Applying Sensor Networks to Evaluate Air Pollutant Emissions from Fugitive and Area Sources

EPA Science Inventory

This is a presentation to be given at Duke University's Wireless Intelligent Sensor Network workshop on June 5, 2013. The presentation discusses the evaluation of a low cost carbon monoxide sensor network applied at a recent forest fire study and also evaluated against a referen...

On the feasibility of measuring urban air pollution by wireless distributed sensor networks.

PubMed

Moltchanov, Sharon; Levy, Ilan; Etzion, Yael; Lerner, Uri; Broday, David M; Fishbain, Barak

2015-01-01

Accurate evaluation of air pollution on human-wellbeing requires high-resolution measurements. Standard air quality monitoring stations provide accurate pollution levels but due to their sparse distribution they cannot capture the highly resolved spatial variations within cities. Similarly, dedicated field campaigns can use tens of measurement devices and obtain highly dense spatial coverage but normally deployment has been limited to short periods of no more than few weeks. Nowadays, advances in communication and sensory technologies enable the deployment of dense grids of wireless distributed air monitoring nodes, yet their sensor ability to capture the spatiotemporal pollutant variability at the sub-neighborhood scale has never been thoroughly tested. This study reports ambient measurements of gaseous air pollutants by a network of six wireless multi-sensor miniature nodes that have been deployed in three urban sites, about 150 m apart. We demonstrate the network's capability to capture spatiotemporal concentration variations at an exceptional fine resolution but highlight the need for a frequent in-situ calibration to maintain the consistency of some sensors. Accordingly, a procedure for a field calibration is proposed and shown to improve the system's performance. Overall, our results support the compatibility of wireless distributed sensor networks for measuring urban air pollution at a sub-neighborhood spatial resolution, which suits the requirement for highly spatiotemporal resolved measurements at the breathing-height when assessing exposure to urban air pollution. Copyright © 2014 Elsevier B.V. All rights reserved.

Measuring NO, NO2, CO2 and O3 with low-cost sensors

NASA Astrophysics Data System (ADS)

Müller, Michael; Graf, Peter; Hüglin, Christoph

2017-04-01

Inexpensive sensors measuring ambient gas concentrations can be integrated in sensor units forming dense sensor networks. The utilized sensors have to be sufficiently accurate as the value of such networks directly depends on the information they provide. Thus, thorough testing of sensors before bringing them into service and the application of effective strategies for performance monitoring and adjustments during service are key elements for operating the low-cost sensors that are currently available on the market. We integrated several types of low-cost sensors into sensor units (Alphasense NO2 B4/B42F/B43F, Alphasense NO B4, SensAir CO2 LP8, Aeroqual O3 SM50), run them in the field next to instruments of air quality monitoring stations and performed tests in the laboratory. The poster summarizes our findings regarding the achieved sensor accuracy, methods to improve sensor performance as well as strategies to monitor the current state of the sensor (drifts, sensitivity) within a sensor network.

Resolving uncertainties in the urban air quality, climate, and vegetation nexus through citizen science, satellite imagery, and atmospheric modeling

NASA Astrophysics Data System (ADS)

Jenerette, D.; Wang, J.; Chandler, M.; Ripplinger, J.; Koutzoukis, S.; Ge, C.; Castro Garcia, L.; Kucera, D.; Liu, X.

2017-12-01

Large uncertainties remain in identifying the distribution of urban air quality and temperature risks across neighborhood to regional scales. Nevertheless, many cities are actively expanding vegetation with an expectation to moderate both climate and air quality risks. We address these uncertainties through an integrated analysis of satellite data, atmospheric modeling, and in-situ environmental sensor networks maintained by citizen scientists. During the summer of 2017 we deployed neighborhood-scale networks of air temperature and ozone sensors through three campaigns across urbanized southern California. During each five-week campaign we deployed six sensor nodes that included an EPA federal equivalent method ozone sensor and a suite of meteorological sensors. Each node was further embedded in a network of 100 air temperature sensors that combined a randomized design developed by the research team and a design co-created by citizen scientists. Between 20 and 60 citizen scientists were recruited for each campaign, with local partners supporting outreach and training to ensure consistent deployment and data gathering. We observed substantial variation in both temperature and ozone concentrations at scales less than 4km, whole city, and the broader southern California region. At the whole city scale the average spatial variation with our ozone sensor network just for city of Long Beach was 26% of the mean, while corresponding variation in air temperature was only 7% of the mean. These findings contrast with atmospheric model estimates of variation at the regional scale of 11% and 1%. Our results show the magnitude of fine-scale variation underestimated by current models and may also suggest scaling functions that can connect neighborhood and regional variation in both ozone and temperature risks in southern California. By engaging citizen science with high quality sensors, satellite data, and real-time forecasting, our results help identify magnitudes of climate and air quality risk variation across scales and can guide individual decisions and urban policies surrounding vegetation to moderate these risks.

Geographically distributed environmental sensor system

DOEpatents

French, Patrick; Veatch, Brad; O'Connor, Mike

2006-10-03

The present invention is directed to a sensor network that includes a number of sensor units and a base unit. The base station operates in a network discovery mode (in which network topology information is collected) in a data polling mode (in which sensed information is collected from selected sensory units). Each of the sensor units can include a number of features, including an anemometer, a rain gauge, a compass, a GPS receiver, a barometric pressure sensor, an air temperature sensor, a humidity sensor, a level, and a radiant temperature sensor.

Mapping urban air quality in near real-time using observations from low-cost sensors and model information.

PubMed

Schneider, Philipp; Castell, Nuria; Vogt, Matthias; Dauge, Franck R; Lahoz, William A; Bartonova, Alena

2017-09-01

The recent emergence of low-cost microsensors measuring various air pollutants has significant potential for carrying out high-resolution mapping of air quality in the urban environment. However, the data obtained by such sensors are generally less reliable than that from standard equipment and they are subject to significant data gaps in both space and time. In order to overcome this issue, we present here a data fusion method based on geostatistics that allows for merging observations of air quality from a network of low-cost sensors with spatial information from an urban-scale air quality model. The performance of the methodology is evaluated for nitrogen dioxide in Oslo, Norway, using both simulated datasets and real-world measurements from a low-cost sensor network for January 2016. The results indicate that the method is capable of producing realistic hourly concentration fields of urban nitrogen dioxide that inherit the spatial patterns from the model and adjust the prior values using the information from the sensor network. The accuracy of the data fusion method is dependent on various factors including the total number of observations, their spatial distribution, their uncertainty (both in terms of systematic biases and random errors), as well as the ability of the model to provide realistic spatial patterns of urban air pollution. A validation against official data from air quality monitoring stations equipped with reference instrumentation indicates that the data fusion method is capable of reproducing city-wide averaged official values with an R 2 of 0.89 and a root mean squared error of 14.3 μg m -3 . It is further capable of reproducing the typical daily cycles of nitrogen dioxide. Overall, the results indicate that the method provides a robust way of extracting useful information from uncertain sensor data using only a time-invariant model dataset and the knowledge contained within an entire sensor network. Copyright © 2017 The Authors. Published by Elsevier Ltd.. All rights reserved.

Outlier Detection in Urban Air Quality Sensor Networks.

PubMed

van Zoest, V M; Stein, A; Hoek, G

2018-01-01

Low-cost urban air quality sensor networks are increasingly used to study the spatio-temporal variability in air pollutant concentrations. Recently installed low-cost urban sensors, however, are more prone to result in erroneous data than conventional monitors, e.g., leading to outliers. Commonly applied outlier detection methods are unsuitable for air pollutant measurements that have large spatial and temporal variations as occur in urban areas. We present a novel outlier detection method based upon a spatio-temporal classification, focusing on hourly NO 2 concentrations. We divide a full year's observations into 16 spatio-temporal classes, reflecting urban background vs. urban traffic stations, weekdays vs. weekends, and four periods per day. For each spatio-temporal class, we detect outliers using the mean and standard deviation of the normal distribution underlying the truncated normal distribution of the NO 2 observations. Applying this method to a low-cost air quality sensor network in the city of Eindhoven, the Netherlands, we found 0.1-0.5% of outliers. Outliers could reflect measurement errors or unusual high air pollution events. Additional evaluation using expert knowledge is needed to decide on treatment of the identified outliers. We conclude that our method is able to detect outliers while maintaining the spatio-temporal variability of air pollutant concentrations in urban areas.

CitySpace Air Sensor Network Project Conducted to Test New Monitoring Capabilities

EPA Pesticide Factsheets

The CitySpace project is a new research effort by EPA to field test new, lower-cost air pollution sensors in a mid-sized city to understand how this emerging technology can add valuable information on air pollution patterns in neighboorhoods.

End-user perspective of low-cost sensors for outdoor air pollution monitoring.

PubMed

Rai, Aakash C; Kumar, Prashant; Pilla, Francesco; Skouloudis, Andreas N; Di Sabatino, Silvana; Ratti, Carlo; Yasar, Ansar; Rickerby, David

2017-12-31

Low-cost sensor technology can potentially revolutionise the area of air pollution monitoring by providing high-density spatiotemporal pollution data. Such data can be utilised for supplementing traditional pollution monitoring, improving exposure estimates, and raising community awareness about air pollution. However, data quality remains a major concern that hinders the widespread adoption of low-cost sensor technology. Unreliable data may mislead unsuspecting users and potentially lead to alarming consequences such as reporting acceptable air pollutant levels when they are above the limits deemed safe for human health. This article provides scientific guidance to the end-users for effectively deploying low-cost sensors for monitoring air pollution and people's exposure, while ensuring reasonable data quality. We review the performance characteristics of several low-cost particle and gas monitoring sensors and provide recommendations to end-users for making proper sensor selection by summarizing the capabilities and limitations of such sensors. The challenges, best practices, and future outlook for effectively deploying low-cost sensors, and maintaining data quality are also discussed. For data quality assurance, a two-stage sensor calibration process is recommended, which includes laboratory calibration under controlled conditions by the manufacturer supplemented with routine calibration checks performed by the end-user under final deployment conditions. For large sensor networks where routine calibration checks are impractical, statistical techniques for data quality assurance should be utilised. Further advancements and adoption of sophisticated mathematical and statistical techniques for sensor calibration, fault detection, and data quality assurance can indeed help to realise the promised benefits of a low-cost air pollution sensor network. Copyright © 2017 Elsevier B.V. All rights reserved.

A smart indoor air quality sensor network

NASA Astrophysics Data System (ADS)

Wen, Jin

2006-03-01

The indoor air quality (IAQ) has an important impact on public health. Currently, the indoor air pollution, caused by gas, particle, and bio-aerosol pollutants, is considered as the top five environmental risks to public health and has an estimated cost of $2 billion/year due to medical cost and lost productivity. Furthermore, current buildings are especially vulnerable for chemical and biological warfare (CBW) agent contamination because the central air conditioning and ventilation system serve as a nature carrier to spread the released agent from one location to the whole indoor environment within a short time period. To assure the IAQ and safety for either new or existing buildings, real time comprehensive IAQ and CBW measurements are needed. With the development of new sensing technologies, economic and reliable comprehensive IAQ and CBW sensors become promising. However, few studies exist that examine the design and evaluation issues related to IAQ and CBW sensor network. In this paper, relevant research areas including IAQ and CBW sensor development, demand control ventilation, indoor CBW sensor system design, and sensor system design for other areas such as water system protection, fault detection and diagnosis, are reviewed and summarized. Potential research opportunities for IAQ and CBW sensor system design and evaluation are discussed.

Technical report: The design and evaluation of a basin-scale wireless sensor network for mountain hydrology

NASA Astrophysics Data System (ADS)

Zhang, Ziran; Glaser, Steven D.; Bales, Roger C.; Conklin, Martha; Rice, Robert; Marks, Danny G.

2017-05-01

A network of sensors for spatially representative water-balance measurements was developed and deployed across the 2000 km2 snow-dominated portion of the upper American River basin, primarily to measure changes in snowpack and soil-water storage, air temperature, and humidity. This wireless sensor network (WSN) consists of 14 sensor clusters, each with 10 measurement nodes that were strategically placed within a 1 km2 area, across different elevations, aspects, slopes, and canopy covers. Compared to existing operational sensor installations, the WSN reduces hydrologic uncertainty in at least three ways. First, redundant measurements improved estimation of lapse rates for air and dew-point temperature. Second, distributed measurements captured local variability and constrained uncertainty in air and dew-point temperature, snow accumulation, and derived hydrologic attributes important for modeling and prediction. Third, the distributed relative-humidity measurements offer a unique capability to monitor upper-basin patterns in dew-point temperature and characterize elevation gradient of water vapor-pressure deficit across steep, variable topography. Network statistics during the first year of operation demonstrated that the WSN was robust for cold, wet, and windy conditions in the basin. The electronic technology used in the WSN-reduced adverse effects, such as high current consumption, multipath signal fading, and clock drift, seen in previous remote WSNs.

Wireless Distributed Environmental Sensor Networks for Air Pollution Measurement-The Promise and the Current Reality.

PubMed

Broday, David M

2017-10-02

The evaluation of the effects of air pollution on public health and human-wellbeing requires reliable data. Standard air quality monitoring stations provide accurate measurements of airborne pollutant levels, but, due to their sparse distribution, they cannot capture accurately the spatial variability of air pollutant concentrations within cities. Dedicated in-depth field campaigns have dense spatial coverage of the measurements but are held for relatively short time periods. Hence, their representativeness is limited. Moreover, the oftentimes integrated measurements represent time-averaged records. Recent advances in communication and sensor technologies enable the deployment of dense grids of Wireless Distributed Environmental Sensor Networks for air quality monitoring, yet their capability to capture urban-scale spatiotemporal pollutant patterns has not been thoroughly examined to date. Here, we summarize our studies on the practicalities of using data streams from sensor nodes for air quality measurement and the required methods to tune the results to different stakeholders and applications. We summarize the results from eight cities across Europe, five sensor technologies-three stationary (with one tested also while moving) and two personal sensor platforms, and eight ambient pollutants. Overall, few sensors showed an exceptional and consistent performance, which can shed light on the fine spatiotemporal urban variability of pollutant concentrations. Stationary sensor nodes were more reliable than personal nodes. In general, the sensor measurements tend to suffer from the interference of various environmental factors and require frequent calibrations. This calls for the development of suitable field calibration procedures, and several such in situ field calibrations are presented.

Wireless Distributed Environmental Sensor Networks for Air Pollution Measurement—The Promise and the Current Reality

PubMed Central

2017-01-01

The evaluation of the effects of air pollution on public health and human-wellbeing requires reliable data. Standard air quality monitoring stations provide accurate measurements of airborne pollutant levels, but, due to their sparse distribution, they cannot capture accurately the spatial variability of air pollutant concentrations within cities. Dedicated in-depth field campaigns have dense spatial coverage of the measurements but are held for relatively short time periods. Hence, their representativeness is limited. Moreover, the oftentimes integrated measurements represent time-averaged records. Recent advances in communication and sensor technologies enable the deployment of dense grids of Wireless Distributed Environmental Sensor Networks for air quality monitoring, yet their capability to capture urban-scale spatiotemporal pollutant patterns has not been thoroughly examined to date. Here, we summarize our studies on the practicalities of using data streams from sensor nodes for air quality measurement and the required methods to tune the results to different stakeholders and applications. We summarize the results from eight cities across Europe, five sensor technologies-three stationary (with one tested also while moving) and two personal sensor platforms, and eight ambient pollutants. Overall, few sensors showed an exceptional and consistent performance, which can shed light on the fine spatiotemporal urban variability of pollutant concentrations. Stationary sensor nodes were more reliable than personal nodes. In general, the sensor measurements tend to suffer from the interference of various environmental factors and require frequent calibrations. This calls for the development of suitable field calibration procedures, and several such in situ field calibrations are presented. PMID:28974042

A Low Cost High Density Sensor Network for Air Quality at London Heathrow Airport

NASA Astrophysics Data System (ADS)

Bright, V.; Mead, M. I.; Popoola, O. A.; Baron, R. P.; Saffell, J.; Stewart, G.; Kaye, P.; Jones, R.

2012-12-01

Atmospheric composition within urban areas has a direct effect on the air quality of an environment in which a large majority of people live and work. Atmospheric pollutants including ozone (O3), nitrogen dioxide (NO2), volatile organic compounds (VOCs) and particulate matter (PM) can have a significant effect on human health. As such it is important to determine the potential exposure of individuals to these atmospheric constituents and investigate the processes that lead to the degradation of air quality within the urban environment. Whilst modelled pollutant levels on the local scale often suggest high degrees of spatial and temporal variability, the relatively sparse fixed site automated urban networks only provide low spatial resolution data that do not appear adequate in detecting such small scale variability. In this paper we demonstrate that measurements can now be made using networks of low-cost sensors that utilise a variety of techniques, including electrochemical and optical, to measure concentrations of atmospheric species. Once equipped with GPS and GPRS to determine position and transmit data respectively, these networks have the potential to provide valuable insights into pollutant variability inherent on the local or micro-scale. The methodology has been demonstrated successfully in field campaigns carried out in cities including London and Valencia, and is now being deployed as part of the Sensor Networks for Air Quality currently deployed at London Heathrow airport (SNAQ-Heathrow) which is outlined in the partner paper presented by Mead et al. (this conference). The SNAQ-Heathrow network of 50 sensor nodes will provide an unprecedented data set that includes measurements of O3, NO, NO2, CO, CO2, SO2, total VOCs, size-speciated PM as well as meteorological variables that include temperature, relative humidity, wind speed and direction. This network will provide high temporal (20 second intervals) and spatial (50 sites within the airport area) resolution data over a 12 month period with data transmitted back to a server every 2 hours. In this paper we present the data capture and storage, data accessibility, data mining and visualisation techniques applied to the measurements of the SNAQ Heathrow high density sensor network, the preliminary results of which provide an insight into the potential use of such networks in characterising air quality, emissions and validating dispersion models on local scales. We also present a web based interface developed for the sensor network that allows users to access archived data and assess meteorological conditions, atmospheric dispersion, pollutant levels and emission rates.

Cooperative UAV-Based Communications Backbone for Sensor Networks

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

Roberts, R S

2001-10-07

The objective of this project is to investigate the use of unmanned air vehicles (UAVs) as mobile, adaptive communications backbones for ground-based sensor networks. In this type of network, the UAVs provide communication connectivity to sensors that cannot communicate with each other because of terrain, distance, or other geographical constraints. In these situations, UAVs provide a vertical communication path for the sensors, thereby mitigating geographic obstacles often imposed on networks. With the proper use of UAVs, connectivity to a widely disbursed sensor network in rugged terrain is readily achieved. Our investigation has focused on networks where multiple cooperating UAVs aremore » used to form a network backbone. The advantage of using multiple UAVs to form the network backbone is parallelization of sensor connectivity. Many widely spaced or isolated sensors can be connected to the network at once using this approach. In these networks, the UAVs logically partition the sensor network into sub-networks (subnets), with one UAV assigned per subnet. Partitioning the network into subnets allows the UAVs to service sensors in parallel thereby decreasing the sensor-to-network connectivity. A UAV services sensors in its subnet by flying a route (path) through the subnet, uplinking data collected by the sensors, and forwarding the data to a ground station. An additional advantage of using multiple UAVs in the network is that they provide redundancy in the communications backbone, so that the failure of a single UAV does not necessarily imply the loss of the network.« less

Community Air Sensor Network (CAIRSENSE) Project: Lower Cost, Continuous Ambient Monitoring Methods

EPA Pesticide Factsheets

CAIRSENSE Project presentation was given at the 108th Annual Meeting of the Air & Waste Management Associate in June 2015. The presentation provides an overview of the CAIRSENSE Project and general info about the sensors used in the CAIRSENSE Project.

Low-Cost Sensor Units for Measuring Urban Air Quality

NASA Astrophysics Data System (ADS)

Popoola, O. A.; Mead, M.; Stewart, G.; Hodgson, T.; McLoed, M.; Baldovi, J.; Landshoff, P.; Hayes, M.; Calleja, M.; Jones, R.

2010-12-01

Measurements of selected key air quality gases (CO, NO & NO2) have been made with a range of miniature low-cost sensors based on electrochemical gas sensing technology incorporating GPS and GPRS for position and communication respectively. Two types of simple to operate sensors units have been designed to be deployed in relatively large numbers. Mobile handheld sensor units designed for operation by members of the public have been deployed on numerous occasions including in Cambridge, London and Valencia. Static sensor units have also been designed for long-term autonomous deployment on existing street furniture. A study was recently completed in which 45 sensor units were deployed in the Cambridge area for a period of 3 months. Results from these studies indicate that air quality varies widely both spatially and temporally. The widely varying concentrations found suggest that the urban environment cannot be fully understood using limited static site (AURN) networks and that a higher resolution, more dispersed network is required to better define air quality in the urban environment. The results also suggest that higher spatial and temporal resolution measurements could improve knowledge of the levels of individual exposure in the urban environment.

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.

On Applicability of Network Coding Technique for 6LoWPAN-based Sensor Networks.

PubMed

Amanowicz, Marek; Krygier, Jaroslaw

2018-05-26

In this paper, the applicability of the network coding technique in 6LoWPAN-based sensor multihop networks is examined. The 6LoWPAN is one of the standards proposed for the Internet of Things architecture. Thus, we can expect the significant growth of traffic in such networks, which can lead to overload and decrease in the sensor network lifetime. The authors propose the inter-session network coding mechanism that can be implemented in resource-limited sensor motes. The solution reduces the overall traffic in the network, and in consequence, the energy consumption is decreased. Used procedures take into account deep header compressions of the native 6LoWPAN packets and the hop-by-hop changes of the header structure. Applied simplifications reduce signaling traffic that is typically occurring in network coding deployments, keeping the solution usefulness for the wireless sensor networks with limited resources. The authors validate the proposed procedures in terms of end-to-end packet delay, packet loss ratio, traffic in the air, total energy consumption, and network lifetime. The solution has been tested in a real wireless sensor network. The results confirm the efficiency of the proposed technique, mostly in delay-tolerant sensor networks.

Theory, Design, and Algorithms for Optimal Control of wireless Networks

DTIC Science & Technology

2010-06-09

The implementation of network-centric warfare technologies is an abiding, critical interest of Air Force Science and Technology efforts for the Warfighter. Wireless communications, strategic signaling are areas of critical Air Force Mission need. Autonomous networks of multiple, heterogeneous Throughput enhancement and robust connectivity in communications and sensor networks are critical factors in net-centric USAF operations. This research directly supports the Air Force vision of information dominance and the development of anywhere, anytime operational readiness.

Spatial and temporal trends from an air quality sensor network near a heavily trafficked intersection

NASA Astrophysics Data System (ADS)

Orlando, P.; Vo, D.; Giossi, C.; George, L.

2017-12-01

With the world-wide increase in urbanization and the increasing usage of combustion vehicles in urban areas, traffic-related air pollution is a growing health hazard. However, there are limited studies that examine the spatial and temporal impacts of traffic-related pollutants within cities. In particular, there are few studies that look at traffic management and its potential for pollution mitigation. In a previous study we examined roadway pollution and traffic parameters with one roadway station instrumented with standard measurement instruments. With the advent of low-cost air pollution sensors, we have expanded our work by observing multiple sites within a neighborhood to understand spatial and temporal exposures. We have deployed a high-density sensor network around urban arterial corridors in SE Portland, Oregon. This network consisted of ten nodes measuring CO, NO, NO2 and O3, and ten nodes measuring CO, CO2, VOC and PM2.5. The co-location of standard measurement instruments provided insight towards the utility of our low-cost sensor network, as the different nodes varied in cost, and potentially in quality. We have identified near-real-time temporal trends and local-scale spatial patterns during the summer of 2017. Meteorological and traffic data were included to further characterize these patterns, exploring the potential for pollution mitigation.

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.

Emerging Needs for Pervasive Passive Wireless Sensor Networks on Aerospace Vehicles

NASA Technical Reports Server (NTRS)

Wilson, William C.; Juarez, Peter D.

2014-01-01

NASA is investigating passive wireless sensor technology to reduce instrumentation mass and volume in ground testing, air flight, and space exploration applications. Vehicle health monitoring systems (VHMS) are desired on all aerospace programs to ensure the safety of the crew and the vehicles. Pervasive passive wireless sensor networks facilitate VHMS on aerospace vehicles. Future wireless sensor networks on board aerospace vehicles will be heterogeneous and will require active and passive network systems. Since much has been published on active wireless sensor networks, this work will focus on the need for passive wireless sensor networks on aerospace vehicles. Several passive wireless technologies such as microelectromechanical systems MEMS, SAW, backscatter, and chipless RFID techniques, have all shown potential to meet the pervasive sensing needs for aerospace VHMS applications. A SAW VHMS application will be presented. In addition, application areas including ground testing, hypersonic aircraft and spacecraft will be explored along with some of the harsh environments found in aerospace applications.

Integrating Metal-Oxide-Decorated CNT Networks with a CMOS Readout in a Gas Sensor

PubMed Central

Lee, Hyunjoong; Lee, Sanghoon; Kim, Dai-Hong; Perello, David; Park, Young June; Hong, Seong-Hyeon; Yun, Minhee; Kim, Suhwan

2012-01-01

We have implemented a tin-oxide-decorated carbon nanotube (CNT) network gas sensor system on a single die. We have also demonstrated the deposition of metallic tin on the CNT network, its subsequent oxidation in air, and the improvement of the lifetime of the sensors. The fabricated array of CNT sensors contains 128 sensor cells for added redundancy and increased accuracy. The read-out integrated circuit (ROIC) was combined with coarse and fine time-to-digital converters to extend its resolution in a power-efficient way. The ROIC is fabricated using a 0.35 μm CMOS process, and the whole sensor system consumes 30 mA at 5 V. The sensor system was successfully tested in the detection of ammonia gas at elevated temperatures. PMID:22736966

Fault Tolerant Computer Network Study

DTIC Science & Technology

1980-04-01

2. 1.2. 2 Air Data The air data function processes air pressures, temperature , and angle- of-attack measurements, and provides calibrated airspeed...attitude direction indicator. 2.1.5.2 Fixtaking Sensors used for fixtaking include the radar (in ground map mode), head- up display (for visual...VFR interdiction mission. The radar (ground map mode) is also the primary sensor at night and in adverse weather if the target presents a

Development of Light Powered Sensor Networks for Thermal Comfort Measurement

PubMed Central

Lee, Dasheng

2008-01-01

Recent technological advances in wireless communications have enabled easy installation of sensor networks with air conditioning equipment control applications. However, the sensor node power supply, through either power lines or battery power, still presents obstacles to the distribution of the sensing systems. In this study, a novel sensor network, powered by the artificial light, was constructed to achieve wireless power transfer and wireless data communications for thermal comfort measurements. The sensing node integrates an IC-based temperature sensor, a radiation thermometer, a relative humidity sensor, a micro machined flow sensor and a microprocessor for predicting mean vote (PMV) calculation. The 935 MHz band RF module was employed for the wireless data communication with a specific protocol based on a special energy beacon enabled mode capable of achieving zero power consumption during the inactive periods of the nodes. A 5W spotlight, with a dual axis tilt platform, can power the distributed nodes over a distance of up to 5 meters. A special algorithm, the maximum entropy method, was developed to estimate the sensing quantity of climate parameters if the communication module did not receive any response from the distributed nodes within a certain time limit. The light-powered sensor networks were able to gather indoor comfort-sensing index levels in good agreement with the comfort-sensing vote (CSV) preferred by a human being and the experimental results within the environment suggested that the sensing system could be used in air conditioning systems to implement a comfort-optimal control strategy. PMID:27873877

Hybridized electromagnetic-triboelectric nanogenerator for scavenging air-flow energy to sustainably power temperature sensors.

PubMed

Wang, Xue; Wang, Shuhua; Yang, Ya; Wang, Zhong Lin

2015-04-28

We report a hybridized nanogenerator with dimensions of 6.7 cm × 4.5 cm × 2 cm and a weight of 42.3 g that consists of two triboelectric nanogenerators (TENGs) and two electromagnetic generators (EMGs) for scavenging air-flow energy. Under an air-flow speed of about 18 m/s, the hybridized nanogenerator can deliver largest output powers of 3.5 mW for one TENG (in correspondence of power per unit mass/volume: 8.8 mW/g and 14.6 kW/m(3)) at a loading resistance of 3 MΩ and 1.8 mW for one EMG (in correspondence of power per unit mass/volume: 0.3 mW/g and 0.4 kW/m(3)) at a loading resistance of 2 kΩ, respectively. The hybridized nanogenerator can be utilized to charge a capacitor of 3300 μF to sustainably power four temperature sensors for realizing self-powered temperature sensor networks. Moreover, a wireless temperature sensor driven by a hybridized nanogenerator charged Li-ion battery can work well to send the temperature data to a receiver/computer at a distance of 1.5 m. This work takes a significant step toward air-flow energy harvesting and its potential applications in self-powered wireless sensor networks.

Matrix Factorisation-based Calibration For Air Quality Crowd-sensing

NASA Astrophysics Data System (ADS)

Dorffer, Clement; Puigt, Matthieu; Delmaire, Gilles; Roussel, Gilles; Rouvoy, Romain; Sagnier, Isabelle

2017-04-01

Internet of Things (IoT) is extending internet to physical objects and places. The internet-enabled objects are thus able to communicate with each other and with their users. One main interest of IoT is the ease of production of huge masses of data (Big Data) using distributed networks of connected objects, thus making possible a fine-grained yet accurate analysis of physical phenomena. Mobile crowdsensing is a way to collect data using IoT. It basically consists of acquiring geolocalized data from the sensors (from or connected to the mobile devices, e.g., smartphones) of a crowd of volunteers. The sensed data are then collectively shared using wireless connection—such as GSM or WiFi—and stored on a dedicated server to be processed. One major application of mobile crowdsensing is environment monitoring. Indeed, with the proliferation of miniaturized yet sensitive sensors on one hand and, on the other hand, of low-cost microcontrollers/single-card PCs, it is easy to extend the sensing abilities of smartphones. Alongside the conventional, regulated, bulky and expensive instruments used in authoritative air quality stations, it is then possible to create a large-scale mobile sensor network providing insightful information about air quality. In particular, the finer spatial sampling rate due to such a dense network should allow air quality models to take into account local effects such as street canyons. However, one key issue with low-cost air quality sensors is the lack of trust in the sensed data. In most crowdsensing scenarios, the sensors (i) cannot be calibrated in a laboratory before or during their deployment and (ii) might be sparsely or continuously faulty (thus providing outliers in the data). Such issues should be automatically handled from the sensor readings. Indeed, due to the masses of generated data, solving the above issues cannot be performed by experts but requires specific data processing techniques. In this work, we assume that some mobile sensors share some information using the APISENSE® crowdsensing platform and we aim to calibrate the sensor responses from the data directly. For that purpose, we express the sensor readings as a low-rank matrix with missing entries and we revisit self-calibration as a Matrix Factorization (MF) problem. In our proposed framework, one factor matrix contains the calibration parameters while the other is structured by the calibration model and contains some values of the sensed phenomenon. The MF calibration approach also uses the precise measurements from ATMO—the French public institution—to drive the calibration of the mobile sensors. MF calibration can be improved using, e.g., the mean calibration parameters provided by the sensor manufacturers, or using sparse priors or a model of the physical phenomenon. All our approaches are shown to provide a better calibration accuracy than matrix-completion-based and robust-regression-based methods, even in difficult scenarios involving a lot of missing data and/or very few accurate references. When combined with a dictionary of air quality patterns, our experiments suggest that MF is not only able to perform sensor network calibration but also to provide detailed maps of air quality.

Low-cost, high-density sensor network for urban emission monitoring: BEACO2N

NASA Astrophysics Data System (ADS)

Kim, J.; Shusterman, A.; Lieschke, K.; Newman, C.; Cohen, R. C.

2017-12-01

In urban environments, air quality is spatially and temporally heterogeneous as diverse emission sources create a high degree of variability even at the neighborhood scale. Conventional air quality monitoring relies on continuous measurements with limited spatial resolution or passive sampling with high-density and low temporal resolution. Either approach averages the air quality information over space or time and hinders our attempts to understand emissions, chemistry, and human exposure in the near-field of emission sources. To better capture the true spatio-temporal heterogeneity of urban conditions, we have deployed a low-cost, high-density air quality monitoring network in San Francisco Bay Area distributed at 2km horizontal spacing. The BErkeley Atmospheric CO2 Observation Network (BEACO2N) consists of approximately 50 sensor nodes, measuring CO2, CO, NO, NO2, O­3, and aerosol. Here we describe field-based calibration approaches that are consistent with the low-cost strategy of the monitoring network. Observations that allow inference of emission factors and identification of specific local emission sources will also be presented.

Wearable sensors for health monitoring

NASA Astrophysics Data System (ADS)

Suciu, George; Butca, Cristina; Ochian, Adelina; Halunga, Simona

2015-02-01

In this paper we describe several wearable sensors, designed for monitoring the health condition of the patients, based on an experimental model. Wearable sensors enable long-term continuous physiological monitoring, which is important for the treatment and management of many chronic illnesses, neurological disorders, and mental health issues. The system is based on a wearable sensors network, which is connected to a computer or smartphone. The wearable sensor network integrates several wearable sensors that can measure different parameters such as body temperature, heart rate and carbon monoxide quantity from the air. After the portable sensors measuring parameter values, they are transmitted by microprocessor through the Bluetooth to the application developed on computer or smartphone, to be interpreted.

CrossVit: enhancing canopy monitoring management practices in viticulture.

PubMed

Matese, Alessandro; Vaccari, Francesco Primo; Tomasi, Diego; Di Gennaro, Salvatore Filippo; Primicerio, Jacopo; Sabatini, Francesco; Guidoni, Silvia

2013-06-13

A new wireless sensor network (WSN), called CrossVit, and based on MEMSIC products, has been tested for two growing seasons in two vineyards in Italy. The aims are to evaluate the monitoring performances of the new WSN directly in the vineyard and collect air temperature, air humidity and solar radiation data to support vineyard management practices. The WSN consists of various levels: the Master/Gateway level coordinates the WSN and performs data aggregation; the Farm/Server level takes care of storing data on a server, data processing and graphic rendering; Nodes level is based on a network of peripheral nodes consisting of a MDA300 sensor board and Iris module and equipped with thermistors for air temperature, photodiodes for global and diffuse solar radiation, and an HTM2500LF sensor for relative humidity. The communication levels are: WSN links between gateways and sensor nodes by ZigBee, and long-range GSM/GPRS links between gateways and the server farm level. The system was able to monitor the agrometeorological parameters in the vineyard: solar radiation, air temperature and air humidity, detecting the differences between the canopy treatments applied. The performance of CrossVit, in terms of monitoring and reliability of the system, have been evaluated considering: its handiness, cost-effective, non-invasive dimensions and low power consumption.

CrossVit: Enhancing Canopy Monitoring Management Practices in Viticulture

PubMed Central

Matese, Alessandro; Vaccari, Francesco Primo; Tomasi, Diego; Di Gennaro, Salvatore Filippo; Primicerio, Jacopo; Sabatini, Francesco; Guidoni, Silvia

2013-01-01

A new wireless sensor network (WSN), called CrossVit, and based on MEMSIC products, has been tested for two growing seasons in two vineyards in Italy. The aims are to evaluate the monitoring performances of the new WSN directly in the vineyard and collect air temperature, air humidity and solar radiation data to support vineyard management practices. The WSN consists of various levels: the Master/Gateway level coordinates the WSN and performs data aggregation; the Farm/Server level takes care of storing data on a server, data processing and graphic rendering; Nodes level is based on a network of peripheral nodes consisting of a MDA300 sensor board and Iris module and equipped with thermistors for air temperature, photodiodes for global and diffuse solar radiation, and an HTM2500LF sensor for relative humidity. The communication levels are: WSN links between gateways and sensor nodes by ZigBee, and long-range GSM/GPRS links between gateways and the server farm level. The system was able to monitor the agrometeorological parameters in the vineyard: solar radiation, air temperature and air humidity, detecting the differences between the canopy treatments applied. The performance of CrossVit, in terms of monitoring and reliability of the system, have been evaluated considering: its handiness, cost-effective, non-invasive dimensions and low power consumption. PMID:23765273

Ubiquitous Sensor Networking for Development (USN4D): an application to pollution monitoring.

PubMed

Bagula, Antoine; Zennaro, Marco; Inggs, Gordon; Scott, Simon; Gascon, David

2012-01-01

This paper presents a new Ubiquitous Sensor Network (USN) Architecture to be used in developing countries and reveals its usefulness by highlighting some of its key features. In complement to a previous ITU proposal, our architecture referred to as "Ubiquitous Sensor Network for Development (USN4D)" integrates in its layers features such as opportunistic data dissemination, long distance deployment and localisation of information to meet the requirements of the developing world. Besides describing some of the most important requirements for the sensor equipment to be used in a USN4D setting, we present the main features and experiments conducted using the "WaspNet" as one of the wireless sensor deployment platforms that meets these requirements. Furthermore, building upon "WaspNet" platform, we present an application to Air pollution Monitoring in the city of Cape Town, in South Africa as one of the first steps towards building community wireless sensor networks (CSN) in the developing world using off-the-shelf sensor equipment.

Ubiquitous Sensor Networking for Development (USN4D): An Application to Pollution Monitoring

PubMed Central

Bagula, Antoine; Zennaro, Marco; Inggs, Gordon; Scott, Simon; Gascon, David

2012-01-01

This paper presents a new Ubiquitous Sensor Network (USN) Architecture to be used in developing countries and reveals its usefulness by highlighting some of its key features. In complement to a previous ITU proposal, our architecture referred to as “Ubiquitous Sensor Network for Development (USN4D)” integrates in its layers features such as opportunistic data dissemination, long distance deployment and localisation of information to meet the requirements of the developing world. Besides describing some of the most important requirements for the sensor equipment to be used in a USN4D setting, we present the main features and experiments conducted using the “WaspNet” as one of the wireless sensor deployment platforms that meets these requirements. Furthermore, building upon “WaspNet” platform, we present an application to Air pollution Monitoring in the city of Cape Town, in South Africa as one of the first steps towards building community wireless sensor networks (CSN) in the developing world using off-the-shelf sensor equipment. PMID:22368476

The BErkeley Atmospheric CO2 Observation Network: field calibration and evaluation of low-cost air quality sensors

NASA Astrophysics Data System (ADS)

Kim, Jinsol; Shusterman, Alexis A.; Lieschke, Kaitlyn J.; Newman, Catherine; Cohen, Ronald C.

2018-04-01

The newest generation of air quality sensors is small, low cost, and easy to deploy. These sensors are an attractive option for developing dense observation networks in support of regulatory activities and scientific research. They are also of interest for use by individuals to characterize their home environment and for citizen science. However, these sensors are difficult to interpret. Although some have an approximately linear response to the target analyte, that response may vary with time, temperature, and/or humidity, and the cross-sensitivity to non-target analytes can be large enough to be confounding. Standard approaches to calibration that are sufficient to account for these variations require a quantity of equipment and labor that negates the attractiveness of the sensors' low cost. Here we describe a novel calibration strategy for a set of sensors, including CO, NO, NO2, and O3, that makes use of (1) multiple co-located sensors, (2) a priori knowledge about the chemistry of NO, NO2, and O3, (3) an estimate of mean emission factors for CO, and (4) the global background of CO. The strategy requires one or more well calibrated anchor points within the network domain, but it does not require direct calibration of any of the individual low-cost sensors. The procedure nonetheless accounts for temperature and drift, in both the sensitivity and zero offset. We demonstrate this calibration on a subset of the sensors comprising BEACO2N, a distributed network of approximately 50 sensor nodes, each measuring CO2, CO, NO, NO2, O3 and particulate matter at 10 s time resolution and approximately 2 km spacing within the San Francisco Bay Area.

Mobile Sensors and Applications for Air Pollutants

EPA Science Inventory

Executive Summary The public has long been interested in understanding what pollutants are in the air they breathe so they can best protect their environmental health and welfare. The current air quality monitoring network consists of discrete stations with expensive equipment ...

Calibration of low-cost gas sensors for an urban air quality monitoring network

NASA Astrophysics Data System (ADS)

Scott, A.; Kelley, C.; He, C.; Ghugare, P.; Lehman, A.; Benish, S.; Stratton, P.; Dickerson, R. R.; Zuidema, C.; Azdoud, Y.; Ren, X.

2017-12-01

In a warming world, environmental pollution may be exacerbated by anthropogenic activities, such as climate change and the urban heat island effect, as well as natural phenomena such as heat waves. However, monitoring air pollution at federal reference standards (approximately 1 part per billion or ppb for ambient ozone) is cost-prohibitive in heterogeneous urban areas as many expensive devices are required to fully capture a region's geo-spatial variability. Innovation in low-cost sensors provide a potential solution, yet technical challenges remain to overcome possible imprecision in the data. We present the calibrations of ozone and nitrous dioxide from a low-cost air quality monitoring device designed for the Baltimore Open Air Project. The sensors used in this study are commercially available thin film electrochemical sensors from SPEC Sensor, which are amperometric, meaning they generate current proportional to volumetric fraction of gas. The results of sensor calibrations in the laboratory and field are presented.

Unattended wireless proximity sensor networks for counterterrorism, force protection, littoral environments, PHM, and tamper monitoring ground applications

NASA Astrophysics Data System (ADS)

Forcier, Bob

2003-09-01

This paper describes a digital-ultrasonic ground network, which forms an unique "unattended mote sensor system" for monitoring the environment, personnel, facilities, vehicles, power generation systems or aircraft in Counter-Terrorism, Force Protection, Prognostic Health Monitoring (PHM) and other ground applications. Unattended wireless smart sensor/tags continuously monitor the environment and provide alerts upon changes or disruptions to the environment. These wireless smart sensor/tags are networked utilizing ultrasonic wireless motes, hybrid RF/Ultrasonic Network Nodes and Base Stations. The network is monitored continuously with a 24/7 remote and secure monitoring system. This system utilizes physical objects such as a vehicle"s structure or a building to provide the media for two way secure communication of key metrics and sensor data and eliminates the "blind spots" that are common in RF solutions because of structural elements of buildings, etc. The digital-ultrasonic sensors have networking capability and a 32-bit identifier, which provide a platform for a robust data acquisition (DAQ) for a large amount of sensors. In addition, the network applies a unique "signature" of the environment by comparing sensor-to-sensor data to pick up on minute changes, which would signal an invasion of unknown elements or signal a potential tampering in equipment or facilities. The system accommodates satellite and other secure network uplinks in either RF or UWB protocols. The wireless sensors can be dispersed by ground or air maneuvers. In addition, the sensors can be incorporated into the structure or surfaces of vehicles, buildings, or clothing of field personnel.

Process for manufacture of thick film hydrogen sensors

DOEpatents

Perdieu, Louisa H.

2000-09-09

A thick film process for producing hydrogen sensors capable of sensing down to a one percent concentration of hydrogen in carrier gasses such as argon, nitrogen, and air. The sensor is also suitable to detect hydrogen gas while immersed in transformer oil. The sensor includes a palladium resistance network thick film printed on a substrate, a portion of which network is coated with a protective hydrogen barrier. The process utilizes a sequence of printing of the requisite materials on a non-conductive substrate with firing temperatures at each step which are less than or equal to the temperature at the previous step.

Node-to-node field calibration of wireless distributed air pollution sensor network.

PubMed

Kizel, Fadi; Etzion, Yael; Shafran-Nathan, Rakefet; Levy, Ilan; Fishbain, Barak; Bartonova, Alena; Broday, David M

2018-02-01

Low-cost air quality sensors offer high-resolution spatiotemporal measurements that can be used for air resources management and exposure estimation. Yet, such sensors require frequent calibration to provide reliable data, since even after a laboratory calibration they might not report correct values when they are deployed in the field, due to interference with other pollutants, as a result of sensitivity to environmental conditions and due to sensor aging and drift. Field calibration has been suggested as a means for overcoming these limitations, with the common strategy involving periodical collocations of the sensors at an air quality monitoring station. However, the cost and complexity involved in relocating numerous sensor nodes back and forth, and the loss of data during the repeated calibration periods make this strategy inefficient. This work examines an alternative approach, a node-to-node (N2N) calibration, where only one sensor in each chain is directly calibrated against the reference measurements and the rest of the sensors are calibrated sequentially one against the other while they are deployed and collocated in pairs. The calibration can be performed multiple times as a routine procedure. This procedure minimizes the total number of sensor relocations, and enables calibration while simultaneously collecting data at the deployment sites. We studied N2N chain calibration and the propagation of the calibration error analytically, computationally and experimentally. The in-situ N2N calibration is shown to be generic and applicable for different pollutants, sensing technologies, sensor platforms, chain lengths, and sensor order within the chain. In particular, we show that chain calibration of three nodes, each calibrated for a week, propagate calibration errors that are similar to those found in direct field calibration. Hence, N2N calibration is shown to be suitable for calibration of distributed sensor networks. Copyright © 2017 Elsevier Ltd. All rights reserved.

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

CityAir app: Mapping air-quality perception using people as sensors

NASA Astrophysics Data System (ADS)

Castell, Nuria; Fredriksen, Mirjam; Cole-Hunter, Thomas; Robinson, Johanna; Keune, Hans; Nieuwenhuijsen, Mark; Bartonova, Alena

2016-04-01

Outdoor air pollution is a major environmental health problem affecting all people in developed and developing countries alike. Ambient (outdoor) air pollution in both cities and rural areas was estimated to cause 3.7 million premature deaths worldwide in 2012. In modern society, people are expending an increasing amount of time in polluted urban environments, thus increasing their exposure and associated health responses. Some cities provide information about air pollution levels to their citizens using air quality monitoring networks. However, due to their high cost and maintenance, the density of the monitoring networks is very low and not capable to capture the high temporal and spatial variability of air pollution. Thus, the citizen lacks a specific answer to the question of "how the air quality is in our surroundings". In the framework of the EU-funded CITI-SENSE project the innovative concept of People as Sensors is being applied to the field of outdoor air pollution. This is being done in eight European cities, including Barcelona, Belgrade, Edinburgh, Haifa, Ljubljana, Oslo, Ostrava and Vienna. People as Sensors defines a measurement model, in which measurements are not only taken by hardware sensors, but in which also humans can contribute with their individual "measurements" such as their subjective perception of air quality and other personal observations. In order to collect the personal observations a mobile app, CityAir, has been developed. CityAir allows citizens to rate the air quality in their surroundings with colour at their current location: green if air quality is very good, yellow if air quality is good, orange if air quality is poor and red if air quality is very poor. The users have also the possibility of indicating the source of pollution (i.e. traffic, industry, wood burning) and writing a comment. The information is on-line and accessible for other app users, thus contributing to create an air-quality map based on citizens' perception. Currently, 400 + Android OS and 180+ iOS smartphone users in 12+ countries have downloaded, installed and used CityAir. The central advantage of the People as Sensors approach is that it can complement costly physical sensor networks. The observations made in smartphones are shared and other persons can consult those to take decisions as for instance choosing a cleaner route to bicycle to work or avoid exercising in certain areas that day. The drawbacks are limited comparability and interpretability, and the inherent uncertainty. CityAir can be seen as a democratic platform for empowering citizens to contribute to environmental governance, facilitating the communication between the citizen and the decision makers. Citizens are encouraged to participate in sharing their perception on the air quality in their city. Citizens become agents of change by uncovering and sharing their perception of air quality in a place that matters to them. We discuss the current challenges: how to involve citizens in the use of the app and how to communicate and visualize the information in a way that is useful for the citizens; point out possible solutions, and pin-point directions for future research.

Energy Harvesting Chip and the Chip Based Power Supply Development for a Wireless Sensor Network.

PubMed

Lee, Dasheng

2008-12-02

In this study, an energy harvesting chip was developed to scavenge energy from artificial light to charge a wireless sensor node. The chip core is a miniature transformer with a nano-ferrofluid magnetic core. The chip embedded transformer can convert harvested energy from its solar cell to variable voltage output for driving multiple loads. This chip system yields a simple, small, and more importantly, a battery-less power supply solution. The sensor node is equipped with multiple sensors that can be enabled by the energy harvesting power supply to collect information about the human body comfort degree. Compared with lab instruments, the nodes with temperature, humidity and photosensors driven by harvested energy had variation coefficient measurement precision of less than 6% deviation under low environmental light of 240 lux. The thermal comfort was affected by the air speed. A flow sensor equipped on the sensor node was used to detect airflow speed. Due to its high power consumption, this sensor node provided 15% less accuracy than the instruments, but it still can meet the requirement of analysis for predicted mean votes (PMV) measurement. The energy harvesting wireless sensor network (WSN) was deployed in a 24-hour convenience store to detect thermal comfort degree from the air conditioning control. During one year operation, the sensor network powered by the energy harvesting chip retained normal functions to collect the PMV index of the store. According to the one month statistics of communication status, the packet loss rate (PLR) is 2.3%, which is as good as the presented results of those WSNs powered by battery. Referring to the electric power records, almost 54% energy can be saved by the feedback control of an energy harvesting sensor network. These results illustrate that, scavenging energy not only creates a reliable power source for electronic devices, such as wireless sensor nodes, but can also be an energy source by building an energy efficient program.

Energy Harvesting Chip and the Chip Based Power Supply Development for a Wireless Sensor Network

PubMed Central

Lee, Dasheng

2008-01-01

In this study, an energy harvesting chip was developed to scavenge energy from artificial light to charge a wireless sensor node. The chip core is a miniature transformer with a nano-ferrofluid magnetic core. The chip embedded transformer can convert harvested energy from its solar cell to variable voltage output for driving multiple loads. This chip system yields a simple, small, and more importantly, a battery-less power supply solution. The sensor node is equipped with multiple sensors that can be enabled by the energy harvesting power supply to collect information about the human body comfort degree. Compared with lab instruments, the nodes with temperature, humidity and photosensors driven by harvested energy had variation coefficient measurement precision of less than 6% deviation under low environmental light of 240 lux. The thermal comfort was affected by the air speed. A flow sensor equipped on the sensor node was used to detect airflow speed. Due to its high power consumption, this sensor node provided 15% less accuracy than the instruments, but it still can meet the requirement of analysis for predicted mean votes (PMV) measurement. The energy harvesting wireless sensor network (WSN) was deployed in a 24-hour convenience store to detect thermal comfort degree from the air conditioning control. During one year operation, the sensor network powered by the energy harvesting chip retained normal functions to collect the PMV index of the store. According to the one month statistics of communication status, the packet loss rate (PLR) is 2.3%, which is as good as the presented results of those WSNs powered by battery. Referring to the electric power records, almost 54% energy can be saved by the feedback control of an energy harvesting sensor network. These results illustrate that, scavenging energy not only creates a reliable power source for electronic devices, such as wireless sensor nodes, but can also be an energy source by building an energy efficient program. PMID:27873953

Respirable particulate monitoring with remote sensors. (Public health ecology: Air pollution)

NASA Technical Reports Server (NTRS)

Severs, R. K.

1974-01-01

The feasibility of monitoring atmospheric aerosols in the respirable range from air or space platforms was studied. Secondary reflectance targets were located in the industrial area and near Galveston Bay. Multichannel remote sensor data were utilized to calculate the aerosol extinction coefficient and thus determine the aerosol size distribution. Houston Texas air sampling network high volume data were utilized to generate computer isopleth maps of suspended particulates and to establish the mass loading of the atmosphere. In addition, a five channel nephelometer and a multistage particulate air sampler were used to collect data. The extinction coefficient determined from remote sensor data proved more representative of wide areal phenomena than that calculated from on site measurements. It was also demonstrated that a significant reduction in the standard deviation of the extinction coefficient could be achieved by reducing the bandwidths used in remote sensor.

Aircraft Aerodynamic Parameter Detection Using Micro Hot-Film Flow Sensor Array and BP Neural Network Identification

PubMed Central

Que, Ruiyi; Zhu, Rong

2012-01-01

Air speed, angle of sideslip and angle of attack are fundamental aerodynamic parameters for controlling most aircraft. For small aircraft for which conventional detecting devices are too bulky and heavy to be utilized, a novel and practical methodology by which the aerodynamic parameters are inferred using a micro hot-film flow sensor array mounted on the surface of the wing is proposed. A back-propagation neural network is used to model the coupling relationship between readings of the sensor array and aerodynamic parameters. Two different sensor arrangements are tested in wind tunnel experiments and dependence of the system performance on the sensor arrangement is analyzed. PMID:23112638

Aircraft aerodynamic parameter detection using micro hot-film flow sensor array and BP neural network identification.

PubMed

Que, Ruiyi; Zhu, Rong

2012-01-01

Air speed, angle of sideslip and angle of attack are fundamental aerodynamic parameters for controlling most aircraft. For small aircraft for which conventional detecting devices are too bulky and heavy to be utilized, a novel and practical methodology by which the aerodynamic parameters are inferred using a micro hot-film flow sensor array mounted on the surface of the wing is proposed. A back-propagation neural network is used to model the coupling relationship between readings of the sensor array and aerodynamic parameters. Two different sensor arrangements are tested in wind tunnel experiments and dependence of the system performance on the sensor arrangement is analyzed.

Classifying Sources Influencing Indoor Air Quality (IAQ) Using Artificial Neural Network (ANN)

PubMed Central

Mad Saad, Shaharil; Melvin Andrew, Allan; Md Shakaff, Ali Yeon; Mohd Saad, Abdul Rahman; Muhamad Yusof @ Kamarudin, Azman; Zakaria, Ammar

2015-01-01

Monitoring indoor air quality (IAQ) is deemed important nowadays. A sophisticated IAQ monitoring system which could classify the source influencing the IAQ is definitely going to be very helpful to the users. Therefore, in this paper, an IAQ monitoring system has been proposed with a newly added feature which enables the system to identify the sources influencing the level of IAQ. In order to achieve this, the data collected has been trained with artificial neural network or ANN—a proven method for pattern recognition. Basically, the proposed system consists of sensor module cloud (SMC), base station and service-oriented client. The SMC contain collections of sensor modules that measure the air quality data and transmit the captured data to base station through wireless network. The IAQ monitoring system is also equipped with IAQ Index and thermal comfort index which could tell the users about the room’s conditions. The results showed that the system is able to measure the level of air quality and successfully classify the sources influencing IAQ in various environments like ambient air, chemical presence, fragrance presence, foods and beverages and human activity. PMID:26007724

A Wireless Sensor Network for Vineyard Monitoring That Uses Image Processing

PubMed Central

Lloret, Jaime; Bosch, Ignacio; Sendra, Sandra; Serrano, Arturo

2011-01-01

The first step to detect when a vineyard has any type of deficiency, pest or disease is to observe its stems, its grapes and/or its leaves. To place a sensor in each leaf of every vineyard is obviously not feasible in terms of cost and deployment. We should thus look for new methods to detect these symptoms precisely and economically. In this paper, we present a wireless sensor network where each sensor node takes images from the field and internally uses image processing techniques to detect any unusual status in the leaves. This symptom could be caused by a deficiency, pest, disease or other harmful agent. When it is detected, the sensor node sends a message to a sink node through the wireless sensor network in order to notify the problem to the farmer. The wireless sensor uses the IEEE 802.11 a/b/g/n standard, which allows connections from large distances in open air. This paper describes the wireless sensor network design, the wireless sensor deployment, how the node processes the images in order to monitor the vineyard, and the sensor network traffic obtained from a test bed performed in a flat vineyard in Spain. Although the system is not able to distinguish between deficiency, pest, disease or other harmful agents, a symptoms image database and a neuronal network could be added in order learn from the experience and provide an accurate problem diagnosis. PMID:22163948

A wireless sensor network for vineyard monitoring that uses image processing.

PubMed

Lloret, Jaime; Bosch, Ignacio; Sendra, Sandra; Serrano, Arturo

2011-01-01

The first step to detect when a vineyard has any type of deficiency, pest or disease is to observe its stems, its grapes and/or its leaves. To place a sensor in each leaf of every vineyard is obviously not feasible in terms of cost and deployment. We should thus look for new methods to detect these symptoms precisely and economically. In this paper, we present a wireless sensor network where each sensor node takes images from the field and internally uses image processing techniques to detect any unusual status in the leaves. This symptom could be caused by a deficiency, pest, disease or other harmful agent. When it is detected, the sensor node sends a message to a sink node through the wireless sensor network in order to notify the problem to the farmer. The wireless sensor uses the IEEE 802.11 a/b/g/n standard, which allows connections from large distances in open air. This paper describes the wireless sensor network design, the wireless sensor deployment, how the node processes the images in order to monitor the vineyard, and the sensor network traffic obtained from a test bed performed in a flat vineyard in Spain. Although the system is not able to distinguish between deficiency, pest, disease or other harmful agents, a symptoms image database and a neuronal network could be added in order learn from the experience and provide an accurate problem diagnosis.

Empirical downscaling of daily minimum air temperature at very fine resolutions in complex terrain

Treesearch

Zachary A. Holden; John T. Abatzoglou; Charles H. Luce; L. Scott Baggett

2011-01-01

Available air temperature models do not adequately account for the influence of terrain on nocturnal air temperatures. An empirical model for night time air temperatures was developed using a network of one hundred and forty inexpensive temperature sensors deployed across the Bitterroot National Forest, Montana. A principle component analysis (PCA) on minimum...

Seluge++: A Secure Over-the-Air Programming Scheme in Wireless Sensor Networks

PubMed Central

Doroodgar, Farzan; Razzaque, Mohammad Abdur; Isnin, Ismail Fauzi

2014-01-01

Over-the-air dissemination of code updates in wireless sensor networks have been researchers' point of interest in the last few years, and, more importantly, security challenges toward the remote propagation of code updating have occupied the majority of efforts in this context. Many security models have been proposed to establish a balance between the energy consumption and security strength, having their concentration on the constrained nature of wireless sensor network (WSN) nodes. For authentication purposes, most of them have used a Merkle hash tree to avoid using multiple public cryptography operations. These models mostly have assumed an environment in which security has to be at a standard level. Therefore, they have not investigated the tree structure for mission-critical situations in which security has to be at the maximum possible level (e.g., military applications, healthcare). Considering this, we investigate existing security models used in over-the-air dissemination of code updates for possible vulnerabilities, and then, we provide a set of countermeasures, correspondingly named Security Model Requirements. Based on the investigation, we concentrate on Seluge, one of the existing over-the-air programming schemes, and we propose an improved version of it, named Seluge++, which complies with the Security Model Requirements and replaces the use of the inefficient Merkle tree with a novel method. Analytical and simulation results show the improvements in Seluge++ compared to Seluge. PMID:24618781

Seluge++: a secure over-the-air programming scheme in wireless sensor networks.

PubMed

Doroodgar, Farzan; Abdur Razzaque, Mohammad; Isnin, Ismail Fauzi

2014-03-11

Over-the-air dissemination of code updates in wireless sensor networks have been researchers' point of interest in the last few years, and, more importantly, security challenges toward the remote propagation of code updating have occupied the majority of efforts in this context. Many security models have been proposed to establish a balance between the energy consumption and security strength, having their concentration on the constrained nature of wireless sensor network (WSN) nodes. For authentication purposes, most of them have used a Merkle hash tree to avoid using multiple public cryptography operations. These models mostly have assumed an environment in which security has to be at a standard level. Therefore, they have not investigated the tree structure for mission-critical situations in which security has to be at the maximum possible level (e.g., military applications, healthcare). Considering this, we investigate existing security models used in over-the-air dissemination of code updates for possible vulnerabilities, and then, we provide a set of countermeasures, correspondingly named Security Model Requirements. Based on the investigation, we concentrate on Seluge, one of the existing over-the-air programming schemes, and we propose an improved version of it, named Seluge++, which complies with the Security Model Requirements and replaces the use of the inefficient Merkle tree with a novel method. Analytical and simulation results show the improvements in Seluge++ compared to Seluge.

Integrated Air and Missile Defense (IAMD)

DTIC Science & Technology

2015-12-01

equal to or greater than the effectiveness levels of fielded TBM and CM/ABT defense systems. Common Command and Control The Army IAMD SoS common C2...externally developed sensors and shooters to provide an effective IAMD capability. The IAMD program will allow transformation to a network-centric system of...systems capability, also referred to as "Plug and Fight", that integrates all Air and Missile Defense (AMD) sensors, weapons, and mission control

Mountainous Ecosystem Sensor Array (MESA): a mesh sensor network for climate change research in remote mountainous environments

NASA Astrophysics Data System (ADS)

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

2013-12-01

Developing sensor networks robust enough to perform unattended in the world's remote regions is critical since these regions serve as important benchmarks that lack anthropogenic influence. Paradoxically, the factors that make these remote, natural sites challenging for sensor networking are often what make them indispensable for climate change research. The MESA (Mountainous Ecosystem Sensor Array) project has faced these challenges and developed a wireless mesh sensor network across a 660 m topoclimatic gradient in a wilderness area in central Idaho. This sensor array uses advances in sensing, networking, and power supply technologies to provide near real-time synchronized data covering a suite of biophysical parameters used in ecosystem process models. The 76 sensors in the network 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, and leaf wetness at synchronized time intervals ranging from two minutes to two hours and spatial scales from a few meters to two kilometers. We present our novel methods of placing sensors and network nodes above, below, and throughout the forest canopy without using meteorological towers. In addition, we explain our decision to use different forms of power (wind and solar) and the equipment we use to control and integrate power harvesting. Further, we describe our use of the network to sense and quantify its own power use. Using examples of environmental data from the project, we discuss how these data may be used to increase our understanding of the effects of climate change on ecosystem processes in mountainous environments. MESA sensor locations across a 700 m topoclimatic gradient at the University of Idaho Taylor Wilderness Research Station.

The deployment of carbon monoxide wireless sensor network (CO-WSN) for ambient air monitoring.

PubMed

Chaiwatpongsakorn, Chaichana; Lu, Mingming; Keener, Tim C; Khang, Soon-Jai

2014-06-16

Wireless sensor networks are becoming increasingly important as an alternative solution for environment monitoring because they can reduce cost and complexity. Also, they can improve reliability and data availability in places where traditional monitoring methods are difficult to site. In this study, a carbon monoxide wireless sensor network (CO-WSN) was developed to measure carbon monoxide concentrations at a major traffic intersection near the University of Cincinnati main campus. The system has been deployed over two weeks during Fall 2010, and Summer 2011-2012, traffic data was also recorded by using a manual traffic counter and a video camcorder to characterize vehicles at the intersection 24 h, particularly, during the morning and evening peak hour periods. According to the field test results, the 1 hr-average CO concentrations were found to range from 0.1-1.0 ppm which is lower than the National Ambient Air Quality Standards (NAAQS) 35 ppm on a one-hour averaging period. During rush hour periods, the traffic volume at the intersection varied from 2,067 to 3,076 vehicles per hour with 97% being passenger vehicles. Furthermore, the traffic volume based on a 1-h average showed good correlation (R2 = 0.87) with the 1-h average CO-WSN concentrations for morning and evening peak time periods whereas CO-WSN results provided a moderate correlation (R2 = 0.42) with 24 hours traffic volume due to fluctuated changes of meteorological conditions. It is concluded that the performance and the reliability of wireless ambient air monitoring networks can be used as an alternative method for real time air monitoring.

A Modular Plug-And-Play Sensor System for Urban Air Pollution Monitoring: Design, Implementation and Evaluation.

PubMed

Yi, Wei-Ying; Leung, Kwong-Sak; Leung, Yee

2017-12-22

Urban air pollution has caused public concern globally because it seriously affects human life. Modern monitoring systems providing pollution information with high spatio-temporal resolution have been developed to identify personal exposures. However, these systems' hardware specifications and configurations are usually fixed according to the applications. They can be inconvenient to maintain, and difficult to reconfigure and expand with respect to sensing capabilities. This paper aims at tackling these issues by adopting the proposed Modular Sensor System (MSS) architecture and Universal Sensor Interface (USI), and modular design in a sensor node. A compact MSS sensor node is implemented and evaluated. It has expandable sensor modules with plug-and-play feature and supports multiple Wireless Sensor Networks (WSNs). Evaluation results show that MSS sensor nodes can easily fit in different scenarios, adapt to reconfigurations dynamically, and detect low concentration air pollution with high energy efficiency and good data accuracy. We anticipate that the efforts on system maintenance, adaptation, and evolution can be significantly reduced when deploying the system in the field.

A Modular Plug-And-Play Sensor System for Urban Air Pollution Monitoring: Design, Implementation and Evaluation

PubMed Central

2017-01-01

Urban air pollution has caused public concern globally because it seriously affects human life. Modern monitoring systems providing pollution information with high spatio-temporal resolution have been developed to identify personal exposures. However, these systems’ hardware specifications and configurations are usually fixed according to the applications. They can be inconvenient to maintain, and difficult to reconfigure and expand with respect to sensing capabilities. This paper aims at tackling these issues by adopting the proposed Modular Sensor System (MSS) architecture and Universal Sensor Interface (USI), and modular design in a sensor node. A compact MSS sensor node is implemented and evaluated. It has expandable sensor modules with plug-and-play feature and supports multiple Wireless Sensor Networks (WSNs). Evaluation results show that MSS sensor nodes can easily fit in different scenarios, adapt to reconfigurations dynamically, and detect low concentration air pollution with high energy efficiency and good data accuracy. We anticipate that the efforts on system maintenance, adaptation, and evolution can be significantly reduced when deploying the system in the field. PMID:29271952

DexterNet: An Open Platform for Heterogeneous Body Sensor Networks and Its Applications

DTIC Science & Technology

2008-12-19

motion, ECG PC, PDA 802.15.4 No No ALARM-NET pulse oximetry STARGATE Bluetooth No Yes [19] motion, ECG PDA, PC 802.11 (temperature, light, PIR) DexterNet...motion, ECG PDA 802.15.4 Yes Possible via SPINE EIP, GPS PC (e.g., air pollution sensor) MICAz, SHIMMER uses MICAz sensors and STARGATE to relay the

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

PubMed

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

2017-03-20

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

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

PubMed Central

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

2017-01-01

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

WSN based indoor air quality monitoring in classrooms

NASA Astrophysics Data System (ADS)

Wang, S. K.; Chew, S. P.; Jusoh, M. T.; Khairunissa, A.; Leong, K. Y.; Azid, A. A.

2017-03-01

Indoor air quality monitoring is essential as the human health is directly affected by indoor air quality. This paper presents the investigations of the impact of undergraduate students' concentration during lecture due to the indoor air quality in classroom. Three environmental parameters such as temperature, relative humidity and concentration of carbon dioxide are measured using wireless sensor network based air quality monitoring system. This simple yet reliable system is incorporated with DHT-11 and MG-811 sensors. Two classrooms were selected to install the monitoring system. The level of indoor air quality were measured and students' concentration was assessed using intelligent test during normal lecturing section. The test showed significant correlation between the collected environmental parameters and the students' level of performances in their study.

Community Air Sensor Network Project: Lower Cost, Continuous Ambient Monitoring Methods

EPA Science Inventory

This is an extended abstract that will be part of the peer-reviewed proceedings of the AWMA annual meeting in 2015. The extended abstract covers preliminary results from the CAIRSENSE project, which involves testing low cost sensors at an NCore site in Atlanta, GA.

Real-time indoor monitoring system based on wireless sensor networks

NASA Astrophysics Data System (ADS)

Wu, Zhengzhong; Liu, Zilin; Huang, Xiaowei; Liu, Jun

2008-10-01

Wireless sensor networks (WSN) greatly extend our ability to monitor and control the physical world. It can collaborate and aggregate a huge amount of sensed data to provide continuous and spatially dense observation of environment. The control and monitoring of indoor atmosphere conditions represents an important task with the aim of ensuring suitable working and living spaces to people. However, the comprehensive air quality, which includes monitoring of humidity, temperature, gas concentrations, etc., is not so easy to be monitored and controlled. In this paper an indoor WSN monitoring system was developed. In the system several sensors such as temperature sensor, humidity sensor, gases sensor, were built in a RF transceiver board for monitoring indoor environment conditions. The indoor environmental monitoring parameters can be transmitted by wireless to database server and then viewed throw PC or PDA accessed to the local area networks by administrators. The system, which was also field-tested and showed a reliable and robust characteristic, is significant and valuable to people.

Development and field validation of a community-engaged particulate matter air quality monitoring network in Imperial, California, USA.

PubMed

Carvlin, Graeme N; Lugo, Humberto; Olmedo, Luis; Bejarano, Ester; Wilkie, Alexa; Meltzer, Dan; Wong, Michelle; King, Galatea; Northcross, Amanda; Jerrett, Michael; English, Paul B; Hammond, Donald; Seto, Edmund

2017-12-01

The Imperial County Community Air Monitoring Network was developed as part of a community-engaged research study to provide real-time particulate matter (PM) air quality information at a high spatial resolution in Imperial County, California. The network augmented the few existing regulatory monitors and increased monitoring near susceptible populations. Monitors were both calibrated and field validated, a key component of evaluating the quality of the data produced by the community monitoring network. This paper examines the performance of a customized version of the low-cost Dylos optical particle counter used in the community air monitors compared with both PM 2.5 and PM 10 (particulate matter with aerodynamic diameters <2.5 and <10 μm, respectively) federal equivalent method (FEM) beta-attenuation monitors (BAMs) and federal reference method (FRM) gravimetric filters at a collocation site in the study area. A conversion equation was developed that estimates particle mass concentrations from the native Dylos particle counts, taking into account relative humidity. The R 2 for converted hourly averaged Dylos mass measurements versus a PM 2.5 BAM was 0.79 and that versus a PM 10 BAM was 0.78. The performance of the conversion equation was evaluated at six other sites with collocated PM 2.5 environmental beta-attenuation monitors (EBAMs) located throughout Imperial County. The agreement of the Dylos with the EBAMs was moderate to high (R 2 = 0.35-0.81). The performance of low-cost air quality sensors in community networks is currently not well documented. This paper provides a methodology for quantifying the performance of a next-generation Dylos PM sensor used in the Imperial County Community Air Monitoring Network. This air quality network provides data at a much finer spatial and temporal resolution than has previously been possible with government monitoring efforts. Once calibrated and validated, these high-resolution data may provide more information on susceptible populations, assist in the identification of air pollution hotspots, and increase community awareness of air pollution.

Fault Tolerant Airborne Sensor Networks for Air Operations

DTIC Science & Technology

2008-02-01

lives affected by undetected targets. The network is said to have expired when there is no longer a single surviving sensor-pair. Tasking process...tasking a finite number of cooperative agents to randomly emerging targets for their removal. Faults occur when some agents engaged in a mission are...expired. Agents are subject to threat at a level determined by the number of targets present. On the other hand, the rate at which a target is removed

Cooperation among wirelessly connected static and mobile sensor nodes for surveillance applications.

PubMed

de Freitas, Edison Pignaton; Heimfarth, Tales; Vinel, Alexey; Wagner, Flávio Rech; Pereira, Carlos Eduardo; Larsson, Tony

2013-09-25

This paper presents a bio-inspired networking strategy to support the cooperation between static sensors on the ground and mobile sensors in the air to perform surveillance missions in large areas. The goal of the proposal is to provide low overhead in the communication among sensor nodes, while allocating the mobile sensors to perform sensing activities requested by the static ones. Simulations have shown that the strategy is efficient in maintaining low overhead and achieving the desired coordination.

Air Pollution Measurements by Citizen Scientists and NASA Satellites: Data Integration and Analysis

NASA Astrophysics Data System (ADS)

Gupta, P.; Maibach, J.; Levy, R. C.; Doraiswamy, P.; Pikelnaya, O.; Feenstra, B.; Polidori, A.

2017-12-01

PM2.5, or fine particulate matter, is a category of air pollutant consisting of solid particles with effective aerodynamic diameter of less than 2.5 microns. These particles are hazardous to human health, as their small size allows them to penetrate deep into the lungs. Since the late 1990's, the US Environmental Protection Agency has been monitoring PM2.5 using a network of ground-level sensors. Due to cost and space restrictions, the EPA monitoring network remains spatially sparse. That is, while the network spans the extent of the US, the distance between sensors is large enough that significant spatial variation in PM concentration can go undetected. To increase the spatial resolution of monitoring, previous studies have used satellite data to estimate ground-level PM concentrations. From imagery, one can create a measure of haziness due to aerosols, called aerosol optical depth (AOD), which then can be used to estimate PM concentrations using statistical and physical modeling. Additionally, previous research has identified a number of meteorological variables, such as relative humidity and mixing height, which aide in estimating PM concentrations from AOD. Although the high spatial resolution of satellite data is valuable alone for forecasting air quality, higher resolution ground-level data is needed to effectively study the relationship between PM2.5 concentrations and AOD. To this end, we discuss a citizen-science PM monitoring network deployed in California. Using low-cost PM sensors, this network achieves higher spatial resolution. We additionally discuss a software pipeline for integrating resulting PM measurements with satellite data, as well as initial data analysis.

Evaluation of small sensor technology for criteria air pollutants at ground-based sites and a citizen science network

EPA Science Inventory

A number of small sensor technologies for the measurement of NOz, O: and other criteriapollutants have recently emerged. There is a growing interest in understanding the capability ofsensor technology in accurately measuring ambient concentrations of gas-phase criteriapollutants....

Combining Community Engagement and Scientific Approaches in Next-Generation Monitor Siting: The Case of the Imperial County Community Air Network.

PubMed

Wong, Michelle; Bejarano, Esther; Carvlin, Graeme; Fellows, Katie; King, Galatea; Lugo, Humberto; Jerrett, Michael; Meltzer, Dan; Northcross, Amanda; Olmedo, Luis; Seto, Edmund; Wilkie, Alexa; English, Paul

2018-03-15

Air pollution continues to be a global public health threat, and the expanding availability of small, low-cost air sensors has led to increased interest in both personal and crowd-sourced air monitoring. However, to date, few low-cost air monitoring networks have been developed with the scientific rigor or continuity needed to conduct public health surveillance and inform policy. In Imperial County, California, near the U.S./Mexico border, we used a collaborative, community-engaged process to develop a community air monitoring network that attains the scientific rigor required for research, while also achieving community priorities. By engaging community residents in the project design, monitor siting processes, data dissemination, and other key activities, the resulting air monitoring network data are relevant, trusted, understandable, and used by community residents. Integration of spatial analysis and air monitoring best practices into the network development process ensures that the data are reliable and appropriate for use in research activities. This combined approach results in a community air monitoring network that is better able to inform community residents, support research activities, guide public policy, and improve public health. Here we detail the monitor siting process and outline the advantages and challenges of this approach.

Combining Community Engagement and Scientific Approaches in Next-Generation Monitor Siting: The Case of the Imperial County Community Air Network

PubMed Central

Wong, Michelle; Bejarano, Esther; Carvlin, Graeme; King, Galatea; Lugo, Humberto; Jerrett, Michael; Northcross, Amanda; Olmedo, Luis; Seto, Edmund; Wilkie, Alexa; English, Paul

2018-01-01

Air pollution continues to be a global public health threat, and the expanding availability of small, low-cost air sensors has led to increased interest in both personal and crowd-sourced air monitoring. However, to date, few low-cost air monitoring networks have been developed with the scientific rigor or continuity needed to conduct public health surveillance and inform policy. In Imperial County, California, near the U.S./Mexico border, we used a collaborative, community-engaged process to develop a community air monitoring network that attains the scientific rigor required for research, while also achieving community priorities. By engaging community residents in the project design, monitor siting processes, data dissemination, and other key activities, the resulting air monitoring network data are relevant, trusted, understandable, and used by community residents. Integration of spatial analysis and air monitoring best practices into the network development process ensures that the data are reliable and appropriate for use in research activities. This combined approach results in a community air monitoring network that is better able to inform community residents, support research activities, guide public policy, and improve public health. Here we detail the monitor siting process and outline the advantages and challenges of this approach. PMID:29543726

Real-Time Identification of Smoldering and Flaming Combustion Phases in Forest Using a Wireless Sensor Network-Based Multi-Sensor System and Artificial Neural Network

PubMed Central

Yan, Xiaofei; Cheng, Hong; Zhao, Yandong; Yu, Wenhua; Huang, Huan; Zheng, Xiaoliang

2016-01-01

Diverse sensing techniques have been developed and combined with machine learning method for forest fire detection, but none of them referred to identifying smoldering and flaming combustion phases. This study attempts to real-time identify different combustion phases using a developed wireless sensor network (WSN)-based multi-sensor system and artificial neural network (ANN). Sensors (CO, CO2, smoke, air temperature and relative humidity) were integrated into one node of WSN. An experiment was conducted using burning materials from residual of forest to test responses of each node under no, smoldering-dominated and flaming-dominated combustion conditions. The results showed that the five sensors have reasonable responses to artificial forest fire. To reduce cost of the nodes, smoke, CO2 and temperature sensors were chiefly selected through correlation analysis. For achieving higher identification rate, an ANN model was built and trained with inputs of four sensor groups: smoke; smoke and CO2; smoke and temperature; smoke, CO2 and temperature. The model test results showed that multi-sensor input yielded higher predicting accuracy (≥82.5%) than single-sensor input (50.9%–92.5%). Based on these, it is possible to reduce the cost with a relatively high fire identification rate and potential application of the system can be tested in future under real forest condition. PMID:27527175

Monitoring industrial facilities using principles of integration of fiber classifier and local sensor networks

NASA Astrophysics Data System (ADS)

Korotaev, Valery V.; Denisov, Victor M.; Rodrigues, Joel J. P. C.; Serikova, Mariya G.; Timofeev, Andrey V.

2015-05-01

The paper deals with the creation of integrated monitoring systems. They combine fiber-optic classifiers and local sensor networks. These systems allow for the monitoring of complex industrial objects. Together with adjacent natural objects, they form the so-called geotechnical systems. An integrated monitoring system may include one or more spatially continuous fiber-optic classifiers based on optic fiber and one or more arrays of discrete measurement sensors, which are usually combined in sensor networks. Fiber-optic classifiers are already widely used for the control of hazardous extended objects (oil and gas pipelines, railways, high-rise buildings, etc.). To monitor local objects, discrete measurement sensors are generally used (temperature, pressure, inclinometers, strain gauges, accelerometers, sensors measuring the composition of impurities in the air, and many others). However, monitoring complex geotechnical systems require a simultaneous use of continuous spatially distributed sensors based on fiber-optic cable and connected local discrete sensors networks. In fact, we are talking about integration of the two monitoring methods. This combination provides an additional way to create intelligent monitoring systems. Modes of operation of intelligent systems can automatically adapt to changing environmental conditions. For this purpose, context data received from one sensor (e.g., optical channel) may be used to change modes of work of other sensors within the same monitoring system. This work also presents experimental results of the prototype of the integrated monitoring system.

Real-Time Identification of Smoldering and Flaming Combustion Phases in Forest Using a Wireless Sensor Network-Based Multi-Sensor System and Artificial Neural Network.

PubMed

Yan, Xiaofei; Cheng, Hong; Zhao, Yandong; Yu, Wenhua; Huang, Huan; Zheng, Xiaoliang

2016-08-04

Diverse sensing techniques have been developed and combined with machine learning method for forest fire detection, but none of them referred to identifying smoldering and flaming combustion phases. This study attempts to real-time identify different combustion phases using a developed wireless sensor network (WSN)-based multi-sensor system and artificial neural network (ANN). Sensors (CO, CO₂, smoke, air temperature and relative humidity) were integrated into one node of WSN. An experiment was conducted using burning materials from residual of forest to test responses of each node under no, smoldering-dominated and flaming-dominated combustion conditions. The results showed that the five sensors have reasonable responses to artificial forest fire. To reduce cost of the nodes, smoke, CO₂ and temperature sensors were chiefly selected through correlation analysis. For achieving higher identification rate, an ANN model was built and trained with inputs of four sensor groups: smoke; smoke and CO₂; smoke and temperature; smoke, CO₂ and temperature. The model test results showed that multi-sensor input yielded higher predicting accuracy (≥82.5%) than single-sensor input (50.9%-92.5%). Based on these, it is possible to reduce the cost with a relatively high fire identification rate and potential application of the system can be tested in future under real forest condition.

Condition monitoring of an electro-magnetic brake using an artificial neural network

NASA Astrophysics Data System (ADS)

Gofran, T.; Neugebauer, P.; Schramm, D.

2017-10-01

This paper presents a data-driven approach to Condition Monitoring of Electromagnetic brakes without use of additional sensors. For safe and efficient operation of electric motor a regular evaluation and replacement of the friction surface of the brake is required. One such evaluation method consists of direct or indirect sensing of the air-gap between pressure plate and magnet. A larger gap is generally indicative of worn surface(s). Traditionally this has been accomplished by the use of additional sensors - making existing systems complex, cost- sensitive and difficult to maintain. In this work a feed-forward Artificial Neural Network (ANN) is learned with the electrical data of the brake by supervised learning method to estimate the air-gap. The ANN model is optimized on the training set and validated using the test set. The experimental results of estimated air-gap with accuracy of over 95% demonstrate the validity of the proposed approach.

Monitoring urban air quality using a high-density network of low-cost sensor nodes in Oslo, Norway.

NASA Astrophysics Data System (ADS)

Castell, Nuria; Schneider, Philipp; Vogt, Matthias; Dauge, Franck R.; Lahoz, William; Bartonova, Alena

2017-04-01

Urban air quality represents a major public health burden and is a long-standing concern to citizens. Air pollution is associated with a range of diseases, symptoms and conditions that impair health and quality of life. In Oslo, traffic, especially exhaust from heavy-duty and private diesel vehicles and dust resuspension from studded tyres, together with wood burning in winter, are the main sources of pollution. Norway, as part of the European Economic Area, is obliged to comply with the European air quality regulations and ensure clean air. Despite this, Oslo has exceeded both the NO2 and PM10 thresholds for health protection defined in the Directive 2008/50/EC. The air quality in the Oslo area is continuously monitored in 12 compliance monitoring stations. These stations provide reliable and accurate data but their density is too low to provide a detailed spatial distribution of air quality. The emergence of low-cost nodes enables observations at high spatial resolution, providing the opportunity to enhance existing monitoring systems. However, the data generated by these nodes is significantly less accurate and precise than the data provided by reference equipment. We have conducted an evaluation of low-cost nodes to monitor NO2 and PM10, comparing the data collected with low-cost nodes against CEN (European Standardization Organization) reference analysers. During January and March 2016, a network of 24 nodes was deployed in Oslo. During January, high NO2 levels were observed for several days in a row coinciding with the formation of a thermal inversion. During March, we observed an episode with high PM10 levels due to road dust resuspension. Our results show that there is a major technical challenge associated with current commercial low-cost sensors, regarding the sensor robustness and measurement repeatability. Despite this, low-cost sensor nodes are able to reproduce the NO2 and PM10 variability. The data from the sensors was employed to generate detailed NO2 and PM10 air quality maps using a data fusion technique. This way we were able to offer localized air quality information for the city of Oslo. The outlook for commercial low-cost sensors is promising, and our results show that currently some sensors are already capable of providing coarse information about air quality, indicating if the air quality is good, moderate or if the air is heavily polluted. This type of information could be suitable for applications that aim to raise awareness, or engage the community by monitoring local air quality, as such applications do not require the same accuracy as scientific or regulatory monitoring.

The Deployment of Carbon Monoxide Wireless Sensor Network (CO-WSN) for Ambient Air Monitoring

PubMed Central

Chaiwatpongsakorn, Chaichana; Lu, Mingming; Keener, Tim C.; Khang, Soon-Jai

2014-01-01

Wireless sensor networks are becoming increasingly important as an alternative solution for environment monitoring because they can reduce cost and complexity. Also, they can improve reliability and data availability in places where traditional monitoring methods are difficult to site. In this study, a carbon monoxide wireless sensor network (CO-WSN) was developed to measure carbon monoxide concentrations at a major traffic intersection near the University of Cincinnati main campus. The system has been deployed over two weeks during Fall 2010, and Summer 2011–2012, traffic data was also recorded by using a manual traffic counter and a video camcorder to characterize vehicles at the intersection 24 h, particularly, during the morning and evening peak hour periods. According to the field test results, the 1 hr-average CO concentrations were found to range from 0.1–1.0 ppm which is lower than the National Ambient Air Quality Standards (NAAQS) 35 ppm on a one-hour averaging period. During rush hour periods, the traffic volume at the intersection varied from 2,067 to 3,076 vehicles per hour with 97% being passenger vehicles. Furthermore, the traffic volume based on a 1-h average showed good correlation (R2 = 0.87) with the 1-h average CO-WSN concentrations for morning and evening peak time periods whereas CO-WSN results provided a moderate correlation (R2 = 0.42) with 24 hours traffic volume due to fluctuated changes of meteorological conditions. It is concluded that the performance and the reliability of wireless ambient air monitoring networks can be used as an alternative method for real time air monitoring. PMID:24937527

The Imperial County Community Air Monitoring Network: A Model for Community-based Environmental Monitoring for Public Health Action

PubMed Central

Olmedo, Luis; Bejarano, Ester; Lugo, Humberto; Murillo, Eduardo; Seto, Edmund; Wong, Michelle; King, Galatea; Wilkie, Alexa; Meltzer, Dan; Carvlin, Graeme; Jerrett, Michael; Northcross, Amanda

2017-01-01

Summary: The Imperial County Community Air Monitoring Network (the Network) is a collaborative group of community, academic, nongovernmental, and government partners designed to fill the need for more detailed data on particulate matter in an area that often exceeds air quality standards. The Network employs a community-based environmental monitoring process in which the community and researchers have specific, well-defined roles as part of an equitable partnership that also includes shared decision-making to determine study direction, plan research protocols, and conduct project activities. The Network is currently producing real-time particulate matter data from 40 low-cost sensors throughout Imperial County, one of the largest community-based air networks in the United States. Establishment of a community-led air network involves engaging community members to be citizen-scientists in the monitoring, siting, and data collection process. Attention to technical issues regarding instrument calibration and validation and electronic transfer and storage of data is also essential. Finally, continued community health improvements will be predicated on facilitating community ownership and sustainability of the network after research funds have been expended. https://doi.org/10.1289/EHP1772 PMID:28886604

Open hardware, low cost, air quality stations for monitoring ozone in coastal area

NASA Astrophysics Data System (ADS)

Lima, Marco; Donzella, Davide; Pintus, Fabio; Fedi, Adriano; Ferrari, Daniele; Massabò, Marco

2014-05-01

Ozone concentrations in urban and coastal area are a great concern for citizens and, consequently regulator. In the last 20 years the Ozone concentration is almost doubled and it has attracted the public attention because of the well know harmful impacts on human health and biosphere in general. Official monitoring networks usually comprise high precision, high accuracy observation stations, usually managed by public administrations and environmental agency; unfortunately due to their high costs of installation and maintenance, the monitoring stations are relatively sparse. This kind of monitoring networks have been recognized to be unsuitable to effectively characterize the high variability of air quality, especially in areas where pollution sources are various and often not static. We present a prototype of a low cost station for air quality monitoring, specifically developed for complementing the official monitoring stations improving the representation of air quality spatial distribution. We focused on a semi-professional product that could guarantee the highest reliability at the lowest possible cost, supported by a consistent infrastructure for data management. We test two type of Ozone sensor electrochemical and metal oxide. This work is integrated in the ACRONET Paradigm ® project: an open-hardware platform strongly oriented on environmental monitoring. All software and hardware sources will be available on the web. Thus, a computer and a small amount of work tools will be sufficient to create new monitoring networks, with the only constraint to share all the data obtained. It will so possible to create a real "sensing community". The prototype is currently able to measure ozone level, temperature and relative humidity, but soon, with the upcoming changes, it will be able also to monitor dust, carbon monoxide and nitrogen dioxide, always through the use of commercial sensors. The sensors are grouped in a compact board that interfaces with a data-logger able to transmit data to a dedicated server through a GPRS module (no ad hoc radio infrastructure needed). Due to the GPRS low latency transmission the data are transmitted in near-real time. The prototype has an independent power supply. The sensors outputs are directly compared with the measurement of the official fixed monitoring stations. We present preliminary tests of a ozone level assessment obtained without laboratory calibration during a first field campaign in Savona (Italy); the preliminary verification and test show reasonable agreement between low cost sensors and fixed monitoring station ozone level trends (low cost sensors detect gas concentration at ppb level). The preliminary results are promising for complementing the fixed official monitoring networks with low-cost sensors.

Intelligence Control System for Landfills Based on Wireless Sensor Network

NASA Astrophysics Data System (ADS)

Zhang, Qian; Huang, Chuan; Gong, Jian

2018-06-01

This paper put forward an intelligence system for controlling the landfill gas in landfills to make the landfill gas (LFG) exhaust controllably and actively. The system, which is assigned by the wireless sensor network, were developed and supervised by remote applications in workshop instead of manual work. An automatic valve control depending on the sensor units embedded is installed in tube, the air pressure and concentration of LFG are detected to decide the level of the valve switch. The paper also proposed a modified algorithm to solve transmission problem, so that the system can keep a high efficiency and long service life.

A New Black Carbon Sensor for Dense Air Quality Monitoring Networks

PubMed Central

Caubel, Julien J.; Cados, Troy E.; Kirchstetter, Thomas W.

2018-01-01

Low-cost air pollution sensors are emerging and increasingly being deployed in densely distributed wireless networks that provide more spatial resolution than is typical in traditional monitoring of ambient air quality. However, a low-cost option to measure black carbon (BC)—a major component of particulate matter pollution associated with adverse human health risks—is missing. This paper presents a new BC sensor designed to fill this gap, the Aerosol Black Carbon Detector (ABCD), which incorporates a compact weatherproof enclosure, solar-powered rechargeable battery, and cellular communication to enable long-term, remote operation. This paper also demonstrates a data processing methodology that reduces the ABCD’s sensitivity to ambient temperature fluctuations, and therefore improves measurement performance in unconditioned operating environments (e.g., outdoors). A fleet of over 100 ABCDs was operated outdoors in collocation with a commercial BC instrument (Magee Scientific, Model AE33) housed inside a regulatory air quality monitoring station. The measurement performance of the 105 ABCDs is comparable to the AE33. The fleet-average precision and accuracy, expressed in terms of mean absolute percentage error, are 9.2 ± 0.8% (relative to the fleet average data) and 24.6 ± 0.9% (relative to the AE33 data), respectively (fleet-average ± 90% confidence interval). PMID:29494528

A New Black Carbon Sensor for Dense Air Quality Monitoring Networks.

PubMed

Caubel, Julien J; Cados, Troy E; Kirchstetter, Thomas W

2018-03-01

Low-cost air pollution sensors are emerging and increasingly being deployed in densely distributed wireless networks that provide more spatial resolution than is typical in traditional monitoring of ambient air quality. However, a low-cost option to measure black carbon (BC)-a major component of particulate matter pollution associated with adverse human health risks-is missing. This paper presents a new BC sensor designed to fill this gap, the Aerosol Black Carbon Detector (ABCD), which incorporates a compact weatherproof enclosure, solar-powered rechargeable battery, and cellular communication to enable long-term, remote operation. This paper also demonstrates a data processing methodology that reduces the ABCD's sensitivity to ambient temperature fluctuations, and therefore improves measurement performance in unconditioned operating environments (e.g., outdoors). A fleet of over 100 ABCDs was operated outdoors in collocation with a commercial BC instrument (Magee Scientific, Model AE33) housed inside a regulatory air quality monitoring station. The measurement performance of the 105 ABCDs is comparable to the AE33. The fleet-average precision and accuracy, expressed in terms of mean absolute percentage error, are 9.2 ± 0.8% (relative to the fleet average data) and 24.6 ± 0.9% (relative to the AE33 data), respectively (fleet-average ± 90% confidence interval).

Application of Artificial Neural Networks to the Development of Improved Multi-Sensor Retrievals of Near-Surface Air Temperature and Humidity Over Ocean

NASA Technical Reports Server (NTRS)

Roberts, J. Brent; Robertson, Franklin R.; Clayson, Carol Anne

2012-01-01

Improved estimates of near-surface air temperature and air humidity are critical to the development of more accurate turbulent surface heat fluxes over the ocean. Recent progress in retrieving these parameters has been made through the application of artificial neural networks (ANN) and the use of multi-sensor passive microwave observations. Details are provided on the development of an improved retrieval algorithm that applies the nonlinear statistical ANN methodology to a set of observations from the Advanced Microwave Scanning Radiometer (AMSR-E) and the Advanced Microwave Sounding Unit (AMSU-A) that are currently available from the NASA AQUA satellite platform. Statistical inversion techniques require an adequate training dataset to properly capture embedded physical relationships. The development of multiple training datasets containing only in-situ observations, only synthetic observations produced using the Community Radiative Transfer Model (CRTM), or a mixture of each is discussed. An intercomparison of results using each training dataset is provided to highlight the relative advantages and disadvantages of each methodology. Particular emphasis will be placed on the development of retrievals in cloudy versus clear-sky conditions. Near-surface air temperature and humidity retrievals using the multi-sensor ANN algorithms are compared to previous linear and non-linear retrieval schemes.

Development of wireless sensor network for monitoring indoor air pollutant

NASA Astrophysics Data System (ADS)

Saad, Shaharil Mad; Shakaff, Ali Yeon Md; Saad, Abdul Rahman Mohd; Yusof @ Kamarudin, Azman Muhamad

2015-05-01

The air that we breathe with everyday contains variety of contaminants and particles. Some of these contaminants and particles are hazardous to human health. Most of the people don't realize that the content of air they being exposed to whether it was a good or bad air quality. The air quality whether in indoor or outdoor environment can be influenced by physical factors like dust particles, gaseous pollutants (including carbon dioxide, carbon monoxide and volatile organic compounds) and biological like molds and bacteria growth which largely depend on temperature and humidity condition of a room. These kinds of pollutants can affect human health, physical reaction, comfort or work performance. In this study, a wireless sensor network (WSN) monitoring system for monitor air pollutant in indoor environment was developed. The system was divided into three parts: web-based interface program, sensing module and a base station. The measured data was displayed on the web which is can be accessed by the user. The result shows that the overall measured parameters were meet the acceptable limit, requirement and criteria of indoor air pollution inside the building. The research can be used to improve the indoor air quality level in order to create a comfortable working and healthy environment for the occupants inside the building.

Theater-Level Stochastic Air-to-Air Engagement Modeling via Event Occurrence Networks Using Piecewise Polynomial Approximation

DTIC Science & Technology

2001-09-01

diagnosis natural language understanding circuit fault diagnosis pattern recognition machine vision nancial auditing map learning sensor... ACCA ACCB A ights degree of command and control FCC value is assumed to be the average of all the ACC values of the aircraft in the

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.

Characterizing Intra-Urban Air Quality Gradients with a Spatially-Distributed Network

NASA Astrophysics Data System (ADS)

Zimmerman, N.; Ellis, A.; Schurman, M. I.; Gu, P.; Li, H.; Snell, L.; Gu, J.; Subramanian, R.; Robinson, A. L.; Apte, J.; Presto, A. A.

2016-12-01

City-wide air pollution measurements have typically relied on regulatory or research monitoring sites with low spatial density to assess population-scale exposure. However, air pollutant concentrations exhibit significant spatial variability depending on local sources and features of the built environment, which may not be well captured by the existing monitoring regime. To better understand urban spatial and temporal pollution gradients at 1 km resolution, a network of 12 real-time air quality monitoring stations was deployed beginning July 2016 in Pittsburgh, PA. The stations were deployed at sites along an urban-rural transect and in urban locations with a range of traffic, restaurant, and tall building densities to examine the impact of various modifiable factors. Measurements from the stationary monitoring stations were further supported by mobile monitoring, which provided higher spatial resolution pollutant measurements on nearby roadways and enabled routine calibration checks. The stationary monitoring measurements comprise ultrafine particle number (Aerosol Dynamics "MAGIC" CPC), PM2.5 (Met One Neighborhood PM Monitor), black carbon (Met One BC 1050), and a new low-cost air quality monitor, the Real-time Affordable Multi-Pollutant (RAMP) sensor package for measuring CO, NO2, SO2, O3, CO2, temperature and relative humidity. High time-resolution (sub-minute) measurements across the distributed monitoring network enable insight into dynamic pollutant behaviour. Our preliminary findings show that our instruments are sensitive to PM2.5 gradients exceeding 2 micro-grams per cubic meter and ultrafine particle gradients exceeding 1000 particles per cubic centimeter. Additionally, we have developed rigorous calibration protocols to characterize the RAMP sensor response and drift, as well as multiple linear regression models to convert sensor response into pollutant concentrations that are comparable to reference instrumentation.

The Benefits of Using Dense Temperature Sensor Networks to Monitor Urban Warming

NASA Astrophysics Data System (ADS)

Twine, T. E.; Snyder, P. K.; Kucharik, C. J.; Schatz, J.

2015-12-01

Urban heat islands (UHIs) occur when urban and suburban areas experience temperatures that are elevated relative to their rural surroundings because of differences in the fraction of gray and green infrastructure. Studies have shown that communities most at risk for impacts from climate-related disasters (i.e., lower median incomes, higher poverty, lower education, and minorities) tend to live in the hottest areas of cities. Development of adequate climate adaptation tools for cities relies on knowledge of how temperature varies across space and time. Traditionally, a city's urban heat island has been quantified using near-surface air temperature measurements from a few sites. This methodology assumes (1) that the UHI can be characterized by the difference in air temperature from a small number of points, and (2) that these few points represent the urban and rural signatures of the region. This methodology ignores the rich information that could be gained from measurements across the urban to rural transect. This transect could traverse elevations, water bodies, vegetation fraction, and other land surface properties. Two temperature sensor networks were designed and implemented in the Minneapolis-Saint Paul, MN and Madison, WI metropolitan areas beginning in 2011 and 2012, respectively. Both networks use the same model sensor and record temperature every 15 minutes from ~150 sensors. Data from each network has produced new knowledge of how temperature varies diurnally and seasonally across the cities and how the UHI magnitude is influenced by weather phenomena (e.g., wind, snow cover, heat waves) and land surface characteristics such as proximity to inland lakes. However, the two metropolitan areas differ in size, population, structure, and orientation to water bodies. In addition, the sensor networks were established in very different manners. We describe these differences and present lessons learned from the design and ongoing efforts of these two dense networks located in the Midwest USA.

Application of zonal model on indoor air sensor network design

NASA Astrophysics Data System (ADS)

Chen, Y. Lisa; Wen, Jin

2007-04-01

Growing concerns over the safety of the indoor environment have made the use of sensors ubiquitous. Sensors that detect chemical and biological warfare agents can offer early warning of dangerous contaminants. However, current sensor system design is more informed by intuition and experience rather by systematic design. To develop a sensor system design methodology, a proper indoor airflow modeling approach is needed. Various indoor airflow modeling techniques, from complicated computational fluid dynamics approaches to simplified multi-zone approaches, exist in the literature. In this study, the effects of two airflow modeling techniques, multi-zone modeling technique and zonal modeling technique, on indoor air protection sensor system design are discussed. Common building attack scenarios, using a typical CBW agent, are simulated. Both multi-zone and zonal models are used to predict airflows and contaminant dispersion. Genetic Algorithm is then applied to optimize the sensor location and quantity. Differences in the sensor system design resulting from the two airflow models are discussed for a typical office environment and a large hall environment.

SSA Sensor Calibration Best Practices

NASA Astrophysics Data System (ADS)

Johnson, T.

Best practices for calibrating orbit determination sensors in general and space situational awareness (SSA) sensors in particular are presented. These practices were developed over the last ten years within AGI and most recently applied to over 70 sensors in AGI's Commercial Space Operations Center (ComSpOC) and the US Air Force Space Command (AFSPC) Space Surveillance Network (SSN) to evaluate and configure new sensors and perform on-going system calibration. They are generally applicable to any SSA sensor and leverage some unique capabilities of an SSA estimation approach using an optimal sequential filter and smoother. Real world results are presented and analyzed.

Network of Environmental Sensors in Tropical Rain Forests

NASA Astrophysics Data System (ADS)

von Randow, C.; Dos Santos, R. D.; Da Rocha, H.

2010-12-01

The interaction between the Earth’s atmosphere and the terrestrial biosphere plays a fundamental role in the climate system and in biogeochemical and hydrological cycles, through the exchange of energy and mass (for example, water and carbon), between the vegetation and the atmospheric boundary layer, and the main focus of many environmental studies is to quantify this exchange over several terrestrial biomes. Over natural surfaces like the tropical forests, factors like spatial variations in topography or in the vegetation cover can significantly affect the air flow and pose big challenges for the monitoring of the regional carbon budget of terrestrial biomes. It is hardly possible to understand the air flow and reduce the uncertainties of flux measurements in complex terrains like tropical forests without an approach that recognizes the complexity of the spatial variability of the environmental variables. With this motivation, a partnership involving Microsoft Research, Johns Hopkins University, University of São Paulo and Instituto Nacional de Pesquisas Espaciais (INPE, the Brazilian national institute for space research) has been developing research activities to test the use of prototypes of environmental sensors (geosensors) in the Atlantic coastal and in the Amazonian rain forests in Brazil, forming sensor networks with high spatial and temporal resolution, and to develop software tools for data quality control and integration. The main premise is that the geosensors should have relatively low cost, what enables the formation of monitoring networks with a large number of sensors spatially distributed. A pilot study deployed 200+ sensors over the Atlantic coastal forest in Sao Paulo state, Brazil. Here we present the results from this study, highlighting the current discussions on applications of this type of measurements in studies of biosphere-atmosphere interaction in the tropics. Envisioning a possible wide deployment of geosensors in Amazonia in the future, the team is currently working on three main components: 1) assembly and calibration of prototypes of geosensors of air temperature and humidity, with reproductive and reliable ceramic sensor elements that will adequately operate under the environmental conditions observed in the tropics; 2) development of software tools for management, quality control, visualization and integration of data collected in geosensor networks; and 3) planning of the Amazon experimental campaign, with the installation of the first tens to hundreds of sensors within and above the rainforest canopy, aiming at a test of the system to study the spatial variability of temperature and humidity.

Design architecture for multi-zone HVAC control systems from existing single-zone systems using wireless sensor networks

NASA Astrophysics Data System (ADS)

Redfern, Andrew; Koplow, Michael; Wright, Paul

2007-01-01

Most residential heating, ventilating, and air-conditioning (HVAC) systems utilize a single zone for conditioning air throughout the entire house. While inexpensive, these systems lead to wide temperature distributions and inefficient cooling due to the difference in thermal loads in different rooms. The end result is additional cost to the end user because the house is over conditioned. To reduce the total amount of energy used in a home and to increase occupant comfort there is a need for a better control system using multiple temperature zones. Typical multi-zone systems are costly and require extensive infrastructure to function. Recent advances in wireless sensor networks (WSNs) have enabled a low cost drop-in wireless vent register control system. The register control system is controlled by a master controller unit, which collects sensor data from a distributed wireless sensor network. Each sensor node samples local settings (occupancy, light, humidity and temperature) and reports the data back to the master control unit. The master control unit compiles the incoming data and then actuates the vent resisters to control the airflow throughout the house. The control system also utilizes a smart thermostat with a movable set point to enable the user to define their given comfort levels. The new system can reduce the run time of the HVAC system and thus decreasing the amount of energy used and increasing the comfort of the home occupations.

Calibration of an electronic nose for poultry farm

NASA Astrophysics Data System (ADS)

Abdullah, A. H.; Shukor, S. A.; Kamis, M. S.; Shakaff, A. Y. M.; Zakaria, A.; Rahim, N. A.; Mamduh, S. M.; Kamarudin, K.; Saad, F. S. A.; Masnan, M. J.; Mustafa, H.

2017-03-01

Malodour from the poultry farms could cause air pollution and therefore potentially dangerous to humans' and animals' health. This issue also poses sustainability risk to the poultry industries due to objections from local community. The aim of this paper is to develop and calibrate a cost effective and efficient electronic nose for poultry farm air monitoring. The instrument main components include sensor chamber, array of specific sensors, microcontroller, signal conditioning circuits and wireless sensor networks. The instrument was calibrated to allow classification of different concentrations of main volatile compounds in the poultry farm malodour. The outcome of the process will also confirm the device's reliability prior to being used for poultry farm malodour assessment. The Multivariate Analysis (HCA and KNN) and Artificial Neural Network (ANN) pattern recognition technique was used to process the acquired data. The results show that the instrument is able to calibrate the samples using ANN classification model with high accuracy. The finding verifies the instrument's performance to be used as an effective poultry farm malodour monitoring.

Measuring PM and related air pollutants using low-cost ...

EPA Pesticide Factsheets

Emerging air quality sensors may play a key role in better characterizing levels of air pollution in a variety of settings There are a wide range of low-cost (< $500 US) sensors on the market, but few have been characterized. If accurate, this new generation of inexpensive sensors can potentially allow larger fleets of monitors to be deployed to better study the spatial and temporal variability of pollutants. The small size and light weight of these sensors also allows for the possibility of wearable or drone applications. Sensor networks will very likely play a key role in future estimates of human health impacts of pollutants, in particular particulate matter (PM), and will allow for the better characterization of pollutant sources and source regions.We will present measurements from an assortment of sensors, costing $20-$700, that have been used to measure air pollution in the US, India, and China with a focus on estimating PM concentrations. Their performance has been evaluated in these very different settings with low concentrations seen in the US (up to approximately 20 ug m-3) and much higher concentrations measured in India and China (up to approximately 300 ug m-3). Based on these studies the optimal concentration ranges of these sensors have been determined. Used in conjunction with data from a carbon dioxide sensor, emissions factors were estimated in some of the locations. In addition temperature and humidity sensors can be used to calculate c

Wireless Sensor Platform for Cultural Heritage Monitoring and Modeling System

PubMed Central

Bermudez, Sergio A.; Schrott, Alejandro G.; Tsukada, Masahiko; Kargere, Lucretia; Marianno, Fernando; Hamann, Hendrik F.; López, Vanessa; Leona, Marco

2017-01-01

Results from three years of continuous monitoring of environmental conditions using a wireless sensor platform installed at The Cloisters, the medieval branch of the New York Metropolitan Museum of Art, are presented. The platform comprises more than 200 sensors that were distributed in five galleries to assess temperature and air flow and to quantify microclimate changes using physics-based and statistical models. The wireless sensor network data shows a very stable environment within the galleries, while the dense monitoring enables localized monitoring of subtle changes in air quality trends and impact of visitors on the microclimate conditions. The high spatial and temporal resolution data serves as a baseline study to understand the impact of visitors and building operations on the long-term preservation of art objects. PMID:28858223

Wireless Sensor Platform for Cultural Heritage Monitoring and Modeling System.

PubMed

Klein, Levente J; Bermudez, Sergio A; Schrott, Alejandro G; Tsukada, Masahiko; Dionisi-Vici, Paolo; Kargere, Lucretia; Marianno, Fernando; Hamann, Hendrik F; López, Vanessa; Leona, Marco

2017-08-31

Results from three years of continuous monitoring of environmental conditions using a wireless sensor platform installed at The Cloisters, the medieval branch of the New York Metropolitan Museum of Art, are presented. The platform comprises more than 200 sensors that were distributed in five galleries to assess temperature and air flow and to quantify microclimate changes using physics-based and statistical models. The wireless sensor network data shows a very stable environment within the galleries, while the dense monitoring enables localized monitoring of subtle changes in air quality trends and impact of visitors on the microclimate conditions. The high spatial and temporal resolution data serves as a baseline study to understand the impact of visitors and building operations on the long-term preservation of art objects.

A Gap-Filling Procedure for Hydrologic Data Based on Kalman Filtering and Expectation Maximization: Application to Data from the Wireless Sensor Networks of the Sierra Nevada

NASA Astrophysics Data System (ADS)

Coogan, A.; Avanzi, F.; Akella, R.; Conklin, M. H.; Bales, R. C.; Glaser, S. D.

2017-12-01

Automatic meteorological and snow stations provide large amounts of information at dense temporal resolution, but data quality is often compromised by noise and missing values. We present a new gap-filling and cleaning procedure for networks of these stations based on Kalman filtering and expectation maximization. Our method utilizes a multi-sensor, regime-switching Kalman filter to learn a latent process that captures dependencies between nearby stations and handles sharp changes in snowfall rate. Since the latent process is inferred using observations across working stations in the network, it can be used to fill in large data gaps for a malfunctioning station. The procedure was tested on meteorological and snow data from Wireless Sensor Networks (WSN) in the American River basin of the Sierra Nevada. Data include air temperature, relative humidity, and snow depth from dense networks of 10 to 12 stations within 1 km2 swaths. Both wet and dry water years have similar data issues. Data with artificially created gaps was used to quantify the method's performance. Our multi-sensor approach performs better than a single-sensor one, especially with large data gaps, as it learns and exploits the dominant underlying processes in snowpack at each site.

Radar coordination and resource management in a distributed sensor network using emergent control

NASA Astrophysics Data System (ADS)

Weir, B. S.; Sokol, T. M.

2009-05-01

As the list of anti-air warfare and ballistic missile defense missions grows, there is an increasing need to coordinate and optimize usage of radar resources across the netted force. Early attempts at this optimization involved top-down control mechanisms whereby sensors accept resource tasking orders from networked tracking elements. These approaches rely heavily on uncertain knowledge of sensor constraints and capabilities. Furthermore, advanced sensor systems may support self-defense missions of the host platform and are therefore unable to relinquish control to an external function. To surmount these issues, the use of bottom-up emergent control techniques is proposed. The information necessary to make quality, network-wide resource allocations is readily available to sensor nodes with access to a netted track picture. By assessing resource priorities relative to the network (versus local) track picture, sensors can understand the contribution of their resources to the netted force. This allows the sensors to apply resources where most needed and remove waste. Furthermore, simple local rules for resource usage, when properly constructed, allow sensors to obtain a globally optimal resource allocation without direct coordination (emergence). These results are robust to partial implementation (i.e., not all nodes upgraded at once) and failures on individual nodes (whether from casualty or reallocation to other sensor missions), and they leave resource control decisions in the hands of the sensor systems instead of an external function. This paper presents independent research and development work on emergent control of sensor resources and the impact to resource allocation and tracking performance.

Angle of Arrival Detection Through Artificial Neural Network Analysis of Optical Fiber Intensity Patterns

DTIC Science & Technology

1990-12-01

ARTIFICIAL NEURAL NETWORK ANALYSIS OF OPTICAL FIBER INTENSITY PATTERNS THESIS Scott Thomas Captain, USAF AFIT/GE/ENG/90D-62 DTIC...ELECTE ao • JAN08 1991 Approved for public release; distribution unlimited. AFIT/GE/ENG/90D-62 ANGLE OF ARRIVAL DETECTION THROUGH ARTIFICIAL NEURAL NETWORK ANALYSIS... ARTIFICIAL NEURAL NETWORK ANALYSIS OF OPTICAL FIBER INTENSITY PATTERNS L Introduction The optical sensors of United States Air Force reconnaissance

A Community Network of 100 Black Carbon Sensors

NASA Astrophysics Data System (ADS)

Preble, C.; Kirchstetter, T.; Caubel, J.; Cados, T.; Keeling, C.; Chang, S.

2017-12-01

We developed a low-cost black carbon sensor, field tested its performance, and then built and deployed a network of 100 sensors in West Oakland, California. We operated the network for 100 days beginning mid-May 2017 to measure spatially resolved black carbon concentrations throughout the community. West Oakland is a San Francisco Bay Area mixed residential and industrial community that is adjacent to regional port and rail yard facilities and surrounded by major freeways. As such, the community is affected by diesel particulate matter emissions from heavy-duty diesel trucks, locomotives, and ships associated with freight movement. In partnership with Environmental Defense Fund, the Bay Area Air Quality Management District, and the West Oakland Environmental Indicators Project, we deployed the black carbon monitoring network outside of residences and business, along truck routes and arterial streets, and at upwind locations. The sensor employs the filter-based light transmission method to measure black carbon and has good precision and correspondence with current commercial black carbon instruments. Throughout the 100-day period, each of the 100 sensors transmitted data via a cellular network. A MySQL database was built to receive and manage the data in real-time. The database included diagnostic features to monitor each sensor's operational status and facilitate the maintenance of the network. Spatial and temporal patterns in black carbon concentrations will be presented, including patterns around industrial facilities, freeways, and truck routes, as well as the relationship between neighborhood concentrations and the BAAQMD's monitoring site. Lessons learned during this first of its kind black carbon monitoring network will also be shared.

Real-Time Alpine Measurement System Using Wireless Sensor Networks

PubMed Central

2017-01-01

Monitoring the snow pack is crucial for many stakeholders, whether for hydro-power optimization, water management or flood control. Traditional forecasting relies on regression methods, which often results in snow melt runoff predictions of low accuracy in non-average years. Existing ground-based real-time measurement systems do not cover enough physiographic variability and are mostly installed at low elevations. We present the hardware and software design of a state-of-the-art distributed Wireless Sensor Network (WSN)-based autonomous measurement system with real-time remote data transmission that gathers data of snow depth, air temperature, air relative humidity, soil moisture, soil temperature, and solar radiation in physiographically representative locations. Elevation, aspect, slope and vegetation are used to select network locations, and distribute sensors throughout a given network location, since they govern snow pack variability at various scales. Three WSNs were installed in the Sierra Nevada of Northern California throughout the North Fork of the Feather River, upstream of the Oroville dam and multiple powerhouses along the river. The WSNs gathered hydrologic variables and network health statistics throughout the 2017 water year, one of northern Sierra’s wettest years on record. These networks leverage an ultra-low-power wireless technology to interconnect their components and offer recovery features, resilience to data loss due to weather and wildlife disturbances and real-time topological visualizations of the network health. Data show considerable spatial variability of snow depth, even within a 1 km2 network location. Combined with existing systems, these WSNs can better detect precipitation timing and phase in, monitor sub-daily dynamics of infiltration and surface runoff during precipitation or snow melt, and inform hydro power managers about actual ablation and end-of-season date across the landscape. PMID:29120376

Real-Time Alpine Measurement System Using Wireless Sensor Networks.

PubMed

Malek, Sami A; Avanzi, Francesco; Brun-Laguna, Keoma; Maurer, Tessa; Oroza, Carlos A; Hartsough, Peter C; Watteyne, Thomas; Glaser, Steven D

2017-11-09

Monitoring the snow pack is crucial for many stakeholders, whether for hydro-power optimization, water management or flood control. Traditional forecasting relies on regression methods, which often results in snow melt runoff predictions of low accuracy in non-average years. Existing ground-based real-time measurement systems do not cover enough physiographic variability and are mostly installed at low elevations. We present the hardware and software design of a state-of-the-art distributed Wireless Sensor Network (WSN)-based autonomous measurement system with real-time remote data transmission that gathers data of snow depth, air temperature, air relative humidity, soil moisture, soil temperature, and solar radiation in physiographically representative locations. Elevation, aspect, slope and vegetation are used to select network locations, and distribute sensors throughout a given network location, since they govern snow pack variability at various scales. Three WSNs were installed in the Sierra Nevada of Northern California throughout the North Fork of the Feather River, upstream of the Oroville dam and multiple powerhouses along the river. The WSNs gathered hydrologic variables and network health statistics throughout the 2017 water year, one of northern Sierra's wettest years on record. These networks leverage an ultra-low-power wireless technology to interconnect their components and offer recovery features, resilience to data loss due to weather and wildlife disturbances and real-time topological visualizations of the network health. Data show considerable spatial variability of snow depth, even within a 1 km 2 network location. Combined with existing systems, these WSNs can better detect precipitation timing and phase in, monitor sub-daily dynamics of infiltration and surface runoff during precipitation or snow melt, and inform hydro power managers about actual ablation and end-of-season date across the landscape.

Decision-Making Using Real-Time Observations for Environmental Sustainability; an integrated 802.11 sensor network

NASA Astrophysics Data System (ADS)

Dominguez, A.; Kleissl, J.; Farhadi, M.; Kim, D.; Liu, W.; Mao, Y.; Nguyen, H. T.; Roshandell, M.; Sankur, M.; Shiga, Y.; Linden, P.; Hodgkiss, W.

2007-12-01

Meteorological conditions have important implications on human activities. They affect human comfort, productivity, and health, and contribute to material wear and tear. The University of California, San Diego (UCSD)'s proximity to the Pacific Ocean places it in a temperate microclimate which has unique advantages and disadvantages for campus water and energy use and air quality. In particular, the daily sea-breezes provide cool, moist, and salt-laden air to campus. For the Decision-Making Using Real-Time Observations for Environmental Sustainability (DEMROES) project a heterogeneous wireless network of monitoring stations is being set up across the UCSD campus and beyond. Conditions to be monitored include temperature, humidity, wind speed and direction, surface temperatures, solar radiation, particulate matter, CO, NO2, rainfall, and soil moisture. Stations are strategically placed on rooftops and lampposts across campus, as well as select off-campus locations and will transmit data over the UCSD 802.11 wireless network. In addition to rooftop and lamppost stations, mobile stations will be deployed via remotely controlled ground and air units, and stations affixed to campus shuttle busses. These mobile stations will allow for greater spatial resolution of the environmental conditions across campus and inter-sensor calibration. The hardware consists of meteorological, hydrological, and air quality sensors connected to (a) commercial Campbell datalogging systems with serial2IP modules and wireless bridges, and (b) sensor and 802.11 boards based on the dpac technology developed in-house. The measurements will serve campus facilities management with information to feed the energy management system (EMS) for building operation and energy conservation, and irrigation management. The technology developed for this project can be applied elsewhere thereby contributing to hydrologic and ecologic observatories. Through extensive student involvement a new generation of environmental scientists and engineers will be trained to work on the planning and execution of national observatories.

Annual Report to Congress: Military and Security Developments Involving the People’s Republic of China 2015

DTIC Science & Technology

2015-04-07

ships, equipped with advanced anti-ship, anti- air, and anti-submarine weapons and sensors . Whereas “near seas” defense remains the PLA Navy’s...that “destroying or capturing satellites and other sensors … will deprive an opponent of initiative on the battlefield and [make it difficult] for...aircraft are modern avionics and sensors that offer more timely situational awareness for operations in network-centric combat environments, radars

Location verification algorithm of wearable sensors for wireless body area networks.

PubMed

Wang, Hua; Wen, Yingyou; Zhao, Dazhe

2018-01-01

Knowledge of the location of sensor devices is crucial for many medical applications of wireless body area networks, as wearable sensors are designed to monitor vital signs of a patient while the wearer still has the freedom of movement. However, clinicians or patients can misplace the wearable sensors, thereby causing a mismatch between their physical locations and their correct target positions. An error of more than a few centimeters raises the risk of mistreating patients. The present study aims to develop a scheme to calculate and detect the position of wearable sensors without beacon nodes. A new scheme was proposed to verify the location of wearable sensors mounted on the patient's body by inferring differences in atmospheric air pressure and received signal strength indication measurements from wearable sensors. Extensive two-sample t tests were performed to validate the proposed scheme. The proposed scheme could easily recognize a 30-cm horizontal body range and a 65-cm vertical body range to correctly perform sensor localization and limb identification. All experiments indicate that the scheme is suitable for identifying wearable sensor positions in an indoor environment.

PADF electromagnetic source localization using extremum seeking control

NASA Astrophysics Data System (ADS)

Al Issa, Huthaifa A.; Ordóñez, Raúl

2014-10-01

Wireless Sensor Networks (WSNs) are a significant technology attracting considerable research interest. Recent advances in wireless communications and electronics have enabled the development of low-cost, low-power and multi-functional sensors that are small in size and communicate over short distances. Most WSN applications require knowing or measuring locations of thousands of sensors accurately. For example, sensing data without knowing the sensor location is often meaningless. Locations of sensor nodes are fundamental to providing location stamps, locating and tracking objects, forming clusters, and facilitating routing. This research focused on the modeling and implementation of distributed, mobile radar sensor networks. In particular, we worked on the problem of Position-Adaptive Direction Finding (PADF), to determine the location of a non- collaborative transmitter, possibly hidden within a structure, by using a team of cooperative intelligent sensor networks. Position-Adaptive radar concepts have been formulated and investigated at the Air Force Research Laboratory (AFRL) within the past few years. In this paper, we present the simulation performance analysis on the application aspect. We apply Extremum Seeking Control (ESC) schemes by using the swarm seeking problem, where the goal is to design a control law for each individual sensor that can minimize the error metric by adapting the sensor positions in real-time, thereby minimizing the unknown estimation error. As a result we achieved source seeking and collision avoidance of the entire group of the sensor positions.

Air Temperature Error Correction Based on Solar Radiation in an Economical Meteorological Wireless Sensor Network

PubMed Central

Sun, Xingming; Yan, Shuangshuang; Wang, Baowei; Xia, Li; Liu, Qi; Zhang, Hui

2015-01-01

Air temperature (AT) is an extremely vital factor in meteorology, agriculture, military, etc., being used for the prediction of weather disasters, such as drought, flood, frost, etc. Many efforts have been made to monitor the temperature of the atmosphere, like automatic weather stations (AWS). Nevertheless, due to the high cost of specialized AT sensors, they cannot be deployed within a large spatial density. A novel method named the meteorology wireless sensor network relying on a sensing node has been proposed for the purpose of reducing the cost of AT monitoring. However, the temperature sensor on the sensing node can be easily influenced by environmental factors. Previous research has confirmed that there is a close relation between AT and solar radiation (SR). Therefore, this paper presents a method to decrease the error of sensed AT, taking SR into consideration. In this work, we analyzed all of the collected data of AT and SR in May 2014 and found the numerical correspondence between AT error (ATE) and SR. This corresponding relation was used to calculate real-time ATE according to real-time SR and to correct the error of AT in other months. PMID:26213941

Air Temperature Error Correction Based on Solar Radiation in an Economical Meteorological Wireless Sensor Network.

PubMed

Sun, Xingming; Yan, Shuangshuang; Wang, Baowei; Xia, Li; Liu, Qi; Zhang, Hui

2015-07-24

Air temperature (AT) is an extremely vital factor in meteorology, agriculture, military, etc., being used for the prediction of weather disasters, such as drought, flood, frost, etc. Many efforts have been made to monitor the temperature of the atmosphere, like automatic weather stations (AWS). Nevertheless, due to the high cost of specialized AT sensors, they cannot be deployed within a large spatial density. A novel method named the meteorology wireless sensor network relying on a sensing node has been proposed for the purpose of reducing the cost of AT monitoring. However, the temperature sensor on the sensing node can be easily influenced by environmental factors. Previous research has confirmed that there is a close relation between AT and solar radiation (SR). Therefore, this paper presents a method to decrease the error of sensed AT, taking SR into consideration. In this work, we analyzed all of the collected data of AT and SR in May 2014 and found the numerical correspondence between AT error (ATE) and SR. This corresponding relation was used to calculate real-time ATE according to real-time SR and to correct the error of AT in other months.

Solution to the Problem of Calibration of Low-Cost Air Quality Measurement Sensors in Networks.

PubMed

Miskell, Georgia; Salmond, Jennifer A; Williams, David E

2018-04-27

We provide a simple, remote, continuous calibration technique suitable for application in a hierarchical network featuring a few well-maintained, high-quality instruments ("proxies") and a larger number of low-cost devices. The ideas are grounded in a clear definition of the purpose of a low-cost network, defined here as providing reliable information on air quality at small spatiotemporal scales. The technique assumes linearity of the sensor signal. It derives running slope and offset estimates by matching mean and standard deviations of the sensor data to values derived from proxies over the same time. The idea is extremely simple: choose an appropriate proxy and an averaging-time that is sufficiently long to remove the influence of short-term fluctuations but sufficiently short that it preserves the regular diurnal variations. The use of running statistical measures rather than cross-correlation of sites means that the method is robust against periods of missing data. Ideas are first developed using simulated data and then demonstrated using field data, at hourly and 1 min time-scales, from a real network of low-cost semiconductor-based sensors. Despite the almost naïve simplicity of the method, it was robust for both drift detection and calibration correction applications. We discuss the use of generally available geographic and environmental data as well as microscale land-use regression as means to enhance the proxy estimates and to generalize the ideas to other pollutants with high spatial variability, such as nitrogen dioxide and particulates. These improvements can also be used to minimize the required number of proxy sites.

Monitoring Indoor Air Quality for Enhanced Occupational Health.

PubMed

Pitarma, Rui; Marques, Gonçalo; Ferreira, Bárbara Roque

2017-02-01

Indoor environments are characterized by several pollutant sources. Because people spend more than 90% of their time in indoor environments, several studies have pointed out the impact of indoor air quality on the etiopathogenesis of a wide number of non-specific symptoms which characterizes the "Sick Building Syndrome", involving the skin, the upper and lower respiratory tract, the eyes and the nervous system, as well as many building related diseases. Thus, indoor air quality (IAQ) is recognized as an important factor to be controlled for the occupants' health and comfort. The majority of the monitoring systems presently available is very expensive and only allow to collect random samples. This work describes the system (iAQ), a low-cost indoor air quality monitoring wireless sensor network system, developed using Arduino, XBee modules and micro sensors, for storage and availability of monitoring data on a web portal in real time. Five micro sensors of environmental parameters (air temperature, humidity, carbon monoxide, carbon dioxide and luminosity) were used. Other sensors can be added for monitoring specific pollutants. The results reveal that the system can provide an effective indoor air quality assessment to prevent exposure risk. In fact, the indoor air quality may be extremely different compared to what is expected for a quality living environment. Systems like this would have benefit as public health interventions to reduce the burden of symptoms and diseases related to "sick buildings".

Analyses of integrated aircraft cabin contaminant monitoring network based on Kalman consensus filter.

PubMed

Wang, Rui; Li, Yanxiao; Sun, Hui; Chen, Zengqiang

2017-11-01

The modern civil aircrafts use air ventilation pressurized cabins subject to the limited space. In order to monitor multiple contaminants and overcome the hypersensitivity of the single sensor, the paper constructs an output correction integrated sensor configuration using sensors with different measurement theories after comparing to other two different configurations. This proposed configuration works as a node in the contaminant distributed wireless sensor monitoring network. The corresponding measurement error models of integrated sensors are also proposed by using the Kalman consensus filter to estimate states and conduct data fusion in order to regulate the single sensor measurement results. The paper develops the sufficient proof of the Kalman consensus filter stability when considering the system and the observation noises and compares the mean estimation and the mean consensus errors between Kalman consensus filter and local Kalman filter. The numerical example analyses show the effectiveness of the algorithm. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

Benefits of Sharing Information from Commercial Airborne Forward-Looking Sensors in the Next Generation Air Transportation System

NASA Technical Reports Server (NTRS)

Schaffner, Philip R.; Harrah, Steven; Neece, Robert T.

2012-01-01

The air transportation system of the future will need to support much greater traffic densities than are currently possible, while preserving or improving upon current levels of safety. Concepts are under development to support a Next Generation Air Transportation System (NextGen) that by some estimates will need to support up to three times current capacity by the year 2025. Weather and other atmospheric phenomena, such as wake vortices and volcanic ash, constitute major constraints on airspace system capacity and can present hazards to aircraft if encountered. To support safe operations in the NextGen environment advanced systems for collection and dissemination of aviation weather and environmental information will be required. The envisioned NextGen Network Enabled Weather (NNEW) infrastructure will be a critical component of the aviation weather support services, providing access to a common weather picture for all system users. By taking advantage of Network Enabled Operations (NEO) capabilities, a virtual 4-D Weather Data Cube with aviation weather information from many sources will be developed. One new source of weather observations may be airborne forward-looking sensors, such as the X-band weather radar. Future sensor systems that are the subject of current research include advanced multi-frequency and polarimetric radar, a variety of Lidar technologies, and infrared imaging spectrometers.

Web Information Systems for Monitoring and Control of Indoor Air Quality at Subway Stations

NASA Astrophysics Data System (ADS)

Choi, Gi Heung; Choi, Gi Sang; Jang, Joo Hyoung

In crowded subway stations indoor air quality (IAQ) is a key factor for ensuring the safety, health and comfort of passengers. In this study, a framework for web-based information system in VDN environment for monitoring and control of IAQ in subway stations is suggested. Since physical variables that describing IAQ need to be closely monitored and controlled in multiple locations in subway stations, concept of distributed monitoring and control network using wireless media needs to be implemented. Connecting remote wireless sensor network and device (LonWorks) networks to the IP network based on the concept of VDN can provide a powerful, integrated, distributed monitoring and control performance, making a web-based information system possible.

Heterogeneous information sharing of sensor information in contested environments

NASA Astrophysics Data System (ADS)

Wampler, Jason A.; Hsieh, Chien; Toth, Andrew; Sheatsley, Ryan

2017-05-01

The inherent nature of unattended sensors makes these devices most vulnerable to detection, exploitation, and denial in contested environments. Physical access is often cited as the easiest way to compromise any device or network. A new mechanism for mitigating these types of attacks developed under the Assistant Secretary of Defense for Research and Engineering, ASD(R and E) project, "Smoke Screen in Cyberspace", was demonstrated in a live, over-the-air experiment. Smoke Screen encrypts, slices up, and disburses redundant fragments of files throughout the network. Recovery is only possible after recovering all fragments and attacking/denying one or more nodes does not limit the availability of other fragment copies in the network. This experiment proved the feasibility of redundant file fragmentation, and is the foundation for developing sophisticated methods to blacklist compromised nodes, move data fragments from risks of compromise, and forward stored data fragments closer to the anticipated retrieval point. This paper outlines initial results in scalability of node members, fragment size, file size, and performance in a heterogeneous network consisting of the Wireless Network after Next (WNaN) radio and Common Sensor Radio (CSR).

GPS-Derived Precipitable Water Compared with the Air Force Weather Agency’s MM5 Model Output

DTIC Science & Technology

2002-03-26

and less then 100 sensors are available throughout Europe . While the receiver density is currently comparable to the upper-air sounding network...profiles from 38 upper air sites throughout Europe . Based on these empirical formulae and simplifications, Bevis (1992) has determined that the error...Alaska using Bevis’ (1992) empirical correlation based on 8718 radiosonde calculations over 2 years. Other studies have been conducted in Europe and

Building and evaluating sensor-based Citizens' Observatories for improving quality of life in cities

NASA Astrophysics Data System (ADS)

Castell, Nuria; Lahoz, William; Schneider, Philipp; Høiskar, Britt Ann; Grossberndt, Sonja; Naderer, Clemens; Robinson, Johanna; Kocman, David; Horvat, Milena; Bartonova, Alena

2014-05-01

Urban air quality, the environmental quality of public spaces and indoor areas such as schools, are areas of great concern to citizens and policymakers. However, access to information addressing these areas is not always available in a user-friendly manner. In particular, the quality and quantity of this information is not consistent across these areas, and does not reflect differences in needs among users. The EU-funded CITI-SENSE project will build on the concept of the Citizens' Observatories to empower citizens to contribute to and participate in environmental governance, and enable them to support and influence decision making by policymakers. To achieve this goal, CITI-SENSE will develop, test, demonstrate and validate a community-based environmental monitoring and information system using low-cost sensors and Earth Observation applications. Key to achieving this goal is the chain "sensors-platforms-products-users" linking providers of technology to users: (i) technologies for distributed monitoring (sensors); (ii) information and communication technologies (platform); (iii) information products and services (products); (iv) and citizen involvement in both monitoring and societal decisions (users). The CITI-SENSE observatories cover three empowerment initiatives: urban air quality; public spaces; and school indoor quality. The empowerment initiatives are being performed at nine locations across Europe. Each location has adapted the generic case study to their local circumstances and has contacted the urban stakeholders needed to run the study. The empowerment initiatives are divided into two phases: a first phase (Pilot Study), and a second phase (Full Implementation). The main goal of the Pilot Study is to test and evaluate the chain "sensors-platform-products-users". To assess the results of the empowerment initiatives, key performance indicators (KPIs) are being developed; these include questionnaires for users. The KPIs will be used to design the full implementation phase of the project. First results from the Pilot Study will be presented for three participating cities: Ljubljana (Slovenia), Vienna (Austria) and Oslo (Norway), which differ in size, environmental conditions and social perception on local air quality. Ljubljana and Oslo empowerment initiatives include urban air quality, and school indoor air quality, while Vienna only includes urban air quality. For the area of urban air quality, the three cities will deploy a wireless network of five static sensor nodes and distribute five personal sensors among people to be carried while performing daily activities in the pilot study. The data will be accessible to users through mobile phones, web services and other devices. For the full implementation phase the sensor network will comprise a total of 20 to 40 static nodes, depending on the size of the city, and 20 personal nodes. For the school indoor air quality three sensors will be allocated inside the school and one outside. The data will be visible provided in school classrooms giving the students a unique and innovative approach to learn about air quality by being involved. Acknowledgements: CITI-SENSE is a Collaborative Project partly funded by the EU FP7-ENV-2012 under grant agreement no 308524. www.citi-sense.eu.

A Novel Cloud-Based Service Robotics Application to Data Center Environmental Monitoring

PubMed Central

Russo, Ludovico Orlando; Rosa, Stefano; Maggiora, Marcello; Bona, Basilio

2016-01-01

This work presents a robotic application aimed at performing environmental monitoring in data centers. Due to the high energy density managed in data centers, environmental monitoring is crucial for controlling air temperature and humidity throughout the whole environment, in order to improve power efficiency, avoid hardware failures and maximize the life cycle of IT devices. State of the art solutions for data center monitoring are nowadays based on environmental sensor networks, which continuously collect temperature and humidity data. These solutions are still expensive and do not scale well in large environments. This paper presents an alternative to environmental sensor networks that relies on autonomous mobile robots equipped with environmental sensors. The robots are controlled by a centralized cloud robotics platform that enables autonomous navigation and provides a remote client user interface for system management. From the user point of view, our solution simulates an environmental sensor network. The system can easily be reconfigured in order to adapt to management requirements and changes in the layout of the data center. For this reason, it is called the virtual sensor network. This paper discusses the implementation choices with regards to the particular requirements of the application and presents and discusses data collected during a long-term experiment in a real scenario. PMID:27509505

A state of the art regarding urban air quality prediction models

NASA Astrophysics Data System (ADS)

Croitoru, Cristiana; Nastase, Ilinca

2018-02-01

Urban pollution represents an increasing risk to residents of urban regions, particularly in large, over-industrialized cities knowing that the traffic is responsible for more than 25% of air gaseous pollutants and dust particles. Air quality modelling plays an important role in addressing air pollution control and management approaches by providing guidelines for better and more efficient air quality forecasting, along with smart monitoring sensor networks. The advances in technology regarding simulations, forecasting and monitoring are part of the new smart cities which offers a healthy environment for their occupants.

Birmingham Urban Climate Laboratory (BUCL): Experiences, Challenges and Applications of an Urban Temperature Network

NASA Astrophysics Data System (ADS)

Muller, Catherine; Chapman, Lee; Young, Duick; Grimmond, Sue; Cai, Xiaoming

2013-04-01

The Birmingham Urban Climate Laboratory (BUCL) has recently been established by the University of Birmingham. BUCL is an in-situ, real-time urban network that will incorporate 3 nested networks - a wide-array of 25 weather stations, a dense array of 131 low-cost air temperature sensors and a fine-array of temperature sensor across the city-centre (50/km^2) - with the primary aim of monitoring air temperatures across a morphologically-heterogeneous urban conurbation for a variety of applications. During its installation there have been a number of challenges to overcome, including siting equipment in suitable urban locations, ensuring that the measurements were 'representative' of the local-scale climate, managing a large, near real-time data set and implementing QA/QC procedures. From these experiences, the establishment of a standardised urban meteorological network metadata protocol has been proposed in order to improve data quality, to ensure the end-user has access to all the supplementary information they would require for conducting valid analyses and to encourage the adequate recording and documentation of any changes to in-situ urban networks over time. This paper will provide an introduction to the BUCL in-situ network, give an overview of the challenges and experiences gained from its implementation, and finally discuss the proposed applications of the network, including its use in remote sensing observations of urban temperatures, as well as health and infrastructure applications.

Air launch wireless sensor nodes (ALSN) for battle damage assessment (BDA)

NASA Astrophysics Data System (ADS)

Back, Jason M.; Beck, Steven D.; Frank, Mark A.; Hoenes, Eric

2006-05-01

This paper summarizes the Defense Threat Reduction Agency (DTRA) sponsored development and demonstration of an Air Launched Sensor Node (ALSN) system designed to fill DTRA's immediate need to support the Global Strike requirement of weapon-borne deliverable sensors for Battle Damage Assessment (BDA). Unattended ground sensors were integrated into a CBU-103 Tactical Munitions Dispenser (TMD), and flight test demonstrated with the 46 th Test Wing at Eglin AFB, FL. The objectives of the ALSN program were to repackage an existing multi-sensor node system to conform to the payload envelope and deployment configuration design; to integrate this payload into the CBU-103 TMD; and to conduct a combined payload flight test demonstration. The final sensor node included multiple sensors a microphone, a geophone, and multiple directional Passive Infrared (PIR) detectors with processing electronics, a low power wireless communications 802.15.4 mesh network, GPS (Global Positioning System), and power integrated into a form-fit BLU-97 munitions deployable package. This paper will present and discuss the flight test, results, and ALSN performance.

Environment quality monitoring using ARM processor

NASA Astrophysics Data System (ADS)

Vinaya, C. H.; Krishna Thanikanti, Vamsi; Ramasamy, Sudha

2017-11-01

This paper of air quality monitoring system describes a model of sensors network to continuously monitoring the environment with low cost developed model. At present time all over the world turned into a great revolution in industrial domain and on the other hand environment get polluting in a dangerous value. There are so many technologies present to reduce the polluting contents but still there is no completely reduction of that pollution. Even there are different methods to monitor the pollution content; these are much costly that not everyone can adapt those methods or devices. Now we are proposing a sensors connected network to monitor the environment continuously and displaying the pollutant gases percentage in air surroundings and can transmit the results to our mobiles by message. The advantage of this system is easy to design, establish at area to monitor, maintenance and most cost effective as well.

Field calibration of electrochemical NO2 sensors in a citizen science context

NASA Astrophysics Data System (ADS)

Mijling, Bas; Jiang, Qijun; de Jonge, Dave; Bocconi, Stefano

2018-03-01

In many urban areas the population is exposed to elevated levels of air pollution. However, real-time air quality is usually only measured at few locations. These measurements provide a general picture of the state of the air, but they are unable to monitor local differences. New low-cost sensor technology is available for several years now, and has the potential to extend official monitoring networks significantly even though the current generation of sensors suffer from various technical issues.Citizen science experiments based on these sensors must be designed carefully to avoid generation of data which is of poor or even useless quality. This study explores the added value of the 2016 Urban AirQ campaign, which focused on measuring nitrogen dioxide (NO2) in Amsterdam, the Netherlands. Sixteen low-cost air quality sensor devices were built and distributed among volunteers living close to roads with high traffic volume for a 2-month measurement period. Each electrochemical sensor was calibrated in-field next to an air monitoring station during an 8-day period, resulting in R2 ranging from 0.3 to 0.7. When temperature and relative humidity are included in a multilinear regression approach, the NO2 accuracy is improved significantly, with R2 ranging from 0.6 to 0.9. Recalibration after the campaign is crucial, as all sensors show a significant signal drift in the 2-month measurement period. The measurement series between the calibration periods can be corrected for after the measurement period by taking a weighted average of the calibration coefficients.Validation against an independent air monitoring station shows good agreement. Using our approach, the standard deviation of a typical sensor device for NO2 measurements was found to be 7 µg m-3, provided that temperatures are below 30 °C. Stronger ozone titration on street sides causes an underestimation of NO2 concentrations, which 75 % of the time is less than 2.3 µg m-3.Our findings show that citizen science campaigns using low-cost sensors based on the current generations of electrochemical NO2 sensors may provide useful complementary data on local air quality in an urban setting, provided that experiments are properly set up and the data are carefully analysed.

Development of a Wireless Network of Temperature Sensors for Yellowstone National Park (USA)

NASA Astrophysics Data System (ADS)

Munday, D. A.; Hutter, T.; Minolli, M.; Obraczka, K.; Manduchi, R.; Petersen, S.; Lowenstern, J. B.; Heasler, H.

2007-12-01

Temperature sensors deployed at Yellowstone clearly document that thermal features can vary in temperature on a variety of timescales and show regional correlations unrelated to meteorological variables such as air temperature. Yellowstone National Park (YNP) staff currently measures temperatures at over 40 thermal features and streams within the park, utilizing USGS stream gaging stations and portable data loggers deployed in geyser basins. The latter measure temperature every 1 to 15 minutes, and the data are physically downloaded after about 30 days. Installation of a wireless sensor network would: 1) save considerable time and effort in data retrieval, 2) minimize lost data due to equipment failure, and 3) provide a means to monitor thermal perturbations in near-real time. To meet this need, we developed a wireless sensor network capable of in-situ monitoring of air and water temperature. Temperature sensors are dispersed as nodes that communicate among themselves and through relays to a single base-station linked to the Internet. The small, weatherproof sensors operate unattended for over six months at temperatures as low as -40°C. Each uses an ultra-low-power Texas Instruments' MSP430 microcontroller and an SD card as mass storage. They are powered by 15Ah, 3.6 v, inert Li-ion batteries and transmit data via 900MHz radio modules with a 1-km range. The initial prototype consists of 4 nodes, and is designed to scale with additional nodes for finer spatial resolution and broader coverage. Temperature measurements are asynchronous from node to node, with intervals as frequent as 30 seconds. Data are stored internally to withstand temporary communication failures; underlying intelligent software is capable of re-routing data through alternative nodes to the base station and a MySQL data archiving system. We also developed a Google-Maps-based, front-end that displays the data, recent trends and sensor locations. The system was tested in the Santa Cruz Mountains and will be used at Yellowstone National Park during Fall 2007.

A Modular IoT Platform for Real-Time Indoor Air Quality Monitoring.

PubMed

Benammar, Mohieddine; Abdaoui, Abderrazak; Ahmad, Sabbir H M; Touati, Farid; Kadri, Abdullah

2018-02-14

The impact of air quality on health and on life comfort is well established. In many societies, vulnerable elderly and young populations spend most of their time indoors. Therefore, indoor air quality monitoring (IAQM) is of great importance to human health. Engineers and researchers are increasingly focusing their efforts on the design of real-time IAQM systems using wireless sensor networks. This paper presents an end-to-end IAQM system enabling measurement of CO₂, CO, SO₂, NO₂, O₃, Cl₂, ambient temperature, and relative humidity. In IAQM systems, remote users usually use a local gateway to connect wireless sensor nodes in a given monitoring site to the external world for ubiquitous access of data. In this work, the role of the gateway in processing collected air quality data and its reliable dissemination to end-users through a web-server is emphasized. A mechanism for the backup and the restoration of the collected data in the case of Internet outage is presented. The system is adapted to an open-source Internet-of-Things (IoT) web-server platform, called Emoncms, for live monitoring and long-term storage of the collected IAQM data. A modular IAQM architecture is adopted, which results in a smart scalable system that allows seamless integration of various sensing technologies, wireless sensor networks (WSNs) and smart mobile standards. The paper gives full hardware and software details of the proposed solution. Sample IAQM results collected in various locations are also presented to demonstrate the abilities of the system.

UAV Cooperation Architectures for Persistent Sensing

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

Roberts, R S; Kent, C A; Jones, E D

2003-03-20

With the number of small, inexpensive Unmanned Air Vehicles (UAVs) increasing, it is feasible to build multi-UAV sensing networks. In particular, by using UAVs in conjunction with unattended ground sensors, a degree of persistent sensing can be achieved. With proper UAV cooperation algorithms, sensing is maintained even though exceptional events, e.g., the loss of a UAV, have occurred. In this paper a cooperation technique that allows multiple UAVs to perform coordinated, persistent sensing with unattended ground sensors over a wide area is described. The technique automatically adapts the UAV paths so that on the average, the amount of time thatmore » any sensor has to wait for a UAV revisit is minimized. We also describe the Simulation, Tactical Operations and Mission Planning (STOMP) software architecture. This architecture is designed to help simulate and operate distributed sensor networks where multiple UAVs are used to collect data.« less

Remote Monitoring of Post-eruption Volcano Environment Based-On Wireless Sensor Network (WSN): The Mount Sinabung Case

NASA Astrophysics Data System (ADS)

Soeharwinto; Sinulingga, Emerson; Siregar, Baihaqi

2017-01-01

An accurate information can be useful for authorities to make good policies for preventive and mitigation after volcano eruption disaster. Monitoring of environmental parameters of post-eruption volcano provides an important information for authorities. Such monitoring system can be develop using the Wireless Network Sensor technology. Many application has been developed using the Wireless Sensor Network technology, such as floods early warning system, sun radiation mapping, and watershed monitoring. This paper describes the implementation of a remote environment monitoring system of mount Sinabung post-eruption. The system monitor three environmental parameters: soil condition, water quality and air quality (outdoor). Motes equipped with proper sensors, as components of the monitoring system placed in sample locations. The measured value from the sensors periodically sends to data server using 3G/GPRS communication module. The data can be downloaded by the user for further analysis.The measurement and data analysis results generally indicate that the environmental parameters in the range of normal/standard condition. The sample locations are safe for living and suitable for cultivation, but awareness is strictly required due to the uncertainty of Sinabung status.

Identifying and monitoring urban heat island in Bucharest using satellite time series and low cost meteorological sensors

NASA Astrophysics Data System (ADS)

Sandric, Ionut; Onose, Diana; Vanau, Gabriel; Ioja, Cristian

2016-04-01

The present study is focusing on the identification of urban heat island in Bucharest using both remote sensing products and low cost temperature sensors. The urban heat island in Bucharest was analyzed through a network of sensors located in 56 points (47 inside the administrative boundary of the city, 9 outside) 2009-2011. The network lost progressively its initial density, but was reformed during a new phase, 2013-2015. Time series satellite images from MODIS were intersected with the sensors for both phases. Statistical analysis were conducted to identify the temporal and spatial pattern of extreme temperatures in Bucharest. Several environmental factors like albedou, presence and absence of vegetation were used to fit a regression model between MODIS satellite products sensors in order to upscale the temperatures values recorded by MODIS For Bucharest, an important role for air temperature values in urban environments proved to have the local environmental conditions that leads to differences in air temperature at Bucharest city scale between 3-5 °C (both in the summer and in the winter). The UHI maps shows a good correlation with the presence of green areas. Differences in air temperature between higher tree density areas and isolated trees can reach much higher values, averages over 24 h periods still are in the 3-5 °C range The results have been obtained within the project UCLIMESA (Urban Heat Island Monitoring under Present and Future Climate), ongoing between 2013 and 2015 in the framework of the Programme for Research-DevelopmentInnovation for Space Technology and Advanced Research (STAR), administrated by the Romanian Space Agency Keywords: time series, urban heat island

Optimization of Emissions Sensor Networks Incorporating Tradeoffs Between Different Sensor Technologies

NASA Astrophysics Data System (ADS)

Nicholson, B.; Klise, K. A.; Laird, C. D.; Ravikumar, A. P.; Brandt, A. R.

2017-12-01

In order to comply with current and future methane emissions regulations, natural gas producers must develop emissions monitoring strategies for their facilities. In addition, regulators must develop air monitoring strategies over wide areas incorporating multiple facilities. However, in both of these cases, only a limited number of sensors can be deployed. With a wide variety of sensors to choose from in terms of cost, precision, accuracy, spatial coverage, location, orientation, and sampling frequency, it is difficult to design robust monitoring strategies for different scenarios while systematically considering the tradeoffs between different sensor technologies. In addition, the geography, weather, and other site specific conditions can have a large impact on the performance of a sensor network. In this work, we demonstrate methods for calculating optimal sensor networks. Our approach can incorporate tradeoffs between vastly different sensor technologies, optimize over typical wind conditions for a particular area, and consider different objectives such as time to detection or geographic coverage. We do this by pre-computing site specific scenarios and using them as input to a mixed-integer, stochastic programming problem that solves for a sensor network that maximizes the effectiveness of the detection program. Our methods and approach have been incorporated within an open source Python package called Chama with the goal of providing facility operators and regulators with tools for designing more effective and efficient monitoring systems. Sandia National Laboratories is a multi-mission laboratory managed and operated by National Technology and Engineering Solutions of Sandia, LLC., a wholly owned subsidiary of Honeywell International, Inc., for the U.S. Department of Energys National Nuclear Security Administration under contract DE-NA0003525.

Development of high-resolution (250 m) historical daily gridded air temperature data using reanalysis and distributed sensor networks for the US northern Rocky Mountains

Treesearch

Zachary A. Holden; Alan Swanson; Anna E. Klene; John T. Abatzoglou; Solomon Z. Dobrowski; Samuel A. Cushman; John Squires; Gretchen G. Moisen; Jared W. Oyler

2016-01-01

Gridded temperature data sets are typically produced at spatial resolutions that cannot fully resolve fine-scale variation in surface air temperature in regions of complex topography. These data limitations have become increasingly important as scientists and managers attempt to understand and plan for potential climate change impacts. Here, we describe the...

CAIRSENSE-Atlanta

EPA Pesticide Factsheets

Short time interval comparisons of low cost sensor response and corresponding Federal Reference or Federal Equivalent Monitors at an NCOR site located in proximity to Atlanta, GeorgiaThis dataset is associated with the following publication:Jiao, W., G. Hagler, R. Williams, R. Sharpe, R. Brown, D. Garver, R. Judge, M. Caudill, J. Rickard, M. Davis, L. Weinstock, S. Zimmer-Dauphinee, and K. Buckley. Community Air Sensor Network (CAIRSENSE) project: Evaluation of low-cost sensor performance in a suburban environment in the southeastern United States. Atmospheric Measurement Techniques. Copernicus Publications, Katlenburg-Lindau, GERMANY, 9: 5282-5292, (2016).

MEMS device for mass market gas and chemical sensors

NASA Astrophysics Data System (ADS)

Kinkade, Brian R.; Daly, James T.; Johnson, Edward A.

2000-08-01

Gas and chemical sensors are used in many applications. Industrial health and safety monitors allow companies to meet OSHA requirements by detecting harmful levels of toxic or combustible gases. Vehicle emissions are tested during annual inspections. Blood alcohol breathalizers are used by law enforcement. Refrigerant leak detection ensures that the Earth's ozone layer is not being compromised. Industrial combustion emissions are also monitored to minimize pollution. Heating and ventilation systems watch for high levels of carbon dioxide (CO2) to trigger an increase in fresh air exchange. Carbon monoxide detectors are used in homes to prevent poisoning from poor combustion ventilation. Anesthesia gases are monitored during a patients operation. The current economic reality is that two groups of gas sensor technologies are competing in two distinct existing market segments - affordable (less reliable) chemical reaction sensors for consumer markets and reliable (expensive) infrared (IR) spectroscopic sensors for industrial, laboratory, and medical instrumentation markets. Presently high volume mass-market applications are limited to CO detectros and on-board automotive emissions sensors. Due to reliability problems with electrochemical sensor-based CO detectors there is a hesitancy to apply these sensors in other high volume applications. Applications such as: natural gas leak detection, non-invasive blood glucose monitoring, home indoor air quality, personal/portable air quality monitors, home fire/burnt cooking detector, and home food spoilage detectors need a sensor that is a small, efficient, accurate, sensitive, reliable, and inexpensive. Connecting an array of these next generation gas sensors to wireless networks that are starting to proliferate today creates many other applications. Asthmatics could preview the air quality of their destinations as they venture out into the day. HVAC systems could determine if fresh air intake was actually better than the air in the house. Internet grocery delivery services could check for spoiled foods in their clients' refrigerators. City emissions regulators could monitor the various emissions sources throughout the area from their desk to predict how many pollution vouchers they will need to trade in the next week. We describe a new component architecture for mass-market sensors based on silicon microelectromechanical systems (MEMS) technology. MEMS are micrometer-scale devices that can be fabricated as discrete devices or large arrays, using the technology of integrated circuit manufacturing. These new photonic bandgap and MEMS fabricataion technologies will simplify the component technology to provide high-quality gas and chemical sensors at consumer prices.

A Mobile Sensor Network to Map CO2 in Urban Environments

NASA Astrophysics Data System (ADS)

Lee, J.; Christen, A.; Nesic, Z.; Ketler, R.

2014-12-01

Globally, an estimated 80% of all fuel-based CO2 emissions into the atmosphere are attributable to cities, but there is still a lack of tools to map, visualize and monitor emissions to the scales at which emissions reduction strategies can be implemented - the local and urban scale. Mobile CO2 sensors, such as those attached to taxis and other existing mobile platforms, may be a promising way to observe and map CO2 mixing ratios across heterogenous urban environments with a limited number of sensors. Emerging modular open source technologies, and inexpensive compact sensor components not only enable rapid prototyping and replication, but also are allowing for the miniaturization and mobilization of traditionally fixed sensor networks. We aim to optimize the methods and technologies for monitoring CO2 in cities using a network of CO2 sensors deployable on vehicles and bikes. Our sensor technology is contained in a compact weather-proof case (35.8cm x 27.8cm x 11.8cm), powered independently by battery or by car, and includes the Li-Cor Li-820 infrared gas analyzer (Licor Inc, lincoln, NB, USA), Arduino Mega microcontroller (Arduino CC, Italy) and Adafruit GPS (Adafruit Technologies, NY, USA), and digital air temperature thermometer which measure CO2 mixing ratios (ppm), geolocation and speed, pressure and temperature, respectively at 1-second intervals. With the deployment of our sensor technology, we will determine if such a semi-autonomous mobile approach to monitoring CO2 in cities can determine excess urban CO2 mixing ratios (i.e. the 'urban CO2 dome') when compared to values measured at a fixed, remote background site. We present results from a pilot study in Vancouver, BC, where the a network of our new sensors was deployed both in fixed network and in a mobile campaign and examine the spatial biases of the two methods.

Air Force Research Laboratory Resident Associateship Program Continuation

DTIC Science & Technology

2014-12-04

2011-7/17/2012 United States Received Veremyev, Alexander Fedorovich Pasiliao, Eduardo Lewis 8/1/2012-7/31/2013 Russia Sensors Directorate Aga...mass and damping on their modal characteristics. 5 Aerodynamic loads were estimated from the wind -tunnel test data, where the angle of attack of the... Wireless Networks; Throughput Optimization for Cognitive Radio Network with Slowly Varying Channels. 2 Capacity Optimization of MIMO Links with

The “Wireless Sensor Networks for City-Wide Ambient Intelligence (WISE-WAI)” Project

PubMed Central

Casari, Paolo; Castellani, Angelo P.; Cenedese, Angelo; Lora, Claudio; Rossi, Michele; Schenato, Luca; Zorzi, Michele

2009-01-01

This paper gives a detailed technical overview of some of the activities carried out in the context of the “Wireless Sensor networks for city-Wide Ambient Intelligence (WISE-WAI)” project, funded by the Cassa di Risparmio di Padova e Rovigo Foundation, Italy. The main aim of the project is to demonstrate the feasibility of large-scale wireless sensor network deployments, whereby tiny objects integrating one or more environmental sensors (humidity, temperature, light intensity), a microcontroller and a wireless transceiver are deployed over a large area, which in this case involves the buildings of the Department of Information Engineering at the University of Padova. We will describe how the network is organized to provide full-scale automated functions, and which services and applications it is configured to provide. These applications include long-term environmental monitoring, alarm event detection and propagation, single-sensor interrogation, localization and tracking of objects, assisted navigation, as well as fast data dissemination services to be used, e.g., to rapidly re-program all sensors over-the-air. The organization of such a large testbed requires notable efforts in terms of communication protocols and strategies, whose design must pursue scalability, energy efficiency (while sensors are connected through USB cables for logging and debugging purposes, most of them will be battery-operated), as well as the capability to support applications with diverse requirements. These efforts, the description of a subset of the results obtained so far, and of the final objectives to be met are the scope of the present paper. PMID:22408513

Using Arduinos and 3D-printers to Build Research-grade Weather Stations and Environmental Sensors

NASA Astrophysics Data System (ADS)

Ham, J. M.

2013-12-01

Many plant, soil, and surface-boundary-layer processes in the geosphere are governed by the microclimate at the land-air interface. Environmental monitoring is needed at smaller scales and higher frequencies than provided by existing weather monitoring networks. The objective of this project was to design, prototype, and test a research-grade weather station that is based on open-source hardware/software and off-the-shelf components. The idea is that anyone could make these systems with only elementary skills in fabrication and electronics. The first prototypes included measurements of air temperature, humidity, pressure, global irradiance, wind speed, and wind direction. The best approach for measuring precipitation is still being investigated. The data acquisition system was deigned around the Arduino microcontroller and included an LCD-based user interface, SD card data storage, and solar power. Sensors were sampled at 5 s intervals and means, standard deviations, and maximum/minimums were stored at user-defined intervals (5, 30, or 60 min). Several of the sensor components were printed in plastic using a hobby-grade 3D printer (e.g., RepRap Project). Both passive and aspirated radiation shields for measuring air temperature were printed in white Acrylonitrile Butadiene Styrene (ABS). A housing for measuring solar irradiance using a photodiode-based pyranometer was printed in opaque ABS. The prototype weather station was co-deployed with commercial research-grade instruments at an agriculture research unit near Fort Collins, Colorado, USA. Excellent agreement was found between Arduino-based system and commercial weather instruments. The technology was also used to support air quality research and automated air sampling. The next step is to incorporate remote access and station-to-station networking using Wi-Fi, cellular phone, and radio communications (e.g., Xbee).

Using Wireless Sensor Networks in Improvised Explosive Device Detection

DTIC Science & Technology

2007-12-01

data collection (permitting self - healing when a node failure occurs); Sensor nodes Gateway nodes 24 • Energy efficiency (necessary to maintain...Runner” robotic platform (see Figure 1). It is reported that this system can detect a wide range of IEDs, even those concealed in vehicles. However...be as simple as running over a rubber hose to produce enough air pressure to activate a switch. Some IEDs have been remotely detonated with radio

Localisation of an Unknown Number of Land Mines Using a Network of Vapour Detectors

PubMed Central

Chhadé, Hiba Haj; Abdallah, Fahed; Mougharbel, Imad; Gning, Amadou; Julier, Simon; Mihaylova, Lyudmila

2014-01-01

We consider the problem of localising an unknown number of land mines using concentration information provided by a wireless sensor network. A number of vapour sensors/detectors, deployed in the region of interest, are able to detect the concentration of the explosive vapours, emanating from buried land mines. The collected data is communicated to a fusion centre. Using a model for the transport of the explosive chemicals in the air, we determine the unknown number of sources using a Principal Component Analysis (PCA)-based technique. We also formulate the inverse problem of determining the positions and emission rates of the land mines using concentration measurements provided by the wireless sensor network. We present a solution for this problem based on a probabilistic Bayesian technique using a Markov chain Monte Carlo sampling scheme, and we compare it to the least squares optimisation approach. Experiments conducted on simulated data show the effectiveness of the proposed approach. PMID:25384008

The Use of Mobile, Electrochemical Sensor Nodes for the Measurement of Personal Exposure to Gas-Phase Air Pollutants

NASA Astrophysics Data System (ADS)

Stewart, G.; Popoola, O. A.; Mead, M. I.; McKeating, S. J.; Calleja, M.; Hayes, M.; Baron, R. P.; Saffell, J.; Jones, R.

2012-12-01

In this paper we describe how low-cost, lightweight devices, which incorporate GPS and GPRS facilities and contain electrochemical sensors for carbon monoxide (CO), nitrogen monoxide (NO) and nitrogen dioxide (NO2), have been used to collect data representative of personal exposure to these important urban air pollutants. E.U. legislation has set target levels for gases thought to have adverse impacts on human health, and consequently led to a need for a more informed air pollution control policy. With many sites in the U.K. and in the rest of the E.U. still failing to meet annual targets for NO2, a need to better understand pollutant sources and behaviour has arisen. Moreover, while traditional chemiluminescence techniques provide precise measurements, the instruments are sparsely populated around urban centres and are thus limited in their ability to account for true personal exposure. Through a series of laboratory and field studies, it has been shown that electrochemical sensor nodes, when configured suitably and after post-processing of data, can provide selective, reproducible measurements, and that the devices have appropriate detection limits (at the low parts-per-billion level), as well as fast enough response times, for urban air quality studies. Both mobile nodes and their static analogues have been deployed with different aims. Static nodes have been used in dense networks in both the urban environment and in the grounds of a major international airport, as described in the partner papers of Mead et al and Bright et al. Mobile units are easily deployed in scalable networks for short-term studies on personal exposure; these studies have been carried out in a wide range of locations including Lagos, Kuala-Lumpur, London and Valencia. Data collected by both mobile and static sensor nodes illustrate the insufficiency of the existing infrastructure in accounting for both the spatial and temporal variability in air pollutants due to road traffic emissions, and thus also the potential insufficiency at quantifying the risks to health in the surrounding area. Recent campaigns with mobile sensor nodes have included attempts to probe the differences in personal exposure to gas-phase air pollutants at different heights of breathing zone and between different methods of transport.

Integrated microelectronics for smart textiles.

PubMed

Lauterbach, Christl; Glaser, Rupert; Savio, Domnic; Schnell, Markus; Weber, Werner

2005-01-01

The combination of textile fabrics with microelectronics will lead to completely new applications, thus achieving elements of ambient intelligence. The integration of sensor or actuator networks, using fabrics with conductive fibres as a textile motherboard enable the fabrication of large active areas. In this paper we describe an integration technology for the fabrication of a "smart textile" based on a wired peer-to-peer network of microcontrollers with integrated sensors or actuators. A self-organizing and fault-tolerant architecture is accomplished which detects the physical shape of the network. Routing paths are formed for data transmission, automatically circumventing defective or missing areas. The network architecture allows the smart textiles to be produced by reel-to-reel processes, cut into arbitrary shapes subsequently and implemented in systems at low installation costs. The possible applications are manifold, ranging from alarm systems to intelligent guidance systems, passenger recognition in car seats, air conditioning control in interior lining and smart wallpaper with software-defined light switches.

Novel Method for Detection of Air Pollution using Cellular Communication Networks

NASA Astrophysics Data System (ADS)

David, N.; Gao, O. H.

2016-12-01

Air pollution can lead to a wide spectrum of severe and chronic health impacts. Conventional tools for monitoring the phenomenon do not provide a sufficient monitoring solution in a global scale since they are, for example, not representative of the larger space or due to limited deployment as a result of practical limitations, such as: acquisition, installation, and ongoing maintenance costs. Near ground temperature inversions are directly identified with air pollution events since they suppress vertical atmospheric movement and trap pollutants near the ground. Wireless telecommunication links that comprise the data transfer infrastructure in cellular communication networks operate at frequencies of tens of GHz and are affected by different atmospheric phenomena. These systems are deployed near ground level across the globe, including in developing countries such as India, countries in Africa, etc. Many cellular providers routinely store data regarding the received signal levels in the network for quality assurance needs. Temperature inversions cause atmospheric layering, and change the refractive index of the air when compared to standard conditions. As a result, the ducts that are formed can operate, in essence, as atmospheric wave guides, and cause interference (signal amplification / attenuation) in the microwaves measured by the wireless network. Thus, this network is in effect, an existing system of environmental sensors for monitoring temperature inversions and the episodes of air pollution identified with them. This work presents the novel idea, and demonstrates it, in operation, over several events of air pollution which were detected by a standard cellular communication network during routine operation. Reference: David, N. and Gao, H.O. Using cellular communication networks to detect air pollution, Environmental Science & Technology, 2016 (accepted).

A Modular IoT Platform for Real-Time Indoor Air Quality Monitoring

PubMed Central

Abdaoui, Abderrazak; Ahmad, Sabbir H.M.; Touati, Farid; Kadri, Abdullah

2018-01-01

The impact of air quality on health and on life comfort is well established. In many societies, vulnerable elderly and young populations spend most of their time indoors. Therefore, indoor air quality monitoring (IAQM) is of great importance to human health. Engineers and researchers are increasingly focusing their efforts on the design of real-time IAQM systems using wireless sensor networks. This paper presents an end-to-end IAQM system enabling measurement of CO2, CO, SO2, NO2, O3, Cl2, ambient temperature, and relative humidity. In IAQM systems, remote users usually use a local gateway to connect wireless sensor nodes in a given monitoring site to the external world for ubiquitous access of data. In this work, the role of the gateway in processing collected air quality data and its reliable dissemination to end-users through a web-server is emphasized. A mechanism for the backup and the restoration of the collected data in the case of Internet outage is presented. The system is adapted to an open-source Internet-of-Things (IoT) web-server platform, called Emoncms, for live monitoring and long-term storage of the collected IAQM data. A modular IAQM architecture is adopted, which results in a smart scalable system that allows seamless integration of various sensing technologies, wireless sensor networks (WSNs) and smart mobile standards. The paper gives full hardware and software details of the proposed solution. Sample IAQM results collected in various locations are also presented to demonstrate the abilities of the system. PMID:29443893

Survey of energy harvesting and energy scavenging approaches for on-site powering of wireless sensor- and microinstrument-networks

NASA Astrophysics Data System (ADS)

Lee, D.; Dulai, G.; Karanassios, Vassili

2013-05-01

Energy (or power) harvesting can be defined as the gathering and either storing or immediately using energy "freely" available in a local environment. Examples include harvesting energy from obvious sources such as photon-fluxes (e.g., solar), or wind or water waves, or from unusual sources such as naturally occurring pH differences. Energy scavenging can be defined as gathering and storing or immediately re-using energy that has been discarded, for instance, waste heat from air conditioning units, from in-door lights or from everyday actions such as walking or from body-heat. Although the power levels that can be harvested or scavenged are typically low (e.g., from nWatt/cm2 to mWatt/cm2), the key motivation is to harvest or to scavenge energy for a wide variety of applications. Example applications include powering devices in remote weather stations, or wireless Bluetooth headsets, or wearable computing devices or for sensor networks for health and bio-medical applications. Beyond sensors and sensor networks, there is a need to power compete systems, such as portable and energy-autonomous chemical analysis microinstruments for use on-site. A portable microinstrument is one that offers the same functionality as a large one but one that has at least one critical component in the micrometer regime. This paper surveys continuous or discontinuous energy harvesting and energy scavenging approaches (with particular emphasis on sensor and microinstrument networks) and it discusses current trends. It also briefly explores potential future directions, for example, for nature-inspired (e.g., photosynthesis), for human-power driven (e.g., for biomedical applications, or for wearable sensor networks) or for nanotechnology-enabled energy harvesting and energy scavenging approaches.

Autonomous Vehicles and the Net-Centric Battlespace

DTIC Science & Technology

2000-04-01

Autonomous vehicles are playing increasing roles in the air/land/sea network of today’s battlespace. As the Navy’s lead laboratory for command...including remote sensor platforms, communication relays, and work platforms. As these capabilities are developed autonomous vehicles will become an

MARSnet: Mission-aware Autonomous Radar Sensor Network for Future Combat Systems

DTIC Science & Technology

2007-05-03

34Parameter estimation for 3-parameter log-logistic distribution (LLD3) by Porne ", Parameter estimation for 3-parameter log-logistic distribu- tion...section V we physical security, air traffic control, traffic monitoring, andvidefaconu s cribedy. video surveillance, industrial automation etc. Each

Spatio-temporal measurement of indoor particulate matter concentrations using a wireless network of low-cost sensors in households using solid fuels.

PubMed

Patel, Sameer; Li, Jiayu; Pandey, Apoorva; Pervez, Shamsh; Chakrabarty, Rajan K; Biswas, Pratim

2017-01-01

Many households use solid fuels for cooking and heating purposes. There is currently a knowledge gap in our understanding of the variations in indoor air quality throughout the household as most of the studies focus on the areas in the close proximity of the cookstove. A low-cost wireless particulate matter (PM) sensor network was developed and deployed in households in Raipur, India to establish the spatio-temporal variation of PM concentrations. The data from multiple sensors were acquired in real-time with a wireless system. Data collected from the sensors agreed well (R 2 =0.713) with the reference data collected from a commercially available instrument. Low spatial variability was observed within the kitchen due to its small size and poor ventilation - a common feature of most rural Indian kitchens. Due to insufficient ventilation from open doors and windows, high PM concentrations similar to those found in the kitchen were also found in the adjoining rooms. The same household showed significantly different post-extinguished cookstove PM concentration decay rates (0.26mg/m 3 -min and 0.87mg/m 3 -min) on different days, owing to varying natural air exchange rates (7.68m 3 /min and 37.40m 3 /min). Copyright © 2016 Elsevier Inc. All rights reserved.

Assessing community exposure to hazardous air pollutants by combining optical remote sensing and "low-cost" sensor technologies

NASA Astrophysics Data System (ADS)

Pikelnaya, O.; Polidori, A.; Wimmer, R.; Mellqvist, J.; Samuelsson, J.; Marianne, E.; Andersson, P.; Brohede, S.; Izos, O.

2017-12-01

Industrial facilities such as refineries and oil processing facilities can be sources of chemicals adversely affecting human health, for example aromatic hydrocarbons and formaldehyde. In an urban setting, such as the South Coast Air Basin (SCAB), exposure to harmful air pollutants (HAP's) for residents of communities neighboring such facilities is of serious concern. Traditionally, exposure assessments are performed by modeling a community exposure using emission inventories and data collected at fixed air monitoring sites. However, recent field measurements found that emission inventories may underestimate HAP emissions from refineries; and HAP measurements data from fixed sites is lacking spatial resolution; as a result, the impact of HAP emissions on communities is highly uncertain. The next generation air monitoring technologies can help address these challenges. For example, dense "low-cost" sensors allow continuous monitoring of concentrations of pollutants within communities with high temporal- and spatial- resolution, and optical remote sensing (ORS) technologies offer measurements of emission fluxes and real-time ground-concentration mapping of HAPs. South Coast Air Quality Management District (SCAQMD) is currently conducting a multi-year study using ORS methods and "low-cost" Volatile Organic Compounds (VOCs) sensors to monitor HAP emissions from selected industrial facilities in the SCAB and their ambient concentrations in neighboring communities. For this purpose, quarterly mobile ORS surveys are conducted to quantify facility-wide emissions for VOCs, aromatic hydrocarbons and HCHO, and to collect ground-concentration profiles of these pollutants inside neighboring communities. Additionally, "low-cost" sensor nodes for deployment in neighborhood(s) downwind of the facilities have been developed in order to obtain long-term, granular data on neighborhood VOC concentrations, During this presentation we will discuss initial results of quarterly ORS surveys and pilot "low-cost" sensor deployments. We will also outline benefits of using a combination of mobile ORS surveys and "low-cost" sensor networks for community exposure monitoring.

FIRESTORM: a collaborative network suite application for rapid sensor data processing and precise decisive responses

NASA Astrophysics Data System (ADS)

Kaniyantethu, Shaji

2011-06-01

This paper discusses the many features and composed technologies in Firestorm™ - a Distributed Collaborative Fires and Effects software. Modern response management systems capitalize on the capabilities of a plethora of sensors and its output for situational awareness. Firestorm utilizes a unique networked lethality approach by integrating unmanned air and ground vehicles to provide target handoff and sharing of data between humans and sensors. The system employs Bayesian networks for track management of sensor data, and distributed auction algorithms for allocating targets and delivering the right effect without information overload to the Warfighter. Firestorm Networked Effects Component provides joint weapon-target pairing, attack guidance, target selection standards, and other fires and effects components. Moreover, the open and modular architecture allows for easy integration with new data sources. Versatility and adaptability of the application enable it to devise and dispense a suitable response to a wide variety of scenarios. Recently, this application was used for detecting and countering a vehicle intruder with the help of radio frequency spotter sensor, command driven cameras, remote weapon system, portable vehicle arresting barrier, and an unmanned aerial vehicle - which confirmed the presence of the intruder, as well as provided lethal/non-lethal response and battle damage assessment. The completed demonstrations have proved Firestorm's™ validity and feasibility to predict, detect, neutralize, and protect key assets and/or area against a variety of possible threats. The sensors and responding assets can be deployed with numerous configurations to cover the various terrain and environmental conditions, and can be integrated to a number of platforms.

The AirQuality SenseBox

NASA Astrophysics Data System (ADS)

Demuth, Dustin; Nuest, Daniel; Bröring, Arne; Pebesma, Edzer

2013-04-01

In the past year, a group of open hardware enthusiasts and citizen scientists had large success in the crowd-funding of an open hardware-based sensor platform for air quality monitoring, called the Air Quality Egg. Via the kickstarter platform, the group was able to collect triple the amount of money than needed to fulfill their goals. Data generated by the Air Quality Egg is pushed to the data logging platform cosm.com, which makes the devices a part of the Internet of Things. The project aims at increasing the participation of citizens in the collection of data, the development of sensors, the operation of sensor stations, and, as data on cosm is publicly available, the sharing, visualization and analysis of data. Air Quality Eggs can measure NO2 and CO concentrations, as well as relative humidity and temperature. The chosen sensors are low-cost and have limited precision and accurracy. The Air Quality Egg consists of a stationary outdoor and a stationary indoor unit. Each outdoor unit will wirelessly transmit air quality measurements to the indoor unit, which forwards the data to cosm. Most recent versions of the Air Quality Egg allow a rough calibration of the gas sensors and on-the-fly conversion from raw sensor readings (impedance) to meaningful air quality data expressed in units of parts per billion. Data generated by these low-cost platforms are not intended to replace well-calibrated official monitoring stations, but rather augment the density of the total monitoring network with citizen sensors. To improve the usability of the Air Quality Egg, we present a new and more advanced concept, called the AirQuality SenseBox. We made the outdoor platform more autonomous and location-aware by adding solarpanels and rechargeable batteries as a power source. The AirQuality SenseBox knows its own position from a GPS device attached to the platform. As a mobile sensor platform, it can for instance be attached to vehicles. A low-cost and low-power wireless chipset reads the sensors and broadcasts the data. The data is received by gateways that convert the data and forward it to services. Although cosm is still supported, we also use services that are more common in the scientific domain, in particular the OGC Sensor Observation Service. In contrast to the ``One Sender - One Receiver'' (pair) setup proposed by the platform developers, we follow a ``Many Senders - Many Receivers'' (mesh) solution. As data is broadcasted by the platforms, it can be received and processed by any gateway, and, as the sender is not bound to the receiver, applications different from the gateways can receive and evaluate the data measured by the platform. Advantages of our solution are: (i) prepared gateways, which have more precise data at hand, can send calibration instructions to the mobile sensor platforms when those are in proximity; (ii) redundancy is obtained by adding additional gateways, to avoid the loss of data if a gateway fails; (iii) autonomous stations can be ubiquitous, are robust, do not require frequent maintenance, and can be placed at arbitrary locations; (iv) the standardized interface is vendor-independent and allows direct integration into existing analysis software.

Potentials and Limitations of Wireless Sensor Networks for Environmental

NASA Astrophysics Data System (ADS)

Bumberger, J.; Remmler, P.; Hutschenreuther, T.; Toepfer, H.; Dietrich, P.

2013-12-01

Understanding and dealing with environmental challenges worldwide requires suitable interdisciplinary methods and a level of expertise to be able to implement these solutions, so that the lifestyles of future generations can be secured in the years to come. To characterize environmental systems it is necessary to identify and describe processes with suitable methods. Environmental systems are often characterized by their high heterogeneity, so individual measurements for their complete representation are often not sufficient. The application of wireless sensor networks in terrestrial and aquatic ecosystems offer significant benefits as a better consideration of the local test conditions becomes possible. This can be essential for the monitoring of heterogeneous environmental systems. Significant advantages in the application of wireless sensor networks are their self-organizing behaviour, resulting in a major reduction in installation and operation costs and time. In addition, a point measurement with a sensor is significantly improved by measuring at several points. It is also possible to perform analog and digital signal processing and computation on the basis of the measured data close to the sensor. Hence, a significant reduction of the data to be transmitted can be achieved which leads to a better energy management of sensor nodes. Furthermore, their localization via satellite, the miniaturization of the nodes and long-term energy self-sufficiency are current topics under investigation. In this presentation, the possibilities and limitations of the applicability of wireless sensor networks for long-term environmental monitoring are presented. To underline the importance of this future technology, example concepts are given in the field of near-surface geothermics, groundwater observation, measurement of spatial radiation intensity and air humidity on soils, measurement of matter fluxes, greenhouse gas measurement, and landslide monitoring.

A machine learning calibration model using random forests to improve sensor performance for lower-cost air quality monitoring

NASA Astrophysics Data System (ADS)

Zimmerman, Naomi; Presto, Albert A.; Kumar, Sriniwasa P. N.; Gu, Jason; Hauryliuk, Aliaksei; Robinson, Ellis S.; Robinson, Allen L.; Subramanian, R.

2018-01-01

Low-cost sensing strategies hold the promise of denser air quality monitoring networks, which could significantly improve our understanding of personal air pollution exposure. Additionally, low-cost air quality sensors could be deployed to areas where limited monitoring exists. However, low-cost sensors are frequently sensitive to environmental conditions and pollutant cross-sensitivities, which have historically been poorly addressed by laboratory calibrations, limiting their utility for monitoring. In this study, we investigated different calibration models for the Real-time Affordable Multi-Pollutant (RAMP) sensor package, which measures CO, NO2, O3, and CO2. We explored three methods: (1) laboratory univariate linear regression, (2) empirical multiple linear regression, and (3) machine-learning-based calibration models using random forests (RF). Calibration models were developed for 16-19 RAMP monitors (varied by pollutant) using training and testing windows spanning August 2016 through February 2017 in Pittsburgh, PA, US. The random forest models matched (CO) or significantly outperformed (NO2, CO2, O3) the other calibration models, and their accuracy and precision were robust over time for testing windows of up to 16 weeks. Following calibration, average mean absolute error on the testing data set from the random forest models was 38 ppb for CO (14 % relative error), 10 ppm for CO2 (2 % relative error), 3.5 ppb for NO2 (29 % relative error), and 3.4 ppb for O3 (15 % relative error), and Pearson r versus the reference monitors exceeded 0.8 for most units. Model performance is explored in detail, including a quantification of model variable importance, accuracy across different concentration ranges, and performance in a range of monitoring contexts including the National Ambient Air Quality Standards (NAAQS) and the US EPA Air Sensors Guidebook recommendations of minimum data quality for personal exposure measurement. A key strength of the RF approach is that it accounts for pollutant cross-sensitivities. This highlights the importance of developing multipollutant sensor packages (as opposed to single-pollutant monitors); we determined this is especially critical for NO2 and CO2. The evaluation reveals that only the RF-calibrated sensors meet the US EPA Air Sensors Guidebook recommendations of minimum data quality for personal exposure measurement. We also demonstrate that the RF-model-calibrated sensors could detect differences in NO2 concentrations between a near-road site and a suburban site less than 1.5 km away. From this study, we conclude that combining RF models with carefully controlled state-of-the-art multipollutant sensor packages as in the RAMP monitors appears to be a very promising approach to address the poor performance that has plagued low-cost air quality sensors.

Classification of buildings mold threat using electronic nose

NASA Astrophysics Data System (ADS)

Łagód, Grzegorz; Suchorab, Zbigniew; Guz, Łukasz; Sobczuk, Henryk

2017-07-01

Mold is considered to be one of the most important features of Sick Building Syndrome and is an important problem in current building industry. In many cases it is caused by the rising moisture of building envelopes surface and exaggerated humidity of indoor air. Concerning historical buildings it is mostly caused by outdated raising techniques among that is absence of horizontal isolation against moisture and hygroscopic materials applied for construction. Recent buildings also suffer problem of mold risk which is caused in many cases by hermetization leading to improper performance of gravitational ventilation systems that make suitable conditions for mold development. Basing on our research there is proposed a method of buildings mold threat classification using electronic nose, based on a gas sensors array which consists of MOS sensors (metal oxide semiconductor). Used device is frequently applied for air quality assessment in environmental engineering branches. Presented results show the interpretation of e-nose readouts of indoor air sampled in rooms threatened with mold development in comparison with clean reference rooms and synthetic air. Obtained multivariate data were processed, visualized and classified using a PCA (Principal Component Analysis) and ANN (Artificial Neural Network) methods. Described investigation confirmed that electronic nose - gas sensors array supported with data processing enables to classify air samples taken from different rooms affected with mold.

Chip-to-chip SnO2 nanowire network sensors for room temperature H2 detection

NASA Astrophysics Data System (ADS)

Köck, A.; Brunet, E.; Mutinati, G. C.; Maier, T.; Steinhauer, S.

2012-06-01

The employment of nanowires is a very powerful strategy to improve gas sensor performance. We demonstrate a gas sensor device, which is based on silicon chip-to-chip synthesis of ultralong tin oxide (SnO2) nanowires. The sensor device employs an interconnected SnO2 nanowire network configuration, which exhibits a huge surface-to-volume ratio and provides full access of the target gas to the nanowires. The chip-to-chip SnO2 nanowire device is able to detect a H2 concentration of only 20 ppm in synthetic air with ~ 60% relative humidity at room temperature. At an operating temperature of 300°C a concentration of 50 ppm H2 results in a sensitivity of 5%. At this elevated temperature the sensor shows a linear response in a concentration range between 10 ppm and 100 ppm H2. The SnO2-nanowire fabrication procedure based on spray pyrolysis and subsequent annealing is performed at atmospheric pressure, requires no vacuum and allows upscale of the substrate to a wafer size. 3D-integration with CMOS chips is proposed as viable way for practical realization of smart nanowire based gas sensor devices for the consumer market.

Fast notification architecture for wireless sensor networks

NASA Astrophysics Data System (ADS)

Lee, Dong-Hahk

2013-03-01

In an emergency, since it is vital to transmit the message to the users immediately after analysing the data to prevent disaster, this article presents the deployment of a fast notification architecture for a wireless sensor network. The sensor nodes of the proposed architecture can monitor an emergency situation periodically and transmit the sensing data, immediately to the sink node. We decide on the grade of fire situation according to the decision rule using the sensing values of temperature, CO, smoke density and temperature increasing rate. On the other hand, to estimate the grade of air pollution, the sensing data, such as dust, formaldehyde, NO2, CO2, is applied to the given knowledge model. Since the sink node in the architecture has a ZigBee interface, it can transmit the alert messages in real time according to analysed results received from the host server to the terminals equipped with a SIM card-type ZigBee module. Also, the host server notifies the situation to the registered users who have cellular phone through short message service server of the cellular network. Thus, the proposed architecture can adapt an emergency situation dynamically compared to the conventional architecture using video processing. In the testbed, after generating air pollution and fire data, the terminal receives the message in less than 3 s. In the test results, this system can also be applied to buildings and public areas where many people gather together, to prevent unexpected disasters in urban settings.

Position estimation of transceivers in communication networks

DOEpatents

Kent, Claudia A [Pleasanton, CA; Dowla, Farid [Castro Valley, CA

2008-06-03

This invention provides a system and method using wireless communication interfaces coupled with statistical processing of time-of-flight data to locate by position estimation unknown wireless receivers. Such an invention can be applied in sensor network applications, such as environmental monitoring of water in the soil or chemicals in the air where the position of the network nodes is deemed critical. Moreover, the present invention can be arranged to operate in areas where a Global Positioning System (GPS) is not available, such as inside buildings, caves, and tunnels.

Integration of Model-Based Estimation Theory With an Adaptive Finite Volume Method for the Detection of a Moving Gaseous Source via a Mobile Sensor

DTIC Science & Technology

2012-02-29

couples the estimation scheme with the computational scheme, using one to enhance the other. Numerically, this switching changes several of the matrices...2011. 11. M.A. Demetriou, Enforcing and enhancing consensus of spatially distributed filters utilizing mobile sensor networks, Proceedings of the 49th...expected May, 2012. References [1] J. H. Seinfeld and S. N. Pandis, Atmospheric Chemistry and Physics: From Air Pollution to Climate Change. New York

Quality control and gap-filling of PM10 daily mean concentrations with the best linear unbiased estimator.

PubMed

Sozzi, R; Bolignano, A; Ceradini, S; Morelli, M; Petenko, I; Argentini, S

2017-10-15

According to the European Directive 2008/50/CE, the air quality assessment consists in the measurement of the concentration fields, and the evaluation of the mean, number of exceedances, etc. of some chemical species dangerous to human health. The measurements provided by an air quality ground-based monitoring network are the main information source but the availability of these data is often limited by several technical and operational problems. In this paper, the best linear unbiased estimator (BLUE) is proposed to validate the pollutant concentration values and to fill the gaps in the measurement of time series collected by a monitoring network. The BLUE algorithm is tested using the daily mean concentrations of particulate matter having aerodynamic diameter less than 10 μ (PM 10 concentrations) measured by the air quality monitoring sensors operating in the Lazio Region in Italy. The comparison between the estimated and measured data evidences an error comparable with the measurement uncertainty. Due to its simplicity and reliability, the BLUE will be used in the routine quality test procedures of the Lazio air quality monitoring network measurements.

SSL: Signal Similarity-Based Localization for Ocean Sensor Networks.

PubMed

Chen, Pengpeng; Ma, Honglu; Gao, Shouwan; Huang, Yan

2015-11-24

Nowadays, wireless sensor networks are often deployed on the sea surface for ocean scientific monitoring. One of the important challenges is to localize the nodes' positions. Existing localization schemes can be roughly divided into two types: range-based and range-free. The range-based localization approaches heavily depend on extra hardware capabilities, while range-free ones often suffer from poor accuracy and low scalability, far from the practical ocean monitoring applications. In response to the above limitations, this paper proposes a novel signal similarity-based localization (SSL) technology, which localizes the nodes' positions by fully utilizing the similarity of received signal strength and the open-air characteristics of the sea surface. In the localization process, we first estimate the relative distance between neighboring nodes through comparing the similarity of received signal strength and then calculate the relative distance for non-neighboring nodes with the shortest path algorithm. After that, the nodes' relative relation map of the whole network can be obtained. Given at least three anchors, the physical locations of nodes can be finally determined based on the multi-dimensional scaling (MDS) technology. The design is evaluated by two types of ocean experiments: a zonal network and a non-regular network using 28 nodes. Results show that the proposed design improves the localization accuracy compared to typical connectivity-based approaches and also confirm its effectiveness for large-scale ocean sensor networks.

Airport Remote Tower Sensor Systems

NASA Technical Reports Server (NTRS)

Maluf, David A.; Gawdiak, Yuri; Leidichj, Christopher; Papasin, Richard; Tran, Peter B.; Bass, Kevin

2006-01-01

Networks of video cameras, meteorological sensors, and ancillary electronic equipment are under development in collaboration among NASA Ames Research Center, the Federal Aviation Administration (FAA), and the National Oceanic Atmospheric Administration (NOAA). These networks are to be established at and near airports to provide real-time information on local weather conditions that affect aircraft approaches and landings. The prototype network is an airport-approach-zone camera system (AAZCS), which has been deployed at San Francisco International Airport (SFO) and San Carlos Airport (SQL). The AAZCS includes remotely controlled color video cameras located on top of SFO and SQL air-traffic control towers. The cameras are controlled by the NOAA Center Weather Service Unit located at the Oakland Air Route Traffic Control Center and are accessible via a secure Web site. The AAZCS cameras can be zoomed and can be panned and tilted to cover a field of view 220 wide. The NOAA observer can see the sky condition as it is changing, thereby making possible a real-time evaluation of the conditions along the approach zones of SFO and SQL. The next-generation network, denoted a remote tower sensor system (RTSS), will soon be deployed at the Half Moon Bay Airport and a version of it will eventually be deployed at Los Angeles International Airport. In addition to remote control of video cameras via secure Web links, the RTSS offers realtime weather observations, remote sensing, portability, and a capability for deployment at remote and uninhabited sites. The RTSS can be used at airports that lack control towers, as well as at major airport hubs, to provide synthetic augmentation of vision for both local and remote operations under what would otherwise be conditions of low or even zero visibility.

Urban air quality measurements using a sensor-based system

NASA Astrophysics Data System (ADS)

Ródenas, Mila; Hernández, Daniel; Gómez, Tatiana; López, Ramón; Muñoz, Amalia

2017-04-01

Air pollution levels in urban areas have increased the interest, not only of the scientific community but also of the general public, and both at the regional and at the European level. This interest has run in parallel to the development of miniaturized sensors, which only since very recently are suitable for air quality measurements. Certainly, their small size and price allows them to be used as a network of sensors capable of providing high temporal and spatial frequency measurements to characterize an area or city and with increasing potential, under certain considerations, as a complement of conventional methods. Within the frame of the LIFE PHOTOCITYTEX project (use of photocatalytic textiles to help reducing air pollution), CEAM has developed a system to measure gaseous compounds of importance for urban air quality characterization. This system, which allows an autonomous power supply, uses commercial NO, NO2, O3 and CO2 small sensors and incorporates measurements of temperature and humidity. A first version, using XBee boards (Radiofrequency) for communications has been installed in the urban locations defined by the project (tunnel and school), permitting the long-term air quality characterization of sites in the presence of the textiles. An improved second version of the system which also comprises a sensor for measuring particles and which uses GPRS for communications, has been developed and successfully installed in the city center of Valencia. Data are sent to a central server where they can be accessed by citizens in nearly real time and online and, in general, they can be utilized in the air quality characterization, for decision-making related to decontamination (traffic regulation, photocatalytic materials, etc.), in air quality models or in mobile applications of interest for the citizens. Within this work, temporal trends obtained with this system in different urban locations will be shown, discussing the impact of the characteristics of the selected sites and the seasonal variability on the air quality levels observed. Acknowledgements EUPHORE staff is acknowledged. PHOTOCITYTEX project (LIFE13 ENV/ES/000603) is acknowledged for supporting this work. Fundación CEAM is partly supported by Generalitat Valenciana - Spain.

Atmospheric conditions measured by a wireless sensor network on the local scale

NASA Astrophysics Data System (ADS)

Lengfeld, K.; Ament, F.

2010-09-01

Atmospheric conditions close to the surface, like temperature, wind speed and humidity, vary on small scales because of surface heterogeneities. Therefore, the traditional measuring approach of using a single, highly accurate station is of limited representativeness for a larger domain, because it is not able to determine these small scale variabilities. However, both the variability and the domain averages are important information for the development and validation of atmospheric models and soil-vegetation-atmosphere-transfer (SVAT) schemes. Due to progress in microelectronics it is possible to construct networks of comparably cheap meteorological stations with moderate accuracy. Such a network provides data in high spatial and temporal resolution. The EPFL Lausanne developed such a network called SensorScope, consisting of low cost autonomous stations. Each station observes air and surface temperature, humidity, wind direction and speed, incoming solar radiation, precipitation, soil moisture and soil temperature and sends the data via radio communication to a base station. This base station forwards the collected data via GSM/GPRS to a central server. The first measuring campaign took place within the FLUXPAT project in August 2009. We deployed 15 stations as a twin transect near Jülich, Germany. To test the quality of the low cost sensors we compared two of them to more accurate reference systems. It turned out, that although the network sensors are not highly accurate, the measurements are consistent. Consequently an analysis of the pattern of atmospheric conditions is feasible. The transect is 2.3 km long and covers different types of vegetation and a small river. Therefore, we analyse the influence of different land surfaces and the distance to the river on meteorological conditions. For example, we found a difference in air temperature of 0.8°C between the station closest to and the station farthest from the river. The decreasing relative humidity with increasing distance to the river meets our expectations. But there are also some unexpected anomalies in the air temperature, which will be discussed in detail by selected case studies. By analysing the correlation of the fluctuation of the meteorological conditions, we want to detect clusters depending on different land surfaces and distance to the river. Since April 2010 a second deployment is set up at the Airport Hamburg. It consists of 14 stations placed along the two runways in northward and in eastward direction. The aim of this project is to analyse whether the atmospheric conditions in such an uniform environment are really homogeneous. To do so we will apply the same analyses for these measurements we used for FLUXPAT.

Applications of low-cost sensing technologies for air quality monitoring and exposure assessment: How far have they gone?

PubMed

Morawska, Lidia; Thai, Phong K; Liu, Xiaoting; Asumadu-Sakyi, Akwasi; Ayoko, Godwin; Bartonova, Alena; Bedini, Andrea; Chai, Fahe; Christensen, Bryce; Dunbabin, Matthew; Gao, Jian; Hagler, Gayle S W; Jayaratne, Rohan; Kumar, Prashant; Lau, Alexis K H; Louie, Peter K K; Mazaheri, Mandana; Ning, Zhi; Motta, Nunzio; Mullins, Ben; Rahman, Md Mahmudur; Ristovski, Zoran; Shafiei, Mahnaz; Tjondronegoro, Dian; Westerdahl, Dane; Williams, Ron

2018-07-01

Over the past decade, a range of sensor technologies became available on the market, enabling a revolutionary shift in air pollution monitoring and assessment. With their cost of up to three orders of magnitude lower than standard/reference instruments, many avenues for applications have opened up. In particular, broader participation in air quality discussion and utilisation of information on air pollution by communities has become possible. However, many questions have been also asked about the actual benefits of these technologies. To address this issue, we conducted a comprehensive literature search including both the scientific and grey literature. We focused upon two questions: (1) Are these technologies fit for the various purposes envisaged? and (2) How far have these technologies and their applications progressed to provide answers and solutions? Regarding the former, we concluded that there is no clear answer to the question, due to a lack of: sensor/monitor manufacturers' quantitative specifications of performance, consensus regarding recommended end-use and associated minimal performance targets of these technologies, and the ability of the prospective users to formulate the requirements for their applications, or conditions of the intended use. Numerous studies have assessed and reported sensor/monitor performance under a range of specific conditions, and in many cases the performance was concluded to be satisfactory. The specific use cases for sensors/monitors included outdoor in a stationary mode, outdoor in a mobile mode, indoor environments and personal monitoring. Under certain conditions of application, project goals, and monitoring environments, some sensors/monitors were fit for a specific purpose. Based on analysis of 17 large projects, which reached applied outcome stage, and typically conducted by consortia of organizations, we observed that a sizable fraction of them (~ 30%) were commercial and/or crowd-funded. This fact by itself signals a paradigm change in air quality monitoring, which previously had been primarily implemented by government organizations. An additional paradigm-shift indicator is the growing use of machine learning or other advanced data processing approaches to improve sensor/monitor agreement with reference monitors. There is still some way to go in enhancing application of the technologies for source apportionment, which is of particular necessity and urgency in developing countries. Also, there has been somewhat less progress in wide-scale monitoring of personal exposures. However, it can be argued that with a significant future expansion of monitoring networks, including indoor environments, there may be less need for wearable or portable sensors/monitors to assess personal exposure. Traditional personal monitoring would still be valuable where spatial variability of pollutants of interest is at a finer resolution than the monitoring network can resolve. Copyright © 2018 Elsevier Ltd. All rights reserved.

AIRQino, a low-cost air quality mobile platform

NASA Astrophysics Data System (ADS)

Zaldei, Alessandro; Vagnoli, Carolina; Di Lonardo, Sara; Gioli, Beniamino; Gualtieri, Giovanni; Toscano, Piero; Martelli, Francesca; Matese, Alessandro

2015-04-01

Recent air quality regulations (Directive 2008/50/EC) enforce the transition from point-based monitoring networks to new tools that must be capable of mapping and forecasting air quality on the totality of land area, and therefore the totality of citizens. This implies new technologies such as models and additional indicative measurements, are needed in addition to accurate fixed air quality monitoring stations, that until now have been taken as reference by local administrators for the enforcement of various mitigation strategies. However, due to their sporadic spatial distribution, they cannot describe the highly resolved spatial pollutant variations within cities. Integrating additional indicative measurements may provide adequate information on the spatial distribution of the ambient air quality, also allowing for a reduction of the required minimum number of fixed sampling points, whose high cost and complex maintenance still remain a crucial concern for local administrators. New low-cost and small size sensors are becoming available, that could be employed in air quality monitoring including mobile applications. However, accurate assessment of their accuracy and performance both in controlled and real monitoring conditions is crucially needed. Quantifying sensor response is a significant challenge due to the sensitivity to ambient temperature and humidity and the cross-sensitivity to others pollutant species. This study reports the development of an Arduino compatible electronic board (AIRQino) which integrates a series of low-cost metal oxide and NDIR sensors for air quality monitoring, with sensors to measure air temperature, relative humidity, noise, solar radiation and vertical acceleration. A comparative assessment was made for CO2, CO, NO2, CH4, O3, VOCs concentrations, temperature and relative humidity. A controlled climatic chamber study (-80°C / +80°C) was performed to verify temperature and humidity interference using reference gas cylinders and high quality reference sensors. The AIRQino was installed on mobile vectors such as bikes, buses and trams in the cities of Firenze and Siracusa (Italy), that send data real-time to a Web portal. By integrating a microprocessor unit it is capable of directly updating calibration coefficients to provide corrected sensor output as digital string through RS232 serial port. Results from the lab tests and the 'real world' mobile applications are presented and discussed, to assess to what extent this sensor technology might be useful for the development of portable, compact, wireless and cost-effective system for air quality monitoring in urban areas at high spatio-temporal resolution.

Reliable classification of high explosive and chemical/biological artillery using acoustic sensors

NASA Astrophysics Data System (ADS)

Desai, Sachi V.; Hohil, Myron E.; Bass, Henry E.; Chambers, Jim

2005-05-01

Feature extraction methods based on the discrete wavelet transform and multiresolution analysis are used to develop a robust classification algorithm that reliably discriminates between conventional and simulated chemical/biological artillery rounds via acoustic signals produced during detonation utilizing a generic acoustic sensor. Based on the transient properties of the signature blast distinct characteristics arise within the different acoustic signatures because high explosive warheads emphasize concussive and shrapnel effects, while chemical/biological warheads are designed to disperse their contents over large areas, therefore employing a slower burning, less intense explosive to mix and spread their contents. The ensuing blast waves are readily characterized by variations in the corresponding peak pressure and rise time of the blast, differences in the ratio of positive pressure amplitude to the negative amplitude, and variations in the overall duration of the resulting waveform. Unique attributes can also be identified that depend upon the properties of the gun tube, projectile speed at the muzzle, and the explosive burn rates of the warhead. The algorithm enables robust classification of various airburst signatures using acoustics. It is capable of being integrated within an existing chemical/biological sensor, a stand-alone generic sensor, or a part of a disparate sensor suite. When emplaced in high-threat areas, this added capability would further provide field personal with advanced battlefield knowledge without the aide of so-called "sniffer" sensors that rely upon air particle information based on direct contact with possible contaminated air. In this work, the discrete wavelet transform is used to extract the predominant components of these characteristics from air burst signatures at ranges exceeding 2km while maintaining temporal sequence of the data to keep relevance to the transient differences of the airburst signatures. Highly reliable discrimination is achieved with a feedforward neural network classifier trained on a feature space derived from the distribution of wavelet coefficients and higher frequency details found within different levels of the multiresolution decomposition the neural network then is capable of classifying new airburst signatures as Chemical/Biological or High Explosive.

An Indoor Monitoring System for Ambient Assisted Living Based on Internet of Things Architecture

PubMed Central

Marques, Gonçalo; Pitarma, Rui

2016-01-01

The study of systems and architectures for ambient assisted living (AAL) is undoubtedly a topic of great relevance given the aging of the world population. The AAL technologies are designed to meet the needs of the aging population in order to maintain their independence as long as possible. As people typically spend more than 90% of their time in indoor environments, indoor air quality (iAQ) is perceived as an imperative variable to be controlled for the inhabitants’ wellbeing and comfort. Advances in networking, sensors, and embedded devices have made it possible to monitor and provide assistance to people in their homes. The continuous technological advancements make it possible to build smart objects with great capabilities for sensing and connecting several possible advancements in ambient assisted living systems architectures. Indoor environments are characterized by several pollutant sources. Most of the monitoring frameworks instantly accessible are exceptionally costly and only permit the gathering of arbitrary examples. iAQ is an indoor air quality system based on an Internet of Things paradigm that incorporates in its construction Arduino, ESP8266, and XBee technologies for processing and data transmission and micro sensors for data acquisition. It also allows access to data collected through web access and through a mobile application in real time, and this data can be accessed by doctors in order to support medical diagnostics. Five smaller scale sensors of natural parameters (air temperature, moistness, carbon monoxide, carbon dioxide, and glow) were utilized. Different sensors can be included to check for particular contamination. The results reveal that the system can give a viable indoor air quality appraisal in order to anticipate technical interventions for improving indoor air quality. Indeed indoor air quality might be distinctively contrasted with what is normal for a quality living environment. PMID:27869682

An Indoor Monitoring System for Ambient Assisted Living Based on Internet of Things Architecture.

PubMed

Marques, Gonçalo; Pitarma, Rui

2016-11-17

The study of systems and architectures for ambient assisted living (AAL) is undoubtedly a topic of great relevance given the aging of the world population. The AAL technologies are designed to meet the needs of the aging population in order to maintain their independence as long as possible. As people typically spend more than 90% of their time in indoor environments, indoor air quality (iAQ) is perceived as an imperative variable to be controlled for the inhabitants' wellbeing and comfort. Advances in networking, sensors, and embedded devices have made it possible to monitor and provide assistance to people in their homes. The continuous technological advancements make it possible to build smart objects with great capabilities for sensing and connecting several possible advancements in ambient assisted living systems architectures. Indoor environments are characterized by several pollutant sources. Most of the monitoring frameworks instantly accessible are exceptionally costly and only permit the gathering of arbitrary examples. iAQ is an indoor air quality system based on an Internet of Things paradigm that incorporates in its construction Arduino, ESP8266, and XBee technologies for processing and data transmission and micro sensors for data acquisition. It also allows access to data collected through web access and through a mobile application in real time, and this data can be accessed by doctors in order to support medical diagnostics. Five smaller scale sensors of natural parameters (air temperature, moistness, carbon monoxide, carbon dioxide, and glow) were utilized. Different sensors can be included to check for particular contamination. The results reveal that the system can give a viable indoor air quality appraisal in order to anticipate technical interventions for improving indoor air quality. Indeed indoor air quality might be distinctively contrasted with what is normal for a quality living environment.

Implementing wireless sensor networks for architectural heritage conservation

NASA Astrophysics Data System (ADS)

Martínez-Garrido, M. I.; Aparicio, S.; Fort, R.; Izquierdo, M. A. G.; Anaya, J. J.

2012-04-01

Preventive conservation in architectural heritage is one of the most important aims for the development and implementation of new techniques to assess decay, lending to reduce damage before it has occurred and reducing costs in the long term. For that purpose, it is necessary to know all aspects influencing in decay evolution depending on the material under study and its internal and external conditions. Wireless sensor networks are an emerging technology and a minimally invasive technique. The use of these networks facilitates data acquisition and monitoring of a large number of variables that could provoke material damages, such as presence of harmful compounds like salts, dampness, etc. The current project presents different wireless sensors networks (WSN) and sensors used to fulfill the requirements for a complete analysis of main decay agents in a Renaissance church of the 16th century in Madrid (Spain). Current typologies and wireless technologies are studied establishing the most suitable system and the convenience of each one. Firstly, it is very important to consider that microclimate is in close correlation with material deterioration. Therefore a temperature(T) and relative humidity (RH)/moisture network has been developed, using ZigBee wireless communications protocols, and monitoring different points along the church surface. These points are recording RH/T differences depending on the height and the sensor location (inside the material or on the surface). On the other hand, T/RH button sensors have been used, minimizing aesthetical interferences, and concluding which is the most advisable way for monitoring these specific parameters. Due to the fact that microclimate is a complex phenomenon, it is necessary to examine spatial distribution and time evolution at the same time. This work shows both studies since the development expects a long term monitoring. A different wireless network has been deployed to study the effects of pollution caused by other active systems such as a forced-air heating system, the parishioners presence or feasts and other ventilation conditions. Finally weather conditions are registered through a weather station. Outside and inside conditions are compared to incorporate data to the network for a later decay modeling.

Comparison of Calibration Techniques for Low-Cost Air Quality Monitoring

NASA Astrophysics Data System (ADS)

Malings, C.; Ramachandran, S.; Tanzer, R.; Kumar, S. P. N.; Hauryliuk, A.; Zimmerman, N.; Presto, A. A.

2017-12-01

Assessing the intra-city spatial distribution and temporal variability of air quality can be facilitated by a dense network of monitoring stations. However, the cost of implementing such a network can be prohibitive if high-quality but high-cost monitoring systems are used. To this end, the Real-time Affordable Multi-Pollutant (RAMP) sensor package has been developed at the Center for Atmospheric Particle Studies of Carnegie Mellon University, in collaboration with SenSevere LLC. This self-contained unit can measure up to five gases out of CO, SO2, NO, NO2, O3, VOCs, and CO2, along with temperature and relative humidity. Responses of individual gas sensors can vary greatly even when exposed to the same ambient conditions. Those of VOC sensors in particular were observed to vary by a factor-of-8, which suggests that each sensor requires its own calibration model. To this end, we apply and compare two different calibration methods to data collected by RAMP sensors collocated with a reference monitor station. The first method, random forest (RF) modeling, is a rule-based method which maps sensor responses to pollutant concentrations by implementing a trained sequence of decision rules. RF modeling has previously been used for other RAMP gas sensors by the group, and has produced precise calibrated measurements. However, RF models can only predict pollutant concentrations within the range observed in the training data collected during the collocation period. The second method, Gaussian process (GP) modeling, is a probabilistic Bayesian technique whereby broad prior estimates of pollutant concentrations are updated using sensor responses to generate more refined posterior predictions, as well as allowing predictions beyond the range of the training data. The accuracy and precision of these techniques are assessed and compared on VOC data collected during the summer of 2017 in Pittsburgh, PA. By combining pollutant data gathered by each RAMP sensor and applying appropriate calibration techniques, the potentially noisy or biased responses of individual sensors can be mapped to pollutant concentration values which are comparable to those of reference instruments.

Air Force Roadmap 2006-2025

DTIC Science & Technology

2006-06-01

systems. Cyberspace is the electronic medium of net-centric operations, communications systems, and computers, in which horizontal integration and online...will be interoperable, more robust, responsive, and able to support faster spacecraft initialization times. This Intergrated Satellite Control... horizontally and vertically integrated information through machine-to-machine conversations enabled by a peer-based network of sensors, command

DEVELOPMENT OF QUALITY ASSURANCE AND QUALITY CONTROL GUIDANCE FOR GROUND-BASED REMOTE SENSORS FOR USE IN REGULATORY MONITORING

EPA Science Inventory

The U.S. Environmental Protection Agency's (EPA) authority for enhanced monitoring activities is provided for in Title I, Section 182 of the Clean Air Act Amendment of 1990. or example, the Photochemical Assessment Monitoring Station (PAMS) network is one such program which requi...

Integrated Air Surveillance Concept of Operations

DTIC Science & Technology

2011-11-01

information, intelligence, weather data, and other situational awareness-related information. 4.2.4 Shared Services Automated processing of sensor and...other surveillance information will occur through shared services , accessible through an enterprise network infrastructure, that provide for collecting...also be provided, such as information discovery and translation. The IS architecture effort will identify specific shared services . Shared

Air Temperature Distribution Measurement Using Asynchronous-Type Sound Probe

NASA Astrophysics Data System (ADS)

Katano, Yosuke; Wakatsuki, Naoto; Mizutani, Koichi

2009-07-01

In conventional temperature measurement using a sound probe, the operation beginnings of two acoustic sensors must be completely synchronized to measure time of flight (TOF), tf, because the precision of synchronization determines TOF measurement accuracy. A wireless local area network (LAN) is convenient for constructing a sensing grid; however, it causes a fluctuation in the delay of millisecond order. Therefore, it cannot provide sufficient precision for synchronizing acoustic sensors. In previous studies, synchronization was achieved by a trigger line using a coaxial cable; however, the cable reduces the flexibility of a wireless sensing grid especially in larger-scale measurement. In this study, an asynchronous-type sound probe is devised to compensate for the effect of the delay of millisecond order caused by the network. The validity of the probe was examined, and the air temperature distribution was measured using this means. A matrix method is employed to obtain the distribution. Similar results were observed using both asynchronous-type sound probes and thermocouples. This shows the validity of the use of a sensing grid with an asynchronous-type sound probe for temperature distribution measurement even if the trigger line is omitted.

GuMNet - A high altitude monitoring network in the Sierra de Guadarrama (Madrid, Spain)

NASA Astrophysics Data System (ADS)

Santolaria-Canales, Edmundo

2016-04-01

The Guadarrama Monitoring Network (GuMNet) is an observational infrastructure focused on monitoring the state of the atmosphere and the ground in the Sierra de Guadarrama, 50 km NW of the city of Madrid. The network is composed of10 stations ranging from low altitude (900 m a.s.l.) to high mountain climate (2400 m a.s.l.). The atmospheric instrumentation includes sensors for air temperature, air humidity, 4-component net radiation, precipitation, snow height and wind speed and direction. The surface and subsurface infrastructure includes temperature and humidity sensors distributed in 9 trenches up to a maximum of 1 m depth and additionally temperature sensors in 15 PVC cased boreholes down to 20 m and 2 m with a higher vertical resolution close to the surface. All stations are located in exposed open areas except for one site that is in a forested area for measuring air-ground fluxes under forest conditions. High altitude sites are focused on periglacial areas and lower altitude sites have emphasis on pastures. One of the low altitude sites is equipped with a 10 m high tower with 3D sonic anemometers and a CO2/H2O analyzer that will allow the sampling of wind profiles and H2O and CO2 eddy covariance fluxes, important for estimation of CO2 and energy exchanges over complex vegetated surfaces. The network is connected via general packet radio service to the central lab in the Campus of Excellence of Moncloa and management software has been developed to handle the operation of the infrastructure. The data provided by GuMNet will help to improve the characterization of atmospheric variability from turbulent scales to meteorology and climate at high mountain areas, as well as land-atmosphere interactions. The network information aims at meeting the needs of accuracy to be used for biological, agricultural, hydrological, meteorological and climatic investigations in this area with relevance for ecosystem oriented studies. This setup will complement the broader network of meteorological stations of the Spanish National Meteorological Agency(AEMET), mostly distributed in the lower latitude range. This initiative is supported and developed by research groups integrating the GuMNet Consortium from the Complutense and Polytechnical Universities of Madrid (UCM and UPM), the Energetic Environmental and Technological Research Centre (CIEMAT), AEMET, and the National Park Sierra de Guadarrama (PNSG) which provided the initial foundations of this network. GuMNet will be operational in 2016. Web: http://www.ucm.es/gumnet/ Contact: edmundo.santolaria@ucm.es

Advanced Soil Moisture Network Technologies; Developments in Collecting in situ Measurements for Remote Sensing Missions

NASA Astrophysics Data System (ADS)

Moghaddam, M.; Silva, A. R. D.; Akbar, R.; Clewley, D.

2015-12-01

The Soil moisture Sensing Controller And oPtimal Estimator (SoilSCAPE) wireless sensor network has been developed to support Calibration and Validation activities (Cal/Val) for large scale soil moisture remote sensing missions (SMAP and AirMOSS). The technology developed here also readily supports small scale hydrological studies by providing sub-kilometer widespread soil moisture observations. An extensive collection of semi-sparse sensor clusters deployed throughout north-central California and southern Arizona provide near real time soil moisture measurements. Such a wireless network architecture, compared to conventional single points measurement profiles, allows for significant and expanded soil moisture sampling. The work presented here aims at discussing and highlighting novel and new technology developments which increase in situ soil moisture measurements' accuracy, reliability, and robustness with reduced data delivery latency. High efficiency and low maintenance custom hardware have been developed and in-field performance has been demonstrated for a period of three years. The SoilSCAPE technology incorporates (a) intelligent sensing to prevent erroneous measurement reporting, (b) on-board short term memory for data redundancy, (c) adaptive scheduling and sampling capabilities to enhance energy efficiency. A rapid streamlined data delivery architecture openly provides distribution of in situ measurements to SMAP and AirMOSS cal/val activities and other interested parties.

Remote detection of riverine traffic using an ad hoc wireless sensor network

NASA Astrophysics Data System (ADS)

Athan, Stephan P.

2005-05-01

Trafficking of illegal drugs on riverine and inland waterways continues to proliferate in South America. While there has been a successful joint effort to cut off overland and air trafficking routes, there exists a vast river network and Amazon region consisting of over 13,000 water miles that remains difficult to adequately monitor, increasing the likelihood of narcotics moving along this extensive river system. Hence, an effort is underway to provide remote unattended riverine detection in lieu of manned or attended detection measures.

Intelligent Sensing and Classification in DSR-Based Ad Hoc Networks

NASA Astrophysics Data System (ADS)

Dempsey, Tae; Sahin, Gokhan; Morton, Yu T. (Jade

Wireless ad hoc networks have fundamentally altered today's battlefield, with applications ranging from unmanned air vehicles to randomly deployed sensor networks. Security and vulnerabilities in wireless ad hoc networks have been considered at different layers, and many attack strategies have been proposed, including denial of service (DoS) through the intelligent jamming of the most critical packet types of flows in a network. This paper investigates the effectiveness of intelligent jamming in wireless ad hoc networks using the Dynamic Source Routing (DSR) and TCP protocols and introduces an intelligent classifier to facilitate the jamming of such networks. Assuming encrypted packet headers and contents, our classifier is based solely on the observable characteristics of size, inter-arrival timing, and direction and classifies packets with up to 99.4% accuracy in our experiments.

PM2.5 monitoring system based on ZigBee wireless sensor network

NASA Astrophysics Data System (ADS)

Lin, Lukai; Li, Xiangshun; Gu, Weiying

2017-06-01

In the view of the haze problem, aiming at improving the deficiency of the traditional PM2.5 monitoring methods, such as the insufficient real-time monitoring, limited transmission distance, high cost and the difficulty to maintain, the atmosphere PM2.5 monitoring system based on ZigBee technology is designed. The system combines the advantages of ZigBee’s low cost, low power consumption, high reliability and GPRS/Internet’s capability of remote transmission of data. Furthermore, it adopts TI’s Z-Stack protocol stack, and selects CC2530 chip and TI’s MSP430 microcontroller as the core, which establishes the air pollution monitoring network that is helpful for the early prediction of major air pollution disasters.

CAOS: the nested catchment soil-vegetation-atmosphere observation platform

NASA Astrophysics Data System (ADS)

Weiler, Markus; Blume, Theresa

2016-04-01

Most catchment based observations linking hydrometeorology, ecohydrology, soil hydrology and hydrogeology are typically not integrated with each other and lack a consistent and appropriate spatial-temporal resolution. Within the research network CAOS (Catchments As Organized Systems), we have initiated and developed a novel and integrated observation platform in several catchments in Luxembourg. In 20 nested catchments covering three distinct geologies the subscale processes at the bedrock-soil-vegetation-atmosphere interface are being monitored at 46 sensor cluster locations. Each sensor cluster is designed to observe a variety of different fluxes and state variables above and below ground, in the saturated and unsaturated zone. The numbers of sensors are chosen to capture the spatial variability as well the average dynamics. At each of these sensor clusters three soil moisture profiles with sensors at different depths, four soil temperature profiles as well as matric potential, air temperature, relative humidity, global radiation, rainfall/throughfall, sapflow and shallow groundwater and stream water levels are measured continuously. In addition, most sensors also measure temperature (water, soil, atmosphere) and electrical conductivity. This setup allows us to determine the local water and energy balance at each of these sites. The discharge gauging sites in the nested catchments are also equipped with automatic water samplers to monitor water quality and water stable isotopes continuously. Furthermore, water temperature and electrical conductivity observations are extended to over 120 locations distributed across the entire stream network to capture the energy exchange between the groundwater, stream water and atmosphere. The measurements at the sensor clusters are complemented by hydrometeorological observations (rain radar, network of distrometers and dense network of precipitation gauges) and linked with high resolution meteorological models. In this presentation, we will highlight the potential of this integrated observation platform to estimate energy and water exchange between the terrestrial and aquatic systems and the atmosphere, to trace water flow pathways in the unsaturated and saturated zone, and to understand the organization of processes and fluxes and thus runoff generation at different temporal and spatial scales.

An agronomic field-scale sensor network for monitoring soil water and temperature variation

NASA Astrophysics Data System (ADS)

Brown, D. J.; Gasch, C.; Brooks, E. S.; Huggins, D. R.; Campbell, C. S.; Cobos, D. R.

2014-12-01

Environmental sensor networks have been deployed in a variety of contexts to monitor plant, air, water and soil properties. To date, there have been relatively few such networks deployed to monitor dynamic soil properties in cropped fields. Here we report on experience with a distributed soil sensor network that has been deployed for seven years in a research farm with ongoing agronomic field operations. The Washington State University R. J. Cook Agronomy Farm (CAF), Pullman, WA, USA has recently been designated a United States Department of Agriculture (USDA) Long-Term Agro-Ecosystem Research (LTAR) site. In 2007, 12 geo-referenced locations at CAF were instrumented, then in 2009 this network was expended to 42 locations distributed across the 37-ha farm. At each of this locations, Decagon 5TE probes (Decagon Devices Inc., Pullman, WA, USA) were installed at five depths (30, 60, 90, 120, and 150 cm), with temperature and volumetric soil moisture content recorded hourly. Initially, data loggers were wirelessly connected to a data station that could be accessed through a cell connection, but due to the logistics of agronomic field operations, we later buried the dataloggers at each site and now periodically download data via local radio transmission. In this presentation, we share our experience with the installation, maintenance, calibration and data processing associated with an agronomic soil monitoring network. We also present highlights of data derived from this network, including seasonal fluctuations of soil temperature and volumetric water content at each depth, and how these measurements are influenced by crop type, soil properties, landscape position, and precipitation events.

Real-time method for establishing a detection map for a network of sensors

DOEpatents

Nguyen, Hung D; Koch, Mark W; Giron, Casey; Rondeau, Daniel M; Russell, John L

2012-09-11

A method for establishing a detection map of a dynamically configurable sensor network. This method determines an appropriate set of locations for a plurality of sensor units of a sensor network and establishes a detection map for the network of sensors while the network is being set up; the detection map includes the effects of the local terrain and individual sensor performance. Sensor performance is characterized during the placement of the sensor units, which enables dynamic adjustment or reconfiguration of the placement of individual elements of the sensor network during network set-up to accommodate variations in local terrain and individual sensor performance. The reconfiguration of the network during initial set-up to accommodate deviations from idealized individual sensor detection zones improves the effectiveness of the sensor network in detecting activities at a detection perimeter and can provide the desired sensor coverage of an area while minimizing unintentional gaps in coverage.

Direct Adaptive Aircraft Control Using Dynamic Cell Structure Neural Networks

NASA Technical Reports Server (NTRS)

Jorgensen, Charles C.

1997-01-01

A Dynamic Cell Structure (DCS) Neural Network was developed which learns topology representing networks (TRNS) of F-15 aircraft aerodynamic stability and control derivatives. The network is integrated into a direct adaptive tracking controller. The combination produces a robust adaptive architecture capable of handling multiple accident and off- nominal flight scenarios. This paper describes the DCS network and modifications to the parameter estimation procedure. The work represents one step towards an integrated real-time reconfiguration control architecture for rapid prototyping of new aircraft designs. Performance was evaluated using three off-line benchmarks and on-line nonlinear Virtual Reality simulation. Flight control was evaluated under scenarios including differential stabilator lock, soft sensor failure, control and stability derivative variations, and air turbulence.

Sensor Network Architectures for Monitoring Underwater Pipelines

PubMed Central

Mohamed, Nader; Jawhar, Imad; Al-Jaroodi, Jameela; Zhang, Liren

2011-01-01

This paper develops and compares different sensor network architecture designs that can be used for monitoring underwater pipeline infrastructures. These architectures are underwater wired sensor networks, underwater acoustic wireless sensor networks, RF (Radio Frequency) wireless sensor networks, integrated wired/acoustic wireless sensor networks, and integrated wired/RF wireless sensor networks. The paper also discusses the reliability challenges and enhancement approaches for these network architectures. The reliability evaluation, characteristics, advantages, and disadvantages among these architectures are discussed and compared. Three reliability factors are used for the discussion and comparison: the network connectivity, the continuity of power supply for the network, and the physical network security. In addition, the paper also develops and evaluates a hierarchical sensor network framework for underwater pipeline monitoring. PMID:22346669

Sensor network architectures for monitoring underwater pipelines.

PubMed

Mohamed, Nader; Jawhar, Imad; Al-Jaroodi, Jameela; Zhang, Liren

2011-01-01

This paper develops and compares different sensor network architecture designs that can be used for monitoring underwater pipeline infrastructures. These architectures are underwater wired sensor networks, underwater acoustic wireless sensor networks, RF (radio frequency) wireless sensor networks, integrated wired/acoustic wireless sensor networks, and integrated wired/RF wireless sensor networks. The paper also discusses the reliability challenges and enhancement approaches for these network architectures. The reliability evaluation, characteristics, advantages, and disadvantages among these architectures are discussed and compared. Three reliability factors are used for the discussion and comparison: the network connectivity, the continuity of power supply for the network, and the physical network security. In addition, the paper also develops and evaluates a hierarchical sensor network framework for underwater pipeline monitoring.

Measurements of 4 Atmospheric Trace Gases Outside Homes Adjacent to a Multiwell Pad During Drilling, Hydraulic Fracturing, and Production Phases, Using Low-Cost Sensors and Artificial Neural Network Quantification Techniques

NASA Astrophysics Data System (ADS)

Casey, J. G.; Ilie, A. M. C.; Coffey, E.; Collier-Oxandale, A. M.; Hannigan, M.; Vaccaro, C.

2017-12-01

In Colorado and elsewhere in North America, the oil and gas production industry has been growing alongside and in the midst of increasing urban and rural populations. These coinciding trends have resulted in a growing number of people living in close proximity to petroleum production and processing activities, leading to potential public health impacts. Combustion-related emissions from heavy-duty diesel vehicle traffic, generators, compressors, and production stream flaring can potentially lead to locally enhanced levels of nitrogen oxides (NOx), carbon monoxide (CO), and carbon dioxide (CO2). Venting and fugitive emissions of production stream constituents can potentially lead to locally enhanced levels of methane (CH4) and volatile organic compounds (VOCs), some of which (like benzene) are known carcinogens. NOx and VOC emissions can also potentially increase local ozone (O3) production. After learning of a large new multiwell pad on the outskirts of Greeley, Colorado, we were able to quickly mobilize portable air quality monitors outfitted with low-cost gas sensors that respond to CH4, CO2, CO, and O3. The air quality monitors were installed outside homes adjacent to the new multiwell pad several weeks prior to the first spud date. An anemometer was also installed outside one of the homes in order to monitor wind speed and direction. Measurements continued during drilling, hydraulic fracturing, and production phases. The sensors were periodically collocated with reference instruments at a nearby regulatory air quality monitoring site towards calibration via field normalization and validation. Artificial Neural Networks were employed to map sensor signals to trace gas mole fractions during collocation periods. We present measurements of CH4, CO2, CO, and O3 in context with wellpad activities and local meteorology. CO and O3 observations are presented in context with regional measurements and National Ambient Air Quality Standards for each. Wind speed and direction measurements were used to indicate when air masses originated from the direction of the multiwell pad. CO2 mole fractions were used to estimate planetary boundary layer height and CH4 mole fractions were used to identify periods conducive to the pooling and accumulation of production stream venting and fugitive emissions.

Sensitivity-Enhanced Wearable Active Voiceprint Sensor Based on Cellular Polypropylene Piezoelectret.

PubMed

Li, Wenbo; Zhao, Sheng; Wu, Nan; Zhong, Junwen; Wang, Bo; Lin, Shizhe; Chen, Shuwen; Yuan, Fang; Jiang, Hulin; Xiao, Yongjun; Hu, Bin; Zhou, Jun

2017-07-19

Wearable active sensors have extensive applications in mobile biosensing and human-machine interaction but require good flexibility, high sensitivity, excellent stability, and self-powered feature. In this work, cellular polypropylene (PP) piezoelectret was chosen as the core material of a sensitivity-enhanced wearable active voiceprint sensor (SWAVS) to realize voiceprint recognition. By virtue of the dipole orientation control method, the air layers in the piezoelectret were efficiently utilized, and the current sensitivity was enhanced (from 1.98 pA/Hz to 5.81 pA/Hz at 115 dB). The SWAVS exhibited the superiorities of high sensitivity, accurate frequency response, and excellent stability. The voiceprint recognition system could make correct reactions to human voices by judging both the password and speaker. This study presented a voiceprint sensor with potential applications in noncontact biometric recognition and safety guarantee systems, promoting the progress of wearable sensor networks.

An Internet of Things System for Underground Mine Air Quality Pollutant Prediction Based on Azure Machine Learning

PubMed Central

Jo, ByungWan

2018-01-01

The implementation of wireless sensor networks (WSNs) for monitoring the complex, dynamic, and harsh environment of underground coal mines (UCMs) is sought around the world to enhance safety. However, previously developed smart systems are limited to monitoring or, in a few cases, can report events. Therefore, this study introduces a reliable, efficient, and cost-effective internet of things (IoT) system for air quality monitoring with newly added features of assessment and pollutant prediction. This system is comprised of sensor modules, communication protocols, and a base station, running Azure Machine Learning (AML) Studio over it. Arduino-based sensor modules with eight different parameters were installed at separate locations of an operational UCM. Based on the sensed data, the proposed system assesses mine air quality in terms of the mine environment index (MEI). Principal component analysis (PCA) identified CH4, CO, SO2, and H2S as the most influencing gases significantly affecting mine air quality. The results of PCA were fed into the ANN model in AML studio, which enabled the prediction of MEI. An optimum number of neurons were determined for both actual input and PCA-based input parameters. The results showed a better performance of the PCA-based ANN for MEI prediction, with R2 and RMSE values of 0.6654 and 0.2104, respectively. Therefore, the proposed Arduino and AML-based system enhances mine environmental safety by quickly assessing and predicting mine air quality. PMID:29561777

An Internet of Things System for Underground Mine Air Quality Pollutant Prediction Based on Azure Machine Learning.

PubMed

Jo, ByungWan; Khan, Rana Muhammad Asad

2018-03-21

The implementation of wireless sensor networks (WSNs) for monitoring the complex, dynamic, and harsh environment of underground coal mines (UCMs) is sought around the world to enhance safety. However, previously developed smart systems are limited to monitoring or, in a few cases, can report events. Therefore, this study introduces a reliable, efficient, and cost-effective internet of things (IoT) system for air quality monitoring with newly added features of assessment and pollutant prediction. This system is comprised of sensor modules, communication protocols, and a base station, running Azure Machine Learning (AML) Studio over it. Arduino-based sensor modules with eight different parameters were installed at separate locations of an operational UCM. Based on the sensed data, the proposed system assesses mine air quality in terms of the mine environment index (MEI). Principal component analysis (PCA) identified CH₄, CO, SO₂, and H₂S as the most influencing gases significantly affecting mine air quality. The results of PCA were fed into the ANN model in AML studio, which enabled the prediction of MEI. An optimum number of neurons were determined for both actual input and PCA-based input parameters. The results showed a better performance of the PCA-based ANN for MEI prediction, with R ² and RMSE values of 0.6654 and 0.2104, respectively. Therefore, the proposed Arduino and AML-based system enhances mine environmental safety by quickly assessing and predicting mine air quality.

Ground Optical Signal Processing Architecture for Contributing SSA Space Based Sensor Data

NASA Astrophysics Data System (ADS)

Koblick, D.; Klug, M.; Goldsmith, A.; Flewelling, B.; Jah, M.; Shanks, J.; Piña, R.

2014-09-01

The main objective of the DARPA program Orbit Outlook (O^2) is to improve the metric tracking and detection performance of the Space Situational Network (SSN) by adding a diverse low-cost network of contributing sensors to the Space Situational Awareness (SSA) mission. In order to accomplish this objective, not only must a sensor be in constant communication with a planning and scheduling system to process tasking requests, there must be an underlying framework to provide useful data products, such as angles only measurements. Existing optical signal processing implementations such as the Optical Processing Architecture at Lincoln (OPAL) are capable of converting mission data collections to angles only observations, but may be difficult for many users to obtain, support, and customize for low-cost missions and demonstration programs. The Ground Optical Signal Processing Architecture (GOSPA) will ingest raw imagery and telemetry data from a space based electro optical sensor and perform a background removal process to remove anomalous pixels, interpolate over bad pixels, and dominant temporal noise. After background removal, the streak end points and target centroids are located using a corner detection algorithm developed by Air Force Research Laboratory. These identified streak locations are then fused with the corresponding spacecraft telemetry data to determine the Right Ascension and Declination measurements with respect to time. To demonstrate the performance of GOSPA, non-rate tracking collections against a satellite in Geosynchronous Orbit are simulated from a visible optical imaging sensor in a polar Low Earth Orbit. Stars, noise and bad pixels are added to the simulated images based on look angles and sensor parameters. These collections are run through the GOSPA framework to provide angles- only measurements to the Air Force Research Laboratory Constrained Admissible Region Multiple Hypothesis Filter (CAR-MHF) in which an Initial Orbit Determination is performed and compared to truth data.

An Analysis of Peak Wind Speed Data from Collocated Mechanical and Ultrasonic Anemometers

NASA Technical Reports Server (NTRS)

Short, David A.; Wells, Leonard A.; Merceret, Francis J.; Roeder, William P.

2005-01-01

This study focuses on a comparison of peak wind speeds reported by mechanical and ultrasonic anemometers at Cape Canaveral Air Force Station and Kennedy Space Center (CCAFS/KSC) on the east central coast of Florida and Vandenberg Air Force Base (VAFB) on the central coast of California. The legacy mechanical wind instruments on CCAFS/KSC and VAFB weather towers are being changed from propeller-and-vane (CCAFS/KSC) and cup-and-vane (VAFB) sensors to ultrasonic sensors under the Range Standardization and Automation (RSA) program. The wind tower networks on KSC/CCAFS and VAFB have 41 and 27 towers, respectively. Launch Weather Officers, forecasters, and Range Safety analysts at both locations need to understand the performance of the new wind sensors for a myriad of reasons that include weather warnings, watches, advisories, special ground processing operations, launch pad exposure forecasts, user Launch Commit Criteria (LCC) forecasts and evaluations, and toxic dispersion support. The Legacy sensors measure wind speed and direction mechanically. The ultrasonic RSA sensors have no moving parts. Ultrasonic sensors were originally developed to measure very light winds (Lewis and Dover 2004). The technology has evolved and now ultrasonic sensors provide reliable wind data over a broad range of wind speeds. However, because ultrasonic sensors respond more quickly than mechanical sensors to rapid fluctuations in speed, characteristic of gusty wind conditions, comparisons of data from the two sensor types have shown differences in the statistics of peak wind speeds (Lewis and Dover 2004). The 45th Weather Squadron (45 WS) and the 30 WS requested the Applied Meteorology Unit (AMU) to compare data from RSA and Legacy sensors to determine if there are significant differences in peak wind speed information from the two systems.

High Sensitivity Gas Detection Using a Macroscopic Three-Dimensional Graphene Foam Network

PubMed Central

Yavari, Fazel; Chen, Zongping; Thomas, Abhay V.; Ren, Wencai; Cheng, Hui-Ming; Koratkar, Nikhil

2011-01-01

Nanostructures are known to be exquisitely sensitive to the chemical environment and offer ultra-high sensitivity for gas-sensing. However, the fabrication and operation of devices that use individual nanostructures for sensing is complex, expensive and suffers from poor reliability due to contamination and large variability from sample-to-sample. By contrast, conventional solid-state and conducting-polymer sensors offer excellent reliability but suffer from reduced sensitivity at room-temperature. Here we report a macro graphene foam-like three-dimensional network which combines the best of both worlds. The walls of the foam are comprised of few-layer graphene sheets resulting in high sensitivity; we demonstrate parts-per-million level detection of NH3 and NO2 in air at room-temperature. Further, the foam is a mechanically robust and flexible macro-scale network that is easy to contact (without Lithography) and can rival the durability and affordability of traditional sensors. Moreover, Joule-heating expels chemisorbed molecules from the foam's surface leading to fully-reversible and low-power operation. PMID:22355681

WSN system design by using an innovative neural network model to perform thermals forecasting in a urban canyon scenario

NASA Astrophysics Data System (ADS)

Giuseppina, Nicolosi; Salvatore, Tirrito

2015-12-01

Wireless Sensor Networks (WSNs) were studied by researchers in order to manage Heating, Ventilating and Air-Conditioning (HVAC) indoor systems. WSN can be useful specially to regulate indoor confort in a urban canyon scenario, where the thermal parameters vary rapidly, influenced by outdoor climate changing. This paper shows an innovative neural network approach, by using WSN data collected, in order to forecast the indoor temperature to varying the outdoor conditions based on climate parameters and boundary conditions typically of urban canyon. In this work more attention will be done to influence of traffic jam and number of vehicles in queue.

Quantifying Neighborhood-Scale Spatial Variations of Ozone at Open Space and Urban Sites in Boulder, Colorado Using Low-Cost Sensor Technology.

PubMed

Cheadle, Lucy; Deanes, Lauren; Sadighi, Kira; Gordon Casey, Joanna; Collier-Oxandale, Ashley; Hannigan, Michael

2017-09-10

Recent advances in air pollution sensors have led to a new wave of low-cost measurement systems that can be deployed in dense networks to capture small-scale spatio-temporal variations in ozone, a pollutant known to cause negative human health impacts. This study deployed a network of seven low-cost ozone metal oxide sensor systems (UPods) in both an open space and an urban location in Boulder, Colorado during June and July of 2015, to quantify ozone variations on spatial scales ranging from 12 m between UPods to 6.7 km between open space and urban measurement sites with a measurement uncertainty of ~5 ppb. The results showed spatial variability of ozone at both deployment sites, with the largest differences between UPod measurements occurring during the afternoons. The peak median hourly difference between UPods was 6 ppb at 1:00 p.m. at the open space site, and 11 ppb at 4:00 p.m. at the urban site. Overall, the urban ozone measurements were higher than in the open space measurements. This study evaluates the effectiveness of using low-cost sensors to capture microscale spatial and temporal variation of ozone; additionally, it highlights the importance of field calibrations and measurement uncertainty quantification when deploying low-cost sensors.

Neural-network-based state of health diagnostics for an automated radioxenon sampler/analyzer

NASA Astrophysics Data System (ADS)

Keller, Paul E.; Kangas, Lars J.; Hayes, James C.; Schrom, Brian T.; Suarez, Reynold; Hubbard, Charles W.; Heimbigner, Tom R.; McIntyre, Justin I.

2009-05-01

Artificial neural networks (ANNs) are used to determine the state-of-health (SOH) of the Automated Radioxenon Analyzer/Sampler (ARSA). ARSA is a gas collection and analysis system used for non-proliferation monitoring in detecting radioxenon released during nuclear tests. SOH diagnostics are important for automated, unmanned sensing systems so that remote detection and identification of problems can be made without onsite staff. Both recurrent and feed-forward ANNs are presented. The recurrent ANN is trained to predict sensor values based on current valve states, which control air flow, so that with only valve states the normal SOH sensor values can be predicted. Deviation between modeled value and actual is an indication of a potential problem. The feed-forward ANN acts as a nonlinear version of principal components analysis (PCA) and is trained to replicate the normal SOH sensor values. Because of ARSA's complexity, this nonlinear PCA is better able to capture the relationships among the sensors than standard linear PCA and is applicable to both sensor validation and recognizing off-normal operating conditions. Both models provide valuable information to detect impending malfunctions before they occur to avoid unscheduled shutdown. Finally, the ability of ANN methods to predict the system state is presented.

Performance Evaluation of a Prototyped Wireless Ground Sensor Network

DTIC Science & Technology

2005-03-01

the network was capable of dynamic adaptation to failure and degradation. 14. SUBJECT TERMS: Wireless Sensor Network , Unmanned Sensor, Unattended...2 H. WIRELESS SENSOR NETWORKS .................................................................... 3...zation, and network traffic. The evaluated scenarios included outdoor, urban and indoor environments. The characteristics of wireless sensor networks , types

Sensor Authentication in Collaborating Sensor Networks

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

Bielefeldt, Jake Uriah

2014-11-01

In this thesis, we address a new security problem in the realm of collaborating sensor networks. By collaborating sensor networks, we refer to the networks of sensor networks collaborating on a mission, with each sensor network is independently owned and operated by separate entities. Such networks are practical where a number of independent entities can deploy their own sensor networks in multi-national, commercial, and environmental scenarios, and some of these networks will integrate complementary functionalities for a mission. In the scenario, we address an authentication problem wherein the goal is for the Operator O i of Sensor Network S imore » to correctly determine the number of active sensors in Network Si. Such a problem is challenging in collaborating sensor networks where other sensor networks, despite showing an intent to collaborate, may not be completely trustworthy and could compromise the authentication process. We propose two authentication protocols to address this problem. Our protocols rely on Physically Unclonable Functions, which are a hardware based authentication primitive exploiting inherent randomness in circuit fabrication. Our protocols are light-weight, energy efficient, and highly secure against a number of attacks. To the best of our knowledge, ours is the first to addresses a practical security problem in collaborating sensor networks.« less

Incorpoaration of Geosensor Networks Into Internet of Things for Environmental Monitoring

NASA Astrophysics Data System (ADS)

Habibi, R.; Alesheikh, A. A.

2015-12-01

Thanks to the recent advances of miniaturization and the falling costs for sensors and also communication technologies, Internet specially, the number of internet-connected things growth tremendously. Moreover, geosensors with capability of generating high spatial and temporal resolution data, measuring a vast diversity of environmental data and automated operations provide powerful abilities to environmental monitoring tasks. Geosensor nodes are intuitively heterogeneous in terms of the hardware capabilities and communication protocols to take part in the Internet of Things scenarios. Therefore, ensuring interoperability is an important step. With this respect, the focus of this paper is particularly on incorporation of geosensor networks into Internet of things through an architecture for monitoring real-time environmental data with use of OGC Sensor Web Enablement standards. This approach and its applicability is discussed in the context of an air pollution monitoring scenario.

Recognize PM2.5 sources and emission patterns via high-density sensor network: An application case in Beijing

NASA Astrophysics Data System (ADS)

Ba, Yu tao; xian Liu, Bao; Sun, Feng; Wang, Li hua; Zhang, Da wei; Yin, Wen jun

2017-04-01

Beijing suffered severe air pollution during wintertime, 2016, with the unprecedented high level pollutants monitored. As the most dominant pollutant, fine particulate matter (PM2.5) was measured via high-density sensor network (>1000 fixed monitors across 16000 km2 area). This campaign provided precise observations (spatial resolution ≈ 3 km, temporal resolution = 10 min, error of measure < 5 ug/m3) to track potential emission sources. In addition, these observations coupled with WRF-Chem model (Weather Research and Forecasting model coupled with Chemistry) were analyzed to elucidate the effects of atmospheric transportations across regions, both horizontal and vertical, on emission patterns during this haze period. The results quantified the main cause of regional transport and local emission, and highlighted the importance of cross-region cooperation in anti-pollution campaigns.

An efficient management system for wireless sensor networks.

PubMed

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

2010-01-01

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

Evaluation of low-cost electro-chemical sensors for environmental monitoring of ozone, nitrogen dioxide, and carbon monoxide.

PubMed

Afshar-Mohajer, Nima; Zuidema, Christopher; Sousan, Sinan; Hallett, Laura; Tatum, Marcus; Rule, Ana M; Thomas, Geb; Peters, Thomas M; Koehler, Kirsten

2018-02-01

Development of an air quality monitoring network with high spatio-temporal resolution requires installation of a large number of air pollutant monitors. However, state-of-the-art monitors are costly and may not be compatible with wireless data logging systems. In this study, low-cost electro-chemical sensors manufactured by Alphasense Ltd. for detection of CO and oxidative gases (predominantly O 3 and NO 2 ) were evaluated. The voltages from three oxidative gas sensors and three CO sensors were recorded every 2.5 sec when exposed to controlled gas concentrations in a 0.125-m 3 acrylic glass chamber. Electro-chemical sensors for detection of oxidative gases demonstrated sensitivity to both NO 2 and O 3 with similar voltages recorded when exposed to equivalent environmental concentrations of NO 2 or O 3 gases, when evaluated separately. There was a strong linear relationship between the recorded voltages and target concentrations of oxidative gases (R 2 > 0.98) over a wide range of concentrations. Although a strong linear relationship was also observed for CO concentrations below 12 ppm, a saturation effect was observed wherein the voltage only changes minimally for higher CO concentrations (12-50 ppm). The nonlinear behavior of the CO sensors implied their unsuitability for environments where high CO concentrations are expected. Using a manufacturer-supplied shroud, sensors were tested at 2 different flow rates (0.25 and 0.5 Lpm) to mimic field calibration of the sensors with zero air and a span gas concentration (2 ppm NO2 or 15 ppm CO). As with all electrochemical sensors, the tested devices were subject to drift with a bias up to 20% after 9 months of continuous operation. Alphasense CO sensors were found to be a proper choice for occupational and environmental CO monitoring with maximum concentration of 12 ppm, especially due to the field-ready calibration capability. Alphasense oxidative gas sensors are usable only if it is valuable to know the sum of the NO 2 and O 3 concentrations.

Air pollution monitoring network on Milan district area structure and results

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

Cavallaro, A.; Gualdi, R.; Tebaldi, G.

1977-01-01

A discussion of air pollution surveillance in the Milan area covers the geographic and winter characteristics of the Milan area; the monitoring network established by the Provincial Laboratory of Hygiene and Prophylaxis, including 25 sulfur dioxide monitors, 3 automatic dust monitors, 6 weather stations, 2 nitrogen oxide monitors, 3 airport noise sensors, and a coordination center; the statistical procedures used to analyze sulfur dioxide concentration data for each month during the period Oct.-Mar. of the winters of 1970-71 through 1974-75; and concludes that the reduction in sulfur dioxide levels is caused by either the reduction in fuel sulfur content (frommore » 1.77Vertical Bar3< to 1.27Vertical Bar3< in the interval under study) or to improved management of heating plants.« less

Using smartphone batteries as an urban thermometer

NASA Astrophysics Data System (ADS)

Droste, Arjan; Pape, Jan-Jaap; Overeem, Aart; Leijnse, Hidde; Steeneveld, Gert-Jan; Van Delden, Aarnout; Uijlenhoet, Remko

2017-04-01

Taking meteorological measurements in the urban environment is notoriously difficult due to the complex geometry at street and neighbourhood level. Traditional weather stations are absent in cities because of WMO regulations, so urban data has to come from typically expensive measurement-networks, or short intensive campaigns. While traditional measurements are scarce, there is an abundance of smart devices in cities: the well-known Internet of Things. It is for these reasons that crowdsourcing data has an enormous potential in cities, to deliver vast quantities of data without the maintenance costs of a measurement network. A promising source of potentially valuable data is the smartphone, because of its ubiquity and the many sensors most newer phone models now possess. Since most people nowadays have a smartphone, and carry it around wherever they go, data logged by the phone can be used to estimate the urban air temperature. A persistent log taken by nearly all smartphone models, even those without air temperature sensors, is the smartphone's battery temperature. The free OpenSignal smartphone application logs this battery temperature (among many other variables) and the position of the smartphone, which makes it possible to estimate the urban air temperature through a straightforward heat transfer model relating battery temperature to air and body temperature. The obtained urban temperatures are accurate within 1 to 2 degrees of certified measurement stations, proving the huge potential of this innovative method. This poster focuses on describing how thousands of daily smartphone battery temperature measurements can be translated to a relatively robust estimation of an urban air temperature, using 2 years of data from São Paulo in Brazil. Analysis of the results is presented in a separate session.

A Neural Network Based Intelligent Predictive Sensor for Cloudiness, Solar Radiation and Air Temperature

PubMed Central

Ferreira, Pedro M.; Gomes, João M.; Martins, Igor A. C.; Ruano, António E.

2012-01-01

Accurate measurements of global solar radiation and atmospheric temperature, as well as the availability of the predictions of their evolution over time, are important for different areas of applications, such as agriculture, renewable energy and energy management, or thermal comfort in buildings. For this reason, an intelligent, light-weight and portable sensor was developed, using artificial neural network models as the time-series predictor mechanisms. These have been identified with the aid of a procedure based on the multi-objective genetic algorithm. As cloudiness is the most significant factor affecting the solar radiation reaching a particular location on the Earth surface, it has great impact on the performance of predictive solar radiation models for that location. This work also represents one step towards the improvement of such models by using ground-to-sky hemispherical colour digital images as a means to estimate cloudiness by the fraction of visible sky corresponding to clouds and to clear sky. The implementation of predictive models in the prototype has been validated and the system is able to function reliably, providing measurements and four-hour forecasts of cloudiness, solar radiation and air temperature. PMID:23202230

Gust prediction via artificial hair sensor array and neural network

NASA Astrophysics Data System (ADS)

Pankonien, Alexander M.; Thapa Magar, Kaman S.; Beblo, Richard V.; Reich, Gregory W.

2017-04-01

Gust Load Alleviation (GLA) is an important aspect of flight dynamics and control that reduces structural loadings and enhances ride quality. In conventional GLA systems, the structural response to aerodynamic excitation informs the control scheme. A phase lag, imposed by inertia, between the excitation and the measurement inherently limits the effectiveness of these systems. Hence, direct measurement of the aerodynamic loading can eliminate this lag, providing valuable information for effective GLA system design. Distributed arrays of Artificial Hair Sensors (AHS) are ideal for surface flow measurements that can be used to predict other necessary parameters such as aerodynamic forces, moments, and turbulence. In previous work, the spatially distributed surface flow velocities obtained from an array of artificial hair sensors using a Single-State (or feedforward) Neural Network were found to be effective in estimating the steady aerodynamic parameters such as air speed, angle of attack, lift and moment coefficient. This paper extends the investigation of the same configuration to unsteady force and moment estimation, which is important for active GLA control design. Implementing a Recurrent Neural Network that includes previous-timestep sensor information, the hair sensor array is shown to be capable of capturing gust disturbances with a wide range of periods, reducing predictive error in lift and moment by 68% and 52% respectively. The L2 norms of the first layer of the weight matrices were compared showing a 23% emphasis on prior versus current information. The Recurrent architecture also improves robustness, exhibiting only a 30% increase in predictive error when undertrained as compared to a 170% increase by the Single-State NN. This diverse, localized information can thus be directly implemented into a control scheme that alleviates the gusts without waiting for a structural response or requiring user-intensive sensor calibration.

Hybrid architecture for building secure sensor networks

NASA Astrophysics Data System (ADS)

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

2012-04-01

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

Location identification for indoor instantaneous point contaminant source by probability-based inverse Computational Fluid Dynamics modeling.

PubMed

Liu, X; Zhai, Z

2008-02-01

Indoor pollutions jeopardize human health and welfare and may even cause serious morbidity and mortality under extreme conditions. To effectively control and improve indoor environment quality requires immediate interpretation of pollutant sensor readings and accurate identification of indoor pollution history and source characteristics (e.g. source location and release time). This procedure is complicated by non-uniform and dynamic contaminant indoor dispersion behaviors as well as diverse sensor network distributions. This paper introduces a probability concept based inverse modeling method that is able to identify the source location for an instantaneous point source placed in an enclosed environment with known source release time. The study presents the mathematical models that address three different sensing scenarios: sensors without concentration readings, sensors with spatial concentration readings, and sensors with temporal concentration readings. The paper demonstrates the inverse modeling method and algorithm with two case studies: air pollution in an office space and in an aircraft cabin. The predictions were successfully verified against the forward simulation settings, indicating good capability of the method in finding indoor pollutant sources. The research lays a solid ground for further study of the method for more complicated indoor contamination problems. The method developed can help track indoor contaminant source location with limited sensor outputs. This will ensure an effective and prompt execution of building control strategies and thus achieve a healthy and safe indoor environment. The method can also assist the design of optimal sensor networks.

Global Network Connectivity Assessment via Local Data Exchange for Underwater Acoustic Sensor Networks

DTIC Science & Technology

2014-03-31

Network Connectivity Assessment via Local Data Exchange for Underwater Acoustic Sensor Networks M.M. Asadi H. Mahboubi A...2014 Global Network Connectivity Assessment via Local Data Exchange for Underwater Acoustic Sensor Networks Contract Report # AMBUSH.1.1 Contract...pi j /= 0. The sensor network considered in this work is composed of underwater sensors , which use acoustic waves for

Detection and classification of gaseous sulfur compounds by solid electrolyte cyclic voltammetry of cermet sensor array.

PubMed

Kramer, Kirsten E; Rose-Pehrsson, Susan L; Hammond, Mark H; Tillett, Duane; Streckert, Holger H

2007-02-12

Electrochemical sensors composed of a ceramic-metallic (cermet) solid electrolyte are used for the detection of gaseous sulfur compounds SO(2), H(2)S, and CS(2) in a study involving 11 toxic industrial chemical (TIC) compounds. The study examines a sensor array containing four cermet sensors varying in electrode-electrolyte composition, designed to offer selectivity for multiple compounds. The sensors are driven by cyclic voltammetry to produce a current-voltage profile for each analyte. Raw voltammograms are processed by background subtraction of clean air, and the four sensor signals are concatenated to form one vector of points. The high-resolution signal is compressed by wavelet transformation and a probabilistic neural network is used for classification. In this study, training data from one sensor array was used to formulate models which were validated with data from a second sensor array. Of the 11 gases studied, 3 that contained sulfur produced the strongest responses and were successfully analyzed when the remaining compounds were treated as interferents. Analytes were measured from 10 to 200% of their threshold-limited value (TLV) according to the 8-h time weighted average (TWA) exposure limits defined by the National Institute of Occupational Safety and Health (NIOSH). True positive classification rates of 93.3, 96.7, and 76.7% for SO(2), H(2)S, and CS(2), respectively, were achieved for prediction of one sensor unit when a second sensor was used for modeling. True positive rates of 83.3, 90.0, and 90.0% for SO(2), H(2)S, and CS(2), respectively, were achieved for the second sensor unit when the first sensor unit was used for modeling. Most of the misclassifications were for low concentration levels (such 10-25% TLV) in which case the compound was classified as clean air. Between the two sensors, the false positive rates were 2.2% or lower for the three sulfur compounds, 0.9% or lower for the interferents (eight remaining analytes), and 5.8% or lower for clean air. The cermet sensor arrays used in this analysis are rugged, low cost, reusable, and show promise for multiple compound detection at parts-per-million (ppm) levels.

Design process of a photonics network for military platforms

NASA Astrophysics Data System (ADS)

Nelson, George F.; Rao, Nagarajan M.; Krawczak, John A.; Stevens, Rick C.

1999-02-01

Technology development in photonics is rapidly progressing. The concept of a Unified Network will provide re- configurable network access to platform sensors, Vehicle Management Systems, Stores and avionics. The re-configurable taps into the network will accommodate present interface standards and provide scaleability for the insertion of future interfaces. Significant to this development is the design and test of the Optical Backplane Interconnect System funded by Naval Air Systems Command and developed by Lockheed Martin Tactical Defense Systems - Eagan. OBIS results in the merging of the electrical backplane and the optical backplane, with interconnect fabric and card edge connectors finally providing adequate electrical and optical card access. Presently OBIS will support 1.2 Gb/s per fiber over multiples of 12 fibers per ribbon cable.

Signal processing for distributed sensor concept: DISCO

NASA Astrophysics Data System (ADS)

Rafailov, Michael K.

2007-04-01

Distributed Sensor concept - DISCO proposed for multiplication of individual sensor capabilities through cooperative target engagement. DISCO relies on ability of signal processing software to format, to process and to transmit and receive sensor data and to exploit those data in signal synthesis process. Each sensor data is synchronized formatted, Signal-to-Noise Ration (SNR) enhanced and distributed inside of the sensor network. Signal processing technique for DISCO is Recursive Adaptive Frame Integration of Limited data - RAFIL technique that was initially proposed [1] as a way to improve the SNR, reduce data rate and mitigate FPA correlated noise of an individual sensor digital video-signal processing. In Distributed Sensor Concept RAFIL technique is used in segmented way, when constituencies of the technique are spatially and/or temporally separated between transmitters and receivers. Those constituencies include though not limited to two thresholds - one is tuned for optimum probability of detection, the other - to manage required false alarm rate, and limited frame integration placed somewhere between the thresholds as well as formatters, conventional integrators and more. RAFIL allows a non-linear integration that, along with SNR gain, provides system designers more capability where cost, weight, or power considerations limit system data rate, processing, or memory capability [2]. DISCO architecture allows flexible optimization of SNR gain, data rates and noise suppression on sensor's side and limited integration, re-formatting and final threshold on node's side. DISCO with Recursive Adaptive Frame Integration of Limited data may have flexible architecture that allows segmenting the hardware and software to be best suitable for specific DISCO applications and sensing needs - whatever it is air-or-space platforms, ground terminals or integration of sensors network.

Cognitive radio wireless sensor networks: applications, challenges and research trends.

PubMed

Joshi, Gyanendra Prasad; Nam, Seung Yeob; Kim, Sung Won

2013-08-22

A cognitive radio wireless sensor network is one of the candidate areas where cognitive techniques can be used for opportunistic spectrum access. Research in this area is still in its infancy, but it is progressing rapidly. The aim of this study is to classify the existing literature of this fast emerging application area of cognitive radio wireless sensor networks, highlight the key research that has already been undertaken, and indicate open problems. This paper describes the advantages of cognitive radio wireless sensor networks, the difference between ad hoc cognitive radio networks, wireless sensor networks, and cognitive radio wireless sensor networks, potential application areas of cognitive radio wireless sensor networks, challenges and research trend in cognitive radio wireless sensor networks. The sensing schemes suited for cognitive radio wireless sensor networks scenarios are discussed with an emphasis on cooperation and spectrum access methods that ensure the availability of the required QoS. Finally, this paper lists several open research challenges aimed at drawing the attention of the readers toward the important issues that need to be addressed before the vision of completely autonomous cognitive radio wireless sensor networks can be realized.

Evaluation of the spatial and temporal measurement requirements of remote sensors for monitoring regional air pollution episodes

NASA Technical Reports Server (NTRS)

Burke, H. H. K.; Bowley, C. J.; Barnes, J. C.

1979-01-01

The spatial and temporal measurement requirements of satellite sensors for monitoring regional air pollution episodes were evaluated. Use was made of two sets of data from the Sulfate Regional Experiment (SURE), which provided the first ground-based aerosol measurements from a regional-scale station network. The sulfate data were analyzed for two air pollution episode cases. The results of the analysis indicate that the key considerations required for episode mapping from satellite sensors are the following: (1) detection of sulfate levels exceeding 20 micron-g/cu m; (2) capability to view a broad area (of the order of 1500 km swath) because of regional extent of pollution episodes; (3) spatial resolution sufficient to detect variations in sulfate levels of greater than 10 micron-g/cu m over distances of the order of 50 to 75 km; (4) repeat coverage at least on a daily basis; and (5) satellite observations during the mid to late morning local time, when the sulfate levels have begun to increase after the early morning minimum levels, and convective-type cloud cover has not yet increased to the amount reached later in the afternoon. Analysis of the satellite imagery shows that convective clouds can obscure haze patterns. Additional parameters based on spectral analysis include wavelength and bandwidth requirements.

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.

Deployment Considerations for Low-cost Air Quality Sensor Networks; Examining Spatial Variability of Gas-Phase Pollutants Around a Building in Los Angeles

NASA Astrophysics Data System (ADS)

Collier-Oxandale, A. M.; Hannigan, M.; Casey, J. G.; Johnston, J.; Coffey, E.; Thorson, J.

2017-12-01

The field of low-cost air quality sensing technologies is growing rapidly through the continual development of new sensors, increased research into sensor performance, and more and more community groups utilizing sensors to investigate local issues. However, as this technology is still in an exploratory phase, there are few `best-practices' available to serve as guidelines for these projects and the standardization of some procedures could benefit the research community as a whole. For example, deployment considerations such as where and how to place a monitor at a given location are often determined by accessibility and safety, power-requirements, and what is an ideal for sampling the target pollutant. Using data from multiple gas-phase sensors, we will examine the importance of siting considerations for low-cost monitoring systems. During a sampling campaign in Los Angeles, a subset of monitors was deployed at one field site to explore the variability in air quality sensor data around a single building. The site is a three story, multi-family housing unit in a primarily residential neighborhood that is near two major roadways and other potential sources of pollution. Five low-cost monitors were co-located prior to and following the field deployment. During the approximately 2.5-month deployment, these monitors were placed at various heights above street level, on different sides of the building, and on the roof. In our analysis, we will examine how monitor placement affects a sensor's ability to detect local verses more regional trends and how this building-scale spatial variability changes over time. Additionally, examining data from VOC sensors (quantified for methane and total non-methane hydrocarbon signals) and O3 sensors will allow us to compare the variability of primary and secondary pollutants. An outcome of this analysis may include guidelines or `best practices' for siting sensors that could aid in ensuring the collection of high quality field data. These may be particularly useful in community-based projects where monitor siting is typically a collaborative process.

New-generation security network with synergistic IP sensors

NASA Astrophysics Data System (ADS)

Peshko, Igor

2007-09-01

Global Dynamic Monitoring and Security Network (GDMSN) for real-time monitoring of (1) environmental and atmospheric conditions: chemical, biological, radiological and nuclear hazards, climate/man-induced catastrophe areas and terrorism threats; (2) water, soil, food chain quantifiers, and public health care; (3) large government/public/ industrial/ military areas is proposed. Each GDMSN branch contains stationary or mobile terminals (ground, sea, air, or space manned/unmanned vehicles) equipped with portable sensors. The sensory data are transferred via telephone, Internet, TV, security camera and other wire/wireless or optical communication lines. Each sensor is a self-registering, self-reporting, plug-and-play, portable unit that uses unified electrical and/or optical connectors and operates with IP communication protocol. The variant of the system based just on optical technologies cannot be disabled by artificial high-power radio- or gamma-pulses or sunbursts. Each sensor, being supplied with a battery and monitoring means, can be used as a separate portable unit. Military personnel, police officers, firefighters, miners, rescue teams, and nuclear power plant personnel may individually use these sensors. Terminals may be supplied with sensors essential for that specific location. A miniature "universal" optical gas sensor for specific applications in life support and monitoring systems was designed and tested. The sensor is based on the physics of absorption and/or luminescence spectroscopy. It can operate at high pressures and elevated temperatures, such as in professional and military diving equipment, submarines, underground shelters, mines, command stations, aircraft, space shuttles, etc. To enable this capability, the multiple light emitters, detectors and data processing electronics are located within a specially protected chamber.

Influence of different land surfaces on atmospheric conditions measured by a wireless sensor network

NASA Astrophysics Data System (ADS)

Lengfeld, Katharina; Ament, Felix

2010-05-01

Atmospheric conditions close to the surface, like temperature, wind speed and humidity, vary on small scales because of surface heterogeneities. Therefore, the traditional measuring approach of using a single, highly accurate station is of limited representativeness for a larger domain, because it is not able to determine these small scale variabilities. However, both the variability and the domain averages are important information for the development and validation of atmospheric models and soil-vegetation-atmosphere-transfer (SVAT) schemes. Due to progress in microelectronics it is possible to construct networks of comparably cheap meteorological stations with moderate accuracy. Such a network provides data in high spatial and temporal resolution. The EPFL Lausanne developed such a network called SensorScope, consisting of low cost autonomous stations. Each station observes air and surface temperature, humidity, wind direction and speed, incoming solar radiation, precipitations, soil moisture and soil temperature and sends the data via radio communication to a base station. This base station forwards the collected data via GSM/GPRS to a central server. Within the FLUXPAT project in August 2009 we deployed 15 stations as a twin transect near Jülich, Germany. One aim of this first experiment was to test the quality of the low cost sensors by comparing them to more accurate reference measurements. It turned out, that although the network is not highly accurate, the measurements are consistent. Consequently an analysis of the pattern of atmospheric conditions is feasible. For example, we detect a variability of ± 0.5K in the mean temperature at a distance of only 2.3 km. The transect covers different types of vegetation and a small river. Therefore, we analyzed the influence of different land surfaces and the distance to the river on meteorological conditions. On the one hand, some results meet our expectations, e.g. the relative humidity decreases with increasing distance to the river. But on the other hand we found unexpected anomalies in the air temperature, which will be discussed in detail by selected case studies.

International Critical Zone Science: Opportunities to Build a Global Understanding of Land-Water Linkages

NASA Astrophysics Data System (ADS)

McDowell, W. H.

2015-12-01

Critical Zone science examines the structure and properties of the thin veneer that links surface properties to deep geology, at time scales of seconds to millennia. One of the fundamental premises of the US Critical Zone Observatories program is that CZOs should include some measurements made in common at all sites, as these common measurements will enable us to make stronger inferences about how the structure and function of the critical zone interact to drive key processes such as soil formation, stream flow generation, and nutrient export. Recent advances in real-time sensors provide new opportunities to address some fundamental questions about how hillslope soils and streams are linked. Data from the Luquillo Critical Zone Observatory in Puerto Rico, for example, document a previously undescribed transition, or flipping, of stream and soil biogeochemistry in a tropical rain forest. Under typical conditions, soil moisture is high and soil oxygen content is often low, especially at depth. Streams, in contrast, are typically near oxygen saturation. Under severe drought, however, oxygen increases dramatically in soil air and declines to values that are well below saturation in streams. This flipping in redox conditions suggests that despite the strong hydrologic connection between hillslope and stream, gas dynamics and potentially solute dynamics are decoupled along the flow path. The international CZO community has the opportunity to develop a suite of sensor arrays to document soil air, groundwater chemistry, and stream water chemistry. Progress towards realizing the potential of these international networks to develop coherent sensor programs will be addressed based on the current status of sensor deployments in CZO networks in the US, China, and Europe.

A probabilistic method to diagnose faults of air handling units

NASA Astrophysics Data System (ADS)

Dey, Debashis

Air handling unit (AHU) is one of the most extensively used equipment in large commercial buildings. This device is typically customized and lacks quality system integration which can result in hardwire failures and controller errors. Air handling unit Performance Assessment Rules (APAR) is a fault detection tool that uses a set of expert rules derived from mass and energy balances to detect faults in air handling units. APAR is computationally simple enough that it can be embedded in commercial building automation and control systems and relies only upon sensor data and control signals that are commonly available in these systems. Although APAR has many advantages over other methods, for example no training data required and easy to implement commercially, most of the time it is unable to provide the diagnosis of the faults. For instance, a fault on temperature sensor could be fixed bias, drifting bias, inappropriate location, complete failure. Also a fault in mixing box can be return and outdoor damper leak or stuck. In addition, when multiple rules are satisfied the list of faults increases. There is no proper way to have the correct diagnosis for rule based fault detection system. To overcome this limitation we proposed Bayesian Belief Network (BBN) as a diagnostic tool. BBN can be used to simulate diagnostic thinking of FDD experts through a probabilistic way. In this study we developed a new way to detect and diagnose faults in AHU through combining APAR rules and Bayesian Belief network. Bayesian Belief Network is used as a decision support tool for rule based expert system. BBN is highly capable to prioritize faults when multiple rules are satisfied simultaneously. Also it can get information from previous AHU operating conditions and maintenance records to provide proper diagnosis. The proposed model is validated with real time measured data of a campus building at University of Texas at San Antonio (UTSA).The results show that BBN is correctly able to prioritize faults which can be verified by manual investigation.

Wireless sensor networks to assess the impacts of global change in Sierra Nevada (Spain) mountains

NASA Astrophysics Data System (ADS)

Sánchez-Cano, Francisco M.; Bonet-García, Francisco J.; Pérez-Luque, Antonio J.; Suárez-Muñoz, María

2017-04-01

Sierra Nevada Global Change Observatory (southern Spain) aims to improve the ability of ecosystems to address the impacts of global change. To this end, a monitoring program has been implemented based on the collection of long time series on a multitude of biophysical variables. This initiative is part of the Long Term Ecological Research network and is connected to similar ones at national and international level. One of the specific objectives of this LTER site is to improve understanding of the relationships between abiotic factors and ecosystem functioning / structure. Wireless sensor networks are a key instrument for achieving this aim. This contribution describes the design and management of a sensor network that is intended to monitor several biophysical variables with high temporal and spatial resolution in Quercus pyrenaica forests located in this mountain region. The following solution has been adopted in order to obtain the observational data (physical and biological variables). The biological variables will be monitored by PAR sensors (photosynthetically active radiation), and the physical variables will be acquired by a meteorological station and a sensor network composed of temperature and soil moisture sensors, as well as air temperature and humidity ones. To complete the monitoring of the biological variables, a NDVI (Normalized Difference Vegetation Index) camera will be deployed focusing to a Quercus pyrenaica forest from the opposite slope. It should be noted that all monitoring systems exposed will be powered by solar energy. The management of the sensor network covers the deployment of more than 100 sensors, guaranteeing both remote accessibility and reliability of the data. The chosen solution is provided by the company Adevice whose ONE-GO communication system ensures a consistent and efficient sending of those values read by the different sensors towards a central point, from where the information (RAW data) is accessible through WiFi/3G. RAW data is dumped daily in our data center for further processing with the open source software Get-IT. Get-IT was developed by the CNR (National Research Council of Italy) in the context of the RITMARE Flagship Project and LifeWatch Italy in order to combine geographic information with observational data by coupling GeoNode with SOS implementation by 52° North. This solution conforms to our requirements for two reasons, the first is that it provides data persistence, metadata editing and data visualisation tools. The second is that it is the solution adopted by LTER, platform previously mentioned in which we are integrated. This research has been funded by eLTER (Integrated European Long-Term Ecosystem & Socio-Ecological Research Infrastructure) Horizon 2020 EU project, and Sierra Nevada Global Change Observatory (LTER-site).

Time Synchronization in Wireless Sensor Networks

DTIC Science & Technology

2003-01-01

University of California Los Angeles Time Synchronization in Wireless Sensor Networks A dissertation submitted in partial satisfaction of the...4. TITLE AND SUBTITLE Time Synchronization in Wireless Sensor Networks 5a. CONTRACT NUMBER 5b. GRANT NUMBER 5c. PROGRAM ELEMENT NUMBER 6...1 1.1 Wireless Sensor Networks . . . . . . . . . . . . . . . . . . . . . . 1 1.2 Time Synchronization in Sensor Networks

Air Sensor Toolbox

EPA Pesticide Factsheets

Air Sensor Toolbox provides information to citizen scientists, researchers and developers interested in learning more about new lower-cost compact air sensor technologies and tools for measuring air quality.

An overview of the CalNex 2010 field mission: research to extend the understanding of climate and air quality issues in California (Invited)

NASA Astrophysics Data System (ADS)

Ryerson, T. B.

2009-12-01

CalNex is a major field study planned for May and June of 2010. The study, led by NOAA and the California Air Resources Board, coordinates many interagency partners with independent but complementary capabilities and goals. Observations from surface-, aircraft-, ship-, and space-based sensors, along with Lagrangian and Eulerian modeling studies, will be used to extend previous studies and contribute new data and understanding to issues relevant to climate change and air quality in California. This overview will present the integrated approach that will be taken in CalNex, utilizing long-term surface observations, instrumented tall towers, several major intensive ground sites, a network of daily ozonesonde launches, a radar profiling network, multiple instrumented research aircraft, a research vessel, and retrievals from several satellites. The primary CalNex science questions and experimental strategies to address them will be presented, with illustrations and data examples taken from recent field projects in California to provide context for the upcoming study.

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.

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

High density ozone monitoring using gas sensitive semi-conductor sensors in the Lower Fraser Valley, British Columbia.

PubMed

Bart, Mark; Williams, David E; Ainslie, Bruce; McKendry, Ian; Salmond, Jennifer; Grange, Stuart K; Alavi-Shoshtari, Maryam; Steyn, Douw; Henshaw, Geoff S

2014-04-01

A cost-efficient technology for accurate surface ozone monitoring using gas-sensitive semiconducting oxide (GSS) technology, solar power, and automated cell-phone communications was deployed and validated in a 50 sensor test-bed in the Lower Fraser Valley of British Columbia, over 3 months from May-September 2012. Before field deployment, the entire set of instruments was colocated with reference instruments for at least 48 h, comparing hourly averaged data. The standard error of estimate over a typical range 0-50 ppb for the set was 3 ± 2 ppb. Long-term accuracy was assessed over several months by colocation of a subset of ten instruments each at a different reference site. The differences (GSS-reference) of hourly average ozone concentration were normally distributed with mean -1 ppb and standard deviation 6 ppb (6000 measurement pairs). Instrument failures in the field were detected using network correlations and consistency checks on the raw sensor resistance data. Comparisons with modeled spatial O3 fields demonstrate the enhanced monitoring capability of a network that was a hybrid of low-cost and reference instruments, in which GSS sensors are used both to increase station density within a network as well as to extend monitoring into remote areas. This ambitious deployment exposed a number of challenges and lessons, including the logistical effort required to deploy and maintain sites over a summer period, and deficiencies in cell phone communications and battery life. Instrument failures at remote sites suggested that redundancy should be built into the network (especially at critical sites) as well as the possible addition of a "sleep-mode" for GSS monitors. At the network design phase, a more objective approach to optimize interstation distances, and the "information" content of the network is recommended. This study has demonstrated the utility and affordability of the GSS technology for a variety of applications, and the effectiveness of this technology as a means substantially and economically to extend the coverage of an air quality monitoring network. Low-cost, neighborhood-scale networks that produce reliable data can be envisaged.

Archimedean Spiral Pairs with no Electrical Connections as a Passive Wireless Implantable Sensor

PubMed Central

Drazan, John F; Gunko, Aleksandra; Dion, Matthew; Abdoun, Omar; Cady, Nathaniel C; Connor, Kenneth A; Ledet, Eric H

2015-01-01

We have developed, modeled, fabricated, and tested a passive wireless sensor system that exhibits a linear frequency-displacement relationship. The displacement sensor is comprised of two anti-aligned Archimedean coils separated by an insulating dielectric layer. There are no electrical connections between the two coils and there are no onboard electronics. The two coils are inductively and capacitively coupled due to their close proximity. The sensor system is interrogated wirelessly by monitoring the return loss parameter from a vector network analyzer. The resonant frequency of the sensor is dependent on the displacement between the two coils. Due to changes in the inductive and capacitive coupling between the coils at different distances, the resonant frequency is modulated by coil separation. In a specified range, the frequency shift can be linearized with respect to coil separation. Batch fabrication techniques were used to fabricate copper coils for experimental testing with air as the dielectric. Through testing, we validated the performance of sensors as predicted within acceptable errors. Because of its simplicity, this displacement sensor has potential applications for in vivo sensing. PMID:27430033

Cognitive Radio Wireless Sensor Networks: Applications, Challenges and Research Trends

PubMed Central

Joshi, Gyanendra Prasad; Nam, Seung Yeob; Kim, Sung Won

2013-01-01

A cognitive radio wireless sensor network is one of the candidate areas where cognitive techniques can be used for opportunistic spectrum access. Research in this area is still in its infancy, but it is progressing rapidly. The aim of this study is to classify the existing literature of this fast emerging application area of cognitive radio wireless sensor networks, highlight the key research that has already been undertaken, and indicate open problems. This paper describes the advantages of cognitive radio wireless sensor networks, the difference between ad hoc cognitive radio networks, wireless sensor networks, and cognitive radio wireless sensor networks, potential application areas of cognitive radio wireless sensor networks, challenges and research trend in cognitive radio wireless sensor networks. The sensing schemes suited for cognitive radio wireless sensor networks scenarios are discussed with an emphasis on cooperation and spectrum access methods that ensure the availability of the required QoS. Finally, this paper lists several open research challenges aimed at drawing the attention of the readers toward the important issues that need to be addressed before the vision of completely autonomous cognitive radio wireless sensor networks can be realized. PMID:23974152

A Middleware Solution for Wireless IoT Applications in Sparse Smart Cities

PubMed Central

Lanzone, Stefano; Riberto, Giulio; Stefanelli, Cesare; Tortonesi, Mauro

2017-01-01

The spread of off-the-shelf mobile devices equipped with multiple wireless interfaces together with sophisticated sensors is paving the way to novel wireless Internet of Things (IoT) environments, characterized by multi-hop infrastructure-less wireless networks where devices carried by users act as sensors/actuators as well as network nodes. In particular, the paper presents Real Ad-hoc Multi-hop Peer-to peer-Wireless IoT Application (RAMP-WIA), a novel solution that facilitates the development, deployment, and management of applications in sparse Smart City environments, characterized by users willing to collaborate by allowing new applications to be deployed on their smartphones to remotely monitor and control fixed/mobile devices. RAMP-WIA allows users to dynamically configure single-hop wireless links, to manage opportunistically multi-hop packet dispatching considering that the network topology (together with the availability of sensors and actuators) may abruptly change, to actuate reliably sensor nodes specifically considering that only part of them could be actually reachable in a timely manner, and to upgrade dynamically the nodes through over-the-air distribution of new software components. The paper also reports the performance of RAMP-WIA on simple but realistic cases of small-scale deployment scenarios with off-the-shelf Android smartphones and Raspberry Pi devices; these results show not only the feasibility and soundness of the proposed approach, but also the efficiency of the middleware implemented when deployed on real testbeds. PMID:29099745

A Middleware Solution for Wireless IoT Applications in Sparse Smart Cities.

PubMed

Bellavista, Paolo; Giannelli, Carlo; Lanzone, Stefano; Riberto, Giulio; Stefanelli, Cesare; Tortonesi, Mauro

2017-11-03

The spread of off-the-shelf mobile devices equipped with multiple wireless interfaces together with sophisticated sensors is paving the way to novel wireless Internet of Things (IoT) environments, characterized by multi-hop infrastructure-less wireless networks where devices carried by users act as sensors/actuators as well as network nodes. In particular, the paper presents Real Ad-hoc Multi-hop Peer-to peer-Wireless IoT Application (RAMP-WIA), a novel solution that facilitates the development, deployment, and management of applications in sparse Smart City environments, characterized by users willing to collaborate by allowing new applications to be deployed on their smartphones to remotely monitor and control fixed/mobile devices. RAMP-WIA allows users to dynamically configure single-hop wireless links, to manage opportunistically multi-hop packet dispatching considering that the network topology (together with the availability of sensors and actuators) may abruptly change, to actuate reliably sensor nodes specifically considering that only part of them could be actually reachable in a timely manner, and to upgrade dynamically the nodes through over-the-air distribution of new software components. The paper also reports the performance of RAMP-WIA on simple but realistic cases of small-scale deployment scenarios with off-the-shelf Android smartphones and Raspberry Pi devices; these results show not only the feasibility and soundness of the proposed approach, but also the efficiency of the middleware implemented when deployed on real testbeds.

Diode laser absorption sensors for gas-dynamic and combustion flows

NASA Technical Reports Server (NTRS)

Allen, M. G.

1998-01-01

Recent advances in room-temperature, near-IR and visible diode laser sources for tele-communication, high-speed computer networks, and optical data storage applications are enabling a new generation of gas-dynamic and combustion-flow sensors based on laser absorption spectroscopy. In addition to conventional species concentration and density measurements, spectroscopic techniques for temperature, velocity, pressure and mass flux have been demonstrated in laboratory, industrial and technical flows. Combined with fibreoptic distribution networks and ultrasensitive detection strategies, compact and portable sensors are now appearing for a variety of applications. In many cases, the superior spectroscopic quality of the new laser sources compared with earlier cryogenic, mid-IR devices is allowing increased sensitivity of trace species measurements, high-precision spectroscopy of major gas constituents, and stable, autonomous measurement systems. The purpose of this article is to review recent progress in this field and suggest likely directions for future research and development. The various laser-source technologies are briefly reviewed as they relate to sensor applications. Basic theory for laser absorption measurements of gas-dynamic properties is reviewed and special detection strategies for the weak near-IR and visible absorption spectra are described. Typical sensor configurations are described and compared for various application scenarios, ranging from laboratory research to automated field and airborne packages. Recent applications of gas-dynamic sensors for air flows and fluxes of trace atmospheric species are presented. Applications of gas-dynamic and combustion sensors to research and development of high-speed flows aeropropulsion engines, and combustion emissions monitoring are presented in detail, along with emerging flow control systems based on these new sensors. Finally, technology in nonlinear frequency conversion, UV laser materials, room-temperature mid-IR materials and broadly tunable multisection devices is reviewed to suggest new sensor possibilities.

Recent Improvements in Retrieving Near-Surface Air Temperature and Humidity Using Microwave Remote Sensing

NASA Technical Reports Server (NTRS)

Roberts, J. Brent

2010-01-01

Detailed studies of the energy and water cycles require accurate estimation of the turbulent fluxes of moisture and heat across the atmosphere-ocean interface at regional to basin scale. Providing estimates of these latent and sensible heat fluxes over the global ocean necessitates the use of satellite or reanalysis-based estimates of near surface variables. Recent studies have shown that errors in the surface (10 meter)estimates of humidity and temperature are currently the largest sources of uncertainty in the production of turbulent fluxes from satellite observations. Therefore, emphasis has been placed on reducing the systematic errors in the retrieval of these parameters from microwave radiometers. This study discusses recent improvements in the retrieval of air temperature and humidity through improvements in the choice of algorithms (linear vs. nonlinear) and the choice of microwave sensors. Particular focus is placed on improvements using a neural network approach with a single sensor (Special Sensor Microwave/Imager) and the use of combined sensors from the NASA AQUA satellite platform. The latter algorithm utilizes the unique sampling available on AQUA from the Advanced Microwave Scanning Radiometer (AMSR-E) and the Advanced Microwave Sounding Unit (AMSU-A). Current estimates of uncertainty in the near-surface humidity and temperature from single and multi-sensor approaches are discussed and used to estimate errors in the turbulent fluxes.

Silver nanowire/polymer composite soft conductive film fabricated by large-area compatible coating for flexible pressure sensor array

NASA Astrophysics Data System (ADS)

Chen, Sujie; Li, Siying; Peng, Sai; Huang, Yukun; Zhao, Jiaqing; Tang, Wei; Guo, Xiaojun

2018-01-01

Soft conductive films composed of a silver nanowire (AgNW) network, a neutral-pH PEDOT:PSS over-coating layer and a polydimethylsiloxane (PDMS) elastomer substrate are fabricated by large area compatible coating processes. The neutral-pH PEDOT:PSS layer is shown to be able to significantly improve the conductivity, stretchability and air stability of the conductive films. The soft conductive films are patterned using a simple maskless patterning approach to fabricate an 8 × 8 flexible pressure sensor array. It is shown that such soft conductive films can help to improve the sensitivity and reduce the signal crosstalk over the pressure sensor array. Project supported by the Science and Technology Commission of Shanghai Municipality (No. 16JC1400603).

Wireless remote weather monitoring system based on MEMS technologies.

PubMed

Ma, Rong-Hua; Wang, Yu-Hsiang; Lee, Chia-Yen

2011-01-01

This study proposes a wireless remote weather monitoring system based on Micro-Electro-Mechanical Systems (MEMS) and wireless sensor network (WSN) technologies comprising sensors for the measurement of temperature, humidity, pressure, wind speed and direction, integrated on a single chip. The sensing signals are transmitted between the Octopus II-A sensor nodes using WSN technology, following amplification and analog/digital conversion (ADC). Experimental results show that the resistance of the micro temperature sensor increases linearly with input temperature, with an average TCR (temperature coefficient of resistance) value of 8.2 × 10(-4) (°C(-1)). The resistance of the pressure sensor also increases linearly with air pressure, with an average sensitivity value of 3.5 × 10(-2) (Ω/kPa). The sensitivity to humidity increases with ambient temperature due to the effect of temperature on the dielectric constant, which was determined to be 16.9, 21.4, 27.0, and 38.2 (pF/%RH) at 27 °C, 30 °C, 40 °C, and 50 °C, respectively. The velocity of airflow is obtained by summing the variations in resistor response as airflow passed over the sensors providing sensitivity of 4.2 × 10(-2), 9.2 × 10(-2), 9.7 × 10(-2) (Ω/ms(-1)) with power consumption by the heating resistor of 0.2, 0.3, and 0.5 W, respectively. The passage of air across the surface of the flow sensors prompts variations in temperature among each of the sensing resistors. Evaluating these variations in resistance caused by the temperature change enables the measurement of wind direction.

Understanding social and behavioral drivers and impacts of air quality sensor use.

PubMed

Hubbell, Bryan J; Kaufman, Amanda; Rivers, Louie; Schulte, Kayla; Hagler, Gayle; Clougherty, Jane; Cascio, Wayne; Costa, Dan

2018-04-15

Lower-cost air quality sensors (hundreds to thousands of dollars) are now available to individuals and communities. This technology is undergoing a rapid and fragmented evolution, resulting in sensors that have uncertain data quality, measure different air pollutants and possess a variety of design attributes. Why and how individuals and communities choose to use sensors is arguably influenced by social context. For example, community experiences with environmental exposures and health effects and related interactions with industry and government can affect trust in traditional air quality monitoring. To date, little social science research has been conducted to evaluate why or how sensors, and sensor data, are used by individuals and communities, or how the introduction of sensors changes the relationship between communities and air quality managers. This commentary uses a risk governance/responsible innovation framework to identify opportunities for interdisciplinary research that brings together social scientists with air quality researchers involved in developing, testing, and deploying sensors in communities. Potential areas for social science research include communities of sensor users; drivers for use of sensors and sensor data; behavioral, socio-political, and ethical implications of introducing sensors into communities; assessing methods for communicating sensor data; and harnessing crowdsourcing capabilities to analyze sensor data. Social sciences can enhance understanding of perceptions, attitudes, behaviors, and other human factors that drive levels of engagement with and trust in different types of air quality data. New transdisciplinary research bridging social sciences, natural sciences, engineering, and design fields of study, and involving citizen scientists working with professionals from a variety of backgrounds, can increase our understanding of air sensor technology use and its impacts on air quality and public health. Published by Elsevier B.V.

The design of tea garden environmental monitoring system based on WSN

NASA Astrophysics Data System (ADS)

Chen, Huajun; Yuan, Lina

2018-01-01

Through the application of wireless sensor network (WSN) in tea garden, it can realize the change of traditional tea garden to the modern ones, and effectively improves the comprehensive productive capacity of tea garden. According to the requirement of real-time remote in agricultural information collection and monitoring and the power supply affected by environmental limitations, based on WSN, this paper designs a set of tea garden environmental monitoring system, which achieves the monitoring nodes with ad-hoc network as well as automatic acquisition and transmission to the tea plantations of air temperature, light intensity, soil temperature and humidity.

Dependable Wireless Sensor Networks for Prognostics and Health Management: A Survey

DTIC Science & Technology

2014-10-02

sensor network has many advantages. First of all, the absence of wires gives sensor networks the ability to cover a large scale surveillance area...system/component health state. Usually, this information is gathered through independent sensors or a wired network of sensors. The use of a wireless

Microdot - A Four-Bit Microcontroller Designed for Distributed Low-End Computing in Satellites

NASA Astrophysics Data System (ADS)

2002-03-01

Many satellites are an integrated collection of sensors and actuators that require dedicated real-time control. For single processor systems, additional sensors require an increase in computing power and speed to provide the multi-tasking capability needed to service each sensor. Faster processors cost more and consume more power, which taxes a satellite's power resources and may lead to shorter satellite lifetimes. An alternative design approach is a distributed network of small and low power microcontrollers designed for space that handle the computing requirements of each individual sensor and actuator. The design of microdot, a four-bit microcontroller for distributed low-end computing, is presented. The design is based on previous research completed at the Space Electronics Branch, Air Force Research Laboratory (AFRL/VSSE) at Kirtland AFB, NM, and the Air Force Institute of Technology at Wright-Patterson AFB, OH. The Microdot has 29 instructions and a 1K x 4 instruction memory. The distributed computing architecture is based on the Philips Semiconductor I2C Serial Bus Protocol. A prototype was implemented and tested using an Altera Field Programmable Gate Array (FPGA). The prototype was operable to 9.1 MHz. The design was targeted for fabrication in a radiation-hardened-by-design gate-array cell library for the TSMC 0.35 micrometer CMOS process.

Multipath Routing in Wireless Sensor Networks: Survey and Research Challenges

PubMed Central

Radi, Marjan; Dezfouli, Behnam; Bakar, Kamalrulnizam Abu; Lee, Malrey

2012-01-01

A wireless sensor network is a large collection of sensor nodes with limited power supply and constrained computational capability. Due to the restricted communication range and high density of sensor nodes, packet forwarding in sensor networks is usually performed through multi-hop data transmission. Therefore, routing in wireless sensor networks has been considered an important field of research over the past decade. Nowadays, multipath routing approach is widely used in wireless sensor networks to improve network performance through efficient utilization of available network resources. Accordingly, the main aim of this survey is to present the concept of the multipath routing approach and its fundamental challenges, as well as the basic motivations for utilizing this technique in wireless sensor networks. In addition, we present a comprehensive taxonomy on the existing multipath routing protocols, which are especially designed for wireless sensor networks. We highlight the primary motivation behind the development of each protocol category and explain the operation of different protocols in detail, with emphasis on their advantages and disadvantages. Furthermore, this paper compares and summarizes the state-of-the-art multipath routing techniques from the network application point of view. Finally, we identify open issues for further research in the development of multipath routing protocols for wireless sensor networks. PMID:22368490

Multipath routing in wireless sensor networks: survey and research challenges.

PubMed

Radi, Marjan; Dezfouli, Behnam; Abu Bakar, Kamalrulnizam; Lee, Malrey

2012-01-01

A wireless sensor network is a large collection of sensor nodes with limited power supply and constrained computational capability. Due to the restricted communication range and high density of sensor nodes, packet forwarding in sensor networks is usually performed through multi-hop data transmission. Therefore, routing in wireless sensor networks has been considered an important field of research over the past decade. Nowadays, multipath routing approach is widely used in wireless sensor networks to improve network performance through efficient utilization of available network resources. Accordingly, the main aim of this survey is to present the concept of the multipath routing approach and its fundamental challenges, as well as the basic motivations for utilizing this technique in wireless sensor networks. In addition, we present a comprehensive taxonomy on the existing multipath routing protocols, which are especially designed for wireless sensor networks. We highlight the primary motivation behind the development of each protocol category and explain the operation of different protocols in detail, with emphasis on their advantages and disadvantages. Furthermore, this paper compares and summarizes the state-of-the-art multipath routing techniques from the network application point of view. Finally, we identify open issues for further research in the development of multipath routing protocols for wireless sensor networks.

GENASIS national and international monitoring networks for persistent organic pollutants

NASA Astrophysics Data System (ADS)

Brabec, Karel; Dušek, Ladislav; Holoubek, Ivan; Hřebíček, Jiří; Kubásek, Miroslav; Urbánek, Jaroslav

2010-05-01

Persistent organic pollutants (POPs) remain in the centre of scientific attention due to their slow rates of degradation, their toxicity, and potential for both long-range transport and bioaccumulation in living organisms. This group of compounds covers large number of various chemicals from industrial products, such as polychlorinated biphenyls, etc. The GENASIS (Global Environmental Assessment and Information System) information system utilizes data from national and international monitoring networks to obtain as-complete-as-possible set of information and a representative picture of environmental contamination by persistent organic pollutants (POPs). There are data from two main datasets on POPs monitoring: 1.Integrated monitoring of POPs in Košetice Observatory (Czech Republic) which is a long term background site of the European Monitoring and Evaluation Programme (EMEP) for the Central Europe; the data reveals long term trends of POPs in all environmental matrices. The Observatory is the only one in Europe where POPs have been monitored not only in ambient air, but also in wet atmospheric deposition, surface waters, sediments, soil, mosses and needles (integrated monitoring). Consistent data since the year 1996 are available, earlier data (up to 1998) are burdened by high variability and high detection limits. 2.MONET network is ambient air monitoring activities in the Central and Eastern European region (CEEC), Central Asia, Africa and Pacific Islands driven by RECETOX as the Regional Centre of the Stockholm Convention for the region of Central and Eastern Europe under the common name of the MONET networks (MONitoring NETwork). For many of the participating countries these activities generated first data on the atmospheric levels of POPs. The MONET network uses new technologies of air passive sampling, which was developed, tested, and calibrated by RECETOX in cooperation with Environment Canada and Lancaster University, and was originally launched as a model monitoring network providing public administration, private subject, and general public information about air pollution by POPs that had not been previously regularly monitored and whose measurement is further required by global monitoring plan of the Stockholm Convention. The MONET network is international project with many participants. Monitoring in the MONET-CZ network started in 2004 with the pilot project and continues to the current days, MONET CEEC started in 2006 and continues nowadays, MONET Africa started in 2008. The database of the GENASIS systems currently covers MONET-CZ data until the year 2008. The MONET network currently covers 37 countries in the Europe, Asia and Africa with more than 350 sampling sites. The paper will discuss about following topics * Data Fusion in GENASIS: how can GENASIS maximize the value and accuracy of the information gathered from heterogeneous data sources? * Sensor types in GENASIS: which POPs can be measured; what are the physical limitations to achievable accuracy, reliability, and long-term stability of miniaturized sensors; which applications can (not) be realized within these limitations?

Consensus-Based Cooperative Control Based on Pollution Sensing and Traffic Information for Urban Traffic Networks

PubMed Central

Artuñedo, Antonio; del Toro, Raúl M.; Haber, Rodolfo E.

2017-01-01

Nowadays many studies are being conducted to develop solutions for improving the performance of urban traffic networks. One of the main challenges is the necessary cooperation among different entities such as vehicles or infrastructure systems and how to exploit the information available through networks of sensors deployed as infrastructures for smart cities. In this work an algorithm for cooperative control of urban subsystems is proposed to provide a solution for mobility problems in cities. The interconnected traffic lights controller (TLC) network adapts traffic lights cycles, based on traffic and air pollution sensory information, in order to improve the performance of urban traffic networks. The presence of air pollution in cities is not only caused by road traffic but there are other pollution sources that contribute to increase or decrease the pollution level. Due to the distributed and heterogeneous nature of the different components involved, a system of systems engineering approach is applied to design a consensus-based control algorithm. The designed control strategy contains a consensus-based component that uses the information shared in the network for reaching a consensus in the state of TLC network components. Discrete event systems specification is applied for modelling and simulation. The proposed solution is assessed by simulation studies with very promising results to deal with simultaneous responses to both pollution levels and traffic flows in urban traffic networks. PMID:28445398

Consensus-Based Cooperative Control Based on Pollution Sensing and Traffic Information for Urban Traffic Networks.

PubMed

Artuñedo, Antonio; Del Toro, Raúl M; Haber, Rodolfo E

2017-04-26

Nowadays many studies are being conducted to develop solutions for improving the performance of urban traffic networks. One of the main challenges is the necessary cooperation among different entities such as vehicles or infrastructure systems and how to exploit the information available through networks of sensors deployed as infrastructures for smart cities. In this work an algorithm for cooperative control of urban subsystems is proposed to provide a solution for mobility problems in cities. The interconnected traffic lights controller ( TLC ) network adapts traffic lights cycles, based on traffic and air pollution sensory information, in order to improve the performance of urban traffic networks. The presence of air pollution in cities is not only caused by road traffic but there are other pollution sources that contribute to increase or decrease the pollution level. Due to the distributed and heterogeneous nature of the different components involved, a system of systems engineering approach is applied to design a consensus-based control algorithm. The designed control strategy contains a consensus-based component that uses the information shared in the network for reaching a consensus in the state of TLC network components. Discrete event systems specification is applied for modelling and simulation. The proposed solution is assessed by simulation studies with very promising results to deal with simultaneous responses to both pollution levels and traffic flows in urban traffic networks.

Online learning algorithm for time series forecasting suitable for low cost wireless sensor networks nodes.

PubMed

Pardo, Juan; Zamora-Martínez, Francisco; Botella-Rocamora, Paloma

2015-04-21

Time series forecasting is an important predictive methodology which can be applied to a wide range of problems. Particularly, forecasting the indoor temperature permits an improved utilization of the HVAC (Heating, Ventilating and Air Conditioning) systems in a home and thus a better energy efficiency. With such purpose the paper describes how to implement an Artificial Neural Network (ANN) algorithm in a low cost system-on-chip to develop an autonomous intelligent wireless sensor network. The present paper uses a Wireless Sensor Networks (WSN) to monitor and forecast the indoor temperature in a smart home, based on low resources and cost microcontroller technology as the 8051MCU. An on-line learning approach, based on Back-Propagation (BP) algorithm for ANNs, has been developed for real-time time series learning. It performs the model training with every new data that arrive to the system, without saving enormous quantities of data to create a historical database as usual, i.e., without previous knowledge. Consequently to validate the approach a simulation study through a Bayesian baseline model have been tested in order to compare with a database of a real application aiming to see the performance and accuracy. The core of the paper is a new algorithm, based on the BP one, which has been described in detail, and the challenge was how to implement a computational demanding algorithm in a simple architecture with very few hardware resources.

Online Learning Algorithm for Time Series Forecasting Suitable for Low Cost Wireless Sensor Networks Nodes

PubMed Central

Pardo, Juan; Zamora-Martínez, Francisco; Botella-Rocamora, Paloma

2015-01-01

Time series forecasting is an important predictive methodology which can be applied to a wide range of problems. Particularly, forecasting the indoor temperature permits an improved utilization of the HVAC (Heating, Ventilating and Air Conditioning) systems in a home and thus a better energy efficiency. With such purpose the paper describes how to implement an Artificial Neural Network (ANN) algorithm in a low cost system-on-chip to develop an autonomous intelligent wireless sensor network. The present paper uses a Wireless Sensor Networks (WSN) to monitor and forecast the indoor temperature in a smart home, based on low resources and cost microcontroller technology as the 8051MCU. An on-line learning approach, based on Back-Propagation (BP) algorithm for ANNs, has been developed for real-time time series learning. It performs the model training with every new data that arrive to the system, without saving enormous quantities of data to create a historical database as usual, i.e., without previous knowledge. Consequently to validate the approach a simulation study through a Bayesian baseline model have been tested in order to compare with a database of a real application aiming to see the performance and accuracy. The core of the paper is a new algorithm, based on the BP one, which has been described in detail, and the challenge was how to implement a computational demanding algorithm in a simple architecture with very few hardware resources. PMID:25905698

Non-invasive classification of gas-liquid two-phase horizontal flow regimes using an ultrasonic Doppler sensor and a neural network

NASA Astrophysics Data System (ADS)

Musa Abbagoni, Baba; Yeung, Hoi

2016-08-01

The identification of flow pattern is a key issue in multiphase flow which is encountered in the petrochemical industry. It is difficult to identify the gas-liquid flow regimes objectively with the gas-liquid two-phase flow. This paper presents the feasibility of a clamp-on instrument for an objective flow regime classification of two-phase flow using an ultrasonic Doppler sensor and an artificial neural network, which records and processes the ultrasonic signals reflected from the two-phase flow. Experimental data is obtained on a horizontal test rig with a total pipe length of 21 m and 5.08 cm internal diameter carrying air-water two-phase flow under slug, elongated bubble, stratified-wavy and, stratified flow regimes. Multilayer perceptron neural networks (MLPNNs) are used to develop the classification model. The classifier requires features as an input which is representative of the signals. Ultrasound signal features are extracted by applying both power spectral density (PSD) and discrete wavelet transform (DWT) methods to the flow signals. A classification scheme of ‘1-of-C coding method for classification’ was adopted to classify features extracted into one of four flow regime categories. To improve the performance of the flow regime classifier network, a second level neural network was incorporated by using the output of a first level networks feature as an input feature. The addition of the two network models provided a combined neural network model which has achieved a higher accuracy than single neural network models. Classification accuracies are evaluated in the form of both the PSD and DWT features. The success rates of the two models are: (1) using PSD features, the classifier missed 3 datasets out of 24 test datasets of the classification and scored 87.5% accuracy; (2) with the DWT features, the network misclassified only one data point and it was able to classify the flow patterns up to 95.8% accuracy. This approach has demonstrated the success of a clamp-on ultrasound sensor for flow regime classification that would be possible in industry practice. It is considerably more promising than other techniques as it uses a non-invasive and non-radioactive sensor.

Wireless Sensor Networks for Detection of IED Emplacement

DTIC Science & Technology

2009-06-01

unclassified Standard Form 298 (Rev. 8-98) Prescribed by ANSI Std Z39-18 Abstract We are investigating the use of wireless nonimaging -sensor...networks for the difficult problem of detection of suspicious behavior related to IED emplacement. Hardware for surveillance by nonimaging -sensor networks...with people crossing a live sensor network. We conclude that nonimaging -sensor networks can detect a variety of suspicious behavior, but

Theory of Near-Field Scanning with a Probe Array

DTIC Science & Technology

2014-01-01

AIR FORCE RESEARCH LABORATORY SENSORS DIRECTORATE WRIGHT-PATTERSON AIR FORCE BASE, OH 45433-7320 AIR FORCE MATERIEL COMMAND...AFRL/RYMH) Sensors Directorate, Air Force Research Laboratory Wright-Patterson Air Force Base, OH 45433-7320 Air Force Materiel Command, United...S) AND ADDRESS(ES) 10. SPONSORING/MONITORING AGENCY ACRONYM(S) Air Force Research Laboratory Sensors Directorate Wright-Patterson Air Force Base

A Two-Phase Coverage-Enhancing Algorithm for Hybrid Wireless Sensor Networks.

PubMed

Zhang, Qingguo; Fok, Mable P

2017-01-09

Providing field coverage is a key task in many sensor network applications. In certain scenarios, the sensor field may have coverage holes due to random initial deployment of sensors; thus, the desired level of coverage cannot be achieved. A hybrid wireless sensor network is a cost-effective solution to this problem, which is achieved by repositioning a portion of the mobile sensors in the network to meet the network coverage requirement. This paper investigates how to redeploy mobile sensor nodes to improve network coverage in hybrid wireless sensor networks. We propose a two-phase coverage-enhancing algorithm for hybrid wireless sensor networks. In phase one, we use a differential evolution algorithm to compute the candidate's target positions in the mobile sensor nodes that could potentially improve coverage. In the second phase, we use an optimization scheme on the candidate's target positions calculated from phase one to reduce the accumulated potential moving distance of mobile sensors, such that the exact mobile sensor nodes that need to be moved as well as their final target positions can be determined. Experimental results show that the proposed algorithm provided significant improvement in terms of area coverage rate, average moving distance, area coverage-distance rate and the number of moved mobile sensors, when compare with other approaches.

A Two-Phase Coverage-Enhancing Algorithm for Hybrid Wireless Sensor Networks

PubMed Central

Zhang, Qingguo; Fok, Mable P.

2017-01-01

Providing field coverage is a key task in many sensor network applications. In certain scenarios, the sensor field may have coverage holes due to random initial deployment of sensors; thus, the desired level of coverage cannot be achieved. A hybrid wireless sensor network is a cost-effective solution to this problem, which is achieved by repositioning a portion of the mobile sensors in the network to meet the network coverage requirement. This paper investigates how to redeploy mobile sensor nodes to improve network coverage in hybrid wireless sensor networks. We propose a two-phase coverage-enhancing algorithm for hybrid wireless sensor networks. In phase one, we use a differential evolution algorithm to compute the candidate’s target positions in the mobile sensor nodes that could potentially improve coverage. In the second phase, we use an optimization scheme on the candidate’s target positions calculated from phase one to reduce the accumulated potential moving distance of mobile sensors, such that the exact mobile sensor nodes that need to be moved as well as their final target positions can be determined. Experimental results show that the proposed algorithm provided significant improvement in terms of area coverage rate, average moving distance, area coverage–distance rate and the number of moved mobile sensors, when compare with other approaches. PMID:28075365

Key Exchange Trust Evaluation in Peer-to-Peer Sensor Networks With Unconditionally Secure Key Exchange

NASA Astrophysics Data System (ADS)

Gonzalez, Elias; Kish, Laszlo B.

2016-03-01

As the utilization of sensor networks continue to increase, the importance of security becomes more profound. Many industries depend on sensor networks for critical tasks, and a malicious entity can potentially cause catastrophic damage. We propose a new key exchange trust evaluation for peer-to-peer sensor networks, where part of the network has unconditionally secure key exchange. For a given sensor, the higher the portion of channels with unconditionally secure key exchange the higher the trust value. We give a brief introduction to unconditionally secured key exchange concepts and mention current trust measures in sensor networks. We demonstrate the new key exchange trust measure on a hypothetical sensor network using both wired and wireless communication channels.

Microphotonic devices for compact planar lightwave circuits and sensor systems

NASA Astrophysics Data System (ADS)

Cardenas Gonzalez, Jaime

2005-07-01

Higher levels of integration in planar lightwave circuits and sensor systems can reduce fabrication costs and broaden viable applications for optical network and sensor systems. For example, increased integration and functionality can lead to sensor systems that are compact enough for easy transport, rugged enough for field applications, and sensitive enough even for laboratory applications. On the other hand, more functional and compact planar lightwave circuits can make optical networks components less expensive for the metro and access markets in urban areas and allow penetration of fiber to the home. Thus, there is an important area of opportunity for increased integration to provide low cost, compact solutions in both network components and sensor systems. In this dissertation, a novel splitting structure for microcantilever deflection detection is introduced. The splitting structure is designed so that its splitting ratio is dependent on the vertical position of the microcantilever. With this structure, microcantilevers sensitized to detect different analytes or biological agents can be integrated into an array on a single chip. Additionally, the integration of a depolarizer into the optoelectronic integrated circuit in an interferometric fiber optic gyroscope is presented as a means for cost reduction. The savings come in avoiding labor intensive fiber pigtailing steps by permitting batch fabrication of these components. In particular, this dissertation focuses on the design of the waveguides and polarization rotator, and the impact of imperfect components on the performance of the depolarizer. In the area of planar lightwave circuits, this dissertation presents the development of a fabrication process for single air interface bends (SAIBs). SAIBs can increase integration by reducing the area necessary to make a waveguide bend. Fabrication and measurement of a 45° SAIB with a bend efficiency of 93.4% for TM polarization and 92.7% for TE polarization are presented.

Monitoring Mountain Meteorology without Much Money (Invited)

NASA Astrophysics Data System (ADS)

Lundquist, J. D.

2009-12-01

Mountains are the water towers of the world, storing winter precipitation in the form of snow until summer, when it can be used for agriculture and cities. However, mountain weather is highly variable, and measurements are sparsely distributed. In order adequately sample snow and climate variables in complex terrain, we need as many measurements as possible. This means that instruments must be inexpensive and relatively simple to deploy. Here, we demonstrate how dime-sized temperature sensors developed for the refrigeration industry can be used to monitor air temperature (using evergreen trees as radiation shields) and snow cover duration (using the diurnal cycle in near-surface soil temperature). Together, these measurements can be used to recreate accumulated snow water equivalent over the prior year. We also demonstrate how buckets of water may be placed under networked acoustic snow depth sensors to provide an index of daily evaporation rates at SNOTEL stations. (a) Temperature sensor sealed for deployment in the soil. (b) Launching a temperature sensor into a tree. (c) Pulley system to keep sensor above the snow. (a) Photo of bucket underneath acoustic snow depth sensor. (b) Water depth in the bucket as calculated by the snow depth sensor and by a pressure sensor inside the bucket.

Three-dimensional ocean sensor networks: A survey

NASA Astrophysics Data System (ADS)

Wang, Yu; Liu, Yingjian; Guo, Zhongwen

2012-12-01

The past decade has seen a growing interest in ocean sensor networks because of their wide applications in marine research, oceanography, ocean monitoring, offshore exploration, and defense or homeland security. Ocean sensor networks are generally formed with various ocean sensors, autonomous underwater vehicles, surface stations, and research vessels. To make ocean sensor network applications viable, efficient communication among all devices and components is crucial. Due to the unique characteristics of underwater acoustic channels and the complex deployment environment in three dimensional (3D) ocean spaces, new efficient and reliable communication and networking protocols are needed in design of ocean sensor networks. In this paper, we aim to provide an overview of the most recent advances in network design principles for 3D ocean sensor networks, with focuses on deployment, localization, topology design, and position-based routing in 3D ocean spaces.

Availability Issues in Wireless Visual Sensor Networks

PubMed Central

Costa, Daniel G.; Silva, Ivanovitch; Guedes, Luiz Affonso; Vasques, Francisco; Portugal, Paulo

2014-01-01

Wireless visual sensor networks have been considered for a large set of monitoring applications related with surveillance, tracking and multipurpose visual monitoring. When sensors are deployed over a monitored field, permanent faults may happen during the network lifetime, reducing the monitoring quality or rendering parts or the entire network unavailable. In a different way from scalar sensor networks, camera-enabled sensors collect information following a directional sensing model, which changes the notions of vicinity and redundancy. Moreover, visual source nodes may have different relevancies for the applications, according to the monitoring requirements and cameras' poses. In this paper we discuss the most relevant availability issues related to wireless visual sensor networks, addressing availability evaluation and enhancement. Such discussions are valuable when designing, deploying and managing wireless visual sensor networks, bringing significant contributions to these networks. PMID:24526301

The Air Force Interactive Meteorological System: A Research Tool for Satellite Meteorology

DTIC Science & Technology

1992-12-02

NFARnet itself is a subnet to the global computer network INTERNET that links nearly all U.S. government research facilities and universi- ties along...required input to a generalized mathematical solution to the satellite/earth coordinate transform used for earth location of GOES sensor data. A direct...capability also exists to convert absolute coordinates to relative coordinates for transformations associated with gridded fields. 3. Spatial objective

A comparative study of wireless sensor networks and their routing protocols.

PubMed

Bhattacharyya, Debnath; Kim, Tai-hoon; Pal, Subhajit

2010-01-01

Recent developments in the area of micro-sensor devices have accelerated advances in the sensor networks field leading to many new protocols specifically designed for wireless sensor networks (WSNs). Wireless sensor networks with hundreds to thousands of sensor nodes can gather information from an unattended location and transmit the gathered data to a particular user, depending on the application. These sensor nodes have some constraints due to their limited energy, storage capacity and computing power. Data are routed from one node to other using different routing protocols. There are a number of routing protocols for wireless sensor networks. In this review article, we discuss the architecture of wireless sensor networks. Further, we categorize the routing protocols according to some key factors and summarize their mode of operation. Finally, we provide a comparative study on these various protocols.

Underwater Sensor Nodes and Networks

PubMed Central

Lloret, Jaime

2013-01-01

Sensor technology has matured enough to be used in any type of environment. The appearance of new physical sensors has increased the range of environmental parameters for gathering data. Because of the huge amount of unexploited resources in the ocean environment, there is a need of new research in the field of sensors and sensor networks. This special issue is focused on collecting recent advances on underwater sensors and underwater sensor networks in order to measure, monitor, surveillance of and control of underwater environments. On the one hand, from the sensor node perspective, we will see works related with the deployment of physical sensors, development of sensor nodes and transceivers for sensor nodes, sensor measurement analysis and several issues such as layer 1 and 2 protocols for underwater communication and sensor localization and positioning systems. On the other hand, from the sensor network perspective, we will see several architectures and protocols for underwater environments and analysis concerning sensor network measurements. Both sides will provide us a complete view of last scientific advances in this research field. PMID:24013489

Development and Implementation of Low-Cost Mobile Sensor Platforms Within a Wireless Sensor Network

DTIC Science & Technology

2010-09-01

WIRELESS SENSOR NETWORK by Michael Jay Tozzi September 2010 Thesis Advisor: Rachel Goshorn Second Reader: Duane Davis Approved for...Platforms Within a Wireless Sensor Network 6. AUTHOR(S) Tozzi, Michael Jay 5. FUNDING NUMBERS 7. PERFORMING ORGANIZATION NAME(S) AND ADDRESS(ES) Naval...IMPLEMENTATION OF LOW-COST MOBILE SENSOR PLATFORMS WITHIN A WIRELESS SENSOR NETWORK Michael Jay Tozzi Lieutenant, United States Navy B.S., United

Engineering of Sensor Network Structure for Dependable Fusion

DTIC Science & Technology

2014-08-15

Lossy Wireless Sensor Networks , IEEE/ACM Transactions on Networking , (04 2013): 0. doi: 10.1109/TNET.2013.2256795 Soumik Sarkar, Kushal Mukherjee...Phoha, Bharat B. Madan, Asok Ray. Distributed Network Control for Mobile Multi-Modal Wireless Sensor Networks , Journal of Parallel and Distributed...Deadline Constraints, IEEE Transactions on Automatic Control special issue on Wireless Sensor and Actuator Networks , (01 2011): 1. doi: Eric Keller

Distributed sensor coordination for advanced energy systems

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

Tumer, Kagan

Motivation: The ability to collect key system level information is critical to the safe, efficient and reliable operation of advanced power systems. Recent advances in sensor technology have enabled some level of decision making directly at the sensor level. However, coordinating large numbers of sensors, particularly heterogeneous sensors, to achieve system level objectives such as predicting plant efficiency, reducing downtime or predicting outages requires sophisticated coordination algorithms. Indeed, a critical issue in such systems is how to ensure the interaction of a large number of heterogenous system components do not interfere with one another and lead to undesirable behavior. Objectivesmore » and Contributions: The long-term objective of this work is to provide sensor deployment, coordination and networking algorithms for large numbers of sensors to ensure the safe, reliable, and robust operation of advanced energy systems. Our two specific objectives are to: 1. Derive sensor performance metrics for heterogeneous sensor networks. 2. Demonstrate effectiveness, scalability and reconfigurability of heterogeneous sensor network in advanced power systems. The key technical contribution of this work is to push the coordination step to the design of the objective functions of the sensors, allowing networks of heterogeneous sensors to be controlled. By ensuring that the control and coordination is not specific to particular sensor hardware, this approach enables the design and operation of large heterogeneous sensor networks. In addition to the coordination coordination mechanism, this approach allows the system to be reconfigured in response to changing needs (e.g., sudden external events requiring new responses) or changing sensor network characteristics (e.g., sudden changes to plant condition). Impact: The impact of this work extends to a large class of problems relevant to the National Energy Technology Laboratory including sensor placement, heterogeneous sensor coordination, and sensor network control in advanced power systems. Each application has specific needs, but they all share the one crucial underlying problem: how to ensure that the interactions of a large number of heterogenous agents lead to coordinated system behavior. This proposal describes a new paradigm that addresses that very issue in a systematic way. Key Results and Findings: All milestones have been completed. Our results demonstrate that by properly shaping agent objective functions, we can develop large (up to 10,000 devices) heterogeneous sensor networks with key desirable properties. The first milestone shows that properly choosing agent-specific objective functions increases system performance by up to 99.9% compared to global evaluations. The second milestone shows evolutionary algorithms learn excellent sensor network coordination policies prior to network deployment, and these policies can be refined online once the network is deployed. The third milestone shows the resulting sensor networks networks are extremely robust to sensor noise, where networks with up to 25% sensor noise are capable of providing measurements with errors on the order of 10⁻³. The fourth milestone shows the resulting sensor networks are extremely robust to sensor failure, with 25% of the sensors in the system failing resulting in no significant performance losses after system reconfiguration.« less

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

PubMed

Mao, Yuxin; Wei, Guiyi

2010-01-01

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

Coupled sensor/platform control design for low-level chemical detection with position-adaptive micro-UAVs

NASA Astrophysics Data System (ADS)

Goodwin, Thomas; Carr, Ryan; Mitra, Atindra K.; Selmic, Rastko R.

2009-05-01

We discuss the development of Position-Adaptive Sensors [1] for purposes for detecting embedded chemical substances in challenging environments. This concept is a generalization of patented Position-Adaptive Radar Concepts developed at AFRL for challenging conditions such as urban environments. For purposes of investigating the detection of chemical substances using multiple MAV (Micro-UAV) platforms, we have designed and implemented an experimental testbed with sample structures such as wooden carts that contain controlled leakage points. Under this general concept, some of the members of a MAV swarm can serve as external position-adaptive "transmitters" by blowing air over the cart and some of the members of a MAV swarm can serve as external position-adaptive "receivers" that are equipped with chemical or biological (chem/bio) sensors that function as "electronic noses". The objective can be defined as improving the particle count of chem/bio concentrations that impinge on a MAV-based position-adaptive sensor that surrounds a chemical repository, such as a cart, via the development of intelligent position-adaptive control algorithms. The overall effect is to improve the detection and false-alarm statistics of the overall system. Within the major sections of this paper, we discuss a number of different aspects of developing our initial MAV-Based Sensor Testbed. This testbed includes blowers to simulate position-adaptive excitations and a MAV from Draganfly Innovations Inc. with stable design modifications to accommodate our chem/bio sensor boom design. We include details with respect to several critical phases of the development effort including development of the wireless sensor network and experimental apparatus, development of the stable sensor boom for the MAV, integration of chem/bio sensors and sensor node onto the MAV and boom, development of position-adaptive control algorithms and initial tests at IDCAST (Institute for the Development and Commercialization of Advanced Sensor Technologies), and autonomous positionadaptive chem/bio tests and demos in the MAV Lab at AFRL Air Vehicles Directorate. For this particular MAV implementation of chem/bio sensors, we selected miniature Methane, Nitrogen Dioxide, and Carbon Monoxide sensors. To safely simulate the behavior of chem/bio substances in our laboratory environment, we used either cigarette smoke or incense. We present a set of concise parametric results along with visual demonstration of our new position-adaptive sensor capability. Two types of experiments were conducted: with sensor nodes screening the chemical contaminant (cigarette smoke or incense) without MAVs, and with a sensor node integrated with the MAV. It was shown that the MOS-based chemical sensors could be used for chemical leakage detection, as well as for position-adaptive sensors on air/ground vehicles as sniffers for chemical contaminants.

Linking Simulation with Formal Verification and Modeling of Wireless Sensor Network in TLA+

NASA Astrophysics Data System (ADS)

Martyna, Jerzy

In this paper, we present the results of the simulation of a wireless sensor network based on the flooding technique and SPIN protocols. The wireless sensor network was specified and verified by means of the TLA+ specification language [1]. For a model of wireless sensor network built this way simulation was carried with the help of specially constructed software tools. The obtained results allow us to predict the behaviour of the wireless sensor network in various topologies and spatial densities. Visualization of the output data enable precise examination of some phenomenas in wireless sensor networks, such as a hidden terminal, etc.

Review of Portable and Low-Cost Sensors for the Ambient Air Monitoring of Benzene and Other Volatile Organic Compounds

PubMed Central

Kok, Gertjan; Persijn, Stefan; Sauerwald, Tilman

2017-01-01

This article presents a literature review of sensors for the monitoring of benzene in ambient air and other volatile organic compounds. Combined with information provided by stakeholders, manufacturers and literature, the review considers commercially available sensors, including PID-based sensors, semiconductor (resistive gas sensors) and portable on-line measuring devices as for example sensor arrays. The bibliographic collection includes the following topics: sensor description, field of application at fixed sites, indoor and ambient air monitoring, range of concentration levels and limit of detection in air, model descriptions of the phenomena involved in the sensor detection process, gaseous interference selectivity of sensors in complex VOC matrix, validation data in lab experiments and under field conditions. PMID:28657595

Review of Portable and Low-Cost Sensors for the Ambient Air Monitoring of Benzene and Other Volatile Organic Compounds.

PubMed

Spinelle, Laurent; Gerboles, Michel; Kok, Gertjan; Persijn, Stefan; Sauerwald, Tilman

2017-06-28

This article presents a literature review of sensors for the monitoring of benzene in ambient air and other volatile organic compounds. Combined with information provided by stakeholders, manufacturers and literature, the review considers commercially available sensors, including PID-based sensors, semiconductor (resistive gas sensors) and portable on-line measuring devices as for example sensor arrays. The bibliographic collection includes the following topics: sensor description, field of application at fixed sites, indoor and ambient air monitoring, range of concentration levels and limit of detection in air, model descriptions of the phenomena involved in the sensor detection process, gaseous interference selectivity of sensors in complex VOC matrix, validation data in lab experiments and under field conditions.

Air Sensor Guidebook

EPA Science Inventory

This Air Sensor Guidebook has been developed by the U.S. EPA to assist those interested in potentially using lower cost air quality sensor technologies for air quality measurements. Its development was in direct response to a request for such a document following a recent scienti...

Energy optimization in mobile sensor networks

NASA Astrophysics Data System (ADS)

Yu, Shengwei

Mobile sensor networks are considered to consist of a network of mobile robots, each of which has computation, communication and sensing capabilities. Energy efficiency is a critical issue in mobile sensor networks, especially when mobility (i.e., locomotion control), routing (i.e., communications) and sensing are unique characteristics of mobile robots for energy optimization. This thesis focuses on the problem of energy optimization of mobile robotic sensor networks, and the research results can be extended to energy optimization of a network of mobile robots that monitors the environment, or a team of mobile robots that transports materials from stations to stations in a manufacturing environment. On the energy optimization of mobile robotic sensor networks, our research focuses on the investigation and development of distributed optimization algorithms to exploit the mobility of robotic sensor nodes for network lifetime maximization. In particular, the thesis studies these five problems: 1. Network-lifetime maximization by controlling positions of networked mobile sensor robots based on local information with distributed optimization algorithms; 2. Lifetime maximization of mobile sensor networks with energy harvesting modules; 3. Lifetime maximization using joint design of mobility and routing; 4. Optimal control for network energy minimization; 5. Network lifetime maximization in mobile visual sensor networks. In addressing the first problem, we consider only the mobility strategies of the robotic relay nodes in a mobile sensor network in order to maximize its network lifetime. By using variable substitutions, the original problem is converted into a convex problem, and a variant of the sub-gradient method for saddle-point computation is developed for solving this problem. An optimal solution is obtained by the method. Computer simulations show that mobility of robotic sensors can significantly prolong the lifetime of the whole robotic sensor network while consuming negligible amount of energy for mobility cost. For the second problem, the problem is extended to accommodate mobile robotic nodes with energy harvesting capability, which makes it a non-convex optimization problem. The non-convexity issue is tackled by using the existing sequential convex approximation method, based on which we propose a novel procedure of modified sequential convex approximation that has fast convergence speed. For the third problem, the proposed procedure is used to solve another challenging non-convex problem, which results in utilizing mobility and routing simultaneously in mobile robotic sensor networks to prolong the network lifetime. The results indicate that joint design of mobility and routing has an edge over other methods in prolonging network lifetime, which is also the justification for the use of mobility in mobile sensor networks for energy efficiency purpose. For the fourth problem, we include the dynamics of the robotic nodes in the problem by modeling the networked robotic system using hybrid systems theory. A novel distributed method for the networked hybrid system is used to solve the optimal moving trajectories for robotic nodes and optimal network links, which are not answered by previous approaches. Finally, the fact that mobility is more effective in prolonging network lifetime for a data-intensive network leads us to apply our methods to study mobile visual sensor networks, which are useful in many applications. We investigate the joint design of mobility, data routing, and encoding power to help improving the video quality while maximizing the network lifetime. This study leads to a better understanding of the role mobility can play in data-intensive surveillance sensor networks.

Assessment of planetary boundary layer and residual layer heights in the Northeastern U.S. using Lidar, a network of surface observations, and the WRF-STILT model

NASA Astrophysics Data System (ADS)

Barrera, Y.; Nehrkorn, T.; Hegarty, J. D.; Wofsy, S. C.; Gottlieb, E.; Sargent, M. R.; Decola, P.; Jones, T.

2015-12-01

Simulation of the planetary boundary layer (PBL) and residual layer (RL) are key requirements for forecasting air quality in cities and detecting transboundary air pollution events. This study combines information from a network of Mini Micropulse Lidar (MPL) instruments, the CALIOP satellite, meteorological and air pollution measuring sensors, and a particle-transport model to critically test mesoscale transport models at the regional level. Aerosol backscattering measurements were continuously taken with MPL units in various locations within the Northeastern U.S., between September 2012 to August 2015. Data is analyzed using wavelet covariance transforms and image processing techniques. Initial results for the city of Boston show a PBL growth rate between approx. 150 and 300 meters per hour, in the morning to early afternoon (~12-19 UTC). The RL was present throughout the night and day at approx. 1.3 to 2.0 km. Transboundary air pollution events were detected and quantified, and variations in concentrations of greenhouse gases and aerosols were also evaluated. Results were compared to information retrieved from Weather and Research Forecasting (WRF) model and the Stochastic Time-Inverted Lagrangian Transport (STILT) model.

Corrosion detector apparatus for universal assessment of pollution in data centers

DOEpatents

Hamann, Hendrik F.; Klein, Levente I.

2015-08-18

A compact corrosion measurement apparatus and system includes an air fan, a corrosion sensor, a temperature sensor, a humidity sensor, a heater element, and an air flow sensor all under control to monitor and maintain constant air parameters in an environment and minimize environmental fluctuations around the corrosion sensor to overcome the variation commonly encountered in corrosion rate measurement. The corrosion measurement apparatus includes a structure providing an enclosure within which are located the sensors. Constant air flow and temperature is maintained within the enclosure where the corrosion sensor is located by integrating a variable speed air fan and a heater with the corresponding feedback loop control. Temperature and air flow control loops ensure that corrosivity is measured under similar conditions in different facilities offering a general reference point that allow a one to one comparison between facilities with similar or different pollution levels.

Network Computing for Distributed Underwater Acoustic Sensors

DTIC Science & Technology

2014-03-31

underwater sensor network with mobility. In preparation. [3] EvoLogics (2013), Underwater Acoustic Modems, (Product Information Guide... Wireless Communications, 9(9), 2934–2944. [21] Pompili, D. and Akyildiz, I. (2010), A multimedia cross-layer protocol for underwater acoustic sensor networks ... Network Computing for Distributed Underwater Acoustic Sensors M. Barbeau E. Kranakis

Noncontact Monitoring of Respiration by Dynamic Air-Pressure Sensor.

PubMed

Takarada, Tohru; Asada, Tetsunosuke; Sumi, Yoshihisa; Higuchi, Yoshinori

2015-01-01

We have previously reported that a dynamic air-pressure sensor system allows respiratory status to be visually monitored for patients in minimally clothed condition. The dynamic air-pressure sensor measures vital information using changes in air pressure. To utilize this device in the field, we must clarify the influence of clothing conditions on measurement. The present study evaluated use of the dynamic air-pressure sensor system as a respiratory monitor that can reliably detect change in breathing patterns irrespective of clothing. Twelve healthy volunteers reclined on a dental chair positioned horizontally with the sensor pad for measuring air-pressure signals corresponding to respiration placed on the seat back of the dental chair in the central lumbar region. Respiratory measurements were taken under 2 conditions: (a) thinly clothed (subject lying directly on the sensor pad); and (b) thickly clothed (subject lying on the sensor pad covered with a pressure-reducing sheet). Air-pressure signals were recorded and time integration values for air pressure during each expiration were calculated. This information was compared with expiratory tidal volume measured simultaneously by a respirometer connected to the subject via face mask. The dynamic air-pressure sensor was able to receive the signal corresponding to respiration regardless of clothing conditions. A strong correlation was identified between expiratory tidal volume and time integration values for air pressure during each expiration for all subjects under both clothing conditions (0.840-0.988 for the thinly clothed condition and 0.867-0.992 for the thickly clothed condition). These results show that the dynamic air-pressure sensor is useful for monitoring respiratory physiology irrespective of clothing.

A Comparative Study of Sound Speed in Air at Room Temperature between a Pressure Sensor and a Sound Sensor

ERIC Educational Resources Information Center

Amrani, D.

2013-01-01

This paper deals with the comparison of sound speed measurements in air using two types of sensor that are widely employed in physics and engineering education, namely a pressure sensor and a sound sensor. A computer-based laboratory with pressure and sound sensors was used to carry out measurements of air through a 60 ml syringe. The fast Fourier…

Highlights from the Air Sensors 2014 Workshop

EPA Science Inventory

In June 2014, the U.S. Environmental Protection Agency (EPA) hosted its fourth next-generation air monitoring workshop to discuss the current state of the science in air sensor technologies and their applications for environmental monitoring, Air Sensors 2014: A New Frontier. Th...

Capacity Building for Research and Education in GIS/GPS Technology and Systems

DTIC Science & Technology

2015-05-20

In multi- sensor area Wireless Sensor Networking (WSN) fields will be explored. As a step forward the research to be conducted in WSN field is to...Agriculture Using Technology for Crops Scouting in Agriculture Application of Technology in Precision Agriculture Wireless Sensor Network (WSN) in...Cooperative Engagement Capability Range based algorithms for Wireless Sensor Network Self-configurable Wireless Sensor Network Energy Efficient Wireless

Laser-Based and Ultra-Portable Gas Sensor for Indoor and Outdoor Formaldehyde (HCHO) Monitoring

NASA Astrophysics Data System (ADS)

Shutter, J. D.; Allen, N.; Paul, J.; Thiebaud, J.; So, S.; Scherer, J. J.; Keutsch, F. N.

2017-12-01

While used as a key tracer of oxidative chemistry in the atmosphere, formaldehyde (HCHO) is also a known human carcinogen and is listed and regulated by the United States EPA as a hazardous air pollutant. Combustion processes and photochemical oxidation of volatile organic compounds (VOCs) are the major outdoor sources of HCHO, and building materials and household products are ubiquitous sources of indoor HCHO. Due to the ease with which humans can be exposed to HCHO, it is imperative to monitor levels of both indoor and outdoor HCHO exposure in both short and long-term studies.High-quality direct and indirect methods of quantifying HCHO mixing ratios exist, but instrument size and user-friendliness can make them cumbersome or impractical for certain types of indoor and long-term outdoor measurements. In this study, we present urban HCHO measurements by using a new, commercially-available, ppbv-level accurate HCHO gas sensor (Aeris Technologies' MIRA Pico VOC Laser-Based Gas Analyzer) that is highly portable (29 cm x 20 cm x 10 cm), lightweight (3 kg), easy-to-use, and has low power (15 W) consumption. Using an ultra-compact multipass cell, an absorption path length of 13 m is achieved, resulting in a sensor capable of achieving ppbv/s sensitivity levels with no significant spectral interferences.To demonstrate the utility of the gas sensor for emissions measurements, a GPS was attached to the sensor's housing in order to map mobile HCHO measurements in real-time around the Boston, Massachusetts, metro area. Furthermore, the sensor was placed in residential and industrial environments to show its usefulness for indoor and outdoor pollution measurements. Lastly, we show the feasibility of using the HCHO sensor (or a network of them) in long-term monitoring stations for hazardous air pollutants.

A Spatiotemporal Prediction Framework for Air Pollution Based on Deep RNN

NASA Astrophysics Data System (ADS)

Fan, J.; Li, Q.; Hou, J.; Feng, X.; Karimian, H.; Lin, S.

2017-10-01

Time series data in practical applications always contain missing values due to sensor malfunction, network failure, outliers etc. In order to handle missing values in time series, as well as the lack of considering temporal properties in machine learning models, we propose a spatiotemporal prediction framework based on missing value processing algorithms and deep recurrent neural network (DRNN). By using missing tag and missing interval to represent time series patterns, we implement three different missing value fixing algorithms, which are further incorporated into deep neural network that consists of LSTM (Long Short-term Memory) layers and fully connected layers. Real-world air quality and meteorological datasets (Jingjinji area, China) are used for model training and testing. Deep feed forward neural networks (DFNN) and gradient boosting decision trees (GBDT) are trained as baseline models against the proposed DRNN. Performances of three missing value fixing algorithms, as well as different machine learning models are evaluated and analysed. Experiments show that the proposed DRNN framework outperforms both DFNN and GBDT, therefore validating the capacity of the proposed framework. Our results also provides useful insights for better understanding of different strategies that handle missing values.

NY-uHMT: A dense hydro-meteorological network to characterize urban land-atmosphere interactions

NASA Astrophysics Data System (ADS)

Ramamurthy, P.; Lakhankar, T.; Khanbilvardi, R.; Devineni, N.

2016-12-01

Most people in the US live in large Metropolitan areas that have a dense urban core in the center, dominated by built surfaces and surrounded by residential/suburban areas that consist a mix of built, vegetated and permeable surfaces. This creates a gradient in the hydro-meteorological environment giving rise to complex land-atmosphere interactions. Current modeling platforms and observational techniques like tower measurements do not adequately account for the underlying heterogeneity. To address this critical gap in our understanding we have instituted a dense network of sensors in the New York Metropolitan area. This unique urban sensor network consists of instrumentation to monitor soil moisture at multiple depths along with air temperature, relative humidity and precipitation, with room to add additional sensors in the future. The network is autonomous and connected to a centralized server using cellular towers. Apart from describing the spatial variability in hydro-meteorological quantities the network will also aid in conducting high-resolution numerical simulations to study and forecast urban weather and climate. In one such simulation conducted to partition the influence of storage flux, wind pattern and circulation and soil moisture deficit on urban heat island intensity (UHI), we found that the daily variability in UHI in NYC was sensitive to available energy and wind pattern. The long-term trend in UHI was however related to soil moisture deficit. In fact a prolonged heat wave period witnessed during summer 2006 correlated well with an extended dry period and the daily UHI in NYC almost doubled. Moreover, the urban soils also suffered from high degree of dessication, owing to drier urban boundary layer.

Effects of equipment performance on data quality from the National Atmospheric Deposition Program/National Trends Network and the Mercury Deposition Network

USGS Publications Warehouse

Wetherbee, Gregory A.; Rhodes, Mark F.

2013-01-01

The U.S. Geological Survey Branch of Quality Systems operates the Precipitation Chemistry Quality Assurance project (PCQA) to provide independent, external quality-assurance for the National Atmospheric Deposition Program (NADP). NADP is composed of five monitoring networks that measure the chemical composition of precipitation and ambient air. PCQA and the NADP Program Office completed five short-term studies to investigate the effects of equipment performance with respect to the National Trends Network (NTN) and Mercury Deposition Network (MDN) data quality: sample evaporation from NTN collectors; sample volume and mercury loss from MDN collectors; mercury adsorption to MDN collector glassware, grid-type precipitation sensors for precipitation collectors, and the effects of an NTN collector wind shield on sample catch efficiency. Sample-volume evaporation from an NTN Aerochem Metrics (ACM) collector ranged between 1.1–33 percent with a median of 4.7 percent. The results suggest that weekly NTN sample evaporation is small relative to sample volume. MDN sample evaporation occurs predominantly in western and southern regions of the United States (U.S.) and more frequently with modified ACM collectors than with N-CON Systems Inc. collectors due to differences in airflow through the collectors. Variations in mercury concentrations, measured to be as high as 47.5 percent per week with a median of 5 percent, are associated with MDN sample-volume loss. Small amounts of mercury are also lost from MDN samples by adsorption to collector glassware irrespective of collector type. MDN 11-grid sensors were found to open collectors sooner, keep them open longer, and cause fewer lid cycles than NTN 7-grid sensors. Wind shielding an NTN ACM collector resulted in collection of larger quantities of precipitation while also preserving sample integrity.

Demonstration of a roving-host wireless sensor network for rapid assessment monitoring of structural health

NASA Astrophysics Data System (ADS)

Mascarenas, David D. L.; Flynn, Eric; Lin, Kaisen; Farinholt, Kevin; Park, Gyuhae; Gupta, Rajesh; Todd, Michael; Farrar, Charles

2008-03-01

A major challenge impeding the deployment of wireless sensor networks for structural health monitoring (SHM) is developing means to supply power to the sensor nodes in a cost-effective manner. In this work an initial test of a roving-host wireless sensor network was performed on a bridge near Truth or Consequences, NM in August of 2007. The roving-host wireless sensor network features a radio controlled helicopter responsible for wirelessly delivering energy to sensor nodes on an "as-needed" basis. In addition, the helicopter also serves as a central data repository and processing center for the information collected by the sensor network. The sensor nodes used on the bridge were developed for measuring the peak displacement of the bridge, as well as measuring the preload of some of the bolted joints in the bridge. These sensors and sensor nodes were specifically designed to be able to operate from energy supplied wirelessly from the helicopter. The ultimate goal of this research is to ease the requirement for battery power supplies in wireless sensor networks.

Flexible Fusion Structure-Based Performance Optimization Learning for Multisensor Target Tracking

PubMed Central

Ge, Quanbo; Wei, Zhongliang; Cheng, Tianfa; Chen, Shaodong; Wang, Xiangfeng

2017-01-01

Compared with the fixed fusion structure, the flexible fusion structure with mixed fusion methods has better adjustment performance for the complex air task network systems, and it can effectively help the system to achieve the goal under the given constraints. Because of the time-varying situation of the task network system induced by moving nodes and non-cooperative target, and limitations such as communication bandwidth and measurement distance, it is necessary to dynamically adjust the system fusion structure including sensors and fusion methods in a given adjustment period. Aiming at this, this paper studies the design of a flexible fusion algorithm by using an optimization learning technology. The purpose is to dynamically determine the sensors’ numbers and the associated sensors to take part in the centralized and distributed fusion processes, respectively, herein termed sensor subsets selection. Firstly, two system performance indexes are introduced. Especially, the survivability index is presented and defined. Secondly, based on the two indexes and considering other conditions such as communication bandwidth and measurement distance, optimization models for both single target tracking and multi-target tracking are established. Correspondingly, solution steps are given for the two optimization models in detail. Simulation examples are demonstrated to validate the proposed algorithms. PMID:28481243

An Embedded Multi-Agent Systems Based Industrial Wireless Sensor Network

PubMed Central

Brennan, Robert W.

2017-01-01

With the emergence of cyber-physical systems, there has been a growing interest in network-connected devices. One of the key requirements of a cyber-physical device is the ability to sense its environment. Wireless sensor networks are a widely-accepted solution for this requirement. In this study, an embedded multi-agent systems-managed wireless sensor network is presented. A novel architecture is proposed, along with a novel wireless sensor network architecture. Active and passive wireless sensor node types are defined, along with their communication protocols, and two application-specific examples are presented. A series of three experiments is conducted to evaluate the performance of the agent-embedded wireless sensor network. PMID:28906452

An Embedded Multi-Agent Systems Based Industrial Wireless Sensor Network.

PubMed

Taboun, Mohammed S; Brennan, Robert W

2017-09-14

With the emergence of cyber-physical systems, there has been a growing interest in network-connected devices. One of the key requirements of a cyber-physical device is the ability to sense its environment. Wireless sensor networks are a widely-accepted solution for this requirement. In this study, an embedded multi-agent systems-managed wireless sensor network is presented. A novel architecture is proposed, along with a novel wireless sensor network architecture. Active and passive wireless sensor node types are defined, along with their communication protocols, and two application-specific examples are presented. A series of three experiments is conducted to evaluate the performance of the agent-embedded wireless sensor network.

Wearable technology: role in respiratory health and disease.

PubMed

Aliverti, Andrea

2017-06-01

In the future, diagnostic devices will be able to monitor a patient's physiological or biochemical parameters continuously, under natural physiological conditions and in any environment through wearable biomedical sensors. Together with apps that capture and interpret data, and integrated enterprise and cloud data repositories, the networks of wearable devices and body area networks will constitute the healthcare's Internet of Things. In this review, four main areas of interest for respiratory healthcare are described: pulse oximetry, pulmonary ventilation, activity tracking and air quality assessment. Although several issues still need to be solved, smart wearable technologies will provide unique opportunities for the future or personalised respiratory medicine.

Wearable technology: role in respiratory health and disease

PubMed Central

2017-01-01

In the future, diagnostic devices will be able to monitor a patient’s physiological or biochemical parameters continuously, under natural physiological conditions and in any environment through wearable biomedical sensors. Together with apps that capture and interpret data, and integrated enterprise and cloud data repositories, the networks of wearable devices and body area networks will constitute the healthcare’s Internet of Things. In this review, four main areas of interest for respiratory healthcare are described: pulse oximetry, pulmonary ventilation, activity tracking and air quality assessment. Although several issues still need to be solved, smart wearable technologies will provide unique opportunities for the future or personalised respiratory medicine. PMID:28966692

Bio-Inspired Stretchable Absolute Pressure Sensor Network

PubMed Central

Guo, Yue; Li, Yu-Hung; Guo, Zhiqiang; Kim, Kyunglok; Chang, Fu-Kuo; Wang, Shan X.

2016-01-01

A bio-inspired absolute pressure sensor network has been developed. Absolute pressure sensors, distributed on multiple silicon islands, are connected as a network by stretchable polyimide wires. This sensor network, made on a 4’’ wafer, has 77 nodes and can be mounted on various curved surfaces to cover an area up to 0.64 m × 0.64 m, which is 100 times larger than its original size. Due to Micro Electro-Mechanical system (MEMS) surface micromachining technology, ultrathin sensing nodes can be realized with thicknesses of less than 100 µm. Additionally, good linearity and high sensitivity (~14 mV/V/bar) have been achieved. Since the MEMS sensor process has also been well integrated with a flexible polymer substrate process, the entire sensor network can be fabricated in a time-efficient and cost-effective manner. Moreover, an accurate pressure contour can be obtained from the sensor network. Therefore, this absolute pressure sensor network holds significant promise for smart vehicle applications, especially for unmanned aerial vehicles. PMID:26729134

The Coverage Problem in Video-Based Wireless Sensor Networks: A Survey

PubMed Central

Costa, Daniel G.; Guedes, Luiz Affonso

2010-01-01

Wireless sensor networks typically consist of a great number of tiny low-cost electronic devices with limited sensing and computing capabilities which cooperatively communicate to collect some kind of information from an area of interest. When wireless nodes of such networks are equipped with a low-power camera, visual data can be retrieved, facilitating a new set of novel applications. The nature of video-based wireless sensor networks demands new algorithms and solutions, since traditional wireless sensor networks approaches are not feasible or even efficient for that specialized communication scenario. The coverage problem is a crucial issue of wireless sensor networks, requiring specific solutions when video-based sensors are employed. In this paper, it is surveyed the state of the art of this particular issue, regarding strategies, algorithms and general computational solutions. Open research areas are also discussed, envisaging promising investigation considering coverage in video-based wireless sensor networks. PMID:22163651

Distributed Estimation, Coding, and Scheduling in Wireless Visual Sensor Networks

ERIC Educational Resources Information Center

Yu, Chao

2013-01-01

In this thesis, we consider estimation, coding, and sensor scheduling for energy efficient operation of wireless visual sensor networks (VSN), which consist of battery-powered wireless sensors with sensing (imaging), computation, and communication capabilities. The competing requirements for applications of these wireless sensor networks (WSN)…

Optimizing Cluster Heads for Energy Efficiency in Large-Scale Heterogeneous Wireless Sensor Networks

DOE PAGES

Gu, Yi; Wu, Qishi; Rao, Nageswara S. V.

2010-01-01

Many complex sensor network applications require deploying a large number of inexpensive and small sensors in a vast geographical region to achieve quality through quantity. Hierarchical clustering is generally considered as an efficient and scalable way to facilitate the management and operation of such large-scale networks and minimize the total energy consumption for prolonged lifetime. Judicious selection of cluster heads for data integration and communication is critical to the success of applications based on hierarchical sensor networks organized as layered clusters. We investigate the problem of selecting sensor nodes in a predeployed sensor network to be the cluster heads tomore » minimize the total energy needed for data gathering. We rigorously derive an analytical formula to optimize the number of cluster heads in sensor networks under uniform node distribution, and propose a Distance-based Crowdedness Clustering algorithm to determine the cluster heads in sensor networks under general node distribution. The results from an extensive set of experiments on a large number of simulated sensor networks illustrate the performance superiority of the proposed solution over the clustering schemes based on k -means algorithm.« less

Double air-fuel ratio sensor system having double-skip function

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

Katsuno, T.

1988-01-26

A method for controlling the air-fuel ratio in an internal combustion engine is described having a catalyst converter for removing pollutants in the exhaust gas thereof, and upstream-side and downstream-side air-fuel ratio sensors disposed upstream and downstream, respectively, of the catalyst converter for detecting a concentration of a specific component in an exhaust gas, comprising the steps of: comparing the output of the upstream-side air-fuel ratio sensor with a first predetermined value; gradually changing a first air-fuel ratio correction amount in accordance with a result of the comparison of the output of the upstream-side air-fuel ratio sensor with the predeterminedmore » value; shifting the first air-fuel ratio correction amount by a first skip amount during a predetermined time period after the result of the comparison of the upstream-side air-fuel ratio sensor is changed; shifting the first air-fuel ratio correction amount by a second skip amount smaller than the first skip amount after the predetermined time period has passed; comparing the output of the downstream-side air-fuel ratio with a second predetermined value, calculating a second air-fuel ratio correction amount in accordance with the comparison result of the output of the downstream-side air-fuel ratio sensor with the second predetermined value; and adjusting the actual air-fuel ratio in accordance with the first and second air-fuel ratio correction amounts; wherein the gradually-changing step comprises the steps of: gradually decreasing the first air-fuel ratio correction amount when the output of the upstream-side air-fuel sensor is on the rich side with respect to the first predetermined value; and gradually increasing the first air-fuel ratio correction amount when the output of the upstream-side air-fuel sensor is on the lean side with respect to the first predetermined value.« less

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

PubMed Central

Mao, Yuxin; Wei, Guiyi

2010-01-01

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

Smart border: ad-hoc wireless sensor networks for border surveillance

NASA Astrophysics Data System (ADS)

He, Jun; Fallahi, Mahmoud; Norwood, Robert A.; Peyghambarian, Nasser

2011-06-01

Wireless sensor networks have been proposed as promising candidates to provide automated monitoring, target tracking, and intrusion detection for border surveillance. In this paper, we demonstrate an ad-hoc wireless sensor network system for border surveillance. The network consists of heterogeneously autonomous sensor nodes that distributively cooperate with each other to enable a smart border in remote areas. This paper also presents energy-aware and sleeping algorithms designed to maximize the operating lifetime of the deployed sensor network. Lessons learned in building the network and important findings from field experiments are shared in the paper.

The expanding scope of air pollution monitoring can facilitate sustainable development.

PubMed

Knox, Andrew; Mykhaylova, Natalia; Evans, Greg J; Lee, Colin J; Karney, Bryan; Brook, Jeffrey R

2013-03-15

This paper explores technologies currently expanding the physical scope of air pollution monitoring and their potential contributions to the assessment of sustainable development. This potential lies largely in the ability of these technologies to address issues typically on the fringe of the air pollution agenda. Air pollution monitoring tends to be primarily focused on human health, and largely neglects other aspects of sustainable development. Sensor networks, with their relatively inexpensive monitoring nodes, allow for monitoring with finer spatiotemporal resolution. This resolution can support more conclusive studies of air pollution's effect on socio-ecological justice and human quality of life. Satellite observation of air pollution allows for wider geographical scope, and in doing so can facilitate studies of air pollution's effects on natural capital and ecosystem resilience. Many air pollution-related aspects of the sustainability of development in human systems are not being given their due attention. Opportunities exist for air pollution monitoring to attend more to these issues. Improvements to the resolution and scale of monitoring make these opportunities realizable. Copyright © 2012 Elsevier B.V. All rights reserved.

Automated Construction of Node Software Using Attributes in a Ubiquitous Sensor Network Environment

PubMed Central

Lee, Woojin; Kim, Juil; Kang, JangMook

2010-01-01

In sensor networks, nodes must often operate in a demanding environment facing restrictions such as restricted computing resources, unreliable wireless communication and power shortages. Such factors make the development of ubiquitous sensor network (USN) applications challenging. To help developers construct a large amount of node software for sensor network applications easily and rapidly, this paper proposes an approach to the automated construction of node software for USN applications using attributes. In the proposed technique, application construction proceeds by first developing a model for the sensor network and then designing node software by setting the values of the predefined attributes. After that, the sensor network model and the design of node software are verified. The final source codes of the node software are automatically generated from the sensor network model. We illustrate the efficiency of the proposed technique by using a gas/light monitoring application through a case study of a Gas and Light Monitoring System based on the Nano-Qplus operating system. We evaluate the technique using a quantitative metric—the memory size of execution code for node software. Using the proposed approach, developers are able to easily construct sensor network applications and rapidly generate a large number of node softwares at a time in a ubiquitous sensor network environment. PMID:22163678

Automated construction of node software using attributes in a ubiquitous sensor network environment.

PubMed

Lee, Woojin; Kim, Juil; Kang, JangMook

2010-01-01

In sensor networks, nodes must often operate in a demanding environment facing restrictions such as restricted computing resources, unreliable wireless communication and power shortages. Such factors make the development of ubiquitous sensor network (USN) applications challenging. To help developers construct a large amount of node software for sensor network applications easily and rapidly, this paper proposes an approach to the automated construction of node software for USN applications using attributes. In the proposed technique, application construction proceeds by first developing a model for the sensor network and then designing node software by setting the values of the predefined attributes. After that, the sensor network model and the design of node software are verified. The final source codes of the node software are automatically generated from the sensor network model. We illustrate the efficiency of the proposed technique by using a gas/light monitoring application through a case study of a Gas and Light Monitoring System based on the Nano-Qplus operating system. We evaluate the technique using a quantitative metric-the memory size of execution code for node software. Using the proposed approach, developers are able to easily construct sensor network applications and rapidly generate a large number of node softwares at a time in a ubiquitous sensor network environment.

Air temperature sensors: dependence of radiative errors on sensor diameter in precision metrology and meteorology

NASA Astrophysics Data System (ADS)

de Podesta, Michael; Bell, Stephanie; Underwood, Robin

2018-04-01

In both meteorological and metrological applications, it is well known that air temperature sensors are susceptible to radiative errors. However, it is not widely known that the radiative error measured by an air temperature sensor in flowing air depends upon the sensor diameter, with smaller sensors reporting values closer to true air temperature. This is not a transient effect related to sensor heat capacity, but a fluid-dynamical effect arising from heat and mass flow in cylindrical geometries. This result has been known historically and is in meteorology text books. However, its significance does not appear to be widely appreciated and, as a consequence, air temperature can be—and probably is being—widely mis-estimated. In this paper, we first review prior descriptions of the ‘sensor size’ effect from the metrological and meteorological literature. We develop a heat transfer model to describe the process for cylindrical sensors, and evaluate the predicted temperature error for a range of sensor sizes and air speeds. We compare these predictions with published predictions and measurements. We report measurements demonstrating this effect in two laboratories at NPL in which the air flow and temperature are exceptionally closely controlled. The results are consistent with the heat-transfer model, and show that the air temperature error is proportional to the square root of the sensor diameter and that, even under good laboratory conditions, it can exceed 0.1 °C for a 6 mm diameter sensor. We then consider the implications of this result. In metrological applications, errors of the order of 0.1 °C are significant, representing limiting uncertainties in dimensional and mass measurements. In meteorological applications, radiative errors can easily be much larger. But in both cases, an understanding of the diameter dependence allows assessment and correction of the radiative error using a multi-sensor technique.

Development and evaluation of optical fiber NH3 sensors for application in air quality monitoring

NASA Astrophysics Data System (ADS)

Huang, Yu; Wieck, Lucas; Tao, Shiquan

2013-02-01

Ammonia is a major air pollutant emitted from agricultural practices. Sources of ammonia include manure from animal feeding operations and fertilizer from cropping systems. Sensor technologies with capability of continuous real time monitoring of ammonia concentration in air are needed to qualify ammonia emissions from agricultural activities and further evaluate human and animal health effects, study ammonia environmental chemistry, and provide baseline data for air quality standard. We have developed fiber optic ammonia sensors using different sensing reagents and different polymers for immobilizing sensing reagents. The reversible fiber optic sensors have detection limits down to low ppbv levels. The response time of these sensors ranges from seconds to tens minutes depending on transducer design. In this paper, we report our results in the development and evaluation of fiber optic sensor technologies for air quality monitoring. The effect of change of temperature, humidity and carbon dioxide concentration on fiber optic ammonia sensors has been investigated. Carbon dioxide in air was found not interfere the fiber optic sensors for monitoring NH3. However, the change of humidity can cause interferences to some fiber optic NH3 sensors depending on the sensor's transducer design. The sensitivity of fiber optic NH3 sensors was found depends on temperature. Methods and techniques for eliminating these interferences have been proposed.

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

Zone-Based Routing Protocol for Wireless Sensor Networks

PubMed Central

Venkateswarlu Kumaramangalam, Muni; Adiyapatham, Kandasamy; Kandasamy, Chandrasekaran

2014-01-01

Extensive research happening across the globe witnessed the importance of Wireless Sensor Network in the present day application world. In the recent past, various routing algorithms have been proposed to elevate WSN network lifetime. Clustering mechanism is highly successful in conserving energy resources for network activities and has become promising field for researches. However, the problem of unbalanced energy consumption is still open because the cluster head activities are tightly coupled with role and location of a particular node in the network. Several unequal clustering algorithms are proposed to solve this wireless sensor network multihop hot spot problem. Current unequal clustering mechanisms consider only intra- and intercluster communication cost. Proper organization of wireless sensor network into clusters enables efficient utilization of limited resources and enhances lifetime of deployed sensor nodes. This paper considers a novel network organization scheme, energy-efficient edge-based network partitioning scheme, to organize sensor nodes into clusters of equal size. Also, it proposes a cluster-based routing algorithm, called zone-based routing protocol (ZBRP), for elevating sensor network lifetime. Experimental results show that ZBRP out-performs interims of network lifetime and energy conservation with its uniform energy consumption among the cluster heads. PMID:27437455

Zone-Based Routing Protocol for Wireless Sensor Networks.

PubMed

Venkateswarlu Kumaramangalam, Muni; Adiyapatham, Kandasamy; Kandasamy, Chandrasekaran

2014-01-01

Extensive research happening across the globe witnessed the importance of Wireless Sensor Network in the present day application world. In the recent past, various routing algorithms have been proposed to elevate WSN network lifetime. Clustering mechanism is highly successful in conserving energy resources for network activities and has become promising field for researches. However, the problem of unbalanced energy consumption is still open because the cluster head activities are tightly coupled with role and location of a particular node in the network. Several unequal clustering algorithms are proposed to solve this wireless sensor network multihop hot spot problem. Current unequal clustering mechanisms consider only intra- and intercluster communication cost. Proper organization of wireless sensor network into clusters enables efficient utilization of limited resources and enhances lifetime of deployed sensor nodes. This paper considers a novel network organization scheme, energy-efficient edge-based network partitioning scheme, to organize sensor nodes into clusters of equal size. Also, it proposes a cluster-based routing algorithm, called zone-based routing protocol (ZBRP), for elevating sensor network lifetime. Experimental results show that ZBRP out-performs interims of network lifetime and energy conservation with its uniform energy consumption among the cluster heads.

Integration of Satellite, Modeled, and Ground Based Aerosol Data for use in Air Quality and Public Health Applications

NASA Astrophysics Data System (ADS)

Garcia, V.; Kondragunta, S.; Holland, D.; Dimmick, F.; Boothe, V.; Szykman, J.; Chu, A.; Kittaka, C.; Al-Saadi, J.; Engel-Cox, J.; Hoff, R.; Wayland, R.; Rao, S.; Remer, L.

2006-05-01

Advancements in remote sensing over the past decade have been recognized by governments around the world and led to the development of the international Global Earth Observation System of Systems 10-Year Implementation Plan. The plan for the U.S. contribution to GEOSS has been put forth in The Strategic Plan for the U.S. Integrated Earth Observation System (IEOS) developed under IWGEO-CENR. The approach for the development of the U.S. IEOS is to focus on specific societal benefits that can be achieved by integrating the nation's Earth observation capabilities. One such challenge is our ability to understand the impact of poor air quality on human health and well being. Historically, the air monitoring networks put in place for the Nations air quality programs provided the only aerosol air quality data on an ongoing and systematic basis at national levels. However, scientific advances in the remote sensing of aerosols from space have improved dramatically. The MODIS sensor and GOES Imager aboard NASA and NOAA satellites, respectively, provide synoptic-scale measurements of aerosol optical depth (AOD) which have been demonstrated to correlate with high levels of PM10 and PM2.5 at the surface. The MODIS sensor has been shown to be capable of a 1 km x 1 km (at nadir) AOD product, while the GOES Imager can provide AOD at 4 km x 4 km every 30 minutes. Within the next several years NOAA and EPA will begin to issue PM2.5 air quality forecasts over the entire domain of the eastern United States, eventually extending to national coverage. These forecasts will provide continuous estimated values of PM2.5 on a daily basis. A multi-agency collaborative project among government and academia is underway to improve the spatial prediction of fine particulate matter through the integration of multi-sensor and multi-platform aerosol observations (MODIS and GOES), numerical model output, and air monitoring data. By giving more weight to monitoring data in monitored areas and relying on adjusted model output and satellite data in non-monitored areas, a Bayesian hierarchical space-time model will be used to improve the accuracy of prediction and associated prediction errors. The improved spatial predictions will be tested as estimates of exposure for input to modeling relationships between air quality and asthma/other respiratory diseases through CDC under the Environmental Public Health Tracking Network. We will also focus on the use of the predictive spatial maps within the EPA AIRNow program which provides near real-time spatial maps of daily average PM2.5 concentrations across the US. We will present the overall project plan and preliminary results with emphasis on how GEOSS framework is facilitating this effort.

Neural Network-Based Sensor Validation for Turboshaft Engines

NASA Technical Reports Server (NTRS)

Moller, James C.; Litt, Jonathan S.; Guo, Ten-Huei

1998-01-01

Sensor failure detection, isolation, and accommodation using a neural network approach is described. An auto-associative neural network is configured to perform dimensionality reduction on the sensor measurement vector and provide estimated sensor values. The sensor validation scheme is applied in a simulation of the T700 turboshaft engine in closed loop operation. Performance is evaluated based on the ability to detect faults correctly and maintain stable and responsive engine operation. The set of sensor outputs used for engine control forms the network input vector. Analytical redundancy is verified by training networks of successively smaller bottleneck layer sizes. Training data generation and strategy are discussed. The engine maintained stable behavior in the presence of sensor hard failures. With proper selection of fault determination thresholds, stability was maintained in the presence of sensor soft failures.

Decentralized sensor fusion for Ubiquitous Networking Robotics in Urban Areas.

PubMed

Sanfeliu, Alberto; Andrade-Cetto, Juan; Barbosa, Marco; Bowden, Richard; Capitán, Jesús; Corominas, Andreu; Gilbert, Andrew; Illingworth, John; Merino, Luis; Mirats, Josep M; Moreno, Plínio; Ollero, Aníbal; Sequeira, João; Spaan, Matthijs T J

2010-01-01

In this article we explain the architecture for the environment and sensors that has been built for the European project URUS (Ubiquitous Networking Robotics in Urban Sites), a project whose objective is to develop an adaptable network robot architecture for cooperation between network robots and human beings and/or the environment in urban areas. The project goal is to deploy a team of robots in an urban area to give a set of services to a user community. This paper addresses the sensor architecture devised for URUS and the type of robots and sensors used, including environment sensors and sensors onboard the robots. Furthermore, we also explain how sensor fusion takes place to achieve urban outdoor execution of robotic services. Finally some results of the project related to the sensor network are highlighted.

Biology-Inspired Distributed Consensus in Massively-Deployed Sensor Networks

NASA Technical Reports Server (NTRS)

Jones, Kennie H.; Lodding, Kenneth N.; Olariu, Stephan; Wilson, Larry; Xin, Chunsheng

2005-01-01

Promises of ubiquitous control of the physical environment by large-scale wireless sensor networks open avenues for new applications that are expected to redefine the way we live and work. Most of recent research has concentrated on developing techniques for performing relatively simple tasks in small-scale sensor networks assuming some form of centralized control. The main contribution of this work is to propose a new way of looking at large-scale sensor networks, motivated by lessons learned from the way biological ecosystems are organized. Indeed, we believe that techniques used in small-scale sensor networks are not likely to scale to large networks; that such large-scale networks must be viewed as an ecosystem in which the sensors/effectors are organisms whose autonomous actions, based on local information, combine in a communal way to produce global results. As an example of a useful function, we demonstrate that fully distributed consensus can be attained in a scalable fashion in massively deployed sensor networks where individual motes operate based on local information, making local decisions that are aggregated across the network to achieve globally-meaningful effects.

A Mobile Sensor Network System for Monitoring of Unfriendly Environments.

PubMed

Song, Guangming; Zhou, Yaoxin; Ding, Fei; Song, Aiguo

2008-11-14

Observing microclimate changes is one of the most popular applications of wireless sensor networks. However, some target environments are often too dangerous or inaccessible to humans or large robots and there are many challenges for deploying and maintaining wireless sensor networks in those unfriendly environments. This paper presents a mobile sensor network system for solving this problem. The system architecture, the mobile node design, the basic behaviors and advanced network capabilities have been investigated respectively. A wheel-based robotic node architecture is proposed here that can add controlled mobility to wireless sensor networks. A testbed including some prototype nodes has also been created for validating the basic functions of the proposed mobile sensor network system. Motion performance tests have been done to get the positioning errors and power consumption model of the mobile nodes. Results of the autonomous deployment experiment show that the mobile nodes can be distributed evenly into the previously unknown environments. It provides powerful support for network deployment and maintenance and can ensure that the sensor network will work properly in unfriendly environments.

LinkMind: link optimization in swarming mobile sensor networks.

PubMed

Ngo, Trung Dung

2011-01-01

A swarming mobile sensor network is comprised of a swarm of wirelessly connected mobile robots equipped with various sensors. Such a network can be applied in an uncertain environment for services such as cooperative navigation and exploration, object identification and information gathering. One of the most advantageous properties of the swarming wireless sensor network is that mobile nodes can work cooperatively to organize an ad-hoc network and optimize the network link capacity to maximize the transmission of gathered data from a source to a target. This paper describes a new method of link optimization of swarming mobile sensor networks. The new method is based on combination of the artificial potential force guaranteeing connectivities of the mobile sensor nodes and the max-flow min-cut theorem of graph theory ensuring optimization of the network link capacity. The developed algorithm is demonstrated and evaluated in simulation.

LinkMind: Link Optimization in Swarming Mobile Sensor Networks

PubMed Central

Ngo, Trung Dung

2011-01-01

A swarming mobile sensor network is comprised of a swarm of wirelessly connected mobile robots equipped with various sensors. Such a network can be applied in an uncertain environment for services such as cooperative navigation and exploration, object identification and information gathering. One of the most advantageous properties of the swarming wireless sensor network is that mobile nodes can work cooperatively to organize an ad-hoc network and optimize the network link capacity to maximize the transmission of gathered data from a source to a target. This paper describes a new method of link optimization of swarming mobile sensor networks. The new method is based on combination of the artificial potential force guaranteeing connectivities of the mobile sensor nodes and the max-flow min-cut theorem of graph theory ensuring optimization of the network link capacity. The developed algorithm is demonstrated and evaluated in simulation. PMID:22164070

Using Neural Networks for Sensor Validation

NASA Technical Reports Server (NTRS)

Mattern, Duane L.; Jaw, Link C.; Guo, Ten-Huei; Graham, Ronald; McCoy, William

1998-01-01

This paper presents the results of applying two different types of neural networks in two different approaches to the sensor validation problem. The first approach uses a functional approximation neural network as part of a nonlinear observer in a model-based approach to analytical redundancy. The second approach uses an auto-associative neural network to perform nonlinear principal component analysis on a set of redundant sensors to provide an estimate for a single failed sensor. The approaches are demonstrated using a nonlinear simulation of a turbofan engine. The fault detection and sensor estimation results are presented and the training of the auto-associative neural network to provide sensor estimates is discussed.

Open-WiSe: a solar powered wireless sensor network platform.

PubMed

González, Apolinar; Aquino, Raúl; Mata, Walter; Ochoa, Alberto; Saldaña, Pedro; Edwards, Arthur

2012-01-01

Because battery-powered nodes are required in wireless sensor networks and energy consumption represents an important design consideration, alternate energy sources are needed to provide more effective and optimal function. The main goal of this work is to present an energy harvesting wireless sensor network platform, the Open Wireless Sensor node (WiSe). The design and implementation of the solar powered wireless platform is described including the hardware architecture, firmware, and a POSIX Real-Time Kernel. A sleep and wake up strategy was implemented to prolong the lifetime of the wireless sensor network. This platform was developed as a tool for researchers investigating Wireless sensor network or system integrators.

Bluetooth-based wireless sensor networks

NASA Astrophysics Data System (ADS)

You, Ke; Liu, Rui Qiang

2007-11-01

In this work a Bluetooth-based wireless sensor network is proposed. In this bluetooth-based wireless sensor networks, information-driven star topology and energy-saved mode are used, through which a blue master node can control more than seven slave node, the energy of each sensor node is reduced and secure management of each sensor node is improved.

Multisensor system for toxic gases detection generated on indoor environments

NASA Astrophysics Data System (ADS)

Durán, C. M.; Monsalve, P. A. G.; Mosquera, C. J.

2016-11-01

This work describes a wireless multisensory system for different toxic gases detection generated on indoor environments (i.e., Underground coal mines, etc.). The artificial multisensory system proposed in this study was developed through a set of six chemical gas sensors (MQ) of low cost with overlapping sensitivities to detect hazardous gases in the air. A statistical parameter was implemented to the data set and two pattern recognition methods such as Principal Component Analysis (PCA) and Discriminant Function Analysis (DFA) were used for feature selection. The toxic gases categories were classified with a Probabilistic Neural Network (PNN) in order to validate the results previously obtained. The tests were carried out to verify feasibility of the application through a wireless communication model which allowed to monitor and store the information of the sensor signals for the appropriate analysis. The success rate in the measures discrimination was 100%, using an artificial neural network where leave-one-out was used as cross validation method.

Source Authentication for Code Dissemination Supporting Dynamic Packet Size in Wireless Sensor Networks.

PubMed

Kim, Daehee; Kim, Dongwan; An, Sunshin

2016-07-09

Code dissemination in wireless sensor networks (WSNs) is a procedure for distributing a new code image over the air in order to update programs. Due to the fact that WSNs are mostly deployed in unattended and hostile environments, secure code dissemination ensuring authenticity and integrity is essential. Recent works on dynamic packet size control in WSNs allow enhancing the energy efficiency of code dissemination by dynamically changing the packet size on the basis of link quality. However, the authentication tokens attached by the base station become useless in the next hop where the packet size can vary according to the link quality of the next hop. In this paper, we propose three source authentication schemes for code dissemination supporting dynamic packet size. Compared to traditional source authentication schemes such as μTESLA and digital signatures, our schemes provide secure source authentication under the environment, where the packet size changes in each hop, with smaller energy consumption.

Source Authentication for Code Dissemination Supporting Dynamic Packet Size in Wireless Sensor Networks †

PubMed Central

Kim, Daehee; Kim, Dongwan; An, Sunshin

2016-01-01

Code dissemination in wireless sensor networks (WSNs) is a procedure for distributing a new code image over the air in order to update programs. Due to the fact that WSNs are mostly deployed in unattended and hostile environments, secure code dissemination ensuring authenticity and integrity is essential. Recent works on dynamic packet size control in WSNs allow enhancing the energy efficiency of code dissemination by dynamically changing the packet size on the basis of link quality. However, the authentication tokens attached by the base station become useless in the next hop where the packet size can vary according to the link quality of the next hop. In this paper, we propose three source authentication schemes for code dissemination supporting dynamic packet size. Compared to traditional source authentication schemes such as μTESLA and digital signatures, our schemes provide secure source authentication under the environment, where the packet size changes in each hop, with smaller energy consumption. PMID:27409616

Dynamic Hierarchical Sleep Scheduling for Wireless Ad-Hoc Sensor Networks

PubMed Central

Wen, Chih-Yu; Chen, Ying-Chih

2009-01-01

This paper presents two scheduling management schemes for wireless sensor networks, which manage the sensors by utilizing the hierarchical network structure and allocate network resources efficiently. A local criterion is used to simultaneously establish the sensing coverage and connectivity such that dynamic cluster-based sleep scheduling can be achieved. The proposed schemes are simulated and analyzed to abstract the network behaviors in a number of settings. The experimental results show that the proposed algorithms provide efficient network power control and can achieve high scalability in wireless sensor networks. PMID:22412343

Dynamic hierarchical sleep scheduling for wireless ad-hoc sensor networks.

PubMed

Wen, Chih-Yu; Chen, Ying-Chih

2009-01-01

This paper presents two scheduling management schemes for wireless sensor networks, which manage the sensors by utilizing the hierarchical network structure and allocate network resources efficiently. A local criterion is used to simultaneously establish the sensing coverage and connectivity such that dynamic cluster-based sleep scheduling can be achieved. The proposed schemes are simulated and analyzed to abstract the network behaviors in a number of settings. The experimental results show that the proposed algorithms provide efficient network power control and can achieve high scalability in wireless sensor networks.

Tactical Network Load Balancing in Multi-Gateway Wireless Sensor Networks

DTIC Science & Technology

2013-12-01

writeup scrsz = get( 0 ,’ScreenSize’); %Creation of the random Sensor Network fig = figure(1); set(fig, ’Position’,[1 scrsz( 4 )*.25 scrsz(3)*.7...thesis writeup scrsz = get( 0 ,’ScreenSize’); %Creation of the random Sensor Network fig = figure(1); set(fig, ’Position’,[1 scrsz( 4 )*.25 scrsz(3)*.7...TYPE AND DATES COVERED Master’s Thesis 4 . TITLE AND SUBTITLE TACTICAL NETWORK LOAD BALANCING IN MULTI-GATEWAY WIRELESS SENSOR NETWORKS 5

Web-Based Interface for Command and Control of Network Sensors

NASA Technical Reports Server (NTRS)

Wallick, Michael N.; Doubleday, Joshua R.; Shams, Khawaja S.

2010-01-01

This software allows for the visualization and control of a network of sensors through a Web browser interface. It is currently being deployed for a network of sensors monitoring Mt. Saint Helen s volcano; however, this innovation is generic enough that it can be deployed for any type of sensor Web. From this interface, the user is able to fully control and monitor the sensor Web. This includes, but is not limited to, sending "test" commands to individual sensors in the network, monitoring for real-world events, and reacting to those events

Wireless in-situ Sensor Network for Agriculture and Water Monitoring on a River Basin Scale in Southern Finland: Evaluation from a Data User’s Perspective

PubMed Central

Kotamäki, Niina; Thessler, Sirpa; Koskiaho, Jari; Hannukkala, Asko O.; Huitu, Hanna; Huttula, Timo; Havento, Jukka; Järvenpää, Markku

2009-01-01

Sensor networks are increasingly being implemented for environmental monitoring and agriculture to provide spatially accurate and continuous environmental information and (near) real-time applications. These networks provide a large amount of data which poses challenges for ensuring data quality and extracting relevant information. In the present paper we describe a river basin scale wireless sensor network for agriculture and water monitoring. The network, called SoilWeather, is unique and the first of this type in Finland. The performance of the network is assessed from the user and maintainer perspectives, concentrating on data quality, network maintenance and applications. The results showed that the SoilWeather network has been functioning in a relatively reliable way, but also that the maintenance and data quality assurance by automatic algorithms and calibration samples requires a lot of effort, especially in continuous water monitoring over large areas. We see great benefits on sensor networks enabling continuous, real-time monitoring, while data quality control and maintenance efforts highlight the need for tight collaboration between sensor and sensor network owners to decrease costs and increase the quality of the sensor data in large scale applications. PMID:22574050

Fiber optic sensors; Proceedings of the Meeting, Cannes, France, November 26, 27, 1985

NASA Technical Reports Server (NTRS)

Arditty, Herve J. (Editor); Jeunhomme, Luc B. (Editor)

1986-01-01

The conference presents papers on distributed sensors and sensor networks, signal processing and detection techniques, temperature measurements, chemical sensors, and the measurement of pressure, strain, and displacements. Particular attention is given to optical fiber distributed sensors and sensor networks, tactile sensing in robotics using an optical network and Z-plane techniques, and a spontaneous Raman temperature sensor. Other topics include coherence in optical fiber gyroscopes, a high bandwidth two-phase flow void fraction fiber optic sensor, and a fiber-optic dark-field microbend sensor.

Sensor Data Qualification Technique Applied to Gas Turbine Engines

NASA Technical Reports Server (NTRS)

Csank, Jeffrey T.; Simon, Donald L.

2013-01-01

This paper applies a previously developed sensor data qualification technique to a commercial aircraft engine simulation known as the Commercial Modular Aero-Propulsion System Simulation 40,000 (C-MAPSS40k). The sensor data qualification technique is designed to detect, isolate, and accommodate faulty sensor measurements. It features sensor networks, which group various sensors together and relies on an empirically derived analytical model to relate the sensor measurements. Relationships between all member sensors of the network are analyzed to detect and isolate any faulty sensor within the network.

Multistage Security Mechanism For Hybrid, Large-Scale Wireless Sensor Networks

DTIC Science & Technology

2007-06-01

sensor network . Building on research in the areas of the wireless sensor networks (WSN) and the mobile ad hoc networks (MANET), this thesis proposes an...A wide area network consisting of ballistic missile defense satellites and terrestrial nodes can be viewed as a hybrid, large-scale mobile wireless

Sinkhole Avoidance Routing in Wireless Sensor Networks

DTIC Science & Technology

2011-05-09

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

Universal sensor based on the spectroscopy of glow discharge for the detection of traces of atoms or molecules in air

NASA Astrophysics Data System (ADS)

Atutov, S. N.; Galeyev, A. E.; Plekhanov, A. I.; Yakovlev, A. V.

2018-03-01

A sensitive and versatile sensor for the detection of traces of atoms or molecules in air based on the emission spectroscopy of glow discharge in air has been developed and studied. The advantages of this sensor compared to other well-known methods are that it renders the use of ultrahigh vacuum or cryogenic temperatures superfluous. The sensor is insensitive to the presence of water vapor (for example, in exhaled air) because of the absence of strong water lines in the visible spectral range. It has a high spectral selectivity limited only by Doppler broadening of the emission lines. The high selectivity of the sensor combined with a wide spectral range allows the detection of many toxic impurities, which can be present in air. Moreover, the spectral range used covers almost all biomarkers in exhaled air, making the proposed sensor extremely interesting for medical applications. To our knowledge, the proposed method is the first based on a glow discharge in air.

Decentralized Sensor Fusion for Ubiquitous Networking Robotics in Urban Areas

PubMed Central

Sanfeliu, Alberto; Andrade-Cetto, Juan; Barbosa, Marco; Bowden, Richard; Capitán, Jesús; Corominas, Andreu; Gilbert, Andrew; Illingworth, John; Merino, Luis; Mirats, Josep M.; Moreno, Plínio; Ollero, Aníbal; Sequeira, João; Spaan, Matthijs T.J.

2010-01-01

In this article we explain the architecture for the environment and sensors that has been built for the European project URUS (Ubiquitous Networking Robotics in Urban Sites), a project whose objective is to develop an adaptable network robot architecture for cooperation between network robots and human beings and/or the environment in urban areas. The project goal is to deploy a team of robots in an urban area to give a set of services to a user community. This paper addresses the sensor architecture devised for URUS and the type of robots and sensors used, including environment sensors and sensors onboard the robots. Furthermore, we also explain how sensor fusion takes place to achieve urban outdoor execution of robotic services. Finally some results of the project related to the sensor network are highlighted. PMID:22294927

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).

Quantized Synchronization of Chaotic Neural Networks With Scheduled Output Feedback Control.

PubMed

Wan, Ying; Cao, Jinde; Wen, Guanghui

In this paper, the synchronization problem of master-slave chaotic neural networks with remote sensors, quantization process, and communication time delays is investigated. The information communication channel between the master chaotic neural network and slave chaotic neural network consists of several remote sensors, with each sensor able to access only partial knowledge of output information of the master neural network. At each sampling instants, each sensor updates its own measurement and only one sensor is scheduled to transmit its latest information to the controller's side in order to update the control inputs for the slave neural network. Thus, such communication process and control strategy are much more energy-saving comparing with the traditional point-to-point scheme. Sufficient conditions for output feedback control gain matrix, allowable length of sampling intervals, and upper bound of network-induced delays are derived to ensure the quantized synchronization of master-slave chaotic neural networks. Lastly, Chua's circuit system and 4-D Hopfield neural network are simulated to validate the effectiveness of the main results.In this paper, the synchronization problem of master-slave chaotic neural networks with remote sensors, quantization process, and communication time delays is investigated. The information communication channel between the master chaotic neural network and slave chaotic neural network consists of several remote sensors, with each sensor able to access only partial knowledge of output information of the master neural network. At each sampling instants, each sensor updates its own measurement and only one sensor is scheduled to transmit its latest information to the controller's side in order to update the control inputs for the slave neural network. Thus, such communication process and control strategy are much more energy-saving comparing with the traditional point-to-point scheme. Sufficient conditions for output feedback control gain matrix, allowable length of sampling intervals, and upper bound of network-induced delays are derived to ensure the quantized synchronization of master-slave chaotic neural networks. Lastly, Chua's circuit system and 4-D Hopfield neural network are simulated to validate the effectiveness of the main results.

Mechanisms for Prolonging Network Lifetime in Wireless Sensor Networks

ERIC Educational Resources Information Center

Yang, Yinying

2010-01-01

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

Building SDN-Based Agricultural Vehicular Sensor Networks Based on Extended Open vSwitch.

PubMed

Huang, Tao; Yan, Siyu; Yang, Fan; Pan, Tian; Liu, Jiang

2016-01-19

Software-defined vehicular sensor networks in agriculture, such as autonomous vehicle navigation based on wireless multi-sensor networks, can lead to more efficient precision agriculture. In SDN-based vehicle sensor networks, the data plane is simplified and becomes more efficient by introducing a centralized controller. However, in a wireless environment, the main controller node may leave the sensor network due to the dynamic topology change or the unstable wireless signal, leaving the rest of network devices without control, e.g., a sensor node as a switch may forward packets according to stale rules until the controller updates the flow table entries. To solve this problem, this paper proposes a novel SDN-based vehicular sensor networks architecture which can minimize the performance penalty of controller connection loss. We achieve this by designing a connection state detection and self-learning mechanism. We build prototypes based on extended Open vSwitch and Ryu. The experimental results show that the recovery time from controller connection loss is under 100 ms and it keeps rule updating in real time with a stable throughput. This architecture enhances the survivability and stability of SDN-based vehicular sensor networks in precision agriculture.

Building SDN-Based Agricultural Vehicular Sensor Networks Based on Extended Open vSwitch

PubMed Central

Huang, Tao; Yan, Siyu; Yang, Fan; Pan, Tian; Liu, Jiang

2016-01-01

Software-defined vehicular sensor networks in agriculture, such as autonomous vehicle navigation based on wireless multi-sensor networks, can lead to more efficient precision agriculture. In SDN-based vehicle sensor networks, the data plane is simplified and becomes more efficient by introducing a centralized controller. However, in a wireless environment, the main controller node may leave the sensor network due to the dynamic topology change or the unstable wireless signal, leaving the rest of network devices without control, e.g., a sensor node as a switch may forward packets according to stale rules until the controller updates the flow table entries. To solve this problem, this paper proposes a novel SDN-based vehicular sensor networks architecture which can minimize the performance penalty of controller connection loss. We achieve this by designing a connection state detection and self-learning mechanism. We build prototypes based on extended Open vSwitch and Ryu. The experimental results show that the recovery time from controller connection loss is under 100 ms and it keeps rule updating in real time with a stable throughput. This architecture enhances the survivability and stability of SDN-based vehicular sensor networks in precision agriculture. PMID:26797616

High capacity fiber optic sensor networks using hybrid multiplexing techniques and their applications

NASA Astrophysics Data System (ADS)

Sun, Qizhen; Li, Xiaolei; Zhang, Manliang; Liu, Qi; Liu, Hai; Liu, Deming

2013-12-01

Fiber optic sensor network is the development trend of fiber senor technologies and industries. In this paper, I will discuss recent research progress on high capacity fiber sensor networks with hybrid multiplexing techniques and their applications in the fields of security monitoring, environment monitoring, Smart eHome, etc. Firstly, I will present the architecture of hybrid multiplexing sensor passive optical network (HSPON), and the key technologies for integrated access and intelligent management of massive fiber sensor units. Two typical hybrid WDM/TDM fiber sensor networks for perimeter intrusion monitor and cultural relics security are introduced. Secondly, we propose the concept of "Microstructure－Optical X Domin Refecltor (M-OXDR)" for fiber sensor network expansion. By fabricating smart micro-structures with the ability of multidimensional encoded and low insertion loss along the fiber, the fiber sensor network of simple structure and huge capacity more than one thousand could be achieved. Assisted by the WDM/TDM and WDM/FDM decoding methods respectively, we built the verification systems for long-haul and real-time temperature sensing. Finally, I will show the high capacity and flexible fiber sensor network with IPv6 protocol based hybrid fiber/wireless access. By developing the fiber optic sensor with embedded IPv6 protocol conversion module and IPv6 router, huge amounts of fiber optic sensor nodes can be uniquely addressed. Meanwhile, various sensing information could be integrated and accessed to the Next Generation Internet.

New Sensor Technologies for Ocean Exploration and Observation

NASA Astrophysics Data System (ADS)

Manley, J. E.

2005-12-01

NOAA's Office of Ocean Exploration (OE) is an active supporter of new ocean technologies. Sensors, in particular, have been a focus of recent investments as have platforms that can support both dedicated voyages of discovery and Integrated Ocean Observing Systems (IOOS). Recent programs sponsored by OE have developed technical solutions that will be of use in sensor networks and in stand-alone ocean research programs. Particular projects include: 1) the Joint Environmental Science Initiative (JESI) a deployment of a highly flexible marine sensing system, in collaboration with NASA, that demonstrated a new paradigm for marine ecosystem monitoring. 2) the development and testing of an in situ marine mass spectrometer, via grant to the Woods Hole Oceanographic Institution (WHOI). This instrument has been designed to function at depths up to 5000 meters. 3) the evolution of glider AUVs for aerial deployment, through a grant to Webb Research Corporation. This program's goal is air certification for gliders, which will allow them to be operationally deployed from NAVOCEANO aircraft. 4) the development of new behaviors for the Autonomous Benthic Explorer (ABE) allowing it to anchor in place and await instructions, through a grant to WHOI. This will support the operational use of AUVs in observing system networks. 5) development of new sensors for AUVs through a National Ocean Partnership Program (NOPP) award to Rutgers Universty. This project will develop a Fluorescence Induction Relaxation (FIRe) System to measure biomass and integrate the instrument into an AUV glider. 6) an SBIR award for the development of anti-fouling technologies for solar panels and in situ sensors. This effort at Nanohmics Inc. is developing natural product antifoulants (NPA) in optical quality hard polymers. The technology and results of each of these projects are one component of OE's overall approach to technology research and development. OE's technology program represents the leading edge of NOAA investment in ocean sensors and tools that eventually will find application in mission areas such as IOOS. This "big picture" provides context for focused information on detailed results of OE investments. As NOAA increases its investments in IOOS, and related technologies, these projects are timely and should be beneficial to the entire environmental sensor network community.

Instrumental measurement of odour nuisance in city agglomeration using electronic nose

NASA Astrophysics Data System (ADS)

Szulczyński, Bartosz; Dymerski, Tomasz; Gębicki, Jacek; Namieśnik, Jacek

2018-01-01

The paper describes an operation principle of odour nuisance monitoring network in a city agglomeration. Moreover, it presents the results of investigation on ambient air quality with respect to odour obtained during six-month period. The investigation was carried out using a network comprised of six prototypes of electronic nose and Nasal Ranger field olfactometers employed as a reference method. The monitoring network consisted of two measurement stations localized in a vicinity of crude oil processing plant and four stations localized near the main emitters of volatile odorous compounds such as sewage treatment plant, municipal landfill, phosphatic fertilizer production plant. The electronic nose prototype was equipped with a set of six semiconductor sensors by FIGARO Co. and one PID-type sensor. The field olfactometers were utilized for determination of mean concentration of odorants and for calibration of the electronic nose prototypes in order to provide their proper operation. Mean monthly values of odour concentration depended on the site of measurement and on meteorological parameters. They were within 0 - 6.0 ou/m3 range. Performed investigations revealed the possibility of electronic nose instrument application as a tool for monitoring of odour nuisance.

Research Trends in Wireless Visual Sensor Networks When Exploiting Prioritization

PubMed Central

Costa, Daniel G.; Guedes, Luiz Affonso; Vasques, Francisco; Portugal, Paulo

2015-01-01

The development of wireless sensor networks for control and monitoring functions has created a vibrant investigation scenario, where many critical topics, such as communication efficiency and energy consumption, have been investigated in the past few years. However, when sensors are endowed with low-power cameras for visual monitoring, a new scope of challenges is raised, demanding new research efforts. In this context, the resource-constrained nature of sensor nodes has demanded the use of prioritization approaches as a practical mechanism to lower the transmission burden of visual data over wireless sensor networks. Many works in recent years have considered local-level prioritization parameters to enhance the overall performance of those networks, but global-level policies can potentially achieve better results in terms of visual monitoring efficiency. In this paper, we make a broad review of some recent works on priority-based optimizations in wireless visual sensor networks. Moreover, we envisage some research trends when exploiting prioritization, potentially fostering the development of promising optimizations for wireless sensor networks composed of visual sensors. PMID:25599425

DE-Sync: A Doppler-Enhanced Time Synchronization for Mobile Underwater Sensor Networks.

PubMed

Zhou, Feng; Wang, Qi; Nie, DongHu; Qiao, Gang

2018-05-25

Time synchronization is the foundation of cooperative work among nodes of underwater sensor networks; it takes a critical role in the research and application of underwater sensor networks. Although numerous time synchronization protocols have been proposed for terrestrial wireless sensor networks, they cannot be directly applied to underwater sensor networks. This is because most of them typically assume that the propagation delay among sensor nodes is negligible, which is not the case in underwater sensor networks. Time synchronization is mainly affected by a long propagation delay among sensor nodes due to the low propagation speed of acoustic signals. Furthermore, sensor nodes in underwater tend to experience some degree of mobility due to wind or ocean current, or some other nodes are on self-propelled vehicles, such as autonomous underwater vehicles (AUVs). In this paper, we propose a Doppler-enhanced time synchronization scheme for mobile underwater sensor networks, called DE-Sync. Our new scheme considers the effect of the clock skew during the process of estimating the Doppler scale factor and directly substitutes the Doppler scale factor into linear regression to achieve the estimation of the clock skew and offset. Simulation results show that DE-Sync outperforms existing time synchronization protocols in both accuracy and energy efficiency.

Bluetooth Roaming for Sensor Network System in Clinical Environment.

PubMed

Kuroda, Tomohiro; Noma, Haruo; Takase, Kazuhiko; Sasaki, Shigeto; Takemura, Tadamasa

2015-01-01

A sensor network is key infrastructure for advancing a hospital information system (HIS). The authors proposed a method to provide roaming functionality for Bluetooth to realize a Bluetooth-based sensor network, which is suitable to connect clinical devices. The proposed method makes the average response time of a Bluetooth connection less than one second by making the master device repeat the inquiry process endlessly and modifies parameters of the inquiry process. The authors applied the developed sensor network for daily clinical activities in an university hospital, and confirmed the stabilitya and effectiveness of the sensor network. As Bluetooth becomes a quite common wireless interface for medical devices, the proposed protocol that realizes Bluetooth-based sensor network enables HIS to equip various clinical devices and, consequently, lets information and communication technologies advance clinical services.

Integrating legacy medical data sensors in a wireless network infrastucture.

PubMed

Dembeyiotis, S; Konnis, G; Koutsouris, D

2005-01-01

In the process of developing a wireless networking solution to provide effective field-deployable communications and telemetry support for rescuers during major natural disasters, we are faced with the task of interfacing the multitude of medical and other legacy data collection sensors to the network grid. In this paper, we detail a number of solutions, with particular attention given to the issue of data security. The chosen implementation allows for sensor control and management from remote network locations, while the sensors can wirelessly transmit their data to nearby network nodes securely, utilizing the latest commercially available cryptography solutions. Initial testing validates the design choices, while the network-enabled sensors are being integrated in the overall wireless network security framework.

Open-WiSe: A Solar Powered Wireless Sensor Network Platform

PubMed Central

González, Apolinar; Aquino, Raúl; Mata, Walter; Ochoa, Alberto; Saldaña, Pedro; Edwards, Arthur

2012-01-01

Because battery-powered nodes are required in wireless sensor networks and energy consumption represents an important design consideration, alternate energy sources are needed to provide more effective and optimal function. The main goal of this work is to present an energy harvesting wireless sensor network platform, the Open Wireless Sensor node (WiSe). The design and implementation of the solar powered wireless platform is described including the hardware architecture, firmware, and a POSIX Real-Time Kernel. A sleep and wake up strategy was implemented to prolong the lifetime of the wireless sensor network. This platform was developed as a tool for researchers investigating Wireless sensor network or system integrators. PMID:22969396

A Study of Mesoscale Probability Forecasting Performance Based on an Advanced Image Display System.

DTIC Science & Technology

1984-04-30

CLASSIFICATION lb. RESTRICTIVE MARKINGS Uncl assified 2&. SECURITY CLASSIFICATION AUTHORITY 3. DISTRIBUTION/AVAI LABILITY OF REPORT 2b. DE CLASSI FICAT... sensors in the surface network, an air-to-ground lightning detection system, and NWS 6Brown, R. C., 1983: Anatomy of a nesoscale instrumentation system...W. B. Sweezy, R. G. Strauch, E. R. Westwater, and C. G. Little, 1983: An automatic Profiler of the temperatura , wind, and humidity in the troposphere

Assimilating Tropospheric Airborne Meteorological Data Reporting (TAMDAR) Observations and the Relative Value of Other Observation Types

DTIC Science & Technology

2014-08-01

Using real-time weather data from an unmanned aircraft system to support the advanced research version of the weather research and forecast model... system that is used to transmit some MDCRS observations, the Aircraft Communications Addressing and Reporting System (ACARS). A new network of aircraft ...Technical Analysis and Applications Center, and AirDat LLC developed a modified TAMDAR sensor referred to as TAMDAR- Unmanned Aerial System (TAMDAR-U) for

Watchdog Sensor Network with Multi-Stage RF Signal Identification and Cooperative Intrusion Detection

DTIC Science & Technology

2012-03-01

detection and physical layer authentication in mobile Ad Hoc networks and wireless sensor networks (WSNs) have been investigated. Résume Le rapport...IEEE 802.16 d and e (WiMAX); (b) IEEE 802.11 (Wi-Fi) family of a, b, g, n, and s (c) Sensor networks based on IEEE 802.15.4: Wireless USB, Bluetooth... sensor network are investigated for standard compatible wireless signals. The proposed signal existence detection and identification process consists

Source Localization Using Wireless Sensor Networks

DTIC Science & Technology

2006-06-01

performance of the hybrid SI/ML estimation method. A wireless sensor network is simulated in NS-2 to study the network throughput, delay and jitter...indicate that the wireless sensor network has low delay and can support fast information exchange needed in counter-sniper applications.

A survey on bio inspired meta heuristic based clustering protocols for wireless sensor networks

NASA Astrophysics Data System (ADS)

Datta, A.; Nandakumar, S.

2017-11-01

Recent studies have shown that utilizing a mobile sink to harvest and carry data from a Wireless Sensor Network (WSN) can improve network operational efficiency as well as maintain uniform energy consumption by the sensor nodes in the network. Due to Sink mobility, the path between two sensor nodes continuously changes and this has a profound effect on the operational longevity of the network and a need arises for a protocol which utilizes minimal resources in maintaining routes between the mobile sink and the sensor nodes. Swarm Intelligence based techniques inspired by the foraging behavior of ants, termites and honey bees can be artificially simulated and utilized to solve real wireless network problems. The author presents a brief survey on various bio inspired swarm intelligence based protocols used in routing data in wireless sensor networks while outlining their general principle and operation.

Investigation of the spatial variability and possible origins of wind-induced air pressure fluctuations responsible for pressure pumping

NASA Astrophysics Data System (ADS)

Mohr, Manuel; Laemmel, Thomas; Maier, Martin; Zeeman, Matthias; Longdoz, Bernard; Schindler, Dirk

2017-04-01

The exchange of greenhouse gases between the soil and the atmosphere is highly relevant for the climate of the Earth. Recent research suggests that wind-induced air pressure fluctuations can alter the soil gas transport and therefore soil gas efflux significantly. Using a newly developed method, we measured soil gas transport in situ in a well aerated forest soil. Results from these measurements showed that the commonly used soil gas diffusion coefficient is enhanced up to 30% during periods of strong wind-induced air pressure fluctuations. The air pressure fluctuations above the forest floor are only induced at high above-canopy wind speeds (> 5 m s-1) and lie in the frequency range 0.01-0.1 Hz. Moreover, the amplitudes of air pressure fluctuations in this frequency range show a clear quadratic dependence on mean above-canopy wind speed. However, the origin of these wind-induced pressure fluctuations is still unclear. Airflow measurements and high-precision air pressure measurements were conducted at three different vegetation-covered sites (conifer forest, deciduous forest, grassland) to investigate the spatial variability of dominant air pressure fluctuations, their origin and vegetation-dependent characteristics. At the conifer forest site, a vertical profile of air pressure fluctuations was measured and an array consisting of five pressure sensors were installed at the forest floor. At the grassland site, the air pressure measurements were compared with wind observations made by ground-based LIDAR and spatial temperature observations from a fibre-optic sensing network (ScaleX Campaign 2016). Preliminary results show that at all sites the amplitudes of relevant air pressure fluctuations increase with increasing wind speed. Data from the array measurements reveal that there are no time lags between the air pressure signals of different heights, but a time lag existed between the air pressure signals of the sensors distributed laterally on the forest floor, suggesting a horizontal propagation of the air pressure waves.

LWT Based Sensor Node Signal Processing in Vehicle Surveillance Distributed Sensor Network

NASA Astrophysics Data System (ADS)

Cha, Daehyun; Hwang, Chansik

Previous vehicle surveillance researches on distributed sensor network focused on overcoming power limitation and communication bandwidth constraints in sensor node. In spite of this constraints, vehicle surveillance sensor node must have signal compression, feature extraction, target localization, noise cancellation and collaborative signal processing with low computation and communication energy dissipation. In this paper, we introduce an algorithm for light-weight wireless sensor node signal processing based on lifting scheme wavelet analysis feature extraction in distributed sensor network.

Probabilistic QoS Analysis In Wireless Sensor Networks

DTIC Science & Technology

2012-04-01

and A.O. Fapojuwo. TDMA scheduling with optimized energy efficiency and minimum delay in clustered wireless sensor networks . IEEE Trans. on Mobile...Research Computer Science and Engineering, Department of 5-1-2012 Probabilistic QoS Analysis in Wireless Sensor Networks Yunbo Wang University of...Wang, Yunbo, "Probabilistic QoS Analysis in Wireless Sensor Networks " (2012). Computer Science and Engineering: Theses, Dissertations, and Student

RF Characteristics of Mica-Z Wireless Sensor Network Motes

DTIC Science & Technology

2006-03-01

MICA-Z WIRELESS SENSOR NETWORK MOTES by Swee Jin Koh March 2006 Thesis Advisor: Gurminder Singh Thesis Co-Advisor: John C...Mica-Z Wireless Sensor Network Motes 6. AUTHOR(S) : Swee Jin Koh 5. FUNDING NUMBERS 7. PERFORMING ORGANIZATION NAME(S) AND ADDRESS(ES) Naval...ad-hoc deployment. 15. NUMBER OF PAGES 83 14. SUBJECT TERMS: Wireless Sensor Network 16. PRICE CODE 17. SECURITY CLASSIFICATION OF

Path Calculation and Packet Translation for UAV Surveillance in Support of Wireless Sensor Networks

DTIC Science & Technology

2006-09-01

AND PACKET TRANSLATION FOR UAV SURVEILLANCE IN SUPPORT OF WIRELESS SENSOR NETWORKS by Stephen Schall September 2006 Thesis Advisor...Calculation and Packet Translation for UAV Surveillance in Support of Wireless Sensor Networks 6. AUTHOR(S) Stephen Schall 5. FUNDING NUMBERS 7...200 words) Wireless Sensor Networks (WSNs) are a relatively new technology with many potential applications, including military and

Wireless Sensor Network With Geolocation

DTIC Science & Technology

2006-11-01

WIRELESS SENSOR NETWORK WITH GEOLOCATION James Silverstrim and Roderick Passmore Innovative Wireless Technologies Forest, VA 24551 Dr...TYPE N/A 3. DATES COVERED - 4. TITLE AND SUBTITLE Wireless Sensor Network With Geolocation 5a. CONTRACT NUMBER 5b. GRANT NUMBER 5c. PROGRAM...Locationing in distributed ad-hoc wireless sensor networks ”, IEEE ICASSP, May 2001. D. W. Hanson, Fundamentals of Two-Way Time Transfer by Satellite

Performance Evaluation of a Routing Protocol in Wireless Sensor Network

DTIC Science & Technology

2005-12-01

OF A ROUTING PROTOCOL IN WIRELESS SENSOR NETWORKS by Cheng Kiat Amos, Teo December 2005 Thesis Advisors: Gurminder Singh John C...Evaluation of a Routing Protocol in Wireless Sensor Network 6. AUTHOR(S) Cheng Kiat Amos, Teo 5. FUNDING NUMBERS 7. PERFORMING ORGANIZATION NAME(S...need to be strategically positioned and have topologies engineered. As such, recent research into wireless sensor networks has attracted great

Source Localization in Wireless Sensor Networks with Randomly Distributed Elements under Multipath Propagation Conditions

DTIC Science & Technology

2009-03-01

IN WIRELESS SENSOR NETWORKS WITH RANDOMLY DISTRIBUTED ELEMENTS UNDER MULTIPATH PROPAGATION CONDITIONS by Georgios Tsivgoulis March 2009...COVERED Engineer’s Thesis 4. TITLE Source Localization in Wireless Sensor Networks with Randomly Distributed Elements under Multipath Propagation...the non-line-of-sight information. 15. NUMBER OF PAGES 111 14. SUBJECT TERMS Wireless Sensor Network , Direction of Arrival, DOA, Random

Networked sensors for the combat forces

NASA Astrophysics Data System (ADS)

Klager, Gene

2004-11-01

Real-time and detailed information is critical to the success of ground combat forces. Current manned reconnaissance, surveillance, and target acquisition (RSTA) capabilities are not sufficient to cover battlefield intelligence gaps, provide Beyond-Line-of-Sight (BLOS) targeting, and the ambush avoidance information necessary for combat forces operating in hostile situations, complex terrain, and conducting military operations in urban terrain. This paper describes a current US Army program developing advanced networked unmanned/unattended sensor systems to survey these gaps and provide the Commander with real-time, pertinent information. Networked Sensors for the Combat Forces plans to develop and demonstrate a new generation of low cost distributed unmanned sensor systems organic to the RSTA Element. Networked unmanned sensors will provide remote monitoring of gaps, will increase a unit"s area of coverage, and will provide the commander organic assets to complete his Battlefield Situational Awareness (BSA) picture for direct and indirect fire weapons, early warning, and threat avoidance. Current efforts include developing sensor packages for unmanned ground vehicles, small unmanned aerial vehicles, and unattended ground sensors using advanced sensor technologies. These sensors will be integrated with robust networked communications and Battle Command tools for mission planning, intelligence "reachback", and sensor data management. The network architecture design is based on a model that identifies a three-part modular design: 1) standardized sensor message protocols, 2) Sensor Data Management, and 3) Service Oriented Architecture. This simple model provides maximum flexibility for data exchange, information management and distribution. Products include: Sensor suites optimized for unmanned platforms, stationary and mobile versions of the Sensor Data Management Center, Battle Command planning tools, networked communications, and sensor management software. Details of these products and recent test results will be presented.

Air Force Research Laboratory Sensors Directorate Leadership Legacy, 1960-2011

DTIC Science & Technology

2011-03-01

AFRL -RY-WP-TM-2011-1017 AIR FORCE RESEARCH LABORATORY SENSORS DIRECTORATE LEADERSHIP LEGACY, 1960-2011 Compiled by Raymond C. Rang...Structures Divi- sion, Space Vehicles Directorate, Air Force Research Laboratory , Kirtland AFB, N.M. 7. March 1998 - July 1999, Chief, Integration and... Research Laboratory ( AFRL ), and Deputy Director of the Sensors Direc- torate, Air Force Research

Underwater Sensor Network Redeployment Algorithm Based on Wolf Search

PubMed Central

Jiang, Peng; Feng, Yang; Wu, Feng

2016-01-01

This study addresses the optimization of node redeployment coverage in underwater wireless sensor networks. Given that nodes could easily become invalid under a poor environment and the large scale of underwater wireless sensor networks, an underwater sensor network redeployment algorithm was developed based on wolf search. This study is to apply the wolf search algorithm combined with crowded degree control in the deployment of underwater wireless sensor networks. The proposed algorithm uses nodes to ensure coverage of the events, and it avoids the prematurity of the nodes. The algorithm has good coverage effects. In addition, considering that obstacles exist in the underwater environment, nodes are prevented from being invalid by imitating the mechanism of avoiding predators. Thus, the energy consumption of the network is reduced. Comparative analysis shows that the algorithm is simple and effective in wireless sensor network deployment. Compared with the optimized artificial fish swarm algorithm, the proposed algorithm exhibits advantages in network coverage, energy conservation, and obstacle avoidance. PMID:27775659

Development and deployment of a low-cost, mobile-ready, air quality sensor system: progress toward distributed networks and autonomous aerial sampling

NASA Astrophysics Data System (ADS)

Hersey, S. P.; DiVerdi, R.; Gadtaula, P.; Sheneman, T.; Flores, K.; Chen, Y. H.; Jayne, J. T.; Cross, E. S.

2017-12-01

Throughout the 2016-2017 academic year, a new partnership between Olin College of Engineering and Aerodyne Research, Inc. developed an affordable, self-contained air quality monitoring instrument called Modulair. The Modulair instrument is based on the same operating principles as Aerodyne's newly-developed ARISense integrated sensor system, employing electrochemical sensors for gas-phase measurements of CO, NO, NO2, and O3 and an off-the-shelf optical particle counter for particle concentration, number, and size distribution information (0.4 < dp < 17 microns). High Dimensional Model Representation (HDMR) has been used to model the interference derived from relative humidity and temperature as well as the cross-sensitivity of the electrochemical sensors to non-target gas-phase species. The aim of the modeling effort is to provide transparent and robust calibration of electrical signals to pollutant concentrations from a set of electrochemical sensors. Modulair was designed from the ground-up, with custom electronics - including a more powerful microcontroller, a fully re-designed housing and a device-specific backend with a mobile, cloud-based data management system for real-time data posting and analysis. Open source tools and software were utilized in the development of the instrument. All initial work was completed by a team of undergraduate students as part of the Senior Capstone Program in Engineering (SCOPE) at Olin College. Deployment strategies for Modulair include distributed, mobile measurements and drone-based aerial sampling. Design goals for the drone integration include maximizing airborne sampling time and laying the foundation for software integration with the drone's autopilot system to allow for autonomous plume sampling across concentration gradients. Modulair and its flexible deployments enable real-time mapping of air quality data at exposure-relevant spatial scales, as well as regular, autonomous characterization of sources and dispersion of atmospheric pollutants. We will present an overview of the Modulair instrument and results from benchtop and field validation, including mobile and drone-based plume sampling in the Boston area.

Fully wireless pressure sensor based on endoscopy images

NASA Astrophysics Data System (ADS)

Maeda, Yusaku; Mori, Hirohito; Nakagawa, Tomoaki; Takao, Hidekuni

2018-04-01

In this paper, the result of developing a fully wireless pressure sensor based on endoscopy images for an endoscopic surgery is reported for the first time. The sensor device has structural color with a nm-scale narrow gap, and the gap is changed by air pressure. The structural color of the sensor is acquired from camera images. Pressure detection can be realized with existing endoscope configurations only. The inner air pressure of the human body should be measured under flexible-endoscope operation using the sensor. Air pressure monitoring, has two important purposes. The first is to quantitatively measure tumor size under a constant air pressure for treatment selection. The second purpose is to prevent the endangerment of a patient due to over transmission of air. The developed sensor was evaluated, and the detection principle based on only endoscopy images has been successfully demonstrated.

Design of a sensor network for structural health monitoring of a full-scale composite horizontal tail

NASA Astrophysics Data System (ADS)

Gao, Dongyue; Wang, Yishou; Wu, Zhanjun; Rahim, Gorgin; Bai, Shengbao

2014-05-01

The detection capability of a given structural health monitoring (SHM) system strongly depends on its sensor network placement. In order to minimize the number of sensors while maximizing the detection capability, optimal design of the PZT sensor network placement is necessary for structural health monitoring (SHM) of a full-scale composite horizontal tail. In this study, the sensor network optimization was simplified as a problem of determining the sensor array placement between stiffeners to achieve the desired the coverage rate. First, an analysis of the structural layout and load distribution of a composite horizontal tail was performed. The constraint conditions of the optimal design were presented. Then, the SHM algorithm of the composite horizontal tail under static load was proposed. Based on the given SHM algorithm, a sensor network was designed for the full-scale composite horizontal tail structure. Effective profiles of cross-stiffener paths (CRPs) and uncross-stiffener paths (URPs) were estimated by a Lamb wave propagation experiment in a multi-stiffener composite specimen. Based on the coverage rate and the redundancy requirements, a seven-sensor array-network was chosen as the optimal sensor network for each airfoil. Finally, a preliminary SHM experiment was performed on a typical composite aircraft structure component. The reliability of the SHM result for a composite horizontal tail structure under static load was validated. In the result, the red zone represented the delamination damage. The detection capability of the optimized sensor network was verified by SHM of a full-scale composite horizontal tail; all the diagnosis results were obtained in two minutes. The result showed that all the damage in the monitoring region was covered by the sensor network.

GEODIS: A Portable Ocean Bottom Very Broadband Seismic Station

NASA Astrophysics Data System (ADS)

KARCZEWSKI, J.; MONTAGNER, J.; BEGUERY, L.; STUTZMANN, E.; ROULT, G.; LOGNONNE, P.; CACHO, S.; KOENIG, J.; SAVARY, J.

2001-12-01

The last ten years have seen the simultaneous development of a global seismic network coordinated through the FDSN (Federation of Digital Seismograph Networks) and of portable broadband seismic arrays. The same approach can be followed for improving our scientific understanding of the Earth processes below oceanic areas. Both components of ocean bottom geophysical networks, will be coordinated by ION (international Ocean Network). They are complementary since they enable to investigate the Earth structure and processes at different spatial and temporal scales. Geophysical Ocean bottom observatories (hereafter referred as GOBO) and portable seismic stations are sharing common technological problems. However, the issues of power supply and real-time data transmission are more crucial for a GOBO than for a portable temporary station. Since 1999, our group is developing a new "portable" geophysical ocean bottom autonomous station, named GEODIS. This station might be a basic element for a GOBO. It relies on the use of adapted VBB sensors issued from space experiments and technology and on improved electronics compared with previous ocean bottom experiments (SISMOBS/OFM 1992; MOISE 1997). The main characteristics of GEODIS are the following: - 3 axes VBB seismic sensors with a classical flat velocity response 360-0.2s. at 2500V/m/s (intrinsic noise level smaller than LNM). - Automatic (under software control) installation, levelling, centring of the 3 component seismic sensors. - 24 bit digitiser recording at 20sps, 3 seismic component and 1 infrasonic sensor. - Recording by a 16 bit converter at 1sps of the sea temperature in the vicinity of the instrument and housekeeping parameters (temperature, inclinations, power,...). - 1 year autonomy by using Lithium batteries. - Storage of data on Flash card and recording on hard disk every day. - Weight of GEODIS: 186kg in air and 110kg in water. - Overall dimensions: 930 x 930 x 440 mm. GEODIS can be easily installed by a small oceanographic vessel. Therefore, GEODIS has been designed in order to be reliable, with a low power consumption, to be financially affordable, to have excellent performances of sensors, to be easy to install and to recover.

#2) Sensor Technology-State of the Science | Science ...

EPA Pesticide Factsheets

Establish market surveys of commercially-available air quality sensorsConduct an extensive literature survey describing the state of sensor technologiesInvestigate emerging technologies and their potential to meet future air quality monitoring needs for the Agency as well as other partners/stakeholders Develop sensor user guidesEducate sensor developers/sensors users on the state of low cost censorsFacilitate knowledge transfer to Federal/Regional/State air quality associatesWork directly with sensor developers to dramatically speed up the development of next generation air monitoring Support ORD’s Sensor Roadmap by focusing on areas of highest priority (NAAQS, Air Toxics, Citizen Science)Establish highly integrated research efforts across ORD and its partners (internal/external) to ensure consistent The National Exposure Research Laboratory (NERL) Human Exposure and Atmospheric Sciences Division (HEASD) conducts research in support of EPA mission to protect human health and the environment. HEASD research program supports Goal 1 (Clean Air) and Goal 4 (Healthy People) of EPA strategic plan. More specifically, our division conducts research to characterize the movement of pollutants from the source to contact with humans. Our multidisciplinary research program produces Methods, Measurements, and Models to identify relationships between and characterize processes that link source emissions, environmental concentrations, human exposures, and target-tissue dose.

Active Self-Testing Noise Measurement Sensors for Large-Scale Environmental Sensor Networks

PubMed Central

Domínguez, Federico; Cuong, Nguyen The; Reinoso, Felipe; Touhafi, Abdellah; Steenhaut, Kris

2013-01-01

Large-scale noise pollution sensor networks consist of hundreds of spatially distributed microphones that measure environmental noise. These networks provide historical and real-time environmental data to citizens and decision makers and are therefore a key technology to steer environmental policy. However, the high cost of certified environmental microphone sensors render large-scale environmental networks prohibitively expensive. Several environmental network projects have started using off-the-shelf low-cost microphone sensors to reduce their costs, but these sensors have higher failure rates and produce lower quality data. To offset this disadvantage, we developed a low-cost noise sensor that actively checks its condition and indirectly the integrity of the data it produces. The main design concept is to embed a 13 mm speaker in the noise sensor casing and, by regularly scheduling a frequency sweep, estimate the evolution of the microphone's frequency response over time. This paper presents our noise sensor's hardware and software design together with the results of a test deployment in a large-scale environmental network in Belgium. Our middle-range-value sensor (around €50) effectively detected all experienced malfunctions, in laboratory tests and outdoor deployments, with a few false positives. Future improvements could further lower the cost of our sensor below €10. PMID:24351634

Real-Time Environmental Sensors to Improve Health in the Sensing City

NASA Astrophysics Data System (ADS)

Marek, L.; Campbell, M.; Epton, M.; Storer, M.; Kingham, S.

2016-06-01

The opportunity of an emerging smart city in post-disaster Christchurch has been explored as a way to improve the quality of life of people suffering Chronic Obstructive Pulmonary Disease (COPD), which is a progressive disease that affects respiratory function. It affects 1 in 15 New Zealanders and is the 4th largest cause of death, with significant costs to the health system. While, cigarette smoking is the leading cause of COPD, long-term exposure to other lung irritants, such as air pollution, chemical fumes, or dust can also cause and exacerbate it. Currently, we do know little what happens to the patients with COPD after they leave a doctor's care. By learning more about patients' movements in space and time, we can better understand the impacts of both the environment and personal mobility on the disease. This research is studying patients with COPD by using GPS-enabled smartphones, combined with the data about their spatiotemporal movements and information about their actual usage of medication in near real-time. We measure environmental data in the city, including air pollution, humidity and temperature and how this may subsequently be associated with COPD symptoms. In addition to the existing air quality monitoring network, to improve the spatial scale of our analysis, we deployed a series of low-cost Internet of Things (IoT) air quality sensors as well. The study demonstrates how health devices, smartphones and IoT sensors are becoming a part of a new health data ecosystem and how their usage could provide information about high-risk health hotspots, which, in the longer term, could lead to improvement in the quality of life for patients with COPD.

Robust Networking Architecture and Secure Communication Scheme for Heterogeneous Wireless Sensor Networks

ERIC Educational Resources Information Center

McNeal, McKenzie, III.

2012-01-01

Current networking architectures and communication protocols used for Wireless Sensor Networks (WSNs) have been designed to be energy efficient, low latency, and long network lifetime. One major issue that must be addressed is the security in data communication. Due to the limited capabilities of low cost and small sized sensor nodes, designing…

Wireless Cooperative Networks: Self-Configuration and Optimization

DTIC Science & Technology

2011-09-09

TERMS wireless sensor networks , wireless cooperative networks, resource optimization, ultra-wideband, localization, ranging 16. SECURITY...Communications We consider two prevalent relay protocols for wireless sensor networks : decode-and-forward (DF) and amplify-and-forward (AF). To... sensor networks where each node may have its own sensing data to transmit, since they can maximally conserve energy while helping others as relays

A Survey on Security and Privacy in Emerging Sensor Networks: From Viewpoint of Close-Loop.

PubMed

Zhang, Lifu; Zhang, Heng

2016-03-26

Nowadays, as the next generation sensor networks, Cyber-Physical Systems (CPSs) refer to the complex networked systems that have both physical subsystems and cyber components, and the information flow between different subsystems and components is across a communication network, which forms a closed-loop. New generation sensor networks are found in a growing number of applications and have received increasing attention from many inter-disciplines. Opportunities and challenges in the design, analysis, verification and validation of sensor networks co-exists, among which security and privacy are two important ingredients. This paper presents a survey on some recent results in the security and privacy aspects of emerging sensor networks from the viewpoint of the closed-loop. This paper also discusses several future research directions under these two umbrellas.

Autonomous distributed self-organization for mobile wireless sensor networks.

PubMed

Wen, Chih-Yu; Tang, Hung-Kai

2009-01-01

This paper presents an adaptive combined-metrics-based clustering scheme for mobile wireless sensor networks, which manages the mobile sensors by utilizing the hierarchical network structure and allocates network resources efficiently A local criteria is used to help mobile sensors form a new cluster or join a current cluster. The messages transmitted during hierarchical clustering are applied to choose distributed gateways such that communication for adjacent clusters and distributed topology control can be achieved. In order to balance the load among clusters and govern the topology change, a cluster reformation scheme using localized criterions is implemented. The proposed scheme is simulated and analyzed to abstract the network behaviors in a number of settings. The experimental results show that the proposed algorithm provides efficient network topology management and achieves high scalability in mobile sensor networks.

A Low-Power Thermal-Based Sensor System for Low Air Flow Detection

PubMed Central

Arifuzzman, AKM; Haider, Mohammad Rafiqul; Allison, David B.

2016-01-01

Being able to rapidly detect a low air flow rate with high accuracy is essential for various applications in the automotive and biomedical industries. We have developed a thermal-based low air flow sensor with a low-power sensor readout for biomedical applications. The thermal-based air flow sensor comprises a heater and three pairs of temperature sensors that sense temperature differences due to laminar air flow. The thermal-based flow sensor was designed and simulated by using laminar flow, heat transfer in solids and fluids physics in COMSOL MultiPhysics software. The proposed sensor can detect air flow as low as 0.0064 m/sec. The readout circuit is based on a current- controlled ring oscillator in which the output frequency of the ring oscillator is proportional to the temperature differences of the sensors. The entire readout circuit was designed and simulated by using a 130-nm standard CMOS process. The sensor circuit features a small area and low-power consumption of about 22.6 µW with an 800 mV power supply. In the simulation, the output frequency of the ring oscillator and the change in thermistor resistance showed a high linearity with an R2 value of 0.9987. The low-power dissipation, high linearity and small dimensions of the proposed flow sensor and circuit make the system highly suitable for biomedical applications. PMID:28435186

A low-cost sensing system for cooperative air quality monitoring in urban areas.

PubMed

Brienza, Simone; Galli, Andrea; Anastasi, Giuseppe; Bruschi, Paolo

2015-05-26

Air quality in urban areas is a very important topic as it closely affects the health of citizens. Recent studies highlight that the exposure to polluted air can increase the incidence of diseases and deteriorate the quality of life. Hence, it is necessary to develop tools for real-time air quality monitoring, so as to allow appropriate and timely decisions. In this paper, we present uSense, a low-cost cooperative monitoring tool that allows knowing, in real-time, the concentrations of polluting gases in various areas of the city. Specifically, users monitor the areas of their interest by deploying low-cost and low-power sensor nodes. In addition, they can share the collected data following a social networking approach. uSense has been tested through an in-field experimentation performed in different areas of a city. The obtained results are in line with those provided by the local environmental control authority and show that uSense can be profitably used for air quality monitoring.

A novel proposal of GPON-oriented fiber grating sensing data digitalization system for remote sensing network

NASA Astrophysics Data System (ADS)

Wang, Yubao; Zhu, Zhaohui; Wang, Lu; Bai, Jian

2016-05-01

A novel GPON-oriented sensing data digitalization system is proposed to achieve remote monitoring of fiber grating sensing networks utilizing existing optical communication networks in some harsh environments. In which, Quick digitalization of sensing information obtained from the reflected lightwaves by fiber Bragg grating (FBG) sensor is realized, and a novel frame format of sensor signal is designed to suit for public transport so as to facilitate sensor monitoring center to receive and analyze the sensor data. The delay effect, identification method of the sensor data, and various interference factors which influence the sensor data to be correctly received are analyzed. The system simulation is carried out with OptiSystem/Matlab co-simulation approach. The theoretical analysis and simulation results verify the feasibility of the integration of the sensor network and communication network.

Distributed Detection with Collisions in a Random, Single-Hop Wireless Sensor Network

DTIC Science & Technology

2013-05-26

public release; distribution is unlimited. Distributed detection with collisions in a random, single-hop wireless sensor network The views, opinions...1274 2 ABSTRACT Distributed detection with collisions in a random, single-hop wireless sensor network Report Title We consider the problem of... WIRELESS SENSOR NETWORK Gene T. Whipps?† Emre Ertin† Randolph L. Moses† ?U.S. Army Research Laboratory, Adelphi, MD 20783 †The Ohio State University

A Study on Wireless Charging for Prolonging the Lifetime of Wireless Sensor Networks.

PubMed

Tu, Weijian; Xu, Xianghua; Ye, Tingcong; Cheng, Zongmao

2017-07-04

Wireless charging is an important issue in wireless sensor networks, since it can provide an emerging and effective solution in the absence of other power supplies. The state-of-the-art methods employ a mobile car and a predefined moving path to charge the sensor nodes in the network. Previous studies only consider a factor of the network (i.e., residual energy of sensor node) as a constraint to design the wireless charging strategy. However, other factors, such as the travelled distance of the mobile car, can also affect the effectiveness of wireless charging strategy. In this work, we study wireless charging strategy based on the analysis of a combination of two factors, including the residual energy of sensor nodes and the travelled distance of the charging car. Firstly, we theoretically analyze the limited size of the sensor network to match the capability of a charging car. Then, the networked factors are selected as the weights of traveling salesman problem (TSP) to design the moving path of the charging car. Thirdly, the charging time of each sensor node is computed based on the linear programming problem for the charging car. Finally, a charging period for the network is studied. The experimental results show that the proposed approach can significantly maximize the lifetime of the wireless sensor network.

Design and evaluation of a wireless sensor network based aircraft strength testing system.

PubMed

Wu, Jian; Yuan, Shenfang; Zhou, Genyuan; Ji, Sai; Wang, Zilong; Wang, Yang

2009-01-01

The verification of aerospace structures, including full-scale fatigue and static test programs, is essential for structure strength design and evaluation. However, the current overall ground strength testing systems employ a large number of wires for communication among sensors and data acquisition facilities. The centralized data processing makes test programs lack efficiency and intelligence. Wireless sensor network (WSN) technology might be expected to address the limitations of cable-based aeronautical ground testing systems. This paper presents a wireless sensor network based aircraft strength testing (AST) system design and its evaluation on a real aircraft specimen. In this paper, a miniature, high-precision, and shock-proof wireless sensor node is designed for multi-channel strain gauge signal conditioning and monitoring. A cluster-star network topology protocol and application layer interface are designed in detail. To verify the functionality of the designed wireless sensor network for strength testing capability, a multi-point WSN based AST system is developed for static testing of a real aircraft undercarriage. Based on the designed wireless sensor nodes, the wireless sensor network is deployed to gather, process, and transmit strain gauge signals and monitor results under different static test loads. This paper shows the efficiency of the wireless sensor network based AST system, compared to a conventional AST system.

Design and Evaluation of a Wireless Sensor Network Based Aircraft Strength Testing System

PubMed Central

Wu, Jian; Yuan, Shenfang; Zhou, Genyuan; Ji, Sai; Wang, Zilong; Wang, Yang

2009-01-01

The verification of aerospace structures, including full-scale fatigue and static test programs, is essential for structure strength design and evaluation. However, the current overall ground strength testing systems employ a large number of wires for communication among sensors and data acquisition facilities. The centralized data processing makes test programs lack efficiency and intelligence. Wireless sensor network (WSN) technology might be expected to address the limitations of cable-based aeronautical ground testing systems. This paper presents a wireless sensor network based aircraft strength testing (AST) system design and its evaluation on a real aircraft specimen. In this paper, a miniature, high-precision, and shock-proof wireless sensor node is designed for multi-channel strain gauge signal conditioning and monitoring. A cluster-star network topology protocol and application layer interface are designed in detail. To verify the functionality of the designed wireless sensor network for strength testing capability, a multi-point WSN based AST system is developed for static testing of a real aircraft undercarriage. Based on the designed wireless sensor nodes, the wireless sensor network is deployed to gather, process, and transmit strain gauge signals and monitor results under different static test loads. This paper shows the efficiency of the wireless sensor network based AST system, compared to a conventional AST system. PMID:22408521

An Outline of Data Aggregation Security in Heterogeneous Wireless Sensor Networks.

PubMed

Boubiche, Sabrina; Boubiche, Djallel Eddine; Bilami, Azzedine; Toral-Cruz, Homero

2016-04-12

Data aggregation processes aim to reduce the amount of exchanged data in wireless sensor networks and consequently minimize the packet overhead and optimize energy efficiency. Securing the data aggregation process is a real challenge since the aggregation nodes must access the relayed data to apply the aggregation functions. The data aggregation security problem has been widely addressed in classical homogeneous wireless sensor networks, however, most of the proposed security protocols cannot guarantee a high level of security since the sensor node resources are limited. Heterogeneous wireless sensor networks have recently emerged as a new wireless sensor network category which expands the sensor nodes' resources and capabilities. These new kinds of WSNs have opened new research opportunities where security represents a most attractive area. Indeed, robust and high security level algorithms can be used to secure the data aggregation at the heterogeneous aggregation nodes which is impossible in classical homogeneous WSNs. Contrary to the homogeneous sensor networks, the data aggregation security problem is still not sufficiently covered and the proposed data aggregation security protocols are numberless. To address this recent research area, this paper describes the data aggregation security problem in heterogeneous wireless sensor networks and surveys a few proposed security protocols. A classification and evaluation of the existing protocols is also introduced based on the adopted data aggregation security approach.

A Survey on Virtualization of Wireless Sensor Networks

PubMed Central

Islam, Md. Motaharul; Hassan, Mohammad Mehedi; Lee, Ga-Won; Huh, Eui-Nam

2012-01-01

Wireless Sensor Networks (WSNs) are gaining tremendous importance thanks to their broad range of commercial applications such as in smart home automation, health-care and industrial automation. In these applications multi-vendor and heterogeneous sensor nodes are deployed. Due to strict administrative control over the specific WSN domains, communication barriers, conflicting goals and the economic interests of different WSN sensor node vendors, it is difficult to introduce a large scale federated WSN. By allowing heterogeneous sensor nodes in WSNs to coexist on a shared physical sensor substrate, virtualization in sensor network may provide flexibility, cost effective solutions, promote diversity, ensure security and increase manageability. This paper surveys the novel approach of using the large scale federated WSN resources in a sensor virtualization environment. Our focus in this paper is to introduce a few design goals, the challenges and opportunities of research in the field of sensor network virtualization as well as to illustrate a current status of research in this field. This paper also presents a wide array of state-of-the art projects related to sensor network virtualization. PMID:22438759

A survey on virtualization of Wireless Sensor Networks.

PubMed

Islam, Md Motaharul; Hassan, Mohammad Mehedi; Lee, Ga-Won; Huh, Eui-Nam

2012-01-01

Wireless Sensor Networks (WSNs) are gaining tremendous importance thanks to their broad range of commercial applications such as in smart home automation, health-care and industrial automation. In these applications multi-vendor and heterogeneous sensor nodes are deployed. Due to strict administrative control over the specific WSN domains, communication barriers, conflicting goals and the economic interests of different WSN sensor node vendors, it is difficult to introduce a large scale federated WSN. By allowing heterogeneous sensor nodes in WSNs to coexist on a shared physical sensor substrate, virtualization in sensor network may provide flexibility, cost effective solutions, promote diversity, ensure security and increase manageability. This paper surveys the novel approach of using the large scale federated WSN resources in a sensor virtualization environment. Our focus in this paper is to introduce a few design goals, the challenges and opportunities of research in the field of sensor network virtualization as well as to illustrate a current status of research in this field. This paper also presents a wide array of state-of-the art projects related to sensor network virtualization.

Ambient and laboratory evaluation of a low-cost particulate matter sensor.

PubMed

Kelly, K E; Whitaker, J; Petty, A; Widmer, C; Dybwad, A; Sleeth, D; Martin, R; Butterfield, A

2017-02-01

Low-cost, light-scattering-based particulate matter (PM) sensors are becoming more widely available and are being increasingly deployed in ambient and indoor environments because of their low cost and ability to provide high spatial and temporal resolution PM information. Researchers have begun to evaluate some of these sensors under laboratory and environmental conditions. In this study, a low-cost, particulate matter sensor (Plantower PMS 1003/3003) used by a community air-quality network is evaluated in a controlled wind-tunnel environment and in the ambient environment during several winter-time, cold-pool events that are associated with high ambient levels of PM. In the wind-tunnel, the PMS sensor performance is compared to two research-grade, light-scattering instruments, and in the ambient tests, the sensor performance is compared to two federal equivalent (one tapered element oscillating microbalance and one beta attenuation monitor) and gravimetric federal reference methods (FEMs/FRMs) as well as one research-grade instrument (GRIMM). The PMS sensor response correlates well with research-grade instruments in the wind-tunnel tests, and its response is linear over the concentration range tested (200-850 μg/m 3 ). In the ambient tests, this PM sensor correlates better with gravimetric methods than previous studies with correlation coefficients of 0.88. However additional measurements under a variety of ambient conditions are needed. Although the PMS sensor correlated as well as the research-grade instrument to the FRM/FEMs in ambient conditions, its response varies with particle properties to a much greater degree than the research-grade instrument. In addition, the PMS sensors overestimate ambient PM concentrations and begin to exhibit a non-linear response when PM 2.5 concentrations exceed 40 μg/m 3 . These results have important implications for communicating results from low-cost sensor networks, and they highlight the importance of using an appropriate correction factor for the target environmental conditions if the user wants to compare the results to FEM/FRMs. Copyright © 2016 Elsevier Ltd. All rights reserved.

The mid-IR silicon photonics sensor platform (Conference Presentation)

NASA Astrophysics Data System (ADS)

Kimerling, Lionel; Hu, Juejun; Agarwal, Anuradha M.

2017-02-01

Advances in integrated silicon photonics are enabling highly connected sensor networks that offer sensitivity, selectivity and pattern recognition. Cost, performance and the evolution path of the so-called `Internet of Things' will gate the proliferation of these networks. The wavelength spectral range of 3-8um, commonly known as the mid-IR, is critical to specificity for sensors that identify materials by detection of local vibrational modes, reflectivity and thermal emission. For ubiquitous sensing applications in this regime, the sensors must move from premium to commodity level manufacturing volumes and cost. Scaling performance/cost is critically dependent on establishing a minimum set of platform attributes for point, wearable, and physical sensing. Optical sensors are ideal for non-invasive applications. Optical sensor device physics involves evanescent or intra-cavity structures for applied to concentration, interrogation and photo-catalysis functions. The ultimate utility of a platform is dependent on sample delivery/presentation modalities; system reset, recalibration and maintenance capabilities; and sensitivity and selectivity performance. The attributes and performance of a unified Glass-on-Silicon platform has shown good prospects for heterogeneous integration on materials and devices using a low cost process flow. Integrated, single mode, silicon photonic platforms offer significant performance and cost advantages, but they require discovery and qualification of new materials and process integration schemes for the mid-IR. Waveguide integrated light sources based on rare earth dopants and Ge-pumped frequency combs have promise. Optical resonators and waveguide spirals can enhance sensitivity. PbTe materials are among the best choices for a standard, waveguide integrated photodetector. Chalcogenide glasses are capable of transmitting mid-IR signals with high transparency. Integrated sensor case studies of i) high sensitivity analyte detection in solution; ii) gas sensing in air and iii) on-chip spectrometry provide good insight into the tradeoffs being made en route to ubiquitous sensor deployment in an Internet of Things.

Monitoring meteorological spatial variability in viticulture using a low-cost Wireless Sensor Network

NASA Astrophysics Data System (ADS)

Matese, Alessandro; Crisci, Alfonso; Di Gennaro, Filippo; Primicerio, Jacopo; Tomasi, Diego; Guidoni, Silvia

2014-05-01

In a long-term perspective, the current global agricultural scenario will be characterize by critical issues in terms of water resource management and environmental protection. The concept of sustainable agriculture would become crucial at reducing waste, optimizing the use of pesticides and fertilizers to crops real needs. This can be achieved through a minimum-scale monitoring of the crop physiologic status and the environmental parameters that characterize the microclimate. Viticulture is often subject to high variability within the same vineyard, thus becomes important to monitor this heterogeneity to allow a site-specific management and maximize the sustainability and quality of production. Meteorological variability expressed both at vineyard scale (mesoclimate) and at single plant level (microclimate) plays an important role during the grape ripening process. The aim of this work was to compare temperature, humidity and solar radiation measurements at different spatial scales. The measurements were assessed for two seasons (2011, 2012) in two vineyards of the Veneto region (North-East Italy), planted with Pinot gris and Cabernet Sauvignon using a specially designed and developed Wireless Sensor Network (WSN). The WSN consists of various levels: the Master/Gateway level coordinates the WSN and performs data aggregation; the Farm/Server level takes care of storing data on a server, data processing and graphic rendering. Nodes level is based on a network of peripheral nodes consisting of a sensor board equipped with sensors and wireless module. The system was able to monitor the agrometeorological parameters in the vineyard: solar radiation, air temperature and air humidity. Different sources of spatial variation were studied, from meso-scale to micro-scale. A widespread investigation was conducted, building a factorial design able to evidence the role played by any factor influencing the physical environment in the vineyard, such as the surrounding climate effect, canopy management and relative position inside the vineyard. The results highlighted that the impact of agrometeorological parameters variability is predominantly determined by differences between within-field and external-field. These results may provide support for the composition of crop production and disease model simulations where data are usually taken from an agrometeorological station not representative of actual field conditions. Finally, the WSN performances, in terms of monitoring and reliability of the system, have been evaluated considering: its handiness, cost-effective, non-invasive dimensions and low power.

A low cost strategy to monitor the expansion and contraction of the flowing stream network in mountainous headwater catchments

NASA Astrophysics Data System (ADS)

Assendelft, Rick; van Meerveld, Ilja; Seibert, Jan

2017-04-01

Streams are dynamic features in the landscape. The flowing stream network expands and contracts, connects and disconnects in response to rainfall events and seasonal changes in catchment wetness. Sections of the river system that experience these wet and dry cycles are often referred to as temporary streams. Temporary streams are abundant and widely distributed freshwater ecosystems. They account for more than half of the total length of the global stream network, are unique habitats and form important hydrological and ecological links between the uplands and perennial streams. However, temporary streams have been largely unstudied, especially in mountainous headwater catchments. The dynamic character of these systems makes it difficult to monitor them. We describe a low-cost, do-it-yourself strategy to monitor the occurrence of water and flow in temporary streams. We evaluate this strategy in two headwater catchments in Switzerland. The low cost sensor network consists of electrical resistivity sensors, water level switches, temperature sensors and flow sensors. These sensors are connected to Arduino microcontrollers and data loggers, which log the data every 5 minutes. The data from the measurement network are compared with observations (mapping of the temporary stream network) as well as time lapse camera data to evaluate the performance of the sensors. We look at how frequently the output of the sensors (presence and absence of water from the ER and water level data, and flow or no-flow from the flow sensors) corresponds to the observed channel state. This is done for each sensor, per sub-catchment, per precipitation event and per sensor location to determine the best sensor combination to monitor temporary streams in mountainous catchments and in which situation which sensor combination works best. The preliminary results show that the sensors and monitoring network work well. The data from the sensors corresponds with the observations and provides information on the expansion of the stream network pattern.

Air Enquirer's multi-sensor boxes as a tool for High School Education and Atmospheric Research

NASA Astrophysics Data System (ADS)

Morguí, Josep-Anton; Font, Anna; Cañas, Lidia; Vázquez-García, Eusebi; Gini, Andrea; Corominas, Ariadna; Àgueda, Alba; Lobo, Agustin; Ferraz, Carlos; Nofuentes, Manel; Ulldemolins, Delmir; Roca, Alex; Kamnang, Armand; Grossi, Claudia; Curcoll, Roger; Batet, Oscar; Borràs, Silvia; Occhipinti, Paola; Rodó, Xavier

2016-04-01

An educational tool was designed with the aim of making more comprehensive the research done on Greenhouse Gases (GHGs) in the ClimaDat Spanish network of atmospheric observation stations (www.climadat.es). This tool is called Air Enquirer and it consist of a multi-sensor box. It is envisaged to build more than two hundred boxes to yield them to the Spanish High Schools through the Education department (www.educaixa.com) of the "Obra Social 'La Caixa'", who funds this research. The starting point for the development of the Air Enquirers was the experience at IC3 (www.ic3.cat) in the CarboSchools+ FP7 project (www.carboschools.cat, www.carboschools.eu). The Air Enquirer's multi-sensor box is based in Arduino's architecture and contains sensors for CO2, temperature, relative humidity, pressure, and both infrared and visible luminance. The Air Enquirer is designed for taking continuous measurements. Every Air Enquirer ensemble of measurements is used to convert values to standard units (water content in ppmv, and CO2 in ppmv_dry). These values are referred to a calibration made with Cavity Ring Down Spectrometry (Picarro®) under different temperature, pressure, humidity and CO2 concentrations. Multiple sets of Air Enquirers are intercalibrated for its use in parallel during the experiments. The different experiments proposed to the students will be outdoor (observational) or indoor (experimental, in the lab) focusing on understanding the biogeochemistry of GHGs in the ecosystems (mainly CO2), the exchange (flux) of gases, the organic matter production, respiration and decomposition processes, the influence of the anthropogenic activities on the gases (and particles) exchanges, and their interaction with the structure and composition of the atmosphere (temperature, water content, cooling and warming processes, radiative forcing, vertical gradients and horizontal patterns). In order to ensure Air Enquirers a high-profile research performance the experimental designs and the device have been tested under research conditions by professional instruments. Results from several experiments are shown here: i) from vertical profiles obtained by drones (www.hemav.com) over Ebre Delta crops, ii) from measurements on lagoons, salt marshes and marine coastal research in the ClimaDat DEC3 station, iii) from horizontal patterns of variability over and under canopy, related to ecosystem patchiness in the highly instrumented Valderejo ClimaDat mountain station (www.modpow.es) and iv) from urban transects to reveal the urban atmosphere dynamic processes.

Energy Efficient Cluster Based Scheduling Scheme for Wireless Sensor Networks

PubMed Central

Srie Vidhya Janani, E.; Ganesh Kumar, P.

2015-01-01

The energy utilization of sensor nodes in large scale wireless sensor network points out the crucial need for scalable and energy efficient clustering protocols. Since sensor nodes usually operate on batteries, the maximum utility of network is greatly dependent on ideal usage of energy leftover in these sensor nodes. In this paper, we propose an Energy Efficient Cluster Based Scheduling Scheme for wireless sensor networks that balances the sensor network lifetime and energy efficiency. In the first phase of our proposed scheme, cluster topology is discovered and cluster head is chosen based on remaining energy level. The cluster head monitors the network energy threshold value to identify the energy drain rate of all its cluster members. In the second phase, scheduling algorithm is presented to allocate time slots to cluster member data packets. Here congestion occurrence is totally avoided. In the third phase, energy consumption model is proposed to maintain maximum residual energy level across the network. Moreover, we also propose a new packet format which is given to all cluster member nodes. The simulation results prove that the proposed scheme greatly contributes to maximum network lifetime, high energy, reduced overhead, and maximum delivery ratio. PMID:26495417

Design and Analysis of a Data Fusion Scheme in Mobile Wireless Sensor Networks Based on Multi-Protocol Mobile Agents

PubMed Central

Wu, Chunxue; Wu, Wenliang; Wan, Caihua

2017-01-01

Sensors are increasingly used in mobile environments with wireless network connections. Multiple sensor types measure distinct aspects of the same event. Their measurements are then combined to produce integrated, reliable results. As the number of sensors in networks increases, low energy requirements and changing network connections complicate event detection and measurement. We present a data fusion scheme for use in mobile wireless sensor networks with high energy efficiency and low network delays, that still produces reliable results. In the first phase, we used a network simulation where mobile agents dynamically select the next hop migration node based on the stability parameter of the link, and perform the data fusion at the migration node. Agents use the fusion results to decide if it should return the fusion results to the processing center or continue to collect more data. In the second phase. The feasibility of data fusion at the node level is confirmed by an experimental design where fused data from color sensors show near-identical results to actual physical temperatures. These results are potentially important for new large-scale sensor network applications. PMID:29099793

TinyOS-based quality of service management in wireless sensor networks

USGS Publications Warehouse

Peterson, N.; Anusuya-Rangappa, L.; Shirazi, B.A.; Huang, R.; Song, W.-Z.; Miceli, M.; McBride, D.; Hurson, A.; LaHusen, R.

2009-01-01

Previously the cost and extremely limited capabilities of sensors prohibited Quality of Service (QoS) implementations in wireless sensor networks. With advances in technology, sensors are becoming significantly less expensive and the increases in computational and storage capabilities are opening the door for new, sophisticated algorithms to be implemented. Newer sensor network applications require higher data rates with more stringent priority requirements. We introduce a dynamic scheduling algorithm to improve bandwidth for high priority data in sensor networks, called Tiny-DWFQ. Our Tiny-Dynamic Weighted Fair Queuing scheduling algorithm allows for dynamic QoS for prioritized communications by continually adjusting the treatment of communication packages according to their priorities and the current level of network congestion. For performance evaluation, we tested Tiny-DWFQ, Tiny-WFQ (traditional WFQ algorithm implemented in TinyOS), and FIFO queues on an Imote2-based wireless sensor network and report their throughput and packet loss. Our results show that Tiny-DWFQ performs better in all test cases. ?? 2009 IEEE.

Reputation-Based Internet Protocol Security: A Multilayer Security Framework for Mobile Ad Hoc Networks

DTIC Science & Technology

2010-09-01

secure ad-hoc networks of mobile sensors deployed in a hostile environment . These sensors are normally small 86 and resource...Communications Magazine, 51, 2008. 45. Kumar, S.A. “Classification and Review of Security Schemes in Mobile Comput- ing”. Wireless Sensor Network , 2010... Networks ”. Wireless /Mobile Network Security , 2008. 85. Xiao, Y. “Accountability for Wireless LANs, Ad Hoc Networks , and Wireless

Low-cost mobile air pollution monitoring in urban environments: a pilot study in Lubbock, Texas.

PubMed

McKercher, Grant R; Vanos, Jennifer K

2018-06-01

The complex nature of air pollution in urban areas prevents traditional monitoring techniques from obtaining measurements representative of true human exposure. The current study assessed the capability of low-cost mobile monitors to acquire useful data in a city without a monitoring network in place (Lubbock, Texas) using a bicycle platform. The monitoring campaign resulted in 30 days of data along a 13.4 km fixed concentric route. Due to high sensitivities to airflow, the apparent wind velocity was accounted for throughout the route. The data were also normalized into percentiles in order to visualize spatial patterns. The highest estimated pollution levels were located near frequently busy intersections and roads; however, sensor issues resulted in lower confidence. Additional research is needed concerning the appropriate use of low-cost metal oxide sensors for citizen science applications, as measurements can be misleading if the user is unaware of sensors specifications. The simultaneous use of several low-cost mobile platforms, rather than a single platform, as well as the use of high-end cases, are recommended to create a more robust spatial analysis. The issues addressed from this research are important to understand for accurate and beneficial application of low-cost gaseous monitors for citizen science.

Linear air-fuel sensor development

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

Garzon, F.; Miller, C.

1996-12-14

The electrochemical zirconia solid electrolyte oxygen sensor, is extensively used for monitoring oxygen concentrations in various fields. They are currently utilized in automobiles to monitor the exhaust gas composition and control the air-to-fuel ratio, thus reducing harmful emission components and improving fuel economy. Zirconia oxygen sensors, are divided into two classes of devices: (1) potentiometric or logarithmic air/fuel sensors; and (2) amperometric or linear air/fuel sensors. The potentiometric sensors are ideally suited to monitor the air-to-fuel ratio close to the complete combustion stoichiometry; a value of about 14.8 to 1 parts by volume. This occurs because the oxygen concentration changesmore » by many orders of magnitude as the air/fuel ratio is varied through the stoichiometric value. However, the potentiometric sensor is not very sensitive to changes in oxygen partial pressure away from the stoichiometric point due to the logarithmic dependence of the output voltage signal on the oxygen partial pressure. It is often advantageous to operate gasoline power piston engines with excess combustion air; this improves fuel economy and reduces hydrocarbon emissions. To maintain stable combustion away from stoichiometry, and enable engines to operate in the excess oxygen (lean burn) region several limiting-current amperometric sensors have been reported. These sensors are based on the electrochemical oxygen ion pumping of a zirconia electrolyte. They typically show reproducible limiting current plateaus with an applied voltage caused by the gas diffusion overpotential at the cathode.« less

SOUNET: Self-Organized Underwater Wireless Sensor Network.

PubMed

Kim, Hee-Won; Cho, Ho-Shin

2017-02-02

In this paper, we propose an underwater wireless sensor network (UWSN) named SOUNET where sensor nodes form and maintain a tree-topological network for data gathering in a self-organized manner. After network topology discovery via packet flooding, the sensor nodes consistently update their parent node to ensure the best connectivity by referring to the timevarying neighbor tables. Such a persistent and self-adaptive method leads to high network connectivity without any centralized control, even when sensor nodes are added or unexpectedly lost. Furthermore, malfunctions that frequently happen in self-organized networks such as node isolation and closed loop are resolved in a simple way. Simulation results show that SOUNET outperforms other conventional schemes in terms of network connectivity, packet delivery ratio (PDR), and energy consumption throughout the network. In addition, we performed an experiment at the Gyeongcheon Lake in Korea using commercial underwater modems to verify that SOUNET works well in a real environment.

SOUNET: Self-Organized Underwater Wireless Sensor Network

PubMed Central

Kim, Hee-won; Cho, Ho-Shin

2017-01-01

In this paper, we propose an underwater wireless sensor network (UWSN) named SOUNET where sensor nodes form and maintain a tree-topological network for data gathering in a self-organized manner. After network topology discovery via packet flooding, the sensor nodes consistently update their parent node to ensure the best connectivity by referring to the time-varying neighbor tables. Such a persistent and self-adaptive method leads to high network connectivity without any centralized control, even when sensor nodes are added or unexpectedly lost. Furthermore, malfunctions that frequently happen in self-organized networks such as node isolation and closed loop are resolved in a simple way. Simulation results show that SOUNET outperforms other conventional schemes in terms of network connectivity, packet delivery ratio (PDR), and energy consumption throughout the network. In addition, we performed an experiment at the Gyeongcheon Lake in Korea using commercial underwater modems to verify that SOUNET works well in a real environment. PMID:28157164

Autonomous vision networking: miniature wireless sensor networks with imaging technology

NASA Astrophysics Data System (ADS)

Messinger, Gioia; Goldberg, Giora

2006-09-01

The recent emergence of integrated PicoRadio technology, the rise of low power, low cost, System-On-Chip (SOC) CMOS imagers, coupled with the fast evolution of networking protocols and digital signal processing (DSP), created a unique opportunity to achieve the goal of deploying large-scale, low cost, intelligent, ultra-low power distributed wireless sensor networks for the visualization of the environment. Of all sensors, vision is the most desired, but its applications in distributed sensor networks have been elusive so far. Not any more. The practicality and viability of ultra-low power vision networking has been proven and its applications are countless, from security, and chemical analysis to industrial monitoring, asset tracking and visual recognition, vision networking represents a truly disruptive technology applicable to many industries. The presentation discusses some of the critical components and technologies necessary to make these networks and products affordable and ubiquitous - specifically PicoRadios, CMOS imagers, imaging DSP, networking and overall wireless sensor network (WSN) system concepts. The paradigm shift, from large, centralized and expensive sensor platforms, to small, low cost, distributed, sensor networks, is possible due to the emergence and convergence of a few innovative technologies. Avaak has developed a vision network that is aided by other sensors such as motion, acoustic and magnetic, and plans to deploy it for use in military and commercial applications. In comparison to other sensors, imagers produce large data files that require pre-processing and a certain level of compression before these are transmitted to a network server, in order to minimize the load on the network. Some of the most innovative chemical detectors currently in development are based on sensors that change color or pattern in the presence of the desired analytes. These changes are easily recorded and analyzed by a CMOS imager and an on-board DSP processor. Image processing at the sensor node level may also be required for applications in security, asset management and process control. Due to the data bandwidth requirements posed on the network by video sensors, new networking protocols or video extensions to existing standards (e.g. Zigbee) are required. To this end, Avaak has designed and implemented an ultra-low power networking protocol designed to carry large volumes of data through the network. The low power wireless sensor nodes that will be discussed include a chemical sensor integrated with a CMOS digital camera, a controller, a DSP processor and a radio communication transceiver, which enables relaying of an alarm or image message, to a central station. In addition to the communications, identification is very desirable; hence location awareness will be later incorporated to the system in the form of Time-Of-Arrival triangulation, via wide band signaling. While the wireless imaging kernel already exists specific applications for surveillance and chemical detection are under development by Avaak, as part of a co-founded program from ONR and DARPA. Avaak is also designing vision networks for commercial applications - some of which are undergoing initial field tests.

Single Walled Carbon Nanotube Based Air Pocket Encapsulated Ultraviolet Sensor.

PubMed

Kim, Sun Jin; Han, Jin-Woo; Kim, Beomseok; Meyyappan, M

2017-11-22

Carbon nanotube (CNT) is a promising candidate as a sensor material for the sensitive detection of gases/vapors, biomarkers, and even some radiation, as all these external variables affect the resistance and other properties of nanotubes, which forms the basis for sensing. Ultraviolet (UV) radiation does not impact the nanotube properties given the substantial mismatch of bandgaps and therefore, CNTs have never been considered for UV sensing, unlike the popular ZnO and other oxide nanwires. It is well-known that UV assists the adsorption/desorption characteristics of oxygen on carbon nanotubes, which changes the nanotube resistance. Here, we demonstrate a novel sensor structure encapsulated with an air pocket, where the confined air is responsible for the UV sensing mechanism and assures sensor stability and repeatability over time. In addition to the protection from any contamination, the air pocket encapsulated sensor offers negligible baseline drift and fast recovery compared to previously reported sensors. The air pocket isolated from the outside environment can act as a stationary oxygen reservoir, resulting in consistent sensor characteristics. Furthermore, this sensor can be used even in liquid environments.

A Formal Approach to the Selection by Minimum Error and Pattern Method for Sensor Data Loss Reduction in Unstable Wireless Sensor Network Communications

PubMed Central

Kim, Changhwa; Shin, DongHyun

2017-01-01

There are wireless networks in which typically communications are unsafe. Most terrestrial wireless sensor networks belong to this category of networks. Another example of an unsafe communication network is an underwater acoustic sensor network (UWASN). In UWASNs in particular, communication failures occur frequently and the failure durations can range from seconds up to a few hours, days, or even weeks. These communication failures can cause data losses significant enough to seriously damage human life or property, depending on their application areas. In this paper, we propose a framework to reduce sensor data loss during communication failures and we present a formal approach to the Selection by Minimum Error and Pattern (SMEP) method that plays the most important role for the reduction in sensor data loss under the proposed framework. The SMEP method is compared with other methods to validate its effectiveness through experiments using real-field sensor data sets. Moreover, based on our experimental results and performance comparisons, the SMEP method has been validated to be better than others in terms of the average sensor data value error rate caused by sensor data loss. PMID:28498312

A Formal Approach to the Selection by Minimum Error and Pattern Method for Sensor Data Loss Reduction in Unstable Wireless Sensor Network Communications.

PubMed

Kim, Changhwa; Shin, DongHyun

2017-05-12

There are wireless networks in which typically communications are unsafe. Most terrestrial wireless sensor networks belong to this category of networks. Another example of an unsafe communication network is an underwater acoustic sensor network (UWASN). In UWASNs in particular, communication failures occur frequently and the failure durations can range from seconds up to a few hours, days, or even weeks. These communication failures can cause data losses significant enough to seriously damage human life or property, depending on their application areas. In this paper, we propose a framework to reduce sensor data loss during communication failures and we present a formal approach to the Selection by Minimum Error and Pattern (SMEP) method that plays the most important role for the reduction in sensor data loss under the proposed framework. The SMEP method is compared with other methods to validate its effectiveness through experiments using real-field sensor data sets. Moreover, based on our experimental results and performance comparisons, the SMEP method has been validated to be better than others in terms of the average sensor data value error rate caused by sensor data loss.

The Citizen Science Toolbox: A One-Stop Resource for Air Sensor Technology

EPA Science Inventory

The air sensor technology market is exploding with new sensors in all kinds of forms. Developers are putting sensors in wristbands, headphones, and cell phone add-ons. Small, portable and lower-cost measurement devices using sensors are coming on the market with a wide variety of...

Self-localization of wireless sensor networks using self-organizing maps

NASA Astrophysics Data System (ADS)

Ertin, Emre; Priddy, Kevin L.

2005-03-01

Recently there has been a renewed interest in the notion of deploying large numbers of networked sensors for applications ranging from environmental monitoring to surveillance. In a typical scenario a number of sensors are distributed in a region of interest. Each sensor is equipped with sensing, processing and communication capabilities. The information gathered from the sensors can be used to detect, track and classify objects of interest. For a number of locations the sensors location is crucial in interpreting the data collected from those sensors. Scalability requirements dictate sensor nodes that are inexpensive devices without a dedicated localization hardware such as GPS. Therefore the network has to rely on information collected within the network to self-localize. In the literature a number of algorithms has been proposed for network localization which uses measurements informative of range, angle, proximity between nodes. Recent work by Patwari and Hero relies on sensor data without explicit range estimates. The assumption is that the correlation structure in the data is a monotone function of the intersensor distances. In this paper we propose a new method based on unsupervised learning techniques to extract location information from the sensor data itself. We consider a grid consisting of virtual nodes and try to fit grid in the actual sensor network data using the method of self organizing maps. Then known sensor network geometry can be used to rotate and scale the grid to a global coordinate system. Finally, we illustrate how the virtual nodes location information can be used to track a target.

Wireless Sensor Networks: Monitoring and Control

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

Hastbacka, Mildred; Ponoum, Ratcharit; Bouza, Antonio

2013-05-31

The article discusses wireless sensor technologies for building energy monitoring and control. This article, also, addresses wireless sensor networks as well as benefits and challenges of using wireless sensors. The energy savings and market potential of wireless sensors are reviewed.

Detecting and Preventing Sybil Attacks in Wireless Sensor Networks Using Message Authentication and Passing Method.

PubMed

Dhamodharan, Udaya Suriya Raj Kumar; Vayanaperumal, Rajamani

2015-01-01

Wireless sensor networks are highly indispensable for securing network protection. Highly critical attacks of various kinds have been documented in wireless sensor network till now by many researchers. The Sybil attack is a massive destructive attack against the sensor network where numerous genuine identities with forged identities are used for getting an illegal entry into a network. Discerning the Sybil attack, sinkhole, and wormhole attack while multicasting is a tremendous job in wireless sensor network. Basically a Sybil attack means a node which pretends its identity to other nodes. Communication to an illegal node results in data loss and becomes dangerous in the network. The existing method Random Password Comparison has only a scheme which just verifies the node identities by analyzing the neighbors. A survey was done on a Sybil attack with the objective of resolving this problem. The survey has proposed a combined CAM-PVM (compare and match-position verification method) with MAP (message authentication and passing) for detecting, eliminating, and eventually preventing the entry of Sybil nodes in the network. We propose a scheme of assuring security for wireless sensor network, to deal with attacks of these kinds in unicasting and multicasting.

Detecting and Preventing Sybil Attacks in Wireless Sensor Networks Using Message Authentication and Passing Method

PubMed Central

Dhamodharan, Udaya Suriya Raj Kumar; Vayanaperumal, Rajamani

2015-01-01

Wireless sensor networks are highly indispensable for securing network protection. Highly critical attacks of various kinds have been documented in wireless sensor network till now by many researchers. The Sybil attack is a massive destructive attack against the sensor network where numerous genuine identities with forged identities are used for getting an illegal entry into a network. Discerning the Sybil attack, sinkhole, and wormhole attack while multicasting is a tremendous job in wireless sensor network. Basically a Sybil attack means a node which pretends its identity to other nodes. Communication to an illegal node results in data loss and becomes dangerous in the network. The existing method Random Password Comparison has only a scheme which just verifies the node identities by analyzing the neighbors. A survey was done on a Sybil attack with the objective of resolving this problem. The survey has proposed a combined CAM-PVM (compare and match-position verification method) with MAP (message authentication and passing) for detecting, eliminating, and eventually preventing the entry of Sybil nodes in the network. We propose a scheme of assuring security for wireless sensor network, to deal with attacks of these kinds in unicasting and multicasting. PMID:26236773

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...

Topology Optimization for Energy Management in Underwater Sensor Networks

DTIC Science & Technology

2015-02-01

1 To appear in International Journal of Control as a regular paper Topology Optimization for Energy Management in Underwater Sensor Networks ⋆ Devesh...K. Jha1 Thomas A. Wettergren2 Asok Ray1 Kushal Mukherjee3 Keywords: Underwater Sensor Network , Energy Management, Pareto Optimization, Adaptation...Optimization for Energy Management in Underwater Sensor Networks 5a. CONTRACT NUMBER 5b. GRANT NUMBER 5c. PROGRAM ELEMENT NUMBER 6. AUTHOR(S) 5d

Connectivity, Coverage and Placement in Wireless Sensor Networks

PubMed Central

Li, Ji; Andrew, Lachlan L.H.; Foh, Chuan Heng; Zukerman, Moshe; Chen, Hsiao-Hwa

2009-01-01

Wireless communication between sensors allows the formation of flexible sensor networks, which can be deployed rapidly over wide or inaccessible areas. However, the need to gather data from all sensors in the network imposes constraints on the distances between sensors. This survey describes the state of the art in techniques for determining the minimum density and optimal locations of relay nodes and ordinary sensors to ensure connectivity, subject to various degrees of uncertainty in the locations of the nodes. PMID:22408474

IBE-Lite: a lightweight identity-based cryptography for body sensor networks.

PubMed

Tan, Chiu C; Wang, Haodong; Zhong, Sheng; Li, Qun

2009-11-01

A body sensor network (BSN) is a network of sensors deployed on a person's body for health care monitoring. Since the sensors collect personal medical data, security and privacy are important components in a BSN. In this paper, we developed IBE-Lite, a lightweight identity-based encryption suitable for sensors in a BSN. We present protocols based on IBE-Lite that balance security and privacy with accessibility and perform evaluation using experiments conducted on commercially available sensors.

A Survey on Security and Privacy in Emerging Sensor Networks: From Viewpoint of Close-Loop

PubMed Central

Zhang, Lifu; Zhang, Heng

2016-01-01

Nowadays, as the next generation sensor networks, Cyber-Physical Systems (CPSs) refer to the complex networked systems that have both physical subsystems and cyber components, and the information flow between different subsystems and components is across a communication network, which forms a closed-loop. New generation sensor networks are found in a growing number of applications and have received increasing attention from many inter-disciplines. Opportunities and challenges in the design, analysis, verification and validation of sensor networks co-exists, among which security and privacy are two important ingredients. This paper presents a survey on some recent results in the security and privacy aspects of emerging sensor networks from the viewpoint of the closed-loop. This paper also discusses several future research directions under these two umbrellas. PMID:27023559

Smart fabrics: integrating fiber optic sensors and information networks.

PubMed

El-Sherif, Mahmoud

2004-01-01

"Smart Fabrics" are defined as fabrics capable of monitoring their own "health", and sensing environmental conditions. They consist of special type of sensors, signal processing, and communication network embedded into textile substrate. Available conventional sensors and networking systems are not fully technologically mature for such applications. New classes of miniature sensors, signal processing and networking systems are urgently needed for such application. Also, the methodology for integration into textile structures has to be developed. In this paper, the development of smart fabrics with embedded fiber optic systems is presented for applications in health monitoring and diagnostics. Successful development of such smart fabrics with embedded sensors and networks is mainly dependent on the development of the proper miniature sensors technology, and on the integration of these sensors into textile structures. The developed smart fabrics will be discussed and samples of the results will be presented.

Hypergolic fuel detection using individual single walled carbon nanotube networks

NASA Astrophysics Data System (ADS)

Desai, S. C.; Willitsford, A. H.; Sumanasekera, G. U.; Yu, M.; Tian, W. Q.; Jayanthi, C. S.; Wu, S. Y.

2010-06-01

Accurate and reliable detection of hypergolic fuels such as hydrazine (N2H4) and its derivatives is vital to missile defense, aviation, homeland security, and the chemical industry. More importantly these sensors need to be capable of operation at low temperatures (below room temperature) as most of the widely used chemical sensors operate at high temperatures (above 300 °C). In this research a simple and highly sensitive single walled carbon nanotube (SWNT) network sensor was developed for real time monitoring of hydrazine leaks to concentrations at parts per million levels. Upon exposure to hydrazine vapor, the resistance of the air exposed nanotubes (p-type) is observed to increase rapidly while that of the vacuum-degassed nanotubes (n-type) is observed to decrease. It was found that the resistance of the sample can be recovered through vacuum pumping and exposure to ultraviolet light. The experimental results support the electrochemical charge transfer mechanism between the oxygen redox couple of the ambient and the Fermi level of the SWNT. Theoretical results of the hydrazine-SWNT interaction are compared with the experimental observations. It was found that a monolayer of water molecules on the SWNT is necessary to induce strong interactions between hydrazine and the SWNT by way of introducing new occupied states near the bottom of the conduction band of the SWNT.

On-board Model Predictive Control of a Quadrotor Helicopter: Design, Implementation, and Experiments

DTIC Science & Technology

2012-12-13

speed, as the attached rotor effects momentum change of the surrounding air. However, we have in mind applications (e.g. mobile sensor networks... rotors is in play. At any rate, it suffices to note that the thrust from a given rotor is effectively proportional to its rate of rotation; indeed the...negligible impact on lift force when the main rotor is within 2 rotor diameters of the ground (Leishman, 2006). This effect has also been noted in other

Energy Aware Clustering Algorithms for Wireless Sensor Networks

NASA Astrophysics Data System (ADS)

Rakhshan, Noushin; Rafsanjani, Marjan Kuchaki; Liu, Chenglian

2011-09-01

The sensor nodes deployed in wireless sensor networks (WSNs) are extremely power constrained, so maximizing the lifetime of the entire networks is mainly considered in the design. In wireless sensor networks, hierarchical network structures have the advantage of providing scalable and energy efficient solutions. In this paper, we investigate different clustering algorithms for WSNs and also compare these clustering algorithms based on metrics such as clustering distribution, cluster's load balancing, Cluster Head's (CH) selection strategy, CH's role rotation, node mobility, clusters overlapping, intra-cluster communications, reliability, security and location awareness.

Effect of Field Spread on Resting-State Magneto Encephalography Functional Network Analysis: A Computational Modeling Study.

PubMed

Silva Pereira, Silvana; Hindriks, Rikkert; Mühlberg, Stefanie; Maris, Eric; van Ede, Freek; Griffa, Alessandra; Hagmann, Patric; Deco, Gustavo

2017-11-01

A popular way to analyze resting-state electroencephalography (EEG) and magneto encephalography (MEG) data is to treat them as a functional network in which sensors are identified with nodes and the interaction between channel time series and the network connections. Although conceptually appealing, the network-theoretical approach to sensor-level EEG and MEG data is challenged by the fact that EEG and MEG time series are mixtures of source activity. It is, therefore, of interest to assess the relationship between functional networks of source activity and the ensuing sensor-level networks. Since these topological features are of high interest in experimental studies, we address the question of to what extent the network topology can be reconstructed from sensor-level functional connectivity (FC) measures in case of MEG data. Simple simulations that consider only a small number of regions do not allow to assess network properties; therefore, we use a diffusion magnetic resonance imaging-constrained whole-brain computational model of resting-state activity. Our motivation lies behind the fact that still many contributions found in the literature perform network analysis at sensor level, and we aim at showing the discrepancies between source- and sensor-level network topologies by using realistic simulations of resting-state cortical activity. Our main findings are that the effect of field spread on network topology depends on the type of interaction (instantaneous or lagged) and leads to an underestimation of lagged FC at sensor level due to instantaneous mixing of cortical signals, instantaneous interaction is more sensitive to field spread than lagged interaction, and discrepancies are reduced when using planar gradiometers rather than axial gradiometers. We, therefore, recommend using lagged interaction measures on planar gradiometer data when investigating network properties of resting-state sensor-level MEG data.

CMOS: Efficient Clustered Data Monitoring in Sensor Networks

PubMed Central

2013-01-01

Tiny and smart sensors enable applications that access a network of hundreds or thousands of sensors. Thus, recently, many researchers have paid attention to wireless sensor networks (WSNs). The limitation of energy is critical since most sensors are battery-powered and it is very difficult to replace batteries in cases that sensor networks are utilized outdoors. Data transmission between sensor nodes needs more energy than computation in a sensor node. In order to reduce the energy consumption of sensors, we present an approximate data gathering technique, called CMOS, based on the Kalman filter. The goal of CMOS is to efficiently obtain the sensor readings within a certain error bound. In our approach, spatially close sensors are grouped as a cluster. Since a cluster header generates approximate readings of member nodes, a user query can be answered efficiently using the cluster headers. In addition, we suggest an energy efficient clustering method to distribute the energy consumption of cluster headers. Our simulation results with synthetic data demonstrate the efficiency and accuracy of our proposed technique. PMID:24459444

CMOS: efficient clustered data monitoring in sensor networks.

PubMed

Min, Jun-Ki

2013-01-01

Tiny and smart sensors enable applications that access a network of hundreds or thousands of sensors. Thus, recently, many researchers have paid attention to wireless sensor networks (WSNs). The limitation of energy is critical since most sensors are battery-powered and it is very difficult to replace batteries in cases that sensor networks are utilized outdoors. Data transmission between sensor nodes needs more energy than computation in a sensor node. In order to reduce the energy consumption of sensors, we present an approximate data gathering technique, called CMOS, based on the Kalman filter. The goal of CMOS is to efficiently obtain the sensor readings within a certain error bound. In our approach, spatially close sensors are grouped as a cluster. Since a cluster header generates approximate readings of member nodes, a user query can be answered efficiently using the cluster headers. In addition, we suggest an energy efficient clustering method to distribute the energy consumption of cluster headers. Our simulation results with synthetic data demonstrate the efficiency and accuracy of our proposed technique.

Measuring PM and related air pollutants using low-cost sensors

EPA Science Inventory

Emerging air quality sensors may play a key role in better characterizing levels of air pollution in a variety of settings There are a wide range of low-cost (< $500 US) sensors on the market, but few have been characterized. If accurate, this new generation of inexpensive sens...

Optimizing Energy Consumption in Vehicular Sensor Networks by Clustering Using Fuzzy C-Means and Fuzzy Subtractive Algorithms

NASA Astrophysics Data System (ADS)

Ebrahimi, A.; Pahlavani, P.; Masoumi, Z.

2017-09-01

Traffic monitoring and managing in urban intelligent transportation systems (ITS) can be carried out based on vehicular sensor networks. In a vehicular sensor network, vehicles equipped with sensors such as GPS, can act as mobile sensors for sensing the urban traffic and sending the reports to a traffic monitoring center (TMC) for traffic estimation. The energy consumption by the sensor nodes is a main problem in the wireless sensor networks (WSNs); moreover, it is the most important feature in designing these networks. Clustering the sensor nodes is considered as an effective solution to reduce the energy consumption of WSNs. Each cluster should have a Cluster Head (CH), and a number of nodes located within its supervision area. The cluster heads are responsible for gathering and aggregating the information of clusters. Then, it transmits the information to the data collection center. Hence, the use of clustering decreases the volume of transmitting information, and, consequently, reduces the energy consumption of network. In this paper, Fuzzy C-Means (FCM) and Fuzzy Subtractive algorithms are employed to cluster sensors and investigate their performance on the energy consumption of sensors. It can be seen that the FCM algorithm and Fuzzy Subtractive have been reduced energy consumption of vehicle sensors up to 90.68% and 92.18%, respectively. Comparing the performance of the algorithms implies the 1.5 percent improvement in Fuzzy Subtractive algorithm in comparison.

Development and Evaluation of a City-Wide Wireless Weather Sensor Network

ERIC Educational Resources Information Center

Chang, Ben; Wang, Hsue-Yie; Peng, Tian-Yin; Hsu, Ying-Shao

2010-01-01

This project analyzed the effectiveness of a city-wide wireless weather sensor network, the Taipei Weather Science Learning Network (TWIN), in facilitating elementary and junior high students' study of weather science. The network, composed of sixty school-based weather sensor nodes and a centralized weather data archive server, provides students…

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

Resilient Sensor Networks with Spatiotemporal Interpolation of Missing Sensors: An Example of Space Weather Forecasting by Multiple Satellites

PubMed Central

Tokumitsu, Masahiro; Hasegawa, Keisuke; Ishida, Yoshiteru

2016-01-01

This paper attempts to construct a resilient sensor network model with an example of space weather forecasting. The proposed model is based on a dynamic relational network. Space weather forecasting is vital for a satellite operation because an operational team needs to make a decision for providing its satellite service. The proposed model is resilient to failures of sensors or missing data due to the satellite operation. In the proposed model, the missing data of a sensor is interpolated by other sensors associated. This paper demonstrates two examples of space weather forecasting that involves the missing observations in some test cases. In these examples, the sensor network for space weather forecasting continues a diagnosis by replacing faulted sensors with virtual ones. The demonstrations showed that the proposed model is resilient against sensor failures due to suspension of hardware failures or technical reasons. PMID:27092508

Information Fusion in Ad hoc Wireless Sensor Networks for Aircraft Health Monitoring

NASA Astrophysics Data System (ADS)

Fragoulis, Nikos; Tsagaris, Vassilis; Anastassopoulos, Vassilis

In this paper the use of an ad hoc wireless sensor network for implementing a structural health monitoring system is discussed. The network is consisted of sensors deployed throughout the aircraft. These sensors being in the form of a microelectronic chip and consisted of sensing, data processing and communicating components could be easily embedded in any mechanical aircraft component. The established sensor network, due to its ad hoc nature is easily scalable, allowing adding or removing any number of sensors. The position of the sensor nodes need not necessarily to be engineered or predetermined, giving this way the ability to be deployed in inaccessible points. Information collected from various sensors of different modalities throughout the aircraft is then fused in order to provide a more comprehensive image of the aircraft structural health. Sensor level fusion along with decision quality information is used, in order to enhance detection performance.

Resilient Sensor Networks with Spatiotemporal Interpolation of Missing Sensors: An Example of Space Weather Forecasting by Multiple Satellites.

PubMed

Tokumitsu, Masahiro; Hasegawa, Keisuke; Ishida, Yoshiteru

2016-04-15

This paper attempts to construct a resilient sensor network model with an example of space weather forecasting. The proposed model is based on a dynamic relational network. Space weather forecasting is vital for a satellite operation because an operational team needs to make a decision for providing its satellite service. The proposed model is resilient to failures of sensors or missing data due to the satellite operation. In the proposed model, the missing data of a sensor is interpolated by other sensors associated. This paper demonstrates two examples of space weather forecasting that involves the missing observations in some test cases. In these examples, the sensor network for space weather forecasting continues a diagnosis by replacing faulted sensors with virtual ones. The demonstrations showed that the proposed model is resilient against sensor failures due to suspension of hardware failures or technical reasons.

Integration and Analysis of Neighbor Discovery and Link Quality Estimation in Wireless Sensor Networks

PubMed Central

Radi, Marjan; Dezfouli, Behnam; Abu Bakar, Kamalrulnizam; Abd Razak, Shukor

2014-01-01

Network connectivity and link quality information are the fundamental requirements of wireless sensor network protocols to perform their desired functionality. Most of the existing discovery protocols have only focused on the neighbor discovery problem, while a few number of them provide an integrated neighbor search and link estimation. As these protocols require a careful parameter adjustment before network deployment, they cannot provide scalable and accurate network initialization in large-scale dense wireless sensor networks with random topology. Furthermore, performance of these protocols has not entirely been evaluated yet. In this paper, we perform a comprehensive simulation study on the efficiency of employing adaptive protocols compared to the existing nonadaptive protocols for initializing sensor networks with random topology. In this regard, we propose adaptive network initialization protocols which integrate the initial neighbor discovery with link quality estimation process to initialize large-scale dense wireless sensor networks without requiring any parameter adjustment before network deployment. To the best of our knowledge, this work is the first attempt to provide a detailed simulation study on the performance of integrated neighbor discovery and link quality estimation protocols for initializing sensor networks. This study can help system designers to determine the most appropriate approach for different applications. PMID:24678277

Air Sensor Toolbox for Citizen Scientists

EPA Pesticide Factsheets

EPA’s Air Sensor Toolbox provides information and guidance on new low-cost compact technologies for measuring air quality. It provides information to help citizens more effectively and accurately collect air quality data in their community.

Air Sensor Toolbox: Resources and Funding

EPA Pesticide Factsheets

EPA’s Air Sensor Toolbox provides information and guidance on new low-cost compact technologies for measuring air quality. It provides information to help citizens more effectively and accurately collect air quality data in their community.

Data aggregation in wireless sensor networks using the SOAP protocol

NASA Astrophysics Data System (ADS)

Al-Yasiri, A.; Sunley, A.

2007-07-01

Wireless sensor networks (WSN) offer an increasingly attractive method of data gathering in distributed system architectures and dynamic access via wireless connectivity. Wireless sensor networks have physical and resource limitations, this leads to increased complexity for application developers and often results in applications that are closely coupled with network protocols. In this paper, a data aggregation framework using SOAP (Simple Object Access Protocol) on wireless sensor networks is presented. The framework works as a middleware for aggregating data measured by a number of nodes within a network. The aim of the study is to assess the suitability of the protocol in such environments where resources are limited compared to traditional networks.

Wireless Networks under a Backoff Attack: A Game Theoretical Perspective.

PubMed

Parras, Juan; Zazo, Santiago

2018-01-30

We study a wireless sensor network using CSMA/CA in the MAC layer under a backoff attack: some of the sensors of the network are malicious and deviate from the defined contention mechanism. We use Bianchi's network model to study the impact of the malicious sensors on the total network throughput, showing that it causes the throughput to be unfairly distributed among sensors. We model this conflict using game theory tools, where each sensor is a player. We obtain analytical solutions and propose an algorithm, based on Regret Matching, to learn the equilibrium of the game with an arbitrary number of players. Our approach is validated via simulations, showing that our theoretical predictions adjust to reality.

Integrated Sensor Architecture (ISA) for Live Virtual Constructive (LVC) Environments

DTIC Science & Technology

2014-03-01

connect, publish their needs and capabilities, and interact with other systems even on disadvantaged networks. Within the ISA project, three levels of...constructive, disadvantaged network, sensor 1. INTRODUCTION In 2003 the Networked Sensors for the Future Force (NSFF) Advanced Technology Demonstration...While this combination is less optimal over disadvantaged networks, and we do not recommend it there, TCP and TLS perform adequately over networks with

Five Years of BEACO2N: First Results and Lessons Learned

NASA Astrophysics Data System (ADS)

Shusterman, A.; Cohen, R. C.

2017-12-01

The BErkeley Atmospheric CO2 Observation Network (BEACO2N) is an ongoing greenhouse gas and air quality monitoring campaign based in the San Francisco Bay Area of Northern California. BEACO2N is a distributed network instrument consisting of low- to moderate-cost commercial sensors for CO2 and other pollutants installed on top of schools, museums, and other outreach-minded institutions. The reduced cost of each individual sensor "node" enables the deployment of a larger volume of total nodes, resulting in a web of approximately 50 sites with an average node-to-node distance of 2 km. Operating in some variation of this configuration since 2012, BEACO2N offers greater spatio-temporal coverage than any other fixed CO2 monitoring network to date. This high-resolution information allows us to faithfully represent the true heterogeneity of urban emission processes and distinguish between specific sources that are often regulated independently, but typically treated en masse by sparser, conventional surface monitors. However, maintaining and appropriately interpreting a network of BEACO2N's size presents a number of unique data quality and data coverage challenges. Here we describe the quantitative capabilities of the BEACO2N platform, first results from initial attempts at constraining greenhouse gas emission estimates, as well as other lessons learned over the first five years of operation.

An ontology for sensor networks

NASA Astrophysics Data System (ADS)

Compton, Michael; Neuhaus, Holger; Bermudez, Luis; Cox, Simon

2010-05-01

Sensors and networks of sensors are important ways of monitoring and digitizing reality. As the number and size of sensor networks grows, so too does the amount of data collected. Users of such networks typically need to discover the sensors and data that fit their needs without necessarily understanding the complexities of the network itself. The burden on users is eased if the network and its data are expressed in terms of concepts familiar to the users and their job functions, rather than in terms of the network or how it was designed. Furthermore, the task of collecting and combining data from multiple sensor networks is made easier if metadata about the data and the networks is stored in a format and conceptual models that is amenable to machine reasoning and inference. While the OGC's (Open Geospatial Consortium) SWE (Sensor Web Enablement) standards provide for the description and access to data and metadata for sensors, they do not provide facilities for abstraction, categorization, and reasoning consistent with standard technologies. Once sensors and networks are described using rich semantics (that is, by using logic to describe the sensors, the domain of interest, and the measurements) then reasoning and classification can be used to analyse and categorise data, relate measurements with similar information content, and manage, query and task sensors. This will enable types of automated processing and logical assurance built on OGC standards. The W3C SSN-XG (Semantic Sensor Networks Incubator Group) is producing a generic ontology to describe sensors, their environment and the measurements they make. The ontology provides definitions for the structure of sensors and observations, leaving the details of the observed domain unspecified. This allows abstract representations of real world entities, which are not observed directly but through their observable qualities. Domain semantics, units of measurement, time and time series, and location and mobility ontologies can be easily attached when instantiating the ontology for any particular sensors in a domain. After a review of previous work on the specification of sensors, the group is developing the ontology in conjunction with use case development. Part of the difficulty of such work is that relevant concepts from for example OGC standards and other ontologies must be identified and aligned and also placed in a consistent and logically correct way into the ontology. In terms of alignment with OGC's SWE, the ontology is intended to be able to model concepts from SensorML and O&M. Similar to SensorML and O&M, the ontology is based around concepts of systems, processes, and observations. It supports the description of the physical and processing structure of sensors. Sensors are not constrained to physical sensing devices: rather a sensor is anything that can estimate or calculate the value of a phenomenon, so a device or computational process or combination could play the role of a sensor. The representation of a sensor in the ontology links together what is measured (the domain phenomena), the sensor's physical and other properties and its functions and processing. Parts of the ontology are well aligned with SensorML and O&M, but parts are not, and the group is working to understand how differences from (and alignment with) the OGC standards affect the application of the ontology.

Energy-aware scheduling of surveillance in wireless multimedia sensor networks.

PubMed

Wang, Xue; Wang, Sheng; Ma, Junjie; Sun, Xinyao

2010-01-01

Wireless sensor networks involve a large number of sensor nodes with limited energy supply, which impacts the behavior of their application. In wireless multimedia sensor networks, sensor nodes are equipped with audio and visual information collection modules. Multimedia contents are ubiquitously retrieved in surveillance applications. To solve the energy problems during target surveillance with wireless multimedia sensor networks, an energy-aware sensor scheduling method is proposed in this paper. Sensor nodes which acquire acoustic signals are deployed randomly in the sensing fields. Target localization is based on the signal energy feature provided by multiple sensor nodes, employing particle swarm optimization (PSO). During the target surveillance procedure, sensor nodes are adaptively grouped in a totally distributed manner. Specially, the target motion information is extracted by a forecasting algorithm, which is based on the hidden Markov model (HMM). The forecasting results are utilized to awaken sensor node in the vicinity of future target position. According to the two properties, signal energy feature and residual energy, the sensor nodes decide whether to participate in target detection separately with a fuzzy control approach. Meanwhile, the local routing scheme of data transmission towards the observer is discussed. Experimental results demonstrate the efficiency of energy-aware scheduling of surveillance in wireless multimedia sensor network, where significant energy saving is achieved by the sensor awakening approach and data transmission paths are calculated with low computational complexity.

The Use of Neural Networks in Identifying Error Sources in Satellite-Derived Tropical SST Estimates

PubMed Central

Lee, Yung-Hsiang; Ho, Chung-Ru; Su, Feng-Chun; Kuo, Nan-Jung; Cheng, Yu-Hsin

2011-01-01

An neural network model of data mining is used to identify error sources in satellite-derived tropical sea surface temperature (SST) estimates from thermal infrared sensors onboard the Geostationary Operational Environmental Satellite (GOES). By using the Back Propagation Network (BPN) algorithm, it is found that air temperature, relative humidity, and wind speed variation are the major factors causing the errors of GOES SST products in the tropical Pacific. The accuracy of SST estimates is also improved by the model. The root mean square error (RMSE) for the daily SST estimate is reduced from 0.58 K to 0.38 K and mean absolute percentage error (MAPE) is 1.03%. For the hourly mean SST estimate, its RMSE is also reduced from 0.66 K to 0.44 K and the MAPE is 1.3%. PMID:22164030

Using Reputation Systems and Non-Deterministic Routing to Secure Wireless Sensor Networks

PubMed Central

Moya, José M.; Vallejo, Juan Carlos; Fraga, David; Araujo, Álvaro; Villanueva, Daniel; de Goyeneche, Juan-Mariano

2009-01-01

Security in wireless sensor networks is difficult to achieve because of the resource limitations of the sensor nodes. We propose a trust-based decision framework for wireless sensor networks coupled with a non-deterministic routing protocol. Both provide a mechanism to effectively detect and confine common attacks, and, unlike previous approaches, allow bad reputation feedback to the network. This approach has been extensively simulated, obtaining good results, even for unrealistically complex attack scenarios. PMID:22412345

Modelling the Energy Efficient Sensor Nodes for Wireless Sensor Networks

NASA Astrophysics Data System (ADS)

Dahiya, R.; Arora, A. K.; Singh, V. R.

2015-09-01

Energy is an important requirement of wireless sensor networks for better performance. A widely employed energy-saving technique is to place nodes in sleep mode, corresponding to low-power consumption as well as to reduce operational capabilities. In this paper, Markov model of a sensor network is developed. The node is considered to enter a sleep mode. This model is used to investigate the system performance in terms of energy consumption, network capacity and data delivery delay.

Distributed Localization of Active Transmitters in a Wireless Sensor Network

DTIC Science & Technology

2012-03-01

Distributed Localization of Active Transmitters in a Wireless Sensor Network THESIS Oba L. Vincent, 2nd Lieutenant, USAF AFIT/GE/ENG/12-41 DEPARTMENT...protection in the United States. AFIT/GE/ENG/12-41 Distributed Localization of Active Transmitters in a Wireless Sensor Network THESIS Presented to the...Transmitters in a Wireless Sensor Network Oba L. Vincent, B.S.E.E. 2nd Lieutenant, USAF Approved: /signed/ 29 Feb 2012 Maj. Mark D. Silvius, Ph.D. (Chairman

A Study on Wireless Charging for Prolonging the Lifetime of Wireless Sensor Networks

PubMed Central

Tu, Weijian; Xu, Xianghua; Ye, Tingcong; Cheng, Zongmao

2017-01-01

Wireless charging is an important issue in wireless sensor networks, since it can provide an emerging and effective solution in the absence of other power supplies. The state-of-the-art methods employ a mobile car and a predefined moving path to charge the sensor nodes in the network. Previous studies only consider a factor of the network (i.e., residual energy of sensor node) as a constraint to design the wireless charging strategy. However, other factors, such as the travelled distance of the mobile car, can also affect the effectiveness of wireless charging strategy. In this work, we study wireless charging strategy based on the analysis of a combination of two factors, including the residual energy of sensor nodes and the travelled distance of the charging car. Firstly, we theoretically analyze the limited size of the sensor network to match the capability of a charging car. Then, the networked factors are selected as the weights of traveling salesman problem (TSP) to design the moving path of the charging car. Thirdly, the charging time of each sensor node is computed based on the linear programming problem for the charging car. Finally, a charging period for the network is studied. The experimental results show that the proposed approach can significantly maximize the lifetime of the wireless sensor network. PMID:28677639

Multi-Domain SDN Survivability for Agricultural Wireless Sensor Networks.

PubMed

Huang, Tao; Yan, Siyu; Yang, Fan; Liu, Jiang

2016-11-06

Wireless sensor networks (WSNs) have been widely applied in agriculture field; meanwhile, the advent of multi-domain software-defined networks (SDNs) have improved the wireless resource utilization rate and strengthened network management. In recent times, multi-domain SDNs have been applied to agricultural sensor networks, namely multi-domain software-defined wireless sensor networks (SDWSNs). However, when the SDNs controlling agriculture networks suddenly become unavailable, whether intra-domain or inter-domain, sensor network communication is abnormal because of the loss of control. Moreover, there are controller and switch info-updating problems even if the controller becomes available again. To resolve these problems, this paper proposes a new approach based on an Open vSwitch extension for multi-domain SDWSNs, which can enhance agriculture network survivability and stability. We achieved this by designing a connection-state mechanism, a communication mechanism on both L2 and L3, and an info-updating mechanism based on Open vSwitch. The experimental results show that, whether it is agricultural inter-domain or intra-domain during the controller failure period, the sensor switches can enter failure recovery mode as soon as possible so that the sensor network keeps a stable throughput, a short failure recovery time below 300 ms, and low packet loss. Further, the domain can smoothly control the domain network again once the controller becomes available. This approach based on an Open vSwitch extension can enhance the survivability and stability of multi-domain SDWSNs in precision agriculture.

Multi-Domain SDN Survivability for Agricultural Wireless Sensor Networks

PubMed Central

Huang, Tao; Yan, Siyu; Yang, Fan; Liu, Jiang

2016-01-01

Wireless sensor networks (WSNs) have been widely applied in agriculture field; meanwhile, the advent of multi-domain software-defined networks (SDNs) have improved the wireless resource utilization rate and strengthened network management. In recent times, multi-domain SDNs have been applied to agricultural sensor networks, namely multi-domain software-defined wireless sensor networks (SDWSNs). However, when the SDNs controlling agriculture networks suddenly become unavailable, whether intra-domain or inter-domain, sensor network communication is abnormal because of the loss of control. Moreover, there are controller and switch info-updating problems even if the controller becomes available again. To resolve these problems, this paper proposes a new approach based on an Open vSwitch extension for multi-domain SDWSNs, which can enhance agriculture network survivability and stability. We achieved this by designing a connection-state mechanism, a communication mechanism on both L2 and L3, and an info-updating mechanism based on Open vSwitch. The experimental results show that, whether it is agricultural inter-domain or intra-domain during the controller failure period, the sensor switches can enter failure recovery mode as soon as possible so that the sensor network keeps a stable throughput, a short failure recovery time below 300 ms, and low packet loss. Further, the domain can smoothly control the domain network again once the controller becomes available. This approach based on an Open vSwitch extension can enhance the survivability and stability of multi-domain SDWSNs in precision agriculture. PMID:27827971

An Outline of Data Aggregation Security in Heterogeneous Wireless Sensor Networks

PubMed Central

Boubiche, Sabrina; Boubiche, Djallel Eddine; Bilami, Azzedine; Toral-Cruz, Homero

2016-01-01

Data aggregation processes aim to reduce the amount of exchanged data in wireless sensor networks and consequently minimize the packet overhead and optimize energy efficiency. Securing the data aggregation process is a real challenge since the aggregation nodes must access the relayed data to apply the aggregation functions. The data aggregation security problem has been widely addressed in classical homogeneous wireless sensor networks, however, most of the proposed security protocols cannot guarantee a high level of security since the sensor node resources are limited. Heterogeneous wireless sensor networks have recently emerged as a new wireless sensor network category which expands the sensor nodes’ resources and capabilities. These new kinds of WSNs have opened new research opportunities where security represents a most attractive area. Indeed, robust and high security level algorithms can be used to secure the data aggregation at the heterogeneous aggregation nodes which is impossible in classical homogeneous WSNs. Contrary to the homogeneous sensor networks, the data aggregation security problem is still not sufficiently covered and the proposed data aggregation security protocols are numberless. To address this recent research area, this paper describes the data aggregation security problem in heterogeneous wireless sensor networks and surveys a few proposed security protocols. A classification and evaluation of the existing protocols is also introduced based on the adopted data aggregation security approach. PMID:27077866

Real-Time Adaptation of Decision Thresholds in Sensor Networks for Detection of Moving Targets (PREPRINT)

DTIC Science & Technology

2010-01-01

target kinematics for multiple sensor detections is referred to as the track - before - detect strategy, and is commonly adopted in multi-sensor surveillance...of moving targets. Wettergren [4] presented an application of track - before - detect strategies to undersea distributed sensor networks. In de- signing...the deployment of a distributed passive sensor network that employs this track - before - detect procedure, it is impera- tive that the placement of

ADAPTable Sensor Systems Phase 2. Topic 2: Reusable Core Software. Distributed Synchronization Software for the Sensor Nodes

DTIC Science & Technology

2015-03-01

Wireless Sensor Network Using Unreliable GPS Signals Daniel R. Fuhrmann*, Joshua Stomberg§, Saeid Nooshabadi*§ Dustin McIntire†, William Merill... wireless sensor network , when the timing jitter is subject to a empirically determined bimodal non-Gaussian distribution. Specifically, we 1) estimate the...over a nominal 19.2 MHz frequency with an adjustment made every four hours. Index Terms— clock synchronization, GPS, wireless sensor networks , Kalman

Automotive Airbag Safety Enhancement Final Report CRADA No. TSB-1165-95

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

Cutting, Jack; Durrell, Robert

The Vehicle Safety systems (VSS) Division of Quantic Industries, Inc. (QII) manufactured automotive airbag components. When both the driver and the passenger side airbags inflated in a tightly sealed passenger compartment, the compression of the surrounding air could and, in some instances, would cause damage to the eardrums of the occupants. The Aerospace and Division (ADD) of QII had partially developed the technology to fracture the canopy of a jet aircraft at the time of pilot ejection. The technical problem was how to adapt the canopy fracturing technology to the rear window of a motor vehicle in a safe andmore » cost effective manner. The existing approach was to replace the embedded rear window defroster with a series-parallel network of exploding bridge wires (EBWs). This would still provide the defrost function at low voltage/ current, but would cause fracturing of the window when a high current/voltage pulse was applied without pyrotechnics or explosives. The elements of this system were the embedded EBW network and a trunk-mounted fireset. The fireset would store the required energy to fire the network upon the receipt of a trigger signal from the existing air bag crash sensor.« less

The resilient hybrid fiber sensor network with self-healing function

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

Xu, Shibo, E-mail: Shibo-Xu@tju.edu.cn; Liu, Tiegen; Ge, Chunfeng

This paper presents a novel resilient fiber sensor network (FSN) with multi-ring architecture, which could interconnect various kinds of fiber sensors responsible for more than one measurands. We explain how the intelligent control system provides sensors with self-healing function meanwhile sensors are working properly, besides each fiber in FSN is under real-time monitoring. We explain the software process and emergency mechanism to respond failures or other circumstances. To improve the efficiency in the use of limited spectrum resources in some situations, we have two different structures to distribute the light sources rationally. Then, we propose a hybrid sensor working inmore » FSN which is a combination of a distributed sensor and a FBG (Fiber Bragg Grating) array fused in a common fiber sensing temperature and vibrations simultaneously with neglectable crosstalk to each other. By making a failure to a working fiber in experiment, the feasibility and effectiveness of the network with a hybrid sensor has been demonstrated, hybrid sensors could not only work as designed but also survive from destructive failures with the help of resilient network and smart and quick self-healing actions. The network has improved the viability of the fiber sensors and diversity of measurands.« less

Optimization of Self-Directed Target Coverage in Wireless Multimedia Sensor Network

PubMed Central

Yang, Yang; Wang, Yufei; Pi, Dechang; Wang, Ruchuan

2014-01-01

Video and image sensors in wireless multimedia sensor networks (WMSNs) have directed view and limited sensing angle. So the methods to solve target coverage problem for traditional sensor networks, which use circle sensing model, are not suitable for WMSNs. Based on the FoV (field of view) sensing model and FoV disk model proposed, how expected multimedia sensor covers the target is defined by the deflection angle between target and the sensor's current orientation and the distance between target and the sensor. Then target coverage optimization algorithms based on expected coverage value are presented for single-sensor single-target, multisensor single-target, and single-sensor multitargets problems distinguishingly. Selecting the orientation that sensor rotated to cover every target falling in the FoV disk of that sensor for candidate orientations and using genetic algorithm to multisensor multitargets problem, which has NP-complete complexity, then result in the approximated minimum subset of sensors which covers all the targets in networks. Simulation results show the algorithm's performance and the effect of number of targets on the resulting subset. PMID:25136667

Research on trust calculation of wireless sensor networks based on time segmentation

NASA Astrophysics Data System (ADS)

Su, Yaoxin; Gao, Xiufeng; Qiao, Wenxin

2017-05-01

Because the wireless sensor network is different from the traditional network characteristics, it is easy to accept the intrusion from the compromise node. The trust mechanism is the most effective way to defend against internal attacks. Aiming at the shortcomings of the existing trust mechanism, a method of calculating the trust of wireless sensor networks based on time segmentation is proposed. It improves the security of the network and extends the life of the network

A comprehensive survey of energy-aware routing protocols in wireless body area sensor networks.

PubMed

Effatparvar, Mehdi; Dehghan, Mehdi; Rahmani, Amir Masoud

2016-09-01

Wireless body area sensor network is a special purpose wireless sensor network that, employing wireless sensor nodes in, on, or around the human body, makes it possible to measure biological parameters of a person for specific applications. One of the most fundamental concerns in wireless body sensor networks is accurate routing in order to send data promptly and properly, and therefore overcome some of the challenges. Routing protocols for such networks are affected by a large number of factors including energy, topology, temperature, posture, the radio range of sensors, and appropriate quality of service in sensor nodes. Since energy is highly important in wireless body area sensor networks, and increasing the network lifetime results in benefiting greatly from sensor capabilities, improving routing performance with reduced energy consumption presents a major challenge. This paper aims to study wireless body area sensor networks and the related routing methods. It also presents a thorough, comprehensive review of routing methods in wireless body area sensor networks from the perspective of energy. Furthermore, different routing methods affecting the parameter of energy will be classified and compared according to their advantages and disadvantages. In this paper, fundamental concepts of wireless body area sensor networks are provided, and then the advantages and disadvantages of these networks are investigated. Since one of the most fundamental issues in wireless body sensor networks is to perform routing so as to transmit data precisely and promptly, we discuss the same issue. As a result, we propose a classification of the available relevant literature with respect to the key challenge of energy in the routing process. With this end in view, all important papers published between 2000 and 2015 are classified under eight categories including 'Mobility-Aware', 'Thermal-Aware', 'Restriction of Location and Number of Relays', 'Link-aware', 'Cluster- and Tree-Based', 'Cross-Layer', 'Opportunistic', and 'Medium Access Control'. We, then, provide a full description of the statistical analysis of each category in relation to all papers, current hybrid protocols, and the type of simulators used in each paper. Next, we analyze the distribution of papers in each category during various years. Moreover, for each category, the advantages and disadvantages as well as the number of issued papers in different years are given. We also analyze the type of layer and deployment of mathematical models or algorithmic techniques in each category. Finally, after introducing certain important protocols for each category, the goals, advantages, and disadvantages of the protocols are discussed and compared with each other.

An Energy-Efficient and High-Quality Video Transmission Architecture in Wireless Video-Based Sensor Networks.

PubMed

Aghdasi, Hadi S; Abbaspour, Maghsoud; Moghadam, Mohsen Ebrahimi; Samei, Yasaman

2008-08-04

Technological progress in the fields of Micro Electro-Mechanical Systems (MEMS) and wireless communications and also the availability of CMOS cameras, microphones and small-scale array sensors, which may ubiquitously capture multimedia content from the field, have fostered the development of low-cost limited resources Wireless Video-based Sensor Networks (WVSN). With regards to the constraints of videobased sensor nodes and wireless sensor networks, a supporting video stream is not easy to implement with the present sensor network protocols. In this paper, a thorough architecture is presented for video transmission over WVSN called Energy-efficient and high-Quality Video transmission Architecture (EQV-Architecture). This architecture influences three layers of communication protocol stack and considers wireless video sensor nodes constraints like limited process and energy resources while video quality is preserved in the receiver side. Application, transport, and network layers are the layers in which the compression protocol, transport protocol, and routing protocol are proposed respectively, also a dropping scheme is presented in network layer. Simulation results over various environments with dissimilar conditions revealed the effectiveness of the architecture in improving the lifetime of the network as well as preserving the video quality.

A spectral profile multiplexed FBG sensor network with application to strain measurement in a Kevlar woven fabric

NASA Astrophysics Data System (ADS)

Guo, Guodong; Hackney, Drew; Pankow, Mark; Peters, Kara

2017-04-01

A spectral profile division multiplexed fiber Bragg grating (FBG) sensor network is described in this paper. The unique spectral profile of each sensor in the network is identified as a distinct feature to be interrogated. Spectrum overlap is allowed under working conditions. Thus, a specific wavelength window does not need to be allocated to each sensor as in a wavelength division multiplexed (WDM) network. When the sensors are serially connected in the network, the spectrum output is expressed through a truncated series. To track the wavelength shift of each sensor, the identification problem is transformed to a nonlinear optimization problem, which is then solved by a modified dynamic multi-swarm particle swarm optimizer (DMS-PSO). To demonstrate the application of the developed network, a network consisting of four FBGs was integrated into a Kevlar woven fabric, which was under a quasi-static load imposed by an impactor head. Due to the substantial radial strain in the fabric, the spectrums of different FBGs were found to overlap during the loading process. With the developed interrogating method, the overlapped spectrum would be distinguished thus the wavelength shift of each sensor can be monitored.

Sensor networks in the low lands.

PubMed

Meratnia, Nirvana; van der Zwaag, Berend Jan; van Dijk, Hylke W; Bijwaard, Dennis J A; Havinga, Paul J M

2010-01-01

This paper provides an overview of scientific and industrial developments of the last decade in the area of sensor networks in The Netherlands (Low Lands). The goal is to highlight areas in which the Netherlands has made most contributions and is currently a dominant player in the field of sensor networks. On the one hand, motivations, addressed topics, and initiatives taken in this period are presented, while on the other hand, special emphasis is given to identifying current and future trends and formulating a vision for the coming five to ten years. The presented overview and trend analysis clearly show that Dutch research and industrial efforts, in line with recent worldwide developments in the field of sensor technology, present a clear shift from sensor node platforms, operating systems, communication, networking, and data management aspects of the sensor networks to reasoning/cognition, control, and actuation.

Embedded Electro-Optic Sensor Network for the On-Site Calibration and Real-Time Performance Monitoring of Large-Scale Phased Arrays

DTIC Science & Technology

2005-07-09

This final report summarizes the progress during the Phase I SBIR project entitled Embedded Electro - Optic Sensor Network for the On-Site Calibration...network based on an electro - optic field-detection technique (the Electro - optic Sensor Network, or ESN) for the performance evaluation of phased

Implementing Remote Image Capture/Control in a Wireless Sensor Network Utilizing the IEEE 802.15.4 Standard

DTIC Science & Technology

2009-09-01

with the flexibility provided by a wireless sensor network , could provide such enhancements. The objective of this research was to explore the...feasibility of remote management and control of a low-power/low-cost wireless sensor network by implementing a point-to-point wireless network utilizing IEEE

WebDMS: A Web-Based Data Management System for Environmental Data

NASA Astrophysics Data System (ADS)

Ekstrand, A. L.; Haderman, M.; Chan, A.; Dye, T.; White, J. E.; Parajon, G.

2015-12-01

DMS is an environmental Data Management System to manage, quality-control (QC), summarize, document chain-of-custody, and disseminate data from networks ranging in size from a few sites to thousands of sites, instruments, and sensors. The server-client desktop version of DMS is used by local and regional air quality agencies (including the Bay Area Air Quality Management District, the South Coast Air Quality Management District, and the California Air Resources Board), the EPA's AirNow Program, and the EPA's AirNow-International (AirNow-I) program, which offers countries the ability to run an AirNow-like system. As AirNow's core data processing engine, DMS ingests, QCs, and stores real-time data from over 30,000 active sensors at over 5,280 air quality and meteorological sites from over 130 air quality agencies across the United States. As part of the AirNow-I program, several instances of DMS are deployed in China, Mexico, and Taiwan. The U.S. Department of State's StateAir Program also uses DMS for five regions in China and plans to expand to other countries in the future. Recent development has begun to migrate DMS from an onsite desktop application to WebDMS, a web-based application designed to take advantage of cloud hosting and computing services to increase scalability and lower costs. WebDMS will continue to provide easy-to-use data analysis tools, such as time-series graphs, scatterplots, and wind- or pollution-rose diagrams, as well as allowing data to be exported to external systems such as the EPA's Air Quality System (AQS). WebDMS will also provide new GIS analysis features and a suite of web services through a RESTful web API. These changes will better meet air agency needs and allow for broader national and international use (for example, by the AirNow-I partners). We will talk about the challenges and advantages of migrating DMS to the web, modernizing the DMS user interface, and making it more cost-effective to enhance and maintain over time.

77 FR 11789 - Airworthiness Directives; The Boeing Company Airplanes

Federal Register 2010, 2011, 2012, 2013, 2014

2012-02-28

...-icing system for the angle of attack sensor, the total air temperature, and the pitot probes. We are proposing this AD to prevent ice from forming on air data system sensors and consequent loss of or... receive about this proposed AD. Discussion The air data sensor heating system, when ON, heats the pitot...

77 FR 73282 - Airworthiness Directives; The Boeing Company Airplanes

Federal Register 2010, 2011, 2012, 2013, 2014

2012-12-10

... system for the angle of attack sensor, the total air temperature, and the pitot probes. We are issuing this AD to prevent ice from forming on air data system sensors and consequent loss of or misleading... angle of attack sensor, the total air temperature, and the pitot probes. Actions Since Issuance of NPRM...

Low-Cost Fiber Optic Pressure Sensor

DOEpatents

Sheem, Sang K.

2004-05-18

The size and cost of fabricating fiber optic pressure sensors is reduced by fabricating the membrane of the sensor in a non-planar shape. The design of the sensors may be made in such a way that the non-planar membrane becomes a part of an air-tight cavity, so as to make the membrane resilient due to the air-cushion effect of the air-tight cavity. Such non-planar membranes are easier to make and attach.

Low-Cost Fiber Optic Pressure Sensor

DOEpatents

Sheem, Sang K.

2003-07-22

The size and cost of fabricating fiber optic pressure sensors is reduced by fabricating the membrane of the sensor in a non-planar shape. The design of the sensors may be made in such a way that the non-planar membrane becomes a part of an air-tight cavity, so as to make the membrane resilient due to the air-cushion effect of the air-tight cavity. Such non-planar membranes are easier to make and attach.

Automated Data Quality Assurance using OGC Sensor Web Enablement Frameworks for Marine Observatories

NASA Astrophysics Data System (ADS)

Toma, Daniel; Bghiel, Ikram; del Rio, Joaquin; Hidalgo, Alberto; Carreras, Normandino; Manuel, Antoni

2014-05-01

Over the past years, environmental sensors have continuously improved by becoming smaller, cheaper, and more intelligent. Therefore, many sensor networks are increasingly deployed to monitor our environment. But due to the large number of sensor manufacturers, accompanying protocols and data encoding, automated integration and data quality assurance of diverse sensors in an observing systems is not straightforward, requiring development of data management code and manual tedious configuration. However, over the past few years it has been demonstrated that Open-Geospatial Consortium (OGC) frameworks can enable web services with fully-described sensor systems, including data processing, sensor characteristics and quality control tests and results. So far, the SWE framework does not describe how to integrate sensors on-the-fly with minimal human intervention. The data management software which enables access to sensors, data processing and quality control tests has to be implemented and the results have to be manually mapped to the SWE models. In this contribution, we describe a Sensor Plug & Play infrastructure for the Sensor Web by combining (1) OGC PUCK protocol - a simple standard embedded instrument protocol to store and retrieve directly from the devices the declarative description of sensor characteristics and quality control tests, (2) an automatic mechanism for data processing and quality control tests underlying the Sensor Web - the Sensor Interface Descriptor (SID) concept, as well as (3) a model for the declarative description of sensor which serves as a generic data management mechanism - designed as a profile and extension of OGC SWE's SensorML standard. We implement and evaluate our approach by applying it to the OBSEA Observatory, and can be used to demonstrate the ability to assess data quality for temperature, salinity, air pressure and wind speed and direction observations off the coast of Garraf, in the north-eastern Spain.

Sensor Location Problem Optimization for Traffic Network with Different Spatial Distributions of Traffic Information.

PubMed

Bao, Xu; Li, Haijian; Qin, Lingqiao; Xu, Dongwei; Ran, Bin; Rong, Jian

2016-10-27

To obtain adequate traffic information, the density of traffic sensors should be sufficiently high to cover the entire transportation network. However, deploying sensors densely over the entire network may not be realistic for practical applications due to the budgetary constraints of traffic management agencies. This paper describes several possible spatial distributions of traffic information credibility and proposes corresponding different sensor information credibility functions to describe these spatial distribution properties. A maximum benefit model and its simplified model are proposed to solve the traffic sensor location problem. The relationships between the benefit and the number of sensors are formulated with different sensor information credibility functions. Next, expanding models and algorithms in analytic results are performed. For each case, the maximum benefit, the optimal number and spacing of sensors are obtained and the analytic formulations of the optimal sensor locations are derived as well. Finally, a numerical example is proposed to verify the validity and availability of the proposed models for solving a network sensor location problem. The results show that the optimal number of sensors of segments with different model parameters in an entire freeway network can be calculated. Besides, it can also be concluded that the optimal sensor spacing is independent of end restrictions but dependent on the values of model parameters that represent the physical conditions of sensors and roads.

Sensor Location Problem Optimization for Traffic Network with Different Spatial Distributions of Traffic Information

PubMed Central

Bao, Xu; Li, Haijian; Qin, Lingqiao; Xu, Dongwei; Ran, Bin; Rong, Jian

2016-01-01

To obtain adequate traffic information, the density of traffic sensors should be sufficiently high to cover the entire transportation network. However, deploying sensors densely over the entire network may not be realistic for practical applications due to the budgetary constraints of traffic management agencies. This paper describes several possible spatial distributions of traffic information credibility and proposes corresponding different sensor information credibility functions to describe these spatial distribution properties. A maximum benefit model and its simplified model are proposed to solve the traffic sensor location problem. The relationships between the benefit and the number of sensors are formulated with different sensor information credibility functions. Next, expanding models and algorithms in analytic results are performed. For each case, the maximum benefit, the optimal number and spacing of sensors are obtained and the analytic formulations of the optimal sensor locations are derived as well. Finally, a numerical example is proposed to verify the validity and availability of the proposed models for solving a network sensor location problem. The results show that the optimal number of sensors of segments with different model parameters in an entire freeway network can be calculated. Besides, it can also be concluded that the optimal sensor spacing is independent of end restrictions but dependent on the values of model parameters that represent the physical conditions of sensors and roads. PMID:27801794

Temperature and Humidity Calibration of a Low-Cost Wireless Dust Sensor for Real-Time Monitoring.

PubMed

Hojaiji, Hannaneh; Kalantarian, Haik; Bui, Alex A T; King, Christine E; Sarrafzadeh, Majid

2017-03-01

This paper introduces the design, calibration, and validation of a low-cost portable sensor for the real-time measurement of dust particles within the environment. The proposed design consists of low hardware cost and calibration based on temperature and humidity sensing to achieve accurate processing of airborne dust density. Using commercial particulate matter sensors, a highly accurate air quality monitoring sensor was designed and calibrated using real world variations in humidity and temperature for indoor and outdoor applications. Furthermore, to provide a low-cost secure solution for real-time data transfer and monitoring, an onboard Bluetooth module with AES data encryption protocol was implemented. The wireless sensor was tested against a Dylos DC1100 Pro Air Quality Monitor, as well as an Alphasense OPC-N2 optical air quality monitoring sensor for accuracy. The sensor was also tested for reliability by comparing the sensor to an exact copy of itself under indoor and outdoor conditions. It was found that accurate measurements under real-world humid and temperature varying and dynamically changing conditions were achievable using the proposed sensor when compared to the commercially available sensors. In addition to accurate and reliable sensing, this sensor was designed to be wearable and perform real-time data collection and transmission, making it easy to collect and analyze data for air quality monitoring and real-time feedback in remote health monitoring applications. Thus, the proposed device achieves high quality measurements at lower-cost solutions than commercially available wireless sensors for air quality.

What is in my air? Feds facilitating citizen science in the EPA Next Generation Air Monitoring Program

NASA Astrophysics Data System (ADS)

French, R. A.; Preuss, P.

2013-12-01

Recent advances in the development of small-scale and inexpensive air pollutant sensors, coupled with the ubiquitous use of wireless and mobile technology, will transform the field of air quality monitoring. For the first time, the general public may purchase air monitors, which can measure their personal exposure to NOx, Ozone, black carbon, and VOCs for a few hundred dollars. Concerned citizens may now gather the data for themselves to answer questions such as, ';what am I breathing?' and ';is my air clean?' The research and policy community will have access to real-time air quality data collected at the local and regional scale, making targeted protection of environmental health possible. With these benefits come many questions from citizen scientists, policymakers, and researchers. These include, what is the quality of the data? How will the public interpret data from the air sensors and are there guidelines to interpret that data? How do you know if the air sensor is trustworthy? Recognizing that this revolution in air quality monitoring will proceed regardless of the involvement of the government, the Innovation Team at the EPA Office of Research and Development, in partnership with the Office of Enforcement and Compliance Assistance and the Office of Air and Radiation, seized the opportunity to ensure that users of next generation air sensors can realize the full potential benefits of these innovative technologies. These efforts include releasing an EPA Draft Roadmap for Next Generation Air Monitoring, testing air sensors under laboratory and field conditions, field demonstrations of new air sensor technology for the public, and building a community of air sensor developers, researchers, local, state and federal officials, and community members through workshops and a website. This presentation will review the status of those programs, highlighting the particular programs of interest to citizen scientists. The Next Generation Air Monitoring program may serve as a model for similar efforts in the EPA and at other Federal Agencies, who would like to take an active role in facilitating the future of citizen science and environmental monitoring.

Bluetooth gas sensing module combined with smartphones for air quality monitoring.

PubMed

Suárez, José Ignacio; Arroyo, Patricia; Lozano, Jesús; Herrero, José Luis; Padilla, Manuel

2018-08-01

This study addresses the development of a miniaturized (60 × 60 mm) Wireless Sensing Module (WSM) for environmental application and air quality detection. The proposed prototype has six sensors: one for humidity, one for ambient temperature (SHT21 from Sensirion), and four for gas detection (MiCS-4514, MiCS-5526 and MiCS-5914 from SGX Sensortech). The core of the system is based on a high performance 8-bit microcontroller, model PIC18F46K80, from Microchip. The obtained data values were transmitted to the Smartphone through a Bluetooth communication module and a home-developed Android app. The discrimination capability of the module is tested with 10 volatile organic compounds (acetone, acetic acid, benzene, ethanol, ethyl acetate, ethylbenzene, formaldehyde, toluene, xylene, and dimethylacetamide) and the effect of humidity and drift of the sensors is also studied. Results show that 88.33% and 92.22% success rates in classification stage are obtained using Multilayer Perceptron with BackPropagation Learning algorithm and Radial-Basis based Neural Networks, respectively. Copyright © 2018 Elsevier Ltd. All rights reserved.

Wireless Sensor Network Based Subsurface Contaminant Plume Monitoring

DTIC Science & Technology

2012-04-16

Sensor Network (WSN) to monitor contaminant plume movement in naturally heterogeneous subsurface formations to advance the sensor networking based...time to assess the source and predict future plume behavior. This proof-of-concept research aimed at demonstrating the use of an intelligent Wireless

Traffic Profiling in Wireless Sensor Networks

DTIC Science & Technology

2006-12-01

components, that can be used for traffic profiling and monitoring of a wireless sensor network . The work demostrates how the IDS should capture and...observed and analyzed. Finally, initial indications from basic analysis of wireless sensor network traffic demonstrated a high degree of self-similarity.

Large Scale Environmental Monitoring through Integration of Sensor and Mesh Networks.

PubMed

Jurdak, Raja; Nafaa, Abdelhamid; Barbirato, Alessio

2008-11-24

Monitoring outdoor environments through networks of wireless sensors has received interest for collecting physical and chemical samples at high spatial and temporal scales. A central challenge to environmental monitoring applications of sensor networks is the short communication range of the sensor nodes, which increases the complexity and cost of monitoring commodities that are located in geographically spread areas. To address this issue, we propose a new communication architecture that integrates sensor networks with medium range wireless mesh networks, and provides users with an advanced web portal for managing sensed information in an integrated manner. Our architecture adopts a holistic approach targeted at improving the user experience by optimizing the system performance for handling data that originates at the sensors, traverses the mesh network, and resides at the server for user consumption. This holistic approach enables users to set high level policies that can adapt the resolution of information collected at the sensors, set the preferred performance targets for their application, and run a wide range of queries and analysis on both real-time and historical data. All system components and processes will be described in this paper.

Energy-efficient algorithm for classification of states of wireless sensor network using machine learning methods

NASA Astrophysics Data System (ADS)

Yuldashev, M. N.; Vlasov, A. I.; Novikov, A. N.

2018-05-01

This paper focuses on the development of an energy-efficient algorithm for classification of states of a wireless sensor network using machine learning methods. The proposed algorithm reduces energy consumption by: 1) elimination of monitoring of parameters that do not affect the state of the sensor network, 2) reduction of communication sessions over the network (the data are transmitted only if their values can affect the state of the sensor network). The studies of the proposed algorithm have shown that at classification accuracy close to 100%, the number of communication sessions can be reduced by 80%.

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

NASA Astrophysics Data System (ADS)

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

2016-12-01

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

The Robustness Analysis of Wireless Sensor Networks under Uncertain Interference

PubMed Central

Deng, Changjian

2013-01-01

Based on the complex network theory, robustness analysis of condition monitoring wireless sensor network under uncertain interference is present. In the evolution of the topology of sensor networks, the density weighted algebraic connectivity is taken into account, and the phenomenon of removing and repairing the link and node in the network is discussed. Numerical simulation is conducted to explore algebraic connectivity characteristics and network robustness performance. It is found that nodes density has the effect on algebraic connectivity distribution in the random graph model; high density nodes carry more connections, use more throughputs, and may be more unreliable. Moreover, the results show that, when network should be more error tolerant or robust by repairing nodes or adding new nodes, the network should be better clustered in median and high scale wireless sensor networks and be meshing topology in small scale networks. PMID:24363613

Wireless Networks under a Backoff Attack: A Game Theoretical Perspective

PubMed Central

Zazo, Santiago

2018-01-01

We study a wireless sensor network using CSMA/CA in the MAC layer under a backoff attack: some of the sensors of the network are malicious and deviate from the defined contention mechanism. We use Bianchi’s network model to study the impact of the malicious sensors on the total network throughput, showing that it causes the throughput to be unfairly distributed among sensors. We model this conflict using game theory tools, where each sensor is a player. We obtain analytical solutions and propose an algorithm, based on Regret Matching, to learn the equilibrium of the game with an arbitrary number of players. Our approach is validated via simulations, showing that our theoretical predictions adjust to reality. PMID:29385752

Quartz crystal microbalance biosensor for rapid detection of aerosolized microorganisms

NASA Astrophysics Data System (ADS)

Farka, Zdenĕk.; Kovár, David; Skládal, Petr

2015-05-01

Biological warfare agents (BWAs) represent the current menace of the asymmetric war. The early detection of BWAs, especially in the form of bioaerosol, is a challenging task for governments all around the world. Label-free quartz crystal microbalance (QCM) immunosensor and electrochemical immunosensor were developed and tested for rapid detection of BWA surrogate (E. coli) in the form of bioaerosol. Two immobilization strategies for the attachment of antibody were tested; the gold sensor surface was activated by cysteamine and then antibody was covalently linked either using glutaraldehyde, or the reduced antibodies were attached via Sulfo-SMCC. A portable bioaerosol chamber was constructed and used for safe manipulation with aerosolized microorganisms. The dissemination was done using a piezoelectric humidifier, distribution of bioaerosol inside the chamber was ensured using three 12-cm fans. The whole system was controlled remotely using LAN network. The disseminated microbial cells were collected and preconcentrated using the wetted-wall cyclone SASS 2300, the analysis was done using the on-line linked immunosensors. The QCM immunosensor had limit of detection 1×104 CFU·L-1 of air with analysis time 16 min, the whole experiment including dissemination and sensor surface regeneration took 40 min. In case of blank (disseminated sterile buffer), no signal change was observed. The electrochemical immunosensor was able to detect 150 CFU·L-1 of air in 20 min; also in this case, no interferences were observed. Reference measurements were done using particle counter Met One 3400 and by cultivation method on agar plates. The sensors have proved to be applicable for rapid screening of microorganisms in air.

An Expert System And Simulation Approach For Sensor Management & Control In A Distributed Surveillance Network

NASA Astrophysics Data System (ADS)

Leon, Barbara D.; Heller, Paul R.

1987-05-01

A surveillance network is a group of multiplatform sensors cooperating to improve network performance. Network control is distributed as a measure to decrease vulnerability to enemy threat. The network may contain diverse sensor types such as radar, ESM (Electronic Support Measures), IRST (Infrared search and track) and E-0 (Electro-Optical). Each platform may contain a single sensor or suite of sensors. In a surveillance network it is desirable to control sensors to make the overall system more effective. This problem has come to be known as sensor management and control (SM&C). Two major facets of network performance are surveillance and survivability. In a netted environment, surveillance can be enhanced if information from all sensors is combined and sensor operating conditions are controlled to provide a synergistic effect. In contrast, when survivability is the main concern for the network, the best operating status for all sensors would be passive or off. Of course, improving survivability tends to degrade surveillance. Hence, the objective of SM&C is to optimize surveillance and survivability of the network. Too voluminous data of various formats and the quick response time are two characteristics of this problem which make it an ideal application for Artificial Intelligence. A solution to the SM&C problem, presented as a computer simulation, will be presented in this paper. The simulation is a hybrid production written in LISP and FORTRAN. It combines the latest conventional computer programming methods with Artificial Intelligence techniques to produce a flexible state-of-the-art tool to evaluate network performance. The event-driven simulation contains environment models coupled with an expert system. These environment models include sensor (track-while-scan and agile beam) and target models, local tracking, and system tracking. These models are used to generate the environment for the sensor management and control expert system. The expert system, driven by a forward chaining inference engine, makes decisions based on the global database. The global database contains current track and sensor information supplied by the simulation. At present, the rule base emphasizes the surveillance features with rules grouped into three main categories: maintenance and enhancing track on prioritized targets; filling coverage holes and countering jamming; and evaluating sensor status. The paper will describe the architecture used for the expert system and the reasons for selecting the chosen methods. The SM&C simulation produces a graphical representation of sensors and their associated tracks such that the benefits of the sensor management and control expert system are evident. Jammer locations are also part of the display. The paper will describe results from several scenarios that best illustrate the sensor management and control concepts.

Barrow real-time sea ice mass balance data: ingestion, processing, dissemination and archival of multi-sensor data

NASA Astrophysics Data System (ADS)

Grimes, J.; Mahoney, A. R.; Heinrichs, T. A.; Eicken, H.

2012-12-01

Sensor data can be highly variable in nature and also varied depending on the physical quantity being observed, sensor hardware and sampling parameters. The sea ice mass balance site (MBS) operated in Barrow by the University of Alaska Fairbanks (http://seaice.alaska.edu/gi/observatories/barrow_sealevel) is a multisensor platform consisting of a thermistor string, air and water temperature sensors, acoustic altimeters above and below the ice and a humidity sensor. Each sensor has a unique specification and configuration. The data from multiple sensors are combined to generate sea ice data products. For example, ice thickness is calculated from the positions of the upper and lower ice surfaces, which are determined using data from downward-looking and upward-looking acoustic altimeters above and below the ice, respectively. As a data clearinghouse, the Geographic Information Network of Alaska (GINA) processes real time data from many sources, including the Barrow MBS. Doing so requires a system that is easy to use, yet also offers the flexibility to handle data from multisensor observing platforms. In the case of the Barrow MBS, the metadata system needs to accommodate the addition of new and retirement of old sensors from year to year as well as instrument configuration changes caused by, for example, spring melt or inquisitive polar bears. We also require ease of use for both administrators and end users. Here we present the data and processing steps of using sensor data system powered by the NoSQL storage engine, MongoDB. The system has been developed to ingest, process, disseminate and archive data from the Barrow MBS. Storing sensor data in a generalized format, from many different sources, is a challenging task, especially for traditional SQL databases with a set schema. MongoDB is a NoSQL (not only SQL) database that does not require a fixed schema. There are several advantages using this model over the traditional relational database management system (RDBMS) model databases. The lack of a required schema allows flexibility in how the data can be ingested into the database. For example, MongoDB imposes no restrictions on field names. For researchers using the system, this means that the name they have chosen for the sensor is carried through the database, any processing, and to the final output helping to preserve data integrity. Also, MongoDB allows the data to be pushed to it dynamically meaning that field attributes can be defined at the point of ingestion. This allows any sensor data to be ingested as a document and for this functionality to be transferred to the user interface, allowing greater adaptability to different use-case scenarios. In presenting the MondoDB data system being developed for the Barrow MBS, we demonstrate the versatility of this approach and its suitability as the foundation of a Barrow node of the Arctic Observing Network. Authors Jason Grimes - Geographic Information Network of Alaska - jason@gina.alaska.edu Andy Mahony - Geophysical Institute - mahoney@gi.alaska.edu Hajo Eiken - Geophysical Institute - Hajo.Eicken@gi.alaska.edu Tom Heinrichs - Geographic Information Network of Alaska - Tom.Heinrichs@alaska.edu

Consistent Steering System using SCTP for Bluetooth Scatternet Sensor Network

NASA Astrophysics Data System (ADS)

Dhaya, R.; Sadasivam, V.; Kanthavel, R.

2012-12-01

Wireless communication is the best way to convey information from source to destination with flexibility and mobility and Bluetooth is the wireless technology suitable for short distance. On the other hand a wireless sensor network (WSN) consists of spatially distributed autonomous sensors to cooperatively monitor physical or environmental conditions, such as temperature, sound, vibration, pressure, motion or pollutants. Using Bluetooth piconet wireless technique in sensor nodes creates limitation in network depth and placement. The introduction of Scatternet solves the network restrictions with lack of reliability in data transmission. When the depth of the network increases, it results in more difficulties in routing. No authors so far focused on the reliability factors of Scatternet sensor network's routing. This paper illustrates the proposed system architecture and routing mechanism to increase the reliability. The another objective is to use reliable transport protocol that uses the multi-homing concept and supports multiple streams to prevent head-of-line blocking. The results show that the Scatternet sensor network has lower packet loss even in the congestive environment than the existing system suitable for all surveillance applications.

Wireless Sensors Network (Sensornet)

NASA Technical Reports Server (NTRS)

Perotti, J.

2003-01-01

The Wireless Sensor Network System presented in this paper provides a flexible reconfigurable architecture that could be used in a broad range of applications. It also provides a sensor network with increased reliability; decreased maintainability costs, and assured data availability by autonomously and automatically reconfiguring to overcome communication interferences.

Low-power wireless ECG acquisition and classification system for body sensor networks.

PubMed

Lee, Shuenn-Yuh; Hong, Jia-Hua; Hsieh, Cheng-Han; Liang, Ming-Chun; Chang Chien, Shih-Yu; Lin, Kuang-Hao

2015-01-01

A low-power biosignal acquisition and classification system for body sensor networks is proposed. The proposed system consists of three main parts: 1) a high-pass sigma delta modulator-based biosignal processor (BSP) for signal acquisition and digitization, 2) a low-power, super-regenerative on-off keying transceiver for short-range wireless transmission, and 3) a digital signal processor (DSP) for electrocardiogram (ECG) classification. The BSP and transmitter circuits, which are the body-end circuits, can be operated for over 80 days using two 605 mAH zinc-air batteries as the power supply; the power consumption is 586.5 μW. As for the radio frequency receiver and DSP, which are the receiving-end circuits that can be integrated in smartphones or personal computers, power consumption is less than 1 mW. With a wavelet transform-based digital signal processing circuit and a diagnosis control by cardiologists, the accuracy of beat detection and ECG classification are close to 99.44% and 97.25%, respectively. All chips are fabricated in TSMC 0.18-μm standard CMOS process.

On computer vision in wireless sensor networks.

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

Berry, Nina M.; Ko, Teresa H.

Wireless sensor networks allow detailed sensing of otherwise unknown and inaccessible environments. While it would be beneficial to include cameras in a wireless sensor network because images are so rich in information, the power cost of transmitting an image across the wireless network can dramatically shorten the lifespan of the sensor nodes. This paper describe a new paradigm for the incorporation of imaging into wireless networks. Rather than focusing on transmitting images across the network, we show how an image can be processed locally for key features using simple detectors. Contrasted with traditional event detection systems that trigger an imagemore » capture, this enables a new class of sensors which uses a low power imaging sensor to detect a variety of visual cues. Sharing these features among relevant nodes cues specific actions to better provide information about the environment. We report on various existing techniques developed for traditional computer vision research which can aid in this work.« less

Joint Resource Optimization for Cognitive Sensor Networks with SWIPT-Enabled Relay.

PubMed

Lu, Weidang; Lin, Yuanrong; Peng, Hong; Nan, Tian; Liu, Xin

2017-09-13

Energy-constrained wireless networks, such as wireless sensor networks (WSNs), are usually powered by fixed energy supplies (e.g., batteries), which limits the operation time of networks. Simultaneous wireless information and power transfer (SWIPT) is a promising technique to prolong the lifetime of energy-constrained wireless networks. This paper investigates the performance of an underlay cognitive sensor network (CSN) with SWIPT-enabled relay node. In the CSN, the amplify-and-forward (AF) relay sensor node harvests energy from the ambient radio-frequency (RF) signals using power splitting-based relaying (PSR) protocol. Then, it helps forward the signal of source sensor node (SSN) to the destination sensor node (DSN) by using the harvested energy. We study the joint resource optimization including the transmit power and power splitting ratio to maximize CSN's achievable rate with the constraint that the interference caused by the CSN to the primary users (PUs) is within the permissible threshold. Simulation results show that the performance of our proposed joint resource optimization can be significantly improved.

Spatial and Temporal Trends of Air Pollutants in the South Coast Basin Using Low Cost Sensors

EPA Science Inventory

The emergence of small, portable, low-cost air sensors has encouraged a shift from traditional monitoring approaches for air quality. The U.S. Environmental Protection Agency (U.S. EPA), in collaboration with the South Coast Air Quality Management District’s (SCAQMD) Air Quality ...

Air-Microfluidics: Creating Small, Low-cost, Portable Air Quality Sensors

EPA Science Inventory

Air-microfluidics shows great promise in dramatically reducing the size, cost, and power requirements of future air quality sensors without compromising their accuracy. Microfabrication provides a suite of relatively new tools for the development of micro electro mechanical syste...

Development of indoor environmental index: Air quality index and thermal comfort index

NASA Astrophysics Data System (ADS)

Saad, S. M.; Shakaff, A. Y. M.; Saad, A. R. M.; Yusof, A. M.; Andrew, A. M.; Zakaria, A.; Adom, A. H.

2017-03-01

In this paper, index for indoor air quality (also known as IAQI) and thermal comfort index (TCI) have been developed. The IAQI was actually modified from previous outdoor air quality index (AQI) designed by the United States Environmental Protection Agency (US EPA). In order to measure the index, a real-time monitoring system to monitor indoor air quality level was developed. The proposed system consists of three parts: sensor module cloud, base station and service-oriented client. The sensor module cloud (SMC) contains collections of sensor modules that measures the air quality data and transmit the captured data to base station through wireless. Each sensor modules includes an integrated sensor array that can measure indoor air parameters like Carbon Dioxide, Carbon Monoxide, Ozone, Nitrogen Dioxide, Oxygen, Volatile Organic Compound and Particulate Matter. Temperature and humidity were also being measured in order to determine comfort condition in indoor environment. The result from several experiments show that the system is able to measure the air quality presented in IAQI and TCI in many indoor environment settings like air-conditioner, chemical present and cigarette smoke that may impact the air quality. It also shows that the air quality are changing dramatically, thus real-time monitoring system is essential.

Maritime In Situ Sensing Inter-Operable Networks (MISSION)

DTIC Science & Technology

2013-09-30

creating acoustic communications (acomms) technologies enabling underwater sensor networks and distributed systems. Figure 1. Project MISSION...Marn, S. Ramp, F. Bahr, “Implementation of an Underwater Wireless Sensor Network in San Francisco Bay,” Proc. 10th International Mine Warfare...NILUS – An Underwater Acoustic Sensor Network Demonstrator System,” Proc. 10th International Mine Warfare Technology Symposium, Monterey, CA, May 7

Wireless sensor network for monitoring soil moisture and weather conditions

USDA-ARS?s Scientific Manuscript database

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

Experimental study of thin film sensor networks for wind turbine blade damage detection

NASA Astrophysics Data System (ADS)

Downey, A.; Laflamme, S.; Ubertini, F.; Sauder, H.; Sarkar, P.

2017-02-01

Damage detection of wind turbine blades is difficult due to their complex geometry and large size, for which large deployment of sensing systems is typically not economical. A solution is to develop and deploy dedicated sensor networks fabricated from inexpensive materials and electronics. The authors have recently developed a novel skin-type strain gauge for measuring strain over very large surfaces. The skin, a type of large-area electronics, is constituted from a network of soft elastomeric capacitors. The sensing system is analogous to a biological skin, where local strain can be monitored over a global area. In this paper, we propose the utilization of a dense network of soft elastomeric capacitors to detect, localize, and quantify damage on wind turbine blades. We also leverage mature off-the-shelf technologies, in particular resistive strain gauges, to augment such dense sensor network with high accuracy data at key locations, therefore constituting a hybrid dense sensor network. The proposed hybrid dense sensor network is installed inside a wind turbine blade model, and tested in a wind tunnel to simulate an operational environment. Results demonstrate the ability of the hybrid dense sensor network to detect, localize, and quantify damage.

Biomimetic Models for An Ecological Approach to Massively-Deployed Sensor Networks

NASA Technical Reports Server (NTRS)

Jones, Kennie H.; Lodding, Kenneth N.; Olariu, Stephan; Wilson, Larry; Xin, Chunsheng

2005-01-01

Promises of ubiquitous control of the physical environment by massively-deployed wireless sensor networks open avenues for new applications that will redefine the way we live and work. Due to small size and low cost of sensor devices, visionaries promise systems enabled by deployment of massive numbers of sensors ubiquitous throughout our environment working in concert. Recent research has concentrated on developing techniques for performing relatively simple tasks with minimal energy expense, assuming some form of centralized control. Unfortunately, centralized control is not conducive to parallel activities and does not scale to massive size networks. Execution of simple tasks in sparse networks will not lead to the sophisticated applications predicted. We propose a new way of looking at massively-deployed sensor networks, motivated by lessons learned from the way biological ecosystems are organized. We demonstrate that in such a model, fully distributed data aggregation can be performed in a scalable fashion in massively deployed sensor networks, where motes operate on local information, making local decisions that are aggregated across the network to achieve globally-meaningful effects. We show that such architectures may be used to facilitate communication and synchronization in a fault-tolerant manner, while balancing workload and required energy expenditure throughout the network.

Classification of Reactor Facility Operational State Using SPRT Methods with Radiation Sensor Networks

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

Ramirez Aviles, Camila A.; Rao, Nageswara S.

We consider the problem of inferring the operational state of a reactor facility by using measurements from a radiation sensor network, which is deployed around the facility’s ventilation stack. The radiation emissions from the stack decay with distance, and the corresponding measurements are inherently random with parameters determined by radiation intensity levels at the sensor locations. We fuse measurements from network sensors to estimate the intensity at the stack, and use this estimate in a one-sided Sequential Probability Ratio Test (SPRT) to infer the on/off state of the reactor facility. We demonstrate the superior performance of this method over conventionalmore » majority vote fusers and individual sensors using (i) test measurements from a network of NaI sensors, and (ii) emulated measurements using radioactive effluents collected at a reactor facility stack. We analytically quantify the performance improvements of individual sensors and their networks with adaptive thresholds over those with fixed ones, by using the packing number of the radiation intensity space.« less

In-network processing of joins in wireless sensor networks.

PubMed

Kang, Hyunchul

2013-03-11

The join or correlated filtering of sensor readings is one of the fundamental query operations in wireless sensor networks (WSNs). Although the join in centralized or distributed databases is a well-researched problem, join processing in WSNs has quite different characteristics and is much more difficult to perform due to the lack of statistics on sensor readings and the resource constraints of sensor nodes. Since data transmission is orders of magnitude more costly than processing at a sensor node, in-network processing of joins is essential. In this paper, the state-of-the-art techniques for join implementation in WSNs are surveyed. The requirements and challenges, join types, and components of join implementation are described. The open issues for further research are identified.

In-Network Processing of Joins in Wireless Sensor Networks

PubMed Central

Kang, Hyunchul

2013-01-01

The join or correlated filtering of sensor readings is one of the fundamental query operations in wireless sensor networks (WSNs). Although the join in centralized or distributed databases is a well-researched problem, join processing in WSNs has quite different characteristics and is much more difficult to perform due to the lack of statistics on sensor readings and the resource constraints of sensor nodes. Since data transmission is orders of magnitude more costly than processing at a sensor node, in-network processing of joins is essential. In this paper, the state-of-the-art techniques for join implementation in WSNs are surveyed. The requirements and challenges, join types, and components of join implementation are described. The open issues for further research are identified. PMID:23478603