos; Villamayor, Víctor; Gómez, Luis; González-Camino, Maria; Baldasano, Arturo; Castro, G.; Arias, R.; Lapido, Y.; Rodríguez, J.; Romero, Pablo

2015-05-01

The combination of flexibility, productivity, precision and zero-defect manufacturing in future laser-based equipment are a major challenge that faces this enabling technology. New sensors for online monitoring and real-time control of laserbased processes are necessary for improving products quality and increasing manufacture yields. New approaches to fully automate processes towards zero-defect manufacturing demand smarter heads where lasers, optics, actuators, sensors and electronics will be integrated in a unique compact and affordable device. Many defects arising in laser-based manufacturing processes come from instabilities in the dynamics of the laser process. Temperature and heat dynamics are key parameters to be monitored. Low cost infrared imagers with high-speed of response will constitute the next generation of sensors to be implemented in future monitoring and control systems for laser-based processes, capable to provide simultaneous information about heat dynamics and spatial distribution. This work describes the result of using an innovative low-cost high-speed infrared imager based on the first quantum infrared imager monolithically integrated with Si-CMOS ROIC of the market. The sensor is able to provide low resolution images at frame rates up to 10 KHz in uncooled operation at the same cost as traditional infrared spot detectors. In order to demonstrate the capabilities of the new sensor technology, a low-cost camera was assembled on a standard production laser welding head, allowing to register melting pool images at frame rates of 10 kHz. In addition, a specific software was developed for defect detection and classification. Multiple laser welding processes were recorded with the aim to study the performance of the system and its application to the real-time monitoring of laser welding processes. During the experiments, different types of defects were produced and monitored. The classifier was fed with the experimental images obtained. Self-learning strategies were implemented with very promising results, demonstrating the feasibility of using low-cost high-speed infrared imagers in advancing towards a real-time / in-line zero-defect production systems.

Analytical Models of Cross-Layer Protocol Optimization in Real-Time Wireless Sensor Ad Hoc Networks

NASA Astrophysics Data System (ADS)

Hortos, William S.

The real-time interactions among the nodes of a wireless sensor network (WSN) to cooperatively process data from multiple sensors are modeled. Quality-of-service (QoS) metrics are associated with the quality of fused information: throughput, delay, packet error rate, etc. Multivariate point process (MVPP) models of discrete random events in WSNs establish stochastic characteristics of optimal cross-layer protocols. Discrete-event, cross-layer interactions in mobile ad hoc network (MANET) protocols have been modeled using a set of concatenated design parameters and associated resource levels by the MVPPs. Characterization of the "best" cross-layer designs for a MANET is formulated by applying the general theory of martingale representations to controlled MVPPs. Performance is described in terms of concatenated protocol parameters and controlled through conditional rates of the MVPPs. Modeling limitations to determination of closed-form solutions versus explicit iterative solutions for ad hoc WSN controls are examined.

Process and control systems for composites manufacturing

NASA Technical Reports Server (NTRS)

Tsiang, T. H.; Wanamaker, John L.

1992-01-01

A precise control of composite material processing would not only improve part quality, but it would also directly reduce the overall manufacturing cost. The development and incorporation of sensors will help to generate real-time information for material processing relationships and equipment characteristics. In the present work, the thermocouple, pressure transducer, and dielectrometer technologies were investigated. The monitoring sensors were integrated with the computerized control system in three non-autoclave fabrication techniques: hot-press, self contained tool (self heating and pressurizing), and pressure vessel). The sensors were implemented in the parts and tools.

Fault detection and diagnosis using neural network approaches

NASA Technical Reports Server (NTRS)

Kramer, Mark A.

1992-01-01

Neural networks can be used to detect and identify abnormalities in real-time process data. Two basic approaches can be used, the first based on training networks using data representing both normal and abnormal modes of process behavior, and the second based on statistical characterization of the normal mode only. Given data representative of process faults, radial basis function networks can effectively identify failures. This approach is often limited by the lack of fault data, but can be facilitated by process simulation. The second approach employs elliptical and radial basis function neural networks and other models to learn the statistical distributions of process observables under normal conditions. Analytical models of failure modes can then be applied in combination with the neural network models to identify faults. Special methods can be applied to compensate for sensor failures, to produce real-time estimation of missing or failed sensors based on the correlations codified in the neural network.

A Control Chart Approach for Representing and Mining Data Streams with Shape Based Similarity

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

Omitaomu, Olufemi A

The mining of data streams for online condition monitoring is a challenging task in several domains including (electric) power grid system, intelligent manufacturing, and consumer science. Considering a power grid application in which thousands of sensors, called the phasor measurement units, are deployed on the power grid network to continuously collect streams of digital data for real-time situational awareness and system management. Depending on design, each sensor could stream between ten and sixty data samples per second. The myriad of sensory data captured could convey deeper insights about sequence of events in real-time and before major damages are done. However,more » the timely processing and analysis of these high-velocity and high-volume data streams is a challenge. Hence, a new data processing and transformation approach, based on the concept of control charts, for representing sequence of data streams from sensors is proposed. In addition, an application of the proposed approach for enhancing data mining tasks such as clustering using real-world power grid data streams is presented. The results indicate that the proposed approach is very efficient for data streams storage and manipulation.« less

A Real-Time Executive for Multiple-Computer Clusters.

DTIC Science & Technology

1984-12-01

in a real-time environment is tantamount to speed and efficiency. By effectively co-locating real-time sensors and related processing modules, real...of which there are two ki n1 s : multicast group address - virtually any nur.,ber of node groups can be assigned a group address so they are all able...interfaceloopbark by 󈧅’b4, internal _loopback by 02"b4, clear loooback by 󈧇’b4, go offline by Ŝ"b4, eo online by 󈧍’b4, onboard _diagnostic by Oa’b4, cdr

Real-time Bayesian anomaly detection in streaming environmental data

NASA Astrophysics Data System (ADS)

Hill, David J.; Minsker, Barbara S.; Amir, Eyal

2009-04-01

With large volumes of data arriving in near real time from environmental sensors, there is a need for automated detection of anomalous data caused by sensor or transmission errors or by infrequent system behaviors. This study develops and evaluates three automated anomaly detection methods using dynamic Bayesian networks (DBNs), which perform fast, incremental evaluation of data as they become available, scale to large quantities of data, and require no a priori information regarding process variables or types of anomalies that may be encountered. This study investigates these methods' abilities to identify anomalies in eight meteorological data streams from Corpus Christi, Texas. The results indicate that DBN-based detectors, using either robust Kalman filtering or Rao-Blackwellized particle filtering, outperform a DBN-based detector using Kalman filtering, with the former having false positive/negative rates of less than 2%. These methods were successful at identifying data anomalies caused by two real events: a sensor failure and a large storm.

A data-management system using sensor technology and wireless devices for port security

NASA Astrophysics Data System (ADS)

Saldaña, Manuel; Rivera, Javier; Oyola, Jose; Manian, Vidya

2014-05-01

Sensor technologies such as infrared sensors and hyperspectral imaging, video camera surveillance are proven to be viable in port security. Drawing from sources such as infrared sensor data, digital camera images and processed hyperspectral images, this article explores the implementation of a real-time data delivery system. In an effort to improve the manner in which anomaly detection data is delivered to interested parties in port security, this system explores how a client-server architecture can provide protected access to data, reports, and device status. Sensor data and hyperspectral image data will be kept in a monitored directory, where the system will link it to existing users in the database. Since this system will render processed hyperspectral images that are dynamically added to the server - which often occupy a large amount of space - the resolution of these images is trimmed down to around 1024×768 pixels. Changes that occur in any image or data modification that originates from any sensor will trigger a message to all users that have a relation with the aforementioned. These messages will be sent to the corresponding users through automatic email generation and through a push notification using Google Cloud Messaging for Android. Moreover, this paper presents the complete architecture for data reception from the sensors, processing, storage and discusses how users of this system such as port security personnel can use benefit from the use of this service to receive secure real-time notifications if their designated sensors have detected anomalies and/or have remote access to results from processed hyperspectral imagery relevant to their assigned posts.

A Tree Based Self-routing Scheme for Mobility Support in Wireless Sensor Networks

NASA Astrophysics Data System (ADS)

Kim, Young-Duk; Yang, Yeon-Mo; Kang, Won-Seok; Kim, Jin-Wook; An, Jinung

Recently, WSNs (Wireless Sensor Networks) with mobile robot is a growing technology that offer efficient communication services for anytime and anywhere applications. However, the tiny sensor node has very limited network resources due to its low battery power, low data rate, node mobility, and channel interference constraint between neighbors. Thus, in this paper, we proposed a tree based self-routing protocol for autonomous mobile robots based on beacon mode and implemented in real test-bed environments. The proposed scheme offers beacon based real-time scheduling for reliable association process between parent and child nodes. In addition, it supports smooth handover procedure by reducing flooding overhead of control packets. Throughout the performance evaluation by using a real test-bed system and simulation, we illustrate that our proposed scheme demonstrates promising performance for wireless sensor networks with mobile robots.

Optical Sensor for real-time Monitoring of CO(2) Laser Welding Process.

PubMed

Ancona, A; Spagnolo, V; Lugarà, P M; Ferrara, M

2001-11-20

An optical sensor for real-time monitoring of laser welding based on a spectroscopic study of the optical emission of plasma plumes has been developed. The welding plasma's electron temperature was contemporarily monitored for three of the chemical species that constitute the plasma plume by use of related emission lines. The evolution of electron temperature was recorded and analyzed during several welding procedures carried out under various operating conditions. A clear correlation between the mean value and the standard deviation of the plasma's electron temperature and the quality of the welded joint has been found. We used this information to find optimal welding parameters and for real-time detection of weld defects such as crater formation, lack of penetration, weld disruptions, and seam oxidation.

Real-time optically sectioned wide-field microscopy employing structured light illumination and a CMOS detector

NASA Astrophysics Data System (ADS)

Mitic, Jelena; Anhut, Tiemo; Serov, Alexandre; Lasser, Theo; Bourquin, Stephane

2003-07-01

Real-time optically sectioned microscopy is demonstrated using an AC-sensitive detection concept realized with smart CMOS image sensor and structured light illumination by a continuously moving periodic pattern. We describe two different detection systems based on CMOS image sensors for the detection and on-chip processing of the sectioned images in real time. A region-of-interest is sampled at high frame rate. The demodulated signal delivered by the detector corresponds to the depth discriminated image of the sample. The measured FWHM of the axial response depends on the spatial frequency of the projected grid illumination and is in the μm-range. The effect of using broadband incoherent illumination is discussed. The performance of these systems is demonstrated by imaging technical as well as biological samples.

Benchmarking real-time RGBD odometry for light-duty UAVs

NASA Astrophysics Data System (ADS)

Willis, Andrew R.; Sahawneh, Laith R.; Brink, Kevin M.

2016-06-01

This article describes the theoretical and implementation challenges associated with generating 3D odometry estimates (delta-pose) from RGBD sensor data in real-time to facilitate navigation in cluttered indoor environments. The underlying odometry algorithm applies to general 6DoF motion; however, the computational platforms, trajectories, and scene content are motivated by their intended use on indoor, light-duty UAVs. Discussion outlines the overall software pipeline for sensor processing and details how algorithm choices for the underlying feature detection and correspondence computation impact the real-time performance and accuracy of the estimated odometry and associated covariance. This article also explores the consistency of odometry covariance estimates and the correlation between successive odometry estimates. The analysis is intended to provide users information needed to better leverage RGBD odometry within the constraints of their systems.

Computer hardware and software for robotic control

NASA Technical Reports Server (NTRS)

Davis, Virgil Leon

1987-01-01

The KSC has implemented an integrated system that coordinates state-of-the-art robotic subsystems. It is a sensor based real-time robotic control system performing operations beyond the capability of an off-the-shelf robot. The integrated system provides real-time closed loop adaptive path control of position and orientation of all six axes of a large robot; enables the implementation of a highly configurable, expandable testbed for sensor system development; and makes several smart distributed control subsystems (robot arm controller, process controller, graphics display, and vision tracking) appear as intelligent peripherals to a supervisory computer coordinating the overall systems.

CAIRSENSE Study: Real-world evaluation of low cost sensors ...

EPA Pesticide Factsheets

Low-cost air pollution sensors are a rapidly developing field in air monitoring. In recent years, numerous sensors have been developed that can provide real-time concentration data for different air pollutants at costs accessible to individuals and non-regulatory groups. Additionally, these sensors have the potential to improve the spatial resolution of monitoring networks and provide a better understanding of neighborhood- and local-scale air quality and sources. However, many new sensors have not been evaluated to determine their long-term performance and capabilities. In this study, nine different low-cost sensor models, including O3, NO2 and particle sensors, were deployed in Denver, CO from September 2015 to February 2016. Three sensors of each type were deployed to evaluate instrument precision and consistency over the time period. Sensors were co-located with reference monitors at the Denver NCore site in order to evaluate sensor accuracy and precision. Denver was chosen as the location for this study to evaluate sensor performance in dry, high altitude, and low winter temperatures. Sensors were evaluated for data completeness, performance over time, and comparison with regulatory monitors. This presentation will also address challenges and approaches to data logging and processing. Preliminary analysis revealed that most sensors had high data completeness when data loggers were operational (e.g., the Aeroqual O3 sensor ranged from 94-100%), and exhibited

Inertial sensors as real-time feedback improve learning posterior-anterior thoracic manipulation: a randomized controlled trial.

PubMed

Cuesta-Vargas, Antonio I; González-Sánchez, Manuel; Lenfant, Yves

2015-01-01

The purpose of this study was to analyze the effect of real-time feedback on the learning process for posterior-anterior thoracic manipulation (PATM) comparing 2 undergraduate physiotherapy student groups. The study design was a randomized controlled trial in an educational setting. Sixty-one undergraduate physiotherapy students were divided randomly into 2 groups, G1 (n = 31; group without feedback in real time) and G2 (n = 30; group with real-time feedback) participated in this randomized controlled trial. Two groups of physiotherapy students learned PATM, one using a traditional method and the other using real-time feedback (inertial sensor). Measures were obtained preintervention and postintervention. Intragroup preintervention and postintervention and intergroup postintervention scores were calculated. An analysis of the measures' stability was developed through an interclass correlation index. Time, displacement and velocity, and improvement (only between groups) to reach maximum peak and to reach minimum peak from maximum peak, total manipulation time, and stability of all outcome measures were the outcome measures. Statistically significant differences were found in all variables analyzed (intragroup and intergroup) in favor of G2. The values of interclass correlation ranged from 0.627 to 0.706 (G1) and between 0.881 and 0.997 (G2). This study found that the learning process for PATM is facilitated when the student receives real-time feedback. Copyright © 2015 National University of Health Sciences. Published by Elsevier Inc. All rights reserved.

Automated inspection of hot steel slabs

DOEpatents

Martin, R.J.

1985-12-24

The disclosure relates to a real time digital image enhancement system for performing the image enhancement segmentation processing required for a real time automated system for detecting and classifying surface imperfections in hot steel slabs. The system provides for simultaneous execution of edge detection processing and intensity threshold processing in parallel on the same image data produced by a sensor device such as a scanning camera. The results of each process are utilized to validate the results of the other process and a resulting image is generated that contains only corresponding segmentation that is produced by both processes. 5 figs.

Automated inspection of hot steel slabs

DOEpatents

Martin, Ronald J.

1985-01-01

The disclosure relates to a real time digital image enhancement system for performing the image enhancement segmentation processing required for a real time automated system for detecting and classifying surface imperfections in hot steel slabs. The system provides for simultaneous execution of edge detection processing and intensity threshold processing in parallel on the same image data produced by a sensor device such as a scanning camera. The results of each process are utilized to validate the results of the other process and a resulting image is generated that contains only corresponding segmentation that is produced by both processes.

The Use of Ubiquitous Sensor Technology in Evaluating Student Thought Process during Practical Operations for Improving Student Technical and Creative Skills

ERIC Educational Resources Information Center

Jou, Min; Wang, Jingying

2015-01-01

This study investigated a Ubiquitous Sensor System (USS) that we developed to assess student thought process during practical lessons on a real-time basis and to provide students with a reflective learning environment. Behavioral curves and data obtained by the USS would help students understand where they had made mistakes during practical…

Mixed-mode VLSI optic flow sensors for in-flight control of a micro air vehicle

NASA Astrophysics Data System (ADS)

Barrows, Geoffrey L.; Neely, C.

2000-11-01

NRL is developing compact optic flow sensors for use in a variety of small-scale navigation and collision avoidance tasks. These sensors are being developed for use in micro air vehicles (MAVs), which are autonomous aircraft whose maximum dimension is on the order of 15 cm. To achieve desired weight specifications of 1 - 2 grams, mixed-signal VLSI circuitry is being used to develop compact focal plane sensors that directly compute optic flow. As an interim proof of principle, we have constructed a sensor comprising a focal plane sensor head with on-chip processing and a back-end PIC microcontroller. This interim sensors weighs approximately 25 grams and is able to measure optic flow with real-world and low-contrast textures. Variations of this sensor have been used to control the flight of a glider in real-time to avoid collisions with walls.

Real-time Data Access to First Responders: A VORB application

NASA Astrophysics Data System (ADS)

Lu, S.; Kim, J. B.; Bryant, P.; Foley, S.; Vernon, F.; Rajasekar, A.; Meier, S.

2006-12-01

Getting information to first responders is not an easy task. The sensors that provide the information are diverse in formats and come from many disciplines. They are also distributed by location, transmit data at different frequencies and are managed and owned by autonomous administrative entities. Pulling such types of data in real-time, needs a very robust sensor network with reliable data transport and buffering capabilities. Moreover, the system should be extensible and scalable in numbers and sensor types. ROADNet is a real- time sensor network project at UCSD gathering diverse environmental data in real-time or near-real-time. VORB (Virtual Object Ring Buffer) is the middleware used in ROADNet offering simple, uniform and scalable real-time data management for discovering (through metadata), accessing and archiving real-time data and data streams. Recent development in VORB, a web API, has offered quick and simple real-time data integration with web applications. In this poster, we discuss one application developed as part of ROADNet. SMER (Santa Margarita Ecological Reserve) is located in interior Southern California, a region prone to catastrophic wildfires each summer and fall. To provide data during emergencies, we have applied the VORB framework to develop a web-based application for providing access to diverse sensor data including weather data, heat sensor information, and images from cameras. Wildfire fighters have access to real-time data about weather and heat conditions in the area and view pictures taken from cameras at multiple points in the Reserve to pinpoint problem areas. Moreover, they can browse archived images and sensor data from earlier times to provide a comparison framework. To show scalability of the system, we have expanded the sensor network under consideration through other areas in Southern California including sensors accessible by Los Angeles County Fire Department (LACOFD) and those available through the High Performance Wireless Research and Education Network (HPWREN). The poster will discuss the system architecture and components, the types of sensor being used and usage scenarios. The system is currently operational through the SMER web-site.

Uncloaking the Scientific Process

NASA Astrophysics Data System (ADS)

Leitzell, K.; Meier, W.

2009-12-01

Since April 2008, NSIDC has offered daily updates of sea ice data on our Arctic Sea Ice News & Analysis Web page (http://nsidc.org/arcticseaicenews). The images provide near-real-time data to the general public and policy makers, accompanied by monthly or more frequent analysis updates. In February 2009, a crucial channel of the Special Sensor Microwave/Imager (SSM/I) sensor on the Defense Meteorological Satellite Program (DMSP) F15 satellite, from which NSIDC was obtaining near-real-time Arctic sea ice data, suddenly failed. The daily image, which is automatically updated, showed a sudden drop in ice extent of over 50,000 square kilometers. Even after taking the images down, skeptical blogs jumped on the event, posting headlines such as “Errors in publicly presented data - Worth blogging about?” and “NSIDC pulls the plug on sea ice data.” In fact, NSIDC data managers and scientists were well aware that the F15 satellite sensor would eventually fail. NSIDC switched to a previously used back-up sensor, F13, and work to transition to a newer sensor on the F17 satellite had been underway for several weeks. While the deluge of questions from readers and bloggers were frustrating to NSIDC communications staff and scientists, they also presented a chance to give readers a window into the scientific process, and specifically into the collection of satellite data. We decided to publish a clear account of the process used to transition between sensors, as well as a basic explanation of the satellites used to measure sea ice data. While most scientists are familiar with the limitations of near-real-time data, the concept is unfamiliar to many in the general public. The Web page includes links to information on near-real-time data, including notes that images sometimes contain missing or erroneous data, and that delays can occur. However, to a skeptical person, the words that scientists use to describe the processing of final data, including “adjustment,” “bias,” and “correction,” can convey a sinister or political motive. How much information is really necessary for the general public? How much should we share about our processes and motives? This poster/presentation will address some of the dangers and opportunities of presenting near-real-time data to the public, and share some of strategies we used to respond to attacks on our data quality. In order to develop effective responses to climate change, it is important for policymakers to focus on complete data records and not short-term variability in near-real-time data, which may not be indicative of long-term trends or, as in the case presented here, may have errors that need to be corrected. NSIDC clearly states that its near-real-time images and data should not be used for significant conclusions about the long-term state of the climate, but are an initial snapshot for informational purposes. Nonetheless, NSIDC did hear from some policymakers that our data was regularly being used in various briefs within governmental agencies. This has led to greater attention to how our data may be used. However, we hope that our transparency and clear explanations will be valuable in guiding how policymakers employ our data and images in the future.

Affordable multisensor digital video architecture for 360° situational awareness displays

NASA Astrophysics Data System (ADS)

Scheiner, Steven P.; Khan, Dina A.; Marecki, Alexander L.; Berman, David A.; Carberry, Dana

2011-06-01

One of the major challenges facing today's military ground combat vehicle operations is the ability to achieve and maintain full-spectrum situational awareness while under armor (i.e. closed hatch). Thus, the ability to perform basic tasks such as driving, maintaining local situational awareness, surveillance, and targeting will require a high-density array of real time information be processed, distributed, and presented to the vehicle operators and crew in near real time (i.e. low latency). Advances in display and sensor technologies are providing never before seen opportunities to supply large amounts of high fidelity imagery and video to the vehicle operators and crew in real time. To fully realize the advantages of these emerging display and sensor technologies, an underlying digital architecture must be developed that is capable of processing these large amounts of video and data from separate sensor systems and distributing it simultaneously within the vehicle to multiple vehicle operators and crew. This paper will examine the systems and software engineering efforts required to overcome these challenges and will address development of an affordable, integrated digital video architecture. The approaches evaluated will enable both current and future ground combat vehicle systems the flexibility to readily adopt emerging display and sensor technologies, while optimizing the Warfighter Machine Interface (WMI), minimizing lifecycle costs, and improve the survivability of the vehicle crew working in closed-hatch systems during complex ground combat operations.

A Real-Time Marker-Based Visual Sensor Based on a FPGA and a Soft Core Processor

PubMed Central

Tayara, Hilal; Ham, Woonchul; Chong, Kil To

2016-01-01

This paper introduces a real-time marker-based visual sensor architecture for mobile robot localization and navigation. A hardware acceleration architecture for post video processing system was implemented on a field-programmable gate array (FPGA). The pose calculation algorithm was implemented in a System on Chip (SoC) with an Altera Nios II soft-core processor. For every frame, single pass image segmentation and Feature Accelerated Segment Test (FAST) corner detection were used for extracting the predefined markers with known geometries in FPGA. Coplanar PosIT algorithm was implemented on the Nios II soft-core processor supplied with floating point hardware for accelerating floating point operations. Trigonometric functions have been approximated using Taylor series and cubic approximation using Lagrange polynomials. Inverse square root method has been implemented for approximating square root computations. Real time results have been achieved and pixel streams have been processed on the fly without any need to buffer the input frame for further implementation. PMID:27983714

Optical fibre multi-parameter sensing with secure cloud based signal capture and processing

NASA Astrophysics Data System (ADS)

Newe, Thomas; O'Connell, Eoin; Meere, Damien; Yuan, Hongwei; Leen, Gabriel; O'Keeffe, Sinead; Lewis, Elfed

2016-05-01

Recent advancements in cloud computing technologies in the context of optical and optical fibre based systems are reported. The proliferation of real time and multi-channel based sensor systems represents significant growth in data volume. This coupled with a growing need for security presents many challenges and presents a huge opportunity for an evolutionary step in the widespread application of these sensing technologies. A tiered infrastructural system approach is adopted that is designed to facilitate the delivery of Optical Fibre-based "SENsing as a Service- SENaaS". Within this infrastructure, novel optical sensing platforms, deployed within different environments, are interfaced with a Cloud-based backbone infrastructure which facilitates the secure collection, storage and analysis of real-time data. Feedback systems, which harness this data to affect a change within the monitored location/environment/condition, are also discussed. The cloud based system presented here can also be used with chemical and physical sensors that require real-time data analysis, processing and feedback.

A Real-Time Marker-Based Visual Sensor Based on a FPGA and a Soft Core Processor.

PubMed

Tayara, Hilal; Ham, Woonchul; Chong, Kil To

2016-12-15

This paper introduces a real-time marker-based visual sensor architecture for mobile robot localization and navigation. A hardware acceleration architecture for post video processing system was implemented on a field-programmable gate array (FPGA). The pose calculation algorithm was implemented in a System on Chip (SoC) with an Altera Nios II soft-core processor. For every frame, single pass image segmentation and Feature Accelerated Segment Test (FAST) corner detection were used for extracting the predefined markers with known geometries in FPGA. Coplanar PosIT algorithm was implemented on the Nios II soft-core processor supplied with floating point hardware for accelerating floating point operations. Trigonometric functions have been approximated using Taylor series and cubic approximation using Lagrange polynomials. Inverse square root method has been implemented for approximating square root computations. Real time results have been achieved and pixel streams have been processed on the fly without any need to buffer the input frame for further implementation.

The design of real time infrared image generation software based on Creator and Vega

NASA Astrophysics Data System (ADS)

Wang, Rui-feng; Wu, Wei-dong; Huo, Jun-xiu

2013-09-01

Considering the requirement of high reality and real-time quality dynamic infrared image of an infrared image simulation, a method to design real-time infrared image simulation application on the platform of VC++ is proposed. This is based on visual simulation software Creator and Vega. The functions of Creator are introduced simply, and the main features of Vega developing environment are analyzed. The methods of infrared modeling and background are offered, the designing flow chart of the developing process of IR image real-time generation software and the functions of TMM Tool and MAT Tool and sensor module are explained, at the same time, the real-time of software is designed.

Adaptive Sampling in Autonomous Marine Sensor Networks

DTIC Science & Technology

2006-06-01

Analog Processing Section A high-performance preamplifier with low noise characteristics is vital to obtaining quality sonar data. The preamplifier ...research assistantships through the Generic Ocean Array Technology Sonar (GOATS) project, contract N00014-97-1-0202 and contract N00014-05-G-0106 Delivery...Formation Behavior ..................................... 60 5 An AUV Intelligent Sensor for Real-Time Adaptive Sensing 63 5.1 A Logical Sonar Sensor

IJA: an efficient algorithm for query processing in sensor networks.

PubMed

Lee, Hyun Chang; Lee, Young Jae; Lim, Ji Hyang; Kim, Dong Hwa

2011-01-01

One of main features in sensor networks is the function that processes real time state information after gathering needed data from many domains. The component technologies consisting of each node called a sensor node that are including physical sensors, processors, actuators and power have advanced significantly over the last decade. Thanks to the advanced technology, over time sensor networks have been adopted in an all-round industry sensing physical phenomenon. However, sensor nodes in sensor networks are considerably constrained because with their energy and memory resources they have a very limited ability to process any information compared to conventional computer systems. Thus query processing over the nodes should be constrained because of their limitations. Due to the problems, the join operations in sensor networks are typically processed in a distributed manner over a set of nodes and have been studied. By way of example while simple queries, such as select and aggregate queries, in sensor networks have been addressed in the literature, the processing of join queries in sensor networks remains to be investigated. Therefore, in this paper, we propose and describe an Incremental Join Algorithm (IJA) in Sensor Networks to reduce the overhead caused by moving a join pair to the final join node or to minimize the communication cost that is the main consumer of the battery when processing the distributed queries in sensor networks environments. At the same time, the simulation result shows that the proposed IJA algorithm significantly reduces the number of bytes to be moved to join nodes compared to the popular synopsis join algorithm.

IJA: An Efficient Algorithm for Query Processing in Sensor Networks

PubMed Central

Lee, Hyun Chang; Lee, Young Jae; Lim, Ji Hyang; Kim, Dong Hwa

2011-01-01

One of main features in sensor networks is the function that processes real time state information after gathering needed data from many domains. The component technologies consisting of each node called a sensor node that are including physical sensors, processors, actuators and power have advanced significantly over the last decade. Thanks to the advanced technology, over time sensor networks have been adopted in an all-round industry sensing physical phenomenon. However, sensor nodes in sensor networks are considerably constrained because with their energy and memory resources they have a very limited ability to process any information compared to conventional computer systems. Thus query processing over the nodes should be constrained because of their limitations. Due to the problems, the join operations in sensor networks are typically processed in a distributed manner over a set of nodes and have been studied. By way of example while simple queries, such as select and aggregate queries, in sensor networks have been addressed in the literature, the processing of join queries in sensor networks remains to be investigated. Therefore, in this paper, we propose and describe an Incremental Join Algorithm (IJA) in Sensor Networks to reduce the overhead caused by moving a join pair to the final join node or to minimize the communication cost that is the main consumer of the battery when processing the distributed queries in sensor networks environments. At the same time, the simulation result shows that the proposed IJA algorithm significantly reduces the number of bytes to be moved to join nodes compared to the popular synopsis join algorithm. PMID:22319375

Energy-efficient hierarchical processing in the network of wireless intelligent sensors (WISE)

NASA Astrophysics Data System (ADS)

Raskovic, Dejan

Sensor network nodes have benefited from technological advances in the field of wireless communication, processing, and power sources. However, the processing power of microcontrollers is often not sufficient to perform sophisticated processing, while the power requirements of digital signal processing boards or handheld computers are usually too demanding for prolonged system use. We are matching the intrinsic hierarchical nature of many digital signal-processing applications with the natural hierarchy in distributed wireless networks, and building the hierarchical system of wireless intelligent sensors. Our goal is to build a system that will exploit the hierarchical organization to optimize the power consumption and extend battery life for the given time and memory constraints, while providing real-time processing of sensor signals. In addition, we are designing our system to be able to adapt to the current state of the environment, by dynamically changing the algorithm through procedure replacement. This dissertation presents the analysis of hierarchical environment and methods for energy profiling used to evaluate different system design strategies, and to optimize time-effective and energy-efficient processing.

Real-time 3D change detection of IEDs

NASA Astrophysics Data System (ADS)

Wathen, Mitch; Link, Norah; Iles, Peter; Jinkerson, John; Mrstik, Paul; Kusevic, Kresimir; Kovats, David

2012-06-01

Road-side bombs are a real and continuing threat to soldiers in theater. CAE USA recently developed a prototype Volume based Intelligence Surveillance Reconnaissance (VISR) sensor platform for IED detection. This vehicle-mounted, prototype sensor system uses a high data rate LiDAR (1.33 million range measurements per second) to generate a 3D mapping of roadways. The mapped data is used as a reference to generate real-time change detection on future trips on the same roadways. The prototype VISR system is briefly described. The focus of this paper is the methodology used to process the 3D LiDAR data, in real-time, to detect small changes on and near the roadway ahead of a vehicle traveling at moderate speeds with sufficient warning to stop the vehicle at a safe distance from the threat. The system relies on accurate navigation equipment to geo-reference the reference run and the change-detection run. Since it was recognized early in the project that detection of small changes could not be achieved with accurate navigation solutions alone, a scene alignment algorithm was developed to register the reference run with the change detection run prior to applying the change detection algorithm. Good success was achieved in simultaneous real time processing of scene alignment plus change detection.

Commercial Digital/ADP Equipment in the Ocean Environment. Volume 2. User Appendices

DTIC Science & Technology

1978-12-15

is that the LINDA system uses a mini computer with a time sharing system software which allows several terminals to be operated at the same time...Acquisition System (ODAS) consists of sensors, computer hardware and computer software . Certain sensors are interfaced to the computers for real time...on USNS KANE, USNS BENT, and USKS WILKES. Commercial automatic data processing equipment used in ODAS includes: Item Model Computer PDP-9 Tape

Visual Servoing for an Autonomous Hexarotor Using a Neural Network Based PID Controller.

PubMed

Lopez-Franco, Carlos; Gomez-Avila, Javier; Alanis, Alma Y; Arana-Daniel, Nancy; Villaseñor, Carlos

2017-08-12

In recent years, unmanned aerial vehicles (UAVs) have gained significant attention. However, we face two major drawbacks when working with UAVs: high nonlinearities and unknown position in 3D space since it is not provided with on-board sensors that can measure its position with respect to a global coordinate system. In this paper, we present a real-time implementation of a servo control, integrating vision sensors, with a neural proportional integral derivative (PID), in order to develop an hexarotor image based visual servo control (IBVS) that knows the position of the robot by using a velocity vector as a reference to control the hexarotor position. This integration requires a tight coordination between control algorithms, models of the system to be controlled, sensors, hardware and software platforms and well-defined interfaces, to allow the real-time implementation, as well as the design of different processing stages with their respective communication architecture. All of these issues and others provoke the idea that real-time implementations can be considered as a difficult task. For the purpose of showing the effectiveness of the sensor integration and control algorithm to address these issues on a high nonlinear system with noisy sensors as cameras, experiments were performed on the Asctec Firefly on-board computer, including both simulation and experimenta results.

Visual Servoing for an Autonomous Hexarotor Using a Neural Network Based PID Controller

PubMed Central

Lopez-Franco, Carlos; Alanis, Alma Y.; Arana-Daniel, Nancy; Villaseñor, Carlos

2017-01-01

In recent years, unmanned aerial vehicles (UAVs) have gained significant attention. However, we face two major drawbacks when working with UAVs: high nonlinearities and unknown position in 3D space since it is not provided with on-board sensors that can measure its position with respect to a global coordinate system. In this paper, we present a real-time implementation of a servo control, integrating vision sensors, with a neural proportional integral derivative (PID), in order to develop an hexarotor image based visual servo control (IBVS) that knows the position of the robot by using a velocity vector as a reference to control the hexarotor position. This integration requires a tight coordination between control algorithms, models of the system to be controlled, sensors, hardware and software platforms and well-defined interfaces, to allow the real-time implementation, as well as the design of different processing stages with their respective communication architecture. All of these issues and others provoke the idea that real-time implementations can be considered as a difficult task. For the purpose of showing the effectiveness of the sensor integration and control algorithm to address these issues on a high nonlinear system with noisy sensors as cameras, experiments were performed on the Asctec Firefly on-board computer, including both simulation and experimenta results. PMID:28805689

SeismoGeodesy: Combination of High Rate, Real-time GNSS and Accelerometer Observations and Rapid Seismic Event Notification for Earth Quake Early Warning and Volcano Monitoring

NASA Astrophysics Data System (ADS)

Jackson, Michael; Zimakov, Leonid; Moessmer, Matthias

2015-04-01

Scientific GNSS networks are moving towards a model of real-time data acquisition, epoch-by-epoch storage integrity, and on-board real-time position and displacement calculations. This new paradigm allows the integration of real-time, high-rate GNSS displacement information with acceleration and velocity data to create very high-rate displacement records. The mating of these two instruments allows the creation of a new, very high-rate (200 Hz) displacement observable that has the full-scale displacement characteristics of GNSS and high-precision dynamic motions of seismic technologies. It is envisioned that these new observables can be used for earthquake early warning studies, volcano monitoring, and critical infrastructure monitoring applications. Our presentation will focus on the characteristics of GNSS, seismic, and strong motion sensors in high dynamic environments, including historic earthquakes replicated on a shake table over a range of displacements and frequencies. We will explore the optimum integration of these sensors from a filtering perspective including simple harmonic impulses over varying frequencies and amplitudes and under the dynamic conditions of various earthquake scenarios. We will also explore the tradeoffs between various GNSS processing schemes including real-time precise point positioning (PPP) and real-time kinematic (RTK) as applied to seismogeodesy. In addition we will discuss implementation of a Rapid Seismic Event Notification System that provides quick delivery of digital data from seismic stations to the acquisition and processing center and a full data integrity model for real-time earthquake notification that provides warning prior to significant ground shaking.

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.

A Model for Field Deployment of Wireless Sensor Networks (WSNs) within the Domain of Microclimate Habitat Monitoring

ERIC Educational Resources Information Center

Sanborn, Mark

2011-01-01

Wireless sensor networks (WSNs) represent a class of miniaturized information systems designed to monitor physical environments. These smart monitoring systems form collaborative networks utilizing autonomous sensing, data-collection, and processing to provide real-time analytics of observed environments. As a fundamental research area in…

Critical review of real-time methods for solid waste characterisation: Informing material recovery and fuel production.

PubMed

Vrancken, C; Longhurst, P J; Wagland, S T

2017-03-01

Waste management processes generally represent a significant loss of material, energy and economic resources, so legislation and financial incentives are being implemented to improve the recovery of these valuable resources whilst reducing contamination levels. Material recovery and waste derived fuels are potentially valuable options being pursued by industry, using mechanical and biological processes incorporating sensor and sorting technologies developed and optimised for recycling plants. In its current state, waste management presents similarities to other industries that could improve their efficiencies using process analytical technology tools. Existing sensor technologies could be used to measure critical waste characteristics, providing data required by existing legislation, potentially aiding waste treatment processes and assisting stakeholders in decision making. Optical technologies offer the most flexible solution to gather real-time information applicable to each of the waste mechanical and biological treatment processes used by industry. In particular, combinations of optical sensors in the visible and the near-infrared range from 800nm to 2500nm of the spectrum, and different mathematical techniques, are able to provide material information and fuel properties with typical performance levels between 80% and 90%. These sensors not only could be used to aid waste processes, but to provide most waste quality indicators required by existing legislation, whilst offering better tools to the stakeholders. Copyright © 2017 Elsevier Ltd. All rights reserved.

Video image processing to create a speed sensor

DOT National Transportation Integrated Search

1999-11-01

Image processing has been applied to traffic analysis in recent years, with different goals. In the report, a new approach is presented for extracting vehicular speed information, given a sequence of real-time traffic images. We extract moving edges ...

Real Time Analysis of Bioanalytes in Healthcare, Food, Zoology and Botany

PubMed Central

Wang, Tianqi; Ramnarayanan, Ashwin

2017-01-01

The growing demand for real time analysis of bioanalytes has spurred development in the field of wearable technology to offer non-invasive data collection at a low cost. The manufacturing processes for creating these sensing systems vary significantly by the material used, the type of sensors needed and the subject of study as well. The methods predominantly involve stretchable electronic sensors to monitor targets and transmit data mainly through flexible wires or short-range wireless communication devices. Capable of conformal contact, the application of wearable technology goes beyond the healthcare to fields of food, zoology and botany. With a brief review of wearable technology and its applications to various fields, we believe this mini review would be of interest to the reader in broad fields of materials, sensor development and areas where wearable sensors can provide data that are not available elsewhere. PMID:29267256

Real Time Analysis of Bioanalytes in Healthcare, Food, Zoology and Botany.

PubMed

Wang, Tianqi; Ramnarayanan, Ashwin; Cheng, Huanyu

2017-12-21

The growing demand for real time analysis of bioanalytes has spurred development in the field of wearable technology to offer non-invasive data collection at a low cost. The manufacturing processes for creating these sensing systems vary significantly by the material used, the type of sensors needed and the subject of study as well. The methods predominantly involve stretchable electronic sensors to monitor targets and transmit data mainly through flexible wires or short-range wireless communication devices. Capable of conformal contact, the application of wearable technology goes beyond the healthcare to fields of food, zoology and botany. With a brief review of wearable technology and its applications to various fields, we believe this mini review would be of interest to the reader in broad fields of materials, sensor development and areas where wearable sensors can provide data that are not available elsewhere.

Real-Time Variable Rate Spraying in Orchards and Vineyards: A Review

NASA Astrophysics Data System (ADS)

Wandkar, Sachin Vilas; Bhatt, Yogesh Chandra; Jain, H. K.; Nalawade, Sachin M.; Pawar, Shashikant G.

2018-06-01

Effective and efficient use of pesticides in the orchards is of concern since many years. With the conventional constant rate sprayers, equal dose of pesticide is applied to each tree. Since, there is great variation in size and shape of each tree in the orchard, trees gets either oversprayed or undersprayed. Real-time variable rate spraying technology offers pesticide application in accordance with tree size. With the help of suitable sensors, tree characteristics such as canopy volume, foliage density, etc. can be acquired and with the micro-processing unit coupled with proper algorithm, flow of electronic proportional valves can be controlled thus, controlling the flow rate of nozzles according to tree characteristics. Also, sensors can help in the detection of spaces in-between trees which allows to control the spray in spaces. Variable rate spraying helps in achieving precision in spraying operation especially inside orchards. This paper reviews the real-time variable rate spraying technology and efforts made by the various researchers for real-time variable application in the orchards and vineyards.

Real-Time Variable Rate Spraying in Orchards and Vineyards: A Review

NASA Astrophysics Data System (ADS)

Wandkar, Sachin Vilas; Bhatt, Yogesh Chandra; Jain, H. K.; Nalawade, Sachin M.; Pawar, Shashikant G.

2018-02-01

Effective and efficient use of pesticides in the orchards is of concern since many years. With the conventional constant rate sprayers, equal dose of pesticide is applied to each tree. Since, there is great variation in size and shape of each tree in the orchard, trees gets either oversprayed or undersprayed. Real-time variable rate spraying technology offers pesticide application in accordance with tree size. With the help of suitable sensors, tree characteristics such as canopy volume, foliage density, etc. can be acquired and with the micro-processing unit coupled with proper algorithm, flow of electronic proportional valves can be controlled thus, controlling the flow rate of nozzles according to tree characteristics. Also, sensors can help in the detection of spaces in-between trees which allows to control the spray in spaces. Variable rate spraying helps in achieving precision in spraying operation especially inside orchards. This paper reviews the real-time variable rate spraying technology and efforts made by the various researchers for real-time variable application in the orchards and vineyards.

Current Sensor Fault Diagnosis Based on a Sliding Mode Observer for PMSM Driven Systems

PubMed Central

Huang, Gang; Luo, Yi-Ping; Zhang, Chang-Fan; Huang, Yi-Shan; Zhao, Kai-Hui

2015-01-01

This paper proposes a current sensor fault detection method based on a sliding mode observer for the torque closed-loop control system of interior permanent magnet synchronous motors. First, a sliding mode observer based on the extended flux linkage is built to simplify the motor model, which effectively eliminates the phenomenon of salient poles and the dependence on the direct axis inductance parameter, and can also be used for real-time calculation of feedback torque. Then a sliding mode current observer is constructed in αβ coordinates to generate the fault residuals of the phase current sensors. The method can accurately identify abrupt gain faults and slow-variation offset faults in real time in faulty sensors, and the generated residuals of the designed fault detection system are not affected by the unknown input, the structure of the observer, and the theoretical derivation and the stability proof process are concise and simple. The RT-LAB real-time simulation is used to build a simulation model of the hardware in the loop. The simulation and experimental results demonstrate the feasibility and effectiveness of the proposed method. PMID:25970258

Feasibility of an anticipatory noncontact precrash restraint actuation system

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

Kercel, S.W.; Dress, W.B.

1995-12-31

The problem of providing an electronic warning of an impending crash to a precrash restraint system a fraction of a second before physical contact differs from more widely explored problems, such as providing several seconds of crash warning to a driver. One approach to precrash restraint sensing is to apply anticipatory system theory. This consists of nested simplified models of the system to be controlled and of the system`s environment. It requires sensory information to describe the ``current state`` of the system and the environment. The models use the sensory data to make a faster-than-real-time prediction about the near future.more » Anticipation theory is well founded but rarely used. A major problem is to extract real-time current-state information from inexpensive sensors. Providing current-state information to the nested models is the weakest element of the system. Therefore, sensors and real-time processing of sensor signals command the most attention in an assessment of system feasibility. This paper describes problem definition, potential ``showstoppers,`` and ways to overcome them. It includes experiments showing that inexpensive radar is a practical sensing element. It considers fast and inexpensive algorithms to extract information from sensor data.« less

A Real Time System for Multi-Sensor Image Analysis through Pyramidal Segmentation

DTIC Science & Technology

1992-01-30

A Real Time Syte for M~ulti- sensor Image Analysis S. E I0 through Pyramidal Segmentation/ / c •) L. Rudin, S. Osher, G. Koepfler, J.9. Morel 7. ytu...experiments with reconnaissance photography, multi- sensor satellite imagery, medical CT and MRI multi-band data have shown a great practi- cal potential...C ,SF _/ -- / WSM iS-I-0-d41-40450 $tltwt, kw" I (nor.- . Z-97- A real-time system for multi- sensor image analysis through pyramidal segmentation

IVHM Framework for Intelligent Integration for Vehicle Health Management

NASA Technical Reports Server (NTRS)

Paris, Deidre; Trevino, Luis C.; Watson, Michael D.

2005-01-01

Integrated Vehicle Health Management (IVHM) systems for aerospace vehicles, is the process of assessing, preserving, and restoring system functionality across flight and techniques with sensor and communication technologies for spacecraft that can generate responses through detection, diagnosis, reasoning, and adapt to system faults in support of Integrated Intelligent Vehicle Management (IIVM). These real-time responses allow the IIVM to modify the affected vehicle subsystem(s) prior to a catastrophic event. Furthermore, this framework integrates technologies which can provide a continuous, intelligent, and adaptive health state of a vehicle and use this information to improve safety and reduce costs of operations. Recent investments in avionics, health management, and controls have been directed towards IIVM. As this concept has matured, it has become clear that IIVM requires the same sensors and processing capabilities as the real-time avionics functions to support diagnosis of subsystem problems. New sensors have been proposed, in addition to augment the avionics sensors to support better system monitoring and diagnostics. As the designs have been considered, a synergy has been realized where the real-time avionics can utilize sensors proposed for diagnostics and prognostics to make better real-time decisions in response to detected failures. IIVM provides for a single system allowing modularity of functions and hardware across the vehicle. The framework that supports IIVM consists of 11 major on-board functions necessary to fully manage a space vehicle maintaining crew safety and mission objectives. These systems include the following: Guidance and Navigation; Communications and Tracking; Vehicle Monitoring; Information Transport and Integration; Vehicle Diagnostics; Vehicle Prognostics; Vehicle Mission Planning, Automated Repair and Replacement; Vehicle Control; Human Computer Interface; and Onboard Verification and Validation. Furthermore, the presented framework provides complete vehicle management which not only allows for increased crew safety and mission success through new intelligence capabilities, but also yields a mechanism for more efficient vehicle operations.

Advanced Engine Health Management Applications of the SSME Real-Time Vibration Monitoring System

NASA Technical Reports Server (NTRS)

Fiorucci, Tony R.; Lakin, David R., II; Reynolds, Tracy D.; Turner, James E. (Technical Monitor)

2000-01-01

The Real Time Vibration Monitoring System (RTVMS) is a 32-channel high speed vibration data acquisition and processing system developed at Marshall Space Flight Center (MSFC). It Delivers sample rates as high as 51,200 samples/second per channel and performs Fast Fourier Transform (FFT) processing via on-board digital signal processing (DSP) chips in a real-time format. Advanced engine health assessment is achieved by utilizing the vibration spectra to provide accurate sensor validation and enhanced engine vibration redlines. Discrete spectral signatures (such as synchronous) that are indicators of imminent failure can be assessed and utilized to mitigate catastrophic engine failures- a first in rocket engine health assessment. This paper is presented in viewgraph form.

Label-free CMOS bio sensor with on-chip noise reduction scheme for real-time quantitative monitoring of biomolecules.

PubMed

Seong-Jin Kim; Euisik Yoon

2012-06-01

We present a label-free CMOS field-effect transistor sensing array to detect the surface potential change affected by the negative charge in DNA molecules for real-time monitoring and quantification. The proposed CMOS bio sensor includes a new sensing pixel architecture implemented with correlated double sampling for reducing offset fixed pattern noise and 1/f noise of the sensing devices. We incorporated non-surface binding detection which allows real-time continuous monitoring of DNA concentrations without immobilizing them on the sensing surface. Various concentrations of 19-bp oligonucleotides solution can be discriminated using the prototype device fabricated in 1- μm double-poly double-metal standard CMOS process. The detection limit was measured as 1.1 ng/μl with a dynamic range of 40 dB and the transient response time was measured less than 20 seconds.

Virtual Sensor Test Instrumentation

NASA Technical Reports Server (NTRS)

Wang, Roy

2011-01-01

Virtual Sensor Test Instrumentation is based on the concept of smart sensor technology for testing with intelligence needed to perform sell-diagnosis of health, and to participate in a hierarchy of health determination at sensor, process, and system levels. A virtual sensor test instrumentation consists of five elements: (1) a common sensor interface, (2) microprocessor, (3) wireless interface, (4) signal conditioning and ADC/DAC (analog-to-digital conversion/ digital-to-analog conversion), and (5) onboard EEPROM (electrically erasable programmable read-only memory) for metadata storage and executable software to create powerful, scalable, reconfigurable, and reliable embedded and distributed test instruments. In order to maximize the efficient data conversion through the smart sensor node, plug-and-play functionality is required to interface with traditional sensors to enhance their identity and capabilities for data processing and communications. Virtual sensor test instrumentation can be accessible wirelessly via a Network Capable Application Processor (NCAP) or a Smart Transducer Interlace Module (STIM) that may be managed under real-time rule engines for mission-critical applications. The transducer senses the physical quantity being measured and converts it into an electrical signal. The signal is fed to an A/D converter, and is ready for use by the processor to execute functional transformation based on the sensor characteristics stored in a Transducer Electronic Data Sheet (TEDS). Virtual sensor test instrumentation is built upon an open-system architecture with standardized protocol modules/stacks to interface with industry standards and commonly used software. One major benefit for deploying the virtual sensor test instrumentation is the ability, through a plug-and-play common interface, to convert raw sensor data in either analog or digital form, to an IEEE 1451 standard-based smart sensor, which has instructions to program sensors for a wide variety of functions. The sensor data is processed in a distributed fashion across the network, providing a large pool of resources in real time to meet stringent latency requirements.

Distributed Peer-to-Peer Target Tracking in Wireless Sensor Networks

PubMed Central

Wang, Xue; Wang, Sheng; Bi, Dao-Wei; Ma, Jun-Jie

2007-01-01

Target tracking is usually a challenging application for wireless sensor networks (WSNs) because it is always computation-intensive and requires real-time processing. This paper proposes a practical target tracking system based on the auto regressive moving average (ARMA) model in a distributed peer-to-peer (P2P) signal processing framework. In the proposed framework, wireless sensor nodes act as peers that perform target detection, feature extraction, classification and tracking, whereas target localization requires the collaboration between wireless sensor nodes for improving the accuracy and robustness. For carrying out target tracking under the constraints imposed by the limited capabilities of the wireless sensor nodes, some practically feasible algorithms, such as the ARMA model and the 2-D integer lifting wavelet transform, are adopted in single wireless sensor nodes due to their outstanding performance and light computational burden. Furthermore, a progressive multi-view localization algorithm is proposed in distributed P2P signal processing framework considering the tradeoff between the accuracy and energy consumption. Finally, a real world target tracking experiment is illustrated. Results from experimental implementations have demonstrated that the proposed target tracking system based on a distributed P2P signal processing framework can make efficient use of scarce energy and communication resources and achieve target tracking successfully.

NASA End-to-End Data System /NEEDS/ information adaptive system - Performing image processing onboard the spacecraft

NASA Technical Reports Server (NTRS)

Kelly, W. L.; Howle, W. M.; Meredith, B. D.

1980-01-01

The Information Adaptive System (IAS) is an element of the NASA End-to-End Data System (NEEDS) Phase II and is focused toward onbaord image processing. Since the IAS is a data preprocessing system which is closely coupled to the sensor system, it serves as a first step in providing a 'Smart' imaging sensor. Some of the functions planned for the IAS include sensor response nonuniformity correction, geometric correction, data set selection, data formatting, packetization, and adaptive system control. The inclusion of these sensor data preprocessing functions onboard the spacecraft will significantly improve the extraction of information from the sensor data in a timely and cost effective manner and provide the opportunity to design sensor systems which can be reconfigured in near real time for optimum performance. The purpose of this paper is to present the preliminary design of the IAS and the plans for its development.

Sensor Fault Detection and Diagnosis Simulation of a Helicopter Engine in an Intelligent Control Framework

NASA Technical Reports Server (NTRS)

Litt, Jonathan; Kurtkaya, Mehmet; Duyar, Ahmet

1994-01-01

This paper presents an application of a fault detection and diagnosis scheme for the sensor faults of a helicopter engine. The scheme utilizes a model-based approach with real time identification and hypothesis testing which can provide early detection, isolation, and diagnosis of failures. It is an integral part of a proposed intelligent control system with health monitoring capabilities. The intelligent control system will allow for accommodation of faults, reduce maintenance cost, and increase system availability. The scheme compares the measured outputs of the engine with the expected outputs of an engine whose sensor suite is functioning normally. If the differences between the real and expected outputs exceed threshold values, a fault is detected. The isolation of sensor failures is accomplished through a fault parameter isolation technique where parameters which model the faulty process are calculated on-line with a real-time multivariable parameter estimation algorithm. The fault parameters and their patterns can then be analyzed for diagnostic and accommodation purposes. The scheme is applied to the detection and diagnosis of sensor faults of a T700 turboshaft engine. Sensor failures are induced in a T700 nonlinear performance simulation and data obtained are used with the scheme to detect, isolate, and estimate the magnitude of the faults.

LEADER - An integrated engine behavior and design analyses based real-time fault diagnostic expert system for Space Shuttle Main Engine (SSME)

NASA Technical Reports Server (NTRS)

Gupta, U. K.; Ali, M.

1989-01-01

The LEADER expert system has been developed for automatic learning tasks encompassing real-time detection, identification, verification, and correction of anomalous propulsion system operations, using a set of sensors to monitor engine component performance to ascertain anomalies in engine dynamics and behavior. Two diagnostic approaches are embodied in LEADER's architecture: (1) learning and identifying engine behavior patterns to generate novel hypotheses about possible abnormalities, and (2) the direction of engine sensor data processing to perform resoning based on engine design and functional knowledge, as well as the principles of the relevant mechanics and physics.

Noncontact vibration measurements using magnetoresistive sensing elements

NASA Astrophysics Data System (ADS)

Tomassini, R.; Rossi, G.

2016-06-01

Contactless instrumentations is more and more used in turbomachinery testing thanks to the non-intrusive character and the possibility to monitor all the components of the machine at the same time. Performances of blade tip timing (BTT) measurement systems, used for noncontact turbine blade vibration measurements, in terms of uncertainty and resolution are strongly affected by sensor characteristics and processing methods. The sensors used for BTT generate pulses, used for precise measurements of turbine blades time of arrival. Nowadays proximity sensors used in this application are based on optical, capacitive, eddy current and microwave measuring principle. Pressure sensors has been also tried. This paper summarizes the results achieved using a novel instrumentation based on the magnetoresistive sensing elements. The characterization of the novel probe has been already published. The measurement system was validated in test benches and in a real jet-engine comparing different sensor technologies. The whole instrumentation was improved. The work presented in this paper focuses on the current developments. In particular, attention is given to the data processing software and new sensor configurations.

Detecting the Influence of Spreading in Social Networks with Excitable Sensor Networks

PubMed Central

Pei, Sen; Tang, Shaoting; Zheng, Zhiming

2015-01-01

Detecting spreading outbreaks in social networks with sensors is of great significance in applications. Inspired by the formation mechanism of humans’ physical sensations to external stimuli, we propose a new method to detect the influence of spreading by constructing excitable sensor networks. Exploiting the amplifying effect of excitable sensor networks, our method can better detect small-scale spreading processes. At the same time, it can also distinguish large-scale diffusion instances due to the self-inhibition effect of excitable elements. Through simulations of diverse spreading dynamics on typical real-world social networks (Facebook, coauthor, and email social networks), we find that the excitable sensor networks are capable of detecting and ranking spreading processes in a much wider range of influence than other commonly used sensor placement methods, such as random, targeted, acquaintance and distance strategies. In addition, we validate the efficacy of our method with diffusion data from a real-world online social system, Twitter. We find that our method can detect more spreading topics in practice. Our approach provides a new direction in spreading detection and should be useful for designing effective detection methods. PMID:25950181

Maturation of Structural Health Management Systems for Solid Rocket Motors

NASA Technical Reports Server (NTRS)

Quing, Xinlin; Beard, Shawn; Zhang, Chang

2011-01-01

Concepts of an autonomous and automated space-compliant diagnostic system were developed for conditioned-based maintenance (CBM) of rocket motors for space exploration vehicles. The diagnostic system will provide real-time information on the integrity of critical structures on launch vehicles, improve their performance, and greatly increase crew safety while decreasing inspection costs. Using the SMART Layer technology as a basis, detailed procedures and calibration techniques for implementation of the diagnostic system were developed. The diagnostic system is a distributed system, which consists of a sensor network, local data loggers, and a host central processor. The system detects external impact to the structure. The major functions of the system include an estimate of impact location, estimate of impact force at impacted location, and estimate of the structure damage at impacted location. This system consists of a large-area sensor network, dedicated multiple local data loggers with signal processing and data analysis software to allow for real-time, in situ monitoring, and longterm tracking of structural integrity of solid rocket motors. Specifically, the system could provide easy installation of large sensor networks, onboard operation under harsh environments and loading, inspection of inaccessible areas without disassembly, detection of impact events and impact damage in real-time, and monitoring of a large area with local data processing to reduce wiring.

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.

Testing of a Fiber Optic Wear, Erosion and Regression Sensor

NASA Technical Reports Server (NTRS)

Korman, Valentin; Polzin, Kurt A.

2011-01-01

The nature of the physical processes and harsh environments associated with erosion and wear in propulsion environments makes their measurement and real-time rate quantification difficult. A fiber optic sensor capable of determining the wear (regression, erosion, ablation) associated with these environments has been developed and tested in a number of different applications to validate the technique. The sensor consists of two fiber optics that have differing attenuation coefficients and transmit light to detectors. The ratio of the two measured intensities can be correlated to the lengths of the fiber optic lines, and if the fibers and the host parent material in which they are embedded wear at the same rate the remaining length of fiber provides a real-time measure of the wear process. Testing in several disparate situations has been performed, with the data exhibiting excellent qualitative agreement with the theoretical description of the process and when a separate calibrated regression measurement is available good quantitative agreement is obtained as well. The light collected by the fibers can also be used to optically obtain the spectra and measure the internal temperature of the wear layer.

Multi-Wavelength Based Optical Density Sensor for Autonomous Monitoring of Microalgae

PubMed Central

Jia, Fei; Kacira, Murat; Ogden, Kimberly L.

2015-01-01

A multi-wavelength based optical density sensor unit was designed, developed, and evaluated to monitor microalgae growth in real time. The system consisted of five main components including: (1) laser diode modules as light sources; (2) photodiodes as detectors; (3) driver circuit; (4) flow cell; and (5) sensor housing temperature controller. The sensor unit was designed to be integrated into any microalgae culture system for both real time and non-real time optical density measurements and algae growth monitoring applications. It was shown that the sensor unit was capable of monitoring the dynamics and physiological changes of the microalgae culture in real-time. Algae biomass concentration was accurately estimated with optical density measurements at 650, 685 and 780 nm wavelengths used by the sensor unit. The sensor unit was able to monitor cell concentration as high as 1.05 g·L−1 (1.51 × 108 cells·mL−1) during the culture growth without any sample preparation for the measurements. Since high cell concentrations do not need to be diluted using the sensor unit, the system has the potential to be used in industrial microalgae cultivation systems for real time monitoring and control applications that can lead to improved resource use efficiency. PMID:26364640

Application of Raman Spectroscopy and Univariate Modelling As a Process Analytical Technology for Cell Therapy Bioprocessing

PubMed Central

Baradez, Marc-Olivier; Biziato, Daniela; Hassan, Enas; Marshall, Damian

2018-01-01

Cell therapies offer unquestionable promises for the treatment, and in some cases even the cure, of complex diseases. As we start to see more of these therapies gaining market authorization, attention is turning to the bioprocesses used for their manufacture, in particular the challenge of gaining higher levels of process control to help regulate cell behavior, manage process variability, and deliver product of a consistent quality. Many processes already incorporate the measurement of key markers such as nutrient consumption, metabolite production, and cell concentration, but these are often performed off-line and only at set time points in the process. Having the ability to monitor these markers in real-time using in-line sensors would offer significant advantages, allowing faster decision-making and a finer level of process control. In this study, we use Raman spectroscopy as an in-line optical sensor for bioprocess monitoring of an autologous T-cell immunotherapy model produced in a stirred tank bioreactor system. Using reference datasets generated on a standard bioanalyzer, we develop chemometric models from the Raman spectra for glucose, glutamine, lactate, and ammonia. These chemometric models can accurately monitor donor-specific increases in nutrient consumption and metabolite production as the primary T-cell transition from a recovery phase and begin proliferating. Using a univariate modeling approach, we then show how changes in peak intensity within the Raman spectra can be correlated with cell concentration and viability. These models, which act as surrogate markers, can be used to monitor cell behavior including cell proliferation rates, proliferative capacity, and transition of the cells to a quiescent phenotype. Finally, using the univariate models, we also demonstrate how Raman spectroscopy can be applied for real-time monitoring. The ability to measure these key parameters using an in-line Raman optical sensor makes it possible to have immediate feedback on process performance. This could help significantly improve cell therapy bioprocessing by allowing proactive decision-making based on real-time process data. Going forward, these types of in-line sensors also open up opportunities to improve bioprocesses further through concepts such as adaptive manufacturing. PMID:29556497

Application of Raman Spectroscopy and Univariate Modelling As a Process Analytical Technology for Cell Therapy Bioprocessing.

PubMed

Baradez, Marc-Olivier; Biziato, Daniela; Hassan, Enas; Marshall, Damian

2018-01-01

Cell therapies offer unquestionable promises for the treatment, and in some cases even the cure, of complex diseases. As we start to see more of these therapies gaining market authorization, attention is turning to the bioprocesses used for their manufacture, in particular the challenge of gaining higher levels of process control to help regulate cell behavior, manage process variability, and deliver product of a consistent quality. Many processes already incorporate the measurement of key markers such as nutrient consumption, metabolite production, and cell concentration, but these are often performed off-line and only at set time points in the process. Having the ability to monitor these markers in real-time using in-line sensors would offer significant advantages, allowing faster decision-making and a finer level of process control. In this study, we use Raman spectroscopy as an in-line optical sensor for bioprocess monitoring of an autologous T-cell immunotherapy model produced in a stirred tank bioreactor system. Using reference datasets generated on a standard bioanalyzer, we develop chemometric models from the Raman spectra for glucose, glutamine, lactate, and ammonia. These chemometric models can accurately monitor donor-specific increases in nutrient consumption and metabolite production as the primary T-cell transition from a recovery phase and begin proliferating. Using a univariate modeling approach, we then show how changes in peak intensity within the Raman spectra can be correlated with cell concentration and viability. These models, which act as surrogate markers, can be used to monitor cell behavior including cell proliferation rates, proliferative capacity, and transition of the cells to a quiescent phenotype. Finally, using the univariate models, we also demonstrate how Raman spectroscopy can be applied for real-time monitoring. The ability to measure these key parameters using an in-line Raman optical sensor makes it possible to have immediate feedback on process performance. This could help significantly improve cell therapy bioprocessing by allowing proactive decision-making based on real-time process data. Going forward, these types of in-line sensors also open up opportunities to improve bioprocesses further through concepts such as adaptive manufacturing.

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.

An In-situ Real-Time Optical Fiber Sensor Based on Surface Plasmon Resonance for Monitoring the Growth of TiO2 Thin Films

PubMed Central

Tsao, Yu-Chia; Tsai, Woo-Hu; Shih, Wen-Ching; Wu, Mu-Shiang

2013-01-01

An optical fiber sensor based on surface plasmon resonance (SPR) is proposed for monitoring the thickness of deposited nano-thin films. A side-polished multimode SPR optical fiber sensor with an 850 nm-LD is used as the transducing element for real-time monitoring of the deposited TiO2 thin films. The SPR optical fiber sensor was installed in the TiO2 sputtering system in order to measure the thickness of the deposited sample during TiO2 deposition. The SPR response declined in real-time in relation to the growth of the thickness of the TiO2 thin film. Our results show the same trend of the SPR response in real-time and in spectra taken before and after deposition. The SPR transmitted intensity changes by approximately 18.76% corresponding to 50 nm of deposited TiO2 thin film. We have shown that optical fiber sensors utilizing SPR have the potential for real-time monitoring of the SPR technology of nanometer film thickness. The compact size of the SPR fiber sensor enables it to be positioned inside the deposition chamber, and it could thus measure the film thickness directly in real-time. This technology also has potential application for monitoring the deposition of other materials. Moreover, in-situ real-time SPR optical fiber sensor technology is in inexpensive, disposable technique that has anti-interference properties, and the potential to enable on-line monitoring and monitoring of organic coatings. PMID:23881144

An in-situ real-time optical fiber sensor based on surface plasmon resonance for monitoring the growth of TiO2 thin films.

PubMed

Tsao, Yu-Chia; Tsai, Woo-Hu; Shih, Wen-Ching; Wu, Mu-Shiang

2013-07-23

An optical fiber sensor based on surface plasmon resonance (SPR) is proposed for monitoring the thickness of deposited nano-thin films. A side-polished multimode SPR optical fiber sensor with an 850 nm-LD is used as the transducing element for real-time monitoring of the deposited TiO2 thin films. The SPR optical fiber sensor was installed in the TiO2 sputtering system in order to measure the thickness of the deposited sample during TiO2 deposition. The SPR response declined in real-time in relation to the growth of the thickness of the TiO2 thin film. Our results show the same trend of the SPR response in real-time and in spectra taken before and after deposition. The SPR transmitted intensity changes by approximately 18.76% corresponding to 50 nm of deposited TiO2 thin film. We have shown that optical fiber sensors utilizing SPR have the potential for real-time monitoring of the SPR technology of nanometer film thickness. The compact size of the SPR fiber sensor enables it to be positioned inside the deposition chamber, and it could thus measure the film thickness directly in real-time. This technology also has potential application for monitoring the deposition of other materials. Moreover, in-situ real-time SPR optical fiber sensor technology is in inexpensive, disposable technique that has anti-interference properties, and the potential to enable on-line monitoring and monitoring of organic coatings.

Synthetic Foveal Imaging Technology

NASA Technical Reports Server (NTRS)

Hoenk, Michael; Monacos, Steve; Nikzad, Shouleh

2009-01-01

Synthetic Foveal imaging Technology (SyFT) is an emerging discipline of image capture and image-data processing that offers the prospect of greatly increased capabilities for real-time processing of large, high-resolution images (including mosaic images) for such purposes as automated recognition and tracking of moving objects of interest. SyFT offers a solution to the image-data processing problem arising from the proposed development of gigapixel mosaic focal-plane image-detector assemblies for very wide field-of-view imaging with high resolution for detecting and tracking sparse objects or events within narrow subfields of view. In order to identify and track the objects or events without the means of dynamic adaptation to be afforded by SyFT, it would be necessary to post-process data from an image-data space consisting of terabytes of data. Such post-processing would be time-consuming and, as a consequence, could result in missing significant events that could not be observed at all due to the time evolution of such events or could not be observed at required levels of fidelity without such real-time adaptations as adjusting focal-plane operating conditions or aiming of the focal plane in different directions to track such events. The basic concept of foveal imaging is straightforward: In imitation of a natural eye, a foveal-vision image sensor is designed to offer higher resolution in a small region of interest (ROI) within its field of view. Foveal vision reduces the amount of unwanted information that must be transferred from the image sensor to external image-data-processing circuitry. The aforementioned basic concept is not new in itself: indeed, image sensors based on these concepts have been described in several previous NASA Tech Briefs articles. Active-pixel integrated-circuit image sensors that can be programmed in real time to effect foveal artificial vision on demand are one such example. What is new in SyFT is a synergistic combination of recent advances in foveal imaging, computing, and related fields, along with a generalization of the basic foveal-vision concept to admit a synthetic fovea that is not restricted to one contiguous region of an image.

Efficient Skin Temperature Sensor and Stable Gel-Less Sticky ECG Sensor for a Wearable Flexible Healthcare Patch.

PubMed

Yamamoto, Yuki; Yamamoto, Daisuke; Takada, Makoto; Naito, Hiroyoshi; Arie, Takayuki; Akita, Seiji; Takei, Kuniharu

2017-09-01

Wearable, flexible healthcare devices, which can monitor health data to predict and diagnose disease in advance, benefit society. Toward this future, various flexible and stretchable sensors as well as other components are demonstrated by arranging materials, structures, and processes. Although there are many sensor demonstrations, the fundamental characteristics such as the dependence of a temperature sensor on film thickness and the impact of adhesive for an electrocardiogram (ECG) sensor are yet to be explored in detail. In this study, the effect of film thickness for skin temperature measurements, adhesive force, and reliability of gel-less ECG sensors as well as an integrated real-time demonstration is reported. Depending on the ambient conditions, film thickness strongly affects the precision of skin temperature measurements, resulting in a thin flexible film suitable for a temperature sensor in wearable device applications. Furthermore, by arranging the material composition, stable gel-less sticky ECG electrodes are realized. Finally, real-time simultaneous skin temperature and ECG signal recordings are demonstrated by attaching an optimized device onto a volunteer's chest. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Neuromorphic infrared focal plane performs sensor fusion on-plane local-contrast-enhancement spatial and temporal filtering

NASA Astrophysics Data System (ADS)

Massie, Mark A.; Woolaway, James T., II; Curzan, Jon P.; McCarley, Paul L.

1993-08-01

An infrared focal plane has been simulated, designed and fabricated which mimics the form and function of the vertebrate retina. The `Neuromorphic' focal plane has the capability of performing pixel-based sensor fusion and real-time local contrast enhancement, much like the response of the human eye. The device makes use of an indium antimonide detector array with a 3 - 5 micrometers spectral response, and a switched capacitor resistive network to compute a real-time 2D spatial average. This device permits the summation of other sensor outputs to be combined on-chip with the infrared detections of the focal plane itself. The resulting real-time analog processed information thus represents the combined information of many sensors with the advantage that analog spatial and temporal signal processing is performed at the focal plane. A Gaussian subtraction method is used to produce the pixel output which when displayed produces an image with enhanced edges, representing spatial and temporal derivatives in the scene. The spatial and temporal responses of the device are tunable during operation, permitting the operator to `peak up' the response of the array to spatial and temporally varying signals. Such an array adapts to ambient illumination conditions without loss of detection performance. This paper reviews the Neuromorphic infrared focal plane from initial operational simulations to detailed design characteristics, and concludes with a presentation of preliminary operational data for the device as well as videotaped imagery.

Radio frequency telemetry system for sensors and actuators

NASA Technical Reports Server (NTRS)

Simons, Rainee N. (Inventor); Miranda, Felix A. (Inventor)

2003-01-01

The present invention discloses and teaches apparatus for combining Radio Frequency (RF) technology with novel micro-inductor antennas and signal processing circuits for RF telemetry of real time, measured data, from microelectromechanical system (MEMS) sensors, through electromagnetic coupling with a remote powering/receiving device. Such technology has many applications, but is especially useful in the biomedical area.

Radio Frequency Telemetry System for Sensors and Actuators

NASA Technical Reports Server (NTRS)

Simons, Rainee N. (Inventor); Miranda, Felix A. (Inventor)

2003-01-01

The present invention discloses and teaches apparatus for combining Radio Frequency (RF) technology with novel micro-inductor antennas and signal processing circuits for RF telemetry of real time, measured data, from microelectromechanical system (MEMS) sensors, through electromagnetic coupling with a remote poweringheceiving device. Such technology has many applications, but is especially useful in the biomedical area.

Diameter sensors for tree-length harvesting systems

Treesearch

T.P. McDonald; Robert B. Rummer; T.E. Grift

2003-01-01

Most cut-to-length (CTL) harvesters provide sensors for measuring diameter of trees as they are cut and processed. Among other uses, this capability provides a data collection tool for marketing of logs in real time. Logs can be sorted and stacked based on up-to-date market information, then transportation systems optimized to route wood to proper destinations at...

A high sensitivity wear debris sensor using ferrite cores for online oil condition monitoring

NASA Astrophysics Data System (ADS)

Zhu, Xiaoliang; Zhong, Chong; Zhe, Jiang

2017-07-01

Detecting wear debris and measuring the increasing number of wear debris in lubrication oil can indicate abnormal machine wear well ahead of machine failure, and thus are indispensable for online machine health monitoring. A portable wear debris sensor with ferrite cores for online monitoring is presented. The sensor detects wear debris by measuring the inductance change of two planar coils wound around a pair of ferrite cores that make the magnetic flux denser and more uniform in the sensing channel, thereby improving the sensitivity of the sensor. Static testing results showed this wear debris sensor is capable of detecting 11 µm and 50 µm ferrous debris in 1 mm and 7 mm diameter fluidic pipes, respectively; such a high sensitivity has not been achieved before. Furthermore, a synchronized sampling method was also applied to reduce the data size and realize real-time data processing. Dynamic testing results demonstrated that the sensor is capable of detecting wear debris in real time with a high throughput of 750 ml min-1 the measured debris concentration is in good agreement with the actual concentration.

Arch-bridge Lift Process Monitoring by Using Packaged Optical Fibre Strain Sensors with Temperature Compensation

NASA Astrophysics Data System (ADS)

Mokhtar, M. R.; Sun, T.; Grattan, K. T. V.; Owens, K.; Kwasny, J.; Taylor, S. E.; Basheer, P. A. M.; Cleland, D.; Bai, Y.; Sonebi, M.; Davis, G.; Gupta, A.; Hogg, I.; Bell, B.; Doherty, W.; McKeague, S.; Moore, D.; Greeves, K.

2011-08-01

This paper presents a novel sensor design and packaging, specifically developed to allow fibre grating-based sensors to be used in harsh, in-the-field measurement conditions for accurate strain measurement, with full temperature compensation. After these sensors are carefully packaged and calibrated in the laboratory, they are installed onto the paragrid of a set of flat-packed concrete units, created specifically for forming a small-scale, lightweight and inexpensive flexi-arch bridge. During the arch-bridge lifting process, the sensors are used for real-time strain measurements to ensure the quality of the construction. During the work done, the sensors have demonstrated enhanced resilience when embedded in concrete structures, providing accurate and consistent strain measurements during the whole installation process and beyond into monitoring the integrity and use of the structure.

High-temperature optical fiber instrumentation for gas flow monitoring in gas turbine engines

NASA Astrophysics Data System (ADS)

Roberts, Adrian; May, Russell G.; Pickrell, Gary R.; Wang, Anbo

2002-02-01

In the design and testing of gas turbine engines, real-time data about such physical variables as temperature, pressure and acoustics are of critical importance. The high temperature environment experienced in the engines makes conventional electronic sensors devices difficult to apply. Therefore, there is a need for innovative sensors that can reliably operate under the high temperature conditions and with the desirable resolution and frequency response. A fiber optic high temperature sensor system for dynamic pressure measurement is presented in this paper. This sensor is based on a new sensor technology - the self-calibrated interferometric/intensity-based (SCIIB) sensor, recently developed at Virginia Tech. State-of-the-art digital signal processing (DSP) methods are applied to process the signal from the sensor to acquire high-speed frequency response.

A smart ROV solution for ship hull and harbor inspection

NASA Astrophysics Data System (ADS)

Reed, Scott; Wood, Jon; Vazquez, Jose; Mignotte, Pierre-Yves; Privat, Benjamin

2010-04-01

Hull and harbor infrastructure inspections are frequently performed manually and involve quite a bit of risk and human and monetary resources. In any kind of threat and resource constrained environment, this involves unacceptable levels of risk and cost. Modern Remotely Operated Vehicles are highly refined machines that provide features and capabilities previously unavailable. Operations once carried out by divers can now be carried out more quickly, efficiently and safely by smart enabled ROVs. ROVs are rapidly deployable and capable of continuous, reliable operations in adverse conditions. They also provide a stable platform on which multiple sensors may be mounted and utilized to meet the harbor inspection problem. Automated Control software provides ROV's and their pilots with the capability to inspect complex, constrained environments such as those found in a harbor region. This application and the user interface allow the ROV to automatically conduct complex maneuvers relative to the area being inspected and relieves the training requirements and work load for the pilot, allowing he or she to focus on the primary task of survey, inspection and looking for possible threats (such as IEDs, Limpet Mines, signs of sabotage, etc). Real-time sensor processing tools can be integrated into the smart ROV solution to assist the operator. Automatic Target Recognition (ATR) algorithms are used to search through the sensor data collected by the ROV in real time. These algorithms provide immediate feedback on possible threats and notify the operator of regions that may require manual verification. Sensor data (sonar or video) is also mosaiced, providing the operator with real-time situational awareness and a coverage map of the hull or seafloor. Detected objects may also be placed in the context of the large scale characteristics of the hull (or bottom or pilings) and localized. Within the complex areas such as the harbor pier pilings and the running gear of the ship, real-time 3D reconstruction techniques may be used to process profiling sonar data for similar applications. An observation class ROV equipped with sensors, running an operator in the loop, Automated Surface-Computer (ASC) system can inspect an entire harbor region. These systems can autonomously provide coverage information, identify possible threats and provide the level of control required to operate in confined environments. The system may be controlled autonomously or by the operator. Previous inspection results may also be used for change detection applications. This paper presents the SeeByte Smart ROV and sensor processing technology relevant to the harbor inspection problem. These technologies have been tested extensively in real world applications and trials and are demonstrated using real data and examples.

Modification and fixed-point analysis of a Kalman filter for orientation estimation based on 9D inertial measurement unit data.

PubMed

Brückner, Hans-Peter; Spindeldreier, Christian; Blume, Holger

2013-01-01

A common approach for high accuracy sensor fusion based on 9D inertial measurement unit data is Kalman filtering. State of the art floating-point filter algorithms differ in their computational complexity nevertheless, real-time operation on a low-power microcontroller at high sampling rates is not possible. This work presents algorithmic modifications to reduce the computational demands of a two-step minimum order Kalman filter. Furthermore, the required bit-width of a fixed-point filter version is explored. For evaluation real-world data captured using an Xsens MTx inertial sensor is used. Changes in computational latency and orientation estimation accuracy due to the proposed algorithmic modifications and fixed-point number representation are evaluated in detail on a variety of processing platforms enabling on-board processing on wearable sensor platforms.

Optimal Sparse Upstream Sensor Placement for Hydrokinetic Turbines

NASA Astrophysics Data System (ADS)

Cavagnaro, Robert; Strom, Benjamin; Ross, Hannah; Hill, Craig; Polagye, Brian

2016-11-01

Accurate measurement of the flow field incident upon a hydrokinetic turbine is critical for performance evaluation during testing and setting boundary conditions in simulation. Additionally, turbine controllers may leverage real-time flow measurements. Particle image velocimetry (PIV) is capable of rendering a flow field over a wide spatial domain in a controlled, laboratory environment. However, PIV's lack of suitability for natural marine environments, high cost, and intensive post-processing diminish its potential for control applications. Conversely, sensors such as acoustic Doppler velocimeters (ADVs), are designed for field deployment and real-time measurement, but over a small spatial domain. Sparsity-promoting regression analysis such as LASSO is utilized to improve the efficacy of point measurements for real-time applications by determining optimal spatial placement for a small number of ADVs using a training set of PIV velocity fields and turbine data. The study is conducted in a flume (0.8 m2 cross-sectional area, 1 m/s flow) with laboratory-scale axial and cross-flow turbines. Predicted turbine performance utilizing the optimal sparse sensor network and associated regression model is compared to actual performance with corresponding PIV measurements.

Achieving Real-Time Tracking Mobile Wireless Sensors Using SE-KFA

NASA Astrophysics Data System (ADS)

Kadhim Hoomod, Haider, Dr.; Al-Chalabi, Sadeem Marouf M.

2018-05-01

Nowadays, Real-Time Achievement is very important in different fields, like: Auto transport control, some medical applications, celestial body tracking, controlling agent movements, detections and monitoring, etc. This can be tested by different kinds of detection devices, which named "sensors" as such as: infrared sensors, ultrasonic sensor, radars in general, laser light sensor, and so like. Ultrasonic Sensor is the most fundamental one and it has great impact and challenges comparing with others especially when navigating (as an agent). In this paper, concerning to the ultrasonic sensor, sensor(s) detecting and delimitation by themselves then navigate inside a limited area to estimating Real-Time using Speed Equation with Kalman Filter Algorithm as an intelligent estimation algorithm. Then trying to calculate the error comparing to the factual rate of tracking. This paper used Ultrasonic Sensor HC-SR04 with Arduino-UNO as Microcontroller.

Multisensory architectures for action-oriented perception

NASA Astrophysics Data System (ADS)

Alba, L.; Arena, P.; De Fiore, S.; Listán, J.; Patané, L.; Salem, A.; Scordino, G.; Webb, B.

2007-05-01

In order to solve the navigation problem of a mobile robot in an unstructured environment a versatile sensory system and efficient locomotion control algorithms are necessary. In this paper an innovative sensory system for action-oriented perception applied to a legged robot is presented. An important problem we address is how to utilize a large variety and number of sensors, while having systems that can operate in real time. Our solution is to use sensory systems that incorporate analog and parallel processing, inspired by biological systems, to reduce the required data exchange with the motor control layer. In particular, as concerns the visual system, we use the Eye-RIS v1.1 board made by Anafocus, which is based on a fully parallel mixed-signal array sensor-processor chip. The hearing sensor is inspired by the cricket hearing system and allows efficient localization of a specific sound source with a very simple analog circuit. Our robot utilizes additional sensors for touch, posture, load, distance, and heading, and thus requires customized and parallel processing for concurrent acquisition. Therefore a Field Programmable Gate Array (FPGA) based hardware was used to manage the multi-sensory acquisition and processing. This choice was made because FPGAs permit the implementation of customized digital logic blocks that can operate in parallel allowing the sensors to be driven simultaneously. With this approach the multi-sensory architecture proposed can achieve real time capabilities.

An Innovative Optical Sensor for the Online Monitoring and Control of Biomass Concentration in a Membrane Bioreactor System for Lactic Acid Production

PubMed Central

Fan, Rong; Ebrahimi, Mehrdad; Quitmann, Hendrich; Aden, Matthias; Czermak, Peter

2016-01-01

Accurate real-time process control is necessary to increase process efficiency, and optical sensors offer a competitive solution because they provide diverse system information in a noninvasive manner. We used an innovative scattered light sensor for the online monitoring of biomass during lactic acid production in a membrane bioreactor system because biomass determines productivity in this type of process. The upper limit of the measurement range in fermentation broth containing Bacillus coagulans was ~2.2 g·L−1. The specific cell growth rate (µ) during the exponential phase was calculated using data representing the linear range (cell density ≤ 0.5 g·L−1). The results were consistently and reproducibly more accurate than offline measurements of optical density and cell dry weight, because more data were gathered in real-time over a shorter duration. Furthermore, µmax was measured under different filtration conditions (transmembrane pressure 0.3–1.2 bar, crossflow velocity 0.5–1.5 m·s−1), showing that energy input had no significant impact on cell growth. Cell density was monitored using the sensor during filtration and was maintained at a constant level by feeding with glucose according to the fermentation kinetics. Our novel sensor is therefore suitable for integration into control strategies for continuous fermentation in membrane bioreactor systems. PMID:27007380

A GPS-based Real-time Road Traffic Monitoring System

NASA Astrophysics Data System (ADS)

Tanti, Kamal Kumar

In recent years, monitoring systems are astonishingly inclined towards ever more automatic; reliably interconnected, distributed and autonomous operation. Specifically, the measurement, logging, data processing and interpretation activities may be carried out by separate units at different locations in near real-time. The recent evolution of mobile communication devices and communication technologies has fostered a growing interest in the GIS & GPS-based location-aware systems and services. This paper describes a real-time road traffic monitoring system based on integrated mobile field devices (GPS/GSM/IOs) working in tandem with advanced GIS-based application software providing on-the-fly authentications for real-time monitoring and security enhancement. The described system is developed as a fully automated, continuous, real-time monitoring system that employs GPS sensors and Ethernet and/or serial port communication techniques are used to transfer data between GPS receivers at target points and a central processing computer. The data can be processed locally or remotely based on the requirements of client’s satisfaction. Due to the modular architecture of the system, other sensor types may be supported with minimal effort. Data on the distributed network & measurements are transmitted via cellular SIM cards to a Control Unit, which provides for post-processing and network management. The Control Unit may be remotely accessed via an Internet connection. The new system will not only provide more consistent data about the road traffic conditions but also will provide methods for integrating with other Intelligent Transportation Systems (ITS). For communication between the mobile device and central monitoring service GSM technology is used. The resulting system is characterized by autonomy, reliability and a high degree of automation.

Study of weld quality real-time monitoring system for auto-body assembly

NASA Astrophysics Data System (ADS)

Xu, Jun; Li, Yong-Bing; Chen, Guan-Long

2005-12-01

Resistance spot welding (RSW) is widely used for the auto-body assembly in automotive industry. But RSW suffers from a major problem of inconsistent quality from weld to weld. The major problem is the complexity of the basic process that may involve material coatings, electrode force, electrode wear, fit up, etc. Therefore weld quality assurance is still a big challenge and goal. Electrode displacement has proved to be a particularly useful signal which correlates well with weld quality. This paper introduces a novel auto-body spot weld quality monitoring system which uses electrode displacement as the quality parameter. This system chooses the latest laser displacement sensor with high resolution to measure the real-time electrode displacement. It solves the interference problem of sensor mounting by designing special fixture, and can be successfully applied on the portable welding machine. It is capable of evaluating weld quality and making diagnosis of process variations such as surface asperities, shunting, worn electrode and weld expansion with real-time electrode displacement. As proved by application in the workshop, the monitoring system has good stability and reliability, and is qualified for monitoring weld quality in process.

Portable Magnetic Gradiometer for Real-Time Localization and Classification of Unexploded Ordnance

DTIC Science & Technology

2006-09-01

classification (DLC) of Unexploded Ordnance (UXO). The portable gradiometer processes data from triaxial fluxgate magnetometers to develop sets of...low-noise (ង pTrms/√Hz) fluxgate -type Triaxial Magnetometers (TM). Paired sets of TMs comprise magnetic gradient sensor “axes” of the array that...channels of analog B-field data. The digitizers can be locked to the Global Positioning System to provide; a) Precise sensor channel timing, and b

Optical signal processing of spatially distributed sensor data in smart structures

NASA Technical Reports Server (NTRS)

Bennett, K. D.; Claus, R. O.; Murphy, K. A.; Goette, A. M.

1989-01-01

Smart structures which contain dense two- or three-dimensional arrays of attached or embedded sensor elements inherently require signal multiplexing and processing capabilities to permit good spatial data resolution as well as the adequately short calculation times demanded by real time active feedback actuator drive circuitry. This paper reports the implementation of an in-line optical signal processor and its application in a structural sensing system which incorporates multiple discrete optical fiber sensor elements. The signal processor consists of an array of optical fiber couplers having tailored s-parameters and arranged to allow gray code amplitude scaling of sensor inputs. The use of this signal processor in systems designed to indicate the location of distributed strain and damage in composite materials, as well as to quantitatively characterize that damage, is described. Extension of similar signal processing methods to more complicated smart materials and structures applications are discussed.

Monitoring Street-Level Spatial-Temporal Variations of Carbon Monoxide in Urban Settings Using a Wireless Sensor Network (WSN) Framework

PubMed Central

Wen, Tzai-Hung; Jiang, Joe-Air; Sun, Chih-Hong; Juang, Jehn-Yih; Lin, Tzu-Shiang

2013-01-01

Air pollution has become a severe environmental problem due to urbanization and heavy traffic. Monitoring street-level air quality is an important issue, but most official monitoring stations are installed to monitor large-scale air quality conditions, and their limited spatial resolution cannot reflect the detailed variations in air quality that may be induced by traffic jams. By deploying wireless sensors on crossroads and main roads, this study established a pilot framework for a wireless sensor network (WSN)-based real-time monitoring system to understand street-level spatial-temporal changes of carbon monoxide (CO) in urban settings. The system consists of two major components. The first component is the deployment of wireless sensors. We deployed 44 sensor nodes, 40 transmitter nodes and four gateway nodes in this study. Each sensor node includes a signal processing module, a CO sensor and a wireless communication module. In order to capture realistic human exposure to traffic pollutants, all sensors were deployed at a height of 1.5 m on lampposts and traffic signs. The study area covers a total length of 1.5 km of Keelung Road in Taipei City. The other component is a map-based monitoring platform for sensor data visualization and manipulation in time and space. Using intensive real-time street-level monitoring framework, we compared the spatial-temporal patterns of air pollution in different time periods. Our results capture four CO concentration peaks throughout the day at the location, which was located along an arterial and nearby traffic sign. The hourly average could reach 5.3 ppm from 5:00 pm to 7:00 pm due to the traffic congestion. The proposed WSN-based framework captures detailed ground information and potential risk of human exposure to traffic-related air pollution. It also provides street-level insights into real-time monitoring for further early warning of air pollution and urban environmental management. PMID:24287859

Monitoring street-level spatial-temporal variations of carbon monoxide in urban settings using a wireless sensor network (WSN) framework.

PubMed

Wen, Tzai-Hung; Jiang, Joe-Air; Sun, Chih-Hong; Juang, Jehn-Yih; Lin, Tzu-Shiang

2013-11-27

Air pollution has become a severe environmental problem due to urbanization and heavy traffic. Monitoring street-level air quality is an important issue, but most official monitoring stations are installed to monitor large-scale air quality conditions, and their limited spatial resolution cannot reflect the detailed variations in air quality that may be induced by traffic jams. By deploying wireless sensors on crossroads and main roads, this study established a pilot framework for a wireless sensor network (WSN)-based real-time monitoring system to understand street-level spatial-temporal changes of carbon monoxide (CO) in urban settings. The system consists of two major components. The first component is the deployment of wireless sensors. We deployed 44 sensor nodes, 40 transmitter nodes and four gateway nodes in this study. Each sensor node includes a signal processing module, a CO sensor and a wireless communication module. In order to capture realistic human exposure to traffic pollutants, all sensors were deployed at a height of 1.5 m on lampposts and traffic signs. The study area covers a total length of 1.5 km of Keelung Road in Taipei City. The other component is a map-based monitoring platform for sensor data visualization and manipulation in time and space. Using intensive real-time street-level monitoring framework, we compared the spatial-temporal patterns of air pollution in different time periods. Our results capture four CO concentration peaks throughout the day at the location, which was located along an arterial and nearby traffic sign. The hourly average could reach 5.3 ppm from 5:00 pm to 7:00 pm due to the traffic congestion. The proposed WSN-based framework captures detailed ground information and potential risk of human exposure to traffic-related air pollution. It also provides street-level insights into real-time monitoring for further early warning of air pollution and urban environmental management.

High-Speed Scanning Interferometer Using CMOS Image Sensor and FPGA Based on Multifrequency Phase-Tracking Detection

NASA Technical Reports Server (NTRS)

Ohara, Tetsuo

2012-01-01

A sub-aperture stitching optical interferometer can provide a cost-effective solution for an in situ metrology tool for large optics; however, the currently available technologies are not suitable for high-speed and real-time continuous scan. NanoWave s SPPE (Scanning Probe Position Encoder) has been proven to exhibit excellent stability and sub-nanometer precision with a large dynamic range. This same technology can transform many optical interferometers into real-time subnanometer precision tools with only minor modification. The proposed field-programmable gate array (FPGA) signal processing concept, coupled with a new-generation, high-speed, mega-pixel CMOS (complementary metal-oxide semiconductor) image sensor, enables high speed (>1 m/s) and real-time continuous surface profiling that is insensitive to variation of pixel sensitivity and/or optical transmission/reflection. This is especially useful for large optics surface profiling.

SoilNet - A hybrid underground wireless sensor network for near real-time monitoring of hydrological processes

NASA Astrophysics Data System (ADS)

Bogena, H. R.; Huisman, S.; Rosenbaum, U.; Wuethen, A.; Vereecken, H.

2009-04-01

Wireless sensor network technology allows near real-time monitoring of soil properties with a high spatial and temporal resolution for observing hydrological processes in small watersheds. The novel wireless sensor network SoilNet uses the low-cost ZigBee radio network for communication and a hybrid topology with a mixture of underground end devices each wired to several soil sensors and aboveground router devices. The SoilNet sensor network consists of soil water content, salinity and temperature sensors attached to end devices by cables, router devices and a coordinator device. The end devices are buried in the soil and linked wirelessly with nearby aboveground router devices. This ZigBee network design considers channel errors, delays, packet losses, and power and topology constraints. In order to conserve battery power, a reactive routing protocol is used that determines a new route only when it is required. The sensor network is also able to react to external influences, e.g. the occurrence of precipitation. The SoilNet communicator, routing and end devices have been developed by the Forschungszentrum Juelich and will be marketed through external companies. Simultaneously, we have also developed a data management and visualisation system. Recently, a small forest catchment Wüstebach (27 ha) was instrumented with 50 end devices and more than 400 soil sensors in the frame of the TERENO-RUR hydrological observatory. We will present first results of this large sensor network both in terms of spatial-temporal variations in soil water content and the performance of the sensor network (e.g. network stability and power use).

Multivariable control of a rapid thermal processor using ultrasonic sensors

NASA Astrophysics Data System (ADS)

Dankoski, Paul C. P.

The semiconductor manufacturing industry faces the need for tighter control of thermal budget and process variations as circuit feature sizes decrease. Strategies to meet this need include supervisory control, run-to-run control, and real-time feedback control. Typically, the level of control chosen depends upon the actuation and sensing available. Rapid Thermal Processing (RTP) is one step of the manufacturing cycle requiring precise temperature control and hence real-time feedback control. At the outset of this research, the primary ingredient lacking from in-situ RTP temperature control was a suitable sensor. This research looks at an alternative to the traditional approach of pyrometry, which is limited by the unknown and possibly time-varying wafer emissivity. The technique is based upon the temperature dependence of the propagation time of an acoustic wave in the wafer. The aim of this thesis is to evaluate the ultrasonic sensors as a potentially viable sensor for control in RTP. To do this, an experimental implementation was developed at the Center for Integrated Systems. Because of the difficulty in applying a known temperature standard in an RTP environment, calibration to absolute temperature is nontrivial. Given reference propagation delays, multivariable model-based feedback control is applied to the system. The modelling and implementation details are described. The control techniques have been applied to a number of research processes including rapid thermal annealing and rapid thermal crystallization of thin silicon films on quartz/glass substrates.

The use of reverse iontophoresis based surface plasmon resonance for the development of a noninvasive real time transdermal biomarker sensor

NASA Astrophysics Data System (ADS)

Gupta, Niraj K.; Hwang, Yongsoon; Cameron, Brent D.

2016-03-01

Recent developments in the identification of biomarkers offer a potential means to facilitate early disease detection, gauge treatment in drug therapy clinical trials, and to assess the impact of fatigue and/or stress as related to human physical and cognitive performance. For practical implementation, however, real-time sensing and quantification of such physiological biomarkers is preferred. Some key aspects in this process are continuous sample collection and real time detection. Traditionally, blood is considered the gold standard for samples but frequent phlebotomy is painful and inconvenient. Other sources like saliva and passive sweat cannot be precisely controlled and are affected by other limitations. Some of these can be addressed by reverse iontophoresis which is a noninvasive technique capable of facilitating controlled transport of biomolecules up to 20kDa in size across the skin barrier by passing a low level current between two dermal electrodes. The samples collected at the electrode site can then be monitored at site or transported via a microfluidic channel towards a sensor. In the case reported here, the sensor is based on surface plasmon resonance (SPR), which is a label free, real time, and highly sensitive optical sensing technique. The real time SPR detection of targeted biomarkers is then achieved through the use of aptamer surface modification. In this experiment, extraction and detection of orexin A, a stress related biomarker, is used for demonstration purposes.

Automatic parquet block sorting using real-time spectral classification

NASA Astrophysics Data System (ADS)

Astrom, Anders; Astrand, Erik; Johansson, Magnus

1999-03-01

This paper presents a real-time spectral classification system based on the PGP spectrograph and a smart image sensor. The PGP is a spectrograph which extracts the spectral information from a scene and projects the information on an image sensor, which is a method often referred to as Imaging Spectroscopy. The classification is based on linear models and categorizes a number of pixels along a line. Previous systems adopting this method have used standard sensors, which often resulted in poor performance. The new system, however, is based on a patented near-sensor classification method, which exploits analogue features on the smart image sensor. The method reduces the enormous amount of data to be processed at an early stage, thus making true real-time spectral classification possible. The system has been evaluated on hardwood parquet boards showing very good results. The color defects considered in the experiments were blue stain, white sapwood, yellow decay and red decay. In addition to these four defect classes, a reference class was used to indicate correct surface color. The system calculates a statistical measure for each parquet block, giving the pixel defect percentage. The patented method makes it possible to run at very high speeds with a high spectral discrimination ability. Using a powerful illuminator, the system can run with a line frequency exceeding 2000 line/s. This opens up the possibility to maintain high production speed and still measure with good resolution.

A low-cost, portable optical sensing system with wireless communication compatible of real-time and remote detection of dissolved ammonia

NASA Astrophysics Data System (ADS)

Deng, Shijie; Doherty, William; McAuliffe, Michael AP; Salaj-Kosla, Urszula; Lewis, Liam; Huyet, Guillaume

2016-06-01

A low-cost and portable optical chemical sensor based ammonia sensing system that is capable of detecting dissolved ammonia up to 5 ppm is presented. In the system, an optical chemical sensor is designed and fabricated for sensing dissolved ammonia concentrations. The sensor uses eosin as the fluorescence dye which is immobilized on the glass substrate by a gas-permeable protection layer. A compact module is developed to hold the optical components, and a battery powered micro-controller system is designed to read out and process the data measured. The system operates without the requirement of laboratory instruments that makes it cost effective and highly portable. Moreover, the calculated results in the system can be transmitted to a PC wirelessly, which allows the remote and real-time monitoring of dissolved ammonia.

Suitability of Smartphone Inertial Sensors for Real-Time Biofeedback Applications.

PubMed

Kos, Anton; Tomažič, Sašo; Umek, Anton

2016-02-27

This article studies the suitability of smartphones with built-in inertial sensors for biofeedback applications. Biofeedback systems use various sensors to measure body functions and parameters. These sensor data are analyzed, and the results are communicated back to the user, who then tries to act on the feedback signals. Smartphone inertial sensors can be used to capture body movements in biomechanical biofeedback systems. These sensors exhibit various inaccuracies that induce significant angular and positional errors. We studied deterministic and random errors of smartphone accelerometers and gyroscopes, primarily focusing on their biases. Based on extensive measurements, we determined accelerometer and gyroscope noise models and bias variation ranges. Then, we compiled a table of predicted positional and angular errors under various biofeedback system operation conditions. We suggest several bias compensation options that are suitable for various examples of use in real-time biofeedback applications. Measurements within the developed experimental biofeedback application show that under certain conditions, even uncompensated sensors can be used for real-time biofeedback. For general use, especially for more demanding biofeedback applications, sensor biases should be compensated. We are convinced that real-time biofeedback systems based on smartphone inertial sensors are applicable to many similar examples in sports, healthcare, and other areas.

Suitability of Smartphone Inertial Sensors for Real-Time Biofeedback Applications

PubMed Central

Kos, Anton; Tomažič, Sašo; Umek, Anton

2016-01-01

This article studies the suitability of smartphones with built-in inertial sensors for biofeedback applications. Biofeedback systems use various sensors to measure body functions and parameters. These sensor data are analyzed, and the results are communicated back to the user, who then tries to act on the feedback signals. Smartphone inertial sensors can be used to capture body movements in biomechanical biofeedback systems. These sensors exhibit various inaccuracies that induce significant angular and positional errors. We studied deterministic and random errors of smartphone accelerometers and gyroscopes, primarily focusing on their biases. Based on extensive measurements, we determined accelerometer and gyroscope noise models and bias variation ranges. Then, we compiled a table of predicted positional and angular errors under various biofeedback system operation conditions. We suggest several bias compensation options that are suitable for various examples of use in real-time biofeedback applications. Measurements within the developed experimental biofeedback application show that under certain conditions, even uncompensated sensors can be used for real-time biofeedback. For general use, especially for more demanding biofeedback applications, sensor biases should be compensated. We are convinced that real-time biofeedback systems based on smartphone inertial sensors are applicable to many similar examples in sports, healthcare, and other areas. PMID:26927125

PEDOT:PSS-Based Piezo-Resistive Sensors Applied to Reinforcement Glass Fibres for in Situ Measurement during the Composite Material Weaving Process

PubMed Central

Trifigny, Nicolas; Kelly, Fern M.; Cochrane, Cédric; Boussu, François; Koncar, Vladan; Soulat, Damien

2013-01-01

The quality of fibrous reinforcements used in composite materials can be monitored during the weaving process. Fibrous sensors previously developed in our laboratory, based on PEDOT:PSS, have been adapted so as to directly measure the mechanical stress on fabrics under static or dynamic conditions. The objective of our research has been to develop new sensor yarns, with the ability to locally detect mechanical stresses all along the warp or weft yarn. This local detection is undertaken inside the weaving loom in real time during the weaving process. Suitable electronic devices have been designed in order to record in situ measurements delivered by this new fibrous sensor yarn. PMID:23959238

Real-Time Data Processing Onboard Remote Sensor Platforms: Annual Review #3 Data Package

NASA Technical Reports Server (NTRS)

Cook, Sid; Harsanyi, Joe

2003-01-01

The current program status reviewed by this viewgraph presentation includes: 1) New Evaluation Results; 2) Algorithm Improvement Investigations; 3) Electronic Hardware Design; 4) Software Hardware Interface Design.

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.

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 scale-up field experiment for the monitoring of a burning process using chemical, audio, and video sensors.

PubMed

Stavrakakis, P; Agapiou, A; Mikedi, K; Karma, S; Statheropoulos, M; Pallis, G C; Pappa, A

2014-01-01

Fires are becoming more violent and frequent resulting in major economic losses and long-lasting effects on communities and ecosystems; thus, efficient fire monitoring is becoming a necessity. A novel triple multi-sensor approach was developed for monitoring and studying the burning of dry forest fuel in an open field scheduled experiment; chemical, optical, and acoustical sensors were combined to record the fire spread. The results of this integrated field campaign for real-time monitoring of the fire event are presented and discussed. Chemical analysis, despite its limitations, corresponded to the burning process with a minor time delay. Nevertheless, the evolution profile of CO2, CO, NO, and O2 were detected and monitored. The chemical monitoring of smoke components enabled the observing of the different fire phases (flaming, smoldering) based on the emissions identified in each phase. The analysis of fire acoustical signals presented accurate and timely response to the fire event. In the same content, the use of a thermographic camera, for monitoring the biomass burning, was also considerable (both profiles of the intensities of average gray and red component greater than 230) and presented similar promising potentials to audio results. Further work is needed towards integrating sensors signals for automation purposes leading to potential applications in real situations.

Space based optical staring sensor LOS determination and calibration using GCPs observation

NASA Astrophysics Data System (ADS)

Chen, Jun; An, Wei; Deng, Xinpu; Yang, Jungang; Sha, Zhichao

2016-10-01

Line of sight (LOS) attitude determination and calibration is the key prerequisite of tracking and location of targets in space based infrared (IR) surveillance systems (SBIRS) and the LOS determination and calibration of staring sensor is one of the difficulties. This paper provides a novel methodology for removing staring sensor bias through the use of Ground Control Points (GCPs) detected in the background field of the sensor. Based on researching the imaging model and characteristics of the staring sensor of SBIRS geostationary earth orbit part (GEO), the real time LOS attitude determination and calibration algorithm using landmark control point is proposed. The influential factors (including the thermal distortions error, assemble error, and so on) of staring sensor LOS attitude error are equivalent to bias angle of LOS attitude. By establishing the observation equation of GCPs and the state transition equation of bias angle, and using an extend Kalman filter (EKF), the real time estimation of bias angle and the high precision sensor LOS attitude determination and calibration are achieved. The simulation results show that the precision and timeliness of the proposed algorithm meet the request of target tracking and location process in space based infrared surveillance system.

A novel inter-fibre light coupling sensor probe using plastic optical fibre for ethanol concentration monitoring at initial production rate

NASA Astrophysics Data System (ADS)

Memon, Sanober F.; Lewis, Elfed; Pembroke, J. Tony; Chowdhry, Bhawani S.

2017-04-01

A novel, low cost and highly sensitive optical fibre probe sensor for concentration measurement of ethanol solvent (C2H5OH) corresponding to bio-ethanol production rate by an algae is reported. The principle of operation of the sensor is based on inter-fibre light coupling through an evanescent field interaction to couple the light between two multimode fibres mounted parallel to each other at a minimum possible separation i.e. < 1mm. The sensor was fabricated using a low cost 1000um plastic optical fibre (POF) and was characterized for real time measurement in the broadband spectrum including visible and near infra-red. The wavelength dependency of this sensor design was also investigated by post processing analysis of real time data and hence the optimum wavelength range determined. The proposed sensor has shown significant response in the range of 0.005 - 0.1 %v/v (%volume/volume or volume concentration) which depicts the high sensitivity for monitoring very minute changes in concentration corresponding refractive index changes of the solution. Numerically, sensor has shown the sensitivity of 21945 intensity counts/%v/v or 109.7 counts per every 0.0050 %v/v.

Novel Real-Time Diagnosis of the Freezing Process Using an Ultrasonic Transducer

PubMed Central

Tseng, Yen-Hsiang; Cheng, Chin-Chi; Cheng, Hong-Ping; Lee, Dasheng

2015-01-01

The freezing stage governs several critical parameters of the freeze drying process and the quality of the resulting lyophilized products. This paper presents an integrated ultrasonic transducer (UT) in a stainless steel bottle and its application to real-time diagnostics of the water freezing process. The sensor was directly deposited onto the stainless steel bottle using a sol-gel spray technique. It could operate at temperature range from −100 to 400 °C and uses an ultrasonic pulse-echo technique. The progression of the freezing process, including water-in, freezing point and final phase change of water, were all clearly observed using ultrasound. The ultrasonic signals could indicate the three stages of the freezing process and evaluate the cooling and freezing periods under various processing conditions. The temperature was also adopted for evaluating the cooling and freezing periods. These periods increased with water volume and decreased with shelf temperature (i.e., speed of freezing). This study demonstrates the effectiveness of the ultrasonic sensor and technology for diagnosing and optimizing the process of water freezing to save energy. PMID:25946629

The Boom in 3D-Printed Sensor Technology

PubMed Central

Xu, Yuanyuan; Wu, Xiaoyue; Guo, Xiao; Kong, Bin; Zhang, Min; Qian, Xiang; Mi, Shengli; Sun, Wei

2017-01-01

Future sensing applications will include high-performance features, such as toxin detection, real-time monitoring of physiological events, advanced diagnostics, and connected feedback. However, such multi-functional sensors require advancements in sensitivity, specificity, and throughput with the simultaneous delivery of multiple detection in a short time. Recent advances in 3D printing and electronics have brought us closer to sensors with multiplex advantages, and additive manufacturing approaches offer a new scope for sensor fabrication. To this end, we review the recent advances in 3D-printed cutting-edge sensors. These achievements demonstrate the successful application of 3D-printing technology in sensor fabrication, and the selected studies deeply explore the potential for creating sensors with higher performance. Further development of multi-process 3D printing is expected to expand future sensor utility and availability. PMID:28534832

Real-time image mosaicing for medical applications.

PubMed

Loewke, Kevin E; Camarillo, David B; Jobst, Christopher A; Salisbury, J Kenneth

2007-01-01

In this paper we describe the development of a robotically-assisted image mosaicing system for medical applications. The processing occurs in real-time due to a fast initial image alignment provided by robotic position sensing. Near-field imaging, defined by relatively large camera motion, requires translations as well as pan and tilt orientations to be measured. To capture these measurements we use 5-d.o.f. sensing along with a hand-eye calibration to account for sensor offset. This sensor-based approach speeds up the mosaicing, eliminates cumulative errors, and readily handles arbitrary camera motions. Our results have produced visually satisfactory mosaics on a dental model but can be extended to other medical images.

Automated Welding System

NASA Technical Reports Server (NTRS)

Bayless, E. O.; Lawless, K. G.; Kurgan, C.; Nunes, A. C.; Graham, B. F.; Hoffman, D.; Jones, C. S.; Shepard, R.

1993-01-01

Fully automated variable-polarity plasma arc VPPA welding system developed at Marshall Space Flight Center. System eliminates defects caused by human error. Integrates many sensors with mathematical model of the weld and computer-controlled welding equipment. Sensors provide real-time information on geometry of weld bead, location of weld joint, and wire-feed entry. Mathematical model relates geometry of weld to critical parameters of welding process.

Molecular Quantification of the Florida Red Tide Dinoflagellate and the Development of Low Cost, Volunteer-attended Handheld Sensor Networks

NASA Astrophysics Data System (ADS)

Nieuwkerk, D.; Ulrich, R. M.; Paul, J. H.; Hubbard, K.; Kirkpatrick, B. A.; Fanara, T. A.; Bruzek, S.; Hoeglund, A.

2016-02-01

Harmful algal blooms of the dinoflagellate Karenia brevis can cause massive fish-kills and marine mammal mortalities, as well as impact human health via the consumption of brevetoxin-contaminated shellfish and the inhalation of aerosolized toxins. There is a strong effort to predict human health impacts by monitoring the bloom stages of K. brevis, and to prevent health impacts by closing shellfish beds when K. brevis cell concentrations reach toxic levels. The current standard method for quantifying K. brevis is by microscopic enumeration, which requires taxonomic expertise to discern K. brevis cells from other Karenia species as well as a long turnover time to generate data, which limits the number of water samples that can be processed. This EPA-funded study compared a variety of technologies against the current standard (microscopic counts) to quantify the number of K. brevis cells per liter in the water column. Results of this study showed a strong correlation between Real Time Nucleic Acid Sequence-Based Amplification (RT-NASBA) and enumeration by microscopy performed by members of the Florida Fish and Wildlife Research Institute, who are responsible for such monitoring. We are adapting the bench-top RT-NASBA assay to the AmpliFire platform (a handheld sensor that can be used in the field), for point of need K. brevis detection. These handheld sensors will be used by a trained volunteer network and government agencies (FWC, NOAA, and Mote Marine Lab.) to quantify K. brevis cells in the water column of core Gulf of Mexico sites; the results from these sensors will be reported back to the GCOOS observation systems to provide real-time monitoring of K. brevis counts. The real-time information will allow agencies to better monitor fishery closures and predict human health impacts of harmful algal blooms, because a larger number of samples can be processed each week, as the NASBA process removes the rate-limiting step of microscope time.

Improved particle swarm optimization algorithm for android medical care IOT using modified parameters.

PubMed

Sung, Wen-Tsai; Chiang, Yen-Chun

2012-12-01

This study examines wireless sensor network with real-time remote identification using the Android study of things (HCIOT) platform in community healthcare. An improved particle swarm optimization (PSO) method is proposed to efficiently enhance physiological multi-sensors data fusion measurement precision in the Internet of Things (IOT) system. Improved PSO (IPSO) includes: inertia weight factor design, shrinkage factor adjustment to allow improved PSO algorithm data fusion performance. The Android platform is employed to build multi-physiological signal processing and timely medical care of things analysis. Wireless sensor network signal transmission and Internet links allow community or family members to have timely medical care network services.

Method and apparatus for real-time measurement of fuel gas compositions and heating values

DOEpatents

Zelepouga, Serguei; Pratapas, John M.; Saveliev, Alexei V.; Jangale, Vilas V.

2016-03-22

An exemplary embodiment can be an apparatus for real-time, in situ measurement of gas compositions and heating values. The apparatus includes a near infrared sensor for measuring concentrations of hydrocarbons and carbon dioxide, a mid infrared sensor for measuring concentrations of carbon monoxide and a semiconductor based sensor for measuring concentrations of hydrogen gas. A data processor having a computer program for reducing the effects of cross-sensitivities of the sensors to components other than target components of the sensors is also included. Also provided are corresponding or associated methods for real-time, in situ determination of a composition and heating value of a fuel gas.

On-line soft sensing in upstream bioprocessing.

PubMed

Randek, Judit; Mandenius, Carl-Fredrik

2018-02-01

This review provides an overview and a critical discussion of novel possibilities of applying soft sensors for on-line monitoring and control of industrial bioprocesses. Focus is on bio-product formation in the upstream process but also the integration with other parts of the process is addressed. The term soft sensor is used for the combination of analytical hardware data (from sensors, analytical devices, instruments and actuators) with mathematical models that create new real-time information about the process. In particular, the review assesses these possibilities from an industrial perspective, including sensor performance, information value and production economy. The capabilities of existing analytical on-line techniques are scrutinized in view of their usefulness in soft sensor setups and in relation to typical needs in bioprocessing in general. The review concludes with specific recommendations for further development of soft sensors for the monitoring and control of upstream bioprocessing.

1024-Pixel CMOS Multimodality Joint Cellular Sensor/Stimulator Array for Real-Time Holistic Cellular Characterization and Cell-Based Drug Screening.

PubMed

Park, Jong Seok; Aziz, Moez Karim; Li, Sensen; Chi, Taiyun; Grijalva, Sandra Ivonne; Sung, Jung Hoon; Cho, Hee Cheol; Wang, Hua

2018-02-01

This paper presents a fully integrated CMOS multimodality joint sensor/stimulator array with 1024 pixels for real-time holistic cellular characterization and drug screening. The proposed system consists of four pixel groups and four parallel signal-conditioning blocks. Every pixel group contains 16 × 16 pixels, and each pixel includes one gold-plated electrode, four photodiodes, and in-pixel circuits, within a pixel footprint. Each pixel supports real-time extracellular potential recording, optical detection, charge-balanced biphasic current stimulation, and cellular impedance measurement for the same cellular sample. The proposed system is fabricated in a standard 130-nm CMOS process. Rat cardiomyocytes are successfully cultured on-chip. Measured high-resolution optical opacity images, extracellular potential recordings, biphasic current stimulations, and cellular impedance images demonstrate the unique advantages of the system for holistic cell characterization and drug screening. Furthermore, this paper demonstrates the use of optical detection on the on-chip cultured cardiomyocytes to real-time track their cyclic beating pattern and beating rate.

Performance of a real-time sensor and processing system on a helicopter

NASA Astrophysics Data System (ADS)

Kurz, F.; Rosenbaum, D.; Meynberg, O.; Mattyus, G.; Reinartz, P.

2014-11-01

A new optical real-time sensor system (4k system) on a helicopter is now ready to use for applications during disasters, mass events and traffic monitoring scenarios. The sensor was developed light-weighted, small with relatively cheap components in a pylon mounted sideward on a helicopter. The sensor architecture is finally a compromise between the required functionality, the development costs, the weight and the sensor size. Aboard processors are integrated in the 4k sensor system for orthophoto generation, for automatic traffic parameter extraction and for data downlinks. It is planned to add real-time processors for person detection and tracking, for DSM generation and for water detection. Equipped with the newest and most powerful off-the-shelf cameras available, a wide variety of viewing configurations with a frame rate of up to 12 Hz for the different applications is possible. Based on three cameras with 50 mm lenses which are looking in different directions, a maximal FOV of 104° is reachable; with 100 mm lenses a ground sampling distance of 3.5 cm is possible at a flight height of 500 m above ground. In this paper, we present the first data sets and describe the technical components of the sensor. The effect of vibrations of the helicopter on the GNSS/IMU accuracy and on the 4k video quality is analysed. It can be shown, that if the helicopter hoovers the rolling shutter effect affects the 4k video quality drastically. The GNSS/IMU error is higher than the specified limit, which is mainly caused by the vibrations on the helicopter and the insufficient vibrational absorbers on the sensor board.

An Efficient Randomized Algorithm for Real-Time Process Scheduling in PicOS Operating System

NASA Astrophysics Data System (ADS)

Helmy*, Tarek; Fatai, Anifowose; Sallam, El-Sayed

PicOS is an event-driven operating environment designed for use with embedded networked sensors. More specifically, it is designed to support the concurrency in intensive operations required by networked sensors with minimal hardware requirements. Existing process scheduling algorithms of PicOS; a commercial tiny, low-footprint, real-time operating system; have their associated drawbacks. An efficient, alternative algorithm, based on a randomized selection policy, has been proposed, demonstrated, confirmed for efficiency and fairness, on the average, and has been recommended for implementation in PicOS. Simulations were carried out and performance measures such as Average Waiting Time (AWT) and Average Turn-around Time (ATT) were used to assess the efficiency of the proposed randomized version over the existing ones. The results prove that Randomized algorithm is the best and most attractive for implementation in PicOS, since it is most fair and has the least AWT and ATT on average over the other non-preemptive scheduling algorithms implemented in this paper.

Wearable sweat detector device design for health monitoring and clinical diagnosis

NASA Astrophysics Data System (ADS)

Wu, Qiuchen; Zhang, Xiaodong; Tian, Bihao; Zhang, Hongyan; Yu, Yang; Wang, Ming

2017-06-01

Miniaturized sensor is necessary part for wearable detector for biomedical applications. Wearable detector device is indispensable for online health care. This paper presents a concept of an wearable digital health monitoring device design for sweat analysis. The flexible sensor is developed to quantify the amount of hydrogen ions in sweat and skin temperature in real time. The detection system includes pH sensor, temperature sensor, signal processing module, power source, microprocessor, display module and so on. The sweat monitoring device is designed for sport monitoring or clinical diagnosis.

The Purpose of the Sensor Web

NASA Technical Reports Server (NTRS)

Schoeberl, Mark R.

2004-01-01

The Sensor Web concept emerged as the number of Earth Science Satellites began to increase in the recent years. The idea, part of a vision for the future of earth science, was that the sensor systems would be linked in an active way to provide improved forecast capability. This means that a system that is nearly autonomous would need to be developed to allow the satellites to re-target and deploy assets for particular phenomena or provide on board processing for real time data. This talk will describe several elements of the sensor web.

EMPACT 3D: an advanced EMI discrimination sensor for CONUS and OCONUS applications

NASA Astrophysics Data System (ADS)

Keranen, Joe; Miller, Jonathan S.; Schultz, Gregory; Sander-Olhoeft, Morgan; Laudato, Stephen

2018-04-01

We recently developed a new, man-portable, electromagnetic induction (EMI) sensor designed to detect and classify small, unexploded sub-munitions and discriminate them from non-hazardous debris. The ability to distinguish innocuous metal clutter from potentially hazardous unexploded ordnance (UXO) and other explosive remnants of war (ERW) before excavation can significantly accelerate land reclamation efforts by eliminating time spent removing harmless scrap metal. The EMI sensor employs a multi-axis transmitter and receiver configuration to produce data sufficient for anomaly discrimination. A real-time data inversion routine produces intrinsic and extrinsic anomaly features describing the polarizability, location, and orientation of the anomaly under test. We discuss data acquisition and post-processing software development, and results from laboratory and field tests demonstrating the discrimination capability of the system. Data acquisition and real-time processing emphasize ease-of-use, quality control (QC), and display of discrimination results. Integration of the QC and discrimination methods into the data acquisition software reduces the time required between sensor data collection and the final anomaly discrimination result. The system supports multiple concepts of operations (CONOPs) including: 1) a non-GPS cued configuration in which detected anomalies are discriminated and excavated immediately following the anomaly survey; 2) GPS integration to survey multiple anomalies to produce a prioritized dig list with global anomaly locations; and 3) a dynamic mapping configuration supporting detection followed by discrimination and excavation of targets of interest.

A high precision position sensor design and its signal processing algorithm for a maglev train.

PubMed

Xue, Song; Long, Zhiqiang; He, Ning; Chang, Wensen

2012-01-01

High precision positioning technology for a kind of high speed maglev train with an electromagnetic suspension (EMS) system is studied. At first, the basic structure and functions of the position sensor are introduced and some key techniques to enhance the positioning precision are designed. Then, in order to further improve the positioning signal quality and the fault-tolerant ability of the sensor, a new kind of discrete-time tracking differentiator (TD) is proposed based on nonlinear optimal control theory. This new TD has good filtering and differentiating performances and a small calculation load. It is suitable for real-time signal processing. The stability, convergence property and frequency characteristics of the TD are studied and analyzed thoroughly. The delay constant of the TD is figured out and an effective time delay compensation algorithm is proposed. Based on the TD technology, a filtering process is introduced in to improve the positioning signal waveform when the sensor is under bad working conditions, and a two-sensor switching algorithm is designed to eliminate the positioning errors caused by the joint gaps of the long stator. The effectiveness and stability of the sensor and its signal processing algorithms are proved by the experiments on a test train during a long-term test run.

A High Precision Position Sensor Design and Its Signal Processing Algorithm for a Maglev Train

PubMed Central

Xue, Song; Long, Zhiqiang; He, Ning; Chang, Wensen

2012-01-01

High precision positioning technology for a kind of high speed maglev train with an electromagnetic suspension (EMS) system is studied. At first, the basic structure and functions of the position sensor are introduced and some key techniques to enhance the positioning precision are designed. Then, in order to further improve the positioning signal quality and the fault-tolerant ability of the sensor, a new kind of discrete-time tracking differentiator (TD) is proposed based on nonlinear optimal control theory. This new TD has good filtering and differentiating performances and a small calculation load. It is suitable for real-time signal processing. The stability, convergence property and frequency characteristics of the TD are studied and analyzed thoroughly. The delay constant of the TD is figured out and an effective time delay compensation algorithm is proposed. Based on the TD technology, a filtering process is introduced in to improve the positioning signal waveform when the sensor is under bad working conditions, and a two-sensor switching algorithm is designed to eliminate the positioning errors caused by the joint gaps of the long stator. The effectiveness and stability of the sensor and its signal processing algorithms are proved by the experiments on a test train during a long-term test run. PMID:22778582

Real-time monitoring system of composite aircraft wings utilizing Fibre Bragg Grating sensor

NASA Astrophysics Data System (ADS)

Vorathin, E.; Hafizi, Z. M.; Che Ghani, S. A.; Lim, K. S.

2016-10-01

Embedment of Fibre Bragg Grating (FBG) sensor in composite aircraft wings leads to the advancement of structural condition monitoring. The monitored aircraft wings have the capability to give real-time response under critical loading circumstances. The main objective of this paper is to develop a real-time FBG monitoring system for composite aircraft wings to view real-time changes when the structure undergoes some static loadings and dynamic impact. The implementation of matched edge filter FBG interrogation system to convert wavelength variations to strain readings shows that the structure is able to response instantly in real-time when undergoing few loadings and dynamic impact. This smart monitoring system is capable of updating the changes instantly in real-time and shows the weight induced on the composite aircraft wings instantly without any error. It also has a good agreement with acoustic emission (AE) sensor in the dynamic test.

Real-time physiological monitoring with distributed networks of sensors and object-oriented programming techniques

NASA Astrophysics Data System (ADS)

Wiesmann, William P.; Pranger, L. Alex; Bogucki, Mary S.

1998-05-01

Remote monitoring of physiologic data from individual high- risk workers distributed over time and space is a considerable challenge. This is often due to an inadequate capability to accurately integrate large amounts of data into usable information in real time. In this report, we have used the vertical and horizontal organization of the 'fireground' as a framework to design a distributed network of sensors. In this system, sensor output is linked through a hierarchical object oriented programing process to accurately interpret physiological data, incorporate these data into a synchronous model and relay processed data, trends and predictions to members of the fire incident command structure. There are several unique aspects to this approach. The first includes a process to account for variability in vital parameter values for each individual's normal physiologic response by including an adaptive network in each data process. This information is used by the model in an iterative process to baseline a 'normal' physiologic response to a given stress for each individual and to detect deviations that indicate dysfunction or a significant insult. The second unique capability of the system orders the information for each user including the subject, local company officers, medical personnel and the incident commanders. Information can be retrieved and used for training exercises and after action analysis. Finally this system can easily be adapted to existing communication and processing links along with incorporating the best parts of current models through the use of object oriented programming techniques. These modern software techniques are well suited to handling multiple data processes independently over time in a distributed network.

Datalogging the Distillation Process.

ERIC Educational Resources Information Center

Soares, Allan; Creevy, Steven

1995-01-01

Presents a distillation experiment that uses temperature sensors connected to a computer in place of thermometers, and enables the whole class to view the data on a monitor and interpret and discuss the data in real time. (JRH)

Operating Systems for Wireless Sensor Networks: A Survey

PubMed Central

Farooq, Muhammad Omer; Kunz, Thomas

2011-01-01

This paper presents a survey on the current state-of-the-art in Wireless Sensor Network (WSN) Operating Systems (OSs). In recent years, WSNs have received tremendous attention in the research community, with applications in battlefields, industrial process monitoring, home automation, and environmental monitoring, to name but a few. A WSN is a highly dynamic network because nodes die due to severe environmental conditions and battery power depletion. Furthermore, a WSN is composed of miniaturized motes equipped with scarce resources e.g., limited memory and computational abilities. WSNs invariably operate in an unattended mode and in many scenarios it is impossible to replace sensor motes after deployment, therefore a fundamental objective is to optimize the sensor motes’ life time. These characteristics of WSNs impose additional challenges on OS design for WSN, and consequently, OS design for WSN deviates from traditional OS design. The purpose of this survey is to highlight major concerns pertaining to OS design in WSNs and to point out strengths and weaknesses of contemporary OSs for WSNs, keeping in mind the requirements of emerging WSN applications. The state-of-the-art in operating systems for WSNs has been examined in terms of the OS Architecture, Programming Model, Scheduling, Memory Management and Protection, Communication Protocols, Resource Sharing, Support for Real-Time Applications, and additional features. These features are surveyed for both real-time and non-real-time WSN operating systems. PMID:22163934

Operating systems for wireless sensor networks: a survey.

PubMed

Farooq, Muhammad Omer; Kunz, Thomas

2011-01-01

This paper presents a survey on the current state-of-the-art in Wireless Sensor Network (WSN) Operating Systems (OSs). In recent years, WSNs have received tremendous attention in the research community, with applications in battlefields, industrial process monitoring, home automation, and environmental monitoring, to name but a few. A WSN is a highly dynamic network because nodes die due to severe environmental conditions and battery power depletion. Furthermore, a WSN is composed of miniaturized motes equipped with scarce resources e.g., limited memory and computational abilities. WSNs invariably operate in an unattended mode and in many scenarios it is impossible to replace sensor motes after deployment, therefore a fundamental objective is to optimize the sensor motes' life time. These characteristics of WSNs impose additional challenges on OS design for WSN, and consequently, OS design for WSN deviates from traditional OS design. The purpose of this survey is to highlight major concerns pertaining to OS design in WSNs and to point out strengths and weaknesses of contemporary OSs for WSNs, keeping in mind the requirements of emerging WSN applications. The state-of-the-art in operating systems for WSNs has been examined in terms of the OS Architecture, Programming Model, Scheduling, Memory Management and Protection, Communication Protocols, Resource Sharing, Support for Real-Time Applications, and additional features. These features are surveyed for both real-time and non-real-time WSN operating systems.

Research of marine sensor web based on SOA and EDA

NASA Astrophysics Data System (ADS)

Jiang, Yongguo; Dou, Jinfeng; Guo, Zhongwen; Hu, Keyong

2015-04-01

A great deal of ocean sensor observation data exists, for a wide range of marine disciplines, derived from in situ and remote observing platforms, in real-time, near-real-time and delayed mode. Ocean monitoring is routinely completed using sensors and instruments. Standardization is the key requirement for exchanging information about ocean sensors and sensor data and for comparing and combining information from different sensor networks. One or more sensors are often physically integrated into a single ocean `instrument' device, which often brings in many challenges related to diverse sensor data formats, parameters units, different spatiotemporal resolution, application domains, data quality and sensors protocols. To face these challenges requires the standardization efforts aiming at facilitating the so-called Sensor Web, which making it easy to provide public access to sensor data and metadata information. In this paper, a Marine Sensor Web, based on SOA and EDA and integrating the MBARI's PUCK protocol, IEEE 1451 and OGC SWE 2.0, is illustrated with a five-layer architecture. The Web Service layer and Event Process layer are illustrated in detail with an actual example. The demo study has demonstrated that a standard-based system can be built to access sensors and marine instruments distributed globally using common Web browsers for monitoring the environment and oceanic conditions besides marine sensor data on the Web, this framework of Marine Sensor Web can also play an important role in many other domains' information integration.

Additively Manufactured IN718 Components with Wirelessly Powered and Interrogated Embedded Sensing

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

Attridge, Paul; Bajekal, Sanjay; Klecka, Michael

A methodology is described for embedding commercial-off-the-shelf sensors together with wireless communication and power circuit elements using direct laser metal sintered additively manufactured components. Physics based models of the additive manufacturing processes and sensor/wireless level performance models guided the design and embedment processes. A combination of cold spray deposition and laser engineered net shaping was used to fashion the transmitter/receiving elements and embed the sensors, thereby providing environmental protection and component robustness/survivability for harsh conditions. By design, this complement of analog and digital sensors were wirelessly powered and interrogated using a health and utilization monitoring system; enabling real-time, in situmore » prognostics and diagnostics.« less

Development of a Three Dimensional Wireless Sensor Network for Terrain-Climate Research in Remote Mountainous Environments

NASA Astrophysics Data System (ADS)

Kavanagh, K.; Davis, A.; Gessler, P.; Hess, H.; Holden, Z.; Link, T. E.; Newingham, B. A.; Smith, A. M.; Robinson, P.

2011-12-01

Developing sensor networks that are robust enough to perform in the world's remote regions is critical since these regions serve as important benchmarks compared to human-dominated areas. Paradoxically, the factors that make these remote, natural sites challenging for sensor networking are often what make them indispensable for climate change research. We aim to overcome these challenges by developing a three-dimensional sensor network arrayed across a topoclimatic gradient (1100-1800 meters) in a wilderness area in central Idaho. Development of this sensor array builds upon advances in sensing, networking, and power supply technologies coupled with experiences of the multidisciplinary investigators in conducting research in remote mountainous locations. The proposed gradient monitoring network will provide near real-time data from a three-dimensional (3-D) array of sensors measuring biophysical parameters used in ecosystem process models. The network will monitor atmospheric carbon dioxide concentration, humidity, air and soil temperature, soil water content, precipitation, incoming and outgoing shortwave and longwave radiation, snow depth, wind speed and direction, tree stem growth and leaf wetness at time intervals ranging from seconds to days. The long-term goal of this project is to realize a transformative integration of smart sensor networks adaptively communicating data in real-time to ultimately achieve a 3-D visualization of ecosystem processes within remote mountainous regions. Process models will be the interface between the visualization platforms and the sensor network. This will allow us to better predict how non-human dominated terrestrial and aquatic ecosystems function and respond to climate dynamics. Access to the data will be ensured as part of the Northwest Knowledge Network being developed at the University of Idaho, through ongoing Idaho NSF-funded cyber infrastructure initiatives, and existing data management systems funded by NSF, such as the CUAHSI Hydrologic Information System (HIS). These efforts will enhance cross-disciplinary understanding of natural and anthropogenic influences on ecosystem function and ultimately inform decision-making.

Integrated active sensor system for real time vibration monitoring.

PubMed

Liang, Qijie; Yan, Xiaoqin; Liao, Xinqin; Cao, Shiyao; Lu, Shengnan; Zheng, Xin; Zhang, Yue

2015-11-05

We report a self-powered, lightweight and cost-effective active sensor system for vibration monitoring with multiplexed operation based on contact electrification between sensor and detected objects. The as-fabricated sensor matrix is capable of monitoring and mapping the vibration state of large amounts of units. The monitoring contents include: on-off state, vibration frequency and vibration amplitude of each unit. The active sensor system delivers a detection range of 0-60 Hz, high accuracy (relative error below 0.42%), long-term stability (10000 cycles). On the time dimension, the sensor can provide the vibration process memory by recording the outputs of the sensor system in an extend period of time. Besides, the developed sensor system can realize detection under contact mode and non-contact mode. Its high performance is not sensitive to the shape or the conductivity of the detected object. With these features, the active sensor system has great potential in automatic control, remote operation, surveillance and security systems.

Integrated active sensor system for real time vibration monitoring

PubMed Central

Liang, Qijie; Yan, Xiaoqin; Liao, Xinqin; Cao, Shiyao; Lu, Shengnan; Zheng, Xin; Zhang, Yue

2015-01-01

We report a self-powered, lightweight and cost-effective active sensor system for vibration monitoring with multiplexed operation based on contact electrification between sensor and detected objects. The as-fabricated sensor matrix is capable of monitoring and mapping the vibration state of large amounts of units. The monitoring contents include: on-off state, vibration frequency and vibration amplitude of each unit. The active sensor system delivers a detection range of 0–60 Hz, high accuracy (relative error below 0.42%), long-term stability (10000 cycles). On the time dimension, the sensor can provide the vibration process memory by recording the outputs of the sensor system in an extend period of time. Besides, the developed sensor system can realize detection under contact mode and non-contact mode. Its high performance is not sensitive to the shape or the conductivity of the detected object. With these features, the active sensor system has great potential in automatic control, remote operation, surveillance and security systems. PMID:26538293

Adaptive neural network/expert system that learns fault diagnosis for different structures

NASA Astrophysics Data System (ADS)

Simon, Solomon H.

1992-08-01

Corporations need better real-time monitoring and control systems to improve productivity by watching quality and increasing production flexibility. The innovative technology to achieve this goal is evolving in the form artificial intelligence and neural networks applied to sensor processing, fusion, and interpretation. By using these advanced Al techniques, we can leverage existing systems and add value to conventional techniques. Neural networks and knowledge-based expert systems can be combined into intelligent sensor systems which provide real-time monitoring, control, evaluation, and fault diagnosis for production systems. Neural network-based intelligent sensor systems are more reliable because they can provide continuous, non-destructive monitoring and inspection. Use of neural networks can result in sensor fusion and the ability to model highly, non-linear systems. Improved models can provide a foundation for more accurate performance parameters and predictions. We discuss a research software/hardware prototype which integrates neural networks, expert systems, and sensor technologies and which can adapt across a variety of structures to perform fault diagnosis. The flexibility and adaptability of the prototype in learning two structures is presented. Potential applications are discussed.

An ultrasensitive strain sensor with a wide strain range based on graphene armour scales.

PubMed

Yang, Yi-Fan; Tao, Lu-Qi; Pang, Yu; Tian, He; Ju, Zhen-Yi; Wu, Xiao-Ming; Yang, Yi; Ren, Tian-Ling

2018-06-12

An ultrasensitive strain sensor with a wide strain range based on graphene armour scales is demonstrated in this paper. The sensor shows an ultra-high gauge factor (GF, up to 1054) and a wide strain range (ε = 26%), both of which present an advantage compared to most other flexible sensors. Moreover, the sensor is developed by a simple fabrication process. Due to the excellent performance, this strain sensor can meet the demands of subtle, large and complex human motion monitoring, which indicates its tremendous application potential in health monitoring, mechanical control, real-time motion monitoring and so on.

Development of a Capacitive Ice Sensor to Measure Ice Growth in Real Time

PubMed Central

Zhi, Xiang; Cho, Hyo Chang; Wang, Bo; Ahn, Cheol Hee; Moon, Hyeong Soon; Go, Jeung Sang

2015-01-01

This paper presents the development of the capacitive sensor to measure the growth of ice on a fuel pipe surface in real time. The ice sensor consists of pairs of electrodes to detect the change in capacitance and a thermocouple temperature sensor to examine the ice formation situation. In addition, an environmental chamber was specially designed to control the humidity and temperature to simulate the ice formation conditions. From the humidity, a water film is formed on the ice sensor, which results in an increase in capacitance. Ice nucleation occurs, followed by the rapid formation of frost ice that decreases the capacitance suddenly. The capacitance is saturated. The developed ice sensor explains the ice growth providing information about the icing temperature in real time. PMID:25808770

Development of a capacitive ice sensor to measure ice growth in real time.

PubMed

Zhi, Xiang; Cho, Hyo Chang; Wang, Bo; Ahn, Cheol Hee; Moon, Hyeong Soon; Go, Jeung Sang

2015-03-19

This paper presents the development of the capacitive sensor to measure the growth of ice on a fuel pipe surface in real time. The ice sensor consists of pairs of electrodes to detect the change in capacitance and a thermocouple temperature sensor to examine the ice formation situation. In addition, an environmental chamber was specially designed to control the humidity and temperature to simulate the ice formation conditions. From the humidity, a water film is formed on the ice sensor, which results in an increase in capacitance. Ice nucleation occurs, followed by the rapid formation of frost ice that decreases the capacitance suddenly. The capacitance is saturated. The developed ice sensor explains the ice growth providing information about the icing temperature in real time.

Architecture for an integrated real-time air combat and sensor network simulation

NASA Astrophysics Data System (ADS)

Criswell, Evans A.; Rushing, John; Lin, Hong; Graves, Sara

2007-04-01

An architecture for an integrated air combat and sensor network simulation is presented. The architecture integrates two components: a parallel real-time sensor fusion and target tracking simulation, and an air combat simulation. By integrating these two simulations, it becomes possible to experiment with scenarios in which one or both sides in a battle have very large numbers of primitive passive sensors, and to assess the likely effects of those sensors on the outcome of the battle. Modern Air Power is a real-time theater-level air combat simulation that is currently being used as a part of the USAF Air and Space Basic Course (ASBC). The simulation includes a variety of scenarios from the Vietnam war to the present day, and also includes several hypothetical future scenarios. Modern Air Power includes a scenario editor, an order of battle editor, and full AI customization features that make it possible to quickly construct scenarios for any conflict of interest. The scenario editor makes it possible to place a wide variety of sensors including both high fidelity sensors such as radars, and primitive passive sensors that provide only very limited information. The parallel real-time sensor network simulation is capable of handling very large numbers of sensors on a computing cluster of modest size. It can fuse information provided by disparate sensors to detect and track targets, and produce target tracks.

A Versatile Multichannel Digital Signal Processing Module for Microcalorimeter Arrays

NASA Astrophysics Data System (ADS)

Tan, H.; Collins, J. W.; Walby, M.; Hennig, W.; Warburton, W. K.; Grudberg, P.

2012-06-01

Different techniques have been developed for reading out microcalorimeter sensor arrays: individual outputs for small arrays, and time-division or frequency-division or code-division multiplexing for large arrays. Typically, raw waveform data are first read out from the arrays using one of these techniques and then stored on computer hard drives for offline optimum filtering, leading not only to requirements for large storage space but also limitations on achievable count rate. Thus, a read-out module that is capable of processing microcalorimeter signals in real time will be highly desirable. We have developed multichannel digital signal processing electronics that are capable of on-board, real time processing of microcalorimeter sensor signals from multiplexed or individual pixel arrays. It is a 3U PXI module consisting of a standardized core processor board and a set of daughter boards. Each daughter board is designed to interface a specific type of microcalorimeter array to the core processor. The combination of the standardized core plus this set of easily designed and modified daughter boards results in a versatile data acquisition module that not only can easily expand to future detector systems, but is also low cost. In this paper, we first present the core processor/daughter board architecture, and then report the performance of an 8-channel daughter board, which digitizes individual pixel outputs at 1 MSPS with 16-bit precision. We will also introduce a time-division multiplexing type daughter board, which takes in time-division multiplexing signals through fiber-optic cables and then processes the digital signals to generate energy spectra in real time.

A Portable Array-Type Optical Fiber Sensing Instrument for Real-Time Gas Detection

PubMed Central

Hung, San-Shan; Chang, Hsing-Cheng; Chang, I-Nan

2016-01-01

A novel optical fiber array-type of sensing instrument with temperature compensation for real-time detection was developed to measure oxygen, carbon dioxide, and ammonia simultaneously. The proposed instrument is multi-sensing array integrated with real-time measurement module for portable applications. The sensing optical fibers were etched and polished before coating to increase sensitivities. The ammonia and temperature sensors were each composed of a dye-coated single-mode fiber with constructing a fiber Bragg grating and a long-period filter grating for detecting light intensity. Both carbon dioxide and oxygen sensing structures use multimode fibers where 1-hydroxy-3,6,8-pyrene trisulfonic acid trisodium salt is coated for carbon dioxide sensing and Tris(2,2′-bipyridyl) dichlororuthenium(II) hexahydrate and Tris(bipyridine)ruthenium(II) chloride are coated for oxygen sensing. Gas-induced fluorescent light intensity variation was applied to detect gas concentration. The portable gas sensing array was set up by integrating with photo-electronic measurement modules and a human-machine interface to detect gases in real time. The measured data have been processed using piecewise-linear method. The sensitivity of the oxygen sensor were 1.54%/V and 9.62%/V for concentrations less than 1.5% and for concentrations between 1.5% and 6%, respectively. The sensitivity of the carbon dioxide sensor were 8.33%/V and 9.62%/V for concentrations less than 2% and for concentrations between 2% and 5%, respectively. For the ammonia sensor, the sensitivity was 27.78%/V, while ammonia concentration was less than 2%. PMID:27941636

A Portable Array-Type Optical Fiber Sensing Instrument for Real-Time Gas Detection.

PubMed

Hung, San-Shan; Chang, Hsing-Cheng; Chang, I-Nan

2016-12-08

A novel optical fiber array-type of sensing instrument with temperature compensation for real-time detection was developed to measure oxygen, carbon dioxide, and ammonia simultaneously. The proposed instrument is multi-sensing array integrated with real-time measurement module for portable applications. The sensing optical fibers were etched and polished before coating to increase sensitivities. The ammonia and temperature sensors were each composed of a dye-coated single-mode fiber with constructing a fiber Bragg grating and a long-period filter grating for detecting light intensity. Both carbon dioxide and oxygen sensing structures use multimode fibers where 1-hydroxy-3,6,8-pyrene trisulfonic acid trisodium salt is coated for carbon dioxide sensing and Tris(2,2'-bipyridyl) dichlororuthenium(II) hexahydrate and Tris(bipyridine)ruthenium(II) chloride are coated for oxygen sensing. Gas-induced fluorescent light intensity variation was applied to detect gas concentration. The portable gas sensing array was set up by integrating with photo-electronic measurement modules and a human-machine interface to detect gases in real time. The measured data have been processed using piecewise-linear method. The sensitivity of the oxygen sensor were 1.54%/V and 9.62%/V for concentrations less than 1.5% and for concentrations between 1.5% and 6%, respectively. The sensitivity of the carbon dioxide sensor were 8.33%/V and 9.62%/V for concentrations less than 2% and for concentrations between 2% and 5%, respectively. For the ammonia sensor, the sensitivity was 27.78%/V, while ammonia concentration was less than 2%.

Real-time modeling of primitive environments through wavelet sensors and Hebbian learning

NASA Astrophysics Data System (ADS)

Vaccaro, James M.; Yaworsky, Paul S.

1999-06-01

Modeling the world through sensory input necessarily provides a unique perspective for the observer. Given a limited perspective, objects and events cannot always be encoded precisely but must involve crude, quick approximations to deal with sensory information in a real- time manner. As an example, when avoiding an oncoming car, a pedestrian needs to identify the fact that a car is approaching before ascertaining the model or color of the vehicle. In our methodology, we use wavelet-based sensors with self-organized learning to encode basic sensory information in real-time. The wavelet-based sensors provide necessary transformations while a rank-based Hebbian learning scheme encodes a self-organized environment through translation, scale and orientation invariant sensors. Such a self-organized environment is made possible by combining wavelet sets which are orthonormal, log-scale with linear orientation and have automatically generated membership functions. In earlier work we used Gabor wavelet filters, rank-based Hebbian learning and an exponential modulation function to encode textural information from images. Many different types of modulation are possible, but based on biological findings the exponential modulation function provided a good approximation of first spike coding of `integrate and fire' neurons. These types of Hebbian encoding schemes (e.g., exponential modulation, etc.) are useful for quick response and learning, provide several advantages over contemporary neural network learning approaches, and have been found to quantize data nonlinearly. By combining wavelets with Hebbian learning we can provide a real-time front-end for modeling an intelligent process, such as the autonomous control of agents in a simulated environment.

A novel time-domain signal processing algorithm for real time ventricular fibrillation detection

NASA Astrophysics Data System (ADS)

Monte, G. E.; Scarone, N. C.; Liscovsky, P. O.; Rotter S/N, P.

2011-12-01

This paper presents an application of a novel algorithm for real time detection of ECG pathologies, especially ventricular fibrillation. It is based on segmentation and labeling process of an oversampled signal. After this treatment, analyzing sequence of segments, global signal behaviours are obtained in the same way like a human being does. The entire process can be seen as a morphological filtering after a smart data sampling. The algorithm does not require any ECG digital signal pre-processing, and the computational cost is low, so it can be embedded into the sensors for wearable and permanent applications. The proposed algorithms could be the input signal description to expert systems or to artificial intelligence software in order to detect other pathologies.

Photonic crystal fiber modal interferometer with Pd/WO3 coating for real-time monitoring of dissolved hydrogen concentration in transformer oil

NASA Astrophysics Data System (ADS)

Zhang, Ya-nan; Wu, Qilu; Peng, Huijie; Zhao, Yong

2016-12-01

A highly-sensitive and temperature-robust photonic crystal fiber (PCF) modal interferometer coated with Pd/WO3 film was fabricated and studied, aiming for real-time monitoring of dissolved hydrogen concentration in transformer oil. The sensor probe was fabricated by splicing two segments of a single mode fiber (SMF) with both ends of the PCF. Since the collapse of air holes in the PCF in the interfaces between SMF and PCF, a SMF-PCF-SMF interferometer structure was formed. The Pd/WO3 film was fabricated by sol-gel method and coated on the surface of the PCF by dip-coating method. When the Pd/WO3 film is exposed to hydrogen, both the length and cladding refractive index of the PCF would be changed, resulting in the resonant wavelength shift of the interferometer. Experimental results showed that the hydrogen measurement sensitivity of the proposed sensor can reach 0.109 pm/(μl/l) in the transformer oil, with the measurement range of 0-10 000 μl/l and response time less than 33 min. Besides, the proposed sensor was temperature-insensitive without any compensation process, easy to fabricate without any tapering, polishing, or etching process, low cost and quickly response without any oil-gas separation device. All these performances satisfy the actual need of real-time monitoring of dissolved hydrogen concentration in the transformer oil.

Photonic crystal fiber modal interferometer with Pd/WO3 coating for real-time monitoring of dissolved hydrogen concentration in transformer oil.

PubMed

Zhang, Ya-Nan; Wu, Qilu; Peng, Huijie; Zhao, Yong

2016-12-01

A highly-sensitive and temperature-robust photonic crystal fiber (PCF) modal interferometer coated with Pd/WO 3 film was fabricated and studied, aiming for real-time monitoring of dissolved hydrogen concentration in transformer oil. The sensor probe was fabricated by splicing two segments of a single mode fiber (SMF) with both ends of the PCF. Since the collapse of air holes in the PCF in the interfaces between SMF and PCF, a SMF-PCF-SMF interferometer structure was formed. The Pd/WO 3 film was fabricated by sol-gel method and coated on the surface of the PCF by dip-coating method. When the Pd/WO 3 film is exposed to hydrogen, both the length and cladding refractive index of the PCF would be changed, resulting in the resonant wavelength shift of the interferometer. Experimental results showed that the hydrogen measurement sensitivity of the proposed sensor can reach 0.109 pm/(μl/l) in the transformer oil, with the measurement range of 0-10 000 μl/l and response time less than 33 min. Besides, the proposed sensor was temperature-insensitive without any compensation process, easy to fabricate without any tapering, polishing, or etching process, low cost and quickly response without any oil-gas separation device. All these performances satisfy the actual need of real-time monitoring of dissolved hydrogen concentration in the transformer oil.

The MITy micro-rover: Sensing, control, and operation

NASA Technical Reports Server (NTRS)

Malafeew, Eric; Kaliardos, William

1994-01-01

The sensory, control, and operation systems of the 'MITy' Mars micro-rover are discussed. It is shown that the customized sun tracker and laser rangefinder provide internal, autonomous dead reckoning and hazard detection in unstructured environments. The micro-rover consists of three articulated platforms with sensing, processing and payload subsystems connected by a dual spring suspension system. A reactive obstacle avoidance routine makes intelligent use of robot-centered laser information to maneuver through cluttered environments. The hazard sensors include a rangefinder, inclinometers, proximity sensors and collision sensors. A 486/66 laptop computer runs the graphical user interface and programming environment. A graphical window displays robot telemetry in real time and a small TV/VCR is used for real time supervisory control. Guidance, navigation, and control routines work in conjunction with the mapping and obstacle avoidance functions to provide heading and speed commands that maneuver the robot around obstacles and towards the target.

Zinc metal complex as a sensor for simultaneous detection of fluoride and HSO4(-) ions.

PubMed

Singh, Jasminder; Yadav, Manisha; Singh, Ajnesh; Singh, Narinder

2015-07-28

A Schiff base based tripodal receptor was synthesized and complexed with a zinc metal ion (n17) using a very easy single step process. The resulting complex was fully characterized by CHN and single crystal XRD. The real time application of the complex in aqueous media was devised by preparing its organic nanoparticles (ONPs) and their sensor activity was tested with various anions by observing changes in the fluorescence profile of n17. It was observed that ONPs of n17 responded excellently for fluoride and sulfate, producing two different signals, with detection limits of 4.84 × 10(-12) M and 5.67 × 10(-9) M respectively, without having any interference from each other. The real time application of the sensor was also tested using various samples collected from various daily utility items and found to respond exceptionally well.

Cardiac Care Assistance using Self Configured Sensor Network—a Remote Patient Monitoring System

NASA Astrophysics Data System (ADS)

Sarma Dhulipala, V. R.; Kanagachidambaresan, G. R.

2014-04-01

Pervasive health care systems are used to monitor patients remotely without disturbing the normal day-to-day activities in real-time. Wearable physiological sensors required to monitor various significant ecological parameters of the patients are connected to Body Central Unit (BCU). Body Sensor Network (BSN) updates data in real-time and are designed to transmit alerts against abnormalities which enables quick response by medical units in case of an emergency. BSN helps monitoring patient without any need for attention to the subject. BSN helps in reducing the stress and strain caused by hospital environment. In this paper, mathematical models for heartbeat signal, electro cardio graph (ECG) signal and pulse rate are introduced. These signals are compared and their RMS difference-fast Fourier transforms (PRD-FFT) are processed. In the context of cardiac arrest, alert messages of these parameters and first aid for post-surgical operations has been suggested.

A Lightweight Hierarchical Activity Recognition Framework Using Smartphone Sensors

PubMed Central

Han, Manhyung; Bang, Jae Hun; Nugent, Chris; McClean, Sally; Lee, Sungyoung

2014-01-01

Activity recognition for the purposes of recognizing a user's intentions using multimodal sensors is becoming a widely researched topic largely based on the prevalence of the smartphone. Previous studies have reported the difficulty in recognizing life-logs by only using a smartphone due to the challenges with activity modeling and real-time recognition. In addition, recognizing life-logs is difficult due to the absence of an established framework which enables the use of different sources of sensor data. In this paper, we propose a smartphone-based Hierarchical Activity Recognition Framework which extends the Naïve Bayes approach for the processing of activity modeling and real-time activity recognition. The proposed algorithm demonstrates higher accuracy than the Naïve Bayes approach and also enables the recognition of a user's activities within a mobile environment. The proposed algorithm has the ability to classify fifteen activities with an average classification accuracy of 92.96%. PMID:25184486

PAVENET OS: A Compact Hard Real-Time Operating System for Precise Sampling in Wireless Sensor Networks

NASA Astrophysics Data System (ADS)

Saruwatari, Shunsuke; Suzuki, Makoto; Morikawa, Hiroyuki

The paper shows a compact hard real-time operating system for wireless sensor nodes called PAVENET OS. PAVENET OS provides hybrid multithreading: preemptive multithreading and cooperative multithreading. Both of the multithreading are optimized for two kinds of tasks on wireless sensor networks, and those are real-time tasks and best-effort ones. PAVENET OS can efficiently perform hard real-time tasks that cannot be performed by TinyOS. The paper demonstrates the hybrid multithreading realizes compactness and low overheads, which are comparable to those of TinyOS, through quantitative evaluation. The evaluation results show PAVENET OS performs 100 Hz sensor sampling with 0.01% jitter while performing wireless communication tasks, whereas optimized TinyOS has 0.62% jitter. In addition, PAVENET OS has a small footprint and low overheads (minimum RAM size: 29 bytes, minimum ROM size: 490 bytes, minimum task switch time: 23 cycles).

T-L Plane Abstraction-Based Energy-Efficient Real-Time Scheduling for Multi-Core Wireless Sensors.

PubMed

Kim, Youngmin; Lee, Ki-Seong; Pham, Ngoc-Son; Lee, Sun-Ro; Lee, Chan-Gun

2016-07-08

Energy efficiency is considered as a critical requirement for wireless sensor networks. As more wireless sensor nodes are equipped with multi-cores, there are emerging needs for energy-efficient real-time scheduling algorithms. The T-L plane-based scheme is known to be an optimal global scheduling technique for periodic real-time tasks on multi-cores. Unfortunately, there has been a scarcity of studies on extending T-L plane-based scheduling algorithms to exploit energy-saving techniques. In this paper, we propose a new T-L plane-based algorithm enabling energy-efficient real-time scheduling on multi-core sensor nodes with dynamic power management (DPM). Our approach addresses the overhead of processor mode transitions and reduces fragmentations of the idle time, which are inherent in T-L plane-based algorithms. Our experimental results show the effectiveness of the proposed algorithm compared to other energy-aware scheduling methods on T-L plane abstraction.

Real-Time Fault Classification for Plasma Processes

PubMed Central

Yang, Ryan; Chen, Rongshun

2011-01-01

Plasma process tools, which usually cost several millions of US dollars, are often used in the semiconductor fabrication etching process. If the plasma process is halted due to some process fault, the productivity will be reduced and the cost will increase. In order to maximize the product/wafer yield and tool productivity, a timely and effective fault process detection is required in a plasma reactor. The classification of fault events can help the users to quickly identify fault processes, and thus can save downtime of the plasma tool. In this work, optical emission spectroscopy (OES) is employed as the metrology sensor for in-situ process monitoring. Splitting into twelve different match rates by spectrum bands, the matching rate indicator in our previous work (Yang, R.; Chen, R.S. Sensors 2010, 10, 5703–5723) is used to detect the fault process. Based on the match data, a real-time classification of plasma faults is achieved by a novel method, developed in this study. Experiments were conducted to validate the novel fault classification. From the experimental results, we may conclude that the proposed method is feasible inasmuch that the overall accuracy rate of the classification for fault event shifts is 27 out of 28 or about 96.4% in success. PMID:22164001

A Sensor Failure Simulator for Control System Reliability Studies

NASA Technical Reports Server (NTRS)

Melcher, K. J.; Delaat, J. C.; Merrill, W. C.; Oberle, L. G.; Sadler, G. G.; Schaefer, J. H.

1986-01-01

A real-time Sensor Failure Simulator (SFS) was designed and assembled for the Advanced Detection, Isolation, and Accommodation (ADIA) program. Various designs were considered. The design chosen features an IBM-PC/XT. The PC is used to drive analog circuitry for simulating sensor failures in real-time. A user defined scenario describes the failure simulation for each of the five incoming sensor signals. Capabilities exist for editing, saving, and retrieving the failure scenarios. The SFS has been tested closed-loop with the Controls Interface and Monitoring (CIM) unit, the ADIA control, and a real-time F100 hybrid simulation. From a productivity viewpoint, the menu driven user interface has proven to be efficient and easy to use. From a real-time viewpoint, the software controlling the simulation loop executes at greater than 100 cycles/sec.

A sensor failure simulator for control system reliability studies

NASA Astrophysics Data System (ADS)

Melcher, K. J.; Delaat, J. C.; Merrill, W. C.; Oberle, L. G.; Sadler, G. G.; Schaefer, J. H.

A real-time Sensor Failure Simulator (SFS) was designed and assembled for the Advanced Detection, Isolation, and Accommodation (ADIA) program. Various designs were considered. The design chosen features an IBM-PC/XT. The PC is used to drive analog circuitry for simulating sensor failures in real-time. A user defined scenario describes the failure simulation for each of the five incoming sensor signals. Capabilities exist for editing, saving, and retrieving the failure scenarios. The SFS has been tested closed-loop with the Controls Interface and Monitoring (CIM) unit, the ADIA control, and a real-time F100 hybrid simulation. From a productivity viewpoint, the menu driven user interface has proven to be efficient and easy to use. From a real-time viewpoint, the software controlling the simulation loop executes at greater than 100 cycles/sec.

Real-Time Earthquake Monitoring with Spatio-Temporal Fields

NASA Astrophysics Data System (ADS)

Whittier, J. C.; Nittel, S.; Subasinghe, I.

2017-10-01

With live streaming sensors and sensor networks, increasingly large numbers of individual sensors are deployed in physical space. Sensor data streams are a fundamentally novel mechanism to deliver observations to information systems. They enable us to represent spatio-temporal continuous phenomena such as radiation accidents, toxic plumes, or earthquakes almost as instantaneously as they happen in the real world. Sensor data streams discretely sample an earthquake, while the earthquake is continuous over space and time. Programmers attempting to integrate many streams to analyze earthquake activity and scope need to write code to integrate potentially very large sets of asynchronously sampled, concurrent streams in tedious application code. In previous work, we proposed the field stream data model (Liang et al., 2016) for data stream engines. Abstracting the stream of an individual sensor as a temporal field, the field represents the Earth's movement at the sensor position as continuous. This simplifies analysis across many sensors significantly. In this paper, we undertake a feasibility study of using the field stream model and the open source Data Stream Engine (DSE) Apache Spark(Apache Spark, 2017) to implement a real-time earthquake event detection with a subset of the 250 GPS sensor data streams of the Southern California Integrated GPS Network (SCIGN). The field-based real-time stream queries compute maximum displacement values over the latest query window of each stream, and related spatially neighboring streams to identify earthquake events and their extent. Further, we correlated the detected events with an USGS earthquake event feed. The query results are visualized in real-time.

Intraluminal laser atherectomy with ultrasound and electromagnetic guidance

NASA Astrophysics Data System (ADS)

Gregory, Kenton W.; Aretz, H. Thomas; Martinelli, Michael A.; LeDet, Earl G.; Hatch, G. F.; Gregg, Richard E.; Sedlacek, Tomas; Haase, Wayne C.

1991-05-01

The MagellanTM coronary laser atherectomy system is described. It uses high- resolution ultrasound imaging and electromagnetic sensing to provide real-time guidance and control of laser therapy in the coronary arteries. The system consists of a flexible catheter, an electromagnetic navigation antenna, a sensor signal processor and a computer for image processing and display. The small, flexible catheter combines an ultrasound transducer and laser delivery optics, aimed at the artery wall, and an electromagnetic receiving sensor. An extra-corporeal electromagnetic transmit antenna, in combination with catheter sensors, locates the position of the ultrasound and laser beams in the artery. Navigation and ultrasound data are processed electronically to produce real-time, transverse, and axial cross-section images of the artery wall at selected locations. By exploiting the ability of ultrasound to image beneath the surface of artery walls, it is possible to identify candidate treatment sites and perform safe radial laser debulking of atherosclerotic plaque with reduced danger of perforation. The utility of the system in plaque identification and ablation is demonstrated with imaging and experimental results.

Visualization of Nicotine Adenine Dinucleotide Redox Homeostasis with Genetically Encoded Fluorescent Sensors.

PubMed

Zhao, Yuzheng; Zhang, Zhuo; Zou, Yejun; Yang, Yi

2018-01-20

Beyond their roles as redox currency in living organisms, pyridine dinucleotides (NAD + /NADH and NADP + /NADPH) are also precursors or cosubstrates of great significance in various physiologic and pathologic processes. Recent Advances: For many years, it was challenging to develop methodologies for monitoring pyridine dinucleotides in situ or in vivo. Recent advances in fluorescent protein-based sensors provide a rapid, sensitive, specific, and real-time readout of pyridine dinucleotide dynamics in single cells or in vivo, thereby opening a new era of pyridine dinucleotide bioimaging. In this article, we summarize the developments in genetically encoded fluorescent sensors for NAD + /NADH and NADP + /NADPH redox states, as well as their applications in life sciences and drug discovery. The strengths and weaknesses of individual sensors are also discussed. These sensors have the advantages of being specific and organelle targetable, enabling real-time monitoring and subcellular-level quantification of targeted molecules in living cells and in vivo. NAD + /NADH and NADP + /NADPH have distinct functions in metabolic and redox regulation, and thus, a comprehensive evaluation of metabolic and redox states must be multiplexed with a combination of various metabolite sensors in a single cell. Antioxid. Redox Signal. 28, 213-229.

Optical fibre luminescence sensor for real-time LDR brachytherapy dosimetry

NASA Astrophysics Data System (ADS)

Woulfe, P.; Sullivan, F. J.; O'Keeffe, S.

2016-05-01

An optical fibre sensor for monitoring low dose radiation is presented. The sensor is based on a scintillation material embedded within the optical fibre core, which emits visible light when exposed to low level ionising radiation. The incident level of ionising radiation can be determined by analysing the optical emission. An optical fibre sensor is presented, based on radioluminescence whereby radiation sensitive scintillation material, terbium doped gadolinium oxysulphide (Gd2O2S:Tb), is embedded in a cavity of 250μm of a 500μm plastic optical fibre. The sensor is designed for in-vivo monitoring of the radiation dose during radio-active seed implantation for brachytherapy, in prostate cancer treatment, providing oncologists with real-time information of the radiation dose to the target area and/or nearby critical structures. The radiation from the brachytherapy seeds causes emission of visible light from the scintillation material through the process of radioluminescence, which penetrates the fibre, propagating along the optical fibre for remote detection using a multi-pixel photon counter. The sensor demonstrates a high sensitivity to Iodine-125, the radioactive source most commonly used in brachytherapy for treating prostate cancer.

Optical fibre luminescence sensor for real-time LDR brachytherapy dosimetry

NASA Astrophysics Data System (ADS)

Woulfe, P.; O'Keeffe, S.; Sullivan, F. J.

2018-02-01

An optical fibre sensor for monitoring low dose radiation is presented. The sensor is based on a scintillation material embedded within the optical fibre core, which emits visible light when exposed to low level ionising radiation. The incident level of ionising radiation can be determined by analysing the optical emission. An optical fibre sensor is developed, based on radioluminescence whereby radiation sensitive scintillation material, terbium doped gadolinium oxysulphide (Gd2O2S:Tb), is embedded in a cavity of 700μm of a 1mm plastic optical fibre. The sensor is designed for in-vivo monitoring of the radiation dose during radio-active seed implantation for low dose rate (LDR) brachytherapy, in prostate cancer treatment, providing radiation oncologists with real-time information of the radiation dose to the target area and/or nearby organs at risk (OARs). The radiation from the brachytherapy seeds causes emission of visible light from the scintillation material through the process of radioluminescence, which penetrates the fibre, propagating along the optical fibre for remote detection using a multi-pixel photon counter. The sensor demonstrates a high sensitivity to 0.397mCi of Iodine125, the radioactive source most commonly used in brachytherapy for treating prostate cancer.

An embedded multi-core parallel model for real-time stereo imaging

NASA Astrophysics Data System (ADS)

He, Wenjing; Hu, Jian; Niu, Jingyu; Li, Chuanrong; Liu, Guangyu

2018-04-01

The real-time processing based on embedded system will enhance the application capability of stereo imaging for LiDAR and hyperspectral sensor. The task partitioning and scheduling strategies for embedded multiprocessor system starts relatively late, compared with that for PC computer. In this paper, aimed at embedded multi-core processing platform, a parallel model for stereo imaging is studied and verified. After analyzing the computing amount, throughout capacity and buffering requirements, a two-stage pipeline parallel model based on message transmission is established. This model can be applied to fast stereo imaging for airborne sensors with various characteristics. To demonstrate the feasibility and effectiveness of the parallel model, a parallel software was designed using test flight data, based on the 8-core DSP processor TMS320C6678. The results indicate that the design performed well in workload distribution and had a speed-up ratio up to 6.4.

Turbulence Characterization and Control

DTIC Science & Technology

1976-06-01

INSTRUMENTATION 2. 1 Real-Time Data Processing System 2. 2 Routine Meteorological Sensors 2. 3 Microthermal Sensors 2.4 Seeing Monitor 2. 5...Meteorological Tower l8 2-4 Fat Wire Microthermal Probe, Partially Disassembled to 19 Show Integral Electronics 2-5 ASP/SM Combination Shown Mounted...section. 1. 2 PROGRAM STATUS As of the date of this report, the status of the experimental systems are as follows: • Microthermal and

Developing a robust wireless sensor network structure for environmental sensing

NASA Astrophysics Data System (ADS)

Zhang, Z.; Oroza, C.; Glaser, S. D.; Bales, R. C.; Conklin, M. H.

2013-12-01

The American River Hydrologic Observatory is being strategically deployed as a real-time ground-based measurement network that delivers accurate and timely information on snow conditions and other hydrologic attributes with a previously unheard of granularity of time and space. The basin-scale network involves 18 sub-networks set out at physiographically representative locations spanning the seasonally snow-covered half of the 5000 km2 American river basin. Each sub-network, covering about a 1-km2 area, consists of 10 wirelessly networked sensing nodes that continuously measure and telemeter temperature, and snow depth; plus selected locations are equipped with sensors for relative humidity, solar radiation, and soil moisture at several depths. The sensor locations were chosen to maximize the variance sampled for snow depth within the basin. Network design and deployment involves an iterative but efficient process. After sensor-station locations are determined, a robust network of interlinking sensor stations and signal repeaters must be constructed to route sensor data to a central base station with a two-way communicable data uplink. Data can then be uploaded from site to remote servers in real time through satellite and cell modems. Signal repeaters are placed for robustness of a self-healing network with redundant signal paths to the base station. Manual, trial-and-error heuristic approaches for node placement are inefficient and labor intensive. In that approach field personnel must restructure the network in real time and wait for new network statistics to be calculated at the base station before finalizing a placement, acting without knowledge of the global topography or overall network structure. We show how digital elevation plus high-definition aerial photographs to give foliage coverage can optimize planning of signal repeater placements and guarantee a robust network structure prior to the physical deployment. We can also 'stress test' the final network by simulating the failure of an individual node and investigating the effect and the self-healing ability of the stressed network. The resulting sensor network can survive temporary service interruption from a small subset of signal repeaters and sensor stations. The robustness and the resilient of the network performance ensure the integrity of the dataset and the real-time transmissibility during harsh conditions.

High-resolution distributed temperature sensing with the multiphoton-timing technique

NASA Astrophysics Data System (ADS)

Höbel, M.; Ricka, J.; Wüthrich, M.; Binkert, Th.

1995-06-01

We report on a multiphoton-timing distributed temperature sensor (DTS) based on the concept of distributed anti-Stokes Raman thermometry. The sensor combines the advantage of very high spatial resolution (40 cm) with moderate measurement times. In 5 min it is possible to determine the temperature of as many as 4000 points along an optical fiber with an accuracy Delta T less than 2 deg C. The new feature of the DTS system is the combination of a fast single-photon avalanche diode with specially designed real-time signal-processing electronics. We discuss various parameters that affect the operation of analog and photon-timing DTS systems. Particular emphasis is put on the consequences of the nonideal behavior of sensor components and the corresponding correction procedures.

Exploring infrared sensoring for real time welding defects monitoring in GTAW.

PubMed

Alfaro, Sadek C A; Franco, Fernand Díaz

2010-01-01

This paper presents an evaluation of an infrared sensor for monitoring the welding pool temperature in a Gas Tungsten Arc Welding (GTAW) process. The purpose of the study is to develop a real time system control. It is known that the arc welding pool temperature is related to the weld penetration depth; therefore, by monitoring the temperature, the arc pool temperature and penetration depth are also monitored. Various experiments were performed; in some of them the current was varied and the temperature changes were registered, in others, defects were induced throughout the path of the weld bead for a fixed current. These simulated defects resulted in abrupt changes in the average temperature values, thus providing an indication of the presence of a defect. The data has been registered with an acquisition card. To identify defects in the samples under infrared emissions, the timing series were analyzed through graphics and statistic methods. The selection of this technique demonstrates the potential for infrared emission as a welding monitoring parameter sensor.

Exploring Infrared Sensoring for Real Time Welding Defects Monitoring in GTAW

PubMed Central

Alfaro, Sadek C. A.; Franco, Fernand Díaz

2010-01-01

This paper presents an evaluation of an infrared sensor for monitoring the welding pool temperature in a Gas Tungsten Arc Welding (GTAW) process. The purpose of the study is to develop a real time system control. It is known that the arc welding pool temperature is related to the weld penetration depth; therefore, by monitoring the temperature, the arc pool temperature and penetration depth are also monitored. Various experiments were performed; in some of them the current was varied and the temperature changes were registered, in others, defects were induced throughout the path of the weld bead for a fixed current. These simulated defects resulted in abrupt changes in the average temperature values, thus providing an indication of the presence of a defect. The data has been registered with an acquisition card. To identify defects in the samples under infrared emissions, the timing series were analyzed through graphics and statistic methods. The selection of this technique demonstrates the potential for infrared emission as a welding monitoring parameter sensor. PMID:22219697

Development of an Open Source Based Sensor Platform for an Advanced and Comprehensive in-situ DOC Monitoring

NASA Astrophysics Data System (ADS)

Schima, Robert; Goblirsch, Tobias; Paschen, Mathias; Rinke, Karsten; Schelwat, Heinz; Dietrich, Peter; Bumberger, Jan

2016-04-01

The impact of global change, intensive agriculture and complex interactions between humans and the environment show different effects on different scales. However, the desire to obtain a better understanding of ecosystems and process dynamics in nature accentuates the need for observing these processes in higher temporal and spatial resolutions. Especially with regard to the process dynamics and heterogeneity of water catchment areas, a comprehensive monitoring of the ongoing processes and effects remains to be a challenging issue in the field of applied environmental research. Moreover, harsh conditions and a variety of influencing process parameters are representing a particular challenge due to an adaptive in-situ monitoring of vast areas. Today, open source based electronics and cost-effective sensors and sensor components are offering a promising approach to investigate new possibilities of smart phone based mobile data acquisition and comprehensive ad-hoc monitoring of environmental processes. Accordingly, our project aims the development of new strategies for mobile data acquisition and real-time processing of user-specific environmental data, based on a holistic and integrated process. To this end, the concept of our monitoring system covers the data collection, data processing and data integration as well as the data provision within one infrastructure. The whole monitoring system consists of several mobile sensor devices, a smart phone app (Android) and a web service for data processing, data provision and data visualization. The smart phone app allows the configuration of the mobile sensor device and provides some built-in functions such as data visualization or data transmission via e-mail. Besides the measurement of temperature and humidity in air, the mobile sensor device is able to acquire sensor readings for the content of dissolved organic compounds (λ = 254 nm) and turbidity (λ = 860 nm) of surface water based on the developed optical in-situ sensor probe. Here, the miniaturized optical sensor probe allows the monitoring of even shallow water bodies with a depth of less than 5 cm. Compared to common techniques, the inexpensive sensor parts and robust emitting LEDs allow an improved widespread and comprehensive monitoring due to a higher amount of sensor devices. Furthermore, the system consists of a GPS module, a real-time clock and a GSM unit which allow space and time resolved measurements. On October 6th, 2015 an initial experiment was started at the Bode catchment in the Harz region (Germany). Here, the developed DOC and turbidity sensor probes were installed directly at the riverside next to existing sampling points of a large-scaled long-term observation project. The results show a good correspondence between our sensor development and the installed and established instruments. This represents a decisive and cost-effective contribution in the area of environmental research and the monitoring of vast catchment areas.

Developing a Signature Based Safeguards Approach for the Electrorefiner and Salt Cleanup Unit Operations in Pyroprocessing Facilities

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

Murphy, Chantell Lynne-Marie

Traditional nuclear materials accounting does not work well for safeguards when applied to pyroprocessing. Alternate methods such as Signature Based Safeguards (SBS) are being investigated. The goal of SBS is real-time/near-real-time detection of anomalous events in the pyroprocessing facility as they could indicate loss of special nuclear material. In high-throughput reprocessing facilities, metric tons of separated material are processed that must be accounted for. Even with very low uncertainties of accountancy measurements (<0.1%) the uncertainty of the material balances is still greater than the desired level. Novel contributions of this work are as follows: (1) significant enhancement of SBS developmentmore » for the salt cleanup process by creating a new gas sparging process model, selecting sensors to monitor normal operation, identifying safeguards-significant off-normal scenarios, and simulating those off-normal events and generating sensor output; (2) further enhancement of SBS development for the electrorefiner by simulating off-normal events caused by changes in salt concentration and identifying which conditions lead to Pu and Cm not tracking throughout the rest of the system; and (3) new contribution in applying statistical techniques to analyze the signatures gained from these two models to help draw real-time conclusions on anomalous events.« less

Microwave plasma monitoring system for the elemental composition analysis of high temperature process streams

DOEpatents

Woskov, Paul P.; Cohn, Daniel R.; Titus, Charles H.; Surma, Jeffrey E.

1997-01-01

Microwave-induced plasma for continuous, real time trace element monitoring under harsh and variable conditions. The sensor includes a source of high power microwave energy and a shorted waveguide made of a microwave conductive, high temperature capability refractory material communicating with the source of the microwave energy to generate a plasma. The high power waveguide is constructed to be robust in a hot, hostile environment. It includes an aperture for the passage of gases to be analyzed and a spectrometer is connected to receive light from the plasma. Provision is made for real time in situ calibration. The spectrometer disperses the light, which is then analyzed by a computer. The sensor is capable of making continuous, real time quantitative measurements of desired elements, such as the heavy metals lead and mercury. The invention may be incorporated into a high temperature process device and implemented in situ for example, such as with a DC graphite electrode plasma arc furnace. The invention further provides a system for the elemental analysis of process streams by removing particulate and/or droplet samples therefrom and entraining such samples in the gas flow which passes through the plasma flame. Introduction of and entraining samples in the gas flow may be facilitated by a suction pump, regulating gas flow, gravity or combinations thereof.

Real-Time Telemetry System for Amperometric and Potentiometric Electrochemical Sensors

PubMed Central

Wang, Wei-Song; Huang, Hong-Yi; Chen, Shu-Chun; Ho, Kuo-Chuan; Lin, Chia-Yu; Chou, Tse-Chuan; Hu, Chih-Hsien; Wang, Wen-Fong; Wu, Cheng-Feng; Luo, Ching-Hsing

2011-01-01

A real-time telemetry system, which consists of readout circuits, an analog-to-digital converter (ADC), a microcontroller unit (MCU), a graphical user interface (GUI), and a radio frequency (RF) transceiver, is proposed for amperometric and potentiometric electrochemical sensors. By integrating the proposed system with the electrochemical sensors, analyte detection can be conveniently performed. The data is displayed in real-time on a GUI and optionally uploaded to a database via the Internet, allowing it to be accessed remotely. An MCU was implemented using a field programmable gate array (FPGA) to filter noise, transmit data, and provide control over peripheral devices to reduce power consumption, which in sleep mode is 70 mW lower than in operating mode. The readout circuits, which were implemented in the TSMC 0.18-μm CMOS process, include a potentiostat and an instrumentation amplifier (IA). The measurement results show that the proposed potentiostat has a detectable current range of 1 nA to 100 μA, and linearity with an R2 value of 0.99998 in each measured current range. The proposed IA has a common-mode rejection ratio (CMRR) greater than 90 dB. The proposed system was integrated with a potentiometric pH sensor and an amperometric nitrite sensor for in vitro experiments. The proposed system has high linearity (an R2 value greater than 0.99 was obtained in each experiment), a small size of 5.6 cm × 8.7 cm, high portability, and high integration. PMID:22164093

Real-time telemetry system for amperometric and potentiometric electrochemical sensors.

PubMed

Wang, Wei-Song; Huang, Hong-Yi; Chen, Shu-Chun; Ho, Kuo-Chuan; Lin, Chia-Yu; Chou, Tse-Chuan; Hu, Chih-Hsien; Wang, Wen-Fong; Wu, Cheng-Feng; Luo, Ching-Hsing

2011-01-01

A real-time telemetry system, which consists of readout circuits, an analog-to-digital converter (ADC), a microcontroller unit (MCU), a graphical user interface (GUI), and a radio frequency (RF) transceiver, is proposed for amperometric and potentiometric electrochemical sensors. By integrating the proposed system with the electrochemical sensors, analyte detection can be conveniently performed. The data is displayed in real-time on a GUI and optionally uploaded to a database via the Internet, allowing it to be accessed remotely. An MCU was implemented using a field programmable gate array (FPGA) to filter noise, transmit data, and provide control over peripheral devices to reduce power consumption, which in sleep mode is 70 mW lower than in operating mode. The readout circuits, which were implemented in the TSMC 0.18-μm CMOS process, include a potentiostat and an instrumentation amplifier (IA). The measurement results show that the proposed potentiostat has a detectable current range of 1 nA to 100 μA, and linearity with an R2 value of 0.99998 in each measured current range. The proposed IA has a common-mode rejection ratio (CMRR) greater than 90 dB. The proposed system was integrated with a potentiometric pH sensor and an amperometric nitrite sensor for in vitro experiments. The proposed system has high linearity (an R2 value greater than 0.99 was obtained in each experiment), a small size of 5.6 cm × 8.7 cm, high portability, and high integration.

Automated Image Intelligence Adaptive Sensor Management System for High Altitude Long Endurance UAVs in a Dynamic and Anti-Access Area Denial Environment

NASA Astrophysics Data System (ADS)

Kim, Gi Young

The problem we investigate deals with an Image Intelligence (IMINT) sensor allocation schedule for High Altitude Long Endurance UAVs in a dynamic and Anti-Access Area Denial (A2AD) environment. The objective is to maximize the Situational Awareness (SA) of decision makers. The value of SA can be improved in two different ways. First, if a sensor allocated to an Areas of Interest (AOI) detects target activity, then the SA value will be increased. Second, the SA value increases if an AOI is monitored for a certain period of time, regardless of target detections. These values are functions of the sensor allocation time, sensor type and mode. Relatively few studies in the archival literature have been devoted to an analytic, detailed explanation of the target detection process, and AOI monitoring value dynamics. These two values are the fundamental criteria used to choose the most judicious sensor allocation schedule. This research presents mathematical expressions for target detection processes, and shows the monitoring value dynamics. Furthermore, the dynamics of target detection is the result of combined processes between belligerent behavior (target activity) and friendly behavior (sensor allocation). We investigate these combined processes and derive mathematical expressions for simplified cases. These closed form mathematical models can be used for Measures of Effectiveness (MOEs), i.e., target activity detection to evaluate sensor allocation schedules. We also verify these models with discrete event simulations which can also be used to describe more complex systems. We introduce several methodologies to achieve a judicious sensor allocation schedule focusing on the AOI monitoring value. The first methodology is a discrete time integer programming model which provides an optimal solution but is impractical for real world scenarios due to its computation time. Thus, it is necessary to trade off the quality of solution with computation time. The Myopic Greedy Procedure (MGP) is a heuristic which chooses the largest immediate unit time return at each decision epoch. This reduces computation time significantly, but the quality of the solution may be only 95% of optimal (for small size problems). Another alternative is a multi-start random constructive Hybrid Myopic Greedy Procedure (H-MGP), which incorporates stochastic variation in choosing an action at each stage, and repeats it a predetermined number of times (roughly 99.3% of optimal with 1000 repetitions). Finally, the One Stage Look Ahead (OSLA) procedure considers all the 'top choices' at each stage for a temporary time horizon and chooses the best action (roughly 98.8% of optimal with no repetition). Using OSLA procedure, we can have ameliorated solutions within a reasonable computation time. Other important issues discussed in this research are methodologies for the development of input parameters for real world applications.

Fast gradient-based algorithm on extended landscapes for wave-front reconstruction of Earth observation satellite

NASA Astrophysics Data System (ADS)

Thiebaut, C.; Perraud, L.; Delvit, J. M.; Latry, C.

2016-07-01

We present an on-board satellite implementation of a gradient-based (optical flows) algorithm for the shifts estimation between images of a Shack-Hartmann wave-front sensor on extended landscapes. The proposed algorithm has low complexity in comparison with classical correlation methods which is a big advantage for being used on-board a satellite at high instrument data rate and in real-time. The electronic board used for this implementation is designed for space applications and is composed of radiation-hardened software and hardware. Processing times of both shift estimations and pre-processing steps are compatible of on-board real-time computation.

Leveraging knowledge from physiological data: on-body heat stress risk prediction with sensor networks.

PubMed

Gaura, Elena; Kemp, John; Brusey, James

2013-12-01

The paper demonstrates that wearable sensor systems, coupled with real-time on-body processing and actuation, can enhance safety for wearers of heavy protective equipment who are subjected to harsh thermal environments by reducing risk of Uncompensable Heat Stress (UHS). The work focuses on Explosive Ordnance Disposal operatives and shows that predictions of UHS risk can be performed in real-time with sufficient accuracy for real-world use. Furthermore, it is shown that the required sensory input for such algorithms can be obtained with wearable, non-intrusive sensors. Two algorithms, one based on Bayesian nets and another on decision trees, are presented for determining the heat stress risk, considering the mean skin temperature prediction as a proxy. The algorithms are trained on empirical data and have accuracies of 92.1±2.9% and 94.4±2.1%, respectively when tested using leave-one-subject-out cross-validation. In applications such as Explosive Ordnance Disposal operative monitoring, such prediction algorithms can enable autonomous actuation of cooling systems and haptic alerts to minimize casualties.

Low-Cost Detection of Thin Film Stress during Fabrication

NASA Technical Reports Server (NTRS)

Nabors, Sammy A.

2015-01-01

NASA's Marshall Space Flight Center has developed a simple, cost-effective optical method for thin film stress measurements during growth and/or subsequent annealing processes. Stress arising in thin film fabrication presents production challenges for electronic devices, sensors, and optical coatings; it can lead to substrate distortion and deformation, impacting the performance of thin film products. NASA's technique measures in-situ stress using a simple, noncontact fiber optic probe in the thin film vacuum deposition chamber. This enables real-time monitoring of stress during the fabrication process and allows for efficient control of deposition process parameters. By modifying process parameters in real time during fabrication, thin film stress can be optimized or controlled, improving thin film product performance.

ARPA surveillance technology for detection of targets hidden in foliage

NASA Astrophysics Data System (ADS)

Hoff, Lawrence E.; Stotts, Larry B.

1994-02-01

The processing of large quantities of synthetic aperture radar data in real time is a complex problem. Even the image formation process taxes today's most advanced computers. The use of complex algorithms with multiple channels adds another dimension to the computational problem. Advanced Research Projects Agency (ARPA) is currently planning on using the Paragon parallel processor for this task. The Paragon is small enough to allow its use in a sensor aircraft. Candidate algorithms will be implemented on the Paragon for evaluation for real time processing. In this paper ARPA technology developments for detecting targets hidden in foliage are reviewed and examples of signal processing techniques on field collected data are presented.

Posture and activity recognition and energy expenditure prediction in a wearable platform.

PubMed

Sazonova, Nadezhda; Browning, Raymond; Melanson, Edward; Sazonov, Edward

2014-01-01

The use of wearable sensors coupled with the processing power of mobile phones may be an attractive way to provide real-time feedback about physical activity and energy expenditure (EE). Here we describe use of a shoe-based wearable sensor system (SmartShoe) with a mobile phone for real-time prediction and display of time spent in various postures/physical activities and the resulting EE. To deal with processing power and memory limitations of the phone, we introduce new algorithms that require substantially less computational power. The algorithms were validated using data from 15 subjects who performed up to 15 different activities of daily living during a four-hour stay in a room calorimeter. Use of Multinomial Logistic Discrimination (MLD) for posture and activity classification resulted in an accuracy comparable to that of Support Vector Machines (SVM) (90% vs. 95%-98%) while reducing the running time by a factor of 190 and reducing the memory requirement by a factor of 104. Per minute EE estimation using activity-specific models resulted in an accurate EE prediction (RMSE of 0.53 METs vs. RMSE of 0.69 METs using previously reported SVM-branched models). These results demonstrate successful implementation of real-time physical activity monitoring and EE prediction system on a wearable platform.

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

Franzese, Oscar; Zhang, Li; Mahmoud, Anas M.

There are many instances in which it is possible to plan ahead for an emergency evacuation (e.g., an explosion at a chemical processing facility). For those cases, if an accident (or an attack) were to happen, then the best evacuation plan for the prevailing network and weather conditions would be deployed. In other cases (e.g., the derailment of a train transporting hazardous materials), there may not be any previously developed plan to be implemented and decisions must be made ad-hoc on how to proceed with an emergency evacuation. In both situations, the availability of real-time traffic information plays a criticalmore » role in the management of the evacuation operations. To improve public safety during a vehicular emergency evacuation it is necessary to detect losses of road capacity (due to incidents, for example) as early as possible. Once these bottlenecks are identified, re-routing strategies must be determined in real-time and deployed in the field to help dissipate the congestion and increase the efficiency of the evacuation. Due to cost constraints, only large urban areas have traffic sensor deployments that permit access to some sort of real-time traffic information; any evacuation taking place in any other areas of the country would have to proceed without real-time traffic information. The latter was the focus of this SERRI/DHS (Southeast Region Research Initiative/Department of Homeland Security) sponsored project. That is, the main objective on the project was to improve the operations during a vehicular emergency evacuation anywhere by using newly developed real-time traffic-information-gathering technologies to assess traffic conditions and therefore to potentially detect incidents on the main evacuation routes. Phase A of the project consisted in the development and testing of a prototype system composed of sensors that are engineered in such a way that they can be rapidly deployed in the field where and when they are needed. Each one of these sensors is also equipped with their own power supply and a GPS (Global Positioning System) device to auto-determine its spatial location on the transportation network under surveillance. The system is capable of assessing traffic parameters by identifying and re-identifying vehicles in the traffic stream as those vehicles pass over the sensors. The system of sensors transmits, through wireless communication, real-time traffic information (travel time and other parameters) to a command and control center via an NTCIP (National Transportation Communication for ITS Protocol) -compatible interface. As an alternative, an existing NTCIP-compatible system accepts the real-time traffic information mentioned and broadcasts the traffic information to emergency managers, the media and the public via the existing channels. A series of tests, both in a controlled environment and on the field, were conducted to study the feasibility of rapidly deploying the system of traffic sensors and to assess its ability to provide real-time traffic information during an emergency evacuation. The results of these tests indicated that the prototype sensors are reliable and accurate for the type of application that is the focus of this project.« less

Data Centric Sensor Stream Reduction for Real-Time Applications in Wireless Sensor Networks

PubMed Central

Aquino, Andre Luiz Lins; Nakamura, Eduardo Freire

2009-01-01

This work presents a data-centric strategy to meet deadlines in soft real-time applications in wireless sensor networks. This strategy considers three main aspects: (i) The design of real-time application to obtain the minimum deadlines; (ii) An analytic model to estimate the ideal sample size used by data-reduction algorithms; and (iii) Two data-centric stream-based sampling algorithms to perform data reduction whenever necessary. Simulation results show that our data-centric strategies meet deadlines without loosing data representativeness. PMID:22303145

The Contribution of GIS to Display and Analyze the Water Quality Data Collected by a Wireless Sensor Network: Case of Bouregreg Catchment, Morocco

NASA Astrophysics Data System (ADS)

Boubakri, S.; Rhinane, H.

2017-11-01

The monitoring of water quality is, in most cases, managed in the laboratory and not on real time bases. Besides this process being lengthy, it doesn't provide the required specifications to describe the evolution of the quality parameters that are of interest. This study presents the integration of Geographic Information Systems (GIS) with wireless sensor networks (WSN) aiming to create a system able to detect the parameters like temperature, salinity and conductivity in a Moroccan catchment scale and transmit information to the support station. This Information is displayed and evaluated in a GIS using maps and spatial dashboard to monitor the water quality in real time.

Reconfigurable Mobile System - Ground, sea and air applications

NASA Astrophysics Data System (ADS)

Lamonica, Gary L.; Sturges, James W.

1990-11-01

The Reconfigurable Mobile System (RMS) is a highly mobile data-processing unit for military users requiring real-time access to data gathered by airborne (and other) reconnaissance data. RMS combines high-performance computation and image processing workstations with resources for command/control/communications in a single, lightweight shelter. RMS is composed of off-the-shelf components, and is easily reconfigurable to land-vehicle or shipboard versions. Mission planning, which involves an airborne sensor platform's sensor coverage, considered aircraft/sensor capabilities in conjunction with weather, terrain, and threat scenarios. RMS's man-machine interface concept facilitates user familiarization and features iron-based function selection and windowing.

Use of ebRIM-based CSW with sensor observation services for registry and discovery of remote-sensing observations

NASA Astrophysics Data System (ADS)

Chen, Nengcheng; Di, Liping; Yu, Genong; Gong, Jianya; Wei, Yaxing

2009-02-01

Recent advances in Sensor Web geospatial data capture, such as high-resolution in satellite imagery and Web-ready data processing and modeling technologies, have led to the generation of large numbers of datasets from real-time or near real-time observations and measurements. Finding which sensor or data complies with criteria such as specific times, locations, and scales has become a bottleneck for Sensor Web-based applications, especially remote-sensing observations. In this paper, an architecture for use of the integration Sensor Observation Service (SOS) with the Open Geospatial Consortium (OGC) Catalogue Service-Web profile (CSW) is put forward. The architecture consists of a distributed geospatial sensor observation service, a geospatial catalogue service based on the ebXML Registry Information Model (ebRIM), SOS search and registry middleware, and a geospatial sensor portal. The SOS search and registry middleware finds the potential SOS, generating data granule information and inserting the records into CSW. The contents and sequence of the services, the available observations, and the metadata of the observations registry are described. A prototype system is designed and implemented using the service middleware technology and a standard interface and protocol. The feasibility and the response time of registry and retrieval of observations are evaluated using a realistic Earth Observing-1 (EO-1) SOS scenario. Extracting information from SOS requires the same execution time as record generation for CSW. The average data retrieval response time in SOS+CSW mode is 17.6% of that of the SOS-alone mode. The proposed architecture has the more advantages of SOS search and observation data retrieval than the existing sensor Web enabled systems.

A Risk Based Approach to Limit the Effects of Covert Channels for Internet Sensor Data Aggregators for Sensor Privacy

NASA Astrophysics Data System (ADS)

Viecco, Camilo H.; Camp, L. Jean

Effective defense against Internet threats requires data on global real time network status. Internet sensor networks provide such real time network data. However, an organization that participates in a sensor network risks providing a covert channel to attackers if that organization’s sensor can be identified. While there is benefit for every party when any individual participates in such sensor deployments, there are perverse incentives against individual participation. As a result, Internet sensor networks currently provide limited data. Ensuring anonymity of individual sensors can decrease the risk of participating in a sensor network without limiting data provision.

Compact, self-contained enhanced-vision system (EVS) sensor simulator

NASA Astrophysics Data System (ADS)

Tiana, Carlo

2007-04-01

We describe the model SIM-100 PC-based simulator, for imaging sensors used, or planned for use, in Enhanced Vision System (EVS) applications. Typically housed in a small-form-factor PC, it can be easily integrated into existing out-the-window visual simulators for fixed-wing or rotorcraft, to add realistic sensor imagery to the simulator cockpit. Multiple bands of infrared (short-wave, midwave, extended-midwave and longwave) as well as active millimeter-wave RADAR systems can all be simulated in real time. Various aspects of physical and electronic image formation and processing in the sensor are accurately (and optionally) simulated, including sensor random and fixed pattern noise, dead pixels, blooming, B-C scope transformation (MMWR). The effects of various obscurants (fog, rain, etc.) on the sensor imagery are faithfully represented and can be selected by an operator remotely and in real-time. The images generated by the system are ideally suited for many applications, ranging from sensor development engineering tradeoffs (Field Of View, resolution, etc.), to pilot familiarization and operational training, and certification support. The realistic appearance of the simulated images goes well beyond that of currently deployed systems, and beyond that required by certification authorities; this level of realism will become necessary as operational experience with EVS systems grows.

Real-Time Monitoring of Critical Care Analytes in the Bloodstream with Chemical Sensors: Progress and Challenges.

PubMed

Frost, Megan C; Meyerhoff, Mark E

2015-01-01

We review approaches and challenges in developing chemical sensor-based methods to accurately and continuously monitor levels of key analytes in blood related directly to the status of critically ill hospitalized patients. Electrochemical and optical sensor-based technologies have been pursued to measure important critical care species in blood [i.e., oxygen, carbon dioxide, pH, electrolytes (K(+), Na(+), Cl(-), etc.), glucose, and lactate] in real-time or near real-time. The two main configurations examined to date for achieving this goal have been intravascular catheter sensors and patient attached ex vivo sensors with intermittent blood sampling via an attached indwelling catheter. We discuss the status of these configurations and the main issues affecting the accuracy of the measurements, including cell adhesion and thrombus formation on the surface of the sensors, sensor drift, sensor selectivity, etc. Recent approaches to mitigate these nagging performance issues that have prevented these technologies from clinical use are also discussed.

NEEDS - Information Adaptive System

NASA Technical Reports Server (NTRS)

Kelly, W. L.; Benz, H. F.; Meredith, B. D.

1980-01-01

The Information Adaptive System (IAS) is an element of the NASA End-to-End Data System (NEEDS) Phase II and is focused toward onboard image processing. The IAS is a data preprocessing system which is closely coupled to the sensor system. Some of the functions planned for the IAS include sensor response nonuniformity correction, geometric correction, data set selection, data formatting, packetization, and adaptive system control. The inclusion of these sensor data preprocessing functions onboard the spacecraft will significantly improve the extraction of information from the sensor data in a timely and cost effective manner, and provide the opportunity to design sensor systems which can be reconfigured in near real-time for optimum performance. The purpose of this paper is to present the preliminary design of the IAS and the plans for its development.

Design of fiber optic based respiratory sensor for newborn incubator application

NASA Astrophysics Data System (ADS)

Dhia, Arika; Devara, Kresna; Abuzairi, Tomy; Poespawati, N. R.; Purnamaningsih, Retno W.

2018-02-01

This paper reports the design of respiratory sensor using fiber optic for newborn incubator application. The sensor works based on light intensity losses difference obtained due to thorax movement during respiration. The output of the sensor launched to support electronic circuits to be processed in Arduino Uno microcontroler such that the real-time respiratory rate (breath per minute) can be presented on LCD. Experiment results using thorax expansion of newborn simulator show that the system is able to measure respiratory rate from 10 up to 130 breaths per minute with 0.595% error and 0.2% hysteresis error.

Monitoring cure properties of out-of-autoclave BMI composites using IFPI sensor

NASA Astrophysics Data System (ADS)

Kaur, Amardeep; Anandan, Sudharshan; Yuan, Lei; Watkins, Steve E.; Chandrashekhara, K.; Xiao, Hai; Phan, Nam

2016-04-01

A non-destructive technique for inspection of a Bismaleimide (BMI) composite is presented using an optical fiber sensor. High performance BMI composites are used for Aerospace application for their mechanical strength. They are also used as an alternative to toughened epoxy resins. A femtosecond-laser-inscribed Intrinsic Fabry-Perot Interferometer (IFPI) sensor is used to perform real time cure monitoring of a BMI composite. The composite is cured using the out-of-autoclave (OOA) process. The IFPI sensor was used for in-situ monitoring; different curing stages are analyzed throughout the curing process. Temperature-induced-strain was measured to analyze the cure properties. The IFPI structure comprises of two reflecting mirrors inscribed on the core of the fiber using a femtosecond-laser manufacturing process. The manufacturing process makes the sensor thermally stable and robust for embedded applications. The sensor can withstand very high temperatures of up to 850 °C. The temperature and strain sensitivities of embedded IFPI sensor were measured to be 1.4 pm/μepsilon and 0.6 pm/μepsilon respectively.

Real-time turbulence profiling with a pair of laser guide star Shack-Hartmann wavefront sensors for wide-field adaptive optics systems on large to extremely large telescopes.

PubMed

Gilles, L; Ellerbroek, B L

2010-11-01

Real-time turbulence profiling is necessary to tune tomographic wavefront reconstruction algorithms for wide-field adaptive optics (AO) systems on large to extremely large telescopes, and to perform a variety of image post-processing tasks involving point-spread function reconstruction. This paper describes a computationally efficient and accurate numerical technique inspired by the slope detection and ranging (SLODAR) method to perform this task in real time from properly selected Shack-Hartmann wavefront sensor measurements accumulated over a few hundred frames from a pair of laser guide stars, thus eliminating the need for an additional instrument. The algorithm is introduced, followed by a theoretical influence function analysis illustrating its impulse response to high-resolution turbulence profiles. Finally, its performance is assessed in the context of the Thirty Meter Telescope multi-conjugate adaptive optics system via end-to-end wave optics Monte Carlo simulations.

Programmable Automated Welding System (PAWS)

NASA Technical Reports Server (NTRS)

Kline, Martin D.

1994-01-01

An ambitious project to develop an advanced, automated welding system is being funded as part of the Navy Joining Center with Babcock & Wilcox as the prime integrator. This program, the Programmable Automated Welding System (PAWS), involves the integration of both planning and real-time control activities. Planning functions include the development of a graphical decision support system within a standard, portable environment. Real-time control functions include the development of a modular, intelligent, real-time control system and the integration of a number of welding process sensors. This paper presents each of these components of the PAWS and discusses how they can be utilized to automate the welding operation.

Real-Time Mapping: Contemporary Challenges and the Internet of Things as the Way Forward

NASA Astrophysics Data System (ADS)

Bęcek, Kazimierz

2016-12-01

The Internet of Things (IoT) is an emerging technology that was conceived in 1999. The key components of the IoT are intelligent sensors, which represent objects of interest. The adjective `intelligent' is used here in the information gathering sense, not the psychological sense. Some 30 billion sensors that `know' the current status of objects they represent are already connected to the Internet. Various studies indicate that the number of installed sensors will reach 212 billion by 2020. Various scenarios of IoT projects show sensors being able to exchange data with the network as well as between themselves. In this contribution, we discuss the possibility of deploying the IoT in cartography for real-time mapping. A real-time map is prepared using data harvested through querying sensors representing geographical objects, and the concept of a virtual sensor for abstract objects, such as a land parcel, is presented. A virtual sensor may exist as a data record in the cloud. Sensors are identified by an Internet Protocol address (IP address), which implies that geographical objects through their sensors would also have an IP address. This contribution is an updated version of a conference paper presented by the author during the International Federation of Surveyors 2014 Congress in Kuala Lumpur. The author hopes that the use of the IoT for real-time mapping will be considered by the mapmaking community.

Sensors for process control Focus Team report

NASA Astrophysics Data System (ADS)

At the Semiconductor Technology Workshop, held in November 1992, the Semiconductor Industry Association (SIA) convened 179 semiconductor technology experts to assess the 15-year outlook for the semiconductor manufacturing industry. The output of the Workshop, a document entitled 'Semiconductor Technology: Workshop Working Group Reports,' contained an overall roadmap for the technology characteristics envisioned in integrated circuits (IC's) for the period 1992-2007. In addition, the document contained individual roadmaps for numerous key areas in IC manufacturing, such as film deposition, thermal processing, manufacturing systems, exposure technology, etc. The SIA Report did not contain a separate roadmap for contamination free manufacturing (CFM). A key component of CFM for the next 15 years is the use of sensors for (1) defect reduction, (2) improved product quality, (3) improved yield, (4) improved tool utilization through contamination reduction, and (5) real time process control in semiconductor fabrication. The objective of this Focus Team is to generate a Sensors for Process Control Roadmap. Implicit in this objective is the identification of gaps in current sensor technology so that research and development activity in the sensor industry can be stimulated to develop sensor systems capable of meeting the projected roadmap needs. Sensor performance features of interest include detection limit, specificity, sensitivity, ease of installation and maintenance, range, response time, accuracy, precision, ease and frequency of calibration, degree of automation, and adaptability to in-line process control applications.

Continuous, real time microwave plasma element sensor

DOEpatents

Woskov, Paul P.; Smatlak, Donna L.; Cohn, Daniel R.; Wittle, J. Kenneth; Titus, Charles H.; Surma, Jeffrey E.

1995-01-01

Microwave-induced plasma for continuous, real time trace element monitoring under harsh and variable conditions. The sensor includes a source of high power microwave energy and a shorted waveguide made of a microwave conductive, refractory material communicating with the source of the microwave energy to generate a plasma. The high power waveguide is constructed to be robust in a hot, hostile environment. It includes an aperture for the passage of gases to be analyzed and a spectrometer is connected to receive light from the plasma. Provision is made for real time in situ calibration. The spectrometer disperses the light, which is then analyzed by a computer. The sensor is capable of making continuous, real time quantitative measurements of desired elements, such as the heavy metals lead and mercury.

Exploring the impact of big data in economic geology using cloud-based synthetic sensor networks

NASA Astrophysics Data System (ADS)

Klump, J. F.; Robertson, J.

2015-12-01

In a market demanding lower resource prices and increasing efficiencies, resources companies are increasingly looking to the realm of real-time, high-frequency data streams to better measure and manage their minerals processing chain, from pit to plant to port. Sensor streams can include real-time drilling engineering information, data streams from mining trucks, and on-stream sensors operating in the plant feeding back rich chemical information. There are also many opportunities to deploy new sensor streams - unlike environmental monitoring networks, the mine environment is not energy- or bandwidth-limited. Although the promised efficiency dividends are inviting, the path to achieving these is difficult to see for most companies. As well as knowing where to invest in new sensor technology and how to integrate the new data streams, companies must grapple with risk-laden changes to their established methods of control to achieve maximum gains. What is required is a sandbox data environment for the development of analysis and control strategies at scale, allowing companies to de-risk proposed changes before actually deploying them to a live mine environment. In this presentation we describe our approach to simulating real-time scaleable data streams in a mine environment. Our sandbox consists of three layers: (a) a ground-truth layer that contains geological models, which can be statistically based on historical operations data, (b) a measurement layer - a network of RESTful synthetic sensor microservices which can simulate measurements of ground-truth properties, and (c) a control layer, which integrates the sensor streams and drives the measurement and optimisation strategies. The control layer could be a new machine learner, or simply a company's existing data infrastructure. Containerisation allows rapid deployment of large numbers of sensors, as well as service discovery to form a dynamic network of thousands of sensors, at a far lower cost than physically building the network.

A neuro-inspired spike-based PID motor controller for multi-motor robots with low cost FPGAs.

PubMed

Jimenez-Fernandez, Angel; Jimenez-Moreno, Gabriel; Linares-Barranco, Alejandro; Dominguez-Morales, Manuel J; Paz-Vicente, Rafael; Civit-Balcells, Anton

2012-01-01

In this paper we present a neuro-inspired spike-based close-loop controller written in VHDL and implemented for FPGAs. This controller has been focused on controlling a DC motor speed, but only using spikes for information representation, processing and DC motor driving. It could be applied to other motors with proper driver adaptation. This controller architecture represents one of the latest layers in a Spiking Neural Network (SNN), which implements a bridge between robotics actuators and spike-based processing layers and sensors. The presented control system fuses actuation and sensors information as spikes streams, processing these spikes in hard real-time, implementing a massively parallel information processing system, through specialized spike-based circuits. This spike-based close-loop controller has been implemented into an AER platform, designed in our labs, that allows direct control of DC motors: the AER-Robot. Experimental results evidence the viability of the implementation of spike-based controllers, and hardware synthesis denotes low hardware requirements that allow replicating this controller in a high number of parallel controllers working together to allow a real-time robot control.

A Neuro-Inspired Spike-Based PID Motor Controller for Multi-Motor Robots with Low Cost FPGAs

PubMed Central

Jimenez-Fernandez, Angel; Jimenez-Moreno, Gabriel; Linares-Barranco, Alejandro; Dominguez-Morales, Manuel J.; Paz-Vicente, Rafael; Civit-Balcells, Anton

2012-01-01

In this paper we present a neuro-inspired spike-based close-loop controller written in VHDL and implemented for FPGAs. This controller has been focused on controlling a DC motor speed, but only using spikes for information representation, processing and DC motor driving. It could be applied to other motors with proper driver adaptation. This controller architecture represents one of the latest layers in a Spiking Neural Network (SNN), which implements a bridge between robotics actuators and spike-based processing layers and sensors. The presented control system fuses actuation and sensors information as spikes streams, processing these spikes in hard real-time, implementing a massively parallel information processing system, through specialized spike-based circuits. This spike-based close-loop controller has been implemented into an AER platform, designed in our labs, that allows direct control of DC motors: the AER-Robot. Experimental results evidence the viability of the implementation of spike-based controllers, and hardware synthesis denotes low hardware requirements that allow replicating this controller in a high number of parallel controllers working together to allow a real-time robot control. PMID:22666004

Bi-Fi: an embedded sensor/system architecture for REMOTE biological monitoring.

PubMed

Farshchi, Shahin; Pesterev, Aleksey; Nuyujukian, Paul H; Mody, Istvan; Judy, Jack W

2007-11-01

Wireless-enabled processor modules intended for communicating low-frequency phenomena (i.e., temperature, humidity, and ambient light) have been enabled to acquire and transmit multiple biological signals in real time, which has been achieved by using computationally efficient data acquisition, filtering, and compression algorithms, and interfacing the modules with biological interface hardware. The sensor modules can acquire and transmit raw biological signals at a rate of 32 kb/s, which is near the hardware limit of the modules. Furthermore, onboard signal processing enables one channel, sampled at a rate of 4000 samples/s at 12-bit resolution, to be compressed via adaptive differential-pulse-code modulation (ADPCM) and transmitted in real time. In addition, the sensors can be configured to filter and transmit individual time-referenced "spike" waveforms, or to transmit the spike height and width for alleviating network traffic and increasing battery life. The system is capable of acquiring eight channels of analog signals as well as data via an asynchronous serial connection. A back-end server archives the biological data received via networked gateway sensors, and hosts them to a client application that enables users to browse recorded data. The system also acquires, filters, and transmits oxygen saturation and pulse rate via a commercial-off-the-shelf interface board. The system architecture can be configured for performing real-time nonobtrusive biological monitoring of humans or rodents. This paper demonstrates that low-power, computational, and bandwidth-constrained wireless-enabled platforms can indeed be leveraged for wireless biosignal monitoring.

Real-Time Performance of a Self-Powered Environmental IoT Sensor Network System.

PubMed

Wu, Fan; Rüdiger, Christoph; Yuce, Mehmet Rasit

2017-02-01

Wireless sensor networks (WSNs) play an increasingly important role in monitoring applications in many areas. With the emergence of the Internet-of-Things (IoT), many more lowpower sensors will need to be deployed in various environments to collect and monitor data about environmental factors in real time. Providing power supply to these sensor nodes becomes a critical challenge for realizations of IoT applications as sensor nodes are normally battery-powered and have a limited lifetime. This paper proposes a wireless sensor network that is powered by solar energy harvesting. The sensor network monitors the environmental data with low-power sensor electronics and forms a network using multiple XBee wireless modules. A detailed performance analysis of the network system under solar energy harvesting has been presented. The sensor network system and the proposed energy-harvesting techniques are configured to achieve a continuous energy source for the sensor network. The proposed energy-harvesting system has been successfully designed to enable an energy solution in order to keep sensor nodes active and reliable for a whole day. The paper also outlines some of our experiences in real-time implementation of a sensor network system with energy harvesting.

Real-Time Performance of a Self-Powered Environmental IoT Sensor Network System

PubMed Central

Wu, Fan; Rüdiger, Christoph; Yuce, Mehmet Rasit

2017-01-01

Wireless sensor networks (WSNs) play an increasingly important role in monitoring applications in many areas. With the emergence of the Internet-of-Things (IoT), many more low-power sensors will need to be deployed in various environments to collect and monitor data about environmental factors in real time. Providing power supply to these sensor nodes becomes a critical challenge for realizations of IoT applications as sensor nodes are normally battery-powered and have a limited lifetime. This paper proposes a wireless sensor network that is powered by solar energy harvesting. The sensor network monitors the environmental data with low-power sensor electronics and forms a network using multiple XBee wireless modules. A detailed performance analysis of the network system under solar energy harvesting has been presented. The sensor network system and the proposed energy-harvesting techniques are configured to achieve a continuous energy source for the sensor network. The proposed energy-harvesting system has been successfully designed to enable an energy solution in order to keep sensor nodes active and reliable for a whole day. The paper also outlines some of our experiences in real-time implementation of a sensor network system with energy harvesting. PMID:28157148

Semi-physical simulation test for micro CMOS star sensor

NASA Astrophysics Data System (ADS)

Yang, Jian; Zhang, Guang-jun; Jiang, Jie; Fan, Qiao-yun

2008-03-01

A designed star sensor must be extensively tested before launching. Testing star sensor requires complicated process with much time and resources input. Even observing sky on the ground is a challenging and time-consuming job, requiring complicated and expensive equipments, suitable time and location, and prone to be interfered by weather. And moreover, not all stars distributed on the sky can be observed by this testing method. Semi-physical simulation in laboratory reduces the testing cost and helps to debug, analyze and evaluate the star sensor system while developing the model. The test system is composed of optical platform, star field simulator, star field simulator computer, star sensor and the central data processing computer. The test system simulates the starlight with high accuracy and good parallelism, and creates static or dynamic image in FOV (Field of View). The conditions of the test are close to observing real sky. With this system, the test of a micro star tracker designed by Beijing University of Aeronautics and Astronautics has been performed successfully. Some indices including full-sky autonomous star identification time, attitude update frequency and attitude precision etc. meet design requirement of the star sensor. Error source of the testing system is also analyzed. It is concluded that the testing system is cost-saving, efficient, and contributes to optimizing the embed arithmetic, shortening the development cycle and improving engineering design processes.

Adaptive inferential sensors based on evolving fuzzy models.

PubMed

Angelov, Plamen; Kordon, Arthur

2010-04-01

A new technique to the design and use of inferential sensors in the process industry is proposed in this paper, which is based on the recently introduced concept of evolving fuzzy models (EFMs). They address the challenge that the modern process industry faces today, namely, to develop such adaptive and self-calibrating online inferential sensors that reduce the maintenance costs while keeping the high precision and interpretability/transparency. The proposed new methodology makes possible inferential sensors to recalibrate automatically, which reduces significantly the life-cycle efforts for their maintenance. This is achieved by the adaptive and flexible open-structure EFM used. The novelty of this paper lies in the following: (1) the overall concept of inferential sensors with evolving and self-developing structure from the data streams; (2) the new methodology for online automatic selection of input variables that are most relevant for the prediction; (3) the technique to detect automatically a shift in the data pattern using the age of the clusters (and fuzzy rules); (4) the online standardization technique used by the learning procedure of the evolving model; and (5) the application of this innovative approach to several real-life industrial processes from the chemical industry (evolving inferential sensors, namely, eSensors, were used for predicting the chemical properties of different products in The Dow Chemical Company, Freeport, TX). It should be noted, however, that the methodology and conclusions of this paper are valid for the broader area of chemical and process industries in general. The results demonstrate that well-interpretable and with-simple-structure inferential sensors can automatically be designed from the data stream in real time, which predict various process variables of interest. The proposed approach can be used as a basis for the development of a new generation of adaptive and evolving inferential sensors that can address the challenges of the modern advanced process industry.

Acoustic Source Localization via Time Difference of Arrival Estimation for Distributed Sensor Networks Using Tera-Scale Optical Core Devices

DOE PAGES

Imam, Neena; Barhen, Jacob

2009-01-01

For real-time acoustic source localization applications, one of the primary challenges is the considerable growth in computational complexity associated with the emergence of ever larger, active or passive, distributed sensor networks. These sensors rely heavily on battery-operated system components to achieve highly functional automation in signal and information processing. In order to keep communication requirements minimal, it is desirable to perform as much processing on the receiver platforms as possible. However, the complexity of the calculations needed to achieve accurate source localization increases dramatically with the size of sensor arrays, resulting in substantial growth of computational requirements that cannot bemore » readily met with standard hardware. One option to meet this challenge builds upon the emergence of digital optical-core devices. The objective of this work was to explore the implementation of key building block algorithms used in underwater source localization on the optical-core digital processing platform recently introduced by Lenslet Inc. This demonstration of considerably faster signal processing capability should be of substantial significance to the design and innovation of future generations of distributed sensor networks.« less

Design of a Mobile Low-Cost Sensor Network Using Urban Buses for Real-Time Ubiquitous Noise Monitoring.

PubMed

Alsina-Pagès, Rosa Ma; Hernandez-Jayo, Unai; Alías, Francesc; Angulo, Ignacio

2016-12-29

One of the main priorities of smart cities is improving the quality of life of their inhabitants. Traffic noise is one of the pollutant sources that causes a negative impact on the quality of life of citizens, which is gaining attention among authorities. The European Commission has promoted the Environmental Noise Directive 2002/49/EC (END) to inform citizens and to prevent the harmful effects of noise exposure. The measure of acoustic levels using noise maps is a strategic issue in the END action plan. Noise maps are typically calculated by computing the average noise during one year and updated every five years. Hence, the implementation of dynamic noise mapping systems could lead to short-term plan actions, besides helping to better understand the evolution of noise levels along time. Recently, some projects have started the monitoring of noise levels in urban areas by means of acoustic sensor networks settled in strategic locations across the city, while others have taken advantage of collaborative citizen sensing mobile applications. In this paper, we describe the design of an acoustic low-cost sensor network installed on public buses to measure the traffic noise in the city in real time. Moreover, the challenges that a ubiquitous bus acoustic measurement system entails are enumerated and discussed. Specifically, the analysis takes into account the feature extraction of the audio signal, the identification and separation of the road traffic noise from urban traffic noise, the hardware platform to measure and process the acoustic signal, the connectivity between the several nodes of the acoustic sensor network to store the data and, finally, the noise maps' generation process. The implementation and evaluation of the proposal in a real-life scenario is left for future work.

Design of a Mobile Low-Cost Sensor Network Using Urban Buses for Real-Time Ubiquitous Noise Monitoring

PubMed Central

Alsina-Pagès, Rosa Ma; Hernandez-Jayo, Unai; Alías, Francesc; Angulo, Ignacio

2016-01-01

One of the main priorities of smart cities is improving the quality of life of their inhabitants. Traffic noise is one of the pollutant sources that causes a negative impact on the quality of life of citizens, which is gaining attention among authorities. The European Commission has promoted the Environmental Noise Directive 2002/49/EC (END) to inform citizens and to prevent the harmful effects of noise exposure. The measure of acoustic levels using noise maps is a strategic issue in the END action plan. Noise maps are typically calculated by computing the average noise during one year and updated every five years. Hence, the implementation of dynamic noise mapping systems could lead to short-term plan actions, besides helping to better understand the evolution of noise levels along time. Recently, some projects have started the monitoring of noise levels in urban areas by means of acoustic sensor networks settled in strategic locations across the city, while others have taken advantage of collaborative citizen sensing mobile applications. In this paper, we describe the design of an acoustic low-cost sensor network installed on public buses to measure the traffic noise in the city in real time. Moreover, the challenges that a ubiquitous bus acoustic measurement system entails are enumerated and discussed. Specifically, the analysis takes into account the feature extraction of the audio signal, the identification and separation of the road traffic noise from urban traffic noise, the hardware platform to measure and process the acoustic signal, the connectivity between the several nodes of the acoustic sensor network to store the data and, finally, the noise maps’ generation process. The implementation and evaluation of the proposal in a real-life scenario is left for future work. PMID:28036065

MS-BWME: A Wireless Real-Time Monitoring System for Brine Well Mining Equipment

PubMed Central

Xiao, Xinqing; Zhu, Tianyu; Qi, Lin; Moga, Liliana Mihaela; Zhang, Xiaoshuan

2014-01-01

This paper describes a wireless real-time monitoring system (MS-BWME) to monitor the running state of pumps equipment in brine well mining and prevent potential failures that may produce unexpected interruptions with severe consequences. MS-BWME consists of two units: the ZigBee Wireless Sensors Network (WSN) unit and the real-time remote monitoring unit. MS-BWME was implemented and tested in sampled brine wells mining in Qinghai Province and four kinds of indicators were selected to evaluate the performance of the MS-BWME, i.e., sensor calibration, the system's real-time data reception, Received Signal Strength Indicator (RSSI) and sensor node lifetime. The results show that MS-BWME can accurately judge the running state of the pump equipment by acquiring and transmitting the real-time voltage and electric current data of the equipment from the spot and provide real-time decision support aid to help workers overhaul the equipment in a timely manner and resolve failures that might produce unexpected production down-time. The MS-BWME can also be extended to a wide range of equipment monitoring applications. PMID:25340455

The Waterviz: The Confluence of Science, Art and Music Illuminates Pattern and Process in Water Cycle Data

NASA Astrophysics Data System (ADS)

Rustad, L.; Martin, M.; Cortada, X.; Quinn, M.; Garlick, S.; Casey, M.; Green, M. B.

2017-12-01

The WaterViz for Hubbard Brook is a new online tool for creatively communicating water cycle science to a broad audience with real time hydrologic data. Interfacing between the hydrologic sciences, visual arts, music, education, and graphic design, the WaterViz for Hubbard Brook builds on a new generation of digital environmental sensors and wireless communication devices that are revolutionizing how scientists `see' the natural world. In a nutshell, hydrologic data are captured from small first order catchments at the Hubbard Brook Experimental Forest, NH using an array of environmental sensors. These data are transmitted to the internet in real time and are used to drive a computer model that calculates all components of the water cycle for the catchment in real time. These data, in turn, drive an artistic simulation (delivered as a flash animation) and musical sonification (delivered via an internet radio station) of the water cycle,accurately reflecting the hydrologic processes occurring at that moment in time. The WaterViz for Hubbard Brook provides a unique and novel approach to interactively and intuitively engage the viewer with vast amount of data and information on water cycle science. The WaterViz for Hubbard Brook is available at: https://waterviz.org.

Digibaro pressure instrument onboard the Phoenix Lander

NASA Astrophysics Data System (ADS)

Harri, A.-M.; Polkko, J.; Kahanpää, H. H.; Schmidt, W.; Genzer, M. M.; Haukka, H.; Savijarv1, H.; Kauhanen, J.

2009-04-01

The Phoenix Lander landed successfully on the Martian northern polar region. The mission is part of the National Aeronautics and Space Administration's (NASA's) Scout program. Pressure observations onboard the Phoenix lander were performed by an FMI (Finnish Meteorological Institute) instrument, based on a silicon diaphragm sensor head manufactured by Vaisala Inc., combined with MDA data processing electronics. The pressure instrument performed successfully throughout the Phoenix mission. The pressure instrument had 3 pressure sensor heads. One of these was the primary sensor head and the other two were used for monitoring the condition of the primary sensor head during the mission. During the mission the primary sensor was read with a sampling interval of 2 s and the other two were read less frequently as a check of instrument health. The pressure sensor system had a real-time data-processing and calibration algorithm that allowed the removal of temperature dependent calibration effects. In the same manner as the temperature sensor, a total of 256 data records (8.53 min) were buffered and they could either be stored at full resolution, or processed to provide mean, standard deviation, maximum and minimum values for storage on the Phoenix Lander's Meteorological (MET) unit.The time constant was approximately 3s due to locational constraints and dust filtering requirements. Using algorithms compensating for the time constant effect the temporal resolution was good enough to detect pressure drops associated with the passage of nearby dust devils.

T-L Plane Abstraction-Based Energy-Efficient Real-Time Scheduling for Multi-Core Wireless Sensors

PubMed Central

Kim, Youngmin; Lee, Ki-Seong; Pham, Ngoc-Son; Lee, Sun-Ro; Lee, Chan-Gun

2016-01-01

Energy efficiency is considered as a critical requirement for wireless sensor networks. As more wireless sensor nodes are equipped with multi-cores, there are emerging needs for energy-efficient real-time scheduling algorithms. The T-L plane-based scheme is known to be an optimal global scheduling technique for periodic real-time tasks on multi-cores. Unfortunately, there has been a scarcity of studies on extending T-L plane-based scheduling algorithms to exploit energy-saving techniques. In this paper, we propose a new T-L plane-based algorithm enabling energy-efficient real-time scheduling on multi-core sensor nodes with dynamic power management (DPM). Our approach addresses the overhead of processor mode transitions and reduces fragmentations of the idle time, which are inherent in T-L plane-based algorithms. Our experimental results show the effectiveness of the proposed algorithm compared to other energy-aware scheduling methods on T-L plane abstraction. PMID:27399722

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.

Intelligent Vehicle Health Management

NASA Technical Reports Server (NTRS)

Paris, Deidre E.; Trevino, Luis; Watson, Michael D.

2005-01-01

As a part of the overall goal of developing Integrated Vehicle Health Management systems for aerospace vehicles, the NASA Faculty Fellowship Program (NFFP) at Marshall Space Flight Center has performed a pilot study on IVHM principals which integrates researched IVHM technologies in support of Integrated Intelligent Vehicle Management (IIVM). IVHM is the process of assessing, preserving, and restoring system functionality across flight and ground systems (NASA NGLT 2004). The framework presented in this paper integrates advanced computational techniques with sensor and communication technologies for spacecraft that can generate responses through detection, diagnosis, reasoning, and adapt to system faults in support of INM. These real-time responses allow the IIVM to modify the affected vehicle subsystem(s) prior to a catastrophic event. Furthermore, the objective of this pilot program is to develop and integrate technologies which can provide a continuous, intelligent, and adaptive health state of a vehicle and use this information to improve safety and reduce costs of operations. Recent investments in avionics, health management, and controls have been directed towards IIVM. As this concept has matured, it has become clear the INM requires the same sensors and processing capabilities as the real-time avionics functions to support diagnosis of subsystem problems. New sensors have been proposed, in addition, to augment the avionics sensors to support better system monitoring and diagnostics. As the designs have been considered, a synergy has been realized where the real-time avionics can utilize sensors proposed for diagnostics and prognostics to make better real-time decisions in response to detected failures. IIVM provides for a single system allowing modularity of functions and hardware across the vehicle. The framework that supports IIVM consists of 11 major on-board functions necessary to fully manage a space vehicle maintaining crew safety and mission objectives: Guidance and Navigation; Communications and Tracking; Vehicle Monitoring; Information Transport and Integration; Vehicle Diagnostics; Vehicle Prognostics; Vehicle mission Planning; Automated Repair and Replacement; Vehicle Control; Human Computer Interface; and Onboard Verification and Validation. Furthermore, the presented framework provides complete vehicle management which not only allows for increased crew safety and mission success through new intelligence capabilities, but also yields a mechanism for more efficient vehicle operations. The representative IVHM technologies for computer platform using heterogeneous communication, 3) coupled electromagnetic oscillators for enhanced communications, 4) Linux-based real-time systems, 5) genetic algorithms, 6) Bayesian Networks, 7) evolutionary algorithms, 8) dynamic systems control modeling, and 9) advanced sensing capabilities. This paper presents IVHM technologies developed under NASA's NFFP pilot project and the integration of these technologies forms the framework for IIVM.

A real-time multi-channel monitoring system for stem cell culture process.

PubMed

Xicai Yue; Drakakis, E M; Lim, M; Radomska, A; Hua Ye; Mantalaris, A; Panoskaltsis, N; Cass, A

2008-06-01

A novel, up to 128 channels, multi-parametric physiological measurement system suitable for monitoring hematopoietic stem cell culture processes and cell cultures in general is presented in this paper. The system aims to measure in real-time the most important physical and chemical culture parameters of hematopoietic stem cells, including physicochemical parameters, nutrients, and metabolites, in a long-term culture process. The overarching scope of this research effort is to control and optimize the whole bioprocess by means of the acquisition of real-time quantitative physiological information from the culture. The system is designed in a modular manner. Each hardware module can operate as an independent gain programmable, level shift adjustable, 16 channel data acquisition system specific to a sensor type. Up to eight such data acquisition modules can be combined and connected to the host PC to realize the whole system hardware. The control of data acquisition and the subsequent management of data is performed by the system's software which is coded in LabVIEW. Preliminary experimental results presented here show that the system not only has the ability to interface to various types of sensors allowing the monitoring of different types of culture parameters. Moreover, it can capture dynamic variations of culture parameters by means of real-time multi-channel measurements thus providing additional information on both temporal and spatial profiles of these parameters within a bioreactor. The system is by no means constrained in the hematopoietic stem cell culture field only. It is suitable for cell growth monitoring applications in general.

A Low-Cost Tracking System for Running Race Applications Based on Bluetooth Low Energy Technology.

PubMed

Perez-Diaz-de-Cerio, David; Hernández-Solana, Ángela; Valdovinos, Antonio; Valenzuela, Jose Luis

2018-03-20

Timing points used in running races and other competition events are generally based on radio-frequency identification (RFID) technology. Athletes' times are calculated via passive RFID tags and reader kits. Specifically, the reader infrastructure needed is complex and requires the deployment of a mat or ramps which hide the receiver antennae under them. Moreover, with the employed tags, it is not possible to transmit additional and dynamic information such as pulse or oximetry monitoring, alarms, etc. In this paper we present a system based on two low complex schemes allowed in Bluetooth Low Energy (BLE): the non-connectable undirected advertisement process and a modified version of scannable undirected advertisement process using the new capabilities present in Bluetooth 5. After fully describing the system architecture, which allows full real-time position monitoring of the runners using mobile phones on the organizer side and BLE sensors on the participants' side, we derive the mobility patterns of runners and capacity requirements, which are determinant for evaluating the performance of the proposed system. They have been obtained from the analysis of the real data measured in the last Barcelona Marathon. By means of simulations, we demonstrate that, even under disadvantageous conditions (50% error ratio), both schemes perform reliably and are able to detect the 100% of the participants in all the cases. The cell coverage of the system needs to be adjusted when non-connectable process is considered. Nevertheless, through simulation and experimental, we show that the proposed scheme based on the new events available in Bluetooth 5 is clearly the best implementation alternative for all the cases, no matter the coverage area and the runner speed. The proposal widely exceeds the detection requirements of the real scenario, surpassing the measured peaks of 20 sensors per second incoming in the coverage area, moving at speeds that range from 1.5 m/s to 6.25 m/s. The designed real test-bed shows that the scheme is able to detect 72 sensors below 600 ms, fulfilling comfortably the requirements determined for the intended application. The main disadvantage of this system would be that the sensors are active, but we have proved that its consumption can be so low (9.5 µA) that, with a typical button cell, the sensor battery life would be over 10,000 h of use.

A Low-Cost Tracking System for Running Race Applications Based on Bluetooth Low Energy Technology

PubMed Central

2018-01-01

Timing points used in running races and other competition events are generally based on radio-frequency identification (RFID) technology. Athletes’ times are calculated via passive RFID tags and reader kits. Specifically, the reader infrastructure needed is complex and requires the deployment of a mat or ramps which hide the receiver antennae under them. Moreover, with the employed tags, it is not possible to transmit additional and dynamic information such as pulse or oximetry monitoring, alarms, etc. In this paper we present a system based on two low complex schemes allowed in Bluetooth Low Energy (BLE): the non-connectable undirected advertisement process and a modified version of scannable undirected advertisement process using the new capabilities present in Bluetooth 5. After fully describing the system architecture, which allows full real-time position monitoring of the runners using mobile phones on the organizer side and BLE sensors on the participants’ side, we derive the mobility patterns of runners and capacity requirements, which are determinant for evaluating the performance of the proposed system. They have been obtained from the analysis of the real data measured in the last Barcelona Marathon. By means of simulations, we demonstrate that, even under disadvantageous conditions (50% error ratio), both schemes perform reliably and are able to detect the 100% of the participants in all the cases. The cell coverage of the system needs to be adjusted when non-connectable process is considered. Nevertheless, through simulation and experimental, we show that the proposed scheme based on the new events available in Bluetooth 5 is clearly the best implementation alternative for all the cases, no matter the coverage area and the runner speed. The proposal widely exceeds the detection requirements of the real scenario, surpassing the measured peaks of 20 sensors per second incoming in the coverage area, moving at speeds that range from 1.5 m/s to 6.25 m/s. The designed real test-bed shows that the scheme is able to detect 72 sensors below 600 ms, fulfilling comfortably the requirements determined for the intended application. The main disadvantage of this system would be that the sensors are active, but we have proved that its consumption can be so low (9.5 µA) that, with a typical button cell, the sensor battery life would be over 10,000 h of use. PMID:29558432

Real-time oil-saturation monitoring in rock cores with low-field NMR.

PubMed

Mitchell, J; Howe, A M; Clarke, A

2015-07-01

Nuclear magnetic resonance (NMR) provides a powerful suite of tools for studying oil in reservoir core plugs at the laboratory scale. Low-field magnets are preferred for well-log calibration and to minimize magnetic-susceptibility-induced internal gradients in the porous medium. We demonstrate that careful data processing, combined with prior knowledge of the sample properties, enables real-time acquisition and interpretation of saturation state (relative amount of oil and water in the pores of a rock). Robust discrimination of oil and brine is achieved with diffusion weighting. We use this real-time analysis to monitor the forced displacement of oil from porous materials (sintered glass beads and sandstones) and to generate capillary desaturation curves. The real-time output enables in situ modification of the flood protocol and accurate control of the saturation state prior to the acquisition of standard NMR core analysis data, such as diffusion-relaxation correlations. Although applications to oil recovery and core analysis are demonstrated, the implementation highlights the general practicality of low-field NMR as an inline sensor for real-time industrial process control. Copyright © 2015 Elsevier Inc. All rights reserved.

Single-shot and single-sensor high/super-resolution microwave imaging based on metasurface.

PubMed

Wang, Libo; Li, Lianlin; Li, Yunbo; Zhang, Hao Chi; Cui, Tie Jun

2016-06-01

Real-time high-resolution (including super-resolution) imaging with low-cost hardware is a long sought-after goal in various imaging applications. Here, we propose broadband single-shot and single-sensor high-/super-resolution imaging by using a spatio-temporal dispersive metasurface and an imaging reconstruction algorithm. The metasurface with spatio-temporal dispersive property ensures the feasibility of the single-shot and single-sensor imager for super- and high-resolution imaging, since it can convert efficiently the detailed spatial information of the probed object into one-dimensional time- or frequency-dependent signal acquired by a single sensor fixed in the far-field region. The imaging quality can be improved by applying a feature-enhanced reconstruction algorithm in post-processing, and the desired imaging resolution is related to the distance between the object and metasurface. When the object is placed in the vicinity of the metasurface, the super-resolution imaging can be realized. The proposed imaging methodology provides a unique means to perform real-time data acquisition, high-/super-resolution images without employing expensive hardware (e.g. mechanical scanner, antenna array, etc.). We expect that this methodology could make potential breakthroughs in the areas of microwave, terahertz, optical, and even ultrasound imaging.

A Study about Kalman Filters Applied to Embedded Sensors

PubMed Central

Valade, Aurélien; Acco, Pascal; Grabolosa, Pierre; Fourniols, Jean-Yves

2017-01-01

Over the last decade, smart sensors have grown in complexity and can now handle multiple measurement sources. This work establishes a methodology to achieve better estimates of physical values by processing raw measurements within a sensor using multi-physical models and Kalman filters for data fusion. A driving constraint being production cost and power consumption, this methodology focuses on algorithmic complexity while meeting real-time constraints and improving both precision and reliability despite low power processors limitations. Consequently, processing time available for other tasks is maximized. The known problem of estimating a 2D orientation using an inertial measurement unit with automatic gyroscope bias compensation will be used to illustrate the proposed methodology applied to a low power STM32L053 microcontroller. This application shows promising results with a processing time of 1.18 ms at 32 MHz with a 3.8% CPU usage due to the computation at a 26 Hz measurement and estimation rate. PMID:29206187

Object positioning in storages of robotized workcells using LabVIEW Vision

NASA Astrophysics Data System (ADS)

Hryniewicz, P.; Banaś, W.; Sękala, A.; Gwiazda, A.; Foit, K.; Kost, G.

2015-11-01

During the manufacturing process, each performed task is previously developed and adapted to the conditions and the possibilities of the manufacturing plant. The production process is supervised by a team of specialists because any downtime causes great loss of time and hence financial loss. Sensors used in industry for tracking and supervision various stages of a production process make it much easier to maintain it continuous. One of groups of sensors used in industrial applications are non-contact sensors. This group includes: light barriers, optical sensors, rangefinders, vision systems, and ultrasonic sensors. Through to the rapid development of electronics the vision systems were widespread as the most flexible type of non-contact sensors. These systems consist of cameras, devices for data acquisition, devices for data analysis and specialized software. Vision systems work well as sensors that control the production process itself as well as the sensors that control the product quality level. The LabVIEW program as well as the LabVIEW Vision and LabVIEW Builder represent the application that enables program the informatics system intended to process and product quality control. The paper presents elaborated application for positioning elements in a robotized workcell. Basing on geometric parameters of manipulated object or on the basis of previously developed graphical pattern it is possible to determine the position of particular manipulated elements. This application could work in an automatic mode and in real time cooperating with the robot control system. It allows making the workcell functioning more autonomous.

Automating the Processing of Earth Observation Data

NASA Technical Reports Server (NTRS)

Golden, Keith; Pang, Wan-Lin; Nemani, Ramakrishna; Votava, Petr

2003-01-01

NASA s vision for Earth science is to build a "sensor web": an adaptive array of heterogeneous satellites and other sensors that will track important events, such as storms, and provide real-time information about the state of the Earth to a wide variety of customers. Achieving this vision will require automation not only in the scheduling of the observations but also in the processing of the resulting data. To address this need, we are developing a planner-based agent to automatically generate and execute data-flow programs to produce the requested data products.

Magnetostrictive patch sensor system for battery-less real-time measurement of torsional vibrations of rotating shafts

NASA Astrophysics Data System (ADS)

Lee, Jun Kyu; Seung, Hong Min; Park, Chung Il; Lee, Joo Kyung; Lim, Do Hyeong; Kim, Yoon Young

2018-02-01

Real-time uninterrupted measurement for torsional vibrations of rotating shafts is crucial for permanent health monitoring. So far, strain gauge systems with telemetry units have been used for real-time monitoring. However, they have a critical disadvantage in that shaft operations must be stopped intermittently to replace telemetry unit batteries. To find an alternative method to carry out battery-less real-time measurement for torsional vibrations of rotating shafts, a magnetostrictive patch sensor system was proposed in the present study. Since the proposed sensor does not use any powered telemetry system, no battery is needed and thus there is no need to stop rotating shafts for battery replacement. The proposed sensor consists of magnetostrictive patches and small magnets tightly bonded onto a shaft. A solenoid coil is placed around the shaft to convert magnetostrictive patch deformation by shaft torsional vibration into electric voltage output. For sensor design and characterization, investigations were performed in a laboratory on relatively small-sized stationary solid shaft. A magnetostrictive patch sensor system was then designed and installed on a large rotating propulsion shaft of an LPG carrier ship in operation. Vibration signals were measured using the proposed sensor system and compared to those measured with a telemetry unit-equipped strain gauge system.

Intensity Maps Production Using Real-Time Joint Streaming Data Processing From Social and Physical Sensors

NASA Astrophysics Data System (ADS)

Kropivnitskaya, Y. Y.; Tiampo, K. F.; Qin, J.; Bauer, M.

2015-12-01

Intensity is one of the most useful measures of earthquake hazard, as it quantifies the strength of shaking produced at a given distance from the epicenter. Today, there are several data sources that could be used to determine intensity level which can be divided into two main categories. The first category is represented by social data sources, in which the intensity values are collected by interviewing people who experienced the earthquake-induced shaking. In this case, specially developed questionnaires can be used in addition to personal observations published on social networks such as Twitter. These observations are assigned to the appropriate intensity level by correlating specific details and descriptions to the Modified Mercalli Scale. The second category of data sources is represented by observations from different physical sensors installed with the specific purpose of obtaining an instrumentally-derived intensity level. These are usually based on a regression of recorded peak acceleration and/or velocity amplitudes. This approach relates the recorded ground motions to the expected felt and damage distribution through empirical relationships. The goal of this work is to implement and evaluate streaming data processing separately and jointly from both social and physical sensors in order to produce near real-time intensity maps and compare and analyze their quality and evolution through 10-minute time intervals immediately following an earthquake. Results are shown for the case study of the M6.0 2014 South Napa, CA earthquake that occurred on August 24, 2014. The using of innovative streaming and pipelining computing paradigms through IBM InfoSphere Streams platform made it possible to read input data in real-time for low-latency computing of combined intensity level and production of combined intensity maps in near-real time. The results compare three types of intensity maps created based on physical, social and combined data sources. Here we correlate the count and density of Tweets with intensity level and show the importance of processing combined data sources at the earliest time stages after earthquake happens. This method can supplement existing approaches of intensity level detection, especially in the regions with high number of Twitter users and low density of seismic networks.

A Deep Learning Approach to on-Node Sensor Data Analytics for Mobile or Wearable Devices.

PubMed

Ravi, Daniele; Wong, Charence; Lo, Benny; Yang, Guang-Zhong

2017-01-01

The increasing popularity of wearable devices in recent years means that a diverse range of physiological and functional data can now be captured continuously for applications in sports, wellbeing, and healthcare. This wealth of information requires efficient methods of classification and analysis where deep learning is a promising technique for large-scale data analytics. While deep learning has been successful in implementations that utilize high-performance computing platforms, its use on low-power wearable devices is limited by resource constraints. In this paper, we propose a deep learning methodology, which combines features learned from inertial sensor data together with complementary information from a set of shallow features to enable accurate and real-time activity classification. The design of this combined method aims to overcome some of the limitations present in a typical deep learning framework where on-node computation is required. To optimize the proposed method for real-time on-node computation, spectral domain preprocessing is used before the data are passed onto the deep learning framework. The classification accuracy of our proposed deep learning approach is evaluated against state-of-the-art methods using both laboratory and real world activity datasets. Our results show the validity of the approach on different human activity datasets, outperforming other methods, including the two methods used within our combined pipeline. We also demonstrate that the computation times for the proposed method are consistent with the constraints of real-time on-node processing on smartphones and a wearable sensor platform.

Navigation Doppler lidar sensor for precision altitude and vector velocity measurements: flight test results

NASA Astrophysics Data System (ADS)

Pierrottet, Diego; Amzajerdian, Farzin; Petway, Larry; Barnes, Bruce; Lockard, George; Hines, Glenn

2011-06-01

An all fiber Navigation Doppler Lidar (NDL) system is under development at NASA Langley Research Center (LaRC) for precision descent and landing applications on planetary bodies. The sensor produces high-resolution line of sight range, altitude above ground, ground relative attitude, and high precision velocity vector measurements. Previous helicopter flight test results demonstrated the NDL measurement concepts, including measurement precision, accuracies, and operational range. This paper discusses the results obtained from a recent campaign to test the improved sensor hardware, and various signal processing algorithms applicable to real-time processing. The NDL was mounted in an instrumentation pod aboard an Erickson Air-Crane helicopter and flown over various terrains. The sensor was one of several sensors tested in this field test by NASA's Autonomous Landing and Hazard Avoidance Technology (ALHAT) project.

Navigation Doppler Lidar Sensor for Precision Altitude and Vector Velocity Measurements Flight Test Results

NASA Technical Reports Server (NTRS)

Pierrottet, Diego F.; Lockhard, George; Amzajerdian, Farzin; Petway, Larry B.; Barnes, Bruce; Hines, Glenn D.

2011-01-01

An all fiber Navigation Doppler Lidar (NDL) system is under development at NASA Langley Research Center (LaRC) for precision descent and landing applications on planetary bodies. The sensor produces high resolution line of sight range, altitude above ground, ground relative attitude, and high precision velocity vector measurements. Previous helicopter flight test results demonstrated the NDL measurement concepts, including measurement precision, accuracies, and operational range. This paper discusses the results obtained from a recent campaign to test the improved sensor hardware, and various signal processing algorithms applicable to real-time processing. The NDL was mounted in an instrumentation pod aboard an Erickson Air-Crane helicopter and flown over vegetation free terrain. The sensor was one of several sensors tested in this field test by NASA?s Autonomous Landing and Hazard Avoidance Technology (ALHAT) project.

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

Analysis of simulated image sequences from sensors for restricted-visibility operations

NASA Technical Reports Server (NTRS)

Kasturi, Rangachar

1991-01-01

A real time model of the visible output from a 94 GHz sensor, based on a radiometric simulation of the sensor, was developed. A sequence of images as seen from an aircraft as it approaches for landing was simulated using this model. Thirty frames from this sequence of 200 x 200 pixel images were analyzed to identify and track objects in the image using the Cantata image processing package within the visual programming environment provided by the Khoros software system. The image analysis operations are described.

Digital phase demodulation for low-coherence interferometry-based fiber-optic sensors

NASA Astrophysics Data System (ADS)

Liu, Y.; Strum, R.; Stiles, D.; Long, C.; Rakhman, A.; Blokland, W.; Winder, D.; Riemer, B.; Wendel, M.

2018-03-01

We describe a digital phase demodulation scheme for low-coherence interferometry-based fiber-optic sensors by employing a simple generation of phase-shifted signals at the interrogation interferometer. The scheme allows a real-time calibration process and offers capability of measuring large variations (up to the coherence of the light source) at the bandwidth that is only limited by the data acquisition system. The proposed phase demodulation method is analytically derived and its validity and performance are experimentally verified using fiber-optic Fabry-Perot sensors for measurement of strains and vibrations.

Transient plasma estimation: a noise cancelling/identification approach

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

Candy, J.V.; Casper, T.; Kane, R.

1985-03-01

The application of a noise cancelling technique to extract energy storage information from sensors occurring during fusion reactor experiments on the Tandem Mirror Experiment-Upgrade (TMX-U) at the Lawrence Livermore National Laboratory (LLNL) is examined. We show how this technique can be used to decrease the uncertainty in the corresponding sensor measurements used for diagnostics in both real-time and post-experimental environments. We analyze the performance of algorithm on the sensor data and discuss the various tradeoffs. The algorithm suggested is designed using SIG, an interactive signal processing package developed at LLNL.

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.

Kinota: An Open-Source NoSQL implementation of OGC SensorThings for large-scale high-resolution real-time environmental monitoring

NASA Astrophysics Data System (ADS)

Miles, B.; Chepudira, K.; LaBar, W.

2017-12-01

The Open Geospatial Consortium (OGC) SensorThings API (STA) specification, ratified in 2016, is a next-generation open standard for enabling real-time communication of sensor data. Building on over a decade of OGC Sensor Web Enablement (SWE) Standards, STA offers a rich data model that can represent a range of sensor and phenomena types (e.g. fixed sensors sensing fixed phenomena, fixed sensors sensing moving phenomena, mobile sensors sensing fixed phenomena, and mobile sensors sensing moving phenomena) and is data agnostic. Additionally, and in contrast to previous SWE standards, STA is developer-friendly, as is evident from its convenient JSON serialization, and expressive OData-based query language (with support for geospatial queries); with its Message Queue Telemetry Transport (MQTT), STA is also well-suited to efficient real-time data publishing and discovery. All these attributes make STA potentially useful for use in environmental monitoring sensor networks. Here we present Kinota(TM), an Open-Source NoSQL implementation of OGC SensorThings for large-scale high-resolution real-time environmental monitoring. Kinota, which roughly stands for Knowledge from Internet of Things Analyses, relies on Cassandra its underlying data store, which is a horizontally scalable, fault-tolerant open-source database that is often used to store time-series data for Big Data applications (though integration with other NoSQL or rational databases is possible). With this foundation, Kinota can scale to store data from an arbitrary number of sensors collecting data every 500 milliseconds. Additionally, Kinota architecture is very modular allowing for customization by adopters who can choose to replace parts of the existing implementation when desirable. The architecture is also highly portable providing the flexibility to choose between cloud providers like azure, amazon, google etc. The scalable, flexible and cloud friendly architecture of Kinota makes it ideal for use in next-generation large-scale and high-resolution real-time environmental monitoring networks used in domains such as hydrology, geomorphology, and geophysics, as well as management applications such as flood early warning, and regulatory enforcement.

An integrative solution for managing, tracing and citing sensor-related information

NASA Astrophysics Data System (ADS)

Koppe, Roland; Gerchow, Peter; Macario, Ana; Schewe, Ingo; Rehmcke, Steven; Düde, Tobias

2017-04-01

In a data-driven scientific world, the need to capture information on sensors used in the data acquisition process has become increasingly important. Following the recommendations of the Open Geospatial Consortium (OGC), we started by adopting the SensorML standard for describing platforms, devices and sensors. However, it soon became obvious to us that understanding, implementing and filling such standards costs significant effort and cannot be expected from every scientist individually. So we developed a web-based sensor management solution (https://sensor.awi.de) for describing platforms, devices and sensors as hierarchy of systems which supports tracing changes to a system whereas hiding complexity. Each platform contains devices where each device can have sensors associated with specific identifiers, contacts, events, related online resources (e.g. manufacturer factsheets, calibration documentation, data processing documentation), sensor output parameters and geo-location. In order to better understand and address real world requirements, we have closely interacted with field-going scientists in the context of the key national infrastructure project "FRontiers in Arctic marine Monitoring ocean observatory" (FRAM) during the software development. We learned that not only the lineage of observations is crucial for scientists but also alert services using value ranges, flexible output formats and information on data providers (e.g. FTP sources) for example. Mostly important, persistent and citable versions of sensor descriptions are required for traceability and reproducibility allowing seamless integration with existing information systems, e.g. PANGAEA. Within the context of the EU-funded Ocean Data Interoperability Platform project (ODIP II) and in cooperation with 52north we are proving near real-time data via Sensor Observation Services (SOS) along with sensor descriptions based on our sensor management solution. ODIP II also aims to develop a harmonized SensorML profile for the marine community which we will be adopting in our solution as soon as available. In this presentation we will show our sensor management solution which is embedded in our data flow framework to offer out-of-the-box interoperability with existing information systems and standards. In addition, we will present real world examples and challenges related to the description and traceability of sensor metadata.

Low-cost, efficient wireless intelligent sensors (LEWIS) measuring real-time reference-free dynamic displacements

NASA Astrophysics Data System (ADS)

Ozdagli, A. I.; Liu, B.; Moreu, F.

2018-07-01

According to railroad managers, displacement of railroad bridges under service loads is an important parameter in the condition assessment and performance evaluation. However, measuring bridge responses in the field is often costly and labor-intensive. This paper proposes a low-cost, efficient wireless intelligent sensor (LEWIS) platform that can compute in real-time the dynamic transverse displacements of railroad bridges under service loads. This sensing platform drives on an open-source Arduino ecosystem and combines low-cost microcontrollers with affordable accelerometers and wireless transmission modules. The proposed LEWIS system is designed to reconstruct dynamic displacements from acceleration measurements onboard, eliminating the need for offline post-processing, and to transmit the data in real-time to a base station where the inspector at the bridge can see the displacements while the train is crossing, or to a remote office if so desired by internet. Researchers validated the effectiveness of the new LEWIS by conducting a series of laboratory experiments. A shake table setup simulated transverse bridge displacements measured on the field and excited the proposed platform, a commercially available wired expensive accelerometer, and reference LVDT displacement sensor. The responses obtained from the wireless system were compared to the displacements reconstructed from commercial accelerometer readings and the reference LVDT. The results of the laboratory experiments demonstrate that the proposed system is capable of reconstructing transverse displacements of railroad bridges under revenue service traffic accurately and transmitting the data in real-time wirelessly. In conclusion, the platform presented in this paper can be used in the performance assessment of railroad bridge network cost-effectively and accurately. Future work includes collecting real-time reference-free displacements of one railroad bridge in Colorado under train crossings to further prove LEWIS' suitability for engineering applications.

Real-time diagnostics for a reusable rocket engine

NASA Technical Reports Server (NTRS)

Guo, T. H.; Merrill, W.; Duyar, A.

1992-01-01

A hierarchical, decentralized diagnostic system is proposed for the Real-Time Diagnostic System component of the Intelligent Control System (ICS) for reusable rocket engines. The proposed diagnostic system has three layers of information processing: condition monitoring, fault mode detection, and expert system diagnostics. The condition monitoring layer is the first level of signal processing. Here, important features of the sensor data are extracted. These processed data are then used by the higher level fault mode detection layer to do preliminary diagnosis on potential faults at the component level. Because of the closely coupled nature of the rocket engine propulsion system components, it is expected that a given engine condition may trigger more than one fault mode detector. Expert knowledge is needed to resolve the conflicting reports from the various failure mode detectors. This is the function of the diagnostic expert layer. Here, the heuristic nature of this decision process makes it desirable to use an expert system approach. Implementation of the real-time diagnostic system described above requires a wide spectrum of information processing capability. Generally, in the condition monitoring layer, fast data processing is often needed for feature extraction and signal conditioning. This is usually followed by some detection logic to determine the selected faults on the component level. Three different techniques are used to attack different fault detection problems in the NASA LeRC ICS testbed simulation. The first technique employed is the neural network application for real-time sensor validation which includes failure detection, isolation, and accommodation. The second approach demonstrated is the model-based fault diagnosis system using on-line parameter identification. Besides these model based diagnostic schemes, there are still many failure modes which need to be diagnosed by the heuristic expert knowledge. The heuristic expert knowledge is implemented using a real-time expert system tool called G2 by Gensym Corp. Finally, the distributed diagnostic system requires another level of intelligence to oversee the fault mode reports generated by component fault detectors. The decision making at this level can best be done using a rule-based expert system. This level of expert knowledge is also implemented using G2.

A CMOS high speed imaging system design based on FPGA

NASA Astrophysics Data System (ADS)

Tang, Hong; Wang, Huawei; Cao, Jianzhong; Qiao, Mingrui

2015-10-01

CMOS sensors have more advantages than traditional CCD sensors. The imaging system based on CMOS has become a hot spot in research and development. In order to achieve the real-time data acquisition and high-speed transmission, we design a high-speed CMOS imaging system on account of FPGA. The core control chip of this system is XC6SL75T and we take advantages of CameraLink interface and AM41V4 CMOS image sensors to transmit and acquire image data. AM41V4 is a 4 Megapixel High speed 500 frames per second CMOS image sensor with global shutter and 4/3" optical format. The sensor uses column parallel A/D converters to digitize the images. The CameraLink interface adopts DS90CR287 and it can convert 28 bits of LVCMOS/LVTTL data into four LVDS data stream. The reflected light of objects is photographed by the CMOS detectors. CMOS sensors convert the light to electronic signals and then send them to FPGA. FPGA processes data it received and transmits them to upper computer which has acquisition cards through CameraLink interface configured as full models. Then PC will store, visualize and process images later. The structure and principle of the system are both explained in this paper and this paper introduces the hardware and software design of the system. FPGA introduces the driven clock of CMOS. The data in CMOS is converted to LVDS signals and then transmitted to the data acquisition cards. After simulation, the paper presents a row transfer timing sequence of CMOS. The system realized real-time image acquisition and external controls.

Improving Air Force Imagery Reconnaissance Support to Ground Commanders.

DTIC Science & Technology

1983-06-03

reconnaissance support in Southeast Asia due to the long response times of film recovery and 26 processing capabilities and inadequate command and control...reconnaissance is an integral part of the C31 information explosion. Traditional silver halide film products, chemically processed and manually distributed are...being replaced with electronic near-real-time (NRT) imaging sensors. The term "imagery" now includes not only conventional film based products (black

A biomedical sensor system for real-time monitoring of astronauts' physiological parameters during extra-vehicular activities.

PubMed

Fei, Ding-Yu; Zhao, Xiaoming; Boanca, Cosmin; Hughes, Esther; Bai, Ou; Merrell, Ronald; Rafiq, Azhar

2010-07-01

To design and test an embedded biomedical sensor system that can monitor astronauts' comprehensive physiological parameters, and provide real-time data display during extra-vehicle activities (EVA) in the space exploration. An embedded system was developed with an array of biomedical sensors that can be integrated into the spacesuit. Wired communications were tested for physiological data acquisition and data transmission to a computer mounted on the spacesuit during task performances simulating EVA sessions. The sensor integration, data collection and communication, and the real-time data monitoring were successfully validated in the NASA field tests. The developed system may work as an embedded system for monitoring health status during long-term space mission. Copyright 2010 Elsevier Ltd. All rights reserved.

Use of Pattern Classification Algorithms to Interpret Passive and Active Data Streams from a Walking-Speed Robotic Sensor Platform

NASA Astrophysics Data System (ADS)

Dieckman, Eric Allen

In order to perform useful tasks for us, robots must have the ability to notice, recognize, and respond to objects and events in their environment. This requires the acquisition and synthesis of information from a variety of sensors. Here we investigate the performance of a number of sensor modalities in an unstructured outdoor environment, including the Microsoft Kinect, thermal infrared camera, and coffee can radar. Special attention is given to acoustic echolocation measurements of approaching vehicles, where an acoustic parametric array propagates an audible signal to the oncoming target and the Kinect microphone array records the reflected backscattered signal. Although useful information about the target is hidden inside the noisy time domain measurements, the Dynamic Wavelet Fingerprint process (DWFP) is used to create a time-frequency representation of the data. A small-dimensional feature vector is created for each measurement using an intelligent feature selection process for use in statistical pattern classification routines. Using our experimentally measured data from real vehicles at 50 m, this process is able to correctly classify vehicles into one of five classes with 94% accuracy. Fully three-dimensional simulations allow us to study the nonlinear beam propagation and interaction with real-world targets to improve classification results.

Photoacoustic CO2 sensor system: design and potential for miniaturization and integration in silicon

NASA Astrophysics Data System (ADS)

Huber, J.; Wöllenstein, J.

2015-05-01

The detection of CO2 indoors has a large impact on today's sensor market. The ambient room climate is important for human health and wellbeing. The CO2 concentration is a main indicator for indoor climate and correlates with the number of persons inside a room. People in Europe spend more than 90% of their time indoors. This leads to a high demand for miniaturized and energy efficient CO2 sensors. To realize small and energy-efficient mass-market sensors, we develop novel miniaturized photoacoustic sensor systems with optimized design for real-time and selective CO2 detection. The sensor system consists of two chambers, a measurement and a detection chamber. The detection chamber consists of an integrated pressure sensor under special gas atmosphere. As pressure sensor we use a commercially available cell phone microphone. We describe a possible miniaturization process of the developed system by regarding the possibility of integration of all sensor parts. The system is manufactured in precision mechanics with IR-optical sapphire windows as optical connections. During the miniaturization process the sapphire windows are replaced by Si chips with a special IR anti-reflection coating. The developed system is characterized in detail with gas measurements and optical transmission investigations. The results of the characterization process offer a high potential for further miniaturization with high capability for mass market applications.

Cloud-based Web Services for Near-Real-Time Web access to NPP Satellite Imagery and other Data

NASA Astrophysics Data System (ADS)

Evans, J. D.; Valente, E. G.

2010-12-01

We are building a scalable, cloud computing-based infrastructure for Web access to near-real-time data products synthesized from the U.S. National Polar-Orbiting Environmental Satellite System (NPOESS) Preparatory Project (NPP) and other geospatial and meteorological data. Given recent and ongoing changes in the the NPP and NPOESS programs (now Joint Polar Satellite System), the need for timely delivery of NPP data is urgent. We propose an alternative to a traditional, centralized ground segment, using distributed Direct Broadcast facilities linked to industry-standard Web services by a streamlined processing chain running in a scalable cloud computing environment. Our processing chain, currently implemented on Amazon.com's Elastic Compute Cloud (EC2), retrieves raw data from NASA's Moderate Resolution Imaging Spectroradiometer (MODIS) and synthesizes data products such as Sea-Surface Temperature, Vegetation Indices, etc. The cloud computing approach lets us grow and shrink computing resources to meet large and rapid fluctuations (twice daily) in both end-user demand and data availability from polar-orbiting sensors. Early prototypes have delivered various data products to end-users with latencies between 6 and 32 minutes. We have begun to replicate machine instances in the cloud, so as to reduce latency and maintain near-real time data access regardless of increased data input rates or user demand -- all at quite moderate monthly costs. Our service-based approach (in which users invoke software processes on a Web-accessible server) facilitates access into datasets of arbitrary size and resolution, and allows users to request and receive tailored and composite (e.g., false-color multiband) products on demand. To facilitate broad impact and adoption of our technology, we have emphasized open, industry-standard software interfaces and open source software. Through our work, we envision the widespread establishment of similar, derived, or interoperable systems for processing and serving near-real-time data from NPP and other sensors. A scalable architecture based on cloud computing ensures cost-effective, real-time processing and delivery of NPP and other data. Access via standard Web services maximizes its interoperability and usefulness.

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

Continuous, real time microwave plasma element sensor

DOEpatents

Woskov, P.P.; Smatlak, D.L.; Cohn, D.R.; Wittle, J.K.; Titus, C.H.; Surma, J.E.

1995-12-26

Microwave-induced plasma is described for continuous, real time trace element monitoring under harsh and variable conditions. The sensor includes a source of high power microwave energy and a shorted waveguide made of a microwave conductive, refractory material communicating with the source of the microwave energy to generate a plasma. The high power waveguide is constructed to be robust in a hot, hostile environment. It includes an aperture for the passage of gases to be analyzed and a spectrometer is connected to receive light from the plasma. Provision is made for real time in situ calibration. The spectrometer disperses the light, which is then analyzed by a computer. The sensor is capable of making continuous, real time quantitative measurements of desired elements, such as the heavy metals lead and mercury. 3 figs.

Real-time, wide-area hyperspectral imaging sensors for standoff detection of explosives and chemical warfare agents

NASA Astrophysics Data System (ADS)

Gomer, Nathaniel R.; Tazik, Shawna; Gardner, Charles W.; Nelson, Matthew P.

2017-05-01

Hyperspectral imaging (HSI) is a valuable tool for the detection and analysis of targets located within complex backgrounds. HSI can detect threat materials on environmental surfaces, where the concentration of the target of interest is often very low and is typically found within complex scenery. Unfortunately, current generation HSI systems have size, weight, and power limitations that prohibit their use for field-portable and/or real-time applications. Current generation systems commonly provide an inefficient area search rate, require close proximity to the target for screening, and/or are not capable of making real-time measurements. ChemImage Sensor Systems (CISS) is developing a variety of real-time, wide-field hyperspectral imaging systems that utilize shortwave infrared (SWIR) absorption and Raman spectroscopy. SWIR HSI sensors provide wide-area imagery with at or near real time detection speeds. Raman HSI sensors are being developed to overcome two obstacles present in standard Raman detection systems: slow area search rate (due to small laser spot sizes) and lack of eye-safety. SWIR HSI sensors have been integrated into mobile, robot based platforms and handheld variants for the detection of explosives and chemical warfare agents (CWAs). In addition, the fusion of these two technologies into a single system has shown the feasibility of using both techniques concurrently to provide higher probability of detection and lower false alarm rates. This paper will provide background on Raman and SWIR HSI, discuss the applications for these techniques, and provide an overview of novel CISS HSI sensors focusing on sensor design and detection results.

Joint parameter and state estimation algorithms for real-time traffic monitoring.

DOT National Transportation Integrated Search

2013-12-01

A common approach to traffic monitoring is to combine a macroscopic traffic flow model with traffic sensor data in a process called state estimation, data fusion, or data assimilation. The main challenge of traffic state estimation is the integration...

Data processing for water monitoring system

NASA Technical Reports Server (NTRS)

Monford, L.; Linton, A. T.

1978-01-01

Water monitoring data acquisition system is structured about central computer that controls sampling and sensor operation, and analyzes and displays data in real time. Unit is essentially separated into two systems: computer system, and hard wire backup system which may function separately or with computer.

Fuzzy Logic-Based Guaranteed Lifetime Protocol for Real-Time Wireless Sensor Networks.

PubMed

Shah, Babar; Iqbal, Farkhund; Abbas, Ali; Kim, Ki-Il

2015-08-18

Few techniques for guaranteeing a network lifetime have been proposed despite its great impact on network management. Moreover, since the existing schemes are mostly dependent on the combination of disparate parameters, they do not provide additional services, such as real-time communications and balanced energy consumption among sensor nodes; thus, the adaptability problems remain unresolved among nodes in wireless sensor networks (WSNs). To solve these problems, we propose a novel fuzzy logic model to provide real-time communication in a guaranteed WSN lifetime. The proposed fuzzy logic controller accepts the input descriptors energy, time and velocity to determine each node's role for the next duration and the next hop relay node for real-time packets. Through the simulation results, we verified that both the guaranteed network's lifetime and real-time delivery are efficiently ensured by the new fuzzy logic model. In more detail, the above-mentioned two performance metrics are improved up to 8%, as compared to our previous work, and 14% compared to existing schemes, respectively.

Fuzzy Logic-Based Guaranteed Lifetime Protocol for Real-Time Wireless Sensor Networks

PubMed Central

Shah, Babar; Iqbal, Farkhund; Abbas, Ali; Kim, Ki-Il

2015-01-01

Few techniques for guaranteeing a network lifetime have been proposed despite its great impact on network management. Moreover, since the existing schemes are mostly dependent on the combination of disparate parameters, they do not provide additional services, such as real-time communications and balanced energy consumption among sensor nodes; thus, the adaptability problems remain unresolved among nodes in wireless sensor networks (WSNs). To solve these problems, we propose a novel fuzzy logic model to provide real-time communication in a guaranteed WSN lifetime. The proposed fuzzy logic controller accepts the input descriptors energy, time and velocity to determine each node’s role for the next duration and the next hop relay node for real-time packets. Through the simulation results, we verified that both the guaranteed network’s lifetime and real-time delivery are efficiently ensured by the new fuzzy logic model. In more detail, the above-mentioned two performance metrics are improved up to 8%, as compared to our previous work, and 14% compared to existing schemes, respectively. PMID:26295238

The implementation of CMOS sensors within a real time digital mammography intelligent imaging system: The I-ImaS System

NASA Astrophysics Data System (ADS)

Esbrand, C.; Royle, G.; Griffiths, J.; Speller, R.

2009-07-01

The integration of technology with healthcare has undoubtedly propelled the medical imaging sector well into the twenty first century. The concept of digital imaging introduced during the 1970s has since paved the way for established imaging techniques where digital mammography, phase contrast imaging and CT imaging are just a few examples. This paper presents a prototype intelligent digital mammography system designed and developed by a European consortium. The final system, the I-ImaS system, utilises CMOS monolithic active pixel sensor (MAPS) technology promoting on-chip data processing, enabling the acts of data processing and image acquisition to be achieved simultaneously; consequently, statistical analysis of tissue is achievable in real-time for the purpose of x-ray beam modulation via a feedback mechanism during the image acquisition procedure. The imager implements a dual array of twenty 520 pixel × 40 pixel CMOS MAPS sensing devices with a 32μm pixel size, each individually coupled to a 100μm thick thallium doped structured CsI scintillator. This paper presents the first intelligent images of real breast tissue obtained from the prototype system of real excised breast tissue where the x-ray exposure was modulated via the statistical information extracted from the breast tissue itself. Conventional images were experimentally acquired where the statistical analysis of the data was done off-line, resulting in the production of simulated real-time intelligently optimised images. The results obtained indicate real-time image optimisation using the statistical information extracted from the breast as a means of a feedback mechanisms is beneficial and foreseeable in the near future.

Final Technical Report - Advanced Optical Sensors to Minimize Energy Consumption in Polymer Extrusion Processes

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

Susan J. Foulk

Project Objective: The objectives of this study are to develop an accurate and stable on-line sensor system to monitor color and composition on-line in polymer melts, to develop a scheme for using the output to control extruders to eliminate the energy, material and operational costs of off-specification product, and to combine or eliminate some extrusion processes. Background: Polymer extrusion processes are difficult to control because the quality achieved in the final product is complexly affected by the properties of the extruder screw, speed of extrusion, temperature, polymer composition, strength and dispersion properties of additives, and feeder system properties. Extruder systemsmore » are engineered to be highly reproducible so that when the correct settings to produce a particular product are found, that product can be reliably produced time after time. However market conditions often require changes in the final product, different products or grades may be processed in the same equipment, and feed materials vary from lot to lot. All of these changes require empirical adjustment of extruder settings to produce a product meeting specifications. Optical sensor systems that can continuously monitor the composition and color of the extruded polymer could detect process upsets, drift, blending oscillations, and changes in dispersion of additives. Development of an effective control algorithm using the output of the monitor would enable rapid corrections for changes in materials and operating conditions, thereby eliminating most of the scrap and recycle of current processing. This information could be used to identify extruder systems issues, diagnose problem sources, and suggest corrective actions in real-time to help keep extruder system settings within the optimum control region. Using these advanced optical sensor systems would give extruder operators real-time feedback from their process. They could reduce the amount of off-spec product produced and significantly reduce energy consumption. Also, because blending and dispersion of additives and components in the final product could be continuously verified, we believe that, in many cases, intermediate compounding steps could be eliminated (saving even more time and energy).« less

Research on parallel load sharing principle of piezoelectric six-dimensional heavy force/torque sensor

NASA Astrophysics Data System (ADS)

Liu, Wei; Li, Ying-jun; Jia, Zhen-yuan; Zhang, Jun; Qian, Min

2011-01-01

In working process of huge heavy-load manipulators, such as the free forging machine, hydraulic die-forging press, forging manipulator, heavy grasping manipulator, large displacement manipulator, measurement of six-dimensional heavy force/torque and real-time force feedback of the operation interface are basis to realize coordinate operation control and force compliance control. It is also an effective way to raise the control accuracy and achieve highly efficient manufacturing. Facing to solve dynamic measurement problem on six-dimensional time-varying heavy load in extremely manufacturing process, the novel principle of parallel load sharing on six-dimensional heavy force/torque is put forward. The measuring principle of six-dimensional force sensor is analyzed, and the spatial model is built and decoupled. The load sharing ratios are analyzed and calculated in vertical and horizontal directions. The mapping relationship between six-dimensional heavy force/torque value to be measured and output force value is built. The finite element model of parallel piezoelectric six-dimensional heavy force/torque sensor is set up, and its static characteristics are analyzed by ANSYS software. The main parameters, which affect load sharing ratio, are analyzed. The experiments for load sharing with different diameters of parallel axis are designed. The results show that the six-dimensional heavy force/torque sensor has good linearity. Non-linearity errors are less than 1%. The parallel axis makes good effect of load sharing. The larger the diameter is, the better the load sharing effect is. The results of experiments are in accordance with the FEM analysis. The sensor has advantages of large measuring range, good linearity, high inherent frequency, and high rigidity. It can be widely used in extreme environments for real-time accurate measurement of six-dimensional time-varying huge loads on manipulators.

Landslide and Flood Warning System Prototypes based on Wireless Sensor Networks

NASA Astrophysics Data System (ADS)

Hloupis, George; Stavrakas, Ilias; Triantis, Dimos

2010-05-01

Wireless sensor networks (WSNs) are one of the emerging areas that received great attention during the last few years. This is mainly due to the fact that WSNs have provided scientists with the capability of developing real-time monitoring systems equipped with sensors based on Micro-Electro-Mechanical Systems (MEMS). WSNs have great potential for many applications in environmental monitoring since the sensor nodes that comprised from can host several MEMS sensors (such as temperature, humidity, inertial, pressure, strain-gauge) and transducers (such as position, velocity, acceleration, vibration). The resulting devices are small and inexpensive but with limited memory and computing resources. Each sensor node contains a sensing module which along with an RF transceiver. The communication is broadcast-based since the network topology can change rapidly due to node failures [1]. Sensor nodes can transmit their measurements to central servers through gateway nodes without any processing or they make preliminary calculations locally in order to produce results that will be sent to central servers [2]. Based on the above characteristics, two prototypes using WSNs are presented in this paper: A Landslide detection system and a Flood warning system. Both systems sent their data to central processing server where the core of processing routines exists. Transmission is made using Zigbee and IEEE 802.11b protocol but is capable to use VSAT communication also. Landslide detection system uses structured network topology. Each measuring node comprises of a columnar module that is half buried to the area under investigation. Each sensing module contains a geophone, an inclinometer and a set of strain gauges. Data transmitted to central processing server where possible landslide evolution is monitored. Flood detection system uses unstructured network topology since the failure rate of sensor nodes is expected higher. Each sensing module contains a custom water level sensor (based on plastic optical fiber). Data transmitted directly to server where the early warning algorithms monitor the water level variations in real time. Both sensor nodes use power harvesting techniques in order to extend their battery life as much as possible. [1] Yick J.; Mukherjee, B.; Ghosal, D. Wireless sensor network survey. Comput. Netw. 2008, 52, 2292-2330. [2] Garcia, M.; Bri, D.; Boronat, F.; Lloret, J. A new neighbor selection strategy for group-based wireless sensor networks, In The Fourth International Conference on Networking and Services (ICNS 2008), Gosier, Guadalupe, March 16-21, 2008.

Integration of Geo-Sensor Feeds and Event Consumer Services for Real-Time Representation of Iot Nodes

NASA Astrophysics Data System (ADS)

Isikdag, U.; Pilouk, M.

2016-06-01

More and more devices are starting to be connected to the Internet every day. Internet-of-Things (IoT) is known as an architecture where online devices have the ability to communicate and interact with each other in real-time. On the other hand, with the development of IoT related technologies information about devices (i.e. Things) can be acquired in real-time by the humans. The implementation of IoT related technologies requires new approaches to be investigated for novel system architectures. These architectures need to have 3 main abilities. The first one is the ability is to store and query information coming from millions of devices in real-time. The second one is the ability to interact with large number of devices seamlessly regardless of their hardware and their software platforms. The final one is the ability to visualise and present information coming from millions of sensors in real time. The paper provides an architectural approach and implementation tests for storage, exposition and presentation of large amounts of real-time geo-information coming from multiple IoT nodes (and sensors).

An FPGA-based High Speed Parallel Signal Processing System for Adaptive Optics Testbed

NASA Astrophysics Data System (ADS)

Kim, H.; Choi, Y.; Yang, Y.

In this paper a state-of-the-art FPGA (Field Programmable Gate Array) based high speed parallel signal processing system (SPS) for adaptive optics (AO) testbed with 1 kHz wavefront error (WFE) correction frequency is reported. The AO system consists of Shack-Hartmann sensor (SHS) and deformable mirror (DM), tip-tilt sensor (TTS), tip-tilt mirror (TTM) and an FPGA-based high performance SPS to correct wavefront aberrations. The SHS is composed of 400 subapertures and the DM 277 actuators with Fried geometry, requiring high speed parallel computing capability SPS. In this study, the target WFE correction speed is 1 kHz; therefore, it requires massive parallel computing capabilities as well as strict hard real time constraints on measurements from sensors, matrix computation latency for correction algorithms, and output of control signals for actuators. In order to meet them, an FPGA based real-time SPS with parallel computing capabilities is proposed. In particular, the SPS is made up of a National Instrument's (NI's) real time computer and five FPGA boards based on state-of-the-art Xilinx Kintex 7 FPGA. Programming is done with NI's LabView environment, providing flexibility when applying different algorithms for WFE correction. It also facilitates faster programming and debugging environment as compared to conventional ones. One of the five FPGA's is assigned to measure TTS and calculate control signals for TTM, while the rest four are used to receive SHS signal, calculate slops for each subaperture and correction signal for DM. With this parallel processing capabilities of the SPS the overall closed-loop WFE correction speed of 1 kHz has been achieved. System requirements, architecture and implementation issues are described; furthermore, experimental results are also given.

Real-Time Deflection Monitoring for Milling of a Thin-Walled Workpiece by Using PVDF Thin-Film Sensors with a Cantilevered Beam as a Case Study

PubMed Central

Luo, Ming; Liu, Dongsheng; Luo, Huan

2016-01-01

Thin-walled workpieces, such as aero-engine blisks and casings, are usually made of hard-to-cut materials. The wall thickness is very small and it is easy to deflect during milling process under dynamic cutting forces, leading to inaccurate workpiece dimensions and poor surface integrity. To understand the workpiece deflection behavior in a machining process, a new real-time nonintrusive method for deflection monitoring is presented, and a detailed analysis of workpiece deflection for different machining stages of the whole machining process is discussed. The thin-film polyvinylidene fluoride (PVDF) sensor is attached to the non-machining surface of the workpiece to copy the deflection excited by the dynamic cutting force. The relationship between the input deflection and the output voltage of the monitoring system is calibrated by testing. Monitored workpiece deflection results show that the workpiece experiences obvious vibration during the cutter entering the workpiece stage, and vibration during the machining process can be easily tracked by monitoring the deflection of the workpiece. During the cutter exiting the workpiece stage, the workpiece experiences forced vibration firstly, and free vibration exists until the amplitude reduces to zero after the cutter exits the workpiece. Machining results confirmed the suitability of the deflection monitoring system for machining thin-walled workpieces with the application of PVDF sensors. PMID:27626424

Resolving molecule-specific information in dynamic lipid membrane processes with multi-resonant infrared metasurfaces.

PubMed

Rodrigo, Daniel; Tittl, Andreas; Ait-Bouziad, Nadine; John-Herpin, Aurelian; Limaj, Odeta; Kelly, Christopher; Yoo, Daehan; Wittenberg, Nathan J; Oh, Sang-Hyun; Lashuel, Hilal A; Altug, Hatice

2018-06-04

A multitude of biological processes are enabled by complex interactions between lipid membranes and proteins. To understand such dynamic processes, it is crucial to differentiate the constituent biomolecular species and track their individual time evolution without invasive labels. Here, we present a label-free mid-infrared biosensor capable of distinguishing multiple analytes in heterogeneous biological samples with high sensitivity. Our technology leverages a multi-resonant metasurface to simultaneously enhance the different vibrational fingerprints of multiple biomolecules. By providing up to 1000-fold near-field intensity enhancement over both amide and methylene bands, our sensor resolves the interactions of lipid membranes with different polypeptides in real time. Significantly, we demonstrate that our label-free chemically specific sensor can analyze peptide-induced neurotransmitter cargo release from synaptic vesicle mimics. Our sensor opens up exciting possibilities for gaining new insights into biological processes such as signaling or transport in basic research as well as provides a valuable toolkit for bioanalytical and pharmaceutical applications.

Sampling optimization for high-speed weigh-in-motion measurements using in-pavement strain-based sensors

NASA Astrophysics Data System (ADS)

Zhang, Zhiming; Huang, Ying; Bridgelall, Raj; Palek, Leonard; Strommen, Robert

2015-06-01

Weigh-in-motion (WIM) measurement has been widely used for weight enforcement, pavement design, freight management, and intelligent transportation systems to monitor traffic in real-time. However, to use such sensors effectively, vehicles must exit the traffic stream and slow down to match their current capabilities. Hence, agencies need devices with higher vehicle passing speed capabilities to enable continuous weight measurements at mainline speeds. The current practices for data acquisition at such high speeds are fragmented. Deployment configurations and settings depend mainly on the experiences of operation engineers. To assure adequate data, most practitioners use very high frequency measurements that result in redundant samples, thereby diminishing the potential for real-time processing. The larger data memory requirements from higher sample rates also increase storage and processing costs. The field lacks a sampling design or standard to guide appropriate data acquisition of high-speed WIM measurements. This study develops the appropriate sample rate requirements as a function of the vehicle speed. Simulations and field experiments validate the methods developed. The results will serve as guidelines for future high-speed WIM measurements using in-pavement strain-based sensors.

A New Model Based on Adaptation of the External Loop to Compensate the Hysteresis of Tactile Sensors

PubMed Central

Sánchez-Durán, José A.; Vidal-Verdú, Fernando; Oballe-Peinado, Óscar; Castellanos-Ramos, Julián; Hidalgo-López, José A.

2015-01-01

This paper presents a novel method to compensate for hysteresis nonlinearities observed in the response of a tactile sensor. The External Loop Adaptation Method (ELAM) performs a piecewise linear mapping of the experimentally measured external curves of the hysteresis loop to obtain all possible internal cycles. The optimal division of the input interval where the curve is approximated is provided by the error minimization algorithm. This process is carried out off line and provides parameters to compute the split point in real time. A different linear transformation is then performed at the left and right of this point and a more precise fitting is achieved. The models obtained with the ELAM method are compared with those obtained from three other approaches. The results show that the ELAM method achieves a more accurate fitting. Moreover, the involved mathematical operations are simpler and therefore easier to implement in devices such as Field Programmable Gate Array (FPGAs) for real time applications. Furthermore, the method needs to identify fewer parameters and requires no previous selection process of operators or functions. Finally, the method can be applied to other sensors or actuators with complex hysteresis loop shapes. PMID:26501279

A Wireless Electronic Nose System Using a Fe2O3 Gas Sensing Array and Least Squares Support Vector Regression

PubMed Central

Song, Kai; Wang, Qi; Liu, Qi; Zhang, Hongquan; Cheng, Yingguo

2011-01-01

This paper describes the design and implementation of a wireless electronic nose (WEN) system which can online detect the combustible gases methane and hydrogen (CH4/H2) and estimate their concentrations, either singly or in mixtures. The system is composed of two wireless sensor nodes—a slave node and a master node. The former comprises a Fe2O3 gas sensing array for the combustible gas detection, a digital signal processor (DSP) system for real-time sampling and processing the sensor array data and a wireless transceiver unit (WTU) by which the detection results can be transmitted to the master node connected with a computer. A type of Fe2O3 gas sensor insensitive to humidity is developed for resistance to environmental influences. A threshold-based least square support vector regression (LS-SVR)estimator is implemented on a DSP for classification and concentration measurements. Experimental results confirm that LS-SVR produces higher accuracy compared with artificial neural networks (ANNs) and a faster convergence rate than the standard support vector regression (SVR). The designed WEN system effectively achieves gas mixture analysis in a real-time process. PMID:22346587

A Hilbert transform-based smart sensor for detection, classification, and quantification of power quality disturbances.

PubMed

Granados-Lieberman, David; Valtierra-Rodriguez, Martin; Morales-Hernandez, Luis A; Romero-Troncoso, Rene J; Osornio-Rios, Roque A

2013-04-25

Power quality disturbance (PQD) monitoring has become an important issue due to the growing number of disturbing loads connected to the power line and to the susceptibility of certain loads to their presence. In any real power system, there are multiple sources of several disturbances which can have different magnitudes and appear at different times. In order to avoid equipment damage and estimate the damage severity, they have to be detected, classified, and quantified. In this work, a smart sensor for detection, classification, and quantification of PQD is proposed. First, the Hilbert transform (HT) is used as detection technique; then, the classification of the envelope of a PQD obtained through HT is carried out by a feed forward neural network (FFNN). Finally, the root mean square voltage (Vrms), peak voltage (Vpeak), crest factor (CF), and total harmonic distortion (THD) indices calculated through HT and Parseval's theorem as well as an instantaneous exponential time constant quantify the PQD according to the disturbance presented. The aforementioned methodology is processed online using digital hardware signal processing based on field programmable gate array (FPGA). Besides, the proposed smart sensor performance is validated and tested through synthetic signals and under real operating conditions, respectively.

Long-term Acoustic Real-Time Sensor for Polar Areas (LARA)

DTIC Science & Technology

2013-09-30

Volcano and the Middle Valley Ridge segment in the northeast Pacific Ocean. Both areas have seafloor volcanic eruptions forecast for the near future...Sensor for Polar Areas (LARA) for real-time monitoring of marine mammals, ambient noise levels, seismic activities (e.g., eruption of undersea volcanoes...LARA technology will be useful for real-time monitoring of deep-ocean seismic and volcanic activity (e.g., Dziak et al., 2011) - especially in areas

Potentiometric Biosensor for Studying Hydroquinone Cytotoxicity in vitro

PubMed Central

Wang, Yanyan; Chen, Qiang; Zeng, Xiangqun

2009-01-01

Many processes in living cells have electrochemical characteristics that are suitable for measurement by potentiometric biosensors. Potentiometric biosensors allow non invasive, real-time monitoring of the extracellular environment changes by measuring the potential at cell/sensor interface. This can be used as an indicator for overall cell cytotoxicity. The present work employs a potentiometric sensor array to investigate the cytotoxicity of hydroquinone to cultured mammalian V79 cells. Various electrode substrates (Au, PPy-HQ and PPy-PS) used for cell growth were designed and characterized. The controllable release of hydroquinone from PPy substrates was studied. Our results showed that hydroquinone exposure affected cell proliferation and delayed cell growth and attachment in a dose-dependent manner. Additionally, we have shown that exposure of V79 cells to hydroquinone at low doses (i.e 5μM) for more than 15 hours allows V79 cells to gain enhanced adaptability to survive exposure to high toxic HQ doses afterwards. Compared with traditional methods, the potentiometric biosensor not only provides non-invasive and real time monitoring of the cellular reactions but also is more sensitive for in vitro cytotoxicity study. By real time and non-invasive monitoring of the extracellular potential in vitro, the potentiometric sensor system represents a promising biosensor system for drug discovery. PMID:19926470

Research on a new fiber-optic axial pressure sensor of transformer winding based on fiber Bragg grating

NASA Astrophysics Data System (ADS)

Liu, Yuan; Li, Lianqing; Zhao, Lin; Wang, Jiqiang; Liu, Tongyu

2017-12-01

Based on the principle of the fiber Bragg grating, a new type of fiber-optic pressure sensor for axial force measurement of transformer winding is designed, which is designed with the structure of bending plate beam, the optimization of the packaging process, and material of the sensor. Through the calibration experiment to calibrate the sensor, the field test results of the Taikai transformer factory show that the sensitivity of the sensor is 0.133 pm/kPa and the repeatability error is 2.7% FS. The data of the fiber-optic pressure sensor in different positions maintain consistent and repeatable, which can meet the requirement of the real-time monitoring of the axial force of transformer winding.

Real-time bio-sensors for enhanced C2ISR operator performance

NASA Astrophysics Data System (ADS)

Miller, James C.

2005-05-01

The objectives of two Air Force Small Business research topics were to develop a real-time, unobtrusive, biological sensing and monitoring technology for evaluating cognitive readiness in command and control environments (i.e., console operators). We sought an individualized status monitoring system for command and control operators and teams. The system was to consist of a collection of bio-sensing technologies and processing and feedback algorithms that could eventually guide the effective incorporation of fatigue-adaptive workload interventions into weapon systems to mitigate episodes of cognitive overload and lapses in operator attention that often result in missed signals and catastrophic failures. Contractors set about determining what electro-physiological and other indicators of compromised operator states are most amenable for unobtrusive monitoring of psychophysiological and warfighter performance data. They proposed multi-sensor platforms of bio-sensing technologies for development. The sensors will be continuously-wearable or off-body and will not require complicated or uncomfortable preparation. A general overview of the proposed approaches and of progress toward the objective is presented.

A Novel Real-time Carbon Dioxide Analyzer for Health and Environmental Applications

PubMed Central

Zhao, Di; Miller, Dylan; Xian, Xiaojun; Tsow, Francis

2014-01-01

To be able to detect carbon dioxide (CO2) with high accuracy and fast response time is critical for many health and environmental applications. We report on a pocket-sized CO2 sensor for real-time analysis of end-tidal CO2, and environmental CO2. The sensor shows fast and reversible response to CO2 over a wide concentration range, covering the needs of both environmental and health applications. It is also immune to the presence of various interfering gases in ambient or expired air. Furthermore, the sensor has been used for real-time breath analysis, and the results are in good agreement with those from a commercial CO2 detector. PMID:24659857

A Novel Real-time Carbon Dioxide Analyzer for Health and Environmental Applications.

PubMed

Zhao, Di; Miller, Dylan; Xian, Xiaojun; Tsow, Francis; Forzani, Erica S

2014-05-01

To be able to detect carbon dioxide (CO 2 ) with high accuracy and fast response time is critical for many health and environmental applications. We report on a pocket-sized CO 2 sensor for real-time analysis of end-tidal CO 2, and environmental CO 2 . The sensor shows fast and reversible response to CO 2 over a wide concentration range, covering the needs of both environmental and health applications. It is also immune to the presence of various interfering gases in ambient or expired air. Furthermore, the sensor has been used for real-time breath analysis, and the results are in good agreement with those from a commercial CO 2 detector.

System perspectives for mobile platform design in m-Health

NASA Astrophysics Data System (ADS)

Roveda, Janet M.; Fink, Wolfgang

2016-05-01

Advances in integrated circuit technologies have led to the integration of medical sensor front ends with data processing circuits, i.e., mobile platform design for wearable sensors. We discuss design methodologies for wearable sensor nodes and their applications in m-Health. From the user perspective, flexibility, comfort, appearance, fashion, ease-of-use, and visibility are key form factors. From the technology development point of view, high accuracy, low power consumption, and high signal to noise ratio are desirable features. From the embedded software design standpoint, real time data analysis algorithms, application and database interfaces are the critical components to create successful wearable sensor-based products.

An Autonomous Sensor System Architecture for Active Flow and Noise Control Feedback

NASA Technical Reports Server (NTRS)

Humphreys, William M, Jr.; Culliton, William G.

2008-01-01

Multi-channel sensor fusion represents a powerful technique to simply and efficiently extract information from complex phenomena. While the technique has traditionally been used for military target tracking and situational awareness, a study has been successfully completed that demonstrates that sensor fusion can be applied equally well to aerodynamic applications. A prototype autonomous hardware processor was successfully designed and used to detect in real-time the two-dimensional flow reattachment location generated by a simple separated-flow wind tunnel model. The success of this demonstration illustrates the feasibility of using autonomous sensor processing architectures to enhance flow control feedback signal generation.

Improved GSO Optimized ESN Soft-Sensor Model of Flotation Process Based on Multisource Heterogeneous Information Fusion

PubMed Central

Wang, Jie-sheng; Han, Shuang; Shen, Na-na

2014-01-01

For predicting the key technology indicators (concentrate grade and tailings recovery rate) of flotation process, an echo state network (ESN) based fusion soft-sensor model optimized by the improved glowworm swarm optimization (GSO) algorithm is proposed. Firstly, the color feature (saturation and brightness) and texture features (angular second moment, sum entropy, inertia moment, etc.) based on grey-level co-occurrence matrix (GLCM) are adopted to describe the visual characteristics of the flotation froth image. Then the kernel principal component analysis (KPCA) method is used to reduce the dimensionality of the high-dimensional input vector composed by the flotation froth image characteristics and process datum and extracts the nonlinear principal components in order to reduce the ESN dimension and network complex. The ESN soft-sensor model of flotation process is optimized by the GSO algorithm with congestion factor. Simulation results show that the model has better generalization and prediction accuracy to meet the online soft-sensor requirements of the real-time control in the flotation process. PMID:24982935

Feed-Forward Neural Network Soft-Sensor Modeling of Flotation Process Based on Particle Swarm Optimization and Gravitational Search Algorithm

PubMed Central

Wang, Jie-Sheng; Han, Shuang

2015-01-01

For predicting the key technology indicators (concentrate grade and tailings recovery rate) of flotation process, a feed-forward neural network (FNN) based soft-sensor model optimized by the hybrid algorithm combining particle swarm optimization (PSO) algorithm and gravitational search algorithm (GSA) is proposed. Although GSA has better optimization capability, it has slow convergence velocity and is easy to fall into local optimum. So in this paper, the velocity vector and position vector of GSA are adjusted by PSO algorithm in order to improve its convergence speed and prediction accuracy. Finally, the proposed hybrid algorithm is adopted to optimize the parameters of FNN soft-sensor model. Simulation results show that the model has better generalization and prediction accuracy for the concentrate grade and tailings recovery rate to meet the online soft-sensor requirements of the real-time control in the flotation process. PMID:26583034

Real-time distributed video coding for 1K-pixel visual sensor networks

NASA Astrophysics Data System (ADS)

Hanca, Jan; Deligiannis, Nikos; Munteanu, Adrian

2016-07-01

Many applications in visual sensor networks (VSNs) demand the low-cost wireless transmission of video data. In this context, distributed video coding (DVC) has proven its potential to achieve state-of-the-art compression performance while maintaining low computational complexity of the encoder. Despite their proven capabilities, current DVC solutions overlook hardware constraints, and this renders them unsuitable for practical implementations. This paper introduces a DVC architecture that offers highly efficient wireless communication in real-world VSNs. The design takes into account the severe computational and memory constraints imposed by practical implementations on low-resolution visual sensors. We study performance-complexity trade-offs for feedback-channel removal, propose learning-based techniques for rate allocation, and investigate various simplifications of side information generation yielding real-time decoding. The proposed system is evaluated against H.264/AVC intra, Motion-JPEG, and our previously designed DVC prototype for low-resolution visual sensors. Extensive experimental results on various data show significant improvements in multiple configurations. The proposed encoder achieves real-time performance on a 1k-pixel visual sensor mote. Real-time decoding is performed on a Raspberry Pi single-board computer or a low-end notebook PC. To the best of our knowledge, the proposed codec is the first practical DVC deployment on low-resolution VSNs.

Acoustic Emission and Velocity Measurements using a Modular Borehole Prototype Tool to Provide Real Time Rock Mass Characterization.

NASA Astrophysics Data System (ADS)

Collins, D. S.; Pettitt, W. S.; Young, R. P.

2003-04-01

Permanent changes to rock mass properties can occur due to the application of excavation or thermal induced stresses. This project involves the design of hardware and software for the long term monitoring of a rock volume, and the real time analysis and interpretation of induced microcracks and their properties. A set of borehole sondes have been designed with each sonde containing up to 6 sensor modules. Each piezoelectric sensor is dual mode allowing it to either transmit an ultrasonic pulse through a rock mass, or receive ultrasonic waveform data. Good coupling of the sensors with the borehole wall is achieved through a motorized clamping mechanism. The borehole sondes are connected to a surface interface box and digital acquisition system and controlled by a laptop computer. The system allows acoustic emission (AE) data to be recorded at all times using programmable trigger logic. The AE data is processed in real time for 3D source location and magnitude, with further analysis such as mechanism type available offline. Additionally the system allows velocity surveys to be automatically performed at pre-defined times. A modelling component of the project, using a 3D dynamic finite difference code, is investigating the effect that different microcrack distributions have on velocity waveform data in terms of time and frequency amplitude. The modelling codes will be validated using data recorded from laboratory tests on rocks with known crack fabrics, and then used in insitu experimental tests. This modelling information will be used to help interpret, in real time, microcrack characteristics such as crack density, size, and fluid content. The technology has applications in a number of branches of geotechnical and civil engineering including radioactive waste storage, mining, dams, bridges, and oil reservoir monitoring.

Signal processing methodologies for an acoustic fetal heart rate monitor

NASA Technical Reports Server (NTRS)

Pretlow, Robert A., III; Stoughton, John W.

1992-01-01

Research and development is presented of real time signal processing methodologies for the detection of fetal heart tones within a noise-contaminated signal from a passive acoustic sensor. A linear predictor algorithm is utilized for detection of the heart tone event and additional processing derives heart rate. The linear predictor is adaptively 'trained' in a least mean square error sense on generic fetal heart tones recorded from patients. A real time monitor system is described which outputs to a strip chart recorder for plotting the time history of the fetal heart rate. The system is validated in the context of the fetal nonstress test. Comparisons are made with ultrasonic nonstress tests on a series of patients. Comparative data provides favorable indications of the feasibility of the acoustic monitor for clinical use.

Real time sensor for therapeutic radiation delivery

DOEpatents

Bliss, M.; Craig, R.A.; Reeder, P.L.

1998-01-06

The invention is a real time sensor for therapeutic radiation. A probe is placed in or near the patient that senses in real time the dose at the location of the probe. The strength of the dose is determined by either an insertion or an exit probe. The location is determined by a series of vertical and horizontal sensing elements that gives the operator a real time read out dose location relative to placement of the patient. The increased accuracy prevents serious tissue damage to the patient by preventing overdose or delivery of a dose to a wrong location within the body. 14 figs.

Real time sensor for therapeutic radiation delivery

DOEpatents

Bliss, Mary; Craig, Richard A.; Reeder, Paul L.

1998-01-01

The invention is a real time sensor for therapeutic radiation. A probe is placed in or near the patient that senses in real time the dose at the location of the probe. The strength of the dose is determined by either an insertion or an exit probe. The location is determined by a series of vertical and horizontal sensing elements that gives the operator a real time read out dose location relative to placement of the patient. The increased accuracy prevents serious tissue damage to the patient by preventing overdose or delivery of a dose to a wrong location within the body.

Stretchable and Photocatalytically Renewable Electrochemical Sensor Based on Sandwich Nanonetworks for Real-Time Monitoring of Cells.

PubMed

Wang, Ya-Wen; Liu, Yan-Ling; Xu, Jia-Quan; Qin, Yu; Huang, Wei-Hua

2018-05-15

Stretchable electrochemical (EC) sensors have broad prospects in real-time monitoring of living cells and tissues owing to their excellent elasticity and deformability. However, the redox reaction products and cell secretions are easily adsorbed on the electrode, resulting in sensor fouling and passivation. Herein, we developed a stretchable and photocatalytically renewable EC sensor based on Au nanotubes (NTs) and TiO 2 nanowires (NWs) sandwich nanonetworks. The external Au NTs are used for EC sensing, and internal TiO 2 NWs provide photocatalytic performance to degrade contaminants, which endows the sensor with excellent EC performance, high photocatalytic activity, and favorable mechanical tensile property. This allows highly sensitive recycling monitoring of NO released from endothelial cells and 5-HT released from mast cells under their stretching states in real time, therefore providing a promising tool to unravel elastic and mechanically sensitive cells, tissues, and organs.

Robotics technology discipline

NASA Technical Reports Server (NTRS)

Montemerlo, Melvin D.

1990-01-01

Viewgraphs on robotics technology discipline for Space Station Freedom are presented. Topics covered include: mechanisms; sensors; systems engineering processes for integrated robotics; man/machine cooperative control; 3D-real-time machine perception; multiple arm redundancy control; manipulator control from a movable base; multi-agent reasoning; and surfacing evolution technologies.

Real-Time Workload Monitoring: Improving Cognitive Process Models

DTIC Science & Technology

2010-10-01

Research or comparable systems with similar technical properties having been made available on the market by now. Remote sensors lack the required visual...questionnaire. This includes age, gender, alcohol and nicotine consumption, visual status, sleep during the last three days and last night, sportive

CAIRSENSE Study: Real-world evaluation of low cost sensors in Denver, Colorado

EPA Science Inventory

Low-cost air pollution sensors are a rapidly developing field in air monitoring. In recent years, numerous sensors have been developed that can provide real-time concentration data for different air pollutants at costs accessible to individuals and non-regulatory groups. Addition...

An embedded vision system for an unmanned four-rotor helicopter

NASA Astrophysics Data System (ADS)

Lillywhite, Kirt; Lee, Dah-Jye; Tippetts, Beau; Fowers, Spencer; Dennis, Aaron; Nelson, Brent; Archibald, James

2006-10-01

In this paper an embedded vision system and control module is introduced that is capable of controlling an unmanned four-rotor helicopter and processing live video for various law enforcement, security, military, and civilian applications. The vision system is implemented on a newly designed compact FPGA board (Helios). The Helios board contains a Xilinx Virtex-4 FPGA chip and memory making it capable of implementing real time vision algorithms. A Smooth Automated Intelligent Leveling daughter board (SAIL), attached to the Helios board, collects attitude and heading information to be processed in order to control the unmanned helicopter. The SAIL board uses an electrolytic tilt sensor, compass, voltage level converters, and analog to digital converters to perform its operations. While level flight can be maintained, problems stemming from the characteristics of the tilt sensor limits maneuverability of the helicopter. The embedded vision system has proven to give very good results in its performance of a number of real-time robotic vision algorithms.

A Framework for Real-Time Collection, Analysis, and Classification of Ubiquitous Infrasound Data

NASA Astrophysics Data System (ADS)

Christe, A.; Garces, M. A.; Magana-Zook, S. A.; Schnurr, J. M.

2015-12-01

Traditional infrasound arrays are generally expensive to install and maintain. There are ~10^3 infrasound channels on Earth today. The amount of data currently provided by legacy architectures can be processed on a modest server. However, the growing availability of low-cost, ubiquitous, and dense infrasonic sensor networks presents a substantial increase in the volume, velocity, and variety of data flow. Initial data from a prototype ubiquitous global infrasound network is already pushing the boundaries of traditional research server and communication systems, in particular when serving data products over heterogeneous, international network topologies. We present a scalable, cloud-based approach for capturing and analyzing large amounts of dense infrasonic data (>10^6 channels). We utilize Akka actors with WebSockets to maintain data connections with infrasound sensors. Apache Spark provides streaming, batch, machine learning, and graph processing libraries which will permit signature classification, cross-correlation, and other analytics in near real time. This new framework and approach provide significant advantages in scalability and cost.

Precision Landing and Hazard Avoidance Doman

NASA Technical Reports Server (NTRS)

Robertson, Edward A.; Carson, John M., III

2016-01-01

The Precision Landing and Hazard Avoidance (PL&HA) domain addresses the development, integration, testing, and spaceflight infusion of sensing, processing, and GN&C functions critical to the success and safety of future human and robotic exploration missions. PL&HA sensors also have applications to other mission events, such as rendezvous and docking. Autonomous PL&HA builds upon the core GN&C capabilities developed to enable soft, controlled landings on the Moon, Mars, and other solar system bodies. Through the addition of a Terrain Relative Navigation (TRN) function, precision landing within tens of meters of a map-based target is possible. The addition of a 3-D terrain mapping lidar sensor improves the probability of a safe landing via autonomous, real-time Hazard Detection and Avoidance (HDA). PL&HA significantly improves the probability of mission success and enhances access to sites of scientific interest located in challenging terrain. PL&HA can also utilize external navigation aids, such as navigation satellites and surface beacons. Advanced Lidar Sensors High precision ranging, velocimetry, and 3-D terrain mapping Terrain Relative Navigation (TRN) TRN compares onboard reconnaissance data with real-time terrain imaging data to update the S/C position estimate Hazard Detection and Avoidance (HDA) Generates a high-resolution, 3-D terrain map in real-time during the approach trajectory to identify safe landing targets Inertial Navigation During Terminal Descent High precision surface relative sensors enable accurate inertial navigation during terminal descent and a tightly controlled touchdown within meters of the selected safe landing target.

NASA Tech Briefs, January 2005

NASA Technical Reports Server (NTRS)

2005-01-01

Topics covered include: Fiber-Optic Sensor Would Monitor Growth of Polymer Film; Sensors for Pointing Moving Instruments Toward Each Other; Pd/CeO2/SiC Chemical Sensors; Microparticle Flow Sensor; Scattering-Type Surface-Plasmon-Resonance Biosensors; Diode-Laser-Based Spectrometer for Sensing Gases; Improved Cathode Structure for a Direct Methanol Fuel Cell; X-Band, 17-Watt Solid-State Power Amplifier; Improved Anode for a Direct Methanol Fuel Cell; Tools for Designing and Analyzing Structures; Interactive Display of Scenes with Annotations; Solving Common Mathematical Problems; Tools for Basic Statistical Analysis; Program Calculates Forces in Bolted Structural Joints; Integrated Structural Analysis and Test Program; Molybdate Coatings for Protecting Aluminum Against Corrosion; Synthesizing Diamond from Liquid Feedstock; Modifying Silicates for Better Dispersion in Nanocomposites; Powder-Collection System for Ultrasonic/Sonic Drill/Corer; Semiautomated, Reproducible Batch Processing of Soy; Hydrogen Peroxide Enhances Removal of NOx from Flue Gases; Subsurface Ice Probe; Real-Time Simulation of Aeroheating of the Hyper-X Airplane; Using Laser-Induced Incandescence To Measure Soot in Exhaust; Method of Real-Time Principal-Component Analysis; Insect-Inspired Flight Control for Unmanned Aerial Vehicles; Domain Compilation for Embedded Real-Time Planning; Semantic Metrics for Analysis of Software; Simulation of Laser Cooling and Trapping in Engineering Applications; Large Fluvial Fans and Exploration for Hydrocarbons; Doping-Induced Interband Gain in InAs/AlSb Quantum Wells; Development of Software for a Lidar-Altimeter Processor; Upgrading the Space Shuttle Caution and Warning System; and Fractal Reference Signals in Pulse-Width Modulation.

Determination of Exterior Orientation Parameters Through Direct Geo-Referencing in a Real-Time Aerial Monitoring System

NASA Astrophysics Data System (ADS)

Kim, H.; Lee, J.; Choi, K.; Lee, I.

2012-07-01

Rapid responses for emergency situations such as natural disasters or accidents often require geo-spatial information describing the on-going status of the affected area. Such geo-spatial information can be promptly acquired by a manned or unmanned aerial vehicle based multi-sensor system that can monitor the emergent situations in near real-time from the air using several kinds of sensors. Thus, we are in progress of developing such a real-time aerial monitoring system (RAMS) consisting of both aerial and ground segments. The aerial segment acquires the sensory data about the target areas by a low-altitude helicopter system equipped with sensors such as a digital camera and a GPS/IMU system and transmits them to the ground segment through a RF link in real-time. The ground segment, which is a deployable ground station installed on a truck, receives the sensory data and rapidly processes them to generate ortho-images, DEMs, etc. In order to generate geo-spatial information, in this system, exterior orientation parameters (EOP) of the acquired images are obtained through direct geo-referencing because it is difficult to acquire coordinates of ground points in disaster area. The main process, since the data acquisition stage until the measurement of EOP, is discussed as follows. First, at the time of data acquisition, image acquisition time synchronized by GPS time is recorded as part of image file name. Second, the acquired data are then transmitted to the ground segment in real-time. Third, by processing software for ground segment, positions/attitudes of acquired images are calculated through a linear interpolation using the GPS time of the received position/attitude data and images. Finally, the EOPs of images are obtained from position/attitude data by deriving the relationships between a camera coordinate system and a GPS/IMU coordinate system. In this study, we evaluated the accuracy of the EOP decided by direct geo-referencing in our system. To perform this, we used the precisely calculated EOP through the digital photogrammetry workstation (DPW) as reference data. The results of the evaluation indicate that the accuracy of the EOP acquired by our system is reasonable in comparison with the performance of GPS/IMU system. Also our system can acquire precise multi-sensory data to generate the geo-spatial information in emergency situations. In the near future, we plan to complete the development of the rapid generation system of the ground segment. Our system is expected to be able to acquire the ortho-image and DEM on the damaged area in near real-time. Its performance along with the accuracy of the generated geo-spatial information will also be evaluated and reported in the future work.

Real-Time Sensor Validation, Signal Reconstruction, and Feature Detection for an RLV Propulsion Testbed

NASA Technical Reports Server (NTRS)

Jankovsky, Amy L.; Fulton, Christopher E.; Binder, Michael P.; Maul, William A., III; Meyer, Claudia M.

1998-01-01

A real-time system for validating sensor health has been developed in support of the reusable launch vehicle program. This system was designed for use in a propulsion testbed as part of an overall effort to improve the safety, diagnostic capability, and cost of operation of the testbed. The sensor validation system was designed and developed at the NASA Lewis Research Center and integrated into a propulsion checkout and control system as part of an industry-NASA partnership, led by Rockwell International for the Marshall Space Flight Center. The system includes modules for sensor validation, signal reconstruction, and feature detection and was designed to maximize portability to other applications. Review of test data from initial integration testing verified real-time operation and showed the system to perform correctly on both hard and soft sensor failure test cases. This paper discusses the design of the sensor validation and supporting modules developed at LeRC and reviews results obtained from initial test cases.

Omni-Purpose Stretchable Strain Sensor Based on a Highly Dense Nanocracking Structure for Whole-Body Motion Monitoring.

PubMed

Jeon, Hyungkook; Hong, Seong Kyung; Kim, Min Seo; Cho, Seong J; Lim, Geunbae

2017-12-06

Here, we report an omni-purpose stretchable strain sensor (OPSS sensor) based on a nanocracking structure for monitoring whole-body motions including both joint-level and skin-level motions. By controlling and optimizing the nanocracking structure, inspired by the spider sensory system, the OPSS sensor is endowed with both high sensitivity (gauge factor ≈ 30) and a wide working range (strain up to 150%) under great linearity (R 2 = 0.9814) and fast response time (<30 ms). Furthermore, the fabrication process of the OPSS sensor has advantages of being extremely simple, patternable, integrated circuit-compatible, and reliable in terms of reproducibility. Using the OPSS sensor, we detected various human body motions including both moving of joints and subtle deforming of skin such as pulsation. As specific medical applications of the sensor, we also successfully developed a glove-type hand motion detector and a real-time Morse code communication system for patients with general paralysis. Therefore, considering the outstanding sensing performances, great advantages of the fabrication process, and successful results from a variety of practical applications, we believe that the OPSS sensor is a highly suitable strain sensor for whole-body motion monitoring and has potential for a wide range of applications, such as medical robotics and wearable healthcare devices.

Optimal dynamic voltage scaling for wireless sensor nodes with real-time constraints

NASA Astrophysics Data System (ADS)

Cassandras, Christos G.; Zhuang, Shixin

2005-11-01

Sensors are increasingly embedded in manufacturing systems and wirelessly networked to monitor and manage operations ranging from process and inventory control to tracking equipment and even post-manufacturing product monitoring. In building such sensor networks, a critical issue is the limited and hard to replenish energy in the devices involved. Dynamic voltage scaling is a technique that controls the operating voltage of a processor to provide desired performance while conserving energy and prolonging the overall network's lifetime. We consider such power-limited devices processing time-critical tasks which are non-preemptive, aperiodic and have uncertain arrival times. We treat voltage scaling as a dynamic optimization problem whose objective is to minimize energy consumption subject to hard or soft real-time execution constraints. In the case of hard constraints, we build on prior work (which engages a voltage scaling controller at task completion times) by developing an intra-task controller that acts at all arrival times of incoming tasks. We show that this optimization problem can be decomposed into two simpler ones whose solution leads to an algorithm that does not actually require solving any nonlinear programming problems. In the case of soft constraints, this decomposition must be partly relaxed, but it still leads to a scalable (linear in the number of tasks) algorithm. Simulation results are provided to illustrate performance improvements in systems with intra-task controllers compared to uncontrolled systems or those using inter-task control.

In-Situ monitoring and modeling of metal additive manufacturing powder bed fusion

NASA Astrophysics Data System (ADS)

Alldredge, Jacob; Slotwinski, John; Storck, Steven; Kim, Sam; Goldberg, Arnold; Montalbano, Timothy

2018-04-01

One of the major challenges in metal additive manufacturing is developing in-situ sensing and feedback control capabilities to eliminate build errors and allow qualified part creation without the need for costly and destructive external testing. Previously, many groups have focused on high fidelity numerical modeling and true temperature thermal imaging systems. These approaches require large computational resources or costly hardware that requires complex calibration and are difficult to integrate into commercial systems. In addition, due to the rapid change in the state of the material as well as its surface properties, getting true temperature is complicated and difficult. Here, we describe a different approach where we implement a low cost thermal imaging solution allowing for relative temperature measurements sufficient for detecting unwanted process variability. We match this with a faster than real time qualitative model that allows the process to be rapidly modeled during the build. The hope is to combine these two, allowing for the detection of anomalies in real time, enabling corrective action to potentially be taken, or parts to be stopped immediately after the error, saving material and time. Here we describe our sensor setup, its costs and abilities. We also show the ability to detect in real time unwanted process deviations. We also show that the output of our high speed model agrees qualitatively with experimental results. These results lay the groundwork for our vision of an integrated feedback and control scheme that combines low cost, easy to use sensors and fast modeling for process deviation monitoring.

Real-time sensor data validation

NASA Technical Reports Server (NTRS)

Bickmore, Timothy W.

1994-01-01

This report describes the status of an on-going effort to develop software capable of detecting sensor failures on rocket engines in real time. This software could be used in a rocket engine controller to prevent the erroneous shutdown of an engine due to sensor failures which would otherwise be interpreted as engine failures by the control software. The approach taken combines analytical redundancy with Bayesian belief networks to provide a solution which has well defined real-time characteristics and well-defined error rates. Analytical redundancy is a technique in which a sensor's value is predicted by using values from other sensors and known or empirically derived mathematical relations. A set of sensors and a set of relations among them form a network of cross-checks which can be used to periodically validate all of the sensors in the network. Bayesian belief networks provide a method of determining if each of the sensors in the network is valid, given the results of the cross-checks. This approach has been successfully demonstrated on the Technology Test Bed Engine at the NASA Marshall Space Flight Center. Current efforts are focused on extending the system to provide a validation capability for 100 sensors on the Space Shuttle Main Engine.

An Investigation into Spike-Based Neuromorphic Approaches for Artificial Olfactory Systems

PubMed Central

Osseiran, Adam

2017-01-01

The implementation of neuromorphic methods has delivered promising results for vision and auditory sensors. These methods focus on mimicking the neuro-biological architecture to generate and process spike-based information with minimal power consumption. With increasing interest in developing low-power and robust chemical sensors, the application of neuromorphic engineering concepts for electronic noses has provided an impetus for research focusing on improving these instruments. While conventional e-noses apply computationally expensive and power-consuming data-processing strategies, neuromorphic olfactory sensors implement the biological olfaction principles found in humans and insects to simplify the handling of multivariate sensory data by generating and processing spike-based information. Over the last decade, research on neuromorphic olfaction has established the capability of these sensors to tackle problems that plague the current e-nose implementations such as drift, response time, portability, power consumption and size. This article brings together the key contributions in neuromorphic olfaction and identifies future research directions to develop near-real-time olfactory sensors that can be implemented for a range of applications such as biosecurity and environmental monitoring. Furthermore, we aim to expose the computational parallels between neuromorphic olfaction and gustation for future research focusing on the correlation of these senses. PMID:29125586

Cellular nonlinear networks for strike-point localization at JET

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

Arena, P.; Fortuna, L.; Bruno, M.

2005-11-15

At JET, the potential of fast image processing for real-time purposes is thoroughly investigated. Particular attention is devoted to smart sensors based on system on chip technology. The data of the infrared cameras were processed with a chip implementing a cellular nonlinear network (CNN) structure so as to support and complement the magnetic diagnostics in the real-time localization of the strike-point position in the divertor. The circuit consists of two layers of complementary metal-oxide semiconductor components, the first being the sensor and the second implementing the actual CNN. This innovative hardware has made it possible to determine the position ofmore » the maximum thermal load with a time resolution of the order of 30 ms. Good congruency has been found with the measurement from the thermocouples in the divertor, proving the potential of the infrared data in locating the region of the maximum thermal load. The results are also confirmed by JET magnetic codes, both those used for the equilibrium reconstructions and those devoted to the identification of the plasma boundary.« less

Real time interrogation technique for fiber Bragg grating enhanced fiber loop ringdown sensors array.

PubMed

Zhang, Yunlong; Li, Ruoming; Shi, Yuechun; Zhang, Jintao; Chen, Xiangfei; Liu, Shengchun

2015-06-01

A novel fiber Bragg grating aided fiber loop ringdown (FLRD) sensor array and the wavelength-time multiplexing based interrogation technique for the FLRD sensors array are proposed. The interrogation frequency of the system is formulated and the interrelationships among the parameters of the system are analyzed. To validate the performance of the proposed system, a five elements array is experimentally demonstrated, and the system shows the capability of real time monitoring every FLRD element with interrogation frequency of 125.5 Hz.

STS-114 Engine Cut-off Sensor Anomaly Technical Consultation Report

NASA Technical Reports Server (NTRS)

Wilson, Timmy R.; Kichak, Robert A.; Ungar, Eugene K.; Cherney, Robert; Rickman, Steve L.

2009-01-01

The NESC consultation team participated in real-time troubleshooting of the Main Propulsion System (MPS) Engine Cutoff (ECO) sensor system failures during STS-114 launch countdown. The team assisted with External Tank (ET) thermal and ECO Point Sensor Box (PSB) circuit analyses, and made real-time inputs to the Space Shuttle Program (SSP) problem resolution teams. Several long-term recommendations resulted. One recommendation was to conduct cryogenic tests of the ECO sensors to validate, or disprove, the theory that variations in circuit impedance due to cryogenic effects on swaged connections within the sensor were the root cause of STS-114 failures.

Real-time 3D measurement based on structured light illumination considering camera lens distortion

NASA Astrophysics Data System (ADS)

Feng, Shijie; Chen, Qian; Zuo, Chao; Sun, Jiasong; Yu, ShiLing

2014-12-01

Optical three-dimensional (3-D) profilometry is gaining increasing attention for its simplicity, flexibility, high accuracy, and non-contact nature. Recent advances in imaging sensors and digital projection technology further its progress in high-speed, real-time applications, enabling 3-D shapes reconstruction of moving objects and dynamic scenes. In traditional 3-D measurement system where the processing time is not a key factor, camera lens distortion correction is performed directly. However, for the time-critical high-speed applications, the time-consuming correction algorithm is inappropriate to be performed directly during the real-time process. To cope with this issue, here we present a novel high-speed real-time 3-D coordinates measuring technique based on fringe projection with the consideration of the camera lens distortion. A pixel mapping relation between a distorted image and a corrected one is pre-determined and stored in computer memory for real-time fringe correction. And a method of lookup table (LUT) is introduced as well for fast data processing. Our experimental results reveal that the measurement error of the in-plane coordinates has been reduced by one order of magnitude and the accuracy of the out-plane coordinate been tripled after the distortions being eliminated. Moreover, owing to the merit of the LUT, the 3-D reconstruction can be achieved at 92.34 frames per second.

[Construction and analysis of a monitoring system with remote real-time multiple physiological parameters based on cloud computing].

PubMed

Zhu, Lingyun; Li, Lianjie; Meng, Chunyan

2014-12-01

There have been problems in the existing multiple physiological parameter real-time monitoring system, such as insufficient server capacity for physiological data storage and analysis so that data consistency can not be guaranteed, poor performance in real-time, and other issues caused by the growing scale of data. We therefore pro posed a new solution which was with multiple physiological parameters and could calculate clustered background data storage and processing based on cloud computing. Through our studies, a batch processing for longitudinal analysis of patients' historical data was introduced. The process included the resource virtualization of IaaS layer for cloud platform, the construction of real-time computing platform of PaaS layer, the reception and analysis of data stream of SaaS layer, and the bottleneck problem of multi-parameter data transmission, etc. The results were to achieve in real-time physiological information transmission, storage and analysis of a large amount of data. The simulation test results showed that the remote multiple physiological parameter monitoring system based on cloud platform had obvious advantages in processing time and load balancing over the traditional server model. This architecture solved the problems including long turnaround time, poor performance of real-time analysis, lack of extensibility and other issues, which exist in the traditional remote medical services. Technical support was provided in order to facilitate a "wearable wireless sensor plus mobile wireless transmission plus cloud computing service" mode moving towards home health monitoring for multiple physiological parameter wireless monitoring.

Multisensor Network System for Wildfire Detection Using Infrared Image Processing

PubMed Central

Bosch, I.; Serrano, A.; Vergara, L.

2013-01-01

This paper presents the next step in the evolution of multi-sensor wireless network systems in the early automatic detection of forest fires. This network allows remote monitoring of each of the locations as well as communication between each of the sensors and with the control stations. The result is an increased coverage area, with quicker and safer responses. To determine the presence of a forest wildfire, the system employs decision fusion in thermal imaging, which can exploit various expected characteristics of a real fire, including short-term persistence and long-term increases over time. Results from testing in the laboratory and in a real environment are presented to authenticate and verify the accuracy of the operation of the proposed system. The system performance is gauged by the number of alarms and the time to the first alarm (corresponding to a real fire), for different probability of false alarm (PFA). The necessity of including decision fusion is thereby demonstrated. PMID:23843734

Multisensor network system for wildfire detection using infrared image processing.

PubMed

Bosch, I; Serrano, A; Vergara, L

2013-01-01

This paper presents the next step in the evolution of multi-sensor wireless network systems in the early automatic detection of forest fires. This network allows remote monitoring of each of the locations as well as communication between each of the sensors and with the control stations. The result is an increased coverage area, with quicker and safer responses. To determine the presence of a forest wildfire, the system employs decision fusion in thermal imaging, which can exploit various expected characteristics of a real fire, including short-term persistence and long-term increases over time. Results from testing in the laboratory and in a real environment are presented to authenticate and verify the accuracy of the operation of the proposed system. The system performance is gauged by the number of alarms and the time to the first alarm (corresponding to a real fire), for different probability of false alarm (PFA). The necessity of including decision fusion is thereby demonstrated.

A Wireless Sensor System for Real-Time Measurement of Pressure Profiles at Lower Limb Protheses to Ensure Proper Fitting

DTIC Science & Technology

2011-10-01

been developed. The next step is to develop a the base technology into a grid like mapping sensor, construct the excitation and detection circuits...the project involves advancing the base technology into a grid -like mapping se nsor, constructing the excitation and detection circuits, modifying and...further. In conclusion, the screen printing and etching process allows for precise repeat able production of sensing elements for grid fabrication

Real-Time Digital Signal Processing Based on FPGAs for Electronic Skin Implementation †

PubMed Central

Ibrahim, Ali; Gastaldo, Paolo; Chible, Hussein; Valle, Maurizio

2017-01-01

Enabling touch-sensing capability would help appliances understand interaction behaviors with their surroundings. Many recent studies are focusing on the development of electronic skin because of its necessity in various application domains, namely autonomous artificial intelligence (e.g., robots), biomedical instrumentation, and replacement prosthetic devices. An essential task of the electronic skin system is to locally process the tactile data and send structured information either to mimic human skin or to respond to the application demands. The electronic skin must be fabricated together with an embedded electronic system which has the role of acquiring the tactile data, processing, and extracting structured information. On the other hand, processing tactile data requires efficient methods to extract meaningful information from raw sensor data. Machine learning represents an effective method for data analysis in many domains: it has recently demonstrated its effectiveness in processing tactile sensor data. In this framework, this paper presents the implementation of digital signal processing based on FPGAs for tactile data processing. It provides the implementation of a tensorial kernel function for a machine learning approach. Implementation results are assessed by highlighting the FPGA resource utilization and power consumption. Results demonstrate the feasibility of the proposed implementation when real-time classification of input touch modalities are targeted. PMID:28287448

Real-Time Digital Signal Processing Based on FPGAs for Electronic Skin Implementation.

PubMed

Ibrahim, Ali; Gastaldo, Paolo; Chible, Hussein; Valle, Maurizio

2017-03-10

Enabling touch-sensing capability would help appliances understand interaction behaviors with their surroundings. Many recent studies are focusing on the development of electronic skin because of its necessity in various application domains, namely autonomous artificial intelligence (e.g., robots), biomedical instrumentation, and replacement prosthetic devices. An essential task of the electronic skin system is to locally process the tactile data and send structured information either to mimic human skin or to respond to the application demands. The electronic skin must be fabricated together with an embedded electronic system which has the role of acquiring the tactile data, processing, and extracting structured information. On the other hand, processing tactile data requires efficient methods to extract meaningful information from raw sensor data. Machine learning represents an effective method for data analysis in many domains: it has recently demonstrated its effectiveness in processing tactile sensor data. In this framework, this paper presents the implementation of digital signal processing based on FPGAs for tactile data processing. It provides the implementation of a tensorial kernel function for a machine learning approach. Implementation results are assessed by highlighting the FPGA resource utilization and power consumption. Results demonstrate the feasibility of the proposed implementation when real-time classification of input touch modalities are targeted.

Air-dropped sensor network for real-time high-fidelity volcano monitoring

USGS Publications Warehouse

Song, W.-Z.; Huang, R.; Xu, M.; Ma, A.; Shirazi, B.; LaHusen, R.

2009-01-01

This paper presents the design and deployment experience of an air-dropped wireless sensor network for volcano hazard monitoring. The deployment of five stations into the rugged crater of Mount St. Helens only took one hour with a helicopter. The stations communicate with each other through an amplified 802.15.4 radio and establish a self-forming and self-healing multi-hop wireless network. The distance between stations is up to 2 km. Each sensor station collects and delivers real-time continuous seismic, infrasonic, lightning, GPS raw data to a gateway. The main contribution of this paper is the design and evaluation of a robust sensor network to replace data loggers and provide real-time long-term volcano monitoring. The system supports UTC-time synchronized data acquisition with 1ms accuracy, and is online configurable. It has been tested in the lab environment, the outdoor campus and the volcano crater. Despite the heavy rain, snow, and ice as well as gusts exceeding 120 miles per hour, the sensor network has achieved a remarkable packet delivery ratio above 99% with an overall system uptime of about 93.8% over the 1.5 months evaluation period after deployment. Our initial deployment experiences with the system have alleviated the doubts of domain scientists and prove to them that a low-cost sensor network system can support real-time monitoring in extremely harsh environments. Copyright 2009 ACM.

Smartphone-based quantitative measurements on holographic sensors.

PubMed

Khalili Moghaddam, Gita; Lowe, Christopher Robin

2017-01-01

The research reported herein integrates a generic holographic sensor platform and a smartphone-based colour quantification algorithm in order to standardise and improve the determination of the concentration of analytes of interest. The utility of this approach has been exemplified by analysing the replay colour of the captured image of a holographic pH sensor in near real-time. Personalised image encryption followed by a wavelet-based image compression method were applied to secure the image transfer across a bandwidth-limited network to the cloud. The decrypted and decompressed image was processed through four principal steps: Recognition of the hologram in the image with a complex background using a template-based approach, conversion of device-dependent RGB values to device-independent CIEXYZ values using a polynomial model of the camera and computation of the CIEL*a*b* values, use of the colour coordinates of the captured image to segment the image, select the appropriate colour descriptors and, ultimately, locate the region of interest (ROI), i.e. the hologram in this case, and finally, application of a machine learning-based algorithm to correlate the colour coordinates of the ROI to the analyte concentration. Integrating holographic sensors and the colour image processing algorithm potentially offers a cost-effective platform for the remote monitoring of analytes in real time in readily accessible body fluids by minimally trained individuals.

Smartphone-based quantitative measurements on holographic sensors

PubMed Central

Khalili Moghaddam, Gita

2017-01-01

The research reported herein integrates a generic holographic sensor platform and a smartphone-based colour quantification algorithm in order to standardise and improve the determination of the concentration of analytes of interest. The utility of this approach has been exemplified by analysing the replay colour of the captured image of a holographic pH sensor in near real-time. Personalised image encryption followed by a wavelet-based image compression method were applied to secure the image transfer across a bandwidth-limited network to the cloud. The decrypted and decompressed image was processed through four principal steps: Recognition of the hologram in the image with a complex background using a template-based approach, conversion of device-dependent RGB values to device-independent CIEXYZ values using a polynomial model of the camera and computation of the CIEL*a*b* values, use of the colour coordinates of the captured image to segment the image, select the appropriate colour descriptors and, ultimately, locate the region of interest (ROI), i.e. the hologram in this case, and finally, application of a machine learning-based algorithm to correlate the colour coordinates of the ROI to the analyte concentration. Integrating holographic sensors and the colour image processing algorithm potentially offers a cost-effective platform for the remote monitoring of analytes in real time in readily accessible body fluids by minimally trained individuals. PMID:29141008

Study and Control of Various Corona Modes in an Atmospheric Pressure Weakly Ionized Plasma Reactor Using a Current Sensor Characterized by a Broad Frequency Band

NASA Astrophysics Data System (ADS)

Islam, Rokibul; Pedrow, Patrick; Lekobou, William; Englund, Karl

2013-09-01

A broad band current sensor is being used to monitor the various phenomena (primary streamers, secondary streamers, back corona, etc.) associated with an atmospheric pressure needle-array-to-grounded-screen corona discharge. The reactor consists of a PVC tube and the needle array consists of nickel coated steel electrodes with radius of curvature about 50 μ . The grounded screen is made from stainless steel mesh and applied voltage has a frequency of 60 Hz with an RMS value ranging from 0 to 10 kV. The voltage sensor is a resistive divider and the current sensor is a viewing resistor with value 50 Ω. The feed gas stream is presently (argon + acetylene) or (argon + oxygen) with the argon acting as carrier gas and the acetylene and oxygen acting as precursor gases. Voltage and current are captured with a LeCroy 9350AL 500MHz oscilloscope and analyzed with Matlab using digital signal processing algorithms. The goals of the research are 1) to measure reactor electrical power on a real time basis; 2) to provide real time control of the applied voltage and thus avoid spark conditions; and 3) to identify the various corona modes present in the reactor. Processing of substrates takes place downstream from the grounded screen, outside of the harsh corona discharge environment.

Process Analytical Technology for High Shear Wet Granulation: Wet Mass Consistency Reported by In-Line Drag Flow Force Sensor Is Consistent With Powder Rheology Measured by At-Line FT4 Powder Rheometer.

PubMed

Narang, Ajit S; Sheverev, Valery; Freeman, Tim; Both, Douglas; Stepaniuk, Vadim; Delancy, Michael; Millington-Smith, Doug; Macias, Kevin; Subramanian, Ganeshkumar

2016-01-01

Drag flow force (DFF) sensor that measures the force exerted by wet mass in a granulator on a thin cylindrical probe was shown as a promising process analytical technology for real-time in-line high-resolution monitoring of wet mass consistency during high shear wet granulation. Our previous studies indicated that this process analytical technology tool could be correlated to granulation end point established independently through drug product critical quality attributes. In this study, the measurements of flow force by a DFF sensor, taken during wet granulation of 3 placebo formulations with different binder content, are compared with concurrent at line FT4 Powder Rheometer characterization of wet granules collected at different time points of the processing. The wet mass consistency measured by the DFF sensor correlated well with the granulation's resistance to flow and interparticulate interactions as measured by FT4 Powder Rheometer. This indicated that the force pulse magnitude measured by the DFF sensor was indicative of fundamental material properties (e.g., shear viscosity and granule size/density), as they were changing during the granulation process. These studies indicate that DFF sensor can be a valuable tool for wet granulation formulation and process development and scale up, as well as for routine monitoring and control during manufacturing. Copyright © 2016. Published by Elsevier Inc.

Algorithm for real-time detection of signal patterns using phase synchrony: an application to an electrode array

NASA Astrophysics Data System (ADS)

Sadeghi, Saman; MacKay, William A.; van Dam, R. Michael; Thompson, Michael

2011-02-01

Real-time analysis of multi-channel spatio-temporal sensor data presents a considerable technical challenge for a number of applications. For example, in brain-computer interfaces, signal patterns originating on a time-dependent basis from an array of electrodes on the scalp (i.e. electroencephalography) must be analyzed in real time to recognize mental states and translate these to commands which control operations in a machine. In this paper we describe a new technique for recognition of spatio-temporal patterns based on performing online discrimination of time-resolved events through the use of correlation of phase dynamics between various channels in a multi-channel system. The algorithm extracts unique sensor signature patterns associated with each event during a training period and ranks importance of sensor pairs in order to distinguish between time-resolved stimuli to which the system may be exposed during real-time operation. We apply the algorithm to electroencephalographic signals obtained from subjects tested in the neurophysiology laboratories at the University of Toronto. The extension of this algorithm for rapid detection of patterns in other sensing applications, including chemical identification via chemical or bio-chemical sensor arrays, is also discussed.

Real-time process monitoring in a semi-continuous fluid-bed dryer - microwave resonance technology versus near-infrared spectroscopy.

PubMed

Peters, Johanna; Teske, Andreas; Taute, Wolfgang; Döscher, Claas; Höft, Michael; Knöchel, Reinhard; Breitkreutz, Jörg

2018-02-15

The trend towards continuous manufacturing in the pharmaceutical industry is associated with an increasing demand for advanced control strategies. It is a mandatory requirement to obtain reliable real-time information on critical quality attributes (CQA) during every process step as the decision on diversion of material needs to be performed fast and automatically. Where possible, production equipment should provide redundant systems for in-process control (IPC) measurements to ensure continuous process monitoring even if one of the systems is not available. In this paper, two methods for real-time monitoring of granule moisture in a semi-continuous fluid-bed drying unit are compared. While near-infrared (NIR) spectroscopy has already proven to be a suitable process analytical technology (PAT) tool for moisture measurements in fluid-bed applications, microwave resonance technology (MRT) showed difficulties to monitor moistures above 8% until recently. The results indicate, that the newly developed MRT sensor operating at four resonances is capable to compete with NIR spectroscopy. While NIR spectra were preprocessed by mean centering and first derivative before application of partial least squares (PLS) regression to build predictive models (RMSEP = 0.20%), microwave moisture values of two resonances sufficed to build a statistically close multiple linear regression (MLR) model (RMSEP = 0.07%) for moisture prediction. Thereby, it could be verified that moisture monitoring by MRT sensor systems could be a valuable alternative to NIR spectroscopy or could be used as a redundant system providing great ease of application. Copyright © 2017 Elsevier B.V. All rights reserved.

Applying Cognitive Fusion to Space Situational Awareness

NASA Astrophysics Data System (ADS)

Ingram, S.; Shaw, M.; Chan, M.

With recent increases in capability and frequency of rocket launches from countries across the world, maintaining a state-of-the-art Space Situational Awareness model is all the more necessary. We propose a fusion of real-time, natural language processing capability provided by IBM cognitive services with ground-based sensor data of positions and trajectories of satellites in all earth orbits. We believe such insight provided by cognitive services could help determine context to missile launches, help predict when a satellite of interest could be in danger, either by accident or by intent, and could alert interested parties to the perceived threat. We seek to implement an improved Space Situational Awareness model by developing a dynamic factor graph model informed by the fusion of ground-based ”structured” sensor data with ”unstructured” data from the public domain, such as news articles, blogs, and social media, in real time. To this end, we employ IBM’s Cognitive services, specifically, Watson Discovery. Watson Discovery allows real-time natural language processing of text including entity extraction, keyword search, taxonomy classification, concept tagging, relation extraction, sentiment analysis, and emotion analysis. We present various scenarios that demonstrate the utility of this new Space Situational Awareness model, each of which combine past structured information with related open source data. We demonstrate that should the model come to estimate a satellite is ”of interest”, it will indicate it as so, based on the most pertinent data, such as a reading from a sensor or by information available online. We present and discuss the most recent iterations of the model for satellites currently available on Space-Track.org.

Open Source Based Sensor Platform for Mobile Environmental Monitoring and Data Acquisition

NASA Astrophysics Data System (ADS)

Schima, Robert; Goblirsch, Tobias; Misterek, René; Salbach, Christoph; Schlink, Uwe; Francyk, Bogdan; Dietrich, Peter; Bumberger, Jan

2016-04-01

The impact of global change, urbanization and complex interactions between humans and the environment show different effects on different scales. However, the desire to obtain a better understanding of ecosystems and process dynamics in nature accentuates the need for observing these processes in higher temporal and spatial resolutions. Especially with regard to the process dynamics and heterogeneity of urban areas, a comprehensive monitoring of these effects remains to be a challenging issue. Open source based electronics and cost-effective sensors are offering a promising approach to explore new possibilities of mobile data acquisition and innovative strategies and thereby support a comprehensive ad-hoc monitoring and the capturing of environmental processes close to real time. Accordingly, our project aims the development of new strategies for mobile data acquisition and real-time processing of user-specific environmental data, based on a holistic and integrated process. To this end, the concept of our monitoring system covers the data collection, data processing and data integration as well as the data provision within one infrastructure. This ensures a consistent data stream and a rapid data processing. However, the overarching goal is the provision of an integrated service instead of lengthy and arduous data acquisition by hand. Therefore, the system also serves as a data acquisition assistant and gives guidance during the measurements. In technical terms, our monitoring system consists of mobile sensor devices, which can be controlled and managed by a smart phone app (Android). At the moment, the system is able to acquire temperature and humidity in space (GPS) and time (real-time clock) as a built in function. In addition, larger system functionality can be accomplished by adding further sensors for the detection of e.g. fine dust, methane or dissolved organic compounds. From the IT point of view, the system includes a smart phone app and a web service for data processing, data provision and data visualization. The smart phone app allows the configuration of the mobile sensor devices and provides some built-in functions such as simple data visualization or data transmission via e-mail whereas the web service provides the visualization of the data and tools for data processing. In an initial field experiment, a methane monitoring based on our sensor integration platform was performed in the city area of Leipzig (Germany) in late June 2015. The study has shown that an urban monitoring can be conducted based on open source components. Moreover, the system enabled the detection of hot spots and methane emission sources. In September 2015, a larger scaled city monitoring based on the mobile monitoring platform was performed by five independently driving cyclists through the city center of Leipzig (Germany). As a result we were able to instantly show a heat and humidity map of the inner city center as well as an exposure map for each cyclist. This emphasizes the feasibility and high potential of open source based monitoring approaches for future research in the field of urban area monitoring in general, citizen science or the validation of remote sensing data.

Sensor development in the Shuttle era. [infrared temperature sounders and microwave radiometers

NASA Technical Reports Server (NTRS)

Gerding, R. B.; Mantarakis, P. Z.; Webber, D. S.

1975-01-01

The use of the Space Shuttle in the development of earth observation sensors is examined. Two sensor classes are selected for case histories: infrared temperature sounders and microwave radiometers. The most significant finding in each of the developmental studies of these two sensor classes is considered to be the feasibility and value of using the Shuttle/Spacelab as a test vehicle for the operation in space of a versatile multimode experimental sensor. The Shuttle Electrically Scanned Microwave Radiometer and the Shuttle Infrared Interferometer are found to be the most effective instruments in this context. The Shuttle/Spacelab Sortie mission characteristics provide opportunities for new approaches to the development of sensors, using the Shuttle as a test vehicle to improve the efficiency of the process with respect to time, cost, and/or quality of the final product. As for crew functions, the short-term Spacelab mission requires some near real-time evaluation of data quality and sensor function in order to insure efficient data collection.

Strain Sensing Characteristics of Rubbery Carbon Nanotube Composite for Flexible Sensors.

PubMed

Choi, Gyong Rak; Park, Hyung-ki; Huh, Hoon; Kim, Young-Ju; Ham, Heon; Kim, Hyoun Woo; Lim, Kwon Taek; Kim, Sung Yong; Kang, Inpil

2016-02-01

In this study, the piezoresistive properties of CNT (Carbon Nanotube)/EPDM composite are characterized for the applications of a flexible sensor. The CNT/EPDM composites were prepared by using a Brabender mixer with MWCNT (Multi-walled Carbon Nanotube) and organoclay. The static and quasi-dynamic voltage output responses of the composite sensor were also experimentally studied and were compared with those of a conventional foil strain gage. The voltage output by using a signal processing system was fairly stable and it shows somehow linear responses at both of loading and unloading cases with hysteresis. The voltage output was distorted under a quasi-dynamic test due to its unsymmetrical piezoresistive characteristics. The CNT/EPDM sensor showed quite tardy response to its settling time test under static deflections and that would be a hurdle for its real time applications. Furthermore, since the CNT/EPDM sensor does not have directional voltage output to tension and compression, it only could be utilized as a mono-directional force sensor such as a compressive touch sensor.

Development of on package indicator sensor for real-time monitoring of meat quality

PubMed Central

Shukla, Vivek; Kandeepan, G.; Vishnuraj, M. R.

2015-01-01

Aim: The aim was to develop an indicator sensor for real-time monitoring of meat quality and to compare the response of indicator sensor with meat quality parameters at ambient temperature. Materials and Methods: Indicator sensor was prepared using bromophenol blue (1% w/v) as indicator solution and filter paper as indicator carrier. Indicator sensor was fabricated by coating indicator solution onto carrier by centrifugation. To observe the response of indicator sensor buffalo meat was packed in polystyrene foam trays covered with PVC film and indicator sensor was attached to the inner side of packaging film. The pattern of color change in indicator sensor was monitored and compared with meat quality parameters viz. total volatile basic nitrogen, D-glucose, standard plate count and tyrosine value to correlate ability of indicator sensor for its suitability to predict the meat quality and storage life. Results: The indicator sensor changed its color from yellow to blue starting from margins during the storage period of 24 h at ambient temperature and this correlated well with changes in meat quality parameters. Conclusions: The indicator sensor can be used for real-time monitoring of meat quality as the color of indicator sensor changed from yellow to blue starting from margins when meat deteriorates with advancement of the storage period. Thus by observing the color of indicator sensor quality of meat and shelf life can be predicted. PMID:27047103

Implementation of a Real-Time Stacking Algorithm in a Photogrammetric Digital Camera for Uavs

NASA Astrophysics Data System (ADS)

Audi, A.; Pierrot-Deseilligny, M.; Meynard, C.; Thom, C.

2017-08-01

In the recent years, unmanned aerial vehicles (UAVs) have become an interesting tool in aerial photography and photogrammetry activities. In this context, some applications (like cloudy sky surveys, narrow-spectral imagery and night-vision imagery) need a longexposure time where one of the main problems is the motion blur caused by the erratic camera movements during image acquisition. This paper describes an automatic real-time stacking algorithm which produces a high photogrammetric quality final composite image with an equivalent long-exposure time using several images acquired with short-exposure times. Our method is inspired by feature-based image registration technique. The algorithm is implemented on the light-weight IGN camera, which has an IMU sensor and a SoC/FPGA. To obtain the correct parameters for the resampling of images, the presented method accurately estimates the geometrical relation between the first and the Nth image, taking into account the internal parameters and the distortion of the camera. Features are detected in the first image by the FAST detector, than homologous points on other images are obtained by template matching aided by the IMU sensors. The SoC/FPGA in the camera is used to speed up time-consuming parts of the algorithm such as features detection and images resampling in order to achieve a real-time performance as we want to write only the resulting final image to save bandwidth on the storage device. The paper includes a detailed description of the implemented algorithm, resource usage summary, resulting processing time, resulting images, as well as block diagrams of the described architecture. The resulting stacked image obtained on real surveys doesn't seem visually impaired. Timing results demonstrate that our algorithm can be used in real-time since its processing time is less than the writing time of an image in the storage device. An interesting by-product of this algorithm is the 3D rotation estimated by a photogrammetric method between poses, which can be used to recalibrate in real-time the gyrometers of the IMU.

Real-Time Telemetry System for Monitoring Motion of Ships Based on Inertial Sensors.

PubMed

Núñez, José M; Araújo, Marta G; García-Tuñón, I

2017-04-25

A telemetry system for real-time monitoring of the motions, position, speed and course of a ship at sea is presented in this work. The system, conceived as a subsystem of a radar cross-section measurement unit, could also be used in other applications as ships dynamics characterization, on-board cranes, antenna stabilizers, etc. This system was designed to be stand-alone, reliable, easy to deploy, low-cost and free of requirements related to stabilization procedures. In order to achieve such a unique combination of functionalities, we have developed a telemetry system based on redundant inertial and magnetic sensors and GPS (Global Positioning System) measurements. It provides a proper data storage and also has real-time radio data transmission capabilities to an on-shore station. The output of the system can be used either for on-line or off-line processing. Additionally, the system uses dual technologies and COTS (Commercial Off-The-Shelf) components. Motion-positioning measurements and radio data link tests were successfully carried out in several ships of the Spanish Navy, proving the compliance with the design targets and validating our telemetry system.

A conceptual framework for intelligent real-time information processing

NASA Technical Reports Server (NTRS)

Schudy, Robert

1987-01-01

By combining artificial intelligence concepts with the human information processing model of Rasmussen, a conceptual framework was developed for real time artificial intelligence systems which provides a foundation for system organization, control and validation. The approach is based on the description of system processing terms of an abstraction hierarchy of states of knowledge. The states of knowledge are organized along one dimension which corresponds to the extent to which the concepts are expressed in terms of the system inouts or in terms of the system response. Thus organized, the useful states form a generally triangular shape with the sensors and effectors forming the lower two vertices and the full evaluated set of courses of action the apex. Within the triangle boundaries are numerous processing paths which shortcut the detailed processing, by connecting incomplete levels of analysis to partially defined responses. Shortcuts at different levels of abstraction include reflexes, sensory motor control, rule based behavior, and satisficing. This approach was used in the design of a real time tactical decision aiding system, and in defining an intelligent aiding system for transport pilots.

Real-Time Human Ambulation, Activity, and Physiological Monitoring: Taxonomy of Issues, Techniques, Applications, Challenges and Limitations

PubMed Central

Khusainov, Rinat; Azzi, Djamel; Achumba, Ifeyinwa E.; Bersch, Sebastian D.

2013-01-01

Automated methods of real-time, unobtrusive, human ambulation, activity, and wellness monitoring and data analysis using various algorithmic techniques have been subjects of intense research. The general aim is to devise effective means of addressing the demands of assisted living, rehabilitation, and clinical observation and assessment through sensor-based monitoring. The research studies have resulted in a large amount of literature. This paper presents a holistic articulation of the research studies and offers comprehensive insights along four main axes: distribution of existing studies; monitoring device framework and sensor types; data collection, processing and analysis; and applications, limitations and challenges. The aim is to present a systematic and most complete study of literature in the area in order to identify research gaps and prioritize future research directions. PMID:24072027

Real-time monitoring of human blood clotting using a lateral excited film bulk acoustic resonator

NASA Astrophysics Data System (ADS)

Chen, Da; Wang, Jingjng; Wang, Peng; Guo, Qiuquan; Zhang, Zhen; Ma, Jilong

2017-04-01

Frequent assay of hemostatic status is an essential issue for the millions of patients using anticoagulant drugs. In this paper, we presented a micro-fabricated film bulk acoustic sensor for the real-time monitoring of blood clotting and the measurement of hemostatic parameters. The device was made of an Au/ZnO/Si3N4 film stack and excited by a lateral electric field. It operated under a shear mode resonance with the frequency of 1.42 GHz and had a quality factor of 342 in human blood. During the clotting process of blood, the resonant frequency decreased along with the change of blood viscosity and showed an apparent step-ladder curve, revealing the sequential clotting stages. An important hemostatic parameter, prothrombin time, was quantitatively determined from the frequency response for different dilutions of the blood samples. The effect of a typical anticoagulant drug (heparin) on the prothrombin time was exemplarily shown. The proposed sensor displayed a good consistency and clinical comparability with the standard coagulometric methods. Thanks to the availability of direct digital signals, excellent potentials of miniaturization and integration, the proposed sensor has promising application for point-of-care coagulation technologies.

Application of Emerging Open-source Embedded Systems for Enabling Low-cost Wireless Mini-observatory Nodes in the Coastal Zone

NASA Astrophysics Data System (ADS)

Glazer, B. T.

2016-02-01

Here, we describe the development of novel, low-cost, open-source instrumentation to enable wireless data transfer of biogeochemical sensors in the coastal zone. The platform is centered upon the Beaglebone Black single board computer. Process-inquiry in environmental sciences suffers from undersampling; enabling sustained and unattended data collection typically involves expensive instrumentation and infrastructure deployed as cabled observatories with little flexibility in deployment location following initial installation. High cost of commercially-available or custom electronic packages have not only limited the number of sensor node sites that can be targeted by reasonably well-funded academic researchers, but have also entirely prohibited widespread engagement with K-12, public non-profit, and `citizen scientist' STEM audiences. The new platform under development represents a balanced blend of research-grade sensors and low-cost open-source electronics that are easily assembled. Custom, robust, open-source code that remains customizable for specific node configurations can match a specific deployment's measurement needs, depending on the scientific research priorities. We have demonstrated prototype capabilities and versatility through lab testing and field deployments of multiple sensor nodes with multiple sensor inputs, all of which are streaming near-real-time data over wireless RF links to a shore-based base station. On shore, first-pass data processing QA/QC takes place and near-real-time plots are made available on the World Wide Web. Specifically, we have worked closely with an environmental and cultural management and restoration non-profit organization, and middle and high school science classes, engaging their interest in STEM application to local watershed processes. Ultimately, continued successful development of this pilot project can lead to a coastal oceanographic analogue of the popular Weather Underground personal weather station model.

Digital phase demodulation for low-coherence interferometry-based fiber-optic sensors

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

Liu, Y.; Strum, R.; Stiles, D.

In this paper, we describe a digital phase demodulation scheme for low-coherence interferometry-based fiber-optic sensors by employing a simple generation of phase-shifted signals at the interrogation interferometer. The scheme allows a real-time calibration process and offers capability of measuring large variations (up to the coherence of the light source) at the bandwidth that is only limited by the data acquisition system. Finally, the proposed phase demodulation method is analytically derived and its validity and performance are experimentally verified using fiber-optic Fabry–Perot sensors for measurement of strains and vibrations.

Digital phase demodulation for low-coherence interferometry-based fiber-optic sensors

DOE PAGES

Liu, Y.; Strum, R.; Stiles, D.; ...

2017-11-20

In this paper, we describe a digital phase demodulation scheme for low-coherence interferometry-based fiber-optic sensors by employing a simple generation of phase-shifted signals at the interrogation interferometer. The scheme allows a real-time calibration process and offers capability of measuring large variations (up to the coherence of the light source) at the bandwidth that is only limited by the data acquisition system. Finally, the proposed phase demodulation method is analytically derived and its validity and performance are experimentally verified using fiber-optic Fabry–Perot sensors for measurement of strains and vibrations.

Real-Time Processing Library for Open-Source Hardware Biomedical Sensors

PubMed Central

Castro-García, Juan A.; Lebrato-Vázquez, Clara

2018-01-01

Applications involving data acquisition from sensors need samples at a preset frequency rate, the filtering out of noise and/or analysis of certain frequency components. We propose a novel software architecture based on open-software hardware platforms which allows programmers to create data streams from input channels and easily implement filters and frequency analysis objects. The performances of the different classes given in the size of memory allocated and execution time (number of clock cycles) were analyzed in the low-cost platform Arduino Genuino. In addition, 11 people took part in an experiment in which they had to implement several exercises and complete a usability test. Sampling rates under 250 Hz (typical for many biomedical applications) makes it feasible to implement filters, sliding windows and Fourier analysis, operating in real time. Participants rated software usability at 70.2 out of 100 and the ease of use when implementing several signal processing applications was rated at just over 4.4 out of 5. Participants showed their intention of using this software because it was percieved as useful and very easy to use. The performances of the library showed that it may be appropriate for implementing small biomedical real-time applications or for human movement monitoring, even in a simple open-source hardware device like Arduino Genuino. The general perception about this library is that it is easy to use and intuitive. PMID:29596394

Posture and activity recognition and energy expenditure estimation in a wearable platform.

PubMed

Sazonov, Edward; Hegde, Nagaraj; Browning, Raymond C; Melanson, Edward L; Sazonova, Nadezhda A

2015-07-01

The use of wearable sensors coupled with the processing power of mobile phones may be an attractive way to provide real-time feedback about physical activity and energy expenditure (EE). Here, we describe the use of a shoe-based wearable sensor system (SmartShoe) with a mobile phone for real-time recognition of various postures/physical activities and the resulting EE. To deal with processing power and memory limitations of the phone, we compare the use of support vector machines (SVM), multinomial logistic discrimination (MLD), and multilayer perceptrons (MLP) for posture and activity classification followed by activity-branched EE estimation. The algorithms were validated using data from 15 subjects who performed up to 15 different activities of daily living during a 4-h stay in a room calorimeter. MLD and MLP demonstrated activity classification accuracy virtually identical to SVM (∼ 95%) while reducing the running time and the memory requirements by a factor of >10 3. Comparison of per-minute EE estimation using activity-branched models resulted in accurate EE prediction (RMSE = 0.78 kcal/min for SVM and MLD activity classification, 0.77 kcal/min for MLP versus RMSE of 0.75 kcal/min for manual annotation). These results suggest that low-power computational algorithms can be successfully used for real-time physical activity monitoring and EE estimation on a wearable platform.

Real-Time Processing Library for Open-Source Hardware Biomedical Sensors.

PubMed

Molina-Cantero, Alberto J; Castro-García, Juan A; Lebrato-Vázquez, Clara; Gómez-González, Isabel M; Merino-Monge, Manuel

2018-03-29

Applications involving data acquisition from sensors need samples at a preset frequency rate, the filtering out of noise and/or analysis of certain frequency components. We propose a novel software architecture based on open-software hardware platforms which allows programmers to create data streams from input channels and easily implement filters and frequency analysis objects. The performances of the different classes given in the size of memory allocated and execution time (number of clock cycles) were analyzed in the low-cost platform Arduino Genuino. In addition, 11 people took part in an experiment in which they had to implement several exercises and complete a usability test. Sampling rates under 250 Hz (typical for many biomedical applications) makes it feasible to implement filters, sliding windows and Fourier analysis, operating in real time. Participants rated software usability at 70.2 out of 100 and the ease of use when implementing several signal processing applications was rated at just over 4.4 out of 5. Participants showed their intention of using this software because it was percieved as useful and very easy to use. The performances of the library showed that it may be appropriate for implementing small biomedical real-time applications or for human movement monitoring, even in a simple open-source hardware device like Arduino Genuino. The general perception about this library is that it is easy to use and intuitive.

Opportunities and challenges of real-time release testing in biopharmaceutical manufacturing.

PubMed

Jiang, Mo; Severson, Kristen A; Love, John Christopher; Madden, Helena; Swann, Patrick; Zang, Li; Braatz, Richard D

2017-11-01

Real-time release testing (RTRT) is defined as "the ability to evaluate and ensure the quality of in-process and/or final drug product based on process data, which typically includes a valid combination of measured material attributes and process controls" (ICH Q8[R2]). This article discusses sensors (process analytical technology, PAT) and control strategies that enable RTRT for the spectrum of critical quality attributes (CQAs) in biopharmaceutical manufacturing. Case studies from the small-molecule and biologic pharmaceutical industry are described to demonstrate how RTRT can be facilitated by integrated manufacturing and multivariable control strategies to ensure the quality of products. RTRT can enable increased assurance of product safety, efficacy, and quality-with improved productivity including faster release and potentially decreased costs-all of which improve the value to patients. To implement a complete RTRT solution, biologic drug manufacturers need to consider the special attributes of their industry, particularly sterility and the measurement of viral and microbial contamination. Continued advances in on-line and in-line sensor technologies are key for the biopharmaceutical manufacturing industry to achieve the potential of RTRT. Related article: http://onlinelibrary.wiley.com/doi/10.1002/bit.26378/full. © 2017 Wiley Periodicals, Inc.

Real Time Monitoring System of Pollution Waste on Musi River Using Support Vector Machine (SVM) Method

NASA Astrophysics Data System (ADS)

Fachrurrozi, Muhammad; Saparudin; Erwin

2017-04-01

Real-time Monitoring and early detection system which measures the quality standard of waste in Musi River, Palembang, Indonesia is a system for determining air and water pollution level. This system was designed in order to create an integrated monitoring system and provide real time information that can be read. It is designed to measure acidity and water turbidity polluted by industrial waste, as well as to show and provide conditional data integrated in one system. This system consists of inputting and processing the data, and giving output based on processed data. Turbidity, substances, and pH sensor is used as a detector that produce analog electrical direct current voltage (DC). Early detection system works by determining the value of the ammonia threshold, acidity, and turbidity level of water in Musi River. The results is then presented based on the level group pollution by the Support Vector Machine classification method.

Concepts and Development of Bio-Inspired Distributed Embedded Wired/Wireless Sensor Array Architectures for Acoustic Wave Sensing in Integrated Aerospace Vehicles

NASA Technical Reports Server (NTRS)

Ghoshal, Anindya; Prosser, William H.; Kirikera, Goutham; Schulz, Mark J.; Hughes, Derke J.; Orisamolu, Wally

2003-01-01

This paper discusses the modeling of acoustic emissions in plate structures and their sensing by embedded or surface bonded piezoelectric sensor arrays. Three different modeling efforts for acoustic emission (AE) wave generation and propagation are discussed briefly along with their advantages and disadvantages. Continuous sensors placed at right angles on a plate are being discussed as a new approach to measure and locate the source of acoustic waves. Evolutionary novel signal processing algorithms and bio-inspired distributed sensor array systems are used on large structures and integrated aerospace vehicles for AE source localization and preliminary results are presented. These systems allow for a great reduction in the amount of data that needs to be processed and also reduce the chances of false alarms from ambient noises. It is envisioned that these biomimetic sensor arrays and signal processing techniques will be useful for both wireless and wired sensor arrays for real time health monitoring of large integrated aerospace vehicles and earth fixed civil structures. The sensor array architectures can also be used with other types of sensors and for other applications.

Application of a distributed systems architecture for increased speed in image processing on an autonomous ground vehicle

NASA Astrophysics Data System (ADS)

Wright, Adam A.; Momin, Orko; Shin, Young Ho; Shakya, Rahul; Nepal, Kumud; Ahlgren, David J.

2010-01-01

This paper presents the application of a distributed systems architecture to an autonomous ground vehicle, Q, that participates in both the autonomous and navigation challenges of the Intelligent Ground Vehicle Competition. In the autonomous challenge the vehicle is required to follow a course, while avoiding obstacles and staying within the course boundaries, which are marked by white lines. For the navigation challenge, the vehicle is required to reach a set of target destinations, known as way points, with given GPS coordinates and avoid obstacles that it encounters in the process. Previously the vehicle utilized a single laptop to execute all processing activities including image processing, sensor interfacing and data processing, path planning and navigation algorithms and motor control. National Instruments' (NI) LabVIEW served as the programming language for software implementation. As an upgrade to last year's design, a NI compact Reconfigurable Input/Output system (cRIO) was incorporated to the system architecture. The cRIO is NI's solution for rapid prototyping that is equipped with a real time processor, an FPGA and modular input/output. Under the current system, the real time processor handles the path planning and navigation algorithms, the FPGA gathers and processes sensor data. This setup leaves the laptop to focus on running the image processing algorithm. Image processing as previously presented by Nepal et. al. is a multi-step line extraction algorithm and constitutes the largest processor load. This distributed approach results in a faster image processing algorithm which was previously Q's bottleneck. Additionally, the path planning and navigation algorithms are executed more reliably on the real time processor due to the deterministic nature of operation. The implementation of this architecture required exploration of various inter-system communication techniques. Data transfer between the laptop and the real time processor using UDP packets was established as the most reliable protocol after testing various options. Improvement can be made to the system by migrating more algorithms to the hardware based FPGA to further speed up the operations of the vehicle.

A real-time simulation evaluation of an advanced detection. Isolation and accommodation algorithm for sensor failures in turbine engines

NASA Technical Reports Server (NTRS)

Merrill, W. C.; Delaat, J. C.

1986-01-01

An advanced sensor failure detection, isolation, and accommodation (ADIA) algorithm has been developed for use with an aircraft turbofan engine control system. In a previous paper the authors described the ADIA algorithm and its real-time implementation. Subsequent improvements made to the algorithm and implementation are discussed, and the results of an evaluation presented. The evaluation used a real-time, hybrid computer simulation of an F100 turbofan engine.

Virtual sensor models for real-time applications

NASA Astrophysics Data System (ADS)

Hirsenkorn, Nils; Hanke, Timo; Rauch, Andreas; Dehlink, Bernhard; Rasshofer, Ralph; Biebl, Erwin

2016-09-01

Increased complexity and severity of future driver assistance systems demand extensive testing and validation. As supplement to road tests, driving simulations offer various benefits. For driver assistance functions the perception of the sensors is crucial. Therefore, sensors also have to be modeled. In this contribution, a statistical data-driven sensor-model, is described. The state-space based method is capable of modeling various types behavior. In this contribution, the modeling of the position estimation of an automotive radar system, including autocorrelations, is presented. For rendering real-time capability, an efficient implementation is presented.

Smart packaging for the monitoring of fish freshness

NASA Astrophysics Data System (ADS)

Pacquit, Alexis; Lau, King Tong; Diamond, Dermot

2005-06-01

The development of chromo-reactive sensor spots for real time monitoring of fish freshness is described. The on-package sensor spots incorporating an immobilized pH sensitive dye, respond through visible colour change to basic volatile spoilage compounds collectively known as Total Volatile Basic Nitrogen (TVB-N). Trials on fresh fish filets have verified that the sensor can be employed for real time monitoring of fish spoilage. The sensor response can be interrogated with a simple, inexpensive reflectance colorimeter that we have developed based on two LEDs and a photodetector.

Application of Odor Sensors to Ore Sorting and Mill Feed Control

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

Michael G. Nelson

2005-08-01

Control of the feed provided to mineral processing facilities is a continuing challenge. Much effort is currently being devoted to overcoming these problems. These projects are usually described under the general headings of Mine-to-Mill Integration or Mine-Mill Optimization. It should be possible to combine the knowledge of ore type, mineralogy, and other characteristics (located in the mine modeling system), with the advanced capabilities of state-of-the-art mill control systems, to achieve an improved level of control in mineral processing that will allow optimization of the mill processes on an almost real-time basis. This is not happening because mill feed it ismore » often treated as a uniform material, when in reality it varies in composition and characteristics. An investigation was conducted to assess the suitability of odor sensors for maintaining traceability in ore production and processing. Commercially available sensors are now used in food processing, environmental monitoring, and other applications and can detect the presence of very small amounts (0.1-500 ppm) of some molecules. An assortment of such molecules could be used to ''tag'' blocks of ore as they are mined, according to their respective characteristics. Then, as the ore came into the mill, an array of ''electronic noses'' could be used to assess its characteristics in real time. It was found that the Cyranose 320{trademark}, a commercially available odor sensor, can easily distinguish among samples of rock marked with almond, cinnamon, citronella, lemon, and orange oils. Further, the sensor could detect mixtures of rocks marked with various combinations of these oils. Treatment of mixtures of galena and silica with odorant compounds showed no detrimental effects on flotation response in laboratory tests. Additional work is recommended to determine how this concept can be extended to the marking of large volumes of materials.« less

Geosensors to Support Crop Production: Current Applications and User Requirements

PubMed Central

Thessler, Sirpa; Kooistra, Lammert; Teye, Frederick; Huitu, Hanna; Bregt, Arnold K.

2011-01-01

Sensor technology, which benefits from high temporal measuring resolution, real-time data transfer and high spatial resolution of sensor data that shows in-field variations, has the potential to provide added value for crop production. The present paper explores how sensors and sensor networks have been utilised in the crop production process and what their added-value and the main bottlenecks are from the perspective of users. The focus is on sensor based applications and on requirements that users pose for them. Literature and two use cases were reviewed and applications were classified according to the crop production process: sensing of growth conditions, fertilising, irrigation, plant protection, harvesting and fleet control. The potential of sensor technology was widely acknowledged along the crop production chain. Users of the sensors require easy-to-use and reliable applications that are actionable in crop production at reasonable costs. The challenges are to develop sensor technology, data interoperability and management tools as well as data and measurement services in a way that requirements can be met, and potential benefits and added value can be realized in the farms in terms of higher yields, improved quality of yields, decreased input costs and production risks, and less work time and load. PMID:22163978

Dynamic Beam Solutions for Real-Time Simulation and Control Development of Flexible Rockets

NASA Technical Reports Server (NTRS)

Su, Weihua; King, Cecilia K.; Clark, Scott R.; Griffin, Edwin D.; Suhey, Jeffrey D.; Wolf, Michael G.

2016-01-01

In this study, flexible rockets are structurally represented by linear beams. Both direct and indirect solutions of beam dynamic equations are sought to facilitate real-time simulation and control development for flexible rockets. The direct solution is completed by numerically integrate the beam structural dynamic equation using an explicit Newmark-based scheme, which allows for stable and fast transient solutions to the dynamics of flexile rockets. Furthermore, in the real-time operation, the bending strain of the beam is measured by fiber optical sensors (FOS) at intermittent locations along the span, while both angular velocity and translational acceleration are measured at a single point by the inertial measurement unit (IMU). Another study in this paper is to find the analytical and numerical solutions of the beam dynamics based on the limited measurement data to facilitate the real-time control development. Numerical studies demonstrate the accuracy of these real-time solutions to the beam dynamics. Such analytical and numerical solutions, when integrated with data processing and control algorithms and mechanisms, have the potential to increase launch availability by processing flight data into the flexible launch vehicle's control system.

Data Analytics for Smart Parking Applications.

PubMed

Piovesan, Nicola; Turi, Leo; Toigo, Enrico; Martinez, Borja; Rossi, Michele

2016-09-23

We consider real-life smart parking systems where parking lot occupancy data are collected from field sensor devices and sent to backend servers for further processing and usage for applications. Our objective is to make these data useful to end users, such as parking managers, and, ultimately, to citizens. To this end, we concoct and validate an automated classification algorithm having two objectives: (1) outlier detection: to detect sensors with anomalous behavioral patterns, i.e., outliers; and (2) clustering: to group the parking sensors exhibiting similar patterns into distinct clusters. We first analyze the statistics of real parking data, obtaining suitable simulation models for parking traces. We then consider a simple classification algorithm based on the empirical complementary distribution function of occupancy times and show its limitations. Hence, we design a more sophisticated algorithm exploiting unsupervised learning techniques (self-organizing maps). These are tuned following a supervised approach using our trace generator and are compared against other clustering schemes, namely expectation maximization, k-means clustering and DBSCAN, considering six months of data from a real sensor deployment. Our approach is found to be superior in terms of classification accuracy, while also being capable of identifying all of the outliers in the dataset.

Data Analytics for Smart Parking Applications

PubMed Central

Piovesan, Nicola; Turi, Leo; Toigo, Enrico; Martinez, Borja; Rossi, Michele

2016-01-01

We consider real-life smart parking systems where parking lot occupancy data are collected from field sensor devices and sent to backend servers for further processing and usage for applications. Our objective is to make these data useful to end users, such as parking managers, and, ultimately, to citizens. To this end, we concoct and validate an automated classification algorithm having two objectives: (1) outlier detection: to detect sensors with anomalous behavioral patterns, i.e., outliers; and (2) clustering: to group the parking sensors exhibiting similar patterns into distinct clusters. We first analyze the statistics of real parking data, obtaining suitable simulation models for parking traces. We then consider a simple classification algorithm based on the empirical complementary distribution function of occupancy times and show its limitations. Hence, we design a more sophisticated algorithm exploiting unsupervised learning techniques (self-organizing maps). These are tuned following a supervised approach using our trace generator and are compared against other clustering schemes, namely expectation maximization, k-means clustering and DBSCAN, considering six months of data from a real sensor deployment. Our approach is found to be superior in terms of classification accuracy, while also being capable of identifying all of the outliers in the dataset. PMID:27669259

Broadband spectroscopic sensor for real-time monitoring of industrial SO(2) emissions.

PubMed

Xu, Feng; Zhang, Yungang; Somesfalean, Gabriel; Wang, Huashan; Wu, Shaohua; Zhang, Zhiguo

2007-05-01

A spectroscopic system for continuous real-time monitoring of SO(2) concentrations in industrial emissions was developed. The sensor is well suited for field applications due to simple and compact instrumental design, and robust data evaluation based on ultraviolet broadband absorption without the use of any calibration cell. The sensor has a detection limit of 1 ppm, and was employed both for gas-flow simulations with and without suspended particles, and for in situ measurement of SO(2) concentrations in the flue gas emitted from an industrial coal-fired boiler. The price/performance ratio of the instrument is expected to be superior to other comparable real-time monitoring systems.

Wearable physiological sensors and real-time algorithms for detection of acute mountain sickness.

PubMed

Muza, Stephen R

2018-03-01

This is a minireview of potential wearable physiological sensors and algorithms (process and equations) for detection of acute mountain sickness (AMS). Given the emerging status of this effort, the focus of the review is on the current clinical assessment of AMS, known risk factors (environmental, demographic, and physiological), and current understanding of AMS pathophysiology. Studies that have examined a range of physiological variables to develop AMS prediction and/or detection algorithms are reviewed to provide insight and potential technological roadmaps for future development of real-time physiological sensors and algorithms to detect AMS. Given the lack of signs and nonspecific symptoms associated with AMS, development of wearable physiological sensors and embedded algorithms to predict in the near term or detect established AMS will be challenging. Prior work using [Formula: see text], HR, or HRv has not provided the sensitivity and specificity for useful application to predict or detect AMS. Rather than using spot checks as most prior studies have, wearable systems that continuously measure SpO 2 and HR are commercially available. Employing other statistical modeling approaches such as general linear and logistic mixed models or time series analysis to these continuously measured variables is the most promising approach for developing algorithms that are sensitive and specific for physiological prediction or detection of AMS.

Single-shot and single-sensor high/super-resolution microwave imaging based on metasurface

PubMed Central

Wang, Libo; Li, Lianlin; Li, Yunbo; Zhang, Hao Chi; Cui, Tie Jun

2016-01-01

Real-time high-resolution (including super-resolution) imaging with low-cost hardware is a long sought-after goal in various imaging applications. Here, we propose broadband single-shot and single-sensor high-/super-resolution imaging by using a spatio-temporal dispersive metasurface and an imaging reconstruction algorithm. The metasurface with spatio-temporal dispersive property ensures the feasibility of the single-shot and single-sensor imager for super- and high-resolution imaging, since it can convert efficiently the detailed spatial information of the probed object into one-dimensional time- or frequency-dependent signal acquired by a single sensor fixed in the far-field region. The imaging quality can be improved by applying a feature-enhanced reconstruction algorithm in post-processing, and the desired imaging resolution is related to the distance between the object and metasurface. When the object is placed in the vicinity of the metasurface, the super-resolution imaging can be realized. The proposed imaging methodology provides a unique means to perform real-time data acquisition, high-/super-resolution images without employing expensive hardware (e.g. mechanical scanner, antenna array, etc.). We expect that this methodology could make potential breakthroughs in the areas of microwave, terahertz, optical, and even ultrasound imaging. PMID:27246668

Optical fiber sensors for breathing diagnostics

NASA Astrophysics Data System (ADS)

Chen, Q.; Claus, Richard O.; Mecham, Jeffrey B.; Vercellino, M.; Arregui, Francisco J.; Matias, Ignacio R.

2002-03-01

We report the application of an optical fiber-based humidity sensor to the problem of breathing diagnostics. The sensor is fabricated by molecularly self-assembling selected polymers and functionalized inorganic nanoclusters into multilayered optical thin films on the cleaved and polished flat end of a singlemode optical fiber. Prior work has studied the synthesis process and the fundamental mechanisms responsible for the change in optical reflection from the film that occurs as a function of humidity. We will briefly review that prior work as a way to introduce more recent developments. This paper will then discuss the application of these sensors to the analysis of air flow. We have designed the sensor thin film materials for the detection of relative humidity over a wide range, from approximately 10 to 95%, and for response times as short as several tens of milliseconds. This very fast response time allows the near real-time analysis of air flow and humidity during a single breath, with the advantage of very small size.

Human-computer interface glove using flexible piezoelectric sensors

NASA Astrophysics Data System (ADS)

Cha, Youngsu; Seo, Jeonggyu; Kim, Jun-Sik; Park, Jung-Min

2017-05-01

In this note, we propose a human-computer interface glove based on flexible piezoelectric sensors. We select polyvinylidene fluoride as the piezoelectric material for the sensors because of advantages such as a steady piezoelectric characteristic and good flexibility. The sensors are installed in a fabric glove by means of pockets and Velcro bands. We detect changes in the angles of the finger joints from the outputs of the sensors, and use them for controlling a virtual hand that is utilized in virtual object manipulation. To assess the sensing ability of the piezoelectric sensors, we compare the processed angles from the sensor outputs with the real angles from a camera recoding. With good agreement between the processed and real angles, we successfully demonstrate the user interaction system with the virtual hand and interface glove based on the flexible piezoelectric sensors, for four hand motions: fist clenching, pinching, touching, and grasping.

Real-World Neuroimaging Technologies

DTIC Science & Technology

2013-05-10

system enables long-term wear of up to 10 consecutive hours of operation time. The system’s wireless technologies, light weight (200g), and dry sensor ...biomarkers, body sensor networks , brain computer interactionbrain, computer interfaces, data acquisition, electroencephalography monitoring, translational...brain activity in real-world scenarios. INDEX TERMS Behavioral science, biomarkers, body sensor networks , brain computer interfaces, brain computer

A Framework for Integration of IVHM Technologies for Intelligent Integration for Vehicle Management

NASA Technical Reports Server (NTRS)

Paris, Deidre E.; Trevino, Luis; Watson, Mike

2005-01-01

As a part of the overall goal of developing Integrated Vehicle Health Management (IVHM) systems for aerospace vehicles, the NASA Faculty Fellowship Program (NFFP) at Marshall Space Flight Center has performed a pilot study on IVHM principals which integrates researched IVHM technologies in support of Integrated Intelligent Vehicle Management (IIVM). IVHM is the process of assessing, preserving, and restoring system functionality across flight and ground systems (NASA NGLT 2004). The framework presented in this paper integrates advanced computational techniques with sensor and communication technologies for spacecraft that can generate responses through detection, diagnosis, reasoning, and adapt to system faults in support of IIVM. These real-time responses allow the IIVM to modify the effected vehicle subsystem(s) prior to a catastrophic event. Furthermore, the objective of this pilot program is to develop and integrate technologies which can provide a continuous, intelligent, and adaptive health state of a vehicle and use this information to improve safety and reduce costs of operations. Recent investments in avionics, health management, and controls have been directed towards IIVM. As this concept has matured, it has become clear the IIVM requires the same sensors and processing capabilities as the real-time avionics functions to support diagnosis of subsystem problems. New sensors have been proposed, in addition, to augment the avionics sensors to support better system monitoring and diagnostics. As the designs have been considered, a synergy has been realized where the real-time avionics can utilize sensors proposed for diagnostics and prognostics to make better real-time decisions in response to detected failures. IIVM provides for a single system allowing modularity of functions and hardware across the vehicle. The framework that supports IIVM consists of 11 major on-board functions necessary to fully manage a space vehicle maintaining crew safety and mission objectives: Guidance and Navigation; Communications and Tracking; Vehicle Monitoring; Information Transport and Integration; Vehicle Diagnostics; Vehicle Prognostics; Vehicle mission Planning; Automated Repair and Replacement; Vehicle Control; Human Computer Interface; and Onboard Verification and Validation. Furthermore, the presented framework provides complete vehicle management which not only allows for increased crew safety and mission success through new intelligence capabilities, but also yields a mechanism for more efficient vehicle operations. The representative IVHM technologies for IIVH includes: 1) robust controllers for use in re-usable launch vehicles, 2) scaleable/flexible computer platform using heterogeneous communication, 3) coupled electromagnetic oscillators for enhanced communications, 4) Linux-based real-time systems, 5) genetic algorithms, 6) Bayesian Networks, 7) evolutionary algorithms, 8) dynamic systems control modeling, and 9) advanced sensing capabilities. This paper presents IVHM technologies developed under NASA's NFFP pilot project. The integration of these IVHM technologies forms the framework for IIVM.

Pervasive sensing

NASA Astrophysics Data System (ADS)

Nagel, David J.

2000-11-01

The coordinated exploitation of modern communication, micro- sensor and computer technologies makes it possible to give global reach to our senses. Web-cameras for vision, web- microphones for hearing and web-'noses' for smelling, plus the abilities to sense many factors we cannot ordinarily perceive, are either available or will be soon. Applications include (1) determination of weather and environmental conditions on dense grids or over large areas, (2) monitoring of energy usage in buildings, (3) sensing the condition of hardware in electrical power distribution and information systems, (4) improving process control and other manufacturing, (5) development of intelligent terrestrial, marine, aeronautical and space transportation systems, (6) managing the continuum of routine security monitoring, diverse crises and military actions, and (7) medicine, notably the monitoring of the physiology and living conditions of individuals. Some of the emerging capabilities, such as the ability to measure remotely the conditions inside of people in real time, raise interesting social concerns centered on privacy issues. Methods for sensor data fusion and designs for human-computer interfaces are both crucial for the full realization of the potential of pervasive sensing. Computer-generated virtual reality, augmented with real-time sensor data, should be an effective means for presenting information from distributed sensors.

Radio frequency switching network: a technique for infrared sensing

NASA Astrophysics Data System (ADS)

Mechtel, Deborah M.; Jenkins, R. Brian; Joyce, Peter J.; Nelson, Charles L.

2016-10-01

This paper describes a unique technique that implements photoconductive sensors in a radio frequency (RF) switching network designed to locate in real-time the position and intensity of IR radiation incident on a composite structure. In the implementation described here, photoconductive sensors act as rapid response switches in a two-layer RF network embedded in an FR-4 laminate. To detect radiation, phosphorous-doped silicon photoconductive sensors are inserted in GHz range RF transmission lines. By permitting signal propagation only when a sensor is illuminated, the RF signals are selectively routed from lower layer transmission lines to upper layer lines, thereby pinpointing the location and strength of incident radiation. Simulations based on a high frequency three-dimensional planar electromagnetics model are presented and compared to the experimental results. The experimental results are described for GHz range RF signal control for 300- and 180-mW incident energy from 975- to 1060-nm wavelength lasers, respectively, where upon illumination, RF transmission line signal output power doubled when compared to nonilluminated results. The experimental results are also reported for 100-W incident energy from a 1060-nm laser. Test results illustrate real-time signal processing would permit a structure to be controlled in response to incident radiation.

A Fast and On-Machine Measuring System Using the Laser Displacement Sensor for the Contour Parameters of the Drill Pipe Thread.

PubMed

Dong, Zhixu; Sun, Xingwei; Chen, Changzheng; Sun, Mengnan

2018-04-13

The inconvenient loading and unloading of a long and heavy drill pipe gives rise to the difficulty in measuring the contour parameters of its threads at both ends. To solve this problem, in this paper we take the SCK230 drill pipe thread-repairing machine tool as a carrier to design and achieve a fast and on-machine measuring system based on a laser probe. This system drives a laser displacement sensor to acquire the contour data of a certain axial section of the thread by using the servo function of a CNC machine tool. To correct the sensor's measurement errors caused by the measuring point inclination angle, an inclination error model is built to compensate data in real time. To better suppress random error interference and ensure real contour information, a new wavelet threshold function is proposed to process data through the wavelet threshold denoising. Discrete data after denoising is segmented according to the geometrical characteristics of the drill pipe thread, and the regression model of the contour data in each section is fitted by using the method of weighted total least squares (WTLS). Then, the thread parameters are calculated in real time to judge the processing quality. Inclination error experiments show that the proposed compensation model is accurate and effective, and it can improve the data acquisition accuracy of a sensor. Simulation results indicate that the improved threshold function is of better continuity and self-adaptability, which makes sure that denoising effects are guaranteed, and, meanwhile, the complete elimination of real data distorted in random errors is avoided. Additionally, NC50 thread-testing experiments show that the proposed on-machine measuring system can complete the measurement of a 25 mm thread in 7.8 s, with a measurement accuracy of ±8 μm and repeatability limit ≤ 4 μm (high repeatability), and hence the accuracy and efficiency of measurement are both improved.

Enhanced Self Tuning On-Board Real-Time Model (eSTORM) for Aircraft Engine Performance Health Tracking

NASA Technical Reports Server (NTRS)

Volponi, Al; Simon, Donald L. (Technical Monitor)

2008-01-01

A key technological concept for producing reliable engine diagnostics and prognostics exploits the benefits of fusing sensor data, information, and/or processing algorithms. This report describes the development of a hybrid engine model for a propulsion gas turbine engine, which is the result of fusing two diverse modeling methodologies: a physics-based model approach and an empirical model approach. The report describes the process and methods involved in deriving and implementing a hybrid model configuration for a commercial turbofan engine. Among the intended uses for such a model is to enable real-time, on-board tracking of engine module performance changes and engine parameter synthesis for fault detection and accommodation.

Sulfophenyl-Functionalized Reduced Graphene Oxide Networks on Electrospun 3D Scaffold for Ultrasensitive NO₂ Gas Sensor.

PubMed

Zou, Bin; Guo, Yunlong; Shen, Nannan; Xiao, Anshan; Li, Mingjun; Zhu, Liang; Wan, Pengbo; Sun, Xiaoming

2017-12-19

Ultrasensitive room temperature real-time NO₂ sensors are highly desirable due to potential threats on environmental security and personal respiratory. Traditional NO₂ gas sensors with highly operated temperatures (200-600 °C) and limited reversibility are mainly constructed from semiconducting oxide-deposited ceramic tubes or inter-finger probes. Herein, we report the functionalized graphene network film sensors assembled on an electrospun three-dimensional (3D) nanonetwork skeleton for ultrasensitive NO₂ sensing. The functional 3D scaffold was prepared by electrospinning interconnected polyacrylonitrile (PAN) nanofibers onto a nylon window screen to provide a 3D nanonetwork skeleton. Then, the sulfophenyl-functionalized reduced graphene oxide (SFRGO) was assembled on the electrospun 3D nanonetwork skeleton to form SFRGO network films. The assembled functionalized graphene network film sensors exhibit excellent NO₂ sensing performance (10 ppb to 20 ppm) at room temperature, reliable reversibility, good selectivity, and better sensing cycle stability. These improvements can be ascribed to the functionalization of graphene with electron-withdrawing sulfophenyl groups, the high surface-to-volume ratio, and the effective sensing channels from SFRGO wrapping onto the interconnected 3D scaffold. The SFRGO network-sensing film has the advantages of simple preparation, low cost, good processability, and ultrasensitive NO₂ sensing, all advantages that can be utilized for potential integration into smart windows and wearable electronic devices for real-time household gas sensors.

Supervised autonomous rendezvous and docking system technology evaluation

NASA Technical Reports Server (NTRS)

Marzwell, Neville I.

1991-01-01

Technology for manned space flight is mature and has an extensive history of the use of man-in-the-loop rendezvous and docking, but there is no history of automated rendezvous and docking. Sensors exist that can operate in the space environment. The Shuttle radar can be used for ranges down to 30 meters, Japan and France are developing laser rangers, and considerable work is going on in the U.S. However, there is a need to validate a flight qualified sensor for the range of 30 meters to contact. The number of targets and illumination patterns should be minimized to reduce operation constraints with one or more sensors integrated into a robust system for autonomous operation. To achieve system redundancy, it is worthwhile to follow a parallel development of qualifying and extending the range of the 0-12 meter MSFC sensor and to simultaneously qualify the 0-30(+) meter JPL laser ranging system as an additional sensor with overlapping capabilities. Such an approach offers a redundant sensor suite for autonomous rendezvous and docking. The development should include the optimization of integrated sensory systems, packaging, mission envelopes, and computer image processing to mimic brain perception and real-time response. The benefits of the Global Positioning System in providing real-time positioning data of high accuracy must be incorporated into the design. The use of GPS-derived attitude data should be investigated further and validated.

Collaborative Estimation in Distributed Sensor Networks

ERIC Educational Resources Information Center

Kar, Swarnendu

2013-01-01

Networks of smart ultra-portable devices are already indispensable in our lives, augmenting our senses and connecting our lives through real time processing and communication of sensory (e.g., audio, video, location) inputs. Though usually hidden from the user's sight, the engineering of these devices involves fierce tradeoffs between energy…

Landslide monitoring using Geocubes, a wireless network of low-cost GPS receivers

NASA Astrophysics Data System (ADS)

Benoit, Lionel; Thom, Christian; Martin, Olivier

2013-04-01

Many geophysical structures such as landslides, glaciers or even volcanoes are features characterized by small extend area and deformation rate in the order of 1 to 10cm per day. Their study needs ever more accurate positioning data with an increased space and time resolution. Using an ublox LEA-6T GPS receiver, the French national mapping agency IGN developed its own wireless multi-sensor geo-monitoring system named Geocube. The basic device is equipped with a GPS and a wireless communication media and can be completed with various sensor modules such as meteorological sensors, ground humidity and pressure or seismograph. Due to the low cost of each receiver, spatial dense surveying networks are deployed. Data are then continuously collected and transmitted to a processing computer in real-time as well as saved in situ on a Micro-SD card. Among them, raw GPS carrier phase data give access to real-time accurate relative positioning on all mesh nodes if small baselines are used. In order to achieve a high accuracy, a dedicated GPS data processing method based on a Kalman filter is proposed. It allows an epoch by epoch positioning providing a high time resolution. Special attention is paid on two points : adaptation to wireless networks of low-cost GPS and real-time ability. A first test of Geocubes usability under field conditions was carried out during summer 2012. A fifteen receivers network was deployed on the landslide of Super-Sauze (French Alps) for a two months trial. The experimental area, the deployed network and the acquisition protocol are presented. Position time series with a 30 seconds sampling rate are then derived from raw data for 10 mobile receivers on a forty days session. A sub-centimetric accuracy on an epoch by epoch positioning is reached despite difficult field conditions due to a 40° elevation mask in the south direction. Then, the measured deformations are compared with in situ rainfall measurements collected by a dedicated sensor added to a Geocube on a network's node.

Landslide monitoring using Geocubes, a wireless network of low-cost GPS receivers.

NASA Astrophysics Data System (ADS)

Benoit, Lionel; Thom, Christian; Martin, Olivier

2013-04-01

Many geophysical structures such as landslides, glaciers or even volcanoes are features characterized by small extend area and deformation rate in the order of 1 to 10cm per day. Their study needs ever more accurate positioning data with an increased space and time resolution. Using an Ublox LEA-6T GPS receiver, the French national mapping agency IGN developed its own wireless multi-sensor geo-monitoring system named Geocube. The basic device is equipped with a GPS and a wireless communication media and can be completed with various sensor modules such as meteorological sensors, ground humidity and pressure or seismograph. Due to the low cost of each receiver, spatial dense surveying networks are deployed. Data are then continuously collected and transmitted to a processing computer in real-time as well as saved in situ on a Micro-SD card. Among them, raw GPS carrier phase data give access to real-time accurate relative positioning on all mesh nodes if small baselines are used. In order to achieve a high accuracy, a dedicated GPS data processing method based on a Kalman filter is proposed. It allows an epoch by epoch positioning providing a high time resolution. Special attention is paid on two points : adaptation to wireless networks of low-cost GPS and real-time ability. A first test of Geocubes usability under field conditions was carried out during summer 2012. A fifteen receivers network was deployed on the landslide of Super-Sauze (French Alps) for a two months trial. The experimental area, the deployed network and the acquisition protocol are presented. Position time series with a 30 seconds sampling rate are then derived from raw data for 10 mobile receivers on a forty days session. A sub-centimetric accuracy on an epoch by epoch positioning is reached despite difficult field conditions due to a 40° elevation mask in the south direction. Then, the measured deformations are compared with in situ rainfall measurements collected by a dedicated sensor added to a Geocube on a network's node.

Real-Time QoS Routing Protocols in Wireless Multimedia Sensor Networks: Study and Analysis.

PubMed

Alanazi, Adwan; Elleithy, Khaled

2015-09-02

Many routing protocols have been proposed for wireless sensor networks. These routing protocols are almost always based on energy efficiency. However, recent advances in complementary metal-oxide semiconductor (CMOS) cameras and small microphones have led to the development of Wireless Multimedia Sensor Networks (WMSN) as a class of wireless sensor networks which pose additional challenges. The transmission of imaging and video data needs routing protocols with both energy efficiency and Quality of Service (QoS) characteristics in order to guarantee the efficient use of the sensor nodes and effective access to the collected data. Also, with integration of real time applications in Wireless Senor Networks (WSNs), the use of QoS routing protocols is not only becoming a significant topic, but is also gaining the attention of researchers. In designing an efficient QoS routing protocol, the reliability and guarantee of end-to-end delay are critical events while conserving energy. Thus, considerable research has been focused on designing energy efficient and robust QoS routing protocols. In this paper, we present a state of the art research work based on real-time QoS routing protocols for WMSNs that have already been proposed. This paper categorizes the real-time QoS routing protocols into probabilistic and deterministic protocols. In addition, both categories are classified into soft and hard real time protocols by highlighting the QoS issues including the limitations and features of each protocol. Furthermore, we have compared the performance of mobility-aware query based real-time QoS routing protocols from each category using Network Simulator-2 (NS2). This paper also focuses on the design challenges and future research directions as well as highlights the characteristics of each QoS routing protocol.

Real-Time QoS Routing Protocols in Wireless Multimedia Sensor Networks: Study and Analysis

PubMed Central

Alanazi, Adwan; Elleithy, Khaled

2015-01-01

Many routing protocols have been proposed for wireless sensor networks. These routing protocols are almost always based on energy efficiency. However, recent advances in complementary metal-oxide semiconductor (CMOS) cameras and small microphones have led to the development of Wireless Multimedia Sensor Networks (WMSN) as a class of wireless sensor networks which pose additional challenges. The transmission of imaging and video data needs routing protocols with both energy efficiency and Quality of Service (QoS) characteristics in order to guarantee the efficient use of the sensor nodes and effective access to the collected data. Also, with integration of real time applications in Wireless Senor Networks (WSNs), the use of QoS routing protocols is not only becoming a significant topic, but is also gaining the attention of researchers. In designing an efficient QoS routing protocol, the reliability and guarantee of end-to-end delay are critical events while conserving energy. Thus, considerable research has been focused on designing energy efficient and robust QoS routing protocols. In this paper, we present a state of the art research work based on real-time QoS routing protocols for WMSNs that have already been proposed. This paper categorizes the real-time QoS routing protocols into probabilistic and deterministic protocols. In addition, both categories are classified into soft and hard real time protocols by highlighting the QoS issues including the limitations and features of each protocol. Furthermore, we have compared the performance of mobility-aware query based real-time QoS routing protocols from each category using Network Simulator-2 (NS2). This paper also focuses on the design challenges and future research directions as well as highlights the characteristics of each QoS routing protocol. PMID:26364639

Real-time biochemical sensor based on Raman scattering with CMOS contact imaging.

PubMed

Muyun Cao; Yuhua Li; Yadid-Pecht, Orly

2015-08-01

This work presents a biochemical sensor based on Raman scattering with Complementary metal-oxide-semiconductor (CMOS) contact imaging. This biochemical optical sensor is designed for detecting the concentration of solutions. The system is built with a laser diode, an optical filter, a sample holder and a commercial CMOS sensor. The output of the system is analyzed by an image processing program. The system provides instant measurements with a resolution of 0.2 to 0.4 Mol. This low cost and easy-operated small scale system is useful in chemical, biomedical and environmental labs for quantitative bio-chemical concentration detection with results reported comparable to a highly cost commercial spectrometer.

Real-time edge tracking using a tactile sensor

NASA Technical Reports Server (NTRS)

Berger, Alan D.; Volpe, Richard; Khosla, Pradeep K.

1989-01-01

Object recognition through the use of input from multiple sensors is an important aspect of an autonomous manipulation system. In tactile object recognition, it is necessary to determine the location and orientation of object edges and surfaces. A controller is proposed that utilizes a tactile sensor in the feedback loop of a manipulator to track along edges. In the control system, the data from the tactile sensor is first processed to find edges. The parameters of these edges are then used to generate a control signal to a hybrid controller. Theory is presented for tactile edge detection and an edge tracking controller. In addition, experimental verification of the edge tracking controller is presented.

Development of a self-made framework for the acquisition and communication of real-time precipitation data

NASA Astrophysics Data System (ADS)

Pedrozo-Acuña, A.; Magos-Hernández, J. A.; Sánchez-Peralta, J. A.; Blanco-Figueroa, J.; Breña-Naranjo, J. A.

2017-12-01

This contribution presents a real-time system for issuing warnings of intense precipitation events during major storms, developed for Mexico City, Mexico. The system is based on high-temporal resolution (Dt=1min) measurements of precipitation in 10 different points within the city, which report variables such as intensity, number of raindrops, raindrop size, kinetic energy, fall velocity, etc. Each one of these stations, is comprised of an optical disdrometer to measure size and fall velocity of hydrometeors, a solar panel to guarantee an uninterrupted power supply, a wireless broadband access to internet, and a resource constrained device known as Raspberry Pi3 for the processing, storage and sharing of the sensor data over the world wide web. The self-made developed platform follows a component-based system paradigm allowing users to implement custom algorithms and models depending on application requirements. The system is in place since July 2016, and continuous measurements of rainfall in real-time are published over the internet through the webpage www.oh-iiunam.mx. Additionally, the developed platform for the data collection and management interacts with the social network known as Twitter to enable real-time warnings of precipitation events. Key contribution of this development is the design and implementation of a scalable, easy to use, interoperable platform that facilitates the development of real-time precipitation sensor networks and warnings. The system is easy to implement and could be used as a prototype for systems in other regions of the world.

Combination of High Rate, Real-Time GNSS and Accelerometer Observations and Rapid Seismic Event Notification for Earthquake Early Warning and Volcano Monitoring with a Focus on the Pacific Rim.

NASA Astrophysics Data System (ADS)

Zimakov, L. G.; Passmore, P.; Raczka, J.; Alvarez, M.; Jackson, M.

2014-12-01

Scientific GNSS networks are moving towards a model of real-time data acquisition, epoch-by-epoch storage integrity, and on-board real-time position and displacement calculations. This new paradigm allows the integration of real-time, high-rate GNSS displacement information with acceleration and velocity data to create very high-rate displacement records. The mating of these two instruments allows the creation of a new, very high-rate (200 sps) displacement observable that has the full-scale displacement characteristics of GNSS and high-precision dynamic motions of seismic technologies. It is envisioned that these new observables can be used for earthquake early warning studies, volcano monitoring, and critical infrastructure monitoring applications. Our presentation will focus on the characteristics of GNSS, seismic, and strong motion sensors in high dynamic environments, including historic earthquakes in Southern California and the Pacific Rim, replicated on a shake table, over a range of displacements and frequencies. We will explore the optimum integration of these sensors from a filtering perspective including simple harmonic impulses over varying frequencies and amplitudes and under the dynamic conditions of various earthquake scenarios. In addition we will discuss implementation of a Rapid Seismic Event Notification System that provides quick delivery of digital data from seismic stations to the acquisition and processing center and a full data integrity model for real-time earthquake notification that provides warning prior to significant ground shaking.

Real time mitigation of atmospheric turbulence in long distance imaging using the lucky region fusion algorithm with FPGA and GPU hardware acceleration

NASA Astrophysics Data System (ADS)

Jackson, Christopher Robert

"Lucky-region" fusion (LRF) is a synthetic imaging technique that has proven successful in enhancing the quality of images distorted by atmospheric turbulence. The LRF algorithm selects sharp regions of an image obtained from a series of short exposure frames, and fuses the sharp regions into a final, improved image. In previous research, the LRF algorithm had been implemented on a PC using the C programming language. However, the PC did not have sufficient sequential processing power to handle real-time extraction, processing and reduction required when the LRF algorithm was applied to real-time video from fast, high-resolution image sensors. This thesis describes two hardware implementations of the LRF algorithm to achieve real-time image processing. The first was created with a VIRTEX-7 field programmable gate array (FPGA). The other developed using the graphics processing unit (GPU) of a NVIDIA GeForce GTX 690 video card. The novelty in the FPGA approach is the creation of a "black box" LRF video processing system with a general camera link input, a user controller interface, and a camera link video output. We also describe a custom hardware simulation environment we have built to test the FPGA LRF implementation. The advantage of the GPU approach is significantly improved development time, integration of image stabilization into the system, and comparable atmospheric turbulence mitigation.

Anesthetic level prediction using a QCM based E-nose.

PubMed

Saraoğlu, H M; Ozmen, A; Ebeoğlu, M A

2008-06-01

Anesthetic level measurement is a real time process. This paper presents a new method to measure anesthesia level in surgery rooms at hospitals using a QCM based E-Nose. The E-Nose system contains an array of eight different coated QCM sensors. In this work, the best linear reacting sensor is selected from the array and used in the experiments. Then, the sensor response time was observed about 15 min using classic method, which is impractical for on-line anesthetic level detection during a surgery. Later, the sensor transition data is analyzed to reach a decision earlier than the classical method. As a result, it is found out that the slope of transition data gives valuable information to predict the anesthetic level. With this new method, we achieved to find correct anesthetic levels within 100 s.

[Development of automatic urine monitoring system].

PubMed

Wei, Liang; Li, Yongqin; Chen, Bihua

2014-03-01

An automatic urine monitoring system is presented to replace manual operation. The system is composed of the flow sensor, MSP430f149 single chip microcomputer, human-computer interaction module, LCD module, clock module and memory module. The signal of urine volume is captured when the urine flows through the flow sensor and then displayed on the LCD after data processing. The experiment results suggest that the design of the monitor provides a high stability, accurate measurement and good real-time, and meets the demand of the clinical application.

Multimode electromagnetic target discriminator: preliminary data results

NASA Astrophysics Data System (ADS)

Black, Christopher J.; McMichael, Ian T.; Nelson, Carl V.

2004-09-01

This paper describes the Multi-mode Electromagnetic Target Discriminator (METD) sensor and presents preliminary results from recent field experiments. The METD sensor was developed for the US Army RDECOM NVESD by The Johns Hopkins University Applied Physics Laboratory. The METD, based on the technology of the previously developed Electromagnetic Target Discriminator (ETD), is a spatial scanning electromagnetic induction (EMI) sensor that uses both the time-domain (TD) and the frequency-domain (FD) for target detection and classification. Data is collected with a custom data acquisition system and wirelessly transmitted to a base computer. We show that the METD has a high signal-to-noise ratio (SNR), the ability to detect voids created by plastic anti-tank (AT) mines, and is practical for near real-time data processing.

Using Fuzzy Clustering for Real-time Space Flight Safety

NASA Technical Reports Server (NTRS)

Lee, Charles; Haskell, Richard E.; Hanna, Darrin; Alena, Richard L.

2004-01-01

To ensure space flight safety, it is necessary to monitor myriad sensor readings on the ground and in flight. Since a space shuttle has many sensors, monitoring data and drawing conclusions from information contained within the data in real time is challenging. The nature of the information can be critical to the success of the mission and safety of the crew and therefore, must be processed with minimal data-processing time. Data analysis algorithms could be used to synthesize sensor readings and compare data associated with normal operation with the data obtained that contain fault patterns to draw conclusions. Detecting abnormal operation during early stages in the transition from safe to unsafe operation requires a large amount of historical data that can be categorized into different classes (non-risk, risk). Even though the 40 years of shuttle flight program has accumulated volumes of historical data, these data don t comprehensively represent all possible fault patterns since fault patterns are usually unknown before the fault occurs. This paper presents a method that uses a similarity measure between fuzzy clusters to detect possible faults in real time. A clustering technique based on a fuzzy equivalence relation is used to characterize temporal data. Data collected during an initial time period are separated into clusters. These clusters are characterized by their centroids. Clusters formed during subsequent time periods are either merged with an existing cluster or added to the cluster list. The resulting list of cluster centroids, called a cluster group, characterizes the behavior of a particular set of temporal data. The degree to which new clusters formed in a subsequent time period are similar to the cluster group is characterized by a similarity measure, q. This method is applied to downlink data from Columbia flights. The results show that this technique can detect an unexpected fault that has not been present in the training data set.

Development of a Real-Time Pulse Processing Algorithm for TES-Based X-Ray Microcalorimeters

NASA Technical Reports Server (NTRS)

Tan, Hui; Hennig, Wolfgang; Warburton, William K.; Doriese, W. Bertrand; Kilbourne, Caroline A.

2011-01-01

We report here a real-time pulse processing algorithm for superconducting transition-edge sensor (TES) based x-ray microcalorimeters. TES-based. microca1orimeters offer ultra-high energy resolutions, but the small volume of each pixel requires that large arrays of identical microcalorimeter pixe1s be built to achieve sufficient detection efficiency. That in turn requires as much pulse processing as possible must be performed at the front end of readout electronics to avoid transferring large amounts of data to a host computer for post-processing. Therefore, a real-time pulse processing algorithm that not only can be implemented in the readout electronics but also achieve satisfactory energy resolutions is desired. We have developed an algorithm that can be easily implemented. in hardware. We then tested the algorithm offline using several data sets acquired with an 8 x 8 Goddard TES x-ray calorimeter array and 2x16 NIST time-division SQUID multiplexer. We obtained an average energy resolution of close to 3.0 eV at 6 keV for the multiplexed pixels while preserving over 99% of the events in the data sets.

Fault tolerant attitude control for small unmanned aircraft systems equipped with an airflow sensor array.

PubMed

Shen, H; Xu, Y; Dickinson, B T

2014-11-18

Inspired by sensing strategies observed in birds and bats, a new attitude control concept of directly using real-time pressure and shear stresses has recently been studied. It was shown that with an array of onboard airflow sensors, small unmanned aircraft systems can promptly respond to airflow changes and improve flight performances. In this paper, a mapping function is proposed to compute aerodynamic moments from the real-time pressure and shear data in a practical and computationally tractable formulation. Since many microscale airflow sensors are embedded on the small unmanned aircraft system surface, it is highly possible that certain sensors may fail. Here, an adaptive control system is developed that is robust to sensor failure as well as other numerical mismatches in calculating real-time aerodynamic moments. The advantages of the proposed method are shown in the following simulation cases: (i) feedback pressure and wall shear data from a distributed array of 45 airflow sensors; (ii) 50% failure of the symmetrically distributed airflow sensor array; and (iii) failure of all the airflow sensors on one wing. It is shown that even if 50% of the airflow sensors have failures, the aircraft is still stable and able to track the attitude commands.

FPGA-accelerated adaptive optics wavefront control

NASA Astrophysics Data System (ADS)

Mauch, S.; Reger, J.; Reinlein, C.; Appelfelder, M.; Goy, M.; Beckert, E.; Tünnermann, A.

2014-03-01

The speed of real-time adaptive optical systems is primarily restricted by the data processing hardware and computational aspects. Furthermore, the application of mirror layouts with increasing numbers of actuators reduces the bandwidth (speed) of the system and, thus, the number of applicable control algorithms. This burden turns out a key-impediment for deformable mirrors with continuous mirror surface and highly coupled actuator influence functions. In this regard, specialized hardware is necessary for high performance real-time control applications. Our approach to overcome this challenge is an adaptive optics system based on a Shack-Hartmann wavefront sensor (SHWFS) with a CameraLink interface. The data processing is based on a high performance Intel Core i7 Quadcore hard real-time Linux system. Employing a Xilinx Kintex-7 FPGA, an own developed PCie card is outlined in order to accelerate the analysis of a Shack-Hartmann Wavefront Sensor. A recently developed real-time capable spot detection algorithm evaluates the wavefront. The main features of the presented system are the reduction of latency and the acceleration of computation For example, matrix multiplications which in general are of complexity O(n3 are accelerated by using the DSP48 slices of the field-programmable gate array (FPGA) as well as a novel hardware implementation of the SHWFS algorithm. Further benefits are the Streaming SIMD Extensions (SSE) which intensively use the parallelization capability of the processor for further reducing the latency and increasing the bandwidth of the closed-loop. Due to this approach, up to 64 actuators of a deformable mirror can be handled and controlled without noticeable restriction from computational burdens.

Sensor to detect endothelialization on an active coronary stent

PubMed Central

2010-01-01

Background A serious complication with drug-eluting coronary stents is late thrombosis, caused by exposed stent struts not covered by endothelial cells in the healing process. Real-time detection of this healing process could guide physicians for more individualized anti-platelet therapy. Here we present work towards developing a sensor to detect this healing process. Sensors on several stent struts could give information about the heterogeneity of healing across the stent. Methods A piezoelectric microcantilever was insulated with parylene and demonstrated as an endothelialization detector for incorporation within an active coronary stent. After initial characterization, endothelial cells were plated onto the cantilever surface. After they attached to the surface, they caused an increase in mass, and thus a decrease in the resonant frequencies of the cantilever. This shift was then detected electrically with an LCR meter. The self-sensing, self-actuating cantilever does not require an external, optical detection system, thus allowing for implanted applications. Results A cell density of 1300 cells/mm2 on the cantilever surface is detected. Conclusions We have developed a self-actuating, self-sensing device for detecting the presence of endothelial cells on a surface. The device is biocompatible and functions reliably in ionic liquids, making it appropriate for implantable applications. This sensor can be placed along the struts of a coronary stent to detect when the struts have been covered with a layer of endothelial cells and are no longer available surfaces for clot formation. Anti-platelet therapy can be adjusted in real-time with respect to a patient's level of healing and hemorrhaging risks. PMID:21050471

Continuous wireless pressure monitoring and mapping with ultra-small passive sensors for health monitoring and critical care

NASA Astrophysics Data System (ADS)

Chen, Lisa Y.; Tee, Benjamin C.-K.; Chortos, Alex L.; Schwartz, Gregor; Tse, Victor; J. Lipomi, Darren; Wong, H.-S. Philip; McConnell, Michael V.; Bao, Zhenan

2014-10-01

Continuous monitoring of internal physiological parameters is essential for critical care patients, but currently can only be practically achieved via tethered solutions. Here we report a wireless, real-time pressure monitoring system with passive, flexible, millimetre-scale sensors, scaled down to unprecedented dimensions of 1 × 1 × 0.1 cubic millimeters. This level of dimensional scaling is enabled by novel sensor design and detection schemes, which overcome the operating frequency limits of traditional strategies and exhibit insensitivity to lossy tissue environments. We demonstrate the use of this system to capture human pulse waveforms wirelessly in real time as well as to monitor in vivo intracranial pressure continuously in proof-of-concept mice studies using sensors down to 2.5 × 2.5 × 0.1 cubic millimeters. We further introduce printable wireless sensor arrays and show their use in real-time spatial pressure mapping. Looking forward, this technology has broader applications in continuous wireless monitoring of multiple physiological parameters for biomedical research and patient care.

Continuous wireless pressure monitoring and mapping with ultra-small passive sensors for health monitoring and critical care.

PubMed

Chen, Lisa Y; Tee, Benjamin C-K; Chortos, Alex L; Schwartz, Gregor; Tse, Victor; Lipomi, Darren J; Wong, H-S Philip; McConnell, Michael V; Bao, Zhenan

2014-10-06

Continuous monitoring of internal physiological parameters is essential for critical care patients, but currently can only be practically achieved via tethered solutions. Here we report a wireless, real-time pressure monitoring system with passive, flexible, millimetre-scale sensors, scaled down to unprecedented dimensions of 1 × 1 × 0.1 cubic millimeters. This level of dimensional scaling is enabled by novel sensor design and detection schemes, which overcome the operating frequency limits of traditional strategies and exhibit insensitivity to lossy tissue environments. We demonstrate the use of this system to capture human pulse waveforms wirelessly in real time as well as to monitor in vivo intracranial pressure continuously in proof-of-concept mice studies using sensors down to 2.5 × 2.5 × 0.1 cubic millimeters. We further introduce printable wireless sensor arrays and show their use in real-time spatial pressure mapping. Looking forward, this technology has broader applications in continuous wireless monitoring of multiple physiological parameters for biomedical research and patient care.

Multichannel series piezoelectric quartz crystal cell sensor for real time and quantitative monitoring of the living cell and assessment of cytotoxicity.

PubMed

Tong, Feifei; Lian, Yan; Zhou, Huang; Shi, Xiaohong; He, Fengjiao

2014-10-21

A new multichannel series piezoelectric quartz crystal (MSPQC) cell sensor for real time monitoring of living cells in vitro was reported in this paper. The constructed sensor was used successfully to monitor adhesion, spreading, proliferation, and apoptosis of MG63 osteosarcoma cells and investigate the effects of different concentrations of cobalt chloride on MG63 cells. Quantitative real time and dynamic cell analyses data were conducted using the MSPQC cell sensor. Compared with methods such as fluorescence staining and morphology observation by microscopy, the MSPQC cell sensor is noninvasive, label free, simple, cheap, and capable of online monitoring. It can automatically record the growth status of cells and quantitatively evaluate cell proliferation and the apoptotic response to drugs. It will be a valuable detection and analysis tool for the acquisition of cellular level information and is anticipated to have application in the field of cell biology research or cytotoxicity testing in the future.

Software Development to Assist in the Processing and Analysis of Data Obtained Using Fiber Bragg Grating Interrogation Systems

NASA Technical Reports Server (NTRS)

Hicks, Rebecca

2010-01-01

A fiber Bragg grating is a portion of a core of a fiber optic stand that has been treated to affect the way light travels through the strand. Light within a certain narrow range of wavelengths will be reflected along the fiber by the grating, while light outside that range will pass through the grating mostly undisturbed. Since the range of wavelengths that can penetrate the grating depends on the grating itself as well as temperature and mechanical strain, fiber Bragg gratings can be used as temperature and strain sensors. This capability, along with the light-weight nature of the fiber optic strands in which the gratings reside, make fiber optic sensors an ideal candidate for flight testing and monitoring in which temperature and wing strain are factors. A team of NASA Dryden engineers has been working to advance the fiber optic sensor technology since the mid 1990 s. The team has been able to improve the dependability and sample rate of fiber optic sensor systems, making them more suitable for real-time wing shape and strain monitoring and capable of rivaling traditional strain gauge sensors in accuracy. The sensor system was recently tested on the Ikhana unmanned aircraft and will be used on the Global Observer unmanned aircraft. Since a fiber Bragg grating sensor can be placed every halfinch on each optic fiber, and since fibers of approximately 40 feet in length each are to be used on the Global Observer, each of these fibers will have approximately 1,000 sensors. A total of 32 fibers are to be placed on the Global Observer aircraft, to be sampled at a rate of about 50 Hz, meaning about 1.6 million data points will be taken every second. The fiber optic sensors system is capable of producing massive amounts of potentially useful data; however, methods to capture, record, and analyze all of this data in a way that makes the information useful to flight test engineers are currently limited. The purpose of this project is to research the availability of software capable of processing massive amounts of data in both real-time and post-flight settings, and to produce software segments that can be integrated to assist in the task as well. The selected software must be able to: (1) process massive amounts of data (up to 4GB) at a speed useful in a real-time settings (small fractions of a second); (2) process data in post-flight settings to allow test reproduction or further data analysis, inclusive; (3) produce, or make easier to produce, three-dimensional plots/graphs to make the data accessible to flight test engineers; and (4) be customized to allow users to use their own processing formulas or functions and display the data in formats they prefer. Several software programs were evaluated to determine their utility in completing the research objectives. These programs include: OriginLab, Graphis, 3D Grapher, Visualization Sciences Group (VSG) Avizo Wind, Interactive Analysis and Display System (IADS), SigmaPlot, and MATLAB.

Fabrication and characterization of 3C-silicon carbide micro sensor for wireless blood pressure measurements

NASA Astrophysics Data System (ADS)

Basak, Nupur

A potentially implantable single crystal 3C-SiC pressure sensor for blood pressure measurement was designed, simulated, fabricated, characterized and optimized. This research uses a single crystal 3C-SiC, for the first time, to demonstrate its application as a blood pressure measurement sensor. The sensor, which uses the epitaxial grown 3C-SiC membrane to measure changes in pressure, is designed to be wireless, biocompatible and linear. The SiC material was chosen for its superior physical, chemical and mechanical properties; the capacitive sensor uses a 3C-SiC membrane as one of the electrodes; and, the sensor system is wireless for comfort and to allow for convenient reading of real-time pressure data (wireless communication is enabled by connecting the sensor parallel to a planar inductor). Together, the variable capacitive sensor and planar inductor create a pressure sensitive resonant circuit. The sensor system described above allows for implantation into a human patient's body, after which the planar inductor can be coupled with an external inductor to receive data for real-time blood pressure measurement. Electroplating, thick photo-resist characterization, RIE etching, oxidation, CVD, chemical mechanical polishing and wafer bonding were optimized during the process of fabricating the sensor system and, in addition to detailing the sensor system simulation and characterization; the optimized processes are detailed in the dissertation. This absolute pressure sensor is designed to function optimally within the human blood pressure range of 50-350mmHg. The layout and modeling of the sensor uses finite element analysis (FEA) software. The simulations for membrane deflection, stress analysis and electro-mechanical analysis are performed for 100 μm2 and 400μm2sensors. The membrane deflection-pressure, capacitance-pressure and resonant frequency-pressure graphs were obtained, and detailed in the dissertation, along with the planar inductor simulation for differently sized inductors. Ultimately, an optimized sensor with a size of 400μm2 was chosen because of its high sensitivity. The sensor, and the planar inductor, which is 3mm 2, is comparable to the presently researched implantable chip size. The measured inductance of the gold electroplated inductor is 0.371μH. The capacitance changes from 0.934 pF to 0.997pF with frequency shift of 248MHz to 256 MHz. The sensitivity of the sensor is found to be 0.21 fF/mmHg or 27.462 kHz/mmHg with an average non-linearity of 0.23216%.

Addressing Data Veracity in Big Data Applications

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

Aman, Saima; Chelmis, Charalampos; Prasanna, Viktor

Big data applications such as in smart electric grids, transportation, and remote environment monitoring involve geographically dispersed sensors that periodically send back information to central nodes. In many cases, data from sensors is not available at central nodes at a frequency that is required for real-time modeling and decision-making. This may be due to physical limitations of the transmission networks, or due to consumers limiting frequent transmission of data from sensors located at their premises for security and privacy concerns. Such scenarios lead to partial data problem and raise the issue of data veracity in big data applications. We describemore » a novel solution to the problem of making short term predictions (up to a few hours ahead) in absence of real-time data from sensors in Smart Grid. A key implication of our work is that by using real-time data from only a small subset of influential sensors, we are able to make predictions for all sensors. We thus reduce the communication complexity involved in transmitting sensory data in Smart Grids. We use real-world electricity consumption data from smart meters to empirically demonstrate the usefulness of our method. Our dataset consists of data collected at 15-min intervals from 170 smart meters in the USC Microgrid for 7 years, totaling 41,697,600 data points.« less

Comparison of the different approaches to generate holograms from data acquired with a Kinect sensor

NASA Astrophysics Data System (ADS)

Kang, Ji-Hoon; Leportier, Thibault; Ju, Byeong-Kwon; Song, Jin Dong; Lee, Kwang-Hoon; Park, Min-Chul

2017-05-01

Data of real scenes acquired in real-time with a Kinect sensor can be processed with different approaches to generate a hologram. 3D models can be generated from a point cloud or a mesh representation. The advantage of the point cloud approach is that computation process is well established since it involves only diffraction and propagation of point sources between parallel planes. On the other hand, the mesh representation enables to reduce the number of elements necessary to represent the object. Then, even though the computation time for the contribution of a single element increases compared to a simple point, the total computation time can be reduced significantly. However, the algorithm is more complex since propagation of elemental polygons between non-parallel planes should be implemented. Finally, since a depth map of the scene is acquired at the same time than the intensity image, a depth layer approach can also be adopted. This technique is appropriate for a fast computation since propagation of an optical wavefront from one plane to another can be handled efficiently with the fast Fourier transform. Fast computation with depth layer approach is convenient for real time applications, but point cloud method is more appropriate when high resolution is needed. In this study, since Kinect can be used to obtain both point cloud and depth map, we examine the different approaches that can be adopted for hologram computation and compare their performance.

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.

Stretchable Electrochemical Sensor for Real-Time Monitoring of Cells and Tissues.

PubMed

Liu, Yan-Ling; Jin, Zi-He; Liu, Yan-Hong; Hu, Xue-Bo; Qin, Yu; Xu, Jia-Quan; Fan, Cui-Fang; Huang, Wei-Hua

2016-03-24

Stretchable electrochemical sensors are conceivably a powerful technique that provides important chemical information to unravel elastic and curvilinear living body. However, no breakthrough was made in stretchable electrochemical device for biological detection. Herein, we synthesized Au nanotubes (NTs) with large aspect ratio to construct an effective stretchable electrochemical sensor. Interlacing network of Au NTs endows the sensor with desirable stability against mechanical deformation, and Au nanostructure provides excellent electrochemical performance and biocompatibility. This allows for the first time, real-time electrochemical monitoring of mechanically sensitive cells on the sensor both in their stretching-free and stretching states as well as sensing of the inner lining of blood vessels. The results demonstrate the great potential of this sensor in electrochemical detection of living body, opening a new window for stretchable electrochemical sensor in biological exploration. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

SensorDB: a virtual laboratory for the integration, visualization and analysis of varied biological sensor data.

PubMed

Salehi, Ali; Jimenez-Berni, Jose; Deery, David M; Palmer, Doug; Holland, Edward; Rozas-Larraondo, Pablo; Chapman, Scott C; Georgakopoulos, Dimitrios; Furbank, Robert T

2015-01-01

To our knowledge, there is no software or database solution that supports large volumes of biological time series sensor data efficiently and enables data visualization and analysis in real time. Existing solutions for managing data typically use unstructured file systems or relational databases. These systems are not designed to provide instantaneous response to user queries. Furthermore, they do not support rapid data analysis and visualization to enable interactive experiments. In large scale experiments, this behaviour slows research discovery, discourages the widespread sharing and reuse of data that could otherwise inform critical decisions in a timely manner and encourage effective collaboration between groups. In this paper we present SensorDB, a web based virtual laboratory that can manage large volumes of biological time series sensor data while supporting rapid data queries and real-time user interaction. SensorDB is sensor agnostic and uses web-based, state-of-the-art cloud and storage technologies to efficiently gather, analyse and visualize data. Collaboration and data sharing between different agencies and groups is thereby facilitated. SensorDB is available online at http://sensordb.csiro.au.

Airborne net-centric multi-INT sensor control, display, fusion, and exploitation systems

NASA Astrophysics Data System (ADS)

Linne von Berg, Dale C.; Lee, John N.; Kruer, Melvin R.; Duncan, Michael D.; Olchowski, Fred M.; Allman, Eric; Howard, Grant

2004-08-01

The NRL Optical Sciences Division has initiated a multi-year effort to develop and demonstrate an airborne net-centric suite of multi-intelligence (multi-INT) sensors and exploitation systems for real-time target detection and targeting product dissemination. The goal of this Net-centric Multi-Intelligence Fusion Targeting Initiative (NCMIFTI) is to develop an airborne real-time intelligence gathering and targeting system that can be used to detect concealed, camouflaged, and mobile targets. The multi-INT sensor suite will include high-resolution visible/infrared (EO/IR) dual-band cameras, hyperspectral imaging (HSI) sensors in the visible-to-near infrared, short-wave and long-wave infrared (VNIR/SWIR/LWIR) bands, Synthetic Aperture Radar (SAR), electronics intelligence sensors (ELINT), and off-board networked sensors. Other sensors are also being considered for inclusion in the suite to address unique target detection needs. Integrating a suite of multi-INT sensors on a single platform should optimize real-time fusion of the on-board sensor streams, thereby improving the detection probability and reducing the false alarms that occur in reconnaissance systems that use single-sensor types on separate platforms, or that use independent target detection algorithms on multiple sensors. In addition to the integration and fusion of the multi-INT sensors, the effort is establishing an open-systems net-centric architecture that will provide a modular "plug and play" capability for additional sensors and system components and provide distributed connectivity to multiple sites for remote system control and exploitation.

Semi autonomous mine detection system

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

Douglas Few; Roelof Versteeg; Herman Herman

2010-04-01

CMMAD is a risk reduction effort for the AMDS program. As part of CMMAD, multiple instances of semi autonomous robotic mine detection systems were created. Each instance consists of a robotic vehicle equipped with sensors required for navigation and marking, a countermine sensors and a number of integrated software packages which provide for real time processing of the countermine sensor data as well as integrated control of the robotic vehicle, the sensor actuator and the sensor. These systems were used to investigate critical interest functions (CIF) related to countermine robotic systems. To address the autonomy CIF, the INL developed RIKmore » was extended to allow for interaction with a mine sensor processing code (MSPC). In limited field testing this system performed well in detecting, marking and avoiding both AT and AP mines. Based on the results of the CMMAD investigation we conclude that autonomous robotic mine detection is feasible. In addition, CMMAD contributed critical technical advances with regard to sensing, data processing and sensor manipulation, which will advance the performance of future fieldable systems. As a result, no substantial technical barriers exist which preclude – from an autonomous robotic perspective – the rapid development and deployment of fieldable systems.« less

Reliability of sensor-based real-time workflow recognition in laparoscopic cholecystectomy.

PubMed

Kranzfelder, Michael; Schneider, Armin; Fiolka, Adam; Koller, Sebastian; Reiser, Silvano; Vogel, Thomas; Wilhelm, Dirk; Feussner, Hubertus

2014-11-01

Laparoscopic cholecystectomy is a very common minimally invasive surgical procedure that may be improved by autonomous or cooperative assistance support systems. Model-based surgery with a precise definition of distinct procedural tasks (PT) of the operation was implemented and tested to depict and analyze the process of this procedure. Reliability of real-time workflow recognition in laparoscopic cholecystectomy ([Formula: see text] cases) was evaluated by continuous sensor-based data acquisition. Ten PTs were defined including begin/end preparation calots' triangle, clipping/cutting cystic artery and duct, begin/end gallbladder dissection, begin/end hemostasis, gallbladder removal, and end of operation. Data acquisition was achieved with continuous instrument detection, room/table light status, intra-abdominal pressure, table tilt, irrigation/aspiration volume and coagulation/cutting current application. Two independent observers recorded start and endpoint of each step by analysis of the sensor data. The data were cross-checked with laparoscopic video recordings serving as gold standard for PT identification. Bland-Altman analysis revealed for 95% of cases a difference of annotation results within the limits of agreement ranging from [Formula: see text]309 s (PT 7) to +368 s (PT 5). Laparoscopic video and sensor data matched to a greater or lesser extent within the different procedural tasks. In the majority of cases, the observer results exceeded those obtained from the laparoscopic video. Empirical knowledge was required to detect phase transit. A set of sensors used to monitor laparoscopic cholecystectomy procedures was sufficient to enable expert observers to reliably identify each PT. In the future, computer systems may automate the task identification process provided a more robust data inflow is available.

A Hilbert Transform-Based Smart Sensor for Detection, Classification, and Quantification of Power Quality Disturbances

PubMed Central

Granados-Lieberman, David; Valtierra-Rodriguez, Martin; Morales-Hernandez, Luis A.; Romero-Troncoso, Rene J.; Osornio-Rios, Roque A.

2013-01-01

Power quality disturbance (PQD) monitoring has become an important issue due to the growing number of disturbing loads connected to the power line and to the susceptibility of certain loads to their presence. In any real power system, there are multiple sources of several disturbances which can have different magnitudes and appear at different times. In order to avoid equipment damage and estimate the damage severity, they have to be detected, classified, and quantified. In this work, a smart sensor for detection, classification, and quantification of PQD is proposed. First, the Hilbert transform (HT) is used as detection technique; then, the classification of the envelope of a PQD obtained through HT is carried out by a feed forward neural network (FFNN). Finally, the root mean square voltage (Vrms), peak voltage (Vpeak), crest factor (CF), and total harmonic distortion (THD) indices calculated through HT and Parseval's theorem as well as an instantaneous exponential time constant quantify the PQD according to the disturbance presented. The aforementioned methodology is processed online using digital hardware signal processing based on field programmable gate array (FPGA). Besides, the proposed smart sensor performance is validated and tested through synthetic signals and under real operating conditions, respectively. PMID:23698264

Towards Smart Homes Using Low Level Sensory Data

PubMed Central

Khattak, Asad Masood; Truc, Phan Tran Ho; Hung, Le Xuan; Vinh, La The; Dang, Viet-Hung; Guan, Donghai; Pervez, Zeeshan; Han, Manhyung; Lee, Sungyoung; Lee, Young-Koo

2011-01-01

Ubiquitous Life Care (u-Life care) is receiving attention because it provides high quality and low cost care services. To provide spontaneous and robust healthcare services, knowledge of a patient’s real-time daily life activities is required. Context information with real-time daily life activities can help to provide better services and to improve healthcare delivery. The performance and accuracy of existing life care systems is not reliable, even with a limited number of services. This paper presents a Human Activity Recognition Engine (HARE) that monitors human health as well as activities using heterogeneous sensor technology and processes these activities intelligently on a Cloud platform for providing improved care at low cost. We focus on activity recognition using video-based, wearable sensor-based, and location-based activity recognition engines and then use intelligent processing to analyze the context of the activities performed. The experimental results of all the components showed good accuracy against existing techniques. The system is deployed on Cloud for Alzheimer’s disease patients (as a case study) with four activity recognition engines to identify low level activity from the raw data captured by sensors. These are then manipulated using ontology to infer higher level activities and make decisions about a patient’s activity using patient profile information and customized rules. PMID:22247682

Real-time processing of radar return on a parallel computer

NASA Technical Reports Server (NTRS)

Aalfs, David D.

1992-01-01

NASA is working with the FAA to demonstrate the feasibility of pulse Doppler radar as a candidate airborne sensor to detect low altitude windshears. The need to provide the pilot with timely information about possible hazards has motivated a demand for real-time processing of a radar return. Investigated here is parallel processing as a means of accommodating the high data rates required. A PC based parallel computer, called the transputer, is used to investigate issues in real time concurrent processing of radar signals. A transputer network is made up of an array of single instruction stream processors that can be networked in a variety of ways. They are easily reconfigured and software development is largely independent of the particular network topology. The performance of the transputer is evaluated in light of the computational requirements. A number of algorithms have been implemented on the transputers in OCCAM, a language specially designed for parallel processing. These include signal processing algorithms such as the Fast Fourier Transform (FFT), pulse-pair, and autoregressive modelling, as well as routing software to support concurrency. The most computationally intensive task is estimating the spectrum. Two approaches have been taken on this problem, the first and most conventional of which is to use the FFT. By using table look-ups for the basis function and other optimizing techniques, an algorithm has been developed that is sufficient for real time. The other approach is to model the signal as an autoregressive process and estimate the spectrum based on the model coefficients. This technique is attractive because it does not suffer from the spectral leakage problem inherent in the FFT. Benchmark tests indicate that autoregressive modeling is feasible in real time.

Continuous, Real-Time Monitoring of Cocaine in Undiluted Blood Serum via a Microfluidic, Electrochemical Aptamer-Based Sensor

PubMed Central

Swensen, James S.; Xiao, Yi; Ferguson, Brian S.; Lubin, Arica A.; Lai, Rebecca Y.; Heeger, Alan J.; Plaxco, Kevin W.; Soh, H. Tom.

2009-01-01

The development of a biosensor system capable of continuous, real-time measurement of small-molecule analytes directly in complex, unprocessed aqueous samples has been a significant challenge, and successful implementation has been achieved for only a limited number of targets. Towards a general solution to this problem, we report here the Microfluidic Electrochemical Aptamer-based Sensor (MECAS) chip wherein we integrate target-specific DNA aptamers that fold, and thus generate an electrochemical signal, in response to the analyte with a microfluidic detection system. As a model, we demonstrate the continuous, real-time (~1 minute time resolution) detection of the small molecule drug cocaine at near physiological, low micromolar concentrations directly in undiluted, otherwise unmodified blood serum. We believe our approach of integrating folding-based electrochemical sensors with miniaturized detection systems may lay the ground work for the real-time, point-of-care detection of a wide variety of molecular targets. PMID:19271708

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.

Real-time high-level video understanding using data warehouse

NASA Astrophysics Data System (ADS)

Lienard, Bruno; Desurmont, Xavier; Barrie, Bertrand; Delaigle, Jean-Francois

2006-02-01

High-level Video content analysis such as video-surveillance is often limited by computational aspects of automatic image understanding, i.e. it requires huge computing resources for reasoning processes like categorization and huge amount of data to represent knowledge of objects, scenarios and other models. This article explains how to design and develop a "near real-time adaptive image datamart", used, as a decisional support system for vision algorithms, and then as a mass storage system. Using RDF specification as storing format of vision algorithms meta-data, we can optimise the data warehouse concepts for video analysis, add some processes able to adapt the current model and pre-process data to speed-up queries. In this way, when new data is sent from a sensor to the data warehouse for long term storage, using remote procedure call embedded in object-oriented interfaces to simplified queries, they are processed and in memory data-model is updated. After some processing, possible interpretations of this data can be returned back to the sensor. To demonstrate this new approach, we will present typical scenarios applied to this architecture such as people tracking and events detection in a multi-camera network. Finally we will show how this system becomes a high-semantic data container for external data-mining.

Novel Membrane-Based Electrochemical Sensor for Real-Time Bio-Applications

PubMed Central

Alatraktchi, Fatima AlZahra'a; Bakmand, Tanya; Dimaki, Maria; Svendsen, Winnie E.

2014-01-01

This article presents a novel membrane-based sensor for real-time electrochemical investigations of cellular- or tissue cultures. The membrane sensor enables recording of electrical signals from a cell culture without any signal dilution, thus avoiding loss of sensitivity. Moreover, the porosity of the membrane provides optimal culturing conditions similar to existing culturing techniques allowing more efficient nutrient uptake and molecule release. The patterned sensor electrodes were fabricated on a porous membrane by electron-beam evaporation. The electrochemical performance of the membrane electrodes was characterized by cyclic voltammetry and chronoamperometry, and the detection of synthetic dopamine was demonstrated down to a concentration of 3.1 pM. Furthermore, to present the membrane-sensor functionality the dopamine release from cultured PC12 cells was successfully measured. The PC12 cells culturing experiments showed that the membrane-sensor was suitable as a cell culturing substrate for bio-applications. Real-time measurements of dopamine exocytosis in cell cultures were performed, where the transmitter release was recorded at the point of release. The developed membrane-sensor provides a new functionality to the standard culturing methods, enabling sensitive continuous in vitro monitoring and closely mimicking the in vivo conditions. PMID:25421738

Robust real-time horizon detection in full-motion video

NASA Astrophysics Data System (ADS)

Young, Grace B.; Bagnall, Bryan; Lane, Corey; Parameswaran, Shibin

2014-06-01

The ability to detect the horizon on a real-time basis in full-motion video is an important capability to aid and facilitate real-time processing of full-motion videos for the purposes such as object detection, recognition and other video/image segmentation applications. In this paper, we propose a method for real-time horizon detection that is designed to be used as a front-end processing unit for a real-time marine object detection system that carries out object detection and tracking on full-motion videos captured by ship/harbor-mounted cameras, Unmanned Aerial Vehicles (UAVs) or any other method of surveillance for Maritime Domain Awareness (MDA). Unlike existing horizon detection work, we cannot assume a priori the angle or nature (for e.g. straight line) of the horizon, due to the nature of the application domain and the data. Therefore, the proposed real-time algorithm is designed to identify the horizon at any angle and irrespective of objects appearing close to and/or occluding the horizon line (for e.g. trees, vehicles at a distance) by accounting for its non-linear nature. We use a simple two-stage hierarchical methodology, leveraging color-based features, to quickly isolate the region of the image containing the horizon and then perform a more ne-grained horizon detection operation. In this paper, we present our real-time horizon detection results using our algorithm on real-world full-motion video data from a variety of surveillance sensors like UAVs and ship mounted cameras con rming the real-time applicability of this method and its ability to detect horizon with no a priori assumptions.

Structure Optimization of a Grain Impact Piezoelectric Sensor and Its Application for Monitoring Separation Losses on Tangential-Axial Combine Harvesters

PubMed Central

Liang, Zhenwei; Li, Yaoming; Zhao, Zhan; Xu, Lizhang

2015-01-01

Grain separation losses is a key parameter to weigh the performance of combine harvesters, and also a dominant factor for automatically adjusting their major working parameters. The traditional separation losses monitoring method mainly rely on manual efforts, which require a high labor intensity. With recent advancements in sensor technology, electronics and computational processing power, this paper presents an indirect method for monitoring grain separation losses in tangential-axial combine harvesters in real-time. Firstly, we developed a mathematical monitoring model based on detailed comparative data analysis of different feeding quantities. Then, we developed a grain impact piezoelectric sensor utilizing a YT-5 piezoelectric ceramic as the sensing element, and a signal process circuit designed according to differences in voltage amplitude and rise time of collision signals. To improve the sensor performance, theoretical analysis was performed from a structural vibration point of view, and the optimal sensor structural has been selected. Grain collide experiments have shown that the sensor performance was greatly improved. Finally, we installed the sensor on a tangential-longitudinal axial combine harvester, and grain separation losses monitoring experiments were carried out in North China, which results have shown that the monitoring method was feasible, and the biggest measurement relative error was 4.63% when harvesting rice. PMID:25594592

Structure optimization of a grain impact piezoelectric sensor and its application for monitoring separation losses on tangential-axial combine harvesters.

PubMed

Liang, Zhenwei; Li, Yaoming; Zhao, Zhan; Xu, Lizhang

2015-01-14

Grain separation losses is a key parameter to weigh the performance of combine harvesters, and also a dominant factor for automatically adjusting their major working parameters. The traditional separation losses monitoring method mainly rely on manual efforts, which require a high labor intensity. With recent advancements in sensor technology, electronics and computational processing power, this paper presents an indirect method for monitoring grain separation losses in tangential-axial combine harvesters in real-time. Firstly, we developed a mathematical monitoring model based on detailed comparative data analysis of different feeding quantities. Then, we developed a grain impact piezoelectric sensor utilizing a YT-5 piezoelectric ceramic as the sensing element, and a signal process circuit designed according to differences in voltage amplitude and rise time of collision signals. To improve the sensor performance, theoretical analysis was performed from a structural vibration point of view, and the optimal sensor structural has been selected. Grain collide experiments have shown that the sensor performance was greatly improved. Finally, we installed the sensor on a tangential-longitudinal axial combine harvester, and grain separation losses monitoring experiments were carried out in North China, which results have shown that the monitoring method was feasible, and the biggest measurement relative error was 4.63% when harvesting rice.

Real-time identification of indoor pollutant source positions based on neural network locator of contaminant sources and optimized sensor networks.

PubMed

Vukovic, Vladimir; Tabares-Velasco, Paulo Cesar; Srebric, Jelena

2010-09-01

A growing interest in security and occupant exposure to contaminants revealed a need for fast and reliable identification of contaminant sources during incidental situations. To determine potential contaminant source positions in outdoor environments, current state-of-the-art modeling methods use computational fluid dynamic simulations on parallel processors. In indoor environments, current tools match accidental contaminant distributions with cases from precomputed databases of possible concentration distributions. These methods require intensive computations in pre- and postprocessing. On the other hand, neural networks emerged as a tool for rapid concentration forecasting of outdoor environmental contaminants such as nitrogen oxides or sulfur dioxide. All of these modeling methods depend on the type of sensors used for real-time measurements of contaminant concentrations. A review of the existing sensor technologies revealed that no perfect sensor exists, but intensity of work in this area provides promising results in the near future. The main goal of the presented research study was to extend neural network modeling from the outdoor to the indoor identification of source positions, making this technology applicable to building indoor environments. The developed neural network Locator of Contaminant Sources was also used to optimize number and allocation of contaminant concentration sensors for real-time prediction of indoor contaminant source positions. Such prediction should take place within seconds after receiving real-time contaminant concentration sensor data. For the purpose of neural network training, a multizone program provided distributions of contaminant concentrations for known source positions throughout a test building. Trained networks had an output indicating contaminant source positions based on measured concentrations in different building zones. A validation case based on a real building layout and experimental data demonstrated the ability of this method to identify contaminant source positions. Future research intentions are focused on integration with real sensor networks and model improvements for much more complicated contamination scenarios.

Use of external cavity quantum cascade laser compliance voltage in real-time trace gas sensing of multiple chemicals

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

Phillips, Mark C.; Taubman, Matthew S.; Kriesel, Jason M.

2015-02-08

We describe a prototype trace gas sensor designed for real-time detection of multiple chemicals. The sensor uses an external cavity quantum cascade laser (ECQCL) swept over its tuning range of 940-1075 cm-1 (9.30-10.7 µm) at a 10 Hz repetition rate.

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.

Development of real-time extensometer based on image processing

NASA Astrophysics Data System (ADS)

Adinanta, H.; Puranto, P.; Suryadi

2017-04-01

An extensometer system was developed by using high definition web camera as main sensor to track object position. The developed system applied digital image processing techniques. The image processing was used to measure the change of object position. The position measurement was done in real-time so that the system can directly showed the actual position in both x and y-axis. In this research, the relation between pixel and object position changes had been characterized. The system was tested by moving the target in a range of 20 cm in interval of 1 mm. To verify the long run performance, the stability and linearity of continuous measurements on both x and y-axis, this measurement had been conducted for 83 hours. The results show that this image processing-based extensometer had both good stability and linearity.