Wireless Prototype Based on Pressure and Bending Sensors for Measuring Gate Quality

PubMed Central

Grenez, Florent; Villarejo, María Viqueira; Zapirain, Begoña García; Zorrilla, Amaia Méndez

2013-01-01

This paper presents a technological solution based on sensors controlled remotely in order to monitor, track and evaluate the gait quality in people with or without associated pathology. Special hardware simulating a shoe was developed, which consists of three pressure sensors, two bending sensors, an Arduino mini and a Bluetooth module. The obtained signals are digitally processed, calculating the standard deviation and establishing thresholds obtained empirically. A group of users was chosen with the aim of executing two modalities: natural walking and dragging the left foot. The gait was parameterized with the following variables: as far as pressure sensors are concerned, one pressure sensor under the first metatarsal (right sensor), another one under the fifth metatarsal (left) and a third one under the heel were placed. With respect to bending sensors, one bending sensor was placed for the ankle movement and another one for the foot sole. The obtained results show a rate accuracy oscillating between 85% (right sensor) and 100% (heel and bending sensors). Therefore, the developed prototype is able to differentiate between healthy gait and pathological gait, and it will be used as the base of a more complex and integral technological solution, which is being developed currently. PMID:23899935

Wireless prototype based on pressure and bending sensors for measuring gait [corrected] quality.

PubMed

Grenez, Florent; Viqueira Villarejo, María; García Zapirain, Begoña; Méndez Zorrilla, Amaia

2013-07-29

This paper presents a technological solution based on sensors controlled remotely in order to monitor, track and evaluate the gait quality in people with or without associated pathology. Special hardware simulating a shoe was developed, which consists of three pressure sensors, two bending sensors, an Arduino mini and a Bluetooth module. The obtained signals are digitally processed, calculating the standard deviation and establishing thresholds obtained empirically. A group of users was chosen with the aim of executing two modalities: natural walking and dragging the left foot. The gait was parameterized with the following variables: as far as pressure sensors are concerned, one pressure sensor under the first metatarsal (right sensor), another one under the fifth metatarsal (left) and a third one under the heel were placed. With respect to bending sensors, one bending sensor was placed for the ankle movement and another one for the foot sole. The obtained results show a rate accuracy oscillating between 85% (right sensor) and 100% (heel and bending sensors). Therefore, the developed prototype is able to differentiate between healthy gait and pathological gait, and it will be used as the base of a more complex and integral technological solution, which is being developed currently.

Sleep monitoring sensor using flexible metal strain gauge

NASA Astrophysics Data System (ADS)

Kwak, Yeon Hwa; Kim, Jinyong; Kim, Kunnyun

2018-05-01

This paper presents a sleep monitoring sensor based on a flexible metal strain gauge. As quality of life has improved, interest in sleep quality, and related products, has increased. In this study, unlike a conventional single sensor based on a piezoelectric material, a metal strain gauge-based array sensor based on polyimide and nickel chromium (NiCr) is applied to provide movement direction, respiration, and heartbeat data as well as contact-free use by the user during sleeping. Thin-film-type resistive strain gage sensors are fabricated through the conventional flexible printed circuit board (FPCB) process, which is very useful for commercialization. The measurement of movement direction and respiratory rate during sleep were evaluated, and the heart rate data were compared with concurrent electrocardiogram (ECG) data. An algorithm for analyzing sleep data was developed using MATLAB, and the error rate was 4.2% when compared with ECG for heart rate.

Measuring Gait Quality in Parkinson’s Disease through Real-Time Gait Phase Recognition

PubMed Central

Mileti, Ilaria; Germanotta, Marco; Di Sipio, Enrica; Imbimbo, Isabella; Pacilli, Alessandra; Erra, Carmen; Petracca, Martina; Del Prete, Zaccaria; Bentivoglio, Anna Rita; Padua, Luca

2018-01-01

Monitoring gait quality in daily activities through wearable sensors has the potential to improve medical assessment in Parkinson’s Disease (PD). In this study, four gait partitioning methods, two based on thresholds and two based on a machine learning approach, considering the four-phase model, were compared. The methods were tested on 26 PD patients, both in OFF and ON levodopa conditions, and 11 healthy subjects, during walking tasks. All subjects were equipped with inertial sensors placed on feet. Force resistive sensors were used to assess reference time sequence of gait phases. Goodness Index (G) was evaluated to assess accuracy in gait phases estimation. A novel synthetic index called Gait Phase Quality Index (GPQI) was proposed for gait quality assessment. Results revealed optimum performance (G < 0.25) for three tested methods and good performance (0.25 < G < 0.70) for one threshold method. The GPQI resulted significantly higher in PD patients than in healthy subjects, showing a moderate correlation with clinical scales score. Furthermore, in patients with severe gait impairment, GPQI was found higher in OFF than in ON state. Our results unveil the possibility of monitoring gait quality in PD through real-time gait partitioning based on wearable sensors. PMID:29558410

Machine-Learning Based Channel Quality and Stability Estimation for Stream-Based Multichannel Wireless Sensor Networks.

PubMed

Rehan, Waqas; Fischer, Stefan; Rehan, Maaz

2016-09-12

Wireless sensor networks (WSNs) have become more and more diversified and are today able to also support high data rate applications, such as multimedia. In this case, per-packet channel handshaking/switching may result in inducing additional overheads, such as energy consumption, delays and, therefore, data loss. One of the solutions is to perform stream-based channel allocation where channel handshaking is performed once before transmitting the whole data stream. Deciding stream-based channel allocation is more critical in case of multichannel WSNs where channels of different quality/stability are available and the wish for high performance requires sensor nodes to switch to the best among the available channels. In this work, we will focus on devising mechanisms that perform channel quality/stability estimation in order to improve the accommodation of stream-based communication in multichannel wireless sensor networks. For performing channel quality assessment, we have formulated a composite metric, which we call channel rank measurement (CRM), that can demarcate channels into good, intermediate and bad quality on the basis of the standard deviation of the received signal strength indicator (RSSI) and the average of the link quality indicator (LQI) of the received packets. CRM is then used to generate a data set for training a supervised machine learning-based algorithm (which we call Normal Equation based Channel quality prediction (NEC) algorithm) in such a way that it may perform instantaneous channel rank estimation of any channel. Subsequently, two robust extensions of the NEC algorithm are proposed (which we call Normal Equation based Weighted Moving Average Channel quality prediction (NEWMAC) algorithm and Normal Equation based Aggregate Maturity Criteria with Beta Tracking based Channel weight prediction (NEAMCBTC) algorithm), that can perform channel quality estimation on the basis of both current and past values of channel rank estimation. In the end, simulations are made using MATLAB, and the results show that the Extended version of NEAMCBTC algorithm (Ext-NEAMCBTC) outperforms the compared techniques in terms of channel quality and stability assessment. It also minimizes channel switching overheads (in terms of switching delays and energy consumption) for accommodating stream-based communication in multichannel WSNs.

Machine-Learning Based Channel Quality and Stability Estimation for Stream-Based Multichannel Wireless Sensor Networks

PubMed Central

Rehan, Waqas; Fischer, Stefan; Rehan, Maaz

2016-01-01

Wireless sensor networks (WSNs) have become more and more diversified and are today able to also support high data rate applications, such as multimedia. In this case, per-packet channel handshaking/switching may result in inducing additional overheads, such as energy consumption, delays and, therefore, data loss. One of the solutions is to perform stream-based channel allocation where channel handshaking is performed once before transmitting the whole data stream. Deciding stream-based channel allocation is more critical in case of multichannel WSNs where channels of different quality/stability are available and the wish for high performance requires sensor nodes to switch to the best among the available channels. In this work, we will focus on devising mechanisms that perform channel quality/stability estimation in order to improve the accommodation of stream-based communication in multichannel wireless sensor networks. For performing channel quality assessment, we have formulated a composite metric, which we call channel rank measurement (CRM), that can demarcate channels into good, intermediate and bad quality on the basis of the standard deviation of the received signal strength indicator (RSSI) and the average of the link quality indicator (LQI) of the received packets. CRM is then used to generate a data set for training a supervised machine learning-based algorithm (which we call Normal Equation based Channel quality prediction (NEC) algorithm) in such a way that it may perform instantaneous channel rank estimation of any channel. Subsequently, two robust extensions of the NEC algorithm are proposed (which we call Normal Equation based Weighted Moving Average Channel quality prediction (NEWMAC) algorithm and Normal Equation based Aggregate Maturity Criteria with Beta Tracking based Channel weight prediction (NEAMCBTC) algorithm), that can perform channel quality estimation on the basis of both current and past values of channel rank estimation. In the end, simulations are made using MATLAB, and the results show that the Extended version of NEAMCBTC algorithm (Ext-NEAMCBTC) outperforms the compared techniques in terms of channel quality and stability assessment. It also minimizes channel switching overheads (in terms of switching delays and energy consumption) for accommodating stream-based communication in multichannel WSNs. PMID:27626429

Scene-based nonuniformity corrections for optical and SWIR pushbroom sensors.

PubMed

Leathers, Robert; Downes, Trijntje; Priest, Richard

2005-06-27

We propose and evaluate several scene-based methods for computing nonuniformity corrections for visible or near-infrared pushbroom sensors. These methods can be used to compute new nonuniformity correction values or to repair or refine existing radiometric calibrations. For a given data set, the preferred method depends on the quality of the data, the type of scenes being imaged, and the existence and quality of a laboratory calibration. We demonstrate our methods with data from several different sensor systems and provide a generalized approach to be taken for any new data set.

A Wireless, Passive Sensor for Quantifying Packaged Food Quality.

PubMed

Tan, Ee Lim; Ng, Wen Ni; Shao, Ranyuan; Pereles, Brandon D; Ong, Keat Ghee

2007-09-05

This paper describes the fabrication of a wireless, passive sensor based on aninductive-capacitive resonant circuit, and its application for in situ monitoring of thequality of dry, packaged food such as cereals, and fried and baked snacks. The sensor ismade of a planar inductor and capacitor printed on a paper substrate. To monitor foodquality, the sensor is embedded inside the food package by adhering it to the package'sinner wall; its response is remotely detected through a coil connected to a sensor reader. Asfood quality degrades due to increasing humidity inside the package, the paper substrateabsorbs water vapor, changing the capacitor's capacitance and the sensor's resonantfrequency. Therefore, the taste quality of the packaged food can be indirectly determined bymeasuring the change in the sensor's resonant frequency. The novelty of this sensortechnology is its wireless and passive nature, which allows in situ determination of foodquality. In addition, the simple fabrication process and inexpensive sensor material ensure alow sensor cost, thus making this technology economically viable.

Estimation and Fusion for Tracking Over Long-Haul Links Using Artificial Neural Networks

DOE PAGES

Liu, Qiang; Brigham, Katharine; Rao, Nageswara S. V.

2017-02-01

In a long-haul sensor network, sensors are remotely deployed over a large geographical area to perform certain tasks, such as tracking and/or monitoring of one or more dynamic targets. A remote fusion center fuses the information provided by these sensors so that a final estimate of certain target characteristics – such as the position – is expected to possess much improved quality. In this paper, we pursue learning-based approaches for estimation and fusion of target states in longhaul sensor networks. In particular, we consider learning based on various implementations of artificial neural networks (ANNs). Finally, the joint effect of (i)more » imperfect communication condition, namely, link-level loss and delay, and (ii) computation constraints, in the form of low-quality sensor estimates, on ANN-based estimation and fusion, is investigated by means of analytical and simulation studies.« less

Estimation and Fusion for Tracking Over Long-Haul Links Using Artificial Neural Networks

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

Liu, Qiang; Brigham, Katharine; Rao, Nageswara S. V.

In a long-haul sensor network, sensors are remotely deployed over a large geographical area to perform certain tasks, such as tracking and/or monitoring of one or more dynamic targets. A remote fusion center fuses the information provided by these sensors so that a final estimate of certain target characteristics – such as the position – is expected to possess much improved quality. In this paper, we pursue learning-based approaches for estimation and fusion of target states in longhaul sensor networks. In particular, we consider learning based on various implementations of artificial neural networks (ANNs). Finally, the joint effect of (i)more » imperfect communication condition, namely, link-level loss and delay, and (ii) computation constraints, in the form of low-quality sensor estimates, on ANN-based estimation and fusion, is investigated by means of analytical and simulation studies.« less

Real Time Assessment of Potable Water Quality in Distribution Network based on Low Cost Multi-Sensor Array

NASA Astrophysics Data System (ADS)

Bhardwaj, Jyotirmoy; Gupta, Karunesh K.; Khatri, Punit

2018-03-01

New concepts and techniques are replacing traditional methods of water quality parameters measurement systems. This paper proposed a new way of potable water quality assessment in distribution network using Multi Sensor Array (MSA). Extensive research suggests that following parameters i.e. pH, Dissolved Oxygen (D.O.), Conductivity, Oxygen Reduction Potential (ORP), Temperature and Salinity are most suitable to detect overall quality of potable water. Commonly MSA is not an integrated sensor array on some substrate, but rather comprises a set of individual sensors measuring simultaneously different water parameters all together. Based on research, a MSA has been developed followed by signal conditioning unit and finally, an algorithm for easy user interfacing. A dedicated part of this paper also discusses the platform design and significant results. The Objective of this proposed research is to provide simple, efficient, cost effective and socially acceptable means to detect and analyse water bodies regularly and automatically.

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

PubMed Central

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

2017-01-01

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

Coordinating standards and applications for optical water quality sensor networks

USGS Publications Warehouse

Bergamaschi, B.; Pellerin, B.

2011-01-01

Joint USGS-CUAHSI Workshop: In Situ Optical Water Quality Sensor Networks; Shepherdstown, West Virginia, 8-10 June 2011; Advanced in situ optical water quality sensors and new techniques for data analysis hold enormous promise for advancing scientific understanding of aquatic systems through measurements of important biogeochemical parameters at the time scales over which they vary. High-frequency and real-time water quality data also provide the opportunity for early warning of water quality deterioration, trend detection, and science-based decision support. However, developing networks of optical sensors in freshwater systems that report reliable and comparable data across and between sites remains a challenge to the research and monitoring community. To address this, the U.S. Geological Survey (USGS) and the Consortium of Universities for the Advancement of Hydrologic Science, Inc. (CUAHSI), convened a 3-day workshop to explore ways to coordinate development of standards and applications for optical sensors, as well as handling, storage, and analysis of the continuous data they produce.

Photoacoustic imaging with planoconcave optical microresonator sensors: feasibility studies based on phantom imaging

NASA Astrophysics Data System (ADS)

Guggenheim, James A.; Zhang, Edward Z.; Beard, Paul C.

2017-03-01

The planar Fabry-Pérot (FP) sensor provides high quality photoacoustic (PA) images but beam walk-off limits sensitivity and thus penetration depth to ≍1 cm. Planoconcave microresonator sensors eliminate beam walk-off enabling sensitivity to be increased by an order-of-magnitude whilst retaining the highly favourable frequency response and directional characteristics of the FP sensor. The first tomographic PA images obtained in a tissue-realistic phantom using the new sensors are described. These show that the microresonator sensors provide near identical image quality as the planar FP sensor but with significantly greater penetration depth (e.g. 2-3cm) due to their higher sensitivity. This offers the prospect of whole body small animal imaging and clinical imaging to depths previously unattainable using the FP planar sensor.

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.

Pre-Scheduled and Self Organized Sleep-Scheduling Algorithms for Efficient K-Coverage in Wireless Sensor Networks

PubMed Central

Hwang, I-Shyan

2017-01-01

The K-coverage configuration that guarantees coverage of each location by at least K sensors is highly popular and is extensively used to monitor diversified applications in wireless sensor networks. Long network lifetime and high detection quality are the essentials of such K-covered sleep-scheduling algorithms. However, the existing sleep-scheduling algorithms either cause high cost or cannot preserve the detection quality effectively. In this paper, the Pre-Scheduling-based K-coverage Group Scheduling (PSKGS) and Self-Organized K-coverage Scheduling (SKS) algorithms are proposed to settle the problems in the existing sleep-scheduling algorithms. Simulation results show that our pre-scheduled-based KGS approach enhances the detection quality and network lifetime, whereas the self-organized-based SKS algorithm minimizes the computation and communication cost of the nodes and thereby is energy efficient. Besides, SKS outperforms PSKGS in terms of network lifetime and detection quality as it is self-organized. PMID:29257078

Diffractive optical element in materials testing

NASA Astrophysics Data System (ADS)

Silvennoinen, Raimo V. J.; Peiponen, Kai-Erik

1998-09-01

The object of this paper is to present a sensor based on diffractive optics that can be applied for the materials testing. The present sensor, which is based on the use of a computer-generated hologram (CGH) exploits the holographic imagery. The CGH-sensor was introduced for inspection of surface roughness and flatness of metal surfaces. The results drawn out by the present sensor are observed to be in accordance with the experimental data. Together with the double exposure holographic interferometry (DEHI) and digital electronic speckle pattern interferometry (DSPI) in elasticity inspection, the sensor was applied for the investigations of surface quality of opaque fragile materials, which are pharmaceutical compacts. The optical surface quality was observed to be related to the porosity of the pharmaceutical tablets. The CGH-sensor was also applied for investigations of optical quality of thin films as PLZT ceramics and coating of pharmaceutical compacts. The surfaces of PLZT samples showed fluctuations in optical curvature, and wedgeness for all the cases studied. For pharmaceutical compacts, the optical signals were observed to depend to a great extent on the optical constants of the coatings and the substrates, and in addition to the surface porosity under the coating.

A laser-based vision system for weld quality inspection.

PubMed

Huang, Wei; Kovacevic, Radovan

2011-01-01

Welding is a very complex process in which the final weld quality can be affected by many process parameters. In order to inspect the weld quality and detect the presence of various weld defects, different methods and systems are studied and developed. In this paper, a laser-based vision system is developed for non-destructive weld quality inspection. The vision sensor is designed based on the principle of laser triangulation. By processing the images acquired from the vision sensor, the geometrical features of the weld can be obtained. Through the visual analysis of the acquired 3D profiles of the weld, the presences as well as the positions and sizes of the weld defects can be accurately identified and therefore, the non-destructive weld quality inspection can be achieved.

A Laser-Based Vision System for Weld Quality Inspection

PubMed Central

Huang, Wei; Kovacevic, Radovan

2011-01-01

Welding is a very complex process in which the final weld quality can be affected by many process parameters. In order to inspect the weld quality and detect the presence of various weld defects, different methods and systems are studied and developed. In this paper, a laser-based vision system is developed for non-destructive weld quality inspection. The vision sensor is designed based on the principle of laser triangulation. By processing the images acquired from the vision sensor, the geometrical features of the weld can be obtained. Through the visual analysis of the acquired 3D profiles of the weld, the presences as well as the positions and sizes of the weld defects can be accurately identified and therefore, the non-destructive weld quality inspection can be achieved. PMID:22344308

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.

Development of realtime, handheld and portable flood distribution and water quality sensor based android smartphone

NASA Astrophysics Data System (ADS)

Rachmatika, Ratih; Adriyanto, Feri

2017-09-01

Current sensors to monitor water quality are made of manual sensors, which reported to have good performance. However, the major problems, which manual process to get the data. In addition, the data interpretation takes a long time. Due to these problems, a new approach needs to be introduced into the process to prevent a long data acquisition. Therefore, the SIAGA application was proposed. The application of SIAGA is divided into two main applications which are SIBA (Siaga Banjir) and SIAB (Siaga Air Bersih). We using WiFi system which is located at points along the flow of river.. The result can be monitored in the online application based on smartphone which is divided into the river water quality, potential sources of pollution and flood area. Each WiFi point is completed with the instruments which are divided into the sensors that can do the identification of parameters to determine the water quality such as temperature, pH, water level and turbidity. This instrument completed using GPS (Global Positioning System), Full Map menu. The instrument was succesfully monitoredthe flood distribution and water quality in Bengawan Solo river.

A software sensor model based on hybrid fuzzy neural network for rapid estimation water quality in Guangzhou section of Pearl River, China.

PubMed

Zhou, Chunshan; Zhang, Chao; Tian, Di; Wang, Ke; Huang, Mingzhi; Liu, Yanbiao

2018-01-02

In order to manage water resources, a software sensor model was designed to estimate water quality using a hybrid fuzzy neural network (FNN) in Guangzhou section of Pearl River, China. The software sensor system was composed of data storage module, fuzzy decision-making module, neural network module and fuzzy reasoning generator module. Fuzzy subtractive clustering was employed to capture the character of model, and optimize network architecture for enhancing network performance. The results indicate that, on basis of available on-line measured variables, the software sensor model can accurately predict water quality according to the relationship between chemical oxygen demand (COD) and dissolved oxygen (DO), pH and NH 4 + -N. Owing to its ability in recognizing time series patterns and non-linear characteristics, the software sensor-based FNN is obviously superior to the traditional neural network model, and its R (correlation coefficient), MAPE (mean absolute percentage error) and RMSE (root mean square error) are 0.8931, 10.9051 and 0.4634, respectively.

Hybrid electronic tongue based on optical and electrochemical microsensors for quality control of wine.

PubMed

Gutiérrez, Manuel; Llobera, Andreu; Vila-Planas, Jordi; Capdevila, Fina; Demming, Stefanie; Büttgenbach, Stephanus; Mínguez, Santiago; Jiménez-Jorquera, Cecilia

2010-07-01

A multiparametric system able to classify red and white wines according to the grape varieties and for analysing some specific parameters is presented. The system, known as hybrid electronic tongue, consists of an array of electrochemical microsensors and a colorimetric optofluidic system. The array of electrochemical sensors is composed of six ISFETs based sensors, a conductivity sensor, a redox potential sensor and two amperometric electrodes, an Au microelectrode and a microelectrode for sensing electrochemical oxygen demand. The optofluidic system is entirely fabricated in polymer technology and comprises a hollow structure, air mirrors, microlenses and self-alignment structures. The data obtained from these sensors has been treated with multivariate advanced tools; Principal Component Analysis (PCA), for the patterning recognition and classification of wine samples, and Partial-Least Squares (PLS) regression, for quantification of several chemical and optical parameters of interest in wine quality. The results have demonstrated the utility of this system for distinguishing the samples according to the grape variety and year vintage and for quantifying several sample parameters of interest in wine quality control.

Quality Factor Effect on the Wireless Range of Microstrip Patch Antenna Strain Sensors

PubMed Central

Daliri, Ali; Galehdar, Amir; Rowe, Wayne S. T.; John, Sabu; Wang, Chun H.; Ghorbani, Kamran

2014-01-01

Recently introduced passive wireless strain sensors based on microstrip patch antennas have shown great potential for reliable health and usage monitoring in aerospace and civil industries. However, the wireless interrogation range of these sensors is limited to few centimeters, which restricts their practical application. This paper presents an investigation on the effect of circular microstrip patch antenna (CMPA) design on the quality factor and the maximum practical wireless reading range of the sensor. The results reveal that by using appropriate substrate materials the interrogation distance of the CMPA sensor can be increased four-fold, from the previously reported 5 to 20 cm, thus improving considerably the viability of this type of wireless sensors for strain measurement and damage detection. PMID:24451457

Quality factor effect on the wireless range of microstrip patch antenna strain sensors.

PubMed

Daliri, Ali; Galehdar, Amir; Rowe, Wayne S T; John, Sabu; Wang, Chun H; Ghorbani, Kamran

2014-01-02

Recently introduced passive wireless strain sensors based on microstrip patch antennas have shown great potential for reliable health and usage monitoring in aerospace and civil industries. However, the wireless interrogation range of these sensors is limited to few centimeters, which restricts their practical application. This paper presents an investigation on the effect of circular microstrip patch antenna (CMPA) design on the quality factor and the maximum practical wireless reading range of the sensor. The results reveal that by using appropriate substrate materials the interrogation distance of the CMPA sensor can be increased four-fold, from the previously reported 5 to 20 cm, thus improving considerably the viability of this type of wireless sensors for strain measurement and damage detection.

Mobile Sensors Environmental Assessment

DTIC Science & Technology

2005-09-26

4-1 4.1 Impacts of Land-Based Sensors.........................................................................4-1 4.1.1 Air Quality...4-27 4.3 Impacts of the Proposed Action...4-38 4.6 Cumulative Impacts

Sleep Quality Estimation based on Chaos Analysis for Heart Rate Variability

NASA Astrophysics Data System (ADS)

Fukuda, Toshio; Wakuda, Yuki; Hasegawa, Yasuhisa; Arai, Fumihito; Kawaguchi, Mitsuo; Noda, Akiko

In this paper, we propose an algorithm to estimate sleep quality based on a heart rate variability using chaos analysis. Polysomnography(PSG) is a conventional and reliable system to diagnose sleep disorder and to evaluate its severity and therapeatic effect, by estimating sleep quality based on multiple channels. However, a recording process requires a lot of time and a controlled environment for measurement and then an analyzing process of PSG data is hard work because the huge sensed data should be manually evaluated. On the other hand, it is focused that some people make a mistake or cause an accident due to lost of regular sleep and of homeostasis these days. Therefore a simple home system for checking own sleep is required and then the estimation algorithm for the system should be developed. Therefore we propose an algorithm to estimate sleep quality based only on a heart rate variability which can be measured by a simple sensor such as a pressure sensor and an infrared sensor in an uncontrolled environment, by experimentally finding the relationship between chaos indices and sleep quality. The system including the estimation algorithm can inform patterns and quality of own daily sleep to a user, and then the user can previously arranges his life schedule, pays more attention based on sleep results and consult with a doctor.

Inexpensive DAQ based physics labs

NASA Astrophysics Data System (ADS)

Lewis, Benjamin; Clark, Shane

2015-11-01

Quality Data Acquisition (DAQ) based physics labs can be designed using microcontrollers and very low cost sensors with minimal lab equipment. A prototype device with several sensors and documentation for a number of DAQ-based labs is showcased. The device connects to a computer through Bluetooth and uses a simple interface to control the DAQ and display real time graphs, storing the data in .txt and .xls formats. A full device including a larger number of sensors combined with software interface and detailed documentation would provide a high quality physics lab education for minimal cost, for instance in high schools lacking lab equipment or students taking online classes. An entire semester’s lab course could be conducted using a single device with a manufacturing cost of under $20.

Energy and Quality Evaluation for Compressive Sensing of Fetal Electrocardiogram Signals

PubMed Central

Da Poian, Giulia; Brandalise, Denis; Bernardini, Riccardo; Rinaldo, Roberto

2016-01-01

This manuscript addresses the problem of non-invasive fetal Electrocardiogram (ECG) signal acquisition with low power/low complexity sensors. A sensor architecture using the Compressive Sensing (CS) paradigm is compared to a standard compression scheme using wavelets in terms of energy consumption vs. reconstruction quality, and, more importantly, vs. performance of fetal heart beat detection in the reconstructed signals. We show in this paper that a CS scheme based on reconstruction with an over-complete dictionary has similar reconstruction quality to one based on wavelet compression. We also consider, as a more important figure of merit, the accuracy of fetal beat detection after reconstruction as a function of the sensor power consumption. Experimental results with an actual implementation in a commercial device show that CS allows significant reduction of energy consumption in the sensor node, and that the detection performance is comparable to that obtained from original signals for compression ratios up to about 75%. PMID:28025510

Nanostructured Metal Oxide Gas Sensors, a Survey of Applications Carried out at SENSOR Lab, Brescia (Italy) in the Security and Food Quality Fields

PubMed Central

Ponzoni, Andrea; Comini, Elisabetta; Concina, Isabella; Ferroni, Matteo; Falasconi, Matteo; Gobbi, Emanuela; Sberveglieri, Veronica; Sberveglieri, Giorgio

2012-01-01

In this work we report on metal oxide (MOX) based gas sensors, presenting the work done at the SENSOR laboratory of the CNR-IDASC and University of Brescia, Italy since the 80s up to the latest results achieved in recent times. In particular we report the strategies followed at SENSOR during these 30 years to increase the performance of MOX sensors through the development of different preparation techniques, from Rheotaxial Growth Thermal Oxidation (RGTO) to nanowire technology to address sensitivity and stability, and the development of electronic nose systems and pattern recognition techniques to address selectivity. We will show the obtained achievement in the context of selected applications such as safety and security and food quality control. PMID:23235445

Development and Application of a Next Generation Air Sensor Network for the Hong Kong Marathon 2015 Air Quality Monitoring.

PubMed

Sun, Li; Wong, Ka Chun; Wei, Peng; Ye, Sheng; Huang, Hao; Yang, Fenhuan; Westerdahl, Dane; Louie, Peter K K; Luk, Connie W Y; Ning, Zhi

2016-02-05

This study presents the development and evaluation of a next generation air monitoring system with both laboratory and field tests. A multi-parameter algorithm was used to correct for the impact of environmental conditions on the electrochemical sensors for carbon monoxide (CO) and nitrogen dioxide (NO2) pollutants. The field evaluation in an urban roadside environment in comparison to designated monitors showed good agreement with measurement error within 5% of the pollutant concentrations. Multiple sets of the developed system were then deployed in the Hong Kong Marathon 2015 forming a sensor-based network along the marathon route. Real-time air pollution concentration data were wirelessly transmitted and the Air Quality Health Index (AQHI) for the Green Marathon was calculated, which were broadcast to the public on an hourly basis. The route-specific sensor network showed somewhat different pollutant patterns than routine air monitoring, indicating the immediate impact of traffic control during the marathon on the roadside air quality. The study is one of the first applications of a next generation sensor network in international sport events, and it demonstrated the usefulness of the emerging sensor-based air monitoring technology in rapid network deployment to supplement existing air monitoring.

Development and Application of a Next Generation Air Sensor Network for the Hong Kong Marathon 2015 Air Quality Monitoring

PubMed Central

Sun, Li; Wong, Ka Chun; Wei, Peng; Ye, Sheng; Huang, Hao; Yang, Fenhuan; Westerdahl, Dane; Louie, Peter K.K.; Luk, Connie W.Y.; Ning, Zhi

2016-01-01

This study presents the development and evaluation of a next generation air monitoring system with both laboratory and field tests. A multi-parameter algorithm was used to correct for the impact of environmental conditions on the electrochemical sensors for carbon monoxide (CO) and nitrogen dioxide (NO2) pollutants. The field evaluation in an urban roadside environment in comparison to designated monitors showed good agreement with measurement error within 5% of the pollutant concentrations. Multiple sets of the developed system were then deployed in the Hong Kong Marathon 2015 forming a sensor-based network along the marathon route. Real-time air pollution concentration data were wirelessly transmitted and the Air Quality Health Index (AQHI) for the Green Marathon was calculated, which were broadcast to the public on an hourly basis. The route-specific sensor network showed somewhat different pollutant patterns than routine air monitoring, indicating the immediate impact of traffic control during the marathon on the roadside air quality. The study is one of the first applications of a next generation sensor network in international sport events, and it demonstrated the usefulness of the emerging sensor-based air monitoring technology in rapid network deployment to supplement existing air monitoring. PMID:26861336

Fast decision algorithms in low-power embedded processors for quality-of-service based connectivity of mobile sensors in heterogeneous wireless sensor networks.

PubMed

Jaraíz-Simón, María D; Gómez-Pulido, Juan A; Vega-Rodríguez, Miguel A; Sánchez-Pérez, Juan M

2012-01-01

When a mobile wireless sensor is moving along heterogeneous wireless sensor networks, it can be under the coverage of more than one network many times. In these situations, the Vertical Handoff process can happen, where the mobile sensor decides to change its connection from a network to the best network among the available ones according to their quality of service characteristics. A fitness function is used for the handoff decision, being desirable to minimize it. This is an optimization problem which consists of the adjustment of a set of weights for the quality of service. Solving this problem efficiently is relevant to heterogeneous wireless sensor networks in many advanced applications. Numerous works can be found in the literature dealing with the vertical handoff decision, although they all suffer from the same shortfall: a non-comparable efficiency. Therefore, the aim of this work is twofold: first, to develop a fast decision algorithm that explores the entire space of possible combinations of weights, searching that one that minimizes the fitness function; and second, to design and implement a system on chip architecture based on reconfigurable hardware and embedded processors to achieve several goals necessary for competitive mobile terminals: good performance, low power consumption, low economic cost, and small area integration.

Indoor air quality inspection and analysis system based on gas sensor array

NASA Astrophysics Data System (ADS)

Gao, Xiang; Wang, Mingjiang; Fan, Binwen

2017-08-01

A detection and analysis system capable of measuring the concentration of four major gases in indoor air is designed. It uses four gas sensors constitute a gas sensor array, to achieve four indoor gas concentration detection, while the detection of data for further processing to reduce the cross-sensitivity between the gas sensor to improve the accuracy of detection.

Blood detection in the spinal column of whole cooked chicken using an optical fibre based sensor system

NASA Astrophysics Data System (ADS)

Sheridan, C.; O'Farrell, M.; Lyons, W. B.; Lewis, E.; Flanagan, C.; Jackman, N.

2005-01-01

An optical fibre based sensor has been developed to aid the quality assurance of food cooked in industrial ovens by monitoring the product in situ as it cooks. The sensor measures the product colour as it cooks by examining the reflected visible light from the surface as well as the core of the product. This paper examines the use of the sensor for the detection of blood in the spinal area of cooked whole chickens. The results presented here show that the sensor can be successfully used for this purpose.

High Resolution Eddy-Current Wire Testing Based on a Gmr Sensor-Array

NASA Astrophysics Data System (ADS)

Kreutzbruck, Marc; Allweins, Kai; Strackbein, Chris; Bernau, Hendrick

2009-03-01

Increasing demands in materials quality and cost effectiveness have led to advanced standards in manufacturing technology. Especially when dealing with high quality standards in conjunction with high throughput quantitative NDE techniques are vital to provide reliable and fast quality control systems. In this work we illuminate a modern electromagnetic NDE approach using a small GMR sensor array for testing superconducting wires. Four GMR sensors are positioned around the wire. Each GMR sensor provides a field sensitivity of 200 pT/√Hz and a spatial resolution of about 100 μm. This enables us to detect under surface defects of 100 μm in size in a depth of 200 μm with a signal-to-noise ratio of better than 400. Surface defects could be detected with a SNR of up to 10,000. Besides this remarkably SNR the small extent of GMR sensors results in a spatial resolution which offers new visualisation techniques for defect localisation, defect characterization and tomography-like mapping techniques. We also report on inverse algorithms based on either a Finite Element Method or an analytical approach. These allow for accurate defect localization on the urn scale and an estimation of the defect size.

A Steel Ball Surface Quality Inspection Method Based on a Circumferential Eddy Current Array Sensor.

PubMed

Zhang, Huayu; Xie, Fengqin; Cao, Maoyong; Zhong, Mingming

2017-07-01

To efficiently inspect surface defects on steel ball bearings, a new method based on a circumferential eddy current array (CECA) sensor was proposed here. The best probe configuration, in terms of the coil quality factor (Q-factor), magnetic field intensity, and induced eddy current density on the surface of a sample steel ball, was determined using 3-, 4-, 5-, and 6-coil probes, for analysis and comparison. The optimal lift-off from the measured steel ball, the number of probe coils, and the frequency of excitation current suitable for steel ball inspection were obtained. Using the resulting CECA sensor to inspect 46,126 steel balls showed a miss rate of ~0.02%. The sensor was inspected for surface defects as small as 0.05 mm in width and 0.1 mm in depth.

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.

A chemical sensor and biosensor based totally automated water quality monitor for extended space flight: Step 1

NASA Technical Reports Server (NTRS)

Smith, Robert S.

1993-01-01

The result of a literature search to consider what technologies should be represented in a totally automated water quality monitor for extended space flight is presented. It is the result of the first summer in a three year JOVE project. The next step will be to build a test platform at the Authors' school, St. John Fisher College. This will involve undergraduates in NASA related research. The test flow injection analysis system will be used to test the detection limit of sensors and the performance of sensors in groups. Sensor companies and research groups will be encouraged to produce sensors which are not currently available and are needed for this project.

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.

Content-Based Multi-Channel Network Coding Algorithm in the Millimeter-Wave Sensor Network

PubMed Central

Lin, Kai; Wang, Di; Hu, Long

2016-01-01

With the development of wireless technology, the widespread use of 5G is already an irreversible trend, and millimeter-wave sensor networks are becoming more and more common. However, due to the high degree of complexity and bandwidth bottlenecks, the millimeter-wave sensor network still faces numerous problems. In this paper, we propose a novel content-based multi-channel network coding algorithm, which uses the functions of data fusion, multi-channel and network coding to improve the data transmission; the algorithm is referred to as content-based multi-channel network coding (CMNC). The CMNC algorithm provides a fusion-driven model based on the Dempster-Shafer (D-S) evidence theory to classify the sensor nodes into different classes according to the data content. By using the result of the classification, the CMNC algorithm also provides the channel assignment strategy and uses network coding to further improve the quality of data transmission in the millimeter-wave sensor network. Extensive simulations are carried out and compared to other methods. Our simulation results show that the proposed CMNC algorithm can effectively improve the quality of data transmission and has better performance than the compared methods. PMID:27376302

A Survey on Data Quality for Dependable Monitoring in Wireless Sensor Networks.

PubMed

Jesus, Gonçalo; Casimiro, António; Oliveira, Anabela

2017-09-02

Wireless sensor networks are being increasingly used in several application areas, particularly to collect data and monitor physical processes. Non-functional requirements, like reliability, security or availability, are often important and must be accounted for in the application development. For that purpose, there is a large body of knowledge on dependability techniques for distributed systems, which provide a good basis to understand how to satisfy these non-functional requirements of WSN-based monitoring applications. Given the data-centric nature of monitoring applications, it is of particular importance to ensure that data are reliable or, more generically, that they have the necessary quality. In this survey, we look into the problem of ensuring the desired quality of data for dependable monitoring using WSNs. We take a dependability-oriented perspective, reviewing the possible impairments to dependability and the prominent existing solutions to solve or mitigate these impairments. Despite the variety of components that may form a WSN-based monitoring system, we give particular attention to understanding which faults can affect sensors, how they can affect the quality of the information and how this quality can be improved and quantified.

Sensitivity of optical mass sensor enhanced by optomechanical coupling

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

He, Yong, E-mail: hey@cczu.edu.cn

Optical mass sensors based on cavity optomechanics employ radiation pressure force to drive mechanical resonator whose mechanical susceptibility can be described by nonlinear optical transmission spectrum. In this paper, we present an optical mass sensor based on a two-cavity optomechanical system where the mechanical damping rate can be decreased by adjusting a pump power so that the mass sensitivity which depends on the mechanical quality factor has been enhanced greatly. Compared with that of an optical mass sensor based on single-cavity optomechanics, the mass sensitivity of the optical mass sensor is improved by three orders of magnitude. This is anmore » approach to enhance the mass sensitivity by means of optomechanical coupling, which is suitable for all mass sensor based on cavity optomechanics. Finally, we illustrate the accurate measurement for the mass of a few chromosomes, which can be achieved based on the current experimental conditions.« less

Towards a cyber-physical era: soft computing framework based multi-sensor array for water quality monitoring

NASA Astrophysics Data System (ADS)

Bhardwaj, Jyotirmoy; Gupta, Karunesh K.; Gupta, Rajiv

2018-02-01

New concepts and techniques are replacing traditional methods of water quality parameter measurement systems. This paper introduces a cyber-physical system (CPS) approach for water quality assessment in a distribution network. Cyber-physical systems with embedded sensors, processors and actuators can be designed to sense and interact with the water environment. The proposed CPS is comprised of sensing framework integrated with five different water quality parameter sensor nodes and soft computing framework for computational modelling. Soft computing framework utilizes the applications of Python for user interface and fuzzy sciences for decision making. Introduction of multiple sensors in a water distribution network generates a huge number of data matrices, which are sometimes highly complex, difficult to understand and convoluted for effective decision making. Therefore, the proposed system framework also intends to simplify the complexity of obtained sensor data matrices and to support decision making for water engineers through a soft computing framework. The target of this proposed research is to provide a simple and efficient method to identify and detect presence of contamination in a water distribution network using applications of CPS.

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.

Sensor Selection and Data Validation for Reliable Integrated System Health Management

NASA Technical Reports Server (NTRS)

Garg, Sanjay; Melcher, Kevin J.

2008-01-01

For new access to space systems with challenging mission requirements, effective implementation of integrated system health management (ISHM) must be available early in the program to support the design of systems that are safe, reliable, highly autonomous. Early ISHM availability is also needed to promote design for affordable operations; increased knowledge of functional health provided by ISHM supports construction of more efficient operations infrastructure. Lack of early ISHM inclusion in the system design process could result in retrofitting health management systems to augment and expand operational and safety requirements; thereby increasing program cost and risk due to increased instrumentation and computational complexity. Having the right sensors generating the required data to perform condition assessment, such as fault detection and isolation, with a high degree of confidence is critical to reliable operation of ISHM. Also, the data being generated by the sensors needs to be qualified to ensure that the assessments made by the ISHM is not based on faulty data. NASA Glenn Research Center has been developing technologies for sensor selection and data validation as part of the FDDR (Fault Detection, Diagnosis, and Response) element of the Upper Stage project of the Ares 1 launch vehicle development. This presentation will provide an overview of the GRC approach to sensor selection and data quality validation and will present recent results from applications that are representative of the complexity of propulsion systems for access to space vehicles. A brief overview of the sensor selection and data quality validation approaches is provided below. The NASA GRC developed Systematic Sensor Selection Strategy (S4) is a model-based procedure for systematically and quantitatively selecting an optimal sensor suite to provide overall health assessment of a host system. S4 can be logically partitioned into three major subdivisions: the knowledge base, the down-select iteration, and the final selection analysis. The knowledge base required for productive use of S4 consists of system design information and heritage experience together with a focus on components with health implications. The sensor suite down-selection is an iterative process for identifying a group of sensors that provide good fault detection and isolation for targeted fault scenarios. In the final selection analysis, a statistical evaluation algorithm provides the final robustness test for each down-selected sensor suite. NASA GRC has developed an approach to sensor data qualification that applies empirical relationships, threshold detection techniques, and Bayesian belief theory to a network of sensors related by physics (i.e., analytical redundancy) in order to identify the failure of a given sensor within the network. This data quality validation approach extends the state-of-the-art, from red-lines and reasonableness checks that flag a sensor after it fails, to include analytical redundancy-based methods that can identify a sensor in the process of failing. The focus of this effort is on understanding the proper application of analytical redundancy-based data qualification methods for onboard use in monitoring Upper Stage sensors.

Evaluation of electrical capacitance tomography sensor based on the coupling of fluid field and electrostatic field

NASA Astrophysics Data System (ADS)

Ye, Jiamin; Wang, Haigang; Yang, Wuqiang

2016-07-01

Electrical capacitance tomography (ECT) is based on capacitance measurements from electrode pairs mounted outside of a pipe or vessel. The structure of ECT sensors is vital to image quality. In this paper, issues with the number of electrodes and the electrode covering ratio for complex liquid-solids flows in a rotating device are investigated based on a new coupling simulation model. The number of electrodes is increased from 4 to 32 while the electrode covering ratio is changed from 0.1 to 0.9. Using the coupling simulation method, real permittivity distributions and the corresponding capacitance data at 0, 0.5, 1, 2, 3, 5, and 8 s with a rotation speed of 96 rotations per minute (rpm) are collected. Linear back projection (LBP) and Landweber iteration algorithms are used for image reconstruction. The quality of reconstructed images is evaluated by correlation coefficient compared with the real permittivity distributions obtained from the coupling simulation. The sensitivity for each sensor is analyzed and compared with the correlation coefficient. The capacitance data with a range of signal-to-noise ratios (SNRs) of 45, 50, 55 and 60 dB are generated to evaluate the effect of data noise on the performance of ECT sensors. Furthermore, the SNRs of experimental data are analyzed for a stationary pipe with permittivity distribution. Based on the coupling simulation, 16-electrode ECT sensors are recommended to achieve good image quality.

Selection of optimal sensors for predicting performance of polymer electrolyte membrane fuel cell

NASA Astrophysics Data System (ADS)

Mao, Lei; Jackson, Lisa

2016-10-01

In this paper, sensor selection algorithms are investigated based on a sensitivity analysis, and the capability of optimal sensors in predicting PEM fuel cell performance is also studied using test data. The fuel cell model is developed for generating the sensitivity matrix relating sensor measurements and fuel cell health parameters. From the sensitivity matrix, two sensor selection approaches, including the largest gap method, and exhaustive brute force searching technique, are applied to find the optimal sensors providing reliable predictions. Based on the results, a sensor selection approach considering both sensor sensitivity and noise resistance is proposed to find the optimal sensor set with minimum size. Furthermore, the performance of the optimal sensor set is studied to predict fuel cell performance using test data from a PEM fuel cell system. Results demonstrate that with optimal sensors, the performance of PEM fuel cell can be predicted with good quality.

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.

Wavefront sensorless adaptive optics ophthalmoscopy in the human eye

PubMed Central

Hofer, Heidi; Sredar, Nripun; Queener, Hope; Li, Chaohong; Porter, Jason

2011-01-01

Wavefront sensor noise and fidelity place a fundamental limit on achievable image quality in current adaptive optics ophthalmoscopes. Additionally, the wavefront sensor ‘beacon’ can interfere with visual experiments. We demonstrate real-time (25 Hz), wavefront sensorless adaptive optics imaging in the living human eye with image quality rivaling that of wavefront sensor based control in the same system. A stochastic parallel gradient descent algorithm directly optimized the mean intensity in retinal image frames acquired with a confocal adaptive optics scanning laser ophthalmoscope (AOSLO). When imaging through natural, undilated pupils, both control methods resulted in comparable mean image intensities. However, when imaging through dilated pupils, image intensity was generally higher following wavefront sensor-based control. Despite the typically reduced intensity, image contrast was higher, on average, with sensorless control. Wavefront sensorless control is a viable option for imaging the living human eye and future refinements of this technique may result in even greater optical gains. PMID:21934779

Effects of Data Quality on the Characterization of Aerosol Properties from Multiple Sensors

NASA Technical Reports Server (NTRS)

Petrenko, Maksym; Ichoku, Charles; Leptoukh, Gregory

2011-01-01

Cross-comparison of aerosol properties between ground-based and spaceborne measurements is an important validation technique that helps to investigate the uncertainties of aerosol products acquired using spaceborne sensors. However, it has been shown that even minor differences in the cross-characterization procedure may significantly impact the results of such validation. Of particular consideration is the quality assurance I quality control (QA/QC) information - an auxiliary data indicating a "confidence" level (e.g., Bad, Fair, Good, Excellent, etc.) conferred by the retrieval algorithms on the produced data. Depending on the treatment of available QA/QC information, a cross-characterization procedure has the potential of filtering out invalid data points, such as uncertain or erroneous retrievals, which tend to reduce the credibility of such comparisons. However, under certain circumstances, even high QA/QC values may not fully guarantee the quality of the data. For example, retrievals in proximity of a cloud might be particularly perplexing for an aerosol retrieval algorithm, resulting in an invalid data that, nonetheless, could be assigned a high QA/QC confidence. In this presentation, we will study the effects of several QA/QC parameters on cross-characterization of aerosol properties between the data acquired by multiple spaceborne sensors. We will utilize the Multi-sensor Aerosol Products Sampling System (MAPSS) that provides a consistent platform for multi-sensor comparison, including collocation with measurements acquired by the ground-based Aerosol Robotic Network (AERONET), The multi-sensor spaceborne data analyzed include those acquired by the Terra-MODIS, Aqua-MODIS, Terra-MISR, Aura-OMI, Parasol-POLDER, and CalipsoCALIOP satellite instruments.

Evaluation of Micronutrient Sensors for Food Matrices in Resource-Limited Settings: A Systematic Narrative Review.

PubMed

Waller, Anna W; Lotton, Jennifer L; Gaur, Shashank; Andrade, Jeanette M; Andrade, Juan E

2018-06-21

In resource-limited settings, mass food fortification is a common strategy to ensure the population consumes appropriate quantities of essential micronutrients. Food and government organizations in these settings, however, lack tools to monitor the quality and compliance of fortified products and their efficacy to enhance nutrient status. The World Health Organization has developed general guidelines known as ASSURED (Affordable, Sensitive, Specific, User-friendly, Rapid and Robust, Equipment-free, and Deliverable to end-users) to aid the development of useful diagnostic tools for these settings. These guidelines assume performance aspects such as sufficient accuracy, reliability, and validity. The purpose of this systematic narrative review is to examine the micronutrient sensor literature on its adherence towards the ASSURED criteria along with accuracy, reliability, and validation when developing micronutrient sensors for resource-limited settings. Keyword searches were conducted in three databases: Web of Science, PubMed, and Scopus and were based on 6-point inclusion criteria. A 16-question quality assessment tool was developed to determine the adherence towards quality and performance criteria. Of the 2,365 retrieved studies, 42 sensors were included based on inclusion/exclusion criteria. Results showed that improvements to the current sensor design are necessary, especially their affordability, user-friendliness, robustness, equipment-free, and deliverability within the ASSURED criteria, and accuracy and validity of the additional criteria to be useful in resource-limited settings. Although it requires further validation, the 16-question quality assessment tool can be used as a guide in the development of sensors for resource-limited settings. © 2018 Institute of Food Technologists®.

Temperature sensor based on high-Q polymethylmethacrylate optical microbubble

NASA Astrophysics Data System (ADS)

He, Chunhong; Sun, Huijin; Mo, Jun; Yang, Chao; Feng, Guoying; Zhou, Hao; Zhou, Shouhuan

2018-07-01

A new flexible method to fabricate a temperature sensor based on polymethylmethacrylate (PMMA) optical microbubbles, using a volume-controllable pipette, is demonstrated. The high quality factor of the cavity is guaranteed by the smooth wall of the microbubble. The shape and refractive index of the microbubbles change with the surrounding temperature, which leads to the obvious displacement of the whispering gallery mode transmission spectrum. As the surrounding temperature increases, the spectrum undergoes a significant blue shift, hence the microresonator can be used for temperature sensing. A sensitivity of 39 pm °C‑1 is obtained in a PMMA microbubble with a diameter of 740 µm. This work suggests a new convenient approach to achieving high-quality flexible microscale sensors.

Bio-implantable passive on-chip RF-MEMS strain sensing resonators for orthopaedic applications

NASA Astrophysics Data System (ADS)

Melik, Rohat; Kosku Perkgoz, Nihan; Unal, Emre; Puttlitz, Christian; Demir, Hilmi Volkan

2008-11-01

One out of ten bone fractures does not heal properly due to improper load distribution and strain profiles during the healing process. To provide implantable tools for the assessment of bone fractures, we have designed novel, bio-implantable, passive, on-chip, RF-MEMS strain sensors that rely on the resonance frequency shift with mechanical deformation. For this purpose, we modeled, fabricated and experimentally characterized two on-chip sensors with high quality factors for in vivo implantation. One of the sensors has an area of ~0.12 mm2 with a quality factor of ~60 and the other has an area of ~0.07 mm2 with a quality factor of ~70. To monitor the mechanical deformation by measuring the change in the resonance frequencies with the applied load, we employed a controllable, point load applying experimental setup designed and constructed for in vitro characterization. In the case of the sensor with the larger area, when we apply a load of 3920 N, we obtain a frequency shift of ~330 MHz and a quality factor of ~76. For the smaller sensor, the frequency shift and the quality factor are increased to 360 MHz and 95, respectively. These data demonstrate that our sensor chips have the capacity to withstand relatively high physiologic loads, and that the concomitant and very large resonant frequency shift with the applied load is achieved while maintaining a high signal quality factor. These experiments demonstrate that these novel sensors have the capacity for producing high sensitivity strain readout, even when the total device area is considerably small. Also, we have demonstrated that our bio-implantable, passive sensors deliver a telemetric, real-time readout of the strain on a chip. Placing two more resonators on the sides of the sensor to serve as transmitter and receiver antennas, we achieved to transfer contactless power and read out loads in the absence of direct wiring to the sensor. With this model, where telemetric measurements become simpler due to the fact that all sensor system is built on the same chip, we obtain a frequency shift of ~190 MHz with an increase in the quality factor from ~38 to ~46 when a load of 3920 N is applied. Therefore, as a first proof of concept, we have demonstrated the feasibility of our on-chip strain sensors for monitoring the mechanical deformation using telemetry-based systems.

Review on water quality sensors

NASA Astrophysics Data System (ADS)

Kruse, Peter

2018-05-01

Terrestrial life may be carbon-based, but most of its mass is made up of water. Access to clean water is essential to all aspects of maintaining life. Mainly due to human activity, the strain on the water resources of our planet has increased substantially, requiring action in water management and purification. Water quality sensors are needed in order to quantify the problem and verify the success of remedial actions. This review summarizes the most common chemical water quality parameters, and current developments in sensor technology available to monitor them. Particular emphasis is on technologies that lend themselves to reagent-free, low-maintenance, autonomous and continuous monitoring. Chemiresistors and other electrical sensors are discussed in particular detail, while mechanical, optical and electrochemical sensors also find mentioning. The focus here is on the physics of chemical signal transduction in sensor elements that are in direct contact with the analyte. All other sensing methods, and all other elements of sampling, sample pre-treatment as well as the collection, transmission and analysis of the data are not discussed here. Instead, the goal is to highlight the progress and remaining challenges in the development of sensor materials and designs for an audience of physicists and materials scientists.

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.

Instrumental intelligent test of food sensory quality as mimic of human panel test combining multiple cross-perception sensors and data fusion.

PubMed

Ouyang, Qin; Zhao, Jiewen; Chen, Quansheng

2014-09-02

Instrumental test of food quality using perception sensors instead of human panel test is attracting massive attention recently. A novel cross-perception multi-sensors data fusion imitating multiple mammal perception was proposed for the instrumental test in this work. First, three mimic sensors of electronic eye, electronic nose and electronic tongue were used in sequence for data acquisition of rice wine samples. Then all data from the three different sensors were preprocessed and merged. Next, three cross-perception variables i.e., color, aroma and taste, were constructed using principal components analysis (PCA) and multiple linear regression (MLR) which were used as the input of models. MLR, back-propagation artificial neural network (BPANN) and support vector machine (SVM) were comparatively used for modeling, and the instrumental test was achieved for the comprehensive quality of samples. Results showed the proposed cross-perception multi-sensors data fusion presented obvious superiority to the traditional data fusion methodologies, also achieved a high correlation coefficient (>90%) with the human panel test results. This work demonstrated that the instrumental test based on the cross-perception multi-sensors data fusion can actually mimic the human test behavior, therefore is of great significance to ensure the quality of products and decrease the loss of the manufacturers. Copyright © 2014 Elsevier B.V. All rights reserved.

Expected Improvements in the Quantitative Remote Sensing of Optically Complex Waters with the Use of an Optically Fast Hyperspectral Spectrometer—A Modeling Study

PubMed Central

Moses, Wesley J.; Bowles, Jeffrey H.; Corson, Michael R.

2015-01-01

Using simulated data, we investigated the effect of noise in a spaceborne hyperspectral sensor on the accuracy of the atmospheric correction of at-sensor radiances and the consequent uncertainties in retrieved water quality parameters. Specifically, we investigated the improvement expected as the F-number of the sensor is changed from 3.5, which is the smallest among existing operational spaceborne hyperspectral sensors, to 1.0, which is foreseeable in the near future. With the change in F-number, the uncertainties in the atmospherically corrected reflectance decreased by more than 90% across the visible-near-infrared spectrum, the number of pixels with negative reflectance (caused by over-correction) decreased to almost one-third, and the uncertainties in the retrieved water quality parameters decreased by more than 50% and up to 92%. The analysis was based on the sensor model of the Hyperspectral Imager for the Coastal Ocean (HICO) but using a 30-m spatial resolution instead of HICO’s 96 m. Atmospheric correction was performed using Tafkaa. Water quality parameters were retrieved using a numerical method and a semi-analytical algorithm. The results emphasize the effect of sensor noise on water quality parameter retrieval and the need for sensors with high Signal-to-Noise Ratio for quantitative remote sensing of optically complex waters. PMID:25781507

Design and Deployment of Low-Cost Sensors for Monitoring the Water Quality and Fish Behavior in Aquaculture Tanks during the Feeding Process

PubMed Central

Parra, Lorena; García, Laura

2018-01-01

The monitoring of farming processes can optimize the use of resources and improve its sustainability and profitability. In fish farms, the water quality, tank environment, and fish behavior must be monitored. Wireless sensor networks (WSNs) are a promising option to perform this monitoring. Nevertheless, its high cost is slowing the expansion of its use. In this paper, we propose a set of sensors for monitoring the water quality and fish behavior in aquaculture tanks during the feeding process. The WSN is based on physical sensors, composed of simple electronic components. The system proposed can monitor water quality parameters, tank status, the feed falling and fish swimming depth and velocity. In addition, the system includes a smart algorithm to reduce the energy waste when sending the information from the node to the database. The system is composed of three nodes in each tank that send the information though the local area network to a database on the Internet and a smart algorithm that detects abnormal values and sends alarms when they happen. All the sensors are designed, calibrated, and deployed to ensure its suitability. The greatest efforts have been accomplished with the fish presence sensor. The total cost of the sensors and nodes for the proposed system is less than 90 €. PMID:29494560

Design and Deployment of Low-Cost Sensors for Monitoring the Water Quality and Fish Behavior in Aquaculture Tanks during the Feeding Process.

PubMed

Parra, Lorena; Sendra, Sandra; García, Laura; Lloret, Jaime

2018-03-01

The monitoring of farming processes can optimize the use of resources and improve its sustainability and profitability. In fish farms, the water quality, tank environment, and fish behavior must be monitored. Wireless sensor networks (WSNs) are a promising option to perform this monitoring. Nevertheless, its high cost is slowing the expansion of its use. In this paper, we propose a set of sensors for monitoring the water quality and fish behavior in aquaculture tanks during the feeding process. The WSN is based on physical sensors, composed of simple electronic components. The system proposed can monitor water quality parameters, tank status, the feed falling and fish swimming depth and velocity. In addition, the system includes a smart algorithm to reduce the energy waste when sending the information from the node to the database. The system is composed of three nodes in each tank that send the information though the local area network to a database on the Internet and a smart algorithm that detects abnormal values and sends alarms when they happen. All the sensors are designed, calibrated, and deployed to ensure its suitability. The greatest efforts have been accomplished with the fish presence sensor. The total cost of the sensors and nodes for the proposed system is less than 90 €.

Strategy Developed for Selecting Optimal Sensors for Monitoring Engine Health

NASA Technical Reports Server (NTRS)

2004-01-01

Sensor indications during rocket engine operation are the primary means of assessing engine performance and health. Effective selection and location of sensors in the operating engine environment enables accurate real-time condition monitoring and rapid engine controller response to mitigate critical fault conditions. These capabilities are crucial to ensure crew safety and mission success. Effective sensor selection also facilitates postflight condition assessment, which contributes to efficient engine maintenance and reduced operating costs. Under the Next Generation Launch Technology program, the NASA Glenn Research Center, in partnership with Rocketdyne Propulsion and Power, has developed a model-based procedure for systematically selecting an optimal sensor suite for assessing rocket engine system health. This optimization process is termed the systematic sensor selection strategy. Engine health management (EHM) systems generally employ multiple diagnostic procedures including data validation, anomaly detection, fault-isolation, and information fusion. The effectiveness of each diagnostic component is affected by the quality, availability, and compatibility of sensor data. Therefore systematic sensor selection is an enabling technology for EHM. Information in three categories is required by the systematic sensor selection strategy. The first category consists of targeted engine fault information; including the description and estimated risk-reduction factor for each identified fault. Risk-reduction factors are used to define and rank the potential merit of timely fault diagnoses. The second category is composed of candidate sensor information; including type, location, and estimated variance in normal operation. The final category includes the definition of fault scenarios characteristic of each targeted engine fault. These scenarios are defined in terms of engine model hardware parameters. Values of these parameters define engine simulations that generate expected sensor values for targeted fault scenarios. Taken together, this information provides an efficient condensation of the engineering experience and engine flow physics needed for sensor selection. The systematic sensor selection strategy is composed of three primary algorithms. The core of the selection process is a genetic algorithm that iteratively improves a defined quality measure of selected sensor suites. A merit algorithm is employed to compute the quality measure for each test sensor suite presented by the selection process. The quality measure is based on the fidelity of fault detection and the level of fault source discrimination provided by the test sensor suite. An inverse engine model, whose function is to derive hardware performance parameters from sensor data, is an integral part of the merit algorithm. The final component is a statistical evaluation algorithm that characterizes the impact of interference effects, such as control-induced sensor variation and sensor noise, on the probability of fault detection and isolation for optimal and near-optimal sensor suites.

Quality monitoring of extra-virgin olive oil using an optical sensor

NASA Astrophysics Data System (ADS)

Mignani, A. G.; Ciaccheri, L.; Mencaglia, A. A.; Paolesse, R.; Di Natale, C.; Del Nobile, A.; Benedetto, A.; Mentana, A.

2006-04-01

An optical sensor for the detection of olive oil aroma is presented. It is capable of distinguishing different ageing levels of extra-virgin olive oils, and shows effective potential for achieving a non destructive olfactory perception of oil ageing. The sensor is an optical scanner, fitted with an array of metalloporphyrin-based sensors. The scanner provides exposure of the sensors to the flow of the oil vapor being tested, and their sequential spectral interrogation. Spectral data are then processed using chemometric methodologies.

Human Factors Affecting the Patient's Acceptance of Wireless Biomedical Sensors

NASA Astrophysics Data System (ADS)

Fensli, Rune; Boisen, Egil

In monitoring arrhythmia, the quality of medical data from the ECG sensors may be enhanced by being based on everyday life situations. Hence, the development of wireless biomedical sensors is of growing interest, both to diagnose the heart patient, as well as to adjust the regimen. However, human factors such as emotional barriers and stigmatization, may affect the patient's behavior while wearing the equipment, which in turn may influence quality of data. The study of human factors and patient acceptance is important both in relation to the development of such equipment, as well as in evaluating the quality of data gathered from the individual patient. In this paper, we highlight some important aspects in patient acceptance by comparing results from a preliminary clinical trial with patients using a wireless ECG sensor for three days out-of-hospital service, to available published results from telehomecare projects, and discuss important aspects to be taken into account in future investigations.

CardioGuard: A Brassiere-Based Reliable ECG Monitoring Sensor System for Supporting Daily Smartphone Healthcare Applications

PubMed Central

Kwon, Sungjun; Kim, Jeehoon; Kang, Seungwoo; Lee, Youngki; Baek, Hyunjae

2014-01-01

Abstract We propose CardioGuard, a brassiere-based reliable electrocardiogram (ECG) monitoring sensor system, for supporting daily smartphone healthcare applications. It is designed to satisfy two key requirements for user-unobtrusive daily ECG monitoring: reliability of ECG sensing and usability of the sensor. The system is validated through extensive evaluations. The evaluation results showed that the CardioGuard sensor reliably measure the ECG during 12 representative daily activities including diverse movement levels; 89.53% of QRS peaks were detected on average. The questionnaire-based user study with 15 participants showed that the CardioGuard sensor was comfortable and unobtrusive. Additionally, the signal-to-noise ratio test and the washing durability test were conducted to show the high-quality sensing of the proposed sensor and its physical durability in practical use, respectively. PMID:25405527

MOF-Based Membrane Encapsulated ZnO Nanowires for Enhanced Gas Sensor Selectivity.

PubMed

Drobek, Martin; Kim, Jae-Hun; Bechelany, Mikhael; Vallicari, Cyril; Julbe, Anne; Kim, Sang Sub

2016-04-06

Gas sensors are of a great interest for applications including toxic or explosive gases detection in both in-house and industrial environments, air quality monitoring, medical diagnostics, or control of food/cosmetic properties. In the area of semiconductor metal oxides (SMOs)-based sensors, a lot of effort has been devoted to improve the sensing characteristics. In this work, we report on a general methodology for improving the selectivity of SMOx nanowires sensors, based on the coverage of ZnO nanowires with a thin ZIF-8 molecular sieve membrane. The optimized ZnO@ZIF-8-based nanocomposite sensor shows markedly selective response to H2 in comparison with the pristine ZnO nanowires sensor, while showing the negligible sensing response to C7H8 and C6H6. This original MOF-membrane encapsulation strategy applied to nanowires sensor architecture pave the way for other complex 3D architectures and various types of applications requiring either gas or ion selectivity, such as biosensors, photo(catalysts), and electrodes.

A Wireless Sensor Network-Based Approach with Decision Support for Monitoring Lake Water Quality.

PubMed

Huang, Xiaoci; Yi, Jianjun; Chen, Shaoli; Zhu, Xiaomin

2015-11-19

Online monitoring and water quality analysis of lakes are urgently needed. A feasible and effective approach is to use a Wireless Sensor Network (WSN). Lake water environments, like other real world environments, present many changing and unpredictable situations. To ensure flexibility in such an environment, the WSN node has to be prepared to deal with varying situations. This paper presents a WSN self-configuration approach for lake water quality monitoring. The approach is based on the integration of a semantic framework, where a reasoner can make decisions on the configuration of WSN services. We present a WSN ontology and the relevant water quality monitoring context information, which considers its suitability in a pervasive computing environment. We also propose a rule-based reasoning engine that is used to conduct decision support through reasoning techniques and context-awareness. To evaluate the approach, we conduct usability experiments and performance benchmarks.

Coverage-guaranteed sensor node deployment strategies for wireless sensor networks.

PubMed

Fan, Gaojuan; Wang, Ruchuan; Huang, Haiping; Sun, Lijuan; Sha, Chao

2010-01-01

Deployment quality and cost are two conflicting aspects in wireless sensor networks. Random deployment, where the monitored field is covered by randomly and uniformly deployed sensor nodes, is an appropriate approach for large-scale network applications. However, their successful applications depend considerably on the deployment quality that uses the minimum number of sensors to achieve a desired coverage. Currently, the number of sensors required to meet the desired coverage is based on asymptotic analysis, which cannot meet deployment quality due to coverage overestimation in real applications. In this paper, we first investigate the coverage overestimation and address the challenge of designing coverage-guaranteed deployment strategies. To overcome this problem, we propose two deployment strategies, namely, the Expected-area Coverage Deployment (ECD) and BOundary Assistant Deployment (BOAD). The deployment quality of the two strategies is analyzed mathematically. Under the analysis, a lower bound on the number of deployed sensor nodes is given to satisfy the desired deployment quality. We justify the correctness of our analysis through rigorous proof, and validate the effectiveness of the two strategies through extensive simulation experiments. The simulation results show that both strategies alleviate the coverage overestimation significantly. In addition, we also evaluate two proposed strategies in the context of target detection application. The comparison results demonstrate that if the target appears at the boundary of monitored region in a given random deployment, the average intrusion distance of BOAD is considerably shorter than that of ECD with the same desired deployment quality. In contrast, ECD has better performance in terms of the average intrusion distance when the invasion of intruder is from the inside of monitored region.

A Chip and Pixel Qualification Methodology on Imaging Sensors

NASA Technical Reports Server (NTRS)

Chen, Yuan; Guertin, Steven M.; Petkov, Mihail; Nguyen, Duc N.; Novak, Frank

2004-01-01

This paper presents a qualification methodology on imaging sensors. In addition to overall chip reliability characterization based on sensor s overall figure of merit, such as Dark Rate, Linearity, Dark Current Non-Uniformity, Fixed Pattern Noise and Photon Response Non-Uniformity, a simulation technique is proposed and used to project pixel reliability. The projected pixel reliability is directly related to imaging quality and provides additional sensor reliability information and performance control.

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 Survey on Data Quality for Dependable Monitoring in Wireless Sensor Networks

PubMed Central

Oliveira, Anabela

2017-01-01

Wireless sensor networks are being increasingly used in several application areas, particularly to collect data and monitor physical processes. Non-functional requirements, like reliability, security or availability, are often important and must be accounted for in the application development. For that purpose, there is a large body of knowledge on dependability techniques for distributed systems, which provide a good basis to understand how to satisfy these non-functional requirements of WSN-based monitoring applications. Given the data-centric nature of monitoring applications, it is of particular importance to ensure that data are reliable or, more generically, that they have the necessary quality. In this survey, we look into the problem of ensuring the desired quality of data for dependable monitoring using WSNs. We take a dependability-oriented perspective, reviewing the possible impairments to dependability and the prominent existing solutions to solve or mitigate these impairments. Despite the variety of components that may form a WSN-based monitoring system, we give particular attention to understanding which faults can affect sensors, how they can affect the quality of the information and how this quality can be improved and quantified. PMID:28869505

Environmental urban runoff monitoring

NASA Astrophysics Data System (ADS)

Yu, Byunggu; Behera, Pradeep K.; Kim, Seon Ho; Ramirez Rochac, Juan F.; Branham, Travis

2010-04-01

Urban stormwater runoff has been a critical and chronic problem in the quantity and quality of receiving waters, resulting in a major environmental concern. To address this problem engineers and professionals have developed a number of solutions which include various monitoring and modeling techniques. The most fundamental issue in these solutions is accurate monitoring of the quantity and quality of the runoff from both combined and separated sewer systems. This study proposes a new water quantity monitoring system, based on recent developments in sensor technology. Rather than using a single independent sensor, we harness an intelligent sensor platform that integrates various sensors, a wireless communication module, data storage, a battery, and processing power such that more comprehensive, efficient, and scalable data acquisition becomes possible. Our experimental results show the feasibility and applicability of such a sensor platform in the laboratory test setting.

High-Performance Sensors Based on Resistance Fluctuations of Single-Layer-Graphene Transistors.

PubMed

Amin, Kazi Rafsanjani; Bid, Aveek

2015-09-09

One of the most interesting predicted applications of graphene-monolayer-based devices is as high-quality sensors. In this article, we show, through systematic experiments, a chemical vapor sensor based on the measurement of low-frequency resistance fluctuations of single-layer-graphene field-effect-transistor devices. The sensor has extremely high sensitivity, very high specificity, high fidelity, and fast response times. The performance of the device using this scheme of measurement (which uses resistance fluctuations as the detection parameter) is more than 2 orders of magnitude better than a detection scheme in which changes in the average value of the resistance is monitored. We propose a number-density-fluctuation-based model to explain the superior characteristics of a noise-measurement-based detection scheme presented in this article.

Overhauser Geomagnetic Sensor Based on the Dynamic Nuclear Polarization Effect for Magnetic Prospecting

PubMed Central

Ge, Jian; Dong, Haobin; Liu, Huan; Yuan, Zhiwen; Dong, He; Zhao, Zhizhuo; Liu, Yonghua; Zhu, Jun; Zhang, Haiyang

2016-01-01

Based on the dynamic nuclear polarization (DNP) effect, an alternative design of an Overhauser geomagnetic sensor is presented that enhances the proton polarization and increases the amplitude of the free induction decay (FID) signal. The short-pulse method is adopted to rotate the enhanced proton magnetization into the plane of precession to create an FID signal. To reduce the negative effect of the powerful electromagnetic interference, the design of the anti-interference of the pick-up coil is studied. Furthermore, the radio frequency polarization method based on the capacitive-loaded coaxial cavity is proposed to improve the quality factor of the resonant circuit. In addition, a special test instrument is designed that enables the simultaneous testing of the classical proton precession and the Overhauser sensor. Overall, comparison experiments with and without the free radical of the Overhauser sensors show that the DNP effect does effectively improve the amplitude and quality of the FID signal, and the magnetic sensitivity, resolution and range reach to 10 pT/Hz1/2@1 Hz, 0.0023 nT and 20–100 μT, respectively. PMID:27258283

Sunlight Intensity Based Global Positioning System for Near-Surface Underwater Sensors

PubMed Central

Gómez, Javier V.; Sandnes, Frode E.; Fernández, Borja

2012-01-01

Water monitoring is important in domains including documenting climate change, weather prediction and fishing. This paper presents a simple and energy efficient localization strategy for near surface buoy based sensors. Sensors can be dropped randomly in the ocean and thus self-calibrate in terms of geographic location such that geo-tagged observations of water quality can be made without the need for costly and energy consuming GPS-hardware. The strategy is based on nodes with an accurate clock and light sensors that can regularly sample the level of light intensity. The measurements are fitted into a celestial model of the earth motion around the sun. By identifying the trajectory of the sun across the skies one can accurately determine sunrise and sunset times, and thus extract the longitude and latitude of the sensor. Unlike previous localization techniques for underwater sensors, the current approach does not rely on stationary or mobile reference points. PMID:22438746

Sunlight intensity based global positioning system for near-surface underwater sensors.

PubMed

Gómez, Javier V; Sandnes, Frode E; Fernández, Borja

2012-01-01

Water monitoring is important in domains including documenting climate change, weather prediction and fishing. This paper presents a simple and energy efficient localization strategy for near surface buoy based sensors. Sensors can be dropped randomly in the ocean and thus self-calibrate in terms of geographic location such that geo-tagged observations of water quality can be made without the need for costly and energy consuming GPS-hardware. The strategy is based on nodes with an accurate clock and light sensors that can regularly sample the level of light intensity. The measurements are fitted into a celestial model of the earth motion around the sun. By identifying the trajectory of the sun across the skies one can accurately determine sunrise and sunset times, and thus extract the longitude and latitude of the sensor. Unlike previous localization techniques for underwater sensors, the current approach does not rely on stationary or mobile reference points.

Development of a Personal Integrated Environmental Monitoring System

PubMed Central

Wong, Man Sing; Yip, Tsan Pong; Mok, Esmond

2014-01-01

Environmental pollution in the urban areas of Hong Kong has become a serious public issue but most urban inhabitants have no means of judging their own living environment in terms of dangerous threshold and overall livability. Currently there exist many low-cost sensors such as ultra-violet, temperature and air quality sensors that provide reasonably accurate data quality. In this paper, the development and evaluation of Integrated Environmental Monitoring System (IEMS) are illustrated. This system consists of three components: (i) position determination and sensor data collection for real-time geospatial-based environmental monitoring; (ii) on-site data communication and visualization with the aid of an Android-based application; and (iii) data analysis on a web server. This system has shown to be working well during field tests in a bus journey and a construction site. It provides an effective service platform for collecting environmental data in near real-time, and raises the public awareness of environmental quality in micro-environments. PMID:25420154

Detection of premature browning in ground beef with an integrated optical-fibre based sensor using reflection spectroscopy and fibre Bragg grating technology

NASA Astrophysics Data System (ADS)

O'Farrell, M.; Sheridan, C.; Lewis, E.; Zhao, W. Z.; Sun, T.; Grattan, K. T. V.; Kerry, J.; Jackman, N.

2007-07-01

This paper reports on an optical fibre based sensor system to detect the occurrence of premature browning in ground beef. Premature browning (PMB) occurs when, at a temperature below the pasteurisation temperature of 71°C, there are no traces of pink meat left in the patty. PMB is more frequent if poorer quality beef or beef that has been stored under imperfect conditions. The experimental work pertaining to this paper involved cooking fresh meat and meat that has been stored in a freezer for, 1 week, 1 month and 3 months and recording the reflected spectra and temperature at the core of the product, during the cooking process, in order to develop a classifier based on the spectral response and using a Self-Organising Map (SOM) to classify the patties into one of four categories, based on their colour. Further tests were also carried out on developing an all-optical fibre sensor for measuring both the temperature and colour in a single integrated probe. The integrated probe contains two different sensor concepts, one to monitor temperature, based on Fibre Bragg Grating (FBG) technology and a second for meat quality, based on reflection spectroscopy in the visible wavelength range.

Network hydraulics inclusion in water quality event detection using multiple sensor stations data.

PubMed

Oliker, Nurit; Ostfeld, Avi

2015-09-01

Event detection is one of the current most challenging topics in water distribution systems analysis: how regular on-line hydraulic (e.g., pressure, flow) and water quality (e.g., pH, residual chlorine, turbidity) measurements at different network locations can be efficiently utilized to detect water quality contamination events. This study describes an integrated event detection model which combines multiple sensor stations data with network hydraulics. To date event detection modelling is likely limited to single sensor station location and dataset. Single sensor station models are detached from network hydraulics insights and as a result might be significantly exposed to false positive alarms. This work is aimed at decreasing this limitation through integrating local and spatial hydraulic data understanding into an event detection model. The spatial analysis complements the local event detection effort through discovering events with lower signatures by exploring the sensors mutual hydraulic influences. The unique contribution of this study is in incorporating hydraulic simulation information into the overall event detection process of spatially distributed sensors. The methodology is demonstrated on two example applications using base runs and sensitivity analyses. Results show a clear advantage of the suggested model over single-sensor event detection schemes. Copyright © 2015 Elsevier Ltd. All rights reserved.

Detection of Obstacles in Monocular Image Sequences

NASA Technical Reports Server (NTRS)

Kasturi, Rangachar; Camps, Octavia

1997-01-01

The ability to detect and locate runways/taxiways and obstacles in images captured using on-board sensors is an essential first step in the automation of low-altitude flight, landing, takeoff, and taxiing phase of aircraft navigation. Automation of these functions under different weather and lighting situations, can be facilitated by using sensors of different modalities. An aircraft-based Synthetic Vision System (SVS), with sensors of different modalities mounted on-board, complements the current ground-based systems in functions such as detection and prevention of potential runway collisions, airport surface navigation, and landing and takeoff in all weather conditions. In this report, we address the problem of detection of objects in monocular image sequences obtained from two types of sensors, a Passive Millimeter Wave (PMMW) sensor and a video camera mounted on-board a landing aircraft. Since the sensors differ in their spatial resolution, and the quality of the images obtained using these sensors is not the same, different approaches are used for detecting obstacles depending on the sensor type. These approaches are described separately in two parts of this report. The goal of the first part of the report is to develop a method for detecting runways/taxiways and objects on the runway in a sequence of images obtained from a moving PMMW sensor. Since the sensor resolution is low and the image quality is very poor, we propose a model-based approach for detecting runways/taxiways. We use the approximate runway model and the position information of the camera provided by the Global Positioning System (GPS) to define regions of interest in the image plane to search for the image features corresponding to the runway markers. Once the runway region is identified, we use histogram-based thresholding to detect obstacles on the runway and regions outside the runway. This algorithm is tested using image sequences simulated from a single real PMMW image.

Development of on package indicator sensor for real-time monitoring of meat quality

PubMed Central

Shukla, Vivek; Kandeepan, G.; Vishnuraj, M. R.

2015-01-01

Aim: The aim was to develop an indicator sensor for real-time monitoring of meat quality and to compare the response of indicator sensor with meat quality parameters at ambient temperature. Materials and Methods: Indicator sensor was prepared using bromophenol blue (1% w/v) as indicator solution and filter paper as indicator carrier. Indicator sensor was fabricated by coating indicator solution onto carrier by centrifugation. To observe the response of indicator sensor buffalo meat was packed in polystyrene foam trays covered with PVC film and indicator sensor was attached to the inner side of packaging film. The pattern of color change in indicator sensor was monitored and compared with meat quality parameters viz. total volatile basic nitrogen, D-glucose, standard plate count and tyrosine value to correlate ability of indicator sensor for its suitability to predict the meat quality and storage life. Results: The indicator sensor changed its color from yellow to blue starting from margins during the storage period of 24 h at ambient temperature and this correlated well with changes in meat quality parameters. Conclusions: The indicator sensor can be used for real-time monitoring of meat quality as the color of indicator sensor changed from yellow to blue starting from margins when meat deteriorates with advancement of the storage period. Thus by observing the color of indicator sensor quality of meat and shelf life can be predicted. PMID:27047103

Acoustic Emission Behavior of Early Age Concrete Monitored by Embedded Sensors.

PubMed

Qin, Lei; Ren, Hong-Wei; Dong, Bi-Qin; Xing, Feng

2014-10-02

Acoustic emission (AE) is capable of monitoring the cracking activities inside materials. In this study, embedded sensors were employed to monitor the AE behavior of early age concrete. Type 1-3 cement-based piezoelectric composites, which had lower mechanical quality factor and acoustic impedance, were fabricated and used to make sensors. Sensors made of the composites illustrated broadband frequency response. In a laboratory, the cracking of early age concrete was monitored to recognize different hydration stages. The sensors were also embedded in a mass concrete foundation to localize the temperature gradient cracks.

Development of novel wireless sensor for food quality detection

NASA Astrophysics Data System (ADS)

Son Nguyen, Dat; Ngan Le, Nguyen; Phat Lam, Tan; Fribourg-Blanc, Eric; Chien Dang, Mau; Tedjini, Smail

2015-12-01

In this paper we present a wireless sensor for the monitoring of food quality. We integrate sensing capability into ultrahigh frequency (UHF) radio-frequency identification (RFID) tags through the relationship between the physical read-range and permittivity of the object we label with the RFID tags. Using the known variations of food permittivity as a function of time, we can detect the contamination time at which a food product becomes unacceptable for consumption based on the measurement of read-range with the as-designed sensing tags. This low-cost UHF RFID passive sensor was designed and experimentally tested on beef, pork, and cheese with the same storage conditions as in supermarkets. The agreement between the experimental and simulation results show the potential of this technique for practical application in food-quality tracking.

A Review and Analysis of Remote Sensing Capability for Air Quality Measurements as a Potential Decision Support Tool Conducted by the NASA DEVELOP Program

NASA Technical Reports Server (NTRS)

Ross, A.; Richards, A.; Keith, K.; Frew, C.; Boseck, J.; Sutton, S.; Watts, C.; Rickman, D.

2007-01-01

This project focused on a comprehensive utilization of air quality model products as decision support tools (DST) needed for public health applications. A review of past and future air quality measurement methods and their uncertainty, along with the relationship of air quality to national and global public health, is vital. This project described current and future NASA satellite remote sensing and ground sensing capabilities and the potential for using these sensors to enhance the prediction, prevention, and control of public health effects that result from poor air quality. The qualitative uncertainty of current satellite remotely sensed air quality, the ground-based remotely sensed air quality, the air quality/public health model, and the decision making process is evaluated in this study. Current peer-reviewed literature suggests that remotely sensed air quality parameters correlate well with ground-based sensor data. A satellite remote-sensed and ground-sensed data complement is needed to enhance the models/tools used by policy makers for the protection of national and global public health communities

Embedded spectroscopic fiber sensor for on-line arc-welding analysis.

PubMed

Mirapeix, Jesús; Cobo, Adolfo; Quintela, Antonio; López-Higuera, José-Miguel

2007-06-01

A new fiber sensor system designed for spectroscopic analysis and on-line quality assurance of arc-welding processes is presented here. Although several different approaches have been considered for the optical capture of plasma emission in arc-welding processes, they tend to be invasive and make use of optical devices such as collimators or photodiodes. The solution proposed here is based on the arrangement of an optical fiber, which is used at the same time as the optical capturing device and also to deliver the optical information to a spectrometer, embedded within an arc-welding torch. It will be demonstrated that, by using the shielding gas as a protection for the fiber end, the plasma light emission is efficiently collected, forming a sensor system completely transparent and noninvasive for the welding operator. The feasibility of the proposed sensor designed to be used as the input optics of a welding quality-assurance system based on plasma spectroscopy will be demonstrated by means of several welding tests.

Effect of Using an Indoor Air Quality Sensor on Perceptions of and Behaviors Toward Air Pollution (Pittsburgh Empowerment Library Study): Online Survey and Interviews

PubMed Central

Dias, M Beatrice; Taylor, Michael

2018-01-01

Background Air quality affects us all and is a rapidly growing concern in the 21st century. We spend the majority of our lives indoors and can be exposed to a number of pollutants smaller than 2.5 microns (particulate matter, PM2.5) resulting in detrimental health effects. Indoor air quality sensors have the potential to provide people with the information they need to understand their risk and take steps to reduce their exposure. One such sensor is the Speck sensor developed at the Community Robotics, Education and Technology Empowerment Lab at Carnegie Mellon University. This sensor provides users with continuous real-time and historical PM2.5 information, a Web-based platform where people can track their PM2.5 levels over time and learn about ways to reduce their exposure, and a venue (blog post) for the user community to exchange information. Little is known about how the use of such monitors affects people’s knowledge, attitudes, and behaviors with respect to indoor air pollution. Objective The aim of this study was to assess whether using the sensor changes what people know and do about indoor air pollution. Methods We conducted 2 studies. In the first study, we recruited 276 Pittsburgh residents online and through local branches of the Carnegie Library of Pittsburgh, where the Speck sensor was made available by the researchers in the library catalog. Participants completed a 10- to 15-min survey on air pollution knowledge (its health impact, sources, and mitigation options), perceptions of indoor air quality, confidence in mitigation, current behaviors toward air quality, and personal empowerment and creativity in the spring and summer of 2016. In our second study, we surveyed 26 Pittsburgh residents in summer 2016 who checked out the Speck sensor for 3 weeks on the same measures assessed in the first study, with additional questions about the perception and use of the sensor. Follow-up interviews were conducted with a subset of those who used the Speck sensor. Results A series of paired t tests found participants were significantly more knowledgeable (t25=−2.61, P=.02), reported having significantly better indoor air quality (t25=−5.20, P<.001), and felt more confident about knowing how to mitigate their risk (t25=−1.87, P=.07) after using the Speck sensor than before. McNemar test showed participants tended to take more action to reduce indoor air pollution after using the sensor (χ225=2.7, P=.10). Qualitative analysis suggested possible ripple effects of use, including encouraging family and friends to learn about indoor air pollution. Conclusions Providing people with low- or no-cost portable indoor air quality monitors, with a supporting Web-based platform that offers information about how to reduce risk, can help people better express perceptions and adopt behaviors commensurate with the risks they face. Thus, thoughtfully designed and deployed personal sensing devices can help empower people to take steps to reduce their risk. PMID:29519779

Effect of Using an Indoor Air Quality Sensor on Perceptions of and Behaviors Toward Air Pollution (Pittsburgh Empowerment Library Study): Online Survey and Interviews.

PubMed

Wong-Parodi, Gabrielle; Dias, M Beatrice; Taylor, Michael

2018-03-08

Air quality affects us all and is a rapidly growing concern in the 21st century. We spend the majority of our lives indoors and can be exposed to a number of pollutants smaller than 2.5 microns (particulate matter, PM 2.5 ) resulting in detrimental health effects. Indoor air quality sensors have the potential to provide people with the information they need to understand their risk and take steps to reduce their exposure. One such sensor is the Speck sensor developed at the Community Robotics, Education and Technology Empowerment Lab at Carnegie Mellon University. This sensor provides users with continuous real-time and historical PM 2.5 information, a Web-based platform where people can track their PM 2.5 levels over time and learn about ways to reduce their exposure, and a venue (blog post) for the user community to exchange information. Little is known about how the use of such monitors affects people's knowledge, attitudes, and behaviors with respect to indoor air pollution. The aim of this study was to assess whether using the sensor changes what people know and do about indoor air pollution. We conducted 2 studies. In the first study, we recruited 276 Pittsburgh residents online and through local branches of the Carnegie Library of Pittsburgh, where the Speck sensor was made available by the researchers in the library catalog. Participants completed a 10- to 15-min survey on air pollution knowledge (its health impact, sources, and mitigation options), perceptions of indoor air quality, confidence in mitigation, current behaviors toward air quality, and personal empowerment and creativity in the spring and summer of 2016. In our second study, we surveyed 26 Pittsburgh residents in summer 2016 who checked out the Speck sensor for 3 weeks on the same measures assessed in the first study, with additional questions about the perception and use of the sensor. Follow-up interviews were conducted with a subset of those who used the Speck sensor. A series of paired t tests found participants were significantly more knowledgeable (t 25 =-2.61, P=.02), reported having significantly better indoor air quality (t 25 =-5.20, P<.001), and felt more confident about knowing how to mitigate their risk (t 25 =-1.87, P=.07) after using the Speck sensor than before. McNemar test showed participants tended to take more action to reduce indoor air pollution after using the sensor (χ 2 25 =2.7, P=.10). Qualitative analysis suggested possible ripple effects of use, including encouraging family and friends to learn about indoor air pollution. Providing people with low- or no-cost portable indoor air quality monitors, with a supporting Web-based platform that offers information about how to reduce risk, can help people better express perceptions and adopt behaviors commensurate with the risks they face. Thus, thoughtfully designed and deployed personal sensing devices can help empower people to take steps to reduce their risk. ©Gabrielle Wong-Parodi, M Beatrice Dias, Michael Taylor. Originally published in JMIR Mhealth and Uhealth (http://mhealth.jmir.org), 08.03.2018.

Image quality evaluation of eight complementary metal-oxide semiconductor intraoral digital X-ray sensors.

PubMed

Teich, Sorin; Al-Rawi, Wisam; Heima, Masahiro; Faddoul, Fady F; Goldzweig, Gil; Gutmacher, Zvi; Aizenbud, Dror

2016-10-01

To evaluate the image quality generated by eight commercially available intraoral sensors. Eighteen clinicians ranked the quality of a bitewing acquired from one subject using eight different intraoral sensors. Analytical methods used to evaluate clinical image quality included the Visual Grading Characteristics method, which helps to quantify subjective opinions to make them suitable for analysis. The Dexis sensor was ranked significantly better than Sirona and Carestream-Kodak sensors; and the image captured using the Carestream-Kodak sensor was ranked significantly worse than those captured using Dexis, Schick and Cyber Medical Imaging sensors. The Image Works sensor image was rated the lowest by all clinicians. Other comparisons resulted in non-significant results. None of the sensors was considered to generate images of significantly better quality than the other sensors tested. Further research should be directed towards determining the clinical significance of the differences in image quality reported in this study. © 2016 FDI World Dental Federation.

In situ optical water-quality sensor networks - Workshop summary report

USGS Publications Warehouse

Pellerin, Brian A.; Bergamaschi, Brian A.; Horsburgh, Jeffery S.

2012-01-01

Advanced in situ optical water-quality sensors and new techniques for data analysis hold enormous promise for furthering scientific understanding of aquatic systems. These sensors measure important biogeochemical parameters for long deployments, enabling the capture of data at time scales over which they vary most meaningfully. The high-frequency, real-time water-quality data they generate provide opportunities for early warning of water-quality deterioration, trend detection, and science-based decision support. However, developing networks of optical sensors in freshwater systems that report reliable and comparable data across and between sites remains a challenge to the research and monitoring community. To address this, the U. S. Geological Survey (USGS) and the Consortium of Universities for the Advancement of Hydrologic Science, Inc. (CUAHSI) convened a joint 3-day workshop (June 8-10, 2011) at the National Conservation Training Center in Shepardstown, West Virginia, to explore ways to coordinate development of standards and applications for optical sensors, and improve handling, storing, and analyzing the continuous data they produce. The workshop brought together more than 60 scientists, program managers, and vendors from universities, government agencies, and the private sector. Several important outcomes emerged from the presentations and breakout sessions. There was general consensus that making intercalibrated measurements requires that both manufacturers and users better characterize and calibrate the sensors under field conditions. For example, the influence of suspended particles, highly colored water, and temperature on optical sensors remains poorly understood, but consistently accounting for these factors is critical to successful deployment and for interpreting results in different settings. This, in turn, highlights the lack of appropriate standards for sensor calibrations, field checks, and characterizing interferences, as well as methods for data validation, treatment, and analysis of resulting measurements. Participants discussed a wide range of logistical considerations for successful sensor deployments, including key physical infrastructure, data loggers, and remote-communication techniques. Tools to manage, assure, and control quality, and explore large streams of continuous water-quality data are being developed by the USGS, CUAHSI, and other organizations, and will be critical to making full use of these highfrequency data for research and monitoring.

Chlordetect: Commercial Calcium Aluminate Based Conductimetric Sensor for Chloride Presence Detection

PubMed Central

Torres-Luque, Magda; Sánchez-Silva, Mauricio

2017-01-01

Chloride presence affects different environments (soil, water, concrete) decreasing their qualities. In order to assess chloride concentration this paper proposes a novel sensor for detecting and measuring it. This sensor is based on electric changes of commercial monocalcium aluminate (CA) when it interacts with chloride aqueous solutions. CA is used as a dielectric material between two coplanar capacitors. The geometry proposed for this sensor allows to assess the chloride content profile, or to make four times the same measurement. Besides, the experimental design gives us the possibility of study not just the chloride effect, but also the time and some geometric effects due to the sensor design. As a result, this sensor shows a limit of detection, sensitivity, and response time: 0.01 wt % Cl− and 0.06 wt % Cl−, and 2 min, respectively, comparable with other non invasive techniques as optical fibre sensors. PMID:28902147

Recent Advances in Paper-Based Sensors

PubMed Central

Liana, Devi D.; Raguse, Burkhard; Gooding, J. Justin; Chow, Edith

2012-01-01

Paper-based sensors are a new alternative technology for fabricating simple, low-cost, portable and disposable analytical devices for many application areas including clinical diagnosis, food quality control and environmental monitoring. The unique properties of paper which allow passive liquid transport and compatibility with chemicals/biochemicals are the main advantages of using paper as a sensing platform. Depending on the main goal to be achieved in paper-based sensors, the fabrication methods and the analysis techniques can be tuned to fulfill the needs of the end-user. Current paper-based sensors are focused on microfluidic delivery of solution to the detection site whereas more advanced designs involve complex 3-D geometries based on the same microfluidic principles. Although paper-based sensors are very promising, they still suffer from certain limitations such as accuracy and sensitivity. However, it is anticipated that in the future, with advances in fabrication and analytical techniques, that there will be more new and innovative developments in paper-based sensors. These sensors could better meet the current objectives of a viable low-cost and portable device in addition to offering high sensitivity and selectivity, and multiple analyte discrimination. This paper is a review of recent advances in paper-based sensors and covers the following topics: existing fabrication techniques, analytical methods and application areas. Finally, the present challenges and future outlooks are discussed. PMID:23112667

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.

Portable air quality sensor unit for participatory monitoring: an end-to-end VESNA-AQ based prototype

NASA Astrophysics Data System (ADS)

Vucnik, Matevz; Robinson, Johanna; Smolnikar, Miha; Kocman, David; Horvat, Milena; Mohorcic, Mihael

2015-04-01

Key words: portable air quality sensor, CITI-SENSE, participatory monitoring, VESNA-AQ The emergence of low-cost easy to use portable air quality sensors units is opening new possibilities for individuals to assess their exposure to air pollutants at specific place and time, and share this information through the Internet connection. Such portable sensors units are being used in an ongoing citizen science project called CITI-SENSE, which enables citizens to measure and share the data. The project aims through creating citizens observatories' to empower citizens to contribute to and participate in environmental governance, enabling them to support and influence community and societal priorities as well as associated decision making. An air quality measurement system based on VESNA sensor platform was primarily designed within the project for the use as portable sensor unit in selected pilot cities (Belgrade, Ljubljana and Vienna) for monitoring outdoor exposure to pollutants. However, functionally the same unit with different set of sensors could be used for example as an indoor platform. The version designed for the pilot studies was equipped with the following sensors: NO2, O3, CO, temperature, relative humidity, pressure and accelerometer. The personal sensor unit is battery powered and housed in a plastic box. The VESNA-based air quality (AQ) monitoring system comprises the VESNA-AQ portable sensor unit, a smartphone app and the remote server. Personal sensor unit supports wireless connection to an Android smartphone via built-in Wi-Fi. The smartphone in turn serves also as the communication gateway towards the remote server using any of available data connections. Besides the gateway functionality the role of smartphone is to enrich data coming from the personal sensor unit with the GPS location, timestamps and user defined context. This, together with an accelerometer, enables the user to better estimate ones exposure in relation to physical activities, time and location. The end user can monitor the measured parameters through a smartphone application. The smartphone app implements a custom developed LCSP (Lightweight Client Server Protocol) protocol which is used to send requests to the VESNA-AQ unit and to exchange information. When the data is obtained from the VESNA-AQ unit, the mobile application visualizes the data. It also has an option to forward the data to the remote server in a custom JSON structure over a HTTP POST request. The server stores the data in the database and in parallel translates the data to WFS and forwards it to the main CITI-SENSE platform over WFS-T in a common XML format over HTTP POST request. From there data can be accessed through the Internet and visualised in different forms and web applications developed by the CITI-SENSE project. In the course of the project, the collected data will be made publicly available enabling the citizens to participate in environmental governance. Acknowledgements: CITI-SENSE is a Collaborative Project partly funded by the EU FP7-ENV-2012 under grant agreement no 308524 (www.citi-sense.eu).

Sensor-Based Optimization Model for Air Quality Improvement in Home IoT

PubMed Central

Kim, Jonghyuk

2018-01-01

We introduce current home Internet of Things (IoT) technology and present research on its various forms and applications in real life. In addition, we describe IoT marketing strategies as well as specific modeling techniques for improving air quality, a key home IoT service. To this end, we summarize the latest research on sensor-based home IoT, studies on indoor air quality, and technical studies on random data generation. In addition, we develop an air quality improvement model that can be readily applied to the market by acquiring initial analytical data and building infrastructures using spectrum/density analysis and the natural cubic spline method. Accordingly, we generate related data based on user behavioral values. We integrate the logic into the existing home IoT system to enable users to easily access the system through the Web or mobile applications. We expect that the present introduction of a practical marketing application method will contribute to enhancing the expansion of the home IoT market. PMID:29570684

Sensor-Based Optimization Model for Air Quality Improvement in Home IoT.

PubMed

Kim, Jonghyuk; Hwangbo, Hyunwoo

2018-03-23

We introduce current home Internet of Things (IoT) technology and present research on its various forms and applications in real life. In addition, we describe IoT marketing strategies as well as specific modeling techniques for improving air quality, a key home IoT service. To this end, we summarize the latest research on sensor-based home IoT, studies on indoor air quality, and technical studies on random data generation. In addition, we develop an air quality improvement model that can be readily applied to the market by acquiring initial analytical data and building infrastructures using spectrum/density analysis and the natural cubic spline method. Accordingly, we generate related data based on user behavioral values. We integrate the logic into the existing home IoT system to enable users to easily access the system through the Web or mobile applications. We expect that the present introduction of a practical marketing application method will contribute to enhancing the expansion of the home IoT market.

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.

Explore the advantage of High-frequency Water Quality Data in Urban Surface Water: A Case Study in Bristol, UK

NASA Astrophysics Data System (ADS)

Chen, Y.; Han, D.

2017-12-01

Water system is an essential component in a smart city for its sustainability and resilience. The freshness and beauty of the water body would please people as well as benefit the local aquatic ecosystems. Water quality monitoring approach has evolved from the manual lab-based monitoring approach to the manual in-situ monitoring approach, and finally to the latest wireless-sensor-network (WSN) based solutions in recent decades. The development of the in-situ water quality sensors enable humans to collect high-frequency and real-time water quality data. This poster aims to explore the advantages of the high-frequency water quality data over the low-frequency data collected manually. The data is collected by a remote real-time high-frequency water quality monitor system based on the cutting edge smart city infrastructure in Bristol - `Bristol Is Open'. The water quality of Bristol Floating Harbour is monitored which is the focal area of Bristol with new buildings and features redeveloped in the past decades. This poster will first briefly introduce the water quality monitoring system, followed by the analysis of the advantages of the sub-hourly water quality data. Thus, the suggestion on the monitoring frequency will be given.

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.

Development of flexible SAW sensors for non-destructive testing of structure

NASA Astrophysics Data System (ADS)

Takpara, R.; Duquennoy, M.; Courtois, C.; Gonon, M.; Ouaftouh, M.; Martic, G.; Rguiti, M.; Jenot, F.; Seronveaux, L.; Pelegris, C.

2016-02-01

In order to accurately examine structures surfaces, it is interesting to use surface SAW (Surface Acoustic Wave). Such waves are well suited for example to detect early emerging cracks or to test the quality of a coating. In addition, when coatings are thin or when emergent cracks are precocious, it is necessary to excite surface waves beyond 10MHz. Finally, when structures are not flat, it makes sense to have flexible or conformable sensors for their characterization. To address this problem, we propose to develop SAW type of interdigital sensors (or IDT for InterDigital Transducer), based on flexible piezoelectric plates. Initially, in order to optimize these sensors, we modeled the behavior of these sensors and identified the optimum characteristic sizes. In particular, the thickness of the piezoelectric plate and the width of the interdigital electrodes have been studied. Secondly, we made composites based on barium titanate foams in order to have flexible piezoelectric plates and to carry out thereafter sensors. Then, we studied several techniques in order to optimize the interdigitated electrodes deposition on this type of material. One of the difficulties concerns the fineness of these electrodes because the ratio between the length (typically several millimeters) and the width (a few tens of micrometers) of electrodes is very high. Finally, mechanical, electrical and acoustical characterizations of the sensors deposited on aluminum substrates were able to show the quality of our achievement.

Quantum Random Number Generation Using a Quanta Image Sensor

PubMed Central

Amri, Emna; Felk, Yacine; Stucki, Damien; Ma, Jiaju; Fossum, Eric R.

2016-01-01

A new quantum random number generation method is proposed. The method is based on the randomness of the photon emission process and the single photon counting capability of the Quanta Image Sensor (QIS). It has the potential to generate high-quality random numbers with remarkable data output rate. In this paper, the principle of photon statistics and theory of entropy are discussed. Sample data were collected with QIS jot device, and its randomness quality was analyzed. The randomness assessment method and results are discussed. PMID:27367698

Offset Printing Plate Quality Sensor on a Low-Cost Processor

PubMed Central

Poljak, Jelena; Botella, Guillermo; García, Carlos; Poljaček, Sanja Mahović; Prieto-Matías, Manuel; Tirado, Francisco

2013-01-01

The aim of this work is to develop a microprocessor-based sensor that measures the quality of the offset printing plate through the introduction of different image analysis applications. The main features of the presented system are the low cost, the low amount of power consumption, its modularity and easy integration with other industrial modules for printing plates, and its robustness against noise environments. For the sake of clarity, a viability analysis of previous software is presented through different strategies, based on dynamic histogram and Hough transform. This paper provides performance and scalability data compared with existing costly commercial devices. Furthermore, a general overview of quality control possibilities for printing plates is presented and could be useful to a system where such controls are regularly conducted. PMID:24284766

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.

Development of a common biosensor format for an enzyme based biosensor array to monitor fruit quality.

PubMed

Jawaheer, Shobha; White, S F; Rughooputh, S D D V; Cullen, David C

2003-10-15

Individual enzyme-based biosensors involving three-electrode systems were developed for the detection of analytes comprising markers of the stage of maturity and quality in selected fruits of economic importance to tropical countries. Importantly, a common fabrication format has been developed to simplify manufacture and allow future integration of the individual sensors into a single multi-sensor array. Specifically, sensors for beta-D-glucose, total D-glucose, sucrose and ascorbic acid have been developed. Pectin, a natural polysaccharide present in plant cells, was used as a novel matrix to enhance enzyme entrapment and stabilisation in the sensors. Except for ascorbic acid, all the sensors function via the detection of enzymatically generated H2O2 at rhodinised carbon electrodes. Since ascorbic acid is electrochemically active at the working potential chosen (+350 mV vs. Ag/AgCl), it was measured directly. Enzyme sensors demonstrated expected response with respect to their substrates, typically 0-0.8 microA/20 mm2 electrode area response over analyte ranges of 0-7 mM. Interferences related to electrochemically active compounds present in fruits under study were significantly reduced by inclusion of a suitable cellulose acetate (CA) membrane or by enzymatic inactivation with ascorbate oxidase. Initial development was carried out into production of biosensor arrays. CA membranes were used to improve the linear range of the sensors, producing up to a fivefold improvement in the detection range compared to sensors without an additional diffusion barrier.

Development and Evaluation of A Novel and Cost-Effective Approach for Low-Cost NO₂ Sensor Drift Correction.

PubMed

Sun, Li; Westerdahl, Dane; Ning, Zhi

2017-08-19

Emerging low-cost gas sensor technologies have received increasing attention in recent years for air quality measurements due to their small size and convenient deployment. However, in the diverse applications these sensors face many technological challenges, including sensor drift over long-term deployment that cannot be easily addressed using mathematical correction algorithms or machine learning methods. This study aims to develop a novel approach to auto-correct the drift of commonly used electrochemical nitrogen dioxide (NO₂) sensor with comprehensive evaluation of its application. The impact of environmental factors on the NO₂ electrochemical sensor in low-ppb concentration level measurement was evaluated in laboratory and the temperature and relative humidity correction algorithm was evaluated. An automated zeroing protocol was developed and assessed using a chemical absorbent to remove NO₂ as a means to perform zero correction in varying ambient conditions. The sensor system was operated in three different environments in which data were compared to a reference NO₂ analyzer. The results showed that the zero-calibration protocol effectively corrected the observed drift of the sensor output. This technique offers the ability to enhance the performance of low-cost sensor based systems and these findings suggest extension of the approach to improve data quality from sensors measuring other gaseous pollutants in urban air.

Image Sensors Enhance Camera Technologies

NASA Technical Reports Server (NTRS)

2010-01-01

In the 1990s, a Jet Propulsion Laboratory team led by Eric Fossum researched ways of improving complementary metal-oxide semiconductor (CMOS) image sensors in order to miniaturize cameras on spacecraft while maintaining scientific image quality. Fossum s team founded a company to commercialize the resulting CMOS active pixel sensor. Now called the Aptina Imaging Corporation, based in San Jose, California, the company has shipped over 1 billion sensors for use in applications such as digital cameras, camera phones, Web cameras, and automotive cameras. Today, one of every three cell phone cameras on the planet feature Aptina s sensor technology.

Numerical performance analysis of quartz tuning fork-based force sensors

NASA Astrophysics Data System (ADS)

Dagdeviren, Omur E.; Schwarz, Udo D.

2017-01-01

Quartz tuning fork-based force sensors where one prong is immobilized onto a holder while the other one is allowed to oscillate freely (‘qPlus’ configuration) are in widespread use for high-resolution scanning probe microscopy applications. Due to the small size of the tuning forks (≈3 mm) and the complexity of the sensor assemblies, the reliable and repeatable manufacturing of the sensors has been challenging. In this paper, we investigate the contribution of the amount and location of the epoxy glue used to attach the tuning fork to its holder on the sensor’s performance. Towards this end, we use finite element analysis to model the entire sensor assembly and to perform static and dynamic numerical simulations. Our analysis reveals that increasing the thickness of the epoxy layer between prong and holder results in a decrease of the sensor’s spring constant, eigenfrequency, and quality factor while showing an increasing deviation from oscillation in its primary modal shape. Adding epoxy at the sides of the tuning fork also leads to a degradation of the quality factor even though in this case, spring constant and eigenfrequency rise in tandem with a lessening of the deviation from its ideal modal shape.

A novel optical gating method for laser gated imaging

NASA Astrophysics Data System (ADS)

Ginat, Ran; Schneider, Ron; Zohar, Eyal; Nesher, Ofer

2013-06-01

For the past 15 years, Elbit Systems is developing time-resolved active laser-gated imaging (LGI) systems for various applications. Traditional LGI systems are based on high sensitive gated sensors, synchronized to pulsed laser sources. Elbit propriety multi-pulse per frame method, which is being implemented in LGI systems, improves significantly the imaging quality. A significant characteristic of the LGI is its ability to penetrate a disturbing media, such as rain, haze and some fog types. Current LGI systems are based on image intensifier (II) sensors, limiting the system in spectral response, image quality, reliability and cost. A novel propriety optical gating module was developed in Elbit, untying the dependency of LGI system on II. The optical gating module is not bounded to the radiance wavelength and positioned between the system optics and the sensor. This optical gating method supports the use of conventional solid state sensors. By selecting the appropriate solid state sensor, the new LGI systems can operate at any desired wavelength. In this paper we present the new gating method characteristics, performance and its advantages over the II gating method. The use of the gated imaging systems is described in a variety of applications, including results from latest field experiments.

Polymer Optical Fiber Sensor and the Prediction of Sensor Response Utilizing Artificial Neural Networks

NASA Astrophysics Data System (ADS)

Haroglu, Derya

The global market researches showed that there is a growing trend in the field of polymer optical fiber (POF) and POF sensors. Telecommunications, medicine, defense, aerospace, and automotive are the application areas of fiber optic sensors, where the automotive industry is the most promising application area for innovations in the field of POF sensors. The POF sensors in automobiles are particularly for detection of seat occupancy, and intelligent pedestrian protection systems. This dissertation investigates graded index perfluorinated polymer optical fiber as an intensity modulated intrinsic sensor for application in automotive seat occupancy sensing. Since a fiber optic sensor has a high bandwidth, is small in size, is lightweight, and is immune to electromagnetic interference (EMI) it offers higher performance than that of its electrical based counterparts such as strain gauge, elastomeric bladder, and resistive sensor systems. This makes the fiber optic sensor a potential suitable material for seat occupancy sensing. A textile-based fiber optic sensor was designed to be located in the area beneath the typical seated human's thighs. The pressure interval under which the proposed POF sensor design could perform well was found to be between 0.18 and 0.21 N/cm2, where perfluorinated (PF) graded index (GI) POF (62.5/750 mum) was used as the POF material. In addition, the effect of the automotive seat covering including face material (fabric) and foam backing to the sensor's performance was analyzed. The face fabric structure and the thickness of foam backing were not found to be significant factors to change the sensor results. A research study, survey, was conducted of which purpose was to better understand market demands in terms of sensor performance characteristics for automotive seat weight sensors, as a part of the Quality Function Deployment (QFD) House of Quality analysis. The companies joined the survey agreed on the first 5 most important sensor characteristics: reproducibility, accuracy, selectivity, aging, and resolution. Artificial neural network (ANN), a mathematical model formed by mimicking the human nervous system, was used to predict the sensor response. Qwiknet (version 2.23) software was used to develop ANNs and according to the results of Qwiknet the prediction performances for training and testing data sets were 75%, and 83.33% respectively. In this dissertation, Chapter 1 describes the worldwide plastic optical fiber (POF) and fiber optic sensor markets, and the existing textile structures used in fiber optic sensing design particularly for the applications of biomedical and structural health monitoring (SHM). Chapter 2 provides a literature review in detail on polymer optical fibers, fiber optic sensors, and occupancy sensing in the passenger seats of automobiles. Chapter 3 includes the research objectives. Chapter 4 presents the response of POF to tensile loading, bending, and cyclic tensile loading with discussion parts. Chapter 5 includes an e-mail based survey to prioritize customer needs in a Quality Function Deployment (QFD) format utilizing Analytic Hierarchy Process (AHP) and survey results. Chapter 6 describes the POF sensor design and the behavior of it under pressure. Chapter 7 provides a data analysis based on the experimental results of Chapter 6. Chapter 8 presents the summary of this study and recommendations for future work.

A Novel Group Decision-Making Method Based on Sensor Data and Fuzzy Information.

PubMed

Bai, Yu-Ting; Zhang, Bai-Hai; Wang, Xiao-Yi; Jin, Xue-Bo; Xu, Ji-Ping; Su, Ting-Li; Wang, Zhao-Yang

2016-10-28

Algal bloom is a typical phenomenon of the eutrophication of rivers and lakes and makes the water dirty and smelly. It is a serious threat to water security and public health. Most scholars studying solutions for this pollution have studied the principles of remediation approaches, but few have studied the decision-making and selection of the approaches. Existing research uses simplex decision-making information which is highly subjective and uses little of the data from water quality sensors. To utilize these data and solve the rational decision-making problem, a novel group decision-making method is proposed using the sensor data with fuzzy evaluation information. Firstly, the optimal similarity aggregation model of group opinions is built based on the modified similarity measurement of Vague values. Secondly, the approaches' ability to improve the water quality indexes is expressed using Vague evaluation methods. Thirdly, the water quality sensor data are analyzed to match the features of the alternative approaches with grey relational degrees. This allows the best remediation approach to be selected to meet the current water status. Finally, the selection model is applied to the remediation of algal bloom in lakes. The results show this method's rationality and feasibility when using different data from different sources.

Online tools for uncovering data quality issues in satellite-based global precipitation products

NASA Astrophysics Data System (ADS)

Liu, Z.; Heo, G.

2015-12-01

Accurate and timely available global precipitation products are important to many applications such as flood forecasting, hydrological modeling, vector-borne disease research, crop yield estimates, etc. However, data quality issues such as biases and uncertainties are common in satellite-based precipitation products and it is important to understand these issues in applications. In recent years, algorithms using multi-satellites and multi-sensors for satellite-based precipitation estimates have become popular, such as the TRMM (Tropical Rainfall Measuring Mission) Multi-satellite Precipitation Analysis (TMPA) and the latest Integrated Multi-satellitE Retrievals for GPM (IMERG). Studies show that data quality issues for multi-satellite and multi-sensor products can vary with space and time and can be difficult to summarize. Online tools can provide customized results for a given area of interest, allowing customized investigation or comparison on several precipitation products. Because downloading data and software is not required, online tools can facilitate precipitation product evaluation and comparison. In this presentation, we will present online tools to uncover data quality issues in satellite-based global precipitation products. Examples will be presented as well.

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

PubMed

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

2015-06-01

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

An information based approach to improving overhead imagery collection

NASA Astrophysics Data System (ADS)

Sourwine, Matthew J.; Hintz, Kenneth J.

2011-06-01

Recent growth in commercial imaging satellite development has resulted in a complex and diverse set of systems. To simplify this environment for both customer and vendor, an information based sensor management model was built to integrate tasking and scheduling systems. By establishing a relationship between image quality and information, tasking by NIIRS can be utilized to measure the customer's required information content. Focused on a reduction in uncertainty about a target of interest, the sensor manager finds the best sensors to complete the task given the active suite of imaging sensors' functions. This is done through determination of which satellite will meet customer information and timeliness requirements with low likelihood of interference at the highest rate of return.

Implementation of Cyberinfrastructure and Data Management Workflow for a Large-Scale Sensor Network

NASA Astrophysics Data System (ADS)

Jones, A. S.; Horsburgh, J. S.

2014-12-01

Monitoring with in situ environmental sensors and other forms of field-based observation presents many challenges for data management, particularly for large-scale networks consisting of multiple sites, sensors, and personnel. The availability and utility of these data in addressing scientific questions relies on effective cyberinfrastructure that facilitates transformation of raw sensor data into functional data products. It also depends on the ability of researchers to share and access the data in useable formats. In addition to addressing the challenges presented by the quantity of data, monitoring networks need practices to ensure high data quality, including procedures and tools for post processing. Data quality is further enhanced if practitioners are able to track equipment, deployments, calibrations, and other events related to site maintenance and associate these details with observational data. In this presentation we will describe the overall workflow that we have developed for research groups and sites conducting long term monitoring using in situ sensors. Features of the workflow include: software tools to automate the transfer of data from field sites to databases, a Python-based program for data quality control post-processing, a web-based application for online discovery and visualization of data, and a data model and web interface for managing physical infrastructure. By automating the data management workflow, the time from collection to analysis is reduced and sharing and publication is facilitated. The incorporation of metadata standards and descriptions and the use of open-source tools enhances the sustainability and reusability of the data. We will describe the workflow and tools that we have developed in the context of the iUTAH (innovative Urban Transitions and Aridregion Hydrosustainability) monitoring network. The iUTAH network consists of aquatic and climate sensors deployed in three watersheds to monitor Gradients Along Mountain to Urban Transitions (GAMUT). The variety of environmental sensors and the multi-watershed, multi-institutional nature of the network necessitate a well-planned and efficient workflow for acquiring, managing, and sharing sensor data, which should be useful for similar large-scale and long-term networks.

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.

An energy-efficient readout circuit for resonant sensors based on ring-down measurement

NASA Astrophysics Data System (ADS)

Zeng, Z.; Pertijs, M. A. P.; Karabacak, D. M.

2013-02-01

This paper presents an energy-efficient readout circuit for resonant sensors that operates based on a transient measurement method. The resonant sensor is driven at a frequency close to its resonance frequency by an excitation source that can be intermittently disconnected, causing the sensor to oscillate at its resonance frequency with exponentially decaying amplitude. By counting the zero crossings of this ring-down response, the interface circuit can detect the resonance frequency. In contrast with oscillator-based readout, the presented readout circuit is readily able to detect quality factor (Q) of the resonator from the envelope of the ring-down response, and can be used even in the presence of large parasitic capacitors. A prototype of the readout circuit has been integrated in 0.35 μm CMOS technology, and consumes only 36 μA from a 3.3 V supply during a measurement time of 2 ms. The resonance frequency and quality factor of a micro-machined SiN resonator obtained using this prototype are in good agreement with results obtained using impedance analysis. Furthermore, a clear transient response is observed to ethanol flow using the presented readout, demonstrating the use of this technique in sensing applications.

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

An Insertable Passive LC Pressure Sensor Based on an Alumina Ceramic for In Situ Pressure Sensing in High-Temperature Environments.

PubMed

Xiong, Jijun; Li, Chen; Jia, Pinggang; Chen, Xiaoyong; Zhang, Wendong; Liu, Jun; Xue, Chenyang; Tan, Qiulin

2015-08-31

Pressure measurements in high-temperature applications, including compressors, turbines, and others, have become increasingly critical. This paper proposes an implantable passive LC pressure sensor based on an alumina ceramic material for in situ pressure sensing in high-temperature environments. The inductance and capacitance elements of the sensor were designed independently and separated by a thermally insulating material, which is conducive to reducing the influence of the temperature on the inductance element and improving the quality factor of the sensor. In addition, the sensor was fabricated using thick film integrated technology from high-temperature materials that ensure stable operation of the sensor in high-temperature environments. Experimental results showed that the sensor accurately monitored pressures from 0 bar to 2 bar at temperatures up to 800 °C. The sensitivity, linearity, repeatability error, and hysteretic error of the sensor were 0.225 MHz/bar, 95.3%, 5.5%, and 6.2%, respectively.

An Insertable Passive LC Pressure Sensor Based on an Alumina Ceramic for In Situ Pressure Sensing in High-Temperature Environments

PubMed Central

Xiong, Jijun; Li, Chen; Jia, Pinggang; Chen, Xiaoyong; Zhang, Wendong; Liu, Jun; Xue, Chenyang; Tan, Qiulin

2015-01-01

Pressure measurements in high-temperature applications, including compressors, turbines, and others, have become increasingly critical. This paper proposes an implantable passive LC pressure sensor based on an alumina ceramic material for in situ pressure sensing in high-temperature environments. The inductance and capacitance elements of the sensor were designed independently and separated by a thermally insulating material, which is conducive to reducing the influence of the temperature on the inductance element and improving the quality factor of the sensor. In addition, the sensor was fabricated using thick film integrated technology from high-temperature materials that ensure stable operation of the sensor in high-temperature environments. Experimental results showed that the sensor accurately monitored pressures from 0 bar to 2 bar at temperatures up to 800 °C. The sensitivity, linearity, repeatability error, and hysteretic error of the sensor were 0.225 MHz/bar, 95.3%, 5.5%, and 6.2%, respectively. PMID:26334279

Pervasive Monitoring—An Intelligent Sensor Pod Approach for Standardised Measurement Infrastructures

PubMed Central

Resch, Bernd; Mittlboeck, Manfred; Lippautz, Michael

2010-01-01

Geo-sensor networks have traditionally been built up in closed monolithic systems, thus limiting trans-domain usage of real-time measurements. This paper presents the technical infrastructure of a standardised embedded sensing device, which has been developed in the course of the Live Geography approach. The sensor pod implements data provision standards of the Sensor Web Enablement initiative, including an event-based alerting mechanism and location-aware Complex Event Processing functionality for detection of threshold transgression and quality assurance. The goal of this research is that the resultant highly flexible sensing architecture will bring sensor network applications one step further towards the realisation of the vision of a “digital skin for planet earth”. The developed infrastructure can potentially have far-reaching impacts on sensor-based monitoring systems through the deployment of ubiquitous and fine-grained sensor networks. This in turn allows for the straight-forward use of live sensor data in existing spatial decision support systems to enable better-informed decision-making. PMID:22163537

Pervasive monitoring--an intelligent sensor pod approach for standardised measurement infrastructures.

PubMed

Resch, Bernd; Mittlboeck, Manfred; Lippautz, Michael

2010-01-01

Geo-sensor networks have traditionally been built up in closed monolithic systems, thus limiting trans-domain usage of real-time measurements. This paper presents the technical infrastructure of a standardised embedded sensing device, which has been developed in the course of the Live Geography approach. The sensor pod implements data provision standards of the Sensor Web Enablement initiative, including an event-based alerting mechanism and location-aware Complex Event Processing functionality for detection of threshold transgression and quality assurance. The goal of this research is that the resultant highly flexible sensing architecture will bring sensor network applications one step further towards the realisation of the vision of a "digital skin for planet earth". The developed infrastructure can potentially have far-reaching impacts on sensor-based monitoring systems through the deployment of ubiquitous and fine-grained sensor networks. This in turn allows for the straight-forward use of live sensor data in existing spatial decision support systems to enable better-informed decision-making.

Gold nanoparticle-based optical microfluidic sensors for analysis of environmental pollutants.

PubMed

Lafleur, Josiane P; Senkbeil, Silja; Jensen, Thomas G; Kutter, Jörg P

2012-11-21

Conventional methods of environmental analysis can be significantly improved by the development of portable microscale technologies for direct in-field sensing at remote locations. This report demonstrates the vast potential of gold nanoparticle-based microfluidic sensors for the rapid, in-field, detection of two important classes of environmental contaminants - heavy metals and pesticides. Using gold nanoparticle-based microfluidic sensors linked to a simple digital camera as the detector, detection limits as low as 0.6 μg L(-1) and 16 μg L(-1) could be obtained for the heavy metal mercury and the dithiocarbamate pesticide ziram, respectively. These results demonstrate that the attractive optical properties of gold nanoparticle probes combine synergistically with the inherent qualities of microfluidic platforms to offer simple, portable and sensitive sensors for environmental contaminants.

Information integration and diagnosis analysis of equipment status and production quality for machining process

NASA Astrophysics Data System (ADS)

Zan, Tao; Wang, Min; Hu, Jianzhong

2010-12-01

Machining status monitoring technique by multi-sensors can acquire and analyze the machining process information to implement abnormity diagnosis and fault warning. Statistical quality control technique is normally used to distinguish abnormal fluctuations from normal fluctuations through statistical method. In this paper by comparing the advantages and disadvantages of the two methods, the necessity and feasibility of integration and fusion is introduced. Then an approach that integrates multi-sensors status monitoring and statistical process control based on artificial intelligent technique, internet technique and database technique is brought forward. Based on virtual instrument technique the author developed the machining quality assurance system - MoniSysOnline, which has been used to monitoring the grinding machining process. By analyzing the quality data and AE signal information of wheel dressing process the reason of machining quality fluctuation has been obtained. The experiment result indicates that the approach is suitable for the status monitoring and analyzing of machining process.

Method and apparatus for in-process sensing of manufacturing quality

DOEpatents

Hartman, Daniel A [Santa Fe, NM; Dave, Vivek R [Los Alamos, NM; Cola, Mark J [Santa Fe, NM; Carpenter, Robert W [Los Alamos, NM

2005-02-22

A method for determining the quality of an examined weld joint comprising the steps of providing acoustical data from the examined weld joint, and performing a neural network operation on the acoustical data determine the quality of the examined weld joint produced by a friction weld process. The neural network may be trained by the steps of providing acoustical data and observable data from at least one test weld joint, and training the neural network based on the acoustical data and observable data to form a trained neural network so that the trained neural network is capable of determining the quality of a examined weld joint based on acoustical data from the examined weld joint. In addition, an apparatus having a housing, acoustical sensors mounted therein, and means for mounting the housing on a friction weld device so that the acoustical sensors do not contact the weld joint. The apparatus may sample the acoustical data necessary for the neural network to determine the quality of a weld joint.

Method and Apparatus for In-Process Sensing of Manufacturing Quality

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

Hartman, D.A.; Dave, V.R.; Cola, M.J.

2005-02-22

A method for determining the quality of an examined weld joint comprising the steps of providing acoustical data from the examined weld joint, and performing a neural network operation on the acoustical data determine the quality of the examined weld joint produced by a friction weld process. The neural network may be trained by the steps of providing acoustical data and observable data from at least one test weld joint, and training the neural network based on the acoustical data and observable data to form a trained neural network so that the trained neural network is capable of determining themore » quality of a examined weld joint based on acoustical data from the examined weld joint. In addition, an apparatus having a housing, acoustical sensors mounted therein, and means for mounting the housing on a friction weld device so that the acoustical sensors do not contact the weld joint. The apparatus may sample the acoustical data necessary for the neural network to determine the quality of a weld joint.« less

Estimation of tool wear during CNC milling using neural network-based sensor fusion

NASA Astrophysics Data System (ADS)

Ghosh, N.; Ravi, Y. B.; Patra, A.; Mukhopadhyay, S.; Paul, S.; Mohanty, A. R.; Chattopadhyay, A. B.

2007-01-01

Cutting tool wear degrades the product quality in manufacturing processes. Monitoring tool wear value online is therefore needed to prevent degradation in machining quality. Unfortunately there is no direct way of measuring the tool wear online. Therefore one has to adopt an indirect method wherein the tool wear is estimated from several sensors measuring related process variables. In this work, a neural network-based sensor fusion model has been developed for tool condition monitoring (TCM). Features extracted from a number of machining zone signals, namely cutting forces, spindle vibration, spindle current, and sound pressure level have been fused to estimate the average flank wear of the main cutting edge. Novel strategies such as, signal level segmentation for temporal registration, feature space filtering, outlier removal, and estimation space filtering have been proposed. The proposed approach has been validated by both laboratory and industrial implementations.

Long-Term Outdoor Reliability Assessment of a Wireless Unit for Air-Quality Monitoring Based on Nanostructured Films Integrated on Micromachined Platforms

PubMed Central

Leccardi, Matteo; Decarli, Massimiliano; Lorenzelli, Leandro; Milani, Paolo; Mettala, Petteri; Orava, Risto; Barborini, Emanuele

2012-01-01

We have fabricated and tested in long-term field operating conditions a wireless unit for outdoor air quality monitoring. The unit is equipped with two multiparametric sensors, one miniaturized thermo-hygrometer, front-end analogical and digital electronics, and an IEEE 802.15.4 based module for wireless data transmission. Micromachined platforms were functionalized with nanoporous metal-oxides to obtain multiparametric sensors, hosting gas-sensitive, anemometric and temperature transducers. Nanoporous metal-oxide layer was directly deposited on gas sensing regions of micromachined platform batches by hard-mask patterned supersonic cluster beam deposition. An outdoor, roadside experiment was arranged in downtown Milan (Italy), where one wireless sensing unit was continuously operated side by side with standard gas chromatographic instrumentation for air quality measurements. By means of a router PC, data from sensing unit and other instrumentation were collected, merged, and sent to a remote data storage server, through an UMTS device. The whole-system robustness as well as sensor dataset characteristics were continuously characterized over a run-time period of 18 months. PMID:22969394

Application of Sensor Fusion to Improve Uav Image Classification

NASA Astrophysics Data System (ADS)

Jabari, S.; Fathollahi, F.; Zhang, Y.

2017-08-01

Image classification is one of the most important tasks of remote sensing projects including the ones that are based on using UAV images. Improving the quality of UAV images directly affects the classification results and can save a huge amount of time and effort in this area. In this study, we show that sensor fusion can improve image quality which results in increasing the accuracy of image classification. Here, we tested two sensor fusion configurations by using a Panchromatic (Pan) camera along with either a colour camera or a four-band multi-spectral (MS) camera. We use the Pan camera to benefit from its higher sensitivity and the colour or MS camera to benefit from its spectral properties. The resulting images are then compared to the ones acquired by a high resolution single Bayer-pattern colour camera (here referred to as HRC). We assessed the quality of the output images by performing image classification tests. The outputs prove that the proposed sensor fusion configurations can achieve higher accuracies compared to the images of the single Bayer-pattern colour camera. Therefore, incorporating a Pan camera on-board in the UAV missions and performing image fusion can help achieving higher quality images and accordingly higher accuracy classification results.

Automatic relative RPC image model bias compensation through hierarchical image matching for improving DEM quality

NASA Astrophysics Data System (ADS)

Noh, Myoung-Jong; Howat, Ian M.

2018-02-01

The quality and efficiency of automated Digital Elevation Model (DEM) extraction from stereoscopic satellite imagery is critically dependent on the accuracy of the sensor model used for co-locating pixels between stereo-pair images. In the absence of ground control or manual tie point selection, errors in the sensor models must be compensated with increased matching search-spaces, increasing both the computation time and the likelihood of spurious matches. Here we present an algorithm for automatically determining and compensating the relative bias in Rational Polynomial Coefficients (RPCs) between stereo-pairs utilizing hierarchical, sub-pixel image matching in object space. We demonstrate the algorithm using a suite of image stereo-pairs from multiple satellites over a range stereo-photogrammetrically challenging polar terrains. Besides providing a validation of the effectiveness of the algorithm for improving DEM quality, experiments with prescribed sensor model errors yield insight into the dependence of DEM characteristics and quality on relative sensor model bias. This algorithm is included in the Surface Extraction through TIN-based Search-space Minimization (SETSM) DEM extraction software package, which is the primary software used for the U.S. National Science Foundation ArcticDEM and Reference Elevation Model of Antarctica (REMA) products.

Quantifying a Total Non-Methane Hydrocarbon Signal using Low-Cost VOC Sensors in an Effort to Help Communities Learn More About their Air Quality

NASA Astrophysics Data System (ADS)

Collier, A. M.; Hannigan, M.; Piedrahita, R.; Casey, J. G.; Johnston, J.; Chiang, S.

2016-12-01

The growing accessibility of low-cost air quality monitoring technologies has led to their increased usage among community-based organizations, particularly for the monitoring of pollutants dangerous to human health (e.g., hazardous air pollutants or HAPS). However, often these low-cost sensors are `off-the-shelf' and are being utilized in a manner that differs from their intended purpose - necessitating high quality calibrations. For example, VOC sensors intended for the detection of high levels of a particular compound in an industrial setting may instead be used for ambient monitoring of a group of VOCs. Academic/community partnerships can be an ideal way to improve this type of sensor quantification while providing a community with not only the opportunity to use these technologies with additional support around data quality, but also the opportunity for education around the abilities and applications of low-cost sensors. In the spring of 2016, our lab at the University of Colorado, Boulder partnered with communities in Los Angeles and Kern County to deploy low-cost air quality monitors for the purpose of quantifying methane and non-methane hydrocarbon signals in an effort to learn more about potential impacts from local sources (e.g., nearby highways and oil & gas development). The monitoring platform was developed in our lab and is capable of logging multiple gas phase species as well as some environmental parameters. The monitors include two different metal oxide VOC sensors - each with slightly different sensing capabilities. Calibration was achieved using a pre- and post-deployment field normalization to reference monitoring equipment maintained by the South Coast Air Quality Management District. Monitors were then deployed at locations throughout the community. We will present results on our efforts to quantify a total non-methane hydrocarbon signal, observations from the field data, and recommendations for academic/community partnerships formed around air quality monitoring.

Assessment of water quality monitoring for the optimal sensor placement in lake Yahuarcocha using pattern recognition techniques and geographical information systems.

PubMed

Jácome, Gabriel; Valarezo, Carla; Yoo, Changkyoo

2018-03-30

Pollution and the eutrophication process are increasing in lake Yahuarcocha and constant water quality monitoring is essential for a better understanding of the patterns occurring in this ecosystem. In this study, key sensor locations were determined using spatial and temporal analyses combined with geographical information systems (GIS) to assess the influence of weather features, anthropogenic activities, and other non-point pollution sources. A water quality monitoring network was established to obtain data on 14 physicochemical and microbiological parameters at each of seven sample sites over a period of 13 months. A spatial and temporal statistical approach using pattern recognition techniques, such as cluster analysis (CA) and discriminant analysis (DA), was employed to classify and identify the most important water quality parameters in the lake. The original monitoring network was reduced to four optimal sensor locations based on a fuzzy overlay of the interpolations of concentration variations of the most important parameters.

In-situ measurement of thermoset resin degree of cure using embedded fiber optic

NASA Astrophysics Data System (ADS)

Breglio, Giovanni; Cusano, Andrea; Cutolo, Antonello; Calabro, Antonio M.; Cantoni, Stefania; Di Vita, Gandolfo; Buonocore, Vincenzo; Giordano, Michele; Nicolais, Luigi, II

1999-12-01

In this work, a fiber optic sensor based on Fresnel principle is presented. It is used to monitor the variations of the refractive index due to the cure process of an epoxy based resin. These materials are widely used in polymer- matrix composites. The process of thermoset matrix based composite involves mass and heat transfer coupled with irreversible chemical reactions inducing physical changes: the transformation of a fluid resin into a rubber and then into a solid glass. To improve the quality and the reliability of these materials key points are the cure monitoring and the optimization of the manufacturing process. To this aim, the fiber optic embedded sensor has been designed, developed and tested. Preliminary results on sensor capability to monitor the cure kinetics are shown. Correlation between the sensor output and conversion advancement has been proposed following the Lorentz-Lorenz law. Isothermal data form the sensor have been compared with calorimetric analysis of an epoxy based resin.

High-Density, High-Resolution, Low-Cost Air Quality Sensor Networks for Urban Air Monitoring

NASA Astrophysics Data System (ADS)

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

2012-12-01

Monitoring air quality in highly granular environments such as urban areas which are spatially heterogeneous with variable emission sources, measurements need to be made at appropriate spatial and temporal scales. Current routine air quality monitoring networks generally are either composed of sparse expensive installations (incorporating e.g. chemiluminescence instruments) or higher density low time resolution systems (e.g. NO2 diffusion tubes). Either approach may not accurately capture important effects such as pollutant "hot spots" or adequately capture spatial (or temporal) variability. As a result, analysis based on data from traditional low spatial resolution networks, such as personal exposure, may be inaccurate. In this paper we present details of a sophisticated, low-cost, multi species (gas phase, speciated PM, meteorology) air quality measurement network methodology incorporating GPS and GPRS which has been developed for high resolution air quality measurements in urban areas. Sensor networks developed in the Centre for Atmospheric Science (University of Cambridge) incorporated electrochemical gas sensors configured for use in urban air quality studies operating at parts-per-billion (ppb) levels. It has been demonstrated that these sensors can be used to measure key air quality gases such as CO, NO and NO2 at the low ppb mixing ratios present in the urban environment (estimated detection limits <4ppb for CO and NO and <1ppb for NO2. Mead et al (submitted Aug., 2012)). Based on this work, a state of the art multi species instrument package for deployment in scalable sensor networks has been developed which has general applicability. This is currently being employed as part of a major 3 year UK program at London Heathrow airport (the Sensor Networks for Air Quality (SNAQ) Heathrow project). The main project outcome is the creation of a calibrated, high spatial and temporal resolution data set for O3, NO, NO2, SO2, CO, CO2, VOCstotal, size-speciated PM, temperature, relative humidity, wind speed and direction. The network incorporates existing GPRS infrastructures for real time sending of data with low overheads in terms of cost, effort and installation. In this paper we present data from the SNAQ Heathrow project as well as previous deployments showing measurement capability at the ppb level for NO, NO2 and CO. We show that variability can be observed and measured quantitatively using these sensor networks over widely differing time scales from individual emission events, diurnal variability associated with traffic and meteorological conditions, through to longer term synoptic weather conditions and seasonal behaviour. This work demonstrates a widely applicable generic capability to urban areas, airports as well as other complex emissions environments making this sensor system methodology valuable for scientific, policy and regulatory issues. We conclude that the low-cost high-density network philosophy has the potential to provide a more complete assessment of the high-granularity air quality structure generally observed in the environment. Further, when appropriately deployed, has the potential to offer a new paradigm in air quality quantification and monitoring.

Obstacles using amorphous materials for volume applications

NASA Astrophysics Data System (ADS)

Kiessling, Albert; Reininger, Thomas

2012-10-01

This contribution is especially focussed on the attempt to use amorphous or nanocrystalline metals in position sensor applications and to describe the difficulties and obstacles encountered in coherence with the development of appropriate industrial high volume series products in conjunction with the related quality requirements. The main motivation to do these investigations was to beat the generally known sensors especially silicon based Hall-sensors as well as AMR- and GMR-sensors - well known from mobile phones and electronic storage devices like hard discs and others - in terms of cost-effectiveness and functionality.

Refractive index sensor based on lateral-offset of coreless silica interferometer

NASA Astrophysics Data System (ADS)

Baharin, Nur Faizzah; Azmi, Asrul Izam; Abdullah, Ahmad Sharmi; Mohd Noor, Muhammad Yusof

2018-02-01

A compact, cost-effective and high sensitivity fiber interferometer refractive index (RI) sensor based on symmetrical offset coreless silica fiber (CSF) configuration is proposed, optimized and demonstrated. The sensor is formed by splicing a section of CSF between two CSF sections in an offset manner. Thus, two distinct optical paths are created with large index difference, the first path through the connecting CSF sections and the second path is outside the CSF through the surrounding media. RI sensing is established from direct interaction of light with surrounding media, hence high sensitivity can be achieved with a relatively compact sensor length. In the experimental work, a 1.5 mm sensor demonstrates RI sensitivity of 750 nm/RIU for RI range between 1.33 and 1.345. With the main attributes of high sensitivity and compact size, the proposed sensor can be further developed for related applications including blood diagnosis, water quality control and food industries.

Dual resonant frequencies effects on an induction-based oil palm fruit sensor.

PubMed

Harun, Noor Hasmiza; Misron, Norhisam; Mohd Sidek, Roslina; Aris, Ishak; Wakiwaka, Hiroyuki; Tashiro, Kunihisa

2014-11-19

As the main exporter in the oil palm industry, the need to improve the quality of palm oil has become the main interest among all the palm oil millers in Malaysia. To produce good quality palm oil, it is important for the miller to harvest a good oil palm Fresh Fruit Bunch (FFB). Conventionally, the main reference used by Malaysian harvesters is the manual grading standard published by the Malaysian Palm Oil Board (MPOB). A good oil palm FFB consists of all matured fruitlets, aged between 18 to 21 weeks of antheses (WAA). To expedite the harvesting process, it is crucial to implement an automated detection system for determining the maturity of the oil palm FFB. Various automated detection methods have been proposed by researchers in the field to replace the conventional method. In our preliminary study, a novel oil palm fruit sensor to detect the maturity of oil palm fruit bunch was proposed. The design of the proposed air coil sensor based on the inductive sensor was further investigated mainly in the context of the effect of coil diameter to improve its sensitivity. In this paper, the sensitivity of the inductive sensor was further examined with a dual flat-type shape of air coil. The dual air coils were tested on fifteen samples of fruitlet from two categories, namely ripe and unripe. Samples were tested within 20 Hz to 10 MHz while evaluations on both peaks were done separately before the gap between peaks was analyzed. A comparative analysis was conducted to investigate the improvement in sensitivity of the induction-based oil palm fruit sensor as compared to previous works. Results from the comparative study proved that the inductive sensor using a dual flat-type shape air coil has improved by up to 167%. This provides an indication in the improvement in the coil sensitivity of the palm oil fruit sensor based on the induction concept.

Dual Resonant Frequencies Effects on an Induction-Based Oil Palm Fruit Sensor

PubMed Central

Harun, Noor Hasmiza; Misron, Norhisam; Sidek, Roslina Mohd; Aris, Ishak; Wakiwaka, Hiroyuki; Tashiro, Kunihisa

2014-01-01

As the main exporter in the oil palm industry, the need to improve the quality of palm oil has become the main interest among all the palm oil millers in Malaysia. To produce good quality palm oil, it is important for the miller to harvest a good oil palm Fresh Fruit Bunch (FFB). Conventionally, the main reference used by Malaysian harvesters is the manual grading standard published by the Malaysian Palm Oil Board (MPOB). A good oil palm FFB consists of all matured fruitlets, aged between 18 to 21 weeks of antheses (WAA). To expedite the harvesting process, it is crucial to implement an automated detection system for determining the maturity of the oil palm FFB. Various automated detection methods have been proposed by researchers in the field to replace the conventional method. In our preliminary study, a novel oil palm fruit sensor to detect the maturity of oil palm fruit bunch was proposed. The design of the proposed air coil sensor based on the inductive sensor was further investigated mainly in the context of the effect of coil diameter to improve its sensitivity. In this paper, the sensitivity of the inductive sensor was further examined with a dual flat-type shape of air coil. The dual air coils were tested on fifteen samples of fruitlet from two categories, namely ripe and unripe. Samples were tested within 20 Hz to 10 MHz while evaluations on both peaks were done separately before the gap between peaks was analyzed. A comparative analysis was conducted to investigate the improvement in sensitivity of the induction-based oil palm fruit sensor as compared to previous works. Results from the comparative study proved that the inductive sensor using a dual flat-type shape air coil has improved by up to 167%. This provides an indication in the improvement in the coil sensitivity of the palm oil fruit sensor based on the induction concept. PMID:25414970

Meat Quality Assessment by Electronic Nose (Machine Olfaction Technology)

PubMed Central

Ghasemi-Varnamkhasti, Mahdi; Mohtasebi, Seyed Saeid; Siadat, Maryam; Balasubramanian, Sundar

2009-01-01

Over the last twenty years, newly developed chemical sensor systems (so called “electronic noses”) have made odor analyses possible. These systems involve various types of electronic chemical gas sensors with partial specificity, as well as suitable statistical methods enabling the recognition of complex odors. As commercial instruments have become available, a substantial increase in research into the application of electronic noses in the evaluation of volatile compounds in food, cosmetic and other items of everyday life is observed. At present, the commercial gas sensor technologies comprise metal oxide semiconductors, metal oxide semiconductor field effect transistors, organic conducting polymers, and piezoelectric crystal sensors. Further sensors based on fibreoptic, electrochemical and bi-metal principles are still in the developmental stage. Statistical analysis techniques range from simple graphical evaluation to multivariate analysis such as artificial neural network and radial basis function. The introduction of electronic noses into the area of food is envisaged for quality control, process monitoring, freshness evaluation, shelf-life investigation and authenticity assessment. Considerable work has already been carried out on meat, grains, coffee, mushrooms, cheese, sugar, fish, beer and other beverages, as well as on the odor quality evaluation of food packaging material. This paper describes the applications of these systems for meat quality assessment, where fast detection methods are essential for appropriate product management. The results suggest the possibility of using this new technology in meat handling. PMID:22454572

Research of marine sensor web based on SOA and EDA

NASA Astrophysics Data System (ADS)

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

2015-04-01

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

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

NASA Astrophysics Data System (ADS)

Boubakri, S.; Rhinane, H.

2017-11-01

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

Micro sensor node for air pollutant monitoring: hardware and software issues.

PubMed

Choi, Sukwon; Kim, Nakyoung; Cha, Hojung; Ha, Rhan

2009-01-01

Wireless sensor networks equipped with various gas sensors have been actively used for air quality monitoring. Previous studies have typically explored system issues that include middleware or networking performance, but most research has barely considered the details of the hardware and software of the sensor node itself. In this paper, we focus on the design and implementation of a sensor board for air pollutant monitoring applications. Several hardware and software issues are discussed to explore the possibilities of a practical WSN-based air pollution monitoring system. Through extensive experiments and evaluation, we have determined the various characteristics of the gas sensors and their practical implications for air pollutant monitoring systems.

An assessment of African test sites in the context of a global network of quality-assured reference standards

USGS Publications Warehouse

Chander, G.; Xiong, X.; Angal, A.; Choi, T.

2009-01-01

The Committee on Earth Observation Satellites (CEOS) Infrared and Visible Optical Sensors (IVOS) subgroup members established a set of CEOS-endorsed globally distributed reference standard test sites for the postlaunch calibration of space-based optical imaging sensors. This paper discusses the top five African pseudo-invariant sites (Libya 4, Mauritania 1/2, Algeria 3, Libya 1, and Algeria 5) that were identified by the IVOS subgroup. This paper focuses on monitoring the long-term radiometric stability of the Terra Moderate Resolution Imaging Spectroradiometer (MODIS) and the Landsat 7 (L7) Enhanced Thematic Mapper Plus (ETM+) sensors using near-simultaneous and cloud-free image pairs acquired from launch to December 2008 over the five African desert sites. Residual errors and coefficients of determination were also generated to support the quality assessment of the calibration differences between the two sensors. An effort was also made to evaluate the relative stability of these sites for long-term monitoring of the optical sensors. ??2009 IEEE.

The GSN Data Quality Initiative

NASA Astrophysics Data System (ADS)

Davis, J. P.; Anderson, K. R.; Gee, L. S.

2010-12-01

The Global Seismographic Network (GSN) is undertaking a renewed effort to assess and assure data quality that builds upon completion of the major installation phase of the GSN and recent funding to recapitalize most of the network’s equipment including data acquisition systems, ancillary equipment and secondary sensors. We highlight here work by the network operators, the USGS’ Albuquerque Seismological Lab and UCSD’s Project IDA, to ensure that both the quality of the waveforms collected is maximized, that the published metadata accurately reflect the instrument response of the data acquisitions systems, and that data users are informed of the status of the GSN data quality. Procedures to evaluate waveform quality blend tools made available through the IRIS DMC’s Quality Analysis Control Kit (http://www.iris.washington.edu/QUACK/), analysis results provided by the Lamont Waveform Quality Center (www.ldeo.columbia.edu/~ekstrom/Projects/WQC.html), and custom software developed by each of the operators to identify and track known hardware failure modes. Each operator’s equipment upgrade schedule is updated periodically to address sensors identified as failing or problematic and for which replacements are available. Particular attention is also paid to monitoring the GPS clock signal to guarantee that the data are timed properly. Devices based on GPS technology unavailable when the GSN began 25 years ago are being integrated into operations to verify sensor orientations. Portable, broadband seismometers whose stable response can be verified in the laboratory are now co-located with GSN sensors during field visits to verify the existing GSN sensors’ sensitivity. Additional effort is being made to analyze past calibration signals and to check the system response functions of the secondary broadband sensors at GSN sites. The new generation of data acquisition systems will enable relative calibrations to be performed more frequently than was possible in the past. Additional details of this effort can be found at the GSN Quality webpage (www.iris.edu/hq/programs/gsn/quality).

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.

Wearable PPG sensor based alertness scoring system.

PubMed

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

2017-07-01

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

Integrated optics ring-resonator chemical sensor with polymer transduction layer

NASA Technical Reports Server (NTRS)

Ksendzov, A.; Homer, M. L.; Manfreda, A. M.

2004-01-01

An integrated optics chemical sensor based on a ring resonator with an ethyl cellulose polymer coating has been demonstrated. The measured sensitivity to isopropanol in air is 50 ppm-the level immediately useful for health-related air quality monitoring. The resonator was fabricated using SiO2 and SixNy materials. The signal readout is based on tracking the wavelength of a resonance peak. The resonator layout optimisation for sensing applications is discussed.

Design of micro-ring optical sensors and circuits for integration on optical printed circuit boards (O-PCBs)

NASA Astrophysics Data System (ADS)

Lee, El-Hang; Lee, Hyun S.; Lee, S. G.; O, B. H.; Park, S. G.; Kim, K. H.

2007-05-01

We report on the design of micro-ring resonator optical sensors for integration on what we call optical printed circuit boards (O-PCBs). The objective is to realize application-specific O-PCBs, either on hard board or on flexible board, by integrating micro/nano-scale optical sensors for compact, light-weight, low-energy, high-speed, intelligent, and environmentally friendly processing of information. The O-PCBs consist of two-dimensional planar arrays of micro/nano-scale optical wires, circuits and devices that are interconnected and integrated to perform the functions of sensing and then storing, transporting, processing, switching, routing and distributing optical signals that have been collected by means of sensors. For fabrication, the polymer and organic optical wires and waveguides are first fabricated on a board and are used to interconnect and integrate sensors and other micro/ nano-scale photonic devices. Here, in our study, we focus on the sensors based on the micro-ring structures. We designed bio-sensors using silicon based micro-ring resonator. We investigate the characteristics such as sensitivity and selectivity (or quality factor) of micro-ring resonator for their use in bio-sensing application. We performed simulation studies on the quality factor of micro-ring resonators by varying the radius of the ring resonators and the separation between adjacent waveguides. We introduce the effective coupling coefficient as a realistic value to describe the strength of the coupling in micro-ring resonators.

Bayesian performance metrics of binary sensors in homeland security applications

NASA Astrophysics Data System (ADS)

Jannson, Tomasz P.; Forrester, Thomas C.

2008-04-01

Bayesian performance metrics, based on such parameters, as: prior probability, probability of detection (or, accuracy), false alarm rate, and positive predictive value, characterizes the performance of binary sensors; i.e., sensors that have only binary response: true target/false target. Such binary sensors, very common in Homeland Security, produce an alarm that can be true, or false. They include: X-ray airport inspection, IED inspections, product quality control, cancer medical diagnosis, part of ATR, and many others. In this paper, we analyze direct and inverse conditional probabilities in the context of Bayesian inference and binary sensors, using X-ray luggage inspection statistical results as a guideline.

A Novel Deployment Scheme Based on Three-Dimensional Coverage Model for Wireless Sensor Networks

PubMed Central

Xiao, Fu; Yang, Yang; Wang, Ruchuan; Sun, Lijuan

2014-01-01

Coverage pattern and deployment strategy are directly related to the optimum allocation of limited resources for wireless sensor networks, such as energy of nodes, communication bandwidth, and computing power, and quality improvement is largely determined by these for wireless sensor networks. A three-dimensional coverage pattern and deployment scheme are proposed in this paper. Firstly, by analyzing the regular polyhedron models in three-dimensional scene, a coverage pattern based on cuboids is proposed, and then relationship between coverage and sensor nodes' radius is deduced; also the minimum number of sensor nodes to maintain network area's full coverage is calculated. At last, sensor nodes are deployed according to the coverage pattern after the monitor area is subdivided into finite 3D grid. Experimental results show that, compared with traditional random method, sensor nodes number is reduced effectively while coverage rate of monitor area is ensured using our coverage pattern and deterministic deployment scheme. PMID:25045747

Optical Characterization of Lorentz Force Based CMOS-MEMS Magnetic Field Sensor

PubMed Central

Dennis, John Ojur; Ahmad, Farooq; Khir, M. Haris Bin Md; Hamid, Nor Hisham Bin

2015-01-01

Magnetic field sensors are becoming an essential part of everyday life due to the improvements in their sensitivities and resolutions, while at the same time they have become compact, smaller in size and economical. In the work presented herein a Lorentz force based CMOS-MEMS magnetic field sensor is designed, fabricated and optically characterized. The sensor is fabricated by using CMOS thin layers and dry post micromachining is used to release the device structure and finally the sensor chip is packaged in DIP. The sensor consists of a shuttle which is designed to resonate in the lateral direction (first mode of resonance). In the presence of an external magnetic field, the Lorentz force actuates the shuttle in the lateral direction and the amplitude of resonance is measured using an optical method. The differential change in the amplitude of the resonating shuttle shows the strength of the external magnetic field. The resonance frequency of the shuttle is determined to be 8164 Hz experimentally and from the resonance curve, the quality factor and damping ratio are obtained. In an open environment, the quality factor and damping ratio are found to be 51.34 and 0.00973 respectively. The sensitivity of the sensor is determined in static mode to be 0.034 µm/mT when a current of 10 mA passes through the shuttle, while it is found to be higher at resonance with a value of 1.35 µm/mT at 8 mA current. Finally, the resolution of the sensor is found to be 370.37 µT. PMID:26225972

Optical Characterization of Lorentz Force Based CMOS-MEMS Magnetic Field Sensor.

PubMed

Dennis, John Ojur; Ahmad, Farooq; Khir, M Haris Bin Md; Bin Hamid, Nor Hisham

2015-07-27

Magnetic field sensors are becoming an essential part of everyday life due to the improvements in their sensitivities and resolutions, while at the same time they have become compact, smaller in size and economical. In the work presented herein a Lorentz force based CMOS-MEMS magnetic field sensor is designed, fabricated and optically characterized. The sensor is fabricated by using CMOS thin layers and dry post micromachining is used to release the device structure and finally the sensor chip is packaged in DIP. The sensor consists of a shuttle which is designed to resonate in the lateral direction (first mode of resonance). In the presence of an external magnetic field, the Lorentz force actuates the shuttle in the lateral direction and the amplitude of resonance is measured using an optical method. The differential change in the amplitude of the resonating shuttle shows the strength of the external magnetic field. The resonance frequency of the shuttle is determined to be 8164 Hz experimentally and from the resonance curve, the quality factor and damping ratio are obtained. In an open environment, the quality factor and damping ratio are found to be 51.34 and 0.00973 respectively. The sensitivity of the sensor is determined in static mode to be 0.034 µm/mT when a current of 10 mA passes through the shuttle, while it is found to be higher at resonance with a value of 1.35 µm/mT at 8 mA current. Finally, the resolution of the sensor is found to be 370.37 µT.

Health-Enabled Smart Sensor Fusion Technology

NASA Technical Reports Server (NTRS)

Wang, Ray

2012-01-01

A process was designed to fuse data from multiple sensors in order to make a more accurate estimation of the environment and overall health in an intelligent rocket test facility (IRTF), to provide reliable, high-confidence measurements for a variety of propulsion test articles. The object of the technology is to provide sensor fusion based on a distributed architecture. Specifically, the fusion technology is intended to succeed in providing health condition monitoring capability at the intelligent transceiver, such as RF signal strength, battery reading, computing resource monitoring, and sensor data reading. The technology also provides analytic and diagnostic intelligence at the intelligent transceiver, enhancing the IEEE 1451.x-based standard for sensor data management and distributions, as well as providing appropriate communications protocols to enable complex interactions to support timely and high-quality flow of information among the system elements.

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

PubMed Central

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

2013-01-01

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

A novel, optical, on-line bacteria sensor for monitoring drinking water quality

PubMed Central

Højris, Bo; Christensen, Sarah Christine Boesgaard; Albrechtsen, Hans-Jørgen; Smith, Christian; Dahlqvist, Mathis

2016-01-01

Today, microbial drinking water quality is monitored through either time-consuming laboratory methods or indirect on-line measurements. Results are thus either delayed or insufficient to support proactive action. A novel, optical, on-line bacteria sensor with a 10-minute time resolution has been developed. The sensor is based on 3D image recognition, and the obtained pictures are analyzed with algorithms considering 59 quantified image parameters. The sensor counts individual suspended particles and classifies them as either bacteria or abiotic particles. The technology is capable of distinguishing and quantifying bacteria and particles in pure and mixed suspensions, and the quantification correlates with total bacterial counts. Several field applications have demonstrated that the technology can monitor changes in the concentration of bacteria, and is thus well suited for rapid detection of critical conditions such as pollution events in drinking water. PMID:27040142

A novel, optical, on-line bacteria sensor for monitoring drinking water quality.

PubMed

Højris, Bo; Christensen, Sarah Christine Boesgaard; Albrechtsen, Hans-Jørgen; Smith, Christian; Dahlqvist, Mathis

2016-04-04

Today, microbial drinking water quality is monitored through either time-consuming laboratory methods or indirect on-line measurements. Results are thus either delayed or insufficient to support proactive action. A novel, optical, on-line bacteria sensor with a 10-minute time resolution has been developed. The sensor is based on 3D image recognition, and the obtained pictures are analyzed with algorithms considering 59 quantified image parameters. The sensor counts individual suspended particles and classifies them as either bacteria or abiotic particles. The technology is capable of distinguishing and quantifying bacteria and particles in pure and mixed suspensions, and the quantification correlates with total bacterial counts. Several field applications have demonstrated that the technology can monitor changes in the concentration of bacteria, and is thus well suited for rapid detection of critical conditions such as pollution events in drinking water.

Ultrasensitive sensing with three-dimensional terahertz metamaterial absorber

NASA Astrophysics Data System (ADS)

Tan, Siyu; Yan, Fengping; Wang, Wei; Zhou, Hong; Hou, Yafei

2018-05-01

Planar metasurfaces and metamaterial absorbers have shown great promise for label-free sensing applications at microwaves, optical and terahertz frequencies. The realization of high-quality-factor resonance in these structures is of significant interest to enhance the sensing sensitivities to detect minute frequency shifts. We propose and demonstrate in this manuscript an ultrasensitive terahertz metamaterial absorber sensor based on a three-dimensional split ring resonator absorber with a high quality factor of 60.09. The sensing performance of the proposed absorber sensor was systematically investigated through detailed numerical calculations and a maximum refractive index sensitivity of 34.40% RIU‑1 was obtained. Furthermore, the absorber sensor can maintain a high sensitivity for a wide range of incidence angles up to 60° under TM polarization incidence. These findings would improve the design flexibility of the absorber sensors and further open up new avenues to achieve ultrasensitive sensing in the terahertz regime.

Development and Evaluation of A Novel and Cost-Effective Approach for Low-Cost NO2 Sensor Drift Correction

PubMed Central

Sun, Li; Westerdahl, Dane; Ning, Zhi

2017-01-01

Emerging low-cost gas sensor technologies have received increasing attention in recent years for air quality measurements due to their small size and convenient deployment. However, in the diverse applications these sensors face many technological challenges, including sensor drift over long-term deployment that cannot be easily addressed using mathematical correction algorithms or machine learning methods. This study aims to develop a novel approach to auto-correct the drift of commonly used electrochemical nitrogen dioxide (NO2) sensor with comprehensive evaluation of its application. The impact of environmental factors on the NO2 electrochemical sensor in low-ppb concentration level measurement was evaluated in laboratory and the temperature and relative humidity correction algorithm was evaluated. An automated zeroing protocol was developed and assessed using a chemical absorbent to remove NO2 as a means to perform zero correction in varying ambient conditions. The sensor system was operated in three different environments in which data were compared to a reference NO2 analyzer. The results showed that the zero-calibration protocol effectively corrected the observed drift of the sensor output. This technique offers the ability to enhance the performance of low-cost sensor based systems and these findings suggest extension of the approach to improve data quality from sensors measuring other gaseous pollutants in urban air. PMID:28825633

Non-destructive evaluation of ripening and quality traits in apples using a multiparametric fluorescence sensor.

PubMed

Betemps, Débora L; Fachinello, José Carlos; Galarça, Simone P; Portela, Nicácia M; Remorini, Damiano; Massai, Rossano; Agati, Giovanni

2012-07-01

The detection of pigments and colourless flavonoids in apples can provide a useful indication of fruit quality. Optical methods are preferable because they are fast and non-destructive. In this study, a fluorescence-based portable sensor was used in order to non-invasively determine the content of chlorophylls, anthocyanins and flavonols in Fuji, Granny Smith and Golden Delicious apple cultivars. The aim was to define new non-destructive optical indices of apple quality. The anthocyanin index (ANTH) in Fuji was higher in the sunny (i.e. sun-exposed) side of the fruit compared to the shady side. For all cultivars, the flavonol index (FLAV) was higher in the sunny side compared with the shady side. The chlorophyll index (CHL) for the shady sides of Granny Smith and Golden Delicious was significantly higher than for the sunny sides. Fine linear regressions were found between the ANTH, FLAV and CHL indices and the actual anthocyanin, flavonol and chlorophyll concentrations, respectively, which were determined destructively on the apple peel extracts. A negative correlation was found between the apple sugar content and the chlorophyll fluorescence in the far-red spectral band. Our results indicate that a single multiparametric fluorescence-based sensor can provide valuable non-destructive markers of ripening and quality in apples. Copyright © 2012 Society of Chemical Industry.

Data Quality Control Tools Applied to Seismo-Acoustic Arrays in Korea

NASA Astrophysics Data System (ADS)

Park, J.; Hayward, C.; Stump, B. W.

2017-12-01

We assess data quality (data gap, seismometer orientation, timing error, noise level and coherence between co-located sensors) for seismic and infrasound data in South Korea using six seismo-acoustic arrays, BRDAR, CHNAR, KSGAR, KMPAR, TJIAR, and YPDAR, cooperatively operated by Southern Methodist University and Korea Institute for Geosciences and Mineral Resources. Timing errors associated with seismometers can be found based on estimated changes in instrument orientation calculated from RMS errors between the reference array and each array seismometer using waveforms filtered from 0.1 to 0.35 Hz. Noise levels of seismic and infrasound data are analyzed to investigate local environmental effects and seasonal noise variation. In order to examine the spectral properties of the noise, the waveform are analyzed using Welch's method (Welch, 1967) that produces a single power spectral estimate from an average of spectra taken at regular intervals over a specific time period. This analysis quantifies the range of noise conditions found at each of the arrays over the given time period. We take an advantage of the fact that infrasound sensors are co-located or closely located to one another, which allows for a direct comparison of sensors, following the method by Ringler et al. (2010). The power level differences between two sensors at the same array in the frequency band of interest are used to monitor temporal changes in data quality and instrument conditions. A data quality factor is assigned to stations based on the average values of temporal changes estimated in the frequency and time domains. These monitoring tools enable us to automatically assess technical issue related to the instruments and data quality at each seismo-acoustic array as well as to investigate local environmental effects and seasonal variations in both seismic and infrasound data.

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.

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

NASA Astrophysics Data System (ADS)

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

2007-12-01

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

3D Printing-Based Integrated Water Quality Sensing System

PubMed Central

Banna, Muinul; Bera, Kaustav; Sochol, Ryan; Lin, Liwei; Najjaran, Homayoun; Sadiq, Rehan; Hoorfar, Mina

2017-01-01

The online and accurate monitoring of drinking water supply networks is critically in demand to rapidly detect the accidental or deliberate contamination of drinking water. At present, miniaturized water quality monitoring sensors developed in the laboratories are usually tested under ambient pressure and steady-state flow conditions; however, in Water Distribution Systems (WDS), both the pressure and the flowrate fluctuate. In this paper, an interface is designed and fabricated using additive manufacturing or 3D printing technology—material extrusion (Trade Name: fused deposition modeling, FDM) and material jetting—to provide a conduit for miniaturized sensors for continuous online water quality monitoring. The interface is designed to meet two main criteria: low pressure at the inlet of the sensors and a low flowrate to minimize the water bled (i.e., leakage), despite varying pressure from WDS. To meet the above criteria, a two-dimensional computational fluid dynamics model was used to optimize the geometry of the channel. The 3D printed interface, with the embedded miniaturized pH and conductivity sensors, was then tested at different temperatures and flowrates. The results show that the response of the pH sensor is independent of the flowrate and temperature. As for the conductivity sensor, the flowrate and temperature affect only the readings at a very low conductivity (4 µS/cm) and high flowrates (30 mL/min), and a very high conductivity (460 µS/cm), respectively. PMID:28594387

High-performance optical projection controllable ZnO nanorod arrays for microweighing sensors.

PubMed

Wang, Hongbo; Jiang, Shulan; Zhang, Lei; Yu, Bingjun; Chen, Duoli; Yang, Weiqing; Qian, Linmao

2018-03-08

Optical microweighing sensors are an essential component of micro-force measurements in physical, chemical, and biological detection fields, although, their limited detection range (less than 15°) severely hinders their wide application. Such a limitation is mainly attributed to the essential restrictions of traditional light reflection and optical waveguide modes. Here, we report a high-performance optical microweighing sensor based on the synergistic effects of both a new optical projection mode and a ZnO nanorod array sensor. Ascribed to the unique configuration design of this sensing method, this optical microweighing sensor has a wide detection range (more than 80°) and a high sensitivity of 90 nA deg -1 , which is much larger than that of conventional microcantilever-based optical microweighing sensors. Furthermore, the location of the UV light source can be adjusted within a few millimeters, meaning that the microweighing sensor does not need repetitive optical calibration. More importantly, for low height and small incident angles of the UV light source, we can obtain highly sensitive microweighing properties on account of the highly sensitive ZnO nanorod array-based UV sensor. Therefore, this kind of large detection range, non-contact, and non-destructive microweighing sensor has potential applications in air quality monitoring and chemical and biological detection.

Distributed sensor architecture for intelligent control that supports quality of control and quality of service.

PubMed

Poza-Lujan, Jose-Luis; Posadas-Yagüe, Juan-Luis; Simó-Ten, José-Enrique; Simarro, Raúl; Benet, Ginés

2015-02-25

This paper is part of a study of intelligent architectures for distributed control and communications systems. The study focuses on optimizing control systems by evaluating the performance of middleware through quality of service (QoS) parameters and the optimization of control using Quality of Control (QoC) parameters. The main aim of this work is to study, design, develop, and evaluate a distributed control architecture based on the Data-Distribution Service for Real-Time Systems (DDS) communication standard as proposed by the Object Management Group (OMG). As a result of the study, an architecture called Frame-Sensor-Adapter to Control (FSACtrl) has been developed. FSACtrl provides a model to implement an intelligent distributed Event-Based Control (EBC) system with support to measure QoS and QoC parameters. The novelty consists of using, simultaneously, the measured QoS and QoC parameters to make decisions about the control action with a new method called Event Based Quality Integral Cycle. To validate the architecture, the first five Braitenberg vehicles have been implemented using the FSACtrl architecture. The experimental outcomes, demonstrate the convenience of using jointly QoS and QoC parameters in distributed control systems.

Distributed Sensor Architecture for Intelligent Control that Supports Quality of Control and Quality of Service

PubMed Central

Poza-Lujan, Jose-Luis; Posadas-Yagüe, Juan-Luis; Simó-Ten, José-Enrique; Simarro, Raúl; Benet, Ginés

2015-01-01

This paper is part of a study of intelligent architectures for distributed control and communications systems. The study focuses on optimizing control systems by evaluating the performance of middleware through quality of service (QoS) parameters and the optimization of control using Quality of Control (QoC) parameters. The main aim of this work is to study, design, develop, and evaluate a distributed control architecture based on the Data-Distribution Service for Real-Time Systems (DDS) communication standard as proposed by the Object Management Group (OMG). As a result of the study, an architecture called Frame-Sensor-Adapter to Control (FSACtrl) has been developed. FSACtrl provides a model to implement an intelligent distributed Event-Based Control (EBC) system with support to measure QoS and QoC parameters. The novelty consists of using, simultaneously, the measured QoS and QoC parameters to make decisions about the control action with a new method called Event Based Quality Integral Cycle. To validate the architecture, the first five Braitenberg vehicles have been implemented using the FSACtrl architecture. The experimental outcomes, demonstrate the convenience of using jointly QoS and QoC parameters in distributed control systems. PMID:25723145

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.

Inertial Motion Capture Costume Design Study

PubMed Central

Szczęsna, Agnieszka; Skurowski, Przemysław; Lach, Ewa; Pruszowski, Przemysław; Pęszor, Damian; Paszkuta, Marcin; Słupik, Janusz; Lebek, Kamil; Janiak, Mateusz; Polański, Andrzej; Wojciechowski, Konrad

2017-01-01

The paper describes a scalable, wearable multi-sensor system for motion capture based on inertial measurement units (IMUs). Such a unit is composed of accelerometer, gyroscope and magnetometer. The final quality of an obtained motion arises from all the individual parts of the described system. The proposed system is a sequence of the following stages: sensor data acquisition, sensor orientation estimation, system calibration, pose estimation and data visualisation. The construction of the system’s architecture with the dataflow programming paradigm makes it easy to add, remove and replace the data processing steps. The modular architecture of the system allows an effortless introduction of a new sensor orientation estimation algorithms. The original contribution of the paper is the design study of the individual components used in the motion capture system. The two key steps of the system design are explored in this paper: the evaluation of sensors and algorithms for the orientation estimation. The three chosen algorithms have been implemented and investigated as part of the experiment. Due to the fact that the selection of the sensor has a significant impact on the final result, the sensor evaluation process is also explained and tested. The experimental results confirmed that the choice of sensor and orientation estimation algorithm affect the quality of the final results. PMID:28304337

Direct Sensor Orientation of a Land-Based Mobile Mapping System

PubMed Central

Rau, Jiann-Yeou; Habib, Ayman F.; Kersting, Ana P.; Chiang, Kai-Wei; Bang, Ki-In; Tseng, Yi-Hsing; Li, Yu-Hua

2011-01-01

A land-based mobile mapping system (MMS) is flexible and useful for the acquisition of road environment geospatial information. It integrates a set of imaging sensors and a position and orientation system (POS). The positioning quality of such systems is highly dependent on the accuracy of the utilized POS. This limitation is the major drawback due to the elevated cost associated with high-end GPS/INS units, particularly the inertial system. The potential accuracy of the direct sensor orientation depends on the architecture and quality of the GPS/INS integration process as well as the validity of the system calibration (i.e., calibration of the individual sensors as well as the system mounting parameters). In this paper, a novel single-step procedure using integrated sensor orientation with relative orientation constraint for the estimation of the mounting parameters is introduced. A comparative analysis between the proposed single-step and the traditional two-step procedure is carried out. Moreover, the estimated mounting parameters using the different methods are used in a direct geo-referencing procedure to evaluate their performance and the feasibility of the implemented system. Experimental results show that the proposed system using single-step system calibration method can achieve high 3D positioning accuracy. PMID:22164015

A self-optimizing scheme for energy balanced routing in Wireless Sensor Networks using SensorAnt.

PubMed

Shamsan Saleh, Ahmed M; Ali, Borhanuddin Mohd; Rasid, Mohd Fadlee A; Ismail, Alyani

2012-01-01

Planning of energy-efficient protocols is critical for Wireless Sensor Networks (WSNs) because of the constraints on the sensor nodes' energy. The routing protocol should be able to provide uniform power dissipation during transmission to the sink node. In this paper, we present a self-optimization scheme for WSNs which is able to utilize and optimize the sensor nodes' resources, especially the batteries, to achieve balanced energy consumption across all sensor nodes. This method is based on the Ant Colony Optimization (ACO) metaheuristic which is adopted to enhance the paths with the best quality function. The assessment of this function depends on multi-criteria metrics such as the minimum residual battery power, hop count and average energy of both route and network. This method also distributes the traffic load of sensor nodes throughout the WSN leading to reduced energy usage, extended network life time and reduced packet loss. Simulation results show that our scheme performs much better than the Energy Efficient Ant-Based Routing (EEABR) in terms of energy consumption, balancing and efficiency.

EnviroDIY ModularSensors: A Library to give Environmental Sensors a Common Interface of Functions for use with Arduino-Compatible Dataloggers

NASA Astrophysics Data System (ADS)

Aufdenkampe, A. K.; Damiano, S. G.; Hicks, S.; Horsburgh, J. S.

2017-12-01

EnviroDIY is a community for do-it-yourself environmental science and monitoring (https://envirodiy.org), largely focused on sharing ideas for developing Arduino-compatible open-source sensor stations, similar to the EnviroDIY Mayfly datalogger (http://envirodiy.org/mayfly/). Here we present the ModularSensors Arduino code library (https://github.com/EnviroDIY/ModularSensors), deisigned to give all sensors and variables a common interface of functions and returns and to make it very easy to iterate through and log data from many sensors and variables. This library was written primarily for the EnviroDIY Mayfly, but we have begun to test it on other Arduino based boards. We will show the large number of developed sensor interfaces, and examples of using this library code to stream near real time data to the new EnviroDIY Water Quality Data Portal (http://data.envirodiy.org/), a data and software system based on the Observations Data Model v2 (http://www.odm2.org).

Mapping with Small UAS: A Point Cloud Accuracy Assessment

NASA Astrophysics Data System (ADS)

Toth, Charles; Jozkow, Grzegorz; Grejner-Brzezinska, Dorota

2015-12-01

Interest in using inexpensive Unmanned Aerial System (UAS) technology for topographic mapping has recently significantly increased. Small UAS platforms equipped with consumer grade cameras can easily acquire high-resolution aerial imagery allowing for dense point cloud generation, followed by surface model creation and orthophoto production. In contrast to conventional airborne mapping systems, UAS has limited ground coverage due to low flying height and limited flying time, yet it offers an attractive alternative to high performance airborne systems, as the cost of the sensors and platform, and the flight logistics, is relatively low. In addition, UAS is better suited for small area data acquisitions and to acquire data in difficult to access areas, such as urban canyons or densely built-up environments. The main question with respect to the use of UAS is whether the inexpensive consumer sensors installed in UAS platforms can provide the geospatial data quality comparable to that provided by conventional systems. This study aims at the performance evaluation of the current practice of UAS-based topographic mapping by reviewing the practical aspects of sensor configuration, georeferencing and point cloud generation, including comparisons between sensor types and processing tools. The main objective is to provide accuracy characterization and practical information for selecting and using UAS solutions in general mapping applications. The analysis is based on statistical evaluation as well as visual examination of experimental data acquired by a Bergen octocopter with three different image sensor configurations, including a GoPro HERO3+ Black Edition, a Nikon D800 DSLR and a Velodyne HDL-32. In addition, georeferencing data of varying quality were acquired and evaluated. The optical imagery was processed by using three commercial point cloud generation tools. Comparing point clouds created by active and passive sensors by using different quality sensors, and finally, by different commercial software tools, provides essential information for the performance validation of UAS technology.

Chemical preparation of graphene-based nanomaterials and their applications in chemical and biological sensors.

PubMed

Jiang, Hongji

2011-09-05

Graphene is a flat monolayer of carbon atoms packed tightly into a 2D honeycomb lattice that shows many intriguing properties meeting the key requirements for the implementation of highly excellent sensors, and all kinds of proof-of-concept sensors have been devised. To realize the potential sensor applications, the key is to synthesize graphene in a controlled way to achieve enhanced solution-processing capabilities, and at the same time to maintain or even improve the intrinsic properties of graphene. Several production techniques for graphene-based nanomaterials have been developed, ranging from the mechanical cleavage and chemical exfoliation of high-quality graphene to direct growth onto different substrates and the chemical routes using graphite oxide as a precusor to the newly developed bottom-up approach at the molecular level. The current review critically explores the recent progress on the chemical preparation of graphene-based nanomaterials and their applications in sensors. Copyright © 2011 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Evaluation of coffee roasting degree by using electronic nose and artificial neural network for off-line quality control.

PubMed

Romani, Santina; Cevoli, Chiara; Fabbri, Angelo; Alessandrini, Laura; Dalla Rosa, Marco

2012-09-01

An electronic nose (EN) based on an array of 10 metal oxide semiconductor sensors was used, jointly with an artificial neural network (ANN), to predict coffee roasting degree. The flavor release evolution and the main physicochemical modifications (weight loss, density, moisture content, and surface color: L*, a*), during the roasting process of coffee, were monitored at different cooking times (0, 6, 8, 10, 14, 19 min). Principal component analysis (PCA) was used to reduce the dimensionality of sensors data set (600 values per sensor). The selected PCs were used as ANN input variables. Two types of ANN methods (multilayer perceptron [MLP] and general regression neural network [GRNN]) were used in order to estimate the EN signals. For both neural networks the input values were represented by scores of sensors data set PCs, while the output values were the quality parameter at different roasting times. Both the ANNs were able to well predict coffee roasting degree, giving good prediction results for both roasting time and coffee quality parameters. In particular, GRNN showed the highest prediction reliability. Actually the evaluation of coffee roasting degree is mainly a manned operation, substantially based on the empirical final color observation. For this reason it requires well-trained operators with a long professional skill. The coupling of e-nose and artificial neural networks (ANNs) may represent an effective possibility to roasting process automation and to set up a more reproducible procedure for final coffee bean quality characterization. © 2012 Institute of Food Technologists®

Research on dynamic routing mechanisms in wireless sensor networks.

PubMed

Zhao, A Q; Weng, Y N; Lu, Y; Liu, C Y

2014-01-01

WirelessHART is the most widely applied standard in wireless sensor networks nowadays. However, it does not provide any dynamic routing mechanism, which is important for the reliability and robustness of the wireless network applications. In this paper, a collection tree protocol based, dynamic routing mechanism was proposed for WirelessHART network. The dynamic routing mechanism was evaluated through several simulation experiments in three aspects: time for generating the topology, link quality, and stability of network. Besides, the data transmission efficiency of this routing mechanism was analyzed. The simulation and evaluation results show that this mechanism can act as a dynamic routing mechanism for the TDMA-based wireless sensor network.

Forensic use of photo response non-uniformity of imaging sensors and a counter method.

PubMed

Dirik, Ahmet Emir; Karaküçük, Ahmet

2014-01-13

Analogous to use of bullet scratches in forensic science, the authenticity of a digital image can be verified through the noise characteristics of an imaging sensor. In particular, photo-response non-uniformity noise (PRNU) has been used in source camera identification (SCI). However, this technique can be used maliciously to track or inculpate innocent people. To impede such tracking, PRNU noise should be suppressed significantly. Based on this motivation, we propose a counter forensic method to deceive SCI. Experimental results show that it is possible to impede PRNU-based camera identification for various imaging sensors while preserving the image quality.

FPGA-based fused smart-sensor for tool-wear area quantitative estimation in CNC machine inserts.

PubMed

Trejo-Hernandez, Miguel; Osornio-Rios, Roque Alfredo; de Jesus Romero-Troncoso, Rene; Rodriguez-Donate, Carlos; Dominguez-Gonzalez, Aurelio; Herrera-Ruiz, Gilberto

2010-01-01

Manufacturing processes are of great relevance nowadays, when there is a constant claim for better productivity with high quality at low cost. The contribution of this work is the development of a fused smart-sensor, based on FPGA to improve the online quantitative estimation of flank-wear area in CNC machine inserts from the information provided by two primary sensors: the monitoring current output of a servoamplifier, and a 3-axis accelerometer. Results from experimentation show that the fusion of both parameters makes it possible to obtain three times better accuracy when compared with the accuracy obtained from current and vibration signals, individually used.

Technology needs assessment of an atmospheric observation system for tropospheric research missions, part 1

NASA Technical Reports Server (NTRS)

Alvarado, D. R.; Bortner, M. H.; Grenda, R. N.; Frippel, G. G.; Halsey, H.; Neste, S. L.; Kritikos, H.; Keafer, L. S.; Deryder, L. J.

1982-01-01

The technology advancements needed to implement the atmospheric observation satellite systems for air quality research were identified. Tropospheric measurements are considered. The measurements and sensors are based on a model of knowledge objectives in atmospheric science. A set of potential missions and attendant spacecraft and sensors is postulated. The results show that the predominant technology needs will be in passive and active sensors for accurate and frequent global measurements of trace gas concentration profiles.

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.

A Novel Hybrid Error Criterion-Based Active Control Method for on-Line Milling Vibration Suppression with Piezoelectric Actuators and Sensors

PubMed Central

Zhang, Xingwu; Wang, Chenxi; Gao, Robert X.; Yan, Ruqiang; Chen, Xuefeng; Wang, Shibin

2016-01-01

Milling vibration is one of the most serious factors affecting machining quality and precision. In this paper a novel hybrid error criterion-based frequency-domain LMS active control method is constructed and used for vibration suppression of milling processes by piezoelectric actuators and sensors, in which only one Fast Fourier Transform (FFT) is used and no Inverse Fast Fourier Transform (IFFT) is involved. The correction formulas are derived by a steepest descent procedure and the control parameters are analyzed and optimized. Then, a novel hybrid error criterion is constructed to improve the adaptability, reliability and anti-interference ability of the constructed control algorithm. Finally, based on piezoelectric actuators and acceleration sensors, a simulation of a spindle and a milling process experiment are presented to verify the proposed method. Besides, a protection program is added in the control flow to enhance the reliability of the control method in applications. The simulation and experiment results indicate that the proposed method is an effective and reliable way for on-line vibration suppression, and the machining quality can be obviously improved. PMID:26751448

Comparison of the performance of intraoral X-ray sensors using objective image quality assessment.

PubMed

Hellén-Halme, Kristina; Johansson, Curt; Nilsson, Mats

2016-05-01

The main aim of this study was to evaluate the performance of 10 individual sensors of the same make, using objective measures of key image quality parameters. A further aim was to compare 8 brands of sensors. Ten new sensors of 8 different models from 6 manufacturers (i.e., 80 sensors) were included in the study. All sensors were exposed in a standardized way using an X-ray tube voltage of 60 kVp and different exposure times. Sensor response, noise, low-contrast resolution, spatial resolution and uniformity were measured. Individual differences between sensors of the same brand were surprisingly large in some cases. There were clear differences in the characteristics of the different brands of sensors. The largest variations were found for individual sensor response for some of the brands studied. Also, noise level and low contrast resolution showed large variations between brands. Sensors, even of the same brand, vary significantly in their quality. It is thus valuable to establish action levels for the acceptance of newly delivered sensors and to use objective image quality control for commissioning purposes and periodic checks to ensure high performance of individual digital sensors. Copyright © 2016 Elsevier Inc. All rights reserved.

Theoretical and experimental investigations of sensor location for optimal aeroelastic system state estimation

NASA Technical Reports Server (NTRS)

Liu, G.

1985-01-01

One of the major concerns in the design of an active control system is obtaining the information needed for effective feedback. This involves the combination of sensing and estimation. A sensor location index is defined as the weighted sum of the mean square estimation errors in which the sensor locations can be regarded as estimator design parameters. The design goal is to choose these locations to minimize the sensor location index. The choice of the number of sensors is a tradeoff between the estimation quality based upon the same performance index and the total costs of installing and maintaining extra sensors. An experimental study for choosing the sensor location was conducted on an aeroelastic system. The system modeling which includes the unsteady aerodynamics model developed by Stephen Rock was improved. Experimental results verify the trend of the theoretical predictions of the sensor location index for different sensor locations at various wind speeds.

Computer-Aided Sensor Development Focused on Security Issues.

PubMed

Bialas, Andrzej

2016-05-26

The paper examines intelligent sensor and sensor system development according to the Common Criteria methodology, which is the basic security assurance methodology for IT products and systems. The paper presents how the development process can be supported by software tools, design patterns and knowledge engineering. The automation of this process brings cost-, quality-, and time-related advantages, because the most difficult and most laborious activities are software-supported and the design reusability is growing. The paper includes a short introduction to the Common Criteria methodology and its sensor-related applications. In the experimental section the computer-supported and patterns-based IT security development process is presented using the example of an intelligent methane detection sensor. This process is supported by an ontology-based tool for security modeling and analyses. The verified and justified models are transferred straight to the security target specification representing security requirements for the IT product. The novelty of the paper is to provide a patterns-based and computer-aided methodology for the sensors development with a view to achieving their IT security assurance. The paper summarizes the validation experiment focused on this methodology adapted for the sensors system development, and presents directions of future research.

Computer-Aided Sensor Development Focused on Security Issues

PubMed Central

Bialas, Andrzej

2016-01-01

The paper examines intelligent sensor and sensor system development according to the Common Criteria methodology, which is the basic security assurance methodology for IT products and systems. The paper presents how the development process can be supported by software tools, design patterns and knowledge engineering. The automation of this process brings cost-, quality-, and time-related advantages, because the most difficult and most laborious activities are software-supported and the design reusability is growing. The paper includes a short introduction to the Common Criteria methodology and its sensor-related applications. In the experimental section the computer-supported and patterns-based IT security development process is presented using the example of an intelligent methane detection sensor. This process is supported by an ontology-based tool for security modeling and analyses. The verified and justified models are transferred straight to the security target specification representing security requirements for the IT product. The novelty of the paper is to provide a patterns-based and computer-aided methodology for the sensors development with a view to achieving their IT security assurance. The paper summarizes the validation experiment focused on this methodology adapted for the sensors system development, and presents directions of future research. PMID:27240360

The Significance of Witness Sensors for Mass Casualty Incidents and Epidemic Outbreaks.

PubMed

Pan, Chih-Long; Lin, Chih-Hao; Lin, Yan-Ren; Wen, Hsin-Yu; Wen, Jet-Chau

2018-02-02

Due to the increasing number of natural and man-made disasters, mass casualty incidents occur more often than ever before. As a result, health care providers need to adapt in order to cope with the overwhelming patient surge. To ensure quality and safety in health care, accurate information in pandemic disease control, death reduction, and health quality promotion should be highlighted. However, obtaining precise information in real time is an enormous challenge to all researchers of the field. In this paper, innovative strategies are presented to develop a sound information network using the concept of "witness sensors." To overcome the reliability and quality limitations of information obtained through social media, researchers must focus on developing solutions that secure the authenticity of social media messages, especially for matters related to health. To address this challenge, we introduce a novel concept based on the two elements of "witness" and "sensor." Witness sensors can be key players designated to minimize limitations to quality of information and to distinguish fact from fiction during critical events. In order to enhance health communication practices and deliver valid information to end users, the education and management of witness sensors should be further investigated, especially for implementation during mass casualty incidents and epidemic outbreaks. ©Chih-Long Pan, Chih-Hao Lin, Yan-Ren Lin, Hsin-Yu Wen, Jet-Chau Wen. Originally published in the Journal of Medical Internet Research (http://www.jmir.org), 02.02.2018.

Soft sensor modeling based on variable partition ensemble method for nonlinear batch processes

NASA Astrophysics Data System (ADS)

Wang, Li; Chen, Xiangguang; Yang, Kai; Jin, Huaiping

2017-01-01

Batch processes are always characterized by nonlinear and system uncertain properties, therefore, the conventional single model may be ill-suited. A local learning strategy soft sensor based on variable partition ensemble method is developed for the quality prediction of nonlinear and non-Gaussian batch processes. A set of input variable sets are obtained by bootstrapping and PMI criterion. Then, multiple local GPR models are developed based on each local input variable set. When a new test data is coming, the posterior probability of each best performance local model is estimated based on Bayesian inference and used to combine these local GPR models to get the final prediction result. The proposed soft sensor is demonstrated by applying to an industrial fed-batch chlortetracycline fermentation process.

Calibration-free optical chemical sensors

DOEpatents

DeGrandpre, Michael D.

2006-04-11

An apparatus and method for taking absorbance-based chemical measurements are described. In a specific embodiment, an indicator-based pCO₂ (partial pressure of CO₂) sensor displays sensor-to-sensor reproducibility and measurement stability. These qualities are achieved by: 1) renewing the sensing solution, 2) allowing the sensing solution to reach equilibrium with the analyte, and 3) calculating the response from a ratio of the indicator solution absorbances which are determined relative to a blank solution. Careful solution preparation, wavelength calibration, and stray light rejection also contribute to this calibration-free system. Three pCO₂ sensors were calibrated and each had response curves which were essentially identical within the uncertainty of the calibration. Long-term laboratory and field studies showed the response had no drift over extended periods (months). The theoretical response, determined from thermodynamic characterization of the indicator solution, also predicted the observed calibration-free performance.

Optical sensing system based on wireless paired emitter detector diode device and ionogels for lab-on-a-disc water quality analysis.

PubMed

Czugala, Monika; Gorkin, Robert; Phelan, Thomas; Gaughran, Jennifer; Curto, Vincenzo Fabio; Ducrée, Jens; Diamond, Dermot; Benito-Lopez, Fernando

2012-12-07

This work describes the first use of a wireless paired emitter detector diode device (PEDD) as an optical sensor for water quality monitoring in a lab-on-a-disc device. The microfluidic platform, based on an ionogel sensing area combined with a low-cost optical sensor, is applied for quantitative pH and qualitative turbidity monitoring of water samples at point-of-need. The autonomous capabilities of the PEDD system, combined with the portability and wireless communication of the full device, provide the flexibility needed for on-site water testing. Water samples from local fresh and brackish sources were successfully analysed using the device, showing very good correlation with standard bench-top systems.

Development of Software Sensors for Determining Total Phosphorus and Total Nitrogen in Waters

PubMed Central

Lee, Eunhyoung; Han, Sanghoon; Kim, Hyunook

2013-01-01

Total nitrogen (TN) and total phosphorus (TP) concentrations are important parameters to assess the quality of water bodies and are used as criteria to regulate the water quality of the effluent from a wastewater treatment plant (WWTP) in Korea. Therefore, continuous monitoring of TN and TP using in situ instruments is conducted nationwide in Korea. However, most in situ instruments in the market are expensive and require a time-consuming sample pretreatment step, which hinders the widespread use of in situ TN and TP monitoring. In this study, therefore, software sensors based on multiple-regression with a few easily in situ measurable water quality parameters were applied to estimate the TN and TP concentrations in a stream, a lake, combined sewer overflows (CSOs), and WWTP effluent. In general, the developed software sensors predicted TN and TP concentrations of the WWTP effluent and CSOs reasonably well. However, they showed relatively lower predictability for TN and TP concentrations of stream and lake waters, possibly because the water quality of stream and lake waters is more variable than that of WWTP effluent or CSOs. PMID:23307350

Sensor for In-Motion Continuous 3D Shape Measurement Based on Dual Line-Scan Cameras

PubMed Central

Sun, Bo; Zhu, Jigui; Yang, Linghui; Yang, Shourui; Guo, Yin

2016-01-01

The acquisition of three-dimensional surface data plays an increasingly important role in the industrial sector. Numerous 3D shape measurement techniques have been developed. However, there are still limitations and challenges in fast measurement of large-scale objects or high-speed moving objects. The innovative line scan technology opens up new potentialities owing to the ultra-high resolution and line rate. To this end, a sensor for in-motion continuous 3D shape measurement based on dual line-scan cameras is presented. In this paper, the principle and structure of the sensor are investigated. The image matching strategy is addressed and the matching error is analyzed. The sensor has been verified by experiments and high-quality results are obtained. PMID:27869731

Ultra-sensitive Hall sensors based on graphene encapsulated in hexagonal boron nitride

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

Dauber, Jan; Stampfer, Christoph; Peter Grünberg Institute

2015-05-11

The encapsulation of graphene in hexagonal boron nitride provides graphene on substrate with excellent material quality. Here, we present the fabrication and characterization of Hall sensor elements based on graphene boron nitride heterostructures, where we gain from high mobility and low charge carrier density at room temperature. We show a detailed device characterization including Hall effect measurements under vacuum and ambient conditions. We achieve a current- and voltage-related sensitivity of up to 5700 V/AT and 3 V/VT, respectively, outpacing state-of-the-art silicon and III/V Hall sensor devices. Finally, we extract a magnetic resolution limited by low frequency electric noise of less than 50more » nT/√(Hz) making our graphene sensors highly interesting for industrial applications.« less

High sensitivity gas sensor based on high-Q suspended polymer photonic crystal nanocavity

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

Clevenson, Hannah, E-mail: hannahac@mit.edu; Desjardins, Pierre; Gan, Xuetao

2014-06-16

We present high-sensitivity, multi-use optical gas sensors based on a one-dimensional photonic crystal cavity. These devices are implemented in versatile, flexible polymer materials which swell when in contact with a target gas, causing a measurable cavity length change. This change causes a shift in the cavity resonance, allowing precision measurements of gas concentration. We demonstrate suspended polymer nanocavity sensors and the recovery of sensors after the removal of stimulant gas from the system. With a measured quality factor exceeding 10{sup 4}, we show measurements of gas concentration as low as 600 parts per million (ppm) and an experimental sensitivity ofmore » 10 ppm; furthermore, we predict detection levels in the parts-per-billion range for a variety of gases.« less

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.

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.

A Genetic Algorithm Approach to Motion Sensor Placement in Smart Environments.

PubMed

Thomas, Brian L; Crandall, Aaron S; Cook, Diane J

2016-04-01

Smart environments and ubiquitous computing technologies hold great promise for a wide range of real world applications. The medical community is particularly interested in high quality measurement of activities of daily living. With accurate computer modeling of older adults, decision support tools may be built to assist care providers. One aspect of effectively deploying these technologies is determining where the sensors should be placed in the home to effectively support these end goals. This work introduces and evaluates a set of approaches for generating sensor layouts in the home. These approaches range from the gold standard of human intuition-based placement to more advanced search algorithms, including Hill Climbing and Genetic Algorithms. The generated layouts are evaluated based on their ability to detect activities while minimizing the number of needed sensors. Sensor-rich environments can provide valuable insights about adults as they go about their lives. These sensors, once in place, provide information on daily behavior that can facilitate an aging-in-place approach to health care.

A Genetic Algorithm Approach to Motion Sensor Placement in Smart Environments

PubMed Central

Thomas, Brian L.; Crandall, Aaron S.; Cook, Diane J.

2016-01-01

Smart environments and ubiquitous computing technologies hold great promise for a wide range of real world applications. The medical community is particularly interested in high quality measurement of activities of daily living. With accurate computer modeling of older adults, decision support tools may be built to assist care providers. One aspect of effectively deploying these technologies is determining where the sensors should be placed in the home to effectively support these end goals. This work introduces and evaluates a set of approaches for generating sensor layouts in the home. These approaches range from the gold standard of human intuition-based placement to more advanced search algorithms, including Hill Climbing and Genetic Algorithms. The generated layouts are evaluated based on their ability to detect activities while minimizing the number of needed sensors. Sensor-rich environments can provide valuable insights about adults as they go about their lives. These sensors, once in place, provide information on daily behavior that can facilitate an aging-in-place approach to health care. PMID:27453810

Temperature and pH sensors based on graphenic materials.

PubMed

Salvo, P; Calisi, N; Melai, B; Cortigiani, B; Mannini, M; Caneschi, A; Lorenzetti, G; Paoletti, C; Lomonaco, T; Paolicchi, A; Scataglini, I; Dini, V; Romanelli, M; Fuoco, R; Di Francesco, F

2017-05-15

Point-of-care applications and patients' real-time monitoring outside a clinical setting would require disposable and durable sensors to provide better therapies and quality of life for patients. This paper describes the fabrication and performances of a temperature and a pH sensor on a biocompatible and wearable board for healthcare applications. The temperature sensor was based on a reduced graphene oxide (rGO) layer that changed its electrical resistivity with the temperature. When tested in a human serum sample between 25 and 43°C, the sensor had a sensitivity of 110±10Ω/°C and an error of 0.4±0.1°C compared with the reference value set in a thermostatic bath. The pH sensor, based on a graphene oxide (GO) sensitive layer, had a sensitivity of 40±4mV/pH in the pH range between 4 and 10. Five sensor prototypes were tested in a human serum sample over one week and the maximum deviation of the average response from reference values obtained by a glass electrode was 0.2pH units. For biological applications, the temperature and pH sensors were successfully tested for in vitro cytotoxicity with human fibroblast cells (MRC-5) over 24h. Copyright © 2017 Elsevier B.V. All rights reserved.

Wearable sensor use for assessing standing balance and walking stability in people with Parkinson's disease: a systematic review.

PubMed

Hubble, Ryan P; Naughton, Geraldine A; Silburn, Peter A; Cole, Michael H

2015-01-01

Postural instability and gait disability threaten the independence and well-being of people with Parkinson's disease and increase the risk of falls and fall-related injuries. Prospective research has shown that commonly-used clinical assessments of balance and walking lack the sensitivity to accurately and consistently identify those people with Parkinson's disease who are at a higher risk of falling. Wearable sensors provide a portable and affordable alternative for researchers and clinicians who are seeking to objectively assess movements and falls risk in the clinical setting. However, no consensus currently exists on the optimal placements for sensors and the best outcome measures to use for assessing standing balance and walking stability in Parkinson's disease patients. Hence, this systematic review aimed to examine the available literature to establish the best sensor types, locations and outcomes to assess standing balance and walking stability in this population. Papers listed in three electronic databases were searched by title and abstract to identify articles measuring standing balance or walking stability with any kind of wearable sensor among adults diagnosed with PD. To be eligible for inclusion, papers were required to be full-text articles published in English between January 1994 and December 2014 that assessed measures of standing balance or walking stability with wearable sensors in people with PD. Articles were excluded if they; i) did not use any form of wearable sensor to measure variables associated with standing balance or walking stability; ii) did not include a control group or control condition; iii) were an abstract and/or included in the proceedings of a conference; or iv) were a review article or case study. The targeted search of the three electronic databases identified 340 articles that were potentially eligible for inclusion, but following title, abstract and full-text review only 26 articles were deemed to meet the inclusion criteria. Included articles were assessed for methodological quality and relevant data from the papers were extracted and synthesized. Quality assessment of these included articles indicated that 31% were of low methodological quality, while 58% were of moderate methodological quality and 11% were of high methodological quality. All studies adopted a cross-sectional design and used a variety of sensor types and outcome measures to assess standing balance or walking stability in people with Parkinson's disease. Despite the typically low to moderate methodological quality, 81% of the studies reported differences in sensor-based measures of standing balance or walking stability between different groups of Parkinson's disease patients and/or healthy controls. These data support the use of wearable sensors for detecting differences in standing balance and walking stability between people with PD and controls. Further high-quality research is needed to better understand the utility of wearable sensors for the early identification of Parkinson's disease symptoms and for assessing falls risk in this population. CRD42014010838.

Wearable Sensor Use for Assessing Standing Balance and Walking Stability in People with Parkinson’s Disease: A Systematic Review

PubMed Central

Hubble, Ryan P.; Naughton, Geraldine A.; Silburn, Peter A.; Cole, Michael H.

2015-01-01

Background Postural instability and gait disability threaten the independence and well-being of people with Parkinson’s disease and increase the risk of falls and fall-related injuries. Prospective research has shown that commonly-used clinical assessments of balance and walking lack the sensitivity to accurately and consistently identify those people with Parkinson’s disease who are at a higher risk of falling. Wearable sensors provide a portable and affordable alternative for researchers and clinicians who are seeking to objectively assess movements and falls risk in the clinical setting. However, no consensus currently exists on the optimal placements for sensors and the best outcome measures to use for assessing standing balance and walking stability in Parkinson’s disease patients. Hence, this systematic review aimed to examine the available literature to establish the best sensor types, locations and outcomes to assess standing balance and walking stability in this population. Methods Papers listed in three electronic databases were searched by title and abstract to identify articles measuring standing balance or walking stability with any kind of wearable sensor among adults diagnosed with PD. To be eligible for inclusion, papers were required to be full-text articles published in English between January 1994 and December 2014 that assessed measures of standing balance or walking stability with wearable sensors in people with PD. Articles were excluded if they; i) did not use any form of wearable sensor to measure variables associated with standing balance or walking stability; ii) did not include a control group or control condition; iii) were an abstract and/or included in the proceedings of a conference; or iv) were a review article or case study. The targeted search of the three electronic databases identified 340 articles that were potentially eligible for inclusion, but following title, abstract and full-text review only 26 articles were deemed to meet the inclusion criteria. Included articles were assessed for methodological quality and relevant data from the papers were extracted and synthesized. Results Quality assessment of these included articles indicated that 31% were of low methodological quality, while 58% were of moderate methodological quality and 11% were of high methodological quality. All studies adopted a cross-sectional design and used a variety of sensor types and outcome measures to assess standing balance or walking stability in people with Parkinson’s disease. Despite the typically low to moderate methodological quality, 81% of the studies reported differences in sensor-based measures of standing balance or walking stability between different groups of Parkinson’s disease patients and/or healthy controls. Conclusion These data support the use of wearable sensors for detecting differences in standing balance and walking stability between people with PD and controls. Further high-quality research is needed to better understand the utility of wearable sensors for the early identification of Parkinson’s disease symptoms and for assessing falls risk in this population. PROSPERO Registration CRD42014010838 PMID:25894561

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

PubMed

Gong, Jianya; Geng, Jing; Chen, Zeqiang

2015-01-09

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

Overview of the NASA tropospheric environmental quality remote sensing program

NASA Technical Reports Server (NTRS)

Allario, F.; Ayers, W. G.; Hoell, J. M.

1979-01-01

This paper will summarize the current NASA Tropospheric Environmental Quality Remote Sensing Program for studying the global and regional troposphere from space, airborne and ground-based platforms. As part of the program to develop remote sensors for utilization from space, NASA has developed a series of passive and active remote sensors which have undergone field test measurements from airborne and ground platforms. Recent measurements with active lidar and passive gas filter correlation and infrared heterodyne techniques will be summarized for measurements of atmospheric aerosols, CO, SO2, O3, and NH3. These measurements provide the data base required to assess the sensitivity of remote sensors for applications to urban and regional field measurement programs. Studies of Earth Observation Satellite Systems are currently being performed by the scientific community to assess the capability of satellite imagery to detect regions of elevated pollution in the troposphere. The status of NASA sponsored research efforts in interpreting satellite imagery for determining aerosol loadings over land and inland bodies of water will be presented, and comments on the potential of these measurements to supplement in situ and airborne remote sensors in detecting regional haze will be made.

Nanomaterial-enabled Rapid Detection of Water Contaminants.

PubMed

Mao, Shun; Chang, Jingbo; Zhou, Guihua; Chen, Junhong

2015-10-28

Water contaminants, e.g., inorganic chemicals and microorganisms, are critical metrics for water quality monitoring and have significant impacts on human health and plants/organisms living in water. The scope and focus of this review is nanomaterial-based optical, electronic, and electrochemical sensors for rapid detection of water contaminants, e.g., heavy metals, anions, and bacteria. These contaminants are commonly found in different water systems. The importance of water quality monitoring and control demands significant advancement in the detection of contaminants in water because current sensing technologies for water contaminants have limitations. The advantages of nanomaterial-based sensing technologies are highlighted and recent progress on nanomaterial-based sensors for rapid water contaminant detection is discussed. An outlook for future research into this rapidly growing field is also provided. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

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

EPA Science Inventory

In May 2017, a two-day workshop was held in Los Angeles (California, U.S.A.) to gather practitioners who work with low-cost sensors used to make air quality measurements. The community of practice included individuals from academia, industry, non-profit groups, community-based or...

Remote Sensing of Selected Water-Quality Indicators with the Hyperspectral Imager for the Coastal Ocean (HICO) Sensor

EPA Science Inventory

The Hyperspectral Imager for the Coastal Ocean (HICO) offers the coastal environmental monitoring community an unprecedented opportunity to observe changes in coastal and estuarine water quality across a range of spatial scales not feasible with traditional field-based monitoring...

Amperometric Gas Sensors as a Low Cost Emerging Technology Platform for Air Quality Monitoring Applications: A Review.

PubMed

Baron, Ronan; Saffell, John

2017-11-22

This review examines the use of amperometric electrochemical gas sensors for monitoring inorganic gases that affect urban air quality. First, we consider amperometric gas sensor technology including its development toward specifically designed air quality sensors. We then review recent academic and research organizations' studies where this technology has been trialed for air quality monitoring applications: early studies showed the potential of electrochemical gas sensors when colocated with reference Air Quality Monitoring (AQM) stations. Spatially dense networks with fast temporal resolution provide information not available from sparse AQMs with longer recording intervals. We review how this technology is being offered as commercial urban air quality networks and consider the remaining challenges. Sensors must be sensitive, selective, and stable; air quality monitors/nodes must be electronically and mechanically well designed. Data correction is required and models with differing levels of sophistication are being designed. Data analysis and validation is possibly the biggest remaining hurdle needed to deliver reliable concentration readings. Finally, this review also considers the roles of companies, urban infrastructure requirements, and public research in the development of this technology.

Lightweight UAV with on-board photogrammetry and single-frequency GPS positioning for metrology applications

NASA Astrophysics Data System (ADS)

Daakir, M.; Pierrot-Deseilligny, M.; Bosser, P.; Pichard, F.; Thom, C.; Rabot, Y.; Martin, O.

2017-05-01

This article presents a coupled system consisting of a single-frequency GPS receiver and a light photogrammetric quality camera embedded in an Unmanned Aerial Vehicle (UAV). The aim is to produce high quality data that can be used in metrology applications. The issue of Integrated Sensor Orientation (ISO) of camera poses using only GPS measurements is presented and discussed. The accuracy reached by our system based on sensors developed at the French Mapping Agency (IGN) Opto-Electronics, Instrumentation and Metrology Laboratory (LOEMI) is qualified. These sensors are specially designed for close-range aerial image acquisition with a UAV. Lever-arm calibration and time synchronization are explained and performed to reach maximum accuracy. All processing steps are detailed from data acquisition to quality control of final products. We show that an accuracy of a few centimeters can be reached with this system which uses low-cost UAV and GPS module coupled with the IGN-LOEMI home-made camera.

A reliable low cost integrated wireless sensor network for water quality monitoring and level control system in UAE

NASA Astrophysics Data System (ADS)

Abou-Elnour, Ali; Khaleeq, Hyder; Abou-Elnour, Ahmad

2016-04-01

In the present work, wireless sensor network and real-time controlling and monitoring system are integrated for efficient water quality monitoring for environmental and domestic applications. The proposed system has three main components (i) the sensor circuits, (ii) the wireless communication system, and (iii) the monitoring and controlling unit. LabView software has been used in the implementation of the monitoring and controlling system. On the other hand, ZigBee and myRIO wireless modules have been used to implement the wireless system. The water quality parameters are accurately measured by the present computer based monitoring system and the measurement results are instantaneously transmitted and published with minimum infrastructure costs and maximum flexibility in term of distance or location. The mobility and durability of the proposed system are further enhanced by fully powering via a photovoltaic system. The reliability and effectiveness of the system are evaluated under realistic operating conditions.

Odorant binding protein based biomimetic sensors for detection of alcohols associated with Salmonella contamination in packaged beef.

PubMed

Sankaran, Sindhuja; Panigrahi, Suranjan; Mallik, Sanku

2011-03-15

Detection of food-borne bacteria present in the food products is critical to prevent the spread of infectious diseases. Intelligent quality sensors are being developed for detecting bacterial pathogens such as Salmonella in beef. One of our research thrusts was to develop novel sensing materials sensitive to specific indicator alcohols at low concentrations. Present work focuses on developing olfactory sensors mimicking insect odorant binding protein to detect alcohols in low concentrations at room temperature. A quartz crystal microbalance (QCM) based sensor in conjunction with synthetic peptide was developed to detect volatile organic compounds indicative to Salmonella contamination in packaged beef. The peptide sequence used as sensing materials was derived from the amino acids sequence of Drosophila odorant binding protein, LUSH. The sensors were used to detect alcohols: 3-methyl-1-butanol and 1-hexanol. The sensors were sensitive to alcohols with estimated lower detection limits of <5 ppm. Thus, the LUSH-derived QCM sensors exhibited potential to detect alcohols at low ppm concentrations. Copyright © 2011. Published by Elsevier B.V.

Public engagement on urban air pollution: an exploratory study of two interventions.

PubMed

Oltra, Christian; Sala, Roser; Boso, Àlex; Asensio, Sergi López

2017-06-01

The use of portable sensors to measure air quality is a promising approach for the management of urban air quality given its potential to improve public participation in environmental issues and to promote healthy behaviors. However, not all the projects that use air quality mobile sensors consider the potential effects of their use on the attitudes and behaviors of non-expert individuals. This study explores the experiences, perceptions, attitudes, and behavioral intentions of 12 participants who used a real-time NO 2 sensor over a period of 7 days in the metropolitan area of Barcelona and compares them with 16 participants who did not have access to the device but rather to documentary information. The study design is based on recombined focus groups who met at the beginning and end of a 7-day activity. The results suggest that the experience with the sensors, in comparison with the traditional information, generates greater motivation among participants. Also, that the use of the sensor seems to support a more specific awareness of the problem of air pollution. In relation to risk perception, the textual and visual information seems to generate stronger beliefs of severity among participants. In both groups, beliefs of low controllability and self-efficacy are observed. Neither using the sensor nor reading the documentary information seems to contribute positively in this sense. The results of the study aim to contribute to the design of public involvement strategies in urban air pollution.

Motion-related resource allocation in dynamic wireless visual sensor network environments.

PubMed

Katsenou, Angeliki V; Kondi, Lisimachos P; Parsopoulos, Konstantinos E

2014-01-01

This paper investigates quality-driven cross-layer optimization for resource allocation in direct sequence code division multiple access wireless visual sensor networks. We consider a single-hop network topology, where each sensor transmits directly to a centralized control unit (CCU) that manages the available network resources. Our aim is to enable the CCU to jointly allocate the transmission power and source-channel coding rates for each node, under four different quality-driven criteria that take into consideration the varying motion characteristics of each recorded video. For this purpose, we studied two approaches with a different tradeoff of quality and complexity. The first one allocates the resources individually for each sensor, whereas the second clusters them according to the recorded level of motion. In order to address the dynamic nature of the recorded scenery and re-allocate the resources whenever it is dictated by the changes in the amount of motion in the scenery, we propose a mechanism based on the particle swarm optimization algorithm, combined with two restarting schemes that either exploit the previously determined resource allocation or conduct a rough estimation of it. Experimental simulations demonstrate the efficiency of the proposed approaches.

Economic Feasibility of Wireless Sensor Network-Based Service Provision in a Duopoly Setting with a Monopolist Operator.

PubMed

Sanchis-Cano, Angel; Romero, Julián; Sacoto-Cabrera, Erwin J; Guijarro, Luis

2017-11-25

We analyze the feasibility of providing Wireless Sensor Network-data-based services in an Internet of Things scenario from an economical point of view. The scenario has two competing service providers with their own private sensor networks, a network operator and final users. The scenario is analyzed as two games using game theory. In the first game, sensors decide to subscribe or not to the network operator to upload the collected sensing-data, based on a utility function related to the mean service time and the price charged by the operator. In the second game, users decide to subscribe or not to the sensor-data-based service of the service providers based on a Logit discrete choice model related to the quality of the data collected and the subscription price. The sinks and users subscription stages are analyzed using population games and discrete choice models, while network operator and service providers pricing stages are analyzed using optimization and Nash equilibrium concepts respectively. The model is shown feasible from an economic point of view for all the actors if there are enough interested final users and opens the possibility of developing more efficient models with different types of services.

Evaluation of multi-resolution satellite sensors for assessing water quality and bottom depth of Lake Garda.

PubMed

Giardino, Claudia; Bresciani, Mariano; Cazzaniga, Ilaria; Schenk, Karin; Rieger, Patrizia; Braga, Federica; Matta, Erica; Brando, Vittorio E

2014-12-15

In this study we evaluate the capabilities of three satellite sensors for assessing water composition and bottom depth in Lake Garda, Italy. A consistent physics-based processing chain was applied to Moderate Resolution Imaging Spectroradiometer (MODIS), Landsat-8 Operational Land Imager (OLI) and RapidEye. Images gathered on 10 June 2014 were corrected for the atmospheric effects with the 6SV code. The computed remote sensing reflectance (Rrs) from MODIS and OLI were converted into water quality parameters by adopting a spectral inversion procedure based on a bio-optical model calibrated with optical properties of the lake. The same spectral inversion procedure was applied to RapidEye and to OLI data to map bottom depth. In situ measurements of Rrs and of concentrations of water quality parameters collected in five locations were used to evaluate the models. The bottom depth maps from OLI and RapidEye showed similar gradients up to 7 m (r = 0.72). The results indicate that: (1) the spatial and radiometric resolutions of OLI enabled mapping water constituents and bottom properties; (2) MODIS was appropriate for assessing water quality in the pelagic areas at a coarser spatial resolution; and (3) RapidEye had the capability to retrieve bottom depth at high spatial resolution. Future work should evaluate the performance of the three sensors in different bio-optical conditions.

Lightweight, Room-Temperature CO2 Gas Sensor Based on Rare-Earth Metal-Free Composites-An Impedance Study.

PubMed

Willa, Christoph; Schmid, Alexander; Briand, Danick; Yuan, Jiayin; Koziej, Dorota

2017-08-02

We report a light, flexible, and low-power poly(ionic liquid)/alumina composite CO 2 sensor. We monitor the direct-current resistance changes as a function of CO 2 concentration and relative humidity and demonstrate fast and reversible sensing kinetics. Moreover, on the basis of the alternating-current impedance measurements we propose a sensing mechanism related to proton conduction and gas diffusion. The findings presented herein will promote the development of organic/inorganic composite CO 2 gas sensors. In the future, such sensors will be useful for numerous practical applications ranging from indoor air quality control to the monitoring of manufacturing processes.

Using a Fuzzy Light Sensor to Improve the Efficiency of Solar Panels

NASA Astrophysics Data System (ADS)

Suryono; Suseno, Jatmiko Endro; Sulistiati, Ainie Khuriati Riza; Prahara, Tahan

2018-02-01

Solar panel efficiency can be increased by improving the quality of photovoltaic material, the effectiveness of electronic circuit, and the light source tracking model. This research is aimed at improving the quality of solar panels by tracking light source using a fuzzy logic sensor. A fuzzy light sensor property is obtained from two LDR (light dependent resistor) light sensors installed in parallel to each other and is given a light separator in between them. Both sensors are mounted on a solar panel. Sensor output is acquired using a 12 bit ADC from an ATSAM3XE microcontroller and is then sent to a computer using WIFI radio. A PID (Proportional-Integral-Derivative) control algorithm is used to manage the position of the solar panel in line with the input given by the fuzzy light sensor. This control mechanism works based on the margin of fuzzy membership from both sensors that is used to move a motor DC that in turn moves the solar panel. Experimental results show a characteristically symmetrical fuzzy membership of both sensors with a reflected correlation of R=0.9981 after gains from both sensors are arranged with a program. Upon being tested in the field, this system was capable of improving the performance of solar panels in gaining power compared to their original fixed position. The discrepancy was evident when the angle of incoming sunlight approached both 0° and 180°. Further calculations of data acquired by the fuzzy light sensor show increased solar panel power efficiency by up to 5.6%.

Onboard TDI stage estimation and calibration using SNR analysis

NASA Astrophysics Data System (ADS)

Haghshenas, Javad

2017-09-01

Electro-Optical design of a push-broom space camera for a Low Earth Orbit (LEO) remote sensing satellite is performed based on the noise analysis of TDI sensors for very high GSDs and low light level missions. It is well demonstrated that the CCD TDI mode of operation provides increased photosensitivity relative to a linear CCD array, without the sacrifice of spatial resolution. However, for satellite imaging, in order to utilize the advantages which the TDI mode of operation offers, attention should be given to the parameters which affect the image quality of TDI sensors such as jitters, vibrations, noises and etc. A predefined TDI stages may not properly satisfy image quality requirement of the satellite camera. Furthermore, in order to use the whole dynamic range of the sensor, imager must be capable to set the TDI stages in every shots based on the affecting parameters. This paper deals with the optimal estimation and setting the stages based on tradeoffs among MTF, noises and SNR. On-board SNR estimation is simulated using the atmosphere analysis based on the MODTRAN algorithm in PcModWin software. According to the noises models, we have proposed a formulation to estimate TDI stages in such a way to satisfy the system SNR requirement. On the other hand, MTF requirement must be satisfy in the same manner. A proper combination of both parameters will guaranty the full dynamic range usage along with the high SNR and image quality.

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

Humayun, Md Tanim; Divan, Ralu; Liu, Yuzi

Chemoresistive sensors based on multiwalled carbon nanotubes (MWCNTs) functionalized with SnO 2 nanocrystals (NCs) have great potential for detecting trace gases at low concentrations (single ppm levels) at room temperature, because the SnO 2 nanocrystals act as active sites for the chemisorption of gas molecules, and carbon nanotubes (CNTs) act as an excellent current carrying platform, allowing the adsorption of gas on SnO 2 to modulate the resistance of the CNTs. However, uniform conjugation of SnO 2 NCs with MWCNTs is challenging. An effective atomic layer deposition based approach to functionalize the surface of MWCNTs with SnO 2 NCs, resultingmore » in a novel CH 4 sensor with 10 ppm sensitivity, is presented in this paper. Scanning electron microscopy, transmission electron microscopy (TEM), energy dispersive x-ray spectroscopy, and Raman spectroscopy were implemented to study the morphology, elemental composition, and the crystal quality of SnO 2 functionalized MWCNTs. High resolution TEM images showed that the crystal quality of the functionalizing SnO 2 NCs was of high quality with clear lattice fringes and the dimension almost three times smaller than shown thus far in literature. A lift-off based photolithography technique comprising bilayer photoresists was optimized to fabricate SnO 2 functionalized MWCNTs-based chemoresistor sensor, which at room temperature can reliably sense below 10 ppm of CH4 in air. Such low level gas sensitivity, with significant reversible relative resistance change, is believed to be the direct result of the successful functionalization of the MWCNT surface by SnO 2 NCs.« less

FPGA-Based Fused Smart-Sensor for Tool-Wear Area Quantitative Estimation in CNC Machine Inserts

PubMed Central

Trejo-Hernandez, Miguel; Osornio-Rios, Roque Alfredo; de Jesus Romero-Troncoso, Rene; Rodriguez-Donate, Carlos; Dominguez-Gonzalez, Aurelio; Herrera-Ruiz, Gilberto

2010-01-01

Manufacturing processes are of great relevance nowadays, when there is a constant claim for better productivity with high quality at low cost. The contribution of this work is the development of a fused smart-sensor, based on FPGA to improve the online quantitative estimation of flank-wear area in CNC machine inserts from the information provided by two primary sensors: the monitoring current output of a servoamplifier, and a 3-axis accelerometer. Results from experimentation show that the fusion of both parameters makes it possible to obtain three times better accuracy when compared with the accuracy obtained from current and vibration signals, individually used. PMID:22319304

River water quality analysis via headspace detection of volatile organic compounds

NASA Astrophysics Data System (ADS)

Tang, Johnny Jock Lee; Nishi, Phyllis Jacqueline; Chong, Gabriel Eng Wee; Wong, Martin Gideon; Chua, Hong Siang; Persaud, Krishna; Ng, Sing Muk

2017-03-01

Human civilization has intensified the interaction between the community and the environment. This increases the threat on the environm ent for being over exploited and contaminated with m anmade products and synthetic chemicals. Of all, clean water is one of the resources that can be easily contaminated since it is a universal solvent and of high mobility. This work reports the development and optimization of a water quality monitoring system based on metal oxide sensors. The system is intended to a ssist the detection of volatile organic compounds (VOCs) present in water sources online and onsite. The sampling mechanism was based on contactless mode, where headspace partial pressure of the VOCs formed above the water body in a close chamber was drawn for detection at the sensor platform. Pure toluene was used as standard to represent the broad spectrum of VOCs, and the sensor dynamic range was achieved from 1-1000 ppb. Several sensing parameters such as sampling time, headspace volume, and sensor recovery were s tudied and optimized. Besides direct detection of VOC contaminants in the water, the work has also been extended to detect VOCs produced by microbial communities and to c orrelate the size of the communities with the reading of V OCs recorded. This can serve to give b etter indication of water quality, not only on the conce ntration of VOCs c ontamination from chemicals, but also the content of microbes, which some can have severe effect on human health.

Carbon nanotube sensors integrated inside a microfluidic channel for water quality monitoring

NASA Astrophysics Data System (ADS)

Liu, Yu; Li, Xinghui; Dokmeci, Mehmet R.; Wang, Ming L.

2011-04-01

Single-walled carbon nanotubes (SWNTs) with their unique electrical properties and large surface area are remarkable materials for detecting low concentration of toxic and hazardous chemicals (both from the gaseous and liquid phases). Ionic adsorbates in water will attach on to SWNTs and drastically alter their electrical properties. Several SWNTs based pH and chemical sensors have been demonstrated. However, most of them require external components to test and analyze the response of SWNTs to ions inside the liquid samples. Here, we report a water quality monitoring sensor composed of SWNTs integrated inside microfluidic channels and on-chip testing components with a wireless transmission board. To detect multiple analytes in water requires the functionalization of SWNTs with different chemistries. In addition, microfluidic channels are used to guide liquid samples to individual nanotube sensors in an efficient manner. Furthermore, the microfluidic system enables sample mixing and separation before testing. To realize the nanosensors, first microelectrodes were fabricated on an oxidized silicon substrate. Next, PDMS micro channels were fabricated and bonded on the substrate. These channels can be incorporated with a microfluidic system which can be designed to manipulate different analytes for specific molecule detection. Low temperature, solution based Dielectrophoretic (DEP) assembly was conducted inside this microfluidic system which successfully bridged SWNTs between the microelectrodes. The SWNTs sensors were next characterized with different pH buffer solutions. The resistance of SWNTs had a linearly increase as the pH values ranged from 5 to 8. The nanosensor incorporated within the microfluidic system is a versatile platform and can be utilized to detect numerous water pollutants, including toxic organics and microorganisms down to low concentrations. On-chip processing and wireless transmission enables the realization of a full autonomous system for real time monitoring of water quality.

Motion Artifact Quantification and Sensor Fusion for Unobtrusive Health Monitoring.

PubMed

Hoog Antink, Christoph; Schulz, Florian; Leonhardt, Steffen; Walter, Marian

2017-12-25

Sensors integrated into objects of everyday life potentially allow unobtrusive health monitoring at home. However, since the coupling of sensors and subject is not as well-defined as compared to a clinical setting, the signal quality is much more variable and can be disturbed significantly by motion artifacts. One way of tackling this challenge is the combined evaluation of multiple channels via sensor fusion. For robust and accurate sensor fusion, analyzing the influence of motion on different modalities is crucial. In this work, a multimodal sensor setup integrated into an armchair is presented that combines capacitively coupled electrocardiography, reflective photoplethysmography, two high-frequency impedance sensors and two types of ballistocardiography sensors. To quantify motion artifacts, a motion protocol performed by healthy volunteers is recorded with a motion capture system, and reference sensors perform cardiorespiratory monitoring. The shape-based signal-to-noise ratio SNR S is introduced and used to quantify the effect on motion on different sensing modalities. Based on this analysis, an optimal combination of sensors and fusion methodology is developed and evaluated. Using the proposed approach, beat-to-beat heart-rate is estimated with a coverage of 99.5% and a mean absolute error of 7.9 ms on 425 min of data from seven volunteers in a proof-of-concept measurement scenario.

Evaluation of the Sensor Data Record from the Nadir Instruments of the Ozone Mapping Profiler Suite (OMPS)

NASA Technical Reports Server (NTRS)

Wu, Xiangqian; Liu, Quanhua; Zeng, Jian; Grotenhuis, Michael; Qian, Haifeng; Caponi, Maria; Flynn, Larry; Jaross, Glen; Sen, Bhaswar; Buss, Richard H., Jr.;

Development of inferential sensors for real-time quality control of water-level data for the Everglades Depth Estimation Network

USGS Publications Warehouse

Daamen, Ruby C.; Edwin A. Roehl, Jr.; Conrads, Paul

2010-01-01

A technology often used for industrial applications is “inferential sensor.” Rather than installing a redundant sensor to measure a process, such as an additional waterlevel gage, an inferential sensor, or virtual sensor, is developed that estimates the processes measured by the physical sensor. The advantage of an inferential sensor is that it provides a redundant signal to the sensor in the field but without exposure to environmental threats. In the event that a gage does malfunction, the inferential sensor provides an estimate for the period of missing data. The inferential sensor also can be used in the quality assurance and quality control of the data. Inferential sensors for gages in the EDEN network are currently (2010) under development. The inferential sensors will be automated so that the real-time EDEN data will continuously be compared to the inferential sensor signal and digital reports of the status of the real-time data will be sent periodically to the appropriate support personnel. The development and application of inferential sensors is easily transferable to other real-time hydrologic monitoring networks.

Developing Information Services and Tools to Access and Evaluate Data Quality in Global Satellite-based Precipitation Products

NASA Astrophysics Data System (ADS)

Liu, Z.; Shie, C. L.; Meyer, D. J.

2017-12-01

Global satellite-based precipitation products have been widely used in research and applications around the world. Compared to ground-based observations, satellite-based measurements provide precipitation data on a global scale, especially in remote continents and over oceans. Over the years, satellite-based precipitation products have evolved from single sensor and single algorithm to multi-sensors and multi-algorithms. As a result, many satellite-based precipitation products have been enhanced such as spatial and temporal coverages. With inclusion of ground-based measurements, biases of satellite-based precipitation products have been significantly reduced. However, data quality issues still exist and can be caused by many factors such as observations, satellite platform anomaly, algorithms, production, calibration, validation, data services, etc. The NASA Goddard Earth Sciences (GES) Data and Information Services Center (DISC) is home to NASA global precipitation product archives including the Tropical Rainfall Measuring Mission (TRMM), the Global Precipitation Measurement (GPM), as well as other global and regional precipitation products. Precipitation is one of the top downloaded and accessed parameters in the GES DISC data archive. Meanwhile, users want to easily locate and obtain data quality information at regional and global scales to better understand how precipitation products perform and how reliable they are. As data service providers, it is necessary to provide an easy access to data quality information, however, such information normally is not available, and when it is available, it is not in one place and difficult to locate. In this presentation, we will present challenges and activities at the GES DISC to address precipitation data quality issues.

Optimal Power Control in Wireless Powered Sensor Networks: A Dynamic Game-Based Approach

PubMed Central

Xu, Haitao; Guo, Chao; Zhang, Long

2017-01-01

In wireless powered sensor networks (WPSN), it is essential to research uplink transmit power control in order to achieve throughput performance balancing and energy scheduling. Each sensor should have an optimal transmit power level for revenue maximization. In this paper, we discuss a dynamic game-based algorithm for optimal power control in WPSN. The main idea is to use the non-cooperative differential game to control the uplink transmit power of wireless sensors in WPSN, to extend their working hours and to meet QoS (Quality of Services) requirements. Subsequently, the Nash equilibrium solutions are obtained through Bellman dynamic programming. At the same time, an uplink power control algorithm is proposed in a distributed manner. Through numerical simulations, we demonstrate that our algorithm can obtain optimal power control and reach convergence for an infinite horizon. PMID:28282945

Hand-held Raman sensor head for in-situ characterization of meat quality applying a microsystem 671 nm diode laser

NASA Astrophysics Data System (ADS)

Schmidt, Heinar; Sowoidnich, Kay; Maiwald, Martin; Sumpf, Bernd; Kronfeldt, Heinz-Detlef

2009-05-01

A hand-held Raman sensor head was developed for the in-situ characterization of meat quality. As light source, a microsystem based external cavity diode laser module (ECDL) emitting at 671 nm was integrated in the sensor head and attached to a miniaturized optical bench which contains lens optics for excitation and signal collection as well as a Raman filter stage for Rayleigh rejection. The signal is transported with an optical fiber to the detection unit which was in the initial phase a laboratory spectrometer with CCD detector. All elements of the ECDL are aligned on a micro optical bench with 13 x 4 mm2 footprint. The wavelength stability is provided by a reflection Bragg grating and the laser has an optical power of up to 200 mW. However, for the Raman measurements of meat only 35 mW are needed to obtain Raman spectra within 1 - 5 seconds. Short measuring times are essential for the hand-held device. The laser and the sensor head are characterized in terms of stability and performance for in-situ Raman investigations. The function is demonstrated in a series of measurements with raw and packaged pork meat as samples. The suitability of the Raman sensor head for the quality control of meat and other products will be discussed.

Optical techniques for the determination of nitrate in environmental waters: Guidelines for instrument selection, operation, deployment, maintenance, quality assurance, and data reporting

USGS Publications Warehouse

Pellerin, Brian A.; Bergamaschi, Brian A.; Downing, Bryan D.; Saraceno, John Franco; Garrett, Jessica D.; Olsen, Lisa D.

2013-01-01

The recent commercial availability of in situ optical sensors, together with new techniques for data collection and analysis, provides the opportunity to monitor a wide range of water-quality constituents on time scales in which environmental conditions actually change. Of particular interest is the application of ultraviolet (UV) photometers for in situ determination of nitrate concentrations in rivers and streams. The variety of UV nitrate sensors currently available differ in several important ways related to instrument design that affect the accuracy of their nitrate concentration measurements in different types of natural waters. This report provides information about selection and use of UV nitrate sensors by the U.S. Geological Survey to facilitate the collection of high-quality data across studies, sites, and instrument types. For those in need of technical background and information about sensor selection, this report addresses the operating principles, key features and sensor design, sensor characterization techniques and typical interferences, and approaches for sensor deployment. For those needing information about maintaining sensor performance in the field, key sections in this report address maintenance and calibration protocols, quality-assurance techniques, and data formats and reporting. Although the focus of this report is UV nitrate sensors, many of the principles can be applied to other in situ optical sensors for water-quality studies.

High-speed three-dimensional measurements with a fringe projection-based optical sensor

NASA Astrophysics Data System (ADS)

Bräuer-Burchardt, Christian; Breitbarth, Andreas; Kühmstedt, Peter; Notni, Gunther

2014-11-01

An optical three-dimensional (3-D) sensor based on a fringe projection technique that realizes the acquisition of the surface geometry of small objects was developed for highly resolved and ultrafast measurements. It realizes a data acquisition rate up to 60 high-resolution 3-D datasets per second. The high measurement velocity was achieved by consequent fringe code reduction and parallel data processing. The reduction of the length of the fringe image sequence was obtained by omission of the Gray code sequence using the geometric restrictions of the measurement objects and the geometric constraints of the sensor arrangement. The sensor covers three different measurement fields between 20 mm×20 mm and 40 mm×40 mm with a spatial resolution between 10 and 20 μm, respectively. In order to obtain a robust and fast recalibration of the sensor after change of the measurement field, a calibration procedure based on single shot analysis of a special test object was applied which works with low effort and time. The sensor may be used, e.g., for quality inspection of conductor boards or plugs in real-time industrial applications.

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

NASA Astrophysics Data System (ADS)

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

2015-05-01

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

A Sensor-Based Method for Diagnostics of Machine Tool Linear Axes.

PubMed

Vogl, Gregory W; Weiss, Brian A; Donmez, M Alkan

2015-01-01

A linear axis is a vital subsystem of machine tools, which are vital systems within many manufacturing operations. When installed and operating within a manufacturing facility, a machine tool needs to stay in good condition for parts production. All machine tools degrade during operations, yet knowledge of that degradation is illusive; specifically, accurately detecting degradation of linear axes is a manual and time-consuming process. Thus, manufacturers need automated and efficient methods to diagnose the condition of their machine tool linear axes without disruptions to production. The Prognostics and Health Management for Smart Manufacturing Systems (PHM4SMS) project at the National Institute of Standards and Technology (NIST) developed a sensor-based method to quickly estimate the performance degradation of linear axes. The multi-sensor-based method uses data collected from a 'sensor box' to identify changes in linear and angular errors due to axis degradation; the sensor box contains inclinometers, accelerometers, and rate gyroscopes to capture this data. The sensors are expected to be cost effective with respect to savings in production losses and scrapped parts for a machine tool. Numerical simulations, based on sensor bandwidth and noise specifications, show that changes in straightness and angular errors could be known with acceptable test uncertainty ratios. If a sensor box resides on a machine tool and data is collected periodically, then the degradation of the linear axes can be determined and used for diagnostics and prognostics to help optimize maintenance, production schedules, and ultimately part quality.

A Sensor-Based Method for Diagnostics of Machine Tool Linear Axes

PubMed Central

Vogl, Gregory W.; Weiss, Brian A.; Donmez, M. Alkan

2017-01-01

A linear axis is a vital subsystem of machine tools, which are vital systems within many manufacturing operations. When installed and operating within a manufacturing facility, a machine tool needs to stay in good condition for parts production. All machine tools degrade during operations, yet knowledge of that degradation is illusive; specifically, accurately detecting degradation of linear axes is a manual and time-consuming process. Thus, manufacturers need automated and efficient methods to diagnose the condition of their machine tool linear axes without disruptions to production. The Prognostics and Health Management for Smart Manufacturing Systems (PHM4SMS) project at the National Institute of Standards and Technology (NIST) developed a sensor-based method to quickly estimate the performance degradation of linear axes. The multi-sensor-based method uses data collected from a ‘sensor box’ to identify changes in linear and angular errors due to axis degradation; the sensor box contains inclinometers, accelerometers, and rate gyroscopes to capture this data. The sensors are expected to be cost effective with respect to savings in production losses and scrapped parts for a machine tool. Numerical simulations, based on sensor bandwidth and noise specifications, show that changes in straightness and angular errors could be known with acceptable test uncertainty ratios. If a sensor box resides on a machine tool and data is collected periodically, then the degradation of the linear axes can be determined and used for diagnostics and prognostics to help optimize maintenance, production schedules, and ultimately part quality. PMID:28691039

Scales of heterogeneity of water quality in rivers: Insights from high resolution maps based on integrated geospatial, sensor and ROV technologies

EPA Science Inventory

While the spatial heterogeneity of many aquatic ecosystems is acknowledged, rivers are often mistakenly described as homogenous and well-mixed. The collection and visualization of attributes like water quality is key to our perception and management of these ecosystems. The ass...

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...

Triaxial fiber optic magnetic field sensor for MRI applications

NASA Astrophysics Data System (ADS)

Filograno, Massimo L.; Pisco, Marco; Catalano, Angelo; Forte, Ernesto; Aiello, Marco; Soricelli, Andrea; Davino, Daniele; Visone, Ciro; Cutolo, Antonello; Cusano, Andrea

2016-05-01

In this paper, we report a fiber-optic triaxial magnetic field sensor, based on Fiber Bragg Gratings (FBGs) integrated with giant magnetostrictive material, the Terfenol-D. The realized sensor has been designed and engineered for Magnetic Resonance Imaging (MRI) applications. A full magneto-optical characterization of the triaxial sensing probe has been carried out, providing the complex relationship among the FBGs wavelength shift and the applied magnetostatic field vector. Finally, the developed fiber optic sensors have been arranged in a sensor network composed of 20 triaxial sensors for mapping the magnetic field distribution in a MRI-room at a diagnostic center in Naples (SDN), equipped with Positron emission tomography/magnetic resonance (PET/MR) instrumentation. Experimental results reveal that the proposed sensor network can be efficiently used in MRI centers for performing quality assurance tests, paving the way for novel integrated tools to measure the magnetic dose accumulated day by day by MRI operators.

Bio-optical sensor for brain activity measurement based on whispering gallery modes

NASA Astrophysics Data System (ADS)

Ali, Amir R.; Massoud, Yasmin M.

2017-05-01

In this paper, a high-resolution bio-optical sensor is developed for brain activity measurement. The aim is to develop an optical sensor with enough sensitivity to detect small electric field perturbations caused by neuronal action potential. The sensing element is a polymeric dielectric micro-resonator fabricated in a spherical shape with a few hundred microns in diameter. They are made of optical quality polymers that are soft which make them mechanically compatible with tissue. The sensors are attached to or embedded in optical fibers which serve as input/output conduits for the sensors. Hundreds or even thousands of spheres can be attached to a single fiber to detect and transmit signals at different locations. The high quality factor for the optical resonator makes it significantly used in such bio-medical applications. The sensing phenomenon is based on whispering gallery modes (WGM) shifts of the optical sensor. To mimic the brain signals, the spherical resonator is immersed in a homogeneous electrical field that is created by applying potential difference across two metallic plates. One of the plates has a variable voltage while the volt on the other plate kept fixed. Any small perturbations of the potential difference (voltage) lead to change in the electric field intensity. In turn the sensor morphology will be affected due to the change in the electrostriction force acting on it causing change in its WGM. By tracking these WGM shift on the transmission spectrum, the induced potential difference (voltage change) could be measured. Results of a mathematical model simulation agree well with the preliminary experiments. Also, the results show that the brain activity could be measured using this principle.

Depletion-of-Battery Attack: Specificity, Modelling and Analysis.

PubMed

Shakhov, Vladimir; Koo, Insoo

2018-06-06

The emerging Internet of Things (IoT) has great potential; however, the societal costs of the IoT can outweigh its benefits. To unlock IoT potential, there needs to be improvement in the security of IoT applications. There are several standardization initiatives for sensor networks, which eventually converge with the Internet of Things. As sensor-based applications are deployed, security emerges as an essential requirement. One of the critical issues of wireless sensor technology is limited sensor resources, including sensor batteries. This creates a vulnerability to battery-exhausting attacks. Rapid exhaustion of sensor battery power is not only explained by intrusions, but can also be due to random failure of embedded sensor protocols. Thus, most wireless sensor applications, without tools to defend against rash battery exhausting, would be unable to function during prescribed times. In this paper, we consider a special type of threat, in which the harm is malicious depletion of sensor battery power. In contrast to the traditional denial-of-service attack, quality of service under the considered attack is not necessarily degraded. Moreover, the quality of service can increase up to the moment of the sensor set crashes. We argue that this is a distinguishing type of attack. Hence, the application of a traditional defense mechanism against this threat is not always possible. Therefore, effective methods should be developed to counter the threat. We first discuss the feasibility of rash depletion of battery power. Next, we propose a model for evaluation of energy consumption when under attack. Finally, a technique to counter the attack is discussed.

Dynamic Reconfiguration of a RGBD Sensor Based on QoS and QoC Requirements in Distributed Systems.

PubMed

Munera, Eduardo; Poza-Lujan, Jose-Luis; Posadas-Yagüe, Juan-Luis; Simó-Ten, José-Enrique; Noguera, Juan Fco Blanes

2015-07-24

The inclusion of embedded sensors into a networked system provides useful information for many applications. A Distributed Control System (DCS) is one of the clearest examples where processing and communications are constrained by the client's requirements and the capacity of the system. An embedded sensor with advanced processing and communications capabilities supplies high level information, abstracting from the data acquisition process and objects recognition mechanisms. The implementation of an embedded sensor/actuator as a Smart Resource permits clients to access sensor information through distributed network services. Smart resources can offer sensor services as well as computing, communications and peripheral access by implementing a self-aware based adaptation mechanism which adapts the execution profile to the context. On the other hand, information integrity must be ensured when computing processes are dynamically adapted. Therefore, the processing must be adapted to perform tasks in a certain lapse of time but always ensuring a minimum process quality. In the same way, communications must try to reduce the data traffic without excluding relevant information. The main objective of the paper is to present a dynamic configuration mechanism to adapt the sensor processing and communication to the client's requirements in the DCS. This paper describes an implementation of a smart resource based on a Red, Green, Blue, and Depth (RGBD) sensor in order to test the dynamic configuration mechanism presented.

Effective Fingerprint Quality Estimation for Diverse Capture Sensors

PubMed Central

Xie, Shan Juan; Yoon, Sook; Shin, Jinwook; Park, Dong Sun

2010-01-01

Recognizing the quality of fingerprints in advance can be beneficial for improving the performance of fingerprint recognition systems. The representative features to assess the quality of fingerprint images from different types of capture sensors are known to vary. In this paper, an effective quality estimation system that can be adapted for different types of capture sensors is designed by modifying and combining a set of features including orientation certainty, local orientation quality and consistency. The proposed system extracts basic features, and generates next level features which are applicable for various types of capture sensors. The system then uses the Support Vector Machine (SVM) classifier to determine whether or not an image should be accepted as input to the recognition system. The experimental results show that the proposed method can perform better than previous methods in terms of accuracy. In the meanwhile, the proposed method has an ability to eliminate residue images from the optical and capacitive sensors, and the coarse images from thermal sensors. PMID:22163632

Differentiation Between Organic and Non-Organic Apples Using Diffraction Grating and Image Processing-A Cost-Effective Approach.

PubMed

Jiang, Nanfeng; Song, Weiran; Wang, Hui; Guo, Gongde; Liu, Yuanyuan

2018-05-23

As the expectation for higher quality of life increases, consumers have higher demands for quality food. Food authentication is the technical means of ensuring food is what it says it is. A popular approach to food authentication is based on spectroscopy, which has been widely used for identifying and quantifying the chemical components of an object. This approach is non-destructive and effective but expensive. This paper presents a computer vision-based sensor system for food authentication, i.e., differentiating organic from non-organic apples. This sensor system consists of low-cost hardware and pattern recognition software. We use a flashlight to illuminate apples and capture their images through a diffraction grating. These diffraction images are then converted into a data matrix for classification by pattern recognition algorithms, including k -nearest neighbors ( k -NN), support vector machine (SVM) and three partial least squares discriminant analysis (PLS-DA)- based methods. We carry out experiments on a reasonable collection of apple samples and employ a proper pre-processing, resulting in a highest classification accuracy of 94%. Our studies conclude that this sensor system has the potential to provide a viable solution to empower consumers in food authentication.

A black carbon air quality network

NASA Astrophysics Data System (ADS)

Kirchstetter, T.; Caubel, J.; Cados, T.; Preble, C.; Rosen, A.

2016-12-01

We developed a portable, power efficient black carbon sensor for deployment in an air quality network in West Oakland, California. West Oakland is a San Francisco Bay Area residential/industrial community adjacent to regional port and rail yard facilities, and is 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 are collaborating with community members to build and operate a 100-sensor black carbon measurement network for a period of several months. The sensor employs the filter-based light transmission method to measure black carbon. Each sensor node in the network transmits data hourly via SMS text messages. Cost, power consumption, and performance are considered in choosing components (e.g., pump) and operating conditions (e.g., sample flow rate). In field evaluation trials over several weeks at three monitoring locations, the sensor nodes provided black carbon concentrations comparable to commercial instruments and ran autonomously for a week before sample filters and rechargeable batteries needed to be replaced. Buildup to the 100-sensor network is taking place during Fall 2016 and will overlap with other ongoing air monitoring projects and monitoring platforms in West Oakland. Sensors will be placed along commercial corridors, adjacent to freeways, upwind of and within the Port, and throughout the residential community. Spatial and temporal black carbon concentration patterns will help characterize pollution sources and demonstrate the value of sensing networks for characterizing intra-urban air pollution concentrations and exposure to air pollution.

Autonomous Quality Control of Joint Orientation Measured with Inertial Sensors.

PubMed

Lebel, Karina; Boissy, Patrick; Nguyen, Hung; Duval, Christian

2016-07-05

Clinical mobility assessment is traditionally performed in laboratories using complex and expensive equipment. The low accessibility to such equipment, combined with the emerging trend to assess mobility in a free-living environment, creates a need for body-worn sensors (e.g., inertial measurement units-IMUs) that are capable of measuring the complexity in motor performance using meaningful measurements, such as joint orientation. However, accuracy of joint orientation estimates using IMUs may be affected by environment, the joint tracked, type of motion performed and velocity. This study investigates a quality control (QC) process to assess the quality of orientation data based on features extracted from the raw inertial sensors' signals. Joint orientation (trunk, hip, knee, ankle) of twenty participants was acquired by an optical motion capture system and IMUs during a variety of tasks (sit, sit-to-stand transition, walking, turning) performed under varying conditions (speed, environment). An artificial neural network was used to classify good and bad sequences of joint orientation with a sensitivity and a specificity above 83%. This study confirms the possibility to perform QC on IMU joint orientation data based on raw signal features. This innovative QC approach may be of particular interest in a big data context, such as for remote-monitoring of patients' mobility.

Considerations for blending data from various sensors

USGS Publications Warehouse

Bauer, Brian P.; Barringer, Anthony R.

1980-01-01

A project is being proposed at the EROS Data Center to blend the information from sensors aboard various satellites. The problems of, and considerations for, blending data from several satellite-borne sensors are discussed. System descriptions of the sensors aboard the HCMM, TIROS-N, GOES-D, Landsat 3, Landsat D, Seasat, SPOT, Stereosat, and NOSS satellites, and the quantity, quality, image dimensions, and availability of these data are summaries to define attributes of a multi-sensor satellite data base. Unique configurations of equipment, storage, media, and specialized hardware to meet the data system requirement are described as well as archival media and improved sensors that will be on-line within the next 5 years. Definitions and rigor required for blending various sensor data are given. Problems of merging data from the same sensor (intrasensor comparison) and from different sensors (intersensor comparison), the characteristics and advantages of cross-calibration of data, and integration of data into a product matrix field are addressed. Data processing considerations as affected by formation, resolution, and problems of merging large data sets, and organization of data bases for blending data are presented. Examples utilizing GOES and Landsat data are presented to demonstrate techniques of data blending, and recommendations for future implementation of a set of standard scenes and their characteristics necessary for optimal data blending are discussed.

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

NASA Astrophysics Data System (ADS)

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

2011-08-01

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

High-resolution dynamic pressure sensor array based on piezo-phototronic effect tuned photoluminescence imaging.

PubMed

Peng, Mingzeng; Li, Zhou; Liu, Caihong; Zheng, Qiang; Shi, Xieqing; Song, Ming; Zhang, Yang; Du, Shiyu; Zhai, Junyi; Wang, Zhong Lin

2015-03-24

A high-resolution dynamic tactile/pressure display is indispensable to the comprehensive perception of force/mechanical stimulations such as electronic skin, biomechanical imaging/analysis, or personalized signatures. Here, we present a dynamic pressure sensor array based on pressure/strain tuned photoluminescence imaging without the need for electricity. Each sensor is a nanopillar that consists of InGaN/GaN multiple quantum wells. Its photoluminescence intensity can be modulated dramatically and linearly by small strain (0-0.15%) owing to the piezo-phototronic effect. The sensor array has a high pixel density of 6350 dpi and exceptional small standard deviation of photoluminescence. High-quality tactile/pressure sensing distribution can be real-time recorded by parallel photoluminescence imaging without any cross-talk. The sensor array can be inexpensively fabricated over large areas by semiconductor product lines. The proposed dynamic all-optical pressure imaging with excellent resolution, high sensitivity, good uniformity, and ultrafast response time offers a suitable way for smart sensing, micro/nano-opto-electromechanical systems.

Ultra-low power wireless sensing for long-term structural health monitoring

NASA Astrophysics Data System (ADS)

Bilbao, Argenis; Hoover, Davis; Rice, Jennifer; Chapman, Jamie

2011-04-01

Researchers have made significant progress in recent years towards realizing long-term structural health monitoring (SHM) utilizing wireless smart sensor networks (WSSNs). These efforts have focused on improving the performance and robustness of such networks to achieve high quality data acquisition and in-network processing. One of the primary challenges still facing the use of smart sensors for long-term monitoring deployments is their limited power resources. Periodically accessing the sensor nodes to change batteries is not feasible or economical in many deployment cases. While energy harvesting techniques show promise for prolonging unattended network life, low-power design and operation are still critically important. This research presents a new, fully integrated ultra-low power wireless smart sensor node and a flexible base station, both designed for long-term SHM applications. The power consumption of the sensor nodes and base station has been minimized through careful hardware selection and the implementation of power-aware network software, without sacrificing flexibility and functionality.

Optimized ratiometric calcium sensors for functional in vivo imaging of neurons and T lymphocytes.

PubMed

Thestrup, Thomas; Litzlbauer, Julia; Bartholomäus, Ingo; Mues, Marsilius; Russo, Luigi; Dana, Hod; Kovalchuk, Yuri; Liang, Yajie; Kalamakis, Georgios; Laukat, Yvonne; Becker, Stefan; Witte, Gregor; Geiger, Anselm; Allen, Taylor; Rome, Lawrence C; Chen, Tsai-Wen; Kim, Douglas S; Garaschuk, Olga; Griesinger, Christian; Griesbeck, Oliver

2014-02-01

The quality of genetically encoded calcium indicators (GECIs) has improved dramatically in recent years, but high-performing ratiometric indicators are still rare. Here we describe a series of fluorescence resonance energy transfer (FRET)-based calcium biosensors with a reduced number of calcium binding sites per sensor. These 'Twitch' sensors are based on the C-terminal domain of Opsanus troponin C. Their FRET responses were optimized by a large-scale functional screen in bacterial colonies, refined by a secondary screen in rat hippocampal neuron cultures. We tested the in vivo performance of the most sensitive variants in the brain and lymph nodes of mice. The sensitivity of the Twitch sensors matched that of synthetic calcium dyes and allowed visualization of tonic action potential firing in neurons and high resolution functional tracking of T lymphocytes. Given their ratiometric readout, their brightness, large dynamic range and linear response properties, Twitch sensors represent versatile tools for neuroscience and immunology.

Sensoring fusion data from the optic and acoustic emissions of electric arcs in the GMAW-S process for welding quality assessment.

PubMed

Alfaro, Sadek Crisóstomo Absi; Cayo, Eber Huanca

2012-01-01

The present study shows the relationship between welding quality and optical-acoustic emissions from electric arcs, during welding runs, in the GMAW-S process. Bead on plate welding tests was carried out with pre-set parameters chosen from manufacturing standards. During the welding runs interferences were induced on the welding path using paint, grease or gas faults. In each welding run arc voltage, welding current, infrared and acoustic emission values were acquired and parameters such as arc power, acoustic peaks rate and infrared radiation rate computed. Data fusion algorithms were developed by assessing known welding quality parameters from arc emissions. These algorithms have showed better responses when they are based on more than just one sensor. Finally, it was concluded that there is a close relation between arc emissions and quality in welding and it can be measured from arc emissions sensing and data fusion algorithms.

Toward developing long-life water quality sensors for the ISS using planar REDOX and conductivity sensors

NASA Technical Reports Server (NTRS)

Buehler, M. G.; Kuhlman, G. M.; Keymeulen, D.; Myung, N.; Kounaves, S. P.

2003-01-01

REDOX and conductivity sensors are metal electrodes that are used to detect ionic species in solution by measuring the electrochemical cell current as the voltage is scanned. This paper describes the construction of the sensors, the potentiostat electronics, the measurement methodology, and applications to water quality measurements.

An efficient genetic algorithm for maximum coverage deployment in wireless sensor networks.

PubMed

Yoon, Yourim; Kim, Yong-Hyuk

2013-10-01

Sensor networks have a lot of applications such as battlefield surveillance, environmental monitoring, and industrial diagnostics. Coverage is one of the most important performance metrics for sensor networks since it reflects how well a sensor field is monitored. In this paper, we introduce the maximum coverage deployment problem in wireless sensor networks and analyze the properties of the problem and its solution space. Random deployment is the simplest way to deploy sensor nodes but may cause unbalanced deployment and therefore, we need a more intelligent way for sensor deployment. We found that the phenotype space of the problem is a quotient space of the genotype space in a mathematical view. Based on this property, we propose an efficient genetic algorithm using a novel normalization method. A Monte Carlo method is adopted to design an efficient evaluation function, and its computation time is decreased without loss of solution quality using a method that starts from a small number of random samples and gradually increases the number for subsequent generations. The proposed genetic algorithms could be further improved by combining with a well-designed local search. The performance of the proposed genetic algorithm is shown by a comparative experimental study. When compared with random deployment and existing methods, our genetic algorithm was not only about twice faster, but also showed significant performance improvement in quality.

Direct laser writing of polymer micro-ring resonator ultrasonic sensors

NASA Astrophysics Data System (ADS)

Wei, Heming; Krishnaswamy, Sridhar

2017-04-01

With the development of photoacoustic technology in recent years, ultrasound-related sensors play a vital role in a number of areas ranging from scientific research to nondestructive testing. Compared with the traditional PZT transducer as ultrasonic sensors, novel ultrasonic sensors based on optical methods such as micro-ring resonators have gained increasing attention. The total internal reflection of the light along the cavity results in light propagating in microcavities as whispering gallery modes (WGMs), which are extremely sensitive to change in the radius and refractive index of the cavity induced by ultrasound strain field. In this work, we present a polymer optical micro-ring resonator based ultrasonic sensor fabricated by direct laser writing optical lithography. The design consists of a single micro-ring and a straight tapered waveguide that can be directly coupled by single mode fibers (SMFs). The design and fabrication of the printed polymer resonator have been optimized to provide broad bandwidth and high optical quality factor to ensure high detection sensitivity. The experiments demonstrate the potential of the polymer micro-ring resonator to works as a high-performance ultrasonic sensor.

Analysis on the Effect of Sensor Views in Image Reconstruction Produced by Optical Tomography System Using Charge-Coupled Device.

PubMed

Jamaludin, Juliza; Rahim, Ruzairi Abdul; Fazul Rahiman, Mohd Hafiz; Mohd Rohani, Jemmy

2018-04-01

Optical tomography (OPT) is a method to capture a cross-sectional image based on the data obtained by sensors, distributed around the periphery of the analyzed system. This system is based on the measurement of the final light attenuation or absorption of radiation after crossing the measured objects. The number of sensor views will affect the results of image reconstruction, where the high number of sensor views per projection will give a high image quality. This research presents an application of charge-coupled device linear sensor and laser diode in an OPT system. Experiments in detecting solid and transparent objects in crystal clear water were conducted. Two numbers of sensors views, 160 and 320 views are evaluated in this research in reconstructing the images. The image reconstruction algorithms used were filtered images of linear back projection algorithms. Analysis on comparing the simulation and experiments image results shows that, with 320 image views giving less area error than 160 views. This suggests that high image view resulted in the high resolution of image reconstruction.

Development of an NDIR CO2 Sensor-Based System for Assessing Soil Toxicity Using Substrate-Induced Respiration

PubMed Central

Kaur, Jasmeen; Adamchuk, Viacheslav I.; Whalen, Joann K.; Ismail, Ashraf A.

2015-01-01

The eco-toxicological indicators used to evaluate soil quality complement the physico-chemical criteria employed in contaminated site remediation, but their cost, time, sophisticated analytical methods and in-situ inapplicability pose a major challenge to rapidly detect and map the extent of soil contamination. This paper describes a sensor-based approach for measuring potential (substrate-induced) microbial respiration in diesel-contaminated and non-contaminated soil and hence, indirectly evaluates their microbial activity. A simple CO2 sensing system was developed using an inexpensive non-dispersive infrared (NDIR) CO2 sensor and was successfully deployed to differentiate the control and diesel-contaminated soils in terms of CO2 emission after glucose addition. Also, the sensor system distinguished glucose-induced CO2 emission from sterile and control soil samples (p ≤ 0.0001). Significant effects of diesel contamination (p ≤ 0.0001) and soil type (p ≤ 0.0001) on glucose-induced CO2 emission were also found. The developed sensing system can provide in-situ evaluation of soil microbial activity, an indicator of soil quality. The system can be a promising tool for the initial screening of contaminated environmental sites to create high spatial density maps at a relatively low cost. PMID:25730479

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

NASA Astrophysics Data System (ADS)

Ladai, A. D.; Miller, J.

2014-11-01

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

Advancements of Data Anomaly Detection Research in Wireless Sensor Networks: A Survey and Open Issues

PubMed Central

Rassam, Murad A.; Zainal, Anazida; Maarof, Mohd Aizaini

2013-01-01

Wireless Sensor Networks (WSNs) are important and necessary platforms for the future as the concept “Internet of Things” has emerged lately. They are used for monitoring, tracking, or controlling of many applications in industry, health care, habitat, and military. However, the quality of data collected by sensor nodes is affected by anomalies that occur due to various reasons, such as node failures, reading errors, unusual events, and malicious attacks. Therefore, anomaly detection is a necessary process to ensure the quality of sensor data before it is utilized for making decisions. In this review, we present the challenges of anomaly detection in WSNs and state the requirements to design efficient and effective anomaly detection models. We then review the latest advancements of data anomaly detection research in WSNs and classify current detection approaches in five main classes based on the detection methods used to design these approaches. Varieties of the state-of-the-art models for each class are covered and their limitations are highlighted to provide ideas for potential future works. Furthermore, the reviewed approaches are compared and evaluated based on how well they meet the stated requirements. Finally, the general limitations of current approaches are mentioned and further research opportunities are suggested and discussed. PMID:23966182

A Fiber Bragg grating based tilt sensor suitable for constant temperature room

NASA Astrophysics Data System (ADS)

Tang, Guoyu; Wei, Jue; Zhou, Wei; Wu, Mingyu; Yang, Meichao; Xie, Ruijun; Xu, Xiaofeng

2015-07-01

Constant-temperature rooms have been widely used in industrial production, quality testing, and research laboratories. This paper proposes a high-precision tilt sensor suitable for a constant- temperature room, which has achieved a wide-range power change while the fiber Bragg grating (FBG) reflection peak wavelength shifted very little, thereby demonstrating a novel method for obtaining a high-precision tilt sensor. This paper also studies the effect of the reflection peak on measurement precision. The proposed sensor can distinguish the direction of tilt with an excellent sensitivity of 403 dBm/° and a highest achievable resolution of 2.481 × 10-5 ° (that is, 0.08% of the measuring range).

Fast algorithm for wavefront reconstruction in XAO/SCAO with pyramid wavefront sensor

NASA Astrophysics Data System (ADS)

Shatokhina, Iuliia; Obereder, Andreas; Ramlau, Ronny

2014-08-01

We present a fast wavefront reconstruction algorithm developed for an extreme adaptive optics system equipped with a pyramid wavefront sensor on a 42m telescope. The method is called the Preprocessed Cumulative Reconstructor with domain decomposition (P-CuReD). The algorithm is based on the theoretical relationship between pyramid and Shack-Hartmann wavefront sensor data. The algorithm consists of two consecutive steps - a data preprocessing, and an application of the CuReD algorithm, which is a fast method for wavefront reconstruction from Shack-Hartmann sensor data. The closed loop simulation results show that the P-CuReD method provides the same reconstruction quality and is significantly faster than an MVM.

Lightweight, Room-Temperature CO2 Gas Sensor Based on Rare-Earth Metal-Free Composites—An Impedance Study

PubMed Central

2017-01-01

We report a light, flexible, and low-power poly(ionic liquid)/alumina composite CO2 sensor. We monitor the direct-current resistance changes as a function of CO2 concentration and relative humidity and demonstrate fast and reversible sensing kinetics. Moreover, on the basis of the alternating-current impedance measurements we propose a sensing mechanism related to proton conduction and gas diffusion. The findings presented herein will promote the development of organic/inorganic composite CO2 gas sensors. In the future, such sensors will be useful for numerous practical applications ranging from indoor air quality control to the monitoring of manufacturing processes. PMID:28726384

A Data Fusion Method in Wireless Sensor Networks

PubMed Central

Izadi, Davood; Abawajy, Jemal H.; Ghanavati, Sara; Herawan, Tutut

2015-01-01

The success of a Wireless Sensor Network (WSN) deployment strongly depends on the quality of service (QoS) it provides regarding issues such as data accuracy, data aggregation delays and network lifetime maximisation. This is especially challenging in data fusion mechanisms, where a small fraction of low quality data in the fusion input may negatively impact the overall fusion result. In this paper, we present a fuzzy-based data fusion approach for WSN with the aim of increasing the QoS whilst reducing the energy consumption of the sensor network. The proposed approach is able to distinguish and aggregate only true values of the collected data as such, thus reducing the burden of processing the entire data at the base station (BS). It is also able to eliminate redundant data and consequently reduce energy consumption thus increasing the network lifetime. We studied the effectiveness of the proposed data fusion approach experimentally and compared it with two baseline approaches in terms of data collection, number of transferred data packets and energy consumption. The results of the experiments show that the proposed approach achieves better results than the baseline approaches. PMID:25635417

Development and Application of a Wireless Sensor for Space Charge Density Measurement in an Ultra-High-Voltage, Direct-Current Environment

PubMed Central

Xin, Encheng; Ju, Yong; Yuan, Haiwen

2016-01-01

A space charge density wireless measurement system based on the idea of distributed measurement is proposed for collecting and monitoring the space charge density in an ultra-high-voltage direct-current (UHVDC) environment. The proposed system architecture is composed of a number of wireless nodes connected with space charge density sensors and a base station. The space charge density sensor based on atmospheric ion counter method is elaborated and developed, and the ARM microprocessor and Zigbee radio frequency module are applied. The wireless network communication quality and the relationship between energy consumption and transmission distance in the complicated electromagnetic environment is tested. Based on the experimental results, the proposed measurement system demonstrates that it can adapt to the complex electromagnetic environment under the UHVDC transmission lines and can accurately measure the space charge density. PMID:27775627

Development and Application of a Wireless Sensor for Space Charge Density Measurement in an Ultra-High-Voltage, Direct-Current Environment.

PubMed

Xin, Encheng; Ju, Yong; Yuan, Haiwen

2016-10-20

A space charge density wireless measurement system based on the idea of distributed measurement is proposed for collecting and monitoring the space charge density in an ultra-high-voltage direct-current (UHVDC) environment. The proposed system architecture is composed of a number of wireless nodes connected with space charge density sensors and a base station. The space charge density sensor based on atmospheric ion counter method is elaborated and developed, and the ARM microprocessor and Zigbee radio frequency module are applied. The wireless network communication quality and the relationship between energy consumption and transmission distance in the complicated electromagnetic environment is tested. Based on the experimental results, the proposed measurement system demonstrates that it can adapt to the complex electromagnetic environment under the UHVDC transmission lines and can accurately measure the space charge density.

Model-based sensor-less wavefront aberration correction in optical coherence tomography.

PubMed

Verstraete, Hans R G W; Wahls, Sander; Kalkman, Jeroen; Verhaegen, Michel

2015-12-15

Several sensor-less wavefront aberration correction methods that correct nonlinear wavefront aberrations by maximizing the optical coherence tomography (OCT) signal are tested on an OCT setup. A conventional coordinate search method is compared to two model-based optimization methods. The first model-based method takes advantage of the well-known optimization algorithm (NEWUOA) and utilizes a quadratic model. The second model-based method (DONE) is new and utilizes a random multidimensional Fourier-basis expansion. The model-based algorithms achieve lower wavefront errors with up to ten times fewer measurements. Furthermore, the newly proposed DONE method outperforms the NEWUOA method significantly. The DONE algorithm is tested on OCT images and shows a significantly improved image quality.

Portable Electronic Nose Based on Electrochemical Sensors for Food Quality Assessment

PubMed Central

Dymerski, Tomasz; Gębicki, Jacek; Namieśnik, Jacek

2017-01-01

The steady increase in global consumption puts a strain on agriculture and might lead to a decrease in food quality. Currently used techniques of food analysis are often labour-intensive and time-consuming and require extensive sample preparation. For that reason, there is a demand for novel methods that could be used for rapid food quality assessment. A technique based on the use of an array of chemical sensors for holistic analysis of the sample’s headspace is called electronic olfaction. In this article, a prototype of a portable, modular electronic nose intended for food analysis is described. Using the SVM method, it was possible to classify samples of poultry meat based on shelf-life with 100% accuracy, and also samples of rapeseed oil based on the degree of thermal degradation with 100% accuracy. The prototype was also used to detect adulterations of extra virgin olive oil with rapeseed oil with 82% overall accuracy. Due to the modular design, the prototype offers the advantages of solutions targeted for analysis of specific food products, at the same time retaining the flexibility of application. Furthermore, its portability allows the device to be used at different stages of the production and distribution process. PMID:29186754

Object positioning in storages of robotized workcells using LabVIEW Vision

NASA Astrophysics Data System (ADS)

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

2015-11-01

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

Thermally assisted sensor for conformity assessment of biodiesel production

NASA Astrophysics Data System (ADS)

Kawano, M. S.; Kamikawachi, R. C.; Fabris, J. L.; Muller, M.

2015-02-01

Although biodiesel can be intentionally tampered with, impairing its quality, ineffective production processes may also result in a nonconforming final fuel. For an incomplete transesterification reaction, traces of alcohol (ethanol or methanol) or remaining raw material (vegetable oil or animal fats) may be harmful to consumers, the environment or to engines. Traditional methods for biodiesel assessment are complex, time consuming and expensive, leading to the need for the development of new and more versatile processes for quality control. This work describes a refractometric fibre optic based sensor that is thermally assisted, developed to quantify the remaining methanol or vegetable oil in biodiesel blends. The sensing relies on a long period grating to configure an in-fibre interferometer. A complete analytical routine is demonstrated for the sensor allowing the evaluation of the biodiesel blends without segregation of the components. The results show the sensor can determine the presence of oil or methanol in biodiesel with a concentration ranging from 0% to 10% v/v. The sensor presented a resolution and standard combined uncertainty of 0.013% v/v and 0.62% v/v for biodiesel-oil samples, and 0.007% v/v and 0.22% v/v for biodiesel-methanol samples, respectively.

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.

Smart healthcare textile sensor system for unhindered-pervasive health monitoring

NASA Astrophysics Data System (ADS)

Rai, Pratyush; Kumar, Prashanth S.; Oh, Sechang; Kwon, Hyeokjun; Mathur, Gyanesh N.; Varadan, Vijay K.; Agarwal, M. P.

2012-04-01

Simultaneous monitoring of physiological parameters- multi-lead Electrocardiograph (ECG), Heart rate variability, and blood pressure- is imperative to all forms of medical treatments. Using an array of signal recording devices imply that the patient will have to be confined to a bed. Textiles offer durable platform for embedded sensor and communication systems. The smart healthcare textile, presented here, is a mobile system for remote/wireless data recording and conditioning. The wireless textile system has been designed to monitor a patient in a non-obstructive way. It has a potential for facilitating point of care medicine and streamlining ambulatory medicine. The sensor systems were designed and fabricated with textile based components for easy integration on textile platform. An innovative plethysmographic blood pressure monitoring system was designed and tested as an alternative to inflatable blood pressure sphygmomanometer. Flexible dry electrodes technology was implemented for ECG. The sensor systems were tested and conditioned to daily activities of patients, which is not permissible with halter type systems. The signal quality was assessed for it applicability to medical diagnosis. The results were used to corroborate smart textile sensor system's ability to function as a point of care system that can provide quality healthcare.

Economic Feasibility of Wireless Sensor Network-Based Service Provision in a Duopoly Setting with a Monopolist Operator

PubMed Central

Romero, Julián; Sacoto-Cabrera, Erwin J.

2017-01-01

We analyze the feasibility of providing Wireless Sensor Network-data-based services in an Internet of Things scenario from an economical point of view. The scenario has two competing service providers with their own private sensor networks, a network operator and final users. The scenario is analyzed as two games using game theory. In the first game, sensors decide to subscribe or not to the network operator to upload the collected sensing-data, based on a utility function related to the mean service time and the price charged by the operator. In the second game, users decide to subscribe or not to the sensor-data-based service of the service providers based on a Logit discrete choice model related to the quality of the data collected and the subscription price. The sinks and users subscription stages are analyzed using population games and discrete choice models, while network operator and service providers pricing stages are analyzed using optimization and Nash equilibrium concepts respectively. The model is shown feasible from an economic point of view for all the actors if there are enough interested final users and opens the possibility of developing more efficient models with different types of services. PMID:29186847

Optical sensor based on a single CdS nanobelt.

PubMed

Li, Lei; Yang, Shuming; Han, Feng; Wang, Liangjun; Zhang, Xiaotong; Jiang, Zhuangde; Pan, Anlian

2014-04-23

In this paper, an optical sensor based on a cadmium sulfide (CdS) nanobelt has been developed. The CdS nanobelt was synthesized by the vapor phase transportation (VPT) method. X-Ray Diffraction (XRD) and Transmission Electron Microscopy (TEM) results revealed that the nanobelt had a hexagonal wurtzite structure of CdS and presented good crystal quality. A single nanobelt Schottky contact optical sensor was fabricated by the electron beam lithography (EBL) technique, and the device current-voltage results showed back-to-back Schottky diode characteristics. The photosensitivity, dark current and the decay time of the sensor were 4 × 10⁴, 31 ms and 0.2 pA, respectively. The high photosensitivity and the short decay time were because of the exponential dependence of photocurrent on the number of the surface charges and the configuration of the back to back Schottky junctions.

Miniature optical fiber temperature sensor based on FMF-SCF structure

NASA Astrophysics Data System (ADS)

Zhang, Chuanbiao; Ning, Tigang; Zheng, Jingjing; Gao, Xuekai; Lin, Heng; Li, Jing; Pei, Li; Wen, Xiaodong

2018-03-01

We proposed and experimentally demonstrated a miniature optical fiber temperature sensor consisting of a seven core fiber (SCF) and a few mode fiber (FMF). The device is fabricated by splicing a section of FMF with a segment of SCF to form a FMF-SCF based sensing structure, and during the FMF region, few modes can be excited and will propagate within the SCF. In experiment, the proposed device has good quality interferometric spectra, and the highest extinction ratio of 27 dB was achieved. When the temperature increases from room temperature to 110 °C, the temperature response properties of the sensor have been investigated, the wavelength sensitivity of about 91.8 pm/°C and the amplitude sensitivity of about 1.57 × 10-2 a.u./°C are obtained, respectively. Due to its easy and controllable fabrication, the sensor can be a suitable candidate in temperature sensing applications.

Automatic Carbon Dioxide-Methane Gas Sensor Based on the Solubility of Gases in Water

PubMed Central

Cadena-Pereda, Raúl O.; Rivera-Muñoz, Eric M.; Herrera-Ruiz, Gilberto; Gomez-Melendez, Domingo J.; Anaya-Rivera, Ely K.

2012-01-01

Biogas methane content is a relevant variable in anaerobic digestion processing where knowledge of process kinetics or an early indicator of digester failure is needed. The contribution of this work is the development of a novel, simple and low cost automatic carbon dioxide-methane gas sensor based on the solubility of gases in water as the precursor of a sensor for biogas quality monitoring. The device described in this work was used for determining the composition of binary mixtures, such as carbon dioxide-methane, in the range of 0–100%. The design and implementation of a digital signal processor and control system into a low-cost Field Programmable Gate Array (FPGA) platform has permitted the successful application of data acquisition, data distribution and digital data processing, making the construction of a standalone carbon dioxide-methane gas sensor possible. PMID:23112626

Wearable photoplethysmography device prototype for wireless cardiovascular monitoring

NASA Astrophysics Data System (ADS)

Kviesis-Kipge, E.; Grabovskis, A.; Marcinkevics, Z.; Mecnika, V.; Rubenis, O.

2014-05-01

The aim of the study was to develop a prototype system of the smart garment for real time telemetric monitoring of human cardiovascular activity. Two types of photoplethysmography (PPG) sensors for low noise and artefact free signal recording from various sites of the human body that were suitable for integration into smart textile were investigated. The reflectance sensors with single and multiple photodiodes based on "pulse-duration-based signal conversion" signal acquisition principle were designed and evaluated. The technical parameters of the system were measured both on bench and in vivo. Overall, both types of PPG sensors showed acceptable signal quality SNR 86.56±3.00 dB, dynamic range 89.84 dB. However, in-vivo condition tests revealed lower noise and higher accuracy achieved by applying the multiple photodiodes sensor. We concluded that the proposed PPG device prototype is simple and reliable, and therefore, can be utilized in low-cost smart garments.

Automatic carbon dioxide-methane gas sensor based on the solubility of gases in water.

PubMed

Cadena-Pereda, Raúl O; Rivera-Muñoz, Eric M; Herrera-Ruiz, Gilberto; Gomez-Melendez, Domingo J; Anaya-Rivera, Ely K

2012-01-01

Biogas methane content is a relevant variable in anaerobic digestion processing where knowledge of process kinetics or an early indicator of digester failure is needed. The contribution of this work is the development of a novel, simple and low cost automatic carbon dioxide-methane gas sensor based on the solubility of gases in water as the precursor of a sensor for biogas quality monitoring. The device described in this work was used for determining the composition of binary mixtures, such as carbon dioxide-methane, in the range of 0-100%. The design and implementation of a digital signal processor and control system into a low-cost Field Programmable Gate Array (FPGA) platform has permitted the successful application of data acquisition, data distribution and digital data processing, making the construction of a standalone carbon dioxide-methane gas sensor possible.

Substrate Integrated Waveguide (SIW)-Based Wireless Temperature Sensor for Harsh Environments.

PubMed

Tan, Qiulin; Guo, Yanjie; Zhang, Lei; Lu, Fei; Dong, Helei; Xiong, Jijun

2018-05-03

This paper presents a new wireless sensor structure based on a substrate integrated circular waveguide (SICW) for the temperature test in harsh environments. The sensor substrate material is 99% alumina ceramic, and the SICW structure is composed of upper and lower metal plates and a series of metal cylindrical sidewall vias. A rectangular aperture antenna integrated on the surface of the SICW resonator is used for electromagnetic wave transmission between the sensor and the external antenna. The resonant frequency of the temperature sensor decreases when the temperature increases, because the relative permittivity of the alumina ceramic increases with temperature. The temperature sensor presented in this paper was tested four times at a range of 30⁻1200 °C, and a broad band coplanar waveguide (CPW)-fed antenna was used as an interrogation antenna during the test process. The resonant frequency changed from 2.371 to 2.141 GHz as the temperature varied from 30 to 1200 °C, leading to a sensitivity of 0.197 MHz/°C. The quality factor of the sensor changed from 3444.6 to 35.028 when the temperature varied from 30 to 1000 °C.

False alarm reduction in BSN-based cardiac monitoring using signal quality and activity type information.

PubMed

Tanantong, Tanatorn; Nantajeewarawat, Ekawit; Thiemjarus, Surapa

2015-02-09

False alarms in cardiac monitoring affect the quality of medical care, impacting on both patients and healthcare providers. In continuous cardiac monitoring using wireless Body Sensor Networks (BSNs), the quality of ECG signals can be deteriorated owing to several factors, e.g., noises, low battery power, and network transmission problems, often resulting in high false alarm rates. In addition, body movements occurring from activities of daily living (ADLs) can also create false alarms. This paper presents a two-phase framework for false arrhythmia alarm reduction in continuous cardiac monitoring, using signals from an ECG sensor and a 3D accelerometer. In the first phase, classification models constructed using machine learning algorithms are used for labeling input signals. ECG signals are labeled with heartbeat types and signal quality levels, while 3D acceleration signals are labeled with ADL types. In the second phase, a rule-based expert system is used for combining classification results in order to determine whether arrhythmia alarms should be accepted or suppressed. The proposed framework was validated on datasets acquired using BSNs and the MIT-BIH arrhythmia database. For the BSN dataset, acceleration and ECG signals were collected from 10 young and 10 elderly subjects while they were performing ADLs. The framework reduced the false alarm rate from 9.58% to 1.43% in our experimental study, showing that it can potentially assist physicians in diagnosing a vast amount of data acquired from wireless sensors and enhance the performance of continuous cardiac monitoring.

A New Calibration Method for Commercial RGB-D Sensors.

PubMed

Darwish, Walid; Tang, Shenjun; Li, Wenbin; Chen, Wu

2017-05-24

Commercial RGB-D sensors such as Kinect and Structure Sensors have been widely used in the game industry, where geometric fidelity is not of utmost importance. For applications in which high quality 3D is required, i.e., 3D building models of centimeter‑level accuracy, accurate and reliable calibrations of these sensors are required. This paper presents a new model for calibrating the depth measurements of RGB-D sensors based on the structured light concept. Additionally, a new automatic method is proposed for the calibration of all RGB-D parameters, including internal calibration parameters for all cameras, the baseline between the infrared and RGB cameras, and the depth error model. When compared with traditional calibration methods, this new model shows a significant improvement in depth precision for both near and far ranges.

Radiometric and Spatial Characterization of High-Spatial Resolution Sensors

NASA Technical Reports Server (NTRS)

Thome, Kurtis; Zanoni, Vicki (Technical Monitor)

2002-01-01

The development and improvement of commercial hyperspatial sensors in recent years has increased the breadth of information that can be retrieved from spaceborne and airborne imagery. NASA, through it's Scientific Data Purchases, has successfully provided such data sets to its user community. A key element to the usefulness of these data are an understanding of the radiometric and spatial response quality of the imagery. This proposal seeks funding to examine the absolute radiometric calibration of the Ikonos sensor operated by Space Imaging and the recently-launched Quickbird sensor from DigitalGlobe. In addition, we propose to evaluate the spatial response of the two sensors. The proposed methods rely on well-understood, ground-based targets that have been used by the University of Arizona for more than a decade.

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.

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

Pulse Based Time-of-Flight Range Sensing.

PubMed

Sarbolandi, Hamed; Plack, Markus; Kolb, Andreas

2018-05-23

Pulse-based Time-of-Flight (PB-ToF) cameras are an attractive alternative range imaging approach, compared to the widely commercialized Amplitude Modulated Continuous-Wave Time-of-Flight (AMCW-ToF) approach. This paper presents an in-depth evaluation of a PB-ToF camera prototype based on the Hamamatsu area sensor S11963-01CR. We evaluate different ToF-related effects, i.e., temperature drift, systematic error, depth inhomogeneity, multi-path effects, and motion artefacts. Furthermore, we evaluate the systematic error of the system in more detail, and introduce novel concepts to improve the quality of range measurements by modifying the mode of operation of the PB-ToF camera. Finally, we describe the means of measuring the gate response of the PB-ToF sensor and using this information for PB-ToF sensor simulation.

An uncertainty-based distributed fault detection mechanism for wireless sensor networks.

PubMed

Yang, Yang; Gao, Zhipeng; Zhou, Hang; Qiu, Xuesong

2014-04-25

Exchanging too many messages for fault detection will cause not only a degradation of the network quality of service, but also represents a huge burden on the limited energy of sensors. Therefore, we propose an uncertainty-based distributed fault detection through aided judgment of neighbors for wireless sensor networks. The algorithm considers the serious influence of sensing measurement loss and therefore uses Markov decision processes for filling in missing data. Most important of all, fault misjudgments caused by uncertainty conditions are the main drawbacks of traditional distributed fault detection mechanisms. We draw on the experience of evidence fusion rules based on information entropy theory and the degree of disagreement function to increase the accuracy of fault detection. Simulation results demonstrate our algorithm can effectively reduce communication energy overhead due to message exchanges and provide a higher detection accuracy ratio.

#2) Sensor Technology-State of the Science

EPA Science Inventory

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 othe...

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.

Performance Evaluation and Community Application of Low-Cost Sensors for Ozone and Nitrogen Dioxide.

PubMed

Duvall, Rachelle M; Long, Russell W; Beaver, Melinda R; Kronmiller, Keith G; Wheeler, Michael L; Szykman, James J

2016-10-13

This study reports on the performance of electrochemical-based low-cost sensors and their use in a community application. CairClip sensors were collocated with federal reference and equivalent methods and operated in a network of sites by citizen scientists (community members) in Houston, Texas and Denver, Colorado, under the umbrella of the NASA-led DISCOVER-AQ Earth Venture Mission. Measurements were focused on ozone (O₃) and nitrogen dioxide (NO₂). The performance evaluation showed that the CairClip O₃/NO₂ sensor provided a consistent measurement response to that of reference monitors (r² = 0.79 in Houston; r² = 0.72 in Denver) whereas the CairClip NO₂ sensor measurements showed no agreement to reference measurements. The CairClip O₃/NO₂ sensor data from the citizen science sites compared favorably to measurements at nearby reference monitoring sites. This study provides important information on data quality from low-cost sensor technologies and is one of few studies that reports sensor data collected directly by citizen scientists.

Wastewater quality monitoring system using sensor fusion and machine learning techniques.

PubMed

Qin, Xusong; Gao, Furong; Chen, Guohua

2012-03-15

A multi-sensor water quality monitoring system incorporating an UV/Vis spectrometer and a turbidimeter was used to monitor the Chemical Oxygen Demand (COD), Total Suspended Solids (TSS) and Oil & Grease (O&G) concentrations of the effluents from the Chinese restaurant on campus and an electrocoagulation-electroflotation (EC-EF) pilot plant. In order to handle the noise and information unbalance in the fused UV/Vis spectra and turbidity measurements during the calibration model building, an improved boosting method, Boosting-Iterative Predictor Weighting-Partial Least Squares (Boosting-IPW-PLS), was developed in the present study. The Boosting-IPW-PLS method incorporates IPW into boosting scheme to suppress the quality-irrelevant variables by assigning small weights, and builds up the models for the wastewater quality predictions based on the weighted variables. The monitoring system was tested in the field with satisfactory results, underlying the potential of this technique for the online monitoring of water quality. Copyright © 2011 Elsevier Ltd. All rights reserved.

LESS: Link Estimation with Sparse Sampling in Intertidal WSNs

PubMed Central

Ji, Xiaoyu; Chen, Yi-chao; Li, Xiaopeng; Xu, Wenyuan

2018-01-01

Deploying wireless sensor networks (WSN) in the intertidal area is an effective approach for environmental monitoring. To sustain reliable data delivery in such a dynamic environment, a link quality estimation mechanism is crucial. However, our observations in two real WSN systems deployed in the intertidal areas reveal that link update in routing protocols often suffers from energy and bandwidth waste due to the frequent link quality measurement and updates. In this paper, we carefully investigate the network dynamics using real-world sensor network data and find it feasible to achieve accurate estimation of link quality using sparse sampling. We design and implement a compressive-sensing-based link quality estimation protocol, LESS, which incorporates both spatial and temporal characteristics of the system to aid the link update in routing protocols. We evaluate LESS in both real WSN systems and a large-scale simulation, and the results show that LESS can reduce energy and bandwidth consumption by up to 50% while still achieving more than 90% link quality estimation accuracy. PMID:29494557

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

Humayun, Md Tanim; Paprotny, Igor, E-mail: paprotny@uic.edu; Divan, Ralu

Chemoresistive sensors based on multiwalled carbon nanotubes (MWCNTs) functionalized with SnO{sub 2} nanocrystals (NCs) have great potential for detecting trace gases at low concentrations (single ppm levels) at room temperature, because the SnO{sub 2} nanocrystals act as active sites for the chemisorption of gas molecules, and carbon nanotubes (CNTs) act as an excellent current carrying platform, allowing the adsorption of gas on SnO{sub 2} to modulate the resistance of the CNTs. However, uniform conjugation of SnO{sub 2} NCs with MWCNTs is challenging. An effective atomic layer deposition based approach to functionalize the surface of MWCNTs with SnO{sub 2} NCs, resultingmore » in a novel CH{sub 4} sensor with 10 ppm sensitivity, is presented in this paper. Scanning electron microscopy, transmission electron microscopy (TEM), energy dispersive x-ray spectroscopy, and Raman spectroscopy were implemented to study the morphology, elemental composition, and the crystal quality of SnO{sub 2} functionalized MWCNTs. High resolution TEM images showed that the crystal quality of the functionalizing SnO{sub 2} NCs was of high quality with clear lattice fringes and the dimension almost three times smaller than shown thus far in literature. A lift-off based photolithography technique comprising bilayer photoresists was optimized to fabricate SnO{sub 2} functionalized MWCNTs-based chemoresistor sensor, which at room temperature can reliably sense below 10 ppm of CH{sub 4} in air. Such low level gas sensitivity, with significant reversible relative resistance change, is believed to be the direct result of the successful functionalization of the MWCNT surface by SnO{sub 2} NCs.« less

Performance Evaluation of Energy-Autonomous Sensors Using Power-Harvesting Beacons for Environmental Monitoring in Internet of Things (IoT).

PubMed

Moiş, George Dan; Sanislav, Teodora; Folea, Silviu Corneliu; Zeadally, Sherali

2018-05-25

Environmental conditions and air quality monitoring have become crucial today due to the undeniable changes of the climate and accelerated urbanization. To efficiently monitor environmental parameters such as temperature, humidity, and the levels of pollutants, such as fine particulate matter (PM2.5) and volatile organic compounds (VOCs) in the air, and to collect data covering vast geographical areas, the development of cheap energy-autonomous sensors for large scale deployment and fine-grained data acquisition is required. Rapid advances in electronics and communication technologies along with the emergence of paradigms such as Cyber-Physical Systems (CPSs) and the Internet of Things (IoT) have led to the development of low-cost sensor devices that can operate unattended for long periods of time and communicate using wired or wireless connections through the Internet. We investigate the energy efficiency of an environmental monitoring system based on Bluetooth Low Energy (BLE) beacons that operate in the IoT environment. The beacons developed measure the temperature, the relative humidity, the light intensity, and the CO₂ and VOC levels in the air. Based on our analysis we have developed efficient sleep scheduling algorithms that allow the sensor nodes developed to operate autonomously without requiring the replacement of the power supply. The experimental results show that low-power sensors communicating using BLE technology can operate autonomously (from the energy perspective) in applications that monitor the environment or the air quality in indoor or outdoor settings.

QoS and energy aware cooperative routing protocol for wildfire monitoring wireless sensor networks.

PubMed

Maalej, Mohamed; Cherif, Sofiane; Besbes, Hichem

2013-01-01

Wireless sensor networks (WSN) are presented as proper solution for wildfire monitoring. However, this application requires a design of WSN taking into account the network lifetime and the shadowing effect generated by the trees in the forest environment. Cooperative communication is a promising solution for WSN which uses, at each hop, the resources of multiple nodes to transmit its data. Thus, by sharing resources between nodes, the transmission quality is enhanced. In this paper, we use the technique of reinforcement learning by opponent modeling, optimizing a cooperative communication protocol based on RSSI and node energy consumption in a competitive context (RSSI/energy-CC), that is, an energy and quality-of-service aware-based cooperative communication routing protocol. Simulation results show that the proposed algorithm performs well in terms of network lifetime, packet delay, and energy consumption.

A LEO Satellite Navigation Algorithm Based on GPS and Magnetometer Data

NASA Technical Reports Server (NTRS)

Deutschmann, Julie; Bar-Itzhack, Itzhack; Harman, Rick; Bauer, Frank H. (Technical Monitor)

2000-01-01

The Global Positioning System (GPS) has become a standard method for low cost onboard satellite orbit determination. The use of a GPS receiver as an attitude and rate sensor has also been developed in the recent past. Additionally, focus has been given to attitude and orbit estimation using the magnetometer, a low cost, reliable sensor. Combining measurements from both GPS and a magnetometer can provide a robust navigation system that takes advantage of the estimation qualities of both measurements. Ultimately a low cost, accurate navigation system can result, potentially eliminating the need for more costly sensors, including gyroscopes.

Tailoring fiber grating sensors for assessment of highly refractive fuels.

PubMed

Kawano, Marianne Sumie; Heidemann, Bárbara Rutyna; Cardoso, Tárik Kaiel Machado; Possetti, Gustavo Rafael Collere; Kamikawachi, Ricardo Canute; Muller, Marcia; Fabris, José Luís

2012-04-20

Three approaches that allow the tailoring of long period gratings based refractometric sensors for concentration measurement in fuel blends are employed to assess the fuel quality in biodiesel and biodiesel-petrodiesel blend. To allow the analysis of fuel samples with refractive index higher than fiber cladding one, the samples refractive indices were changed by thermo-optic effect and by dilution in a standard substance with low refractive index. The obtained results show the sensor can detect oil concentration in biodiesel samples with resolution as better as 0.07% and biodiesel concentration in biodiesel-petrodiesel samples with average resolution of 0.09%.

Solutions Network Formulation Report. Visible/Infrared Imager/Radiometer Suite and Landsat Data Continuity Mission Simulated Data Products for the Great Lakes Basin Ecological Team

NASA Technical Reports Server (NTRS)

Estep, Leland

2007-01-01

The proposed solution would simulate VIIRS and LDCM sensor data for use in the USGS/USFWS GLBET DST. The VIIRS sensor possesses a spectral range that provides water-penetrating bands that could be used to assess water clarity on a regional spatial scale. The LDCM sensor possesses suitable spectral bands in a range of wavelengths that could be used to map water quality at finer spatial scales relative to VIIRS. Water quality, alongshore sediment transport and pollutant discharge tracking into the Great Lakes system are targeted as the primary products to be developed. A principal benefit of water quality monitoring via satellite imagery is its economy compared to field-data collection methods. Additionally, higher resolution satellite imagery provides a baseline dataset(s) against which later imagery can be overlaid in GIS-based DST programs. Further, information derived from higher resolution satellite imagery can be used to address public concerns and to confirm environmental compliance. The candidate solution supports the Public Health, Coastal Management, and Water Management National Applications.

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.

A Survey of Wireless Sensor Network Based Air Pollution Monitoring Systems

PubMed Central

Yi, Wei Ying; Lo, Kin Ming; Mak, Terrence; Leung, Kwong Sak; Leung, Yee; Meng, Mei Ling

2015-01-01

The air quality in urban areas is a major concern in modern cities due to significant impacts of air pollution on public health, global environment, and worldwide economy. Recent studies reveal the importance of micro-level pollution information, including human personal exposure and acute exposure to air pollutants. A real-time system with high spatio-temporal resolution is essential because of the limited data availability and non-scalability of conventional air pollution monitoring systems. Currently, researchers focus on the concept of The Next Generation Air Pollution Monitoring System (TNGAPMS) and have achieved significant breakthroughs by utilizing the advance sensing technologies, MicroElectroMechanical Systems (MEMS) and Wireless Sensor Network (WSN). However, there exist potential problems of these newly proposed systems, namely the lack of 3D data acquisition ability and the flexibility of the sensor network. In this paper, we classify the existing works into three categories as Static Sensor Network (SSN), Community Sensor Network (CSN) and Vehicle Sensor Network (VSN) based on the carriers of the sensors. Comprehensive reviews and comparisons among these three types of sensor networks were also performed. Last but not least, we discuss the limitations of the existing works and conclude the objectives that we want to achieve in future systems. PMID:26703598

A Survey of Wireless Sensor Network Based Air Pollution Monitoring Systems.

PubMed

Yi, Wei Ying; Lo, Kin Ming; Mak, Terrence; Leung, Kwong Sak; Leung, Yee; Meng, Mei Ling

2015-12-12

The air quality in urban areas is a major concern in modern cities due to significant impacts of air pollution on public health, global environment, and worldwide economy. Recent studies reveal the importance of micro-level pollution information, including human personal exposure and acute exposure to air pollutants. A real-time system with high spatio-temporal resolution is essential because of the limited data availability and non-scalability of conventional air pollution monitoring systems. Currently, researchers focus on the concept of The Next Generation Air Pollution Monitoring System (TNGAPMS) and have achieved significant breakthroughs by utilizing the advance sensing technologies, MicroElectroMechanical Systems (MEMS) and Wireless Sensor Network (WSN). However, there exist potential problems of these newly proposed systems, namely the lack of 3D data acquisition ability and the flexibility of the sensor network. In this paper, we classify the existing works into three categories as Static Sensor Network (SSN), Community Sensor Network (CSN) and Vehicle Sensor Network (VSN) based on the carriers of the sensors. Comprehensive reviews and comparisons among these three types of sensor networks were also performed. Last but not least, we discuss the limitations of the existing works and conclude the objectives that we want to achieve in future systems.

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...

The data quality analyzer: a quality control program for seismic data

USGS Publications Warehouse

Ringler, Adam; Hagerty, M.T.; Holland, James F.; Gonzales, A.; Gee, Lind S.; Edwards, J.D.; Wilson, David; Baker, Adam

2015-01-01

The quantification of data quality is based on the evaluation of various metrics (e.g., timing quality, daily noise levels relative to long-term noise models, and comparisons between broadband data and event synthetics). Users may select which metrics contribute to the assessment and those metrics are aggregated into a “grade” for each station. The DQA is being actively used for station diagnostics and evaluation based on the completed metrics (availability, gap count, timing quality, deviation from a global noise model, deviation from a station noise model, coherence between co-located sensors, and comparison between broadband data and synthetics for earthquakes) on stations in the Global Seismographic Network and Advanced National Seismic System.

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.

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

NASA Astrophysics Data System (ADS)

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

2015-05-01

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

Automatic Earth observation data service based on reusable geo-processing workflow

NASA Astrophysics Data System (ADS)

Chen, Nengcheng; Di, Liping; Gong, Jianya; Yu, Genong; Min, Min

2008-12-01

A common Sensor Web data service framework for Geo-Processing Workflow (GPW) is presented as part of the NASA Sensor Web project. This framework consists of a data service node, a data processing node, a data presentation node, a Catalogue Service node and BPEL engine. An abstract model designer is used to design the top level GPW model, model instantiation service is used to generate the concrete BPEL, and the BPEL execution engine is adopted. The framework is used to generate several kinds of data: raw data from live sensors, coverage or feature data, geospatial products, or sensor maps. A scenario for an EO-1 Sensor Web data service for fire classification is used to test the feasibility of the proposed framework. The execution time and influences of the service framework are evaluated. The experiments show that this framework can improve the quality of services for sensor data retrieval and processing.

Empowering smartphone users with sensor node for air quality measurement

NASA Astrophysics Data System (ADS)

Oletic, Dinko; Bilas, Vedran

2013-06-01

We present an architecture of a sensor node developed for use with smartphones for participatory sensing of air quality in urban environments. Our solution features inexpensive metal-oxide semiconductor gas sensors (MOX) for measurement of CO, O3, NO2 and VOC, along with sensors for ambient temperature and humidity. We focus on our design of sensor interface consisting of power-regulated heater temperature control, and the design of resistance sensing circuit. Accuracy of the sensor interface is characterized. Power consumption of the sensor node is analysed. Preliminary data obtained from the CO gas sensors in laboratory conditions and during the outdoor field-test is shown.

Resource optimized TTSH-URA for multimedia stream authentication in swallowable-capsule-based wireless body sensor networks.

PubMed

Wang, Wei; Wang, Chunqiu; Zhao, Min

2014-03-01

To ease the burdens on the hospitalization capacity, an emerging swallowable-capsule technology has evolved to serve as a remote gastrointestinal (GI) disease examination technique with the aid of the wireless body sensor network (WBSN). Secure multimedia transmission in such a swallowable-capsule-based WBSN faces critical challenges including energy efficiency and content quality guarantee. In this paper, we propose a joint resource allocation and stream authentication scheme to maintain the best possible video quality while ensuring security and energy efficiency in GI-WBSNs. The contribution of this research is twofold. First, we establish a unique signature-hash (S-H) diversity approach in the authentication domain to optimize video authentication robustness and the authentication bit rate overhead over a wireless channel. Based on the full exploration of S-H authentication diversity, we propose a new two-tier signature-hash (TTSH) stream authentication scheme to improve the video quality by reducing authentication dependence overhead while protecting its integrity. Second, we propose to combine this authentication scheme with a unique S-H oriented unequal resource allocation (URA) scheme to improve the energy-distortion-authentication performance of wireless video delivery in GI-WBSN. Our analysis and simulation results demonstrate that the proposed TTSH with URA scheme achieves considerable gain in both authenticated video quality and energy efficiency.

Performance Evaluation of "Low-cost" Sensors for Measuring Gaseous and Particle Air Pollutants: Results from Two Years of Field and Laboratory Testing

NASA Astrophysics Data System (ADS)

Feenstra, B. J.; Polidori, A.; Tisopulos, L.; Papapostolou, V.; Zhang, H.; Pathmanabhan, J.

2016-12-01

In recent years great progress has been made in development of low-cost miniature air quality sensing technologies. Such low-cost sensors offer a prospect of providing a real-time spatially dense information on pollutants, however, the quality of the data produced by these sensors is so far untested. In an effort to inform the general public about the actual performance of commercially available low-cost air quality sensors, in June 2014 the South Coast Air Quality Management District (SCAQMD) has established the Air Quality Sensor Performance Evaluation Center (AQ-SPEC). This program performs a thorough characterization of low-cost sensors under ambient (in the field) and controlled (in the laboratory) conditions. During the field testing, air quality sensors are operated side-by-side with Federal Reference Methods and Federal Equivalent Methods (FRM and FEM, respectively), which are routinely used to measure the ambient concentration of gaseous or particle pollutants for regulatory purposes. Field testing is conducted at two of SCAQMD's existing air monitoring stations, one in Rubidoux and one near the I-710 freeway. Sensors that demonstrate an acceptable performance in the field are brought back to the lab where a "characterization chamber" is used to challenge these devices with known concentrations of different particle and gaseous pollutants under different temperature and relative humidity levels. Testing results for each sensor are then summarized in a technical report and, along with other relevant information, posted online on a dedicated website (www.aqmd.gov/aq-spec) to educate the public about the capabilities of commercially available sensors and their potential applications. During this presentation, the results from two years of field and laboratory testing will be presented. The major strengths and weaknesses of some of the most commonly available particle and gaseous sensors will be discussed.

An integrated multi-sensor fusion-based deep feature learning approach for rotating machinery diagnosis

NASA Astrophysics Data System (ADS)

Liu, Jie; Hu, Youmin; Wang, Yan; Wu, Bo; Fan, Jikai; Hu, Zhongxu

2018-05-01

The diagnosis of complicated fault severity problems in rotating machinery systems is an important issue that affects the productivity and quality of manufacturing processes and industrial applications. However, it usually suffers from several deficiencies. (1) A considerable degree of prior knowledge and expertise is required to not only extract and select specific features from raw sensor signals, and but also choose a suitable fusion for sensor information. (2) Traditional artificial neural networks with shallow architectures are usually adopted and they have a limited ability to learn the complex and variable operating conditions. In multi-sensor-based diagnosis applications in particular, massive high-dimensional and high-volume raw sensor signals need to be processed. In this paper, an integrated multi-sensor fusion-based deep feature learning (IMSFDFL) approach is developed to identify the fault severity in rotating machinery processes. First, traditional statistics and energy spectrum features are extracted from multiple sensors with multiple channels and combined. Then, a fused feature vector is constructed from all of the acquisition channels. Further, deep feature learning with stacked auto-encoders is used to obtain the deep features. Finally, the traditional softmax model is applied to identify the fault severity. The effectiveness of the proposed IMSFDFL approach is primarily verified by a one-stage gearbox experimental platform that uses several accelerometers under different operating conditions. This approach can identify fault severity more effectively than the traditional approaches.

Combining physiological, environmental and locational sensors for citizen-oriented health applications.

PubMed

Huck, J J; Whyatt, J D; Coulton, P; Davison, B; Gradinar, A

2017-03-01

This work investigates the potential of combining the outputs of multiple low-cost sensor technologies for the direct measurement of spatio-temporal variations in phenomena that exist at the interface between our bodies and the environment. The example used herein is the measurement of personal exposure to traffic pollution, which may be considered as a function of the concentration of pollutants in the air and the frequency and volume of that air which enters our lungs. The sensor-based approach described in this paper removes the 'traditional' requirements either to model or interpolate pollution levels or to make assumptions about the physiology of an individual. Rather, a wholly empirical analysis into pollution exposure is possible, based upon high-resolution spatio-temporal data drawn from sensors for NO 2 , nasal airflow and location (GPS). Data are collected via a custom smartphone application and mapped to give an unprecedented insight into exposure to traffic pollution at the individual level. Whilst the quality of data from low-cost miniaturised sensors is not suitable for all applications, there certainly are many applications for which these data would be well suited, particularly those in the field of citizen science. This paper demonstrates both the potential and limitations of sensor-based approaches and discusses the wider relevance of these technologies for the advancement of citizen science.

A teleoperated system for remote site characterization

NASA Technical Reports Server (NTRS)

Sandness, Gerald A.; Richardson, Bradley S.; Pence, Jon

1994-01-01

The detection and characterization of buried objects and materials is an important step in the restoration of burial sites containing chemical and radioactive waste materials at Department of Energy (DOE) and Department of Defense (DOD) facilities. By performing these tasks with remotely controlled sensors, it is possible to obtain improved data quality and consistency as well as enhanced safety for on-site workers. Therefore, the DOE Office of Technology Development and the US Army Environmental Center have jointly supported the development of the Remote Characterization System (RCS). One of the main components of the RCS is a small remotely driven survey vehicle that can transport various combinations of geophysical and radiological sensors. Currently implemented sensors include ground-penetrating radar, magnetometers, an electromagnetic induction sensor, and a sodium iodide radiation detector. The survey vehicle was constructed predominantly of non-metallic materials to minimize its effect on the operation of its geophysical sensors. The system operator controls the vehicle from a remote, truck-mounted, base station. Video images are transmitted to the base station by a radio link to give the operator necessary visual information. Vehicle control commands, tracking information, and sensor data are transmitted between the survey vehicle and the base station by means of a radio ethernet link. Precise vehicle tracking coordinates are provided by a differential Global Positioning System (GPS).

Investigation of hydrologic and biogeochemical controls on arsenic mobilization using distributed sensing at a field site in Munshiganj, Bangladesh

NASA Astrophysics Data System (ADS)

Ramanathan, N.; Estrin, D.; Harmon, T.; Harvey, C.; Jay, J.; Kohler, E.; Rothenberg, S.

2006-12-01

The presence of arsenic in the groundwater has led to the largest environmental poisoning in history; tens of millions of people in the Ganges Delta continue to drink groundwater that is dangerously contaminated with arsenic. A current working hypothesis is that arsenic is mobilized in the near surface environment where sediments are weathered by seasonal changes in the redox state that drive a cycle of pyrite oxidation and iron oxide reduction. In order to test the supporting hypothesis that subsurface geochemical changes may be induced by agricultural activity, we deployed 42 wirelessly networked ion-selective electrodes, including calcium, ammonium, nitrate, ORP, chloride, carbonate, and pH in a rice paddy in the Munshiganj district of Bangladesh in January of 2006. Each sensor was connected to an MDA300 sensor board and Mica2 wireless transceiver and computational device. Over a period of 11 days, we observed clear diel, and diurnal trends in 4 of the electrodes (calcium, ammonium, chloride and carbonate). The trends may be due to hydrological changes, or geochemical changes induced either by photosynthesis in the overlying water (which then infiltrated to the depth of the sensors) or in the root zone of rice plants. While the spatiotemporally dense measurements from wireless sensor networks enable scientists to ask new questions and elucidate complex relationships in heterogeneous physical environments such as soil, there are many practical issues to address in order to collect data usable for scientific purposes. For example, in response to a stream of faults in one of our sensor network deployments, we designed Sympathy to enable users to find and fix problems impacting the quantity of data collected in the field. Sympathy detects packet loss experienced at the base station and systematically assigns blame to faulty components in the network for remediation, replacing the prior policy of ad-hoc node rebooting and battery replacements. Sympathy has been deployed in many habitat monitoring sensor networks. While using Sympathy at our Bangladesh field site we received 80% of the sensor data expected at the base station, upon returning, post-deployment analysis revealed that 42% of these sensor data were potentially faulty. Due to the remote location of the deployment, we were unable to go back and validate the questionable segments of the data set, forcing us to discard potentially interesting information. In addition to being undesirable, this response is often avoidable as well. Even simple actions such as checking sensor connections and quickly validating sensors in the field could have increased our confidence in the quality of the data, minimizing doubts that data observations were simply caused by badly behaving hardware. To improve data quality, we have designed a system called Confidence, which continuously monitors data collected at a base-station to identify faulty data and notify the user in the field of actions they can take to validate the data or remediate the sensor fault. Augmenting a sensor network deployment with Confidence and Sympathy enables users in the identification and remediation of faults impacting the quality and quantity of data respectively.

Detection of wavelengths in the visible range using fiber optic sensors

NASA Astrophysics Data System (ADS)

Díaz, Leonardo; Morales, Yailteh; Mattos, Lorenzo; Torres, Cesar O.

2013-11-01

This paper shows the design and implementation of a fiber optic sensor for detecting and identifying wavelengths in the visible range. The system consists of a diffuse optical fiber, a conventional laser diode 650nm, 2.5mW of power, an ambient light sensor LX1972, a PIC 18F2550 and LCD screen for viewing. The principle used in the detection of the lambda is based on specular reflection and absorption. The optoelectronic device designed and built used the absorption and reflection properties of the material under study, having as active optical medium a bifurcated optical fiber, which is optically coupled to an ambient light sensor, which makes the conversion of light signals to electricas, procedure performed by a microcontroller, which acquires and processes the signal. To verify correct operation of the assembly were utilized the color cards of sewing thread and nail polish as samples for analysis. This optoelectronic device can be used in many applications such as quality control of industrial processes, classification of corks or bottle caps, color quality of textiles, sugar solutions, polymers and food among others.

A novel hydrogel electrolyte extender for rapid application of EEG sensors and extended recordings.

PubMed

Kleffner-Canucci, Killian; Luu, Phan; Naleway, John; Tucker, Don M

2012-04-30

Dense-array EEG recordings are now commonplace in research and gaining acceptance in clinical settings. Application of many sensors with traditional electrolytes is time consuming. Saline electrolytes can be used to minimize application time but recording duration is limited due to evaporation. In the present study, we evaluate a NIPAm (N-isopropyl acrylamide:acrylic acid) base electrolyte extender for use with saline electrolytes. Sensor-scalp impedances and EEG data quality acquired with the electrolyte extender are compared with those obtained for saline and an EEG electrolyte commonly used in clinical exams (Elefix). The results show that when used in conjunction with saline, electrode-scalp impedances and data across the EEG spectrum are comparable with those obtained using Elefix EEG paste. When used in conjunction with saline, the electrolyte extender permits rapid application of dense-sensor arrays and stable, high-quality EEG data to be obtained for at least 4.5 h. This is an enabling technology that will make benefits of dense-array EEG recordings practical for clinical applications. Copyright © 2011 Elsevier B.V. All rights reserved.

Phenoliner: A New Field Phenotyping Platform for Grapevine Research

PubMed Central

Kicherer, Anna; Herzog, Katja; Bendel, Nele; Klück, Hans-Christian; Backhaus, Andreas; Wieland, Markus; Klingbeil, Lasse; Läbe, Thomas; Hohl, Christian; Petry, Willi; Kuhlmann, Heiner; Seiffert, Udo; Töpfer, Reinhard

2017-01-01

In grapevine research the acquisition of phenotypic data is largely restricted to the field due to its perennial nature and size. The methodologies used to assess morphological traits and phenology are mainly limited to visual scoring. Some measurements for biotic and abiotic stress, as well as for quality assessments, are done by invasive measures. The new evolving sensor technologies provide the opportunity to perform non-destructive evaluations of phenotypic traits using different field phenotyping platforms. One of the biggest technical challenges for field phenotyping of grapevines are the varying light conditions and the background. In the present study the Phenoliner is presented, which represents a novel type of a robust field phenotyping platform. The vehicle is based on a grape harvester following the concept of a moveable tunnel. The tunnel it is equipped with different sensor systems (RGB and NIR camera system, hyperspectral camera, RTK-GPS, orientation sensor) and an artificial broadband light source. It is independent from external light conditions and in combination with artificial background, the Phenoliner enables standardised acquisition of high-quality, geo-referenced sensor data. PMID:28708080

Phenoliner: A New Field Phenotyping Platform for Grapevine Research.

PubMed

Kicherer, Anna; Herzog, Katja; Bendel, Nele; Klück, Hans-Christian; Backhaus, Andreas; Wieland, Markus; Rose, Johann Christian; Klingbeil, Lasse; Läbe, Thomas; Hohl, Christian; Petry, Willi; Kuhlmann, Heiner; Seiffert, Udo; Töpfer, Reinhard

2017-07-14

In grapevine research the acquisition of phenotypic data is largely restricted to the field due to its perennial nature and size. The methodologies used to assess morphological traits and phenology are mainly limited to visual scoring. Some measurements for biotic and abiotic stress, as well as for quality assessments, are done by invasive measures. The new evolving sensor technologies provide the opportunity to perform non-destructive evaluations of phenotypic traits using different field phenotyping platforms. One of the biggest technical challenges for field phenotyping of grapevines are the varying light conditions and the background. In the present study the Phenoliner is presented, which represents a novel type of a robust field phenotyping platform. The vehicle is based on a grape harvester following the concept of a moveable tunnel. The tunnel it is equipped with different sensor systems (RGB and NIR camera system, hyperspectral camera, RTK-GPS, orientation sensor) and an artificial broadband light source. It is independent from external light conditions and in combination with artificial background, the Phenoliner enables standardised acquisition of high-quality, geo-referenced sensor data.

Use of multiple sensor technologies for quality control of in situ biogeochemical measurements: A SeaCycler case study

NASA Astrophysics Data System (ADS)

Atamanchuk, Dariia; Koelling, Jannes; Lai, Jeremy; Send, Uwe; Wallace, Douglas

2017-04-01

Over the last two decades observing capacity for the global ocean has increased dramatically. Emerging sensor technologies for dissolved gases, nutrients and bio-optical properties in seawater are allowing extension of in situ observations beyond the traditionally measured salinity, temperature and pressure (CTD). However the effort to extend observations using autonomous instruments and platforms carries the risk of losing the level of data quality achievable through conventional water sampling techniques. We will present results from a case study with the SeaCycler profiling winch focusing on quality control of the in-situ measurements. A total of 13 sensors were deployed from May 2016 to early 2017 on SeaCycler's profiling sensor float, including CTD, dissolved oxygen (O2, 3 sensors), carbon dioxide (pCO2, 2 sensors), nutrients, velocity sensors, fluorometer, transmissometer, single channel PAR sensor, and others. We will highlight how multiple measurement technologies (e.g. for O2 and CO2) complement each other and result in a high quality data product. We will also present an initial assessment of the bio-optical data, their implications for seasonal phytoplankton dynamics and comparisons to climatologies and ocean-color data products obtained from the MODIS satellite.

Method for Optimal Sensor Deployment on 3D Terrains Utilizing a Steady State Genetic Algorithm with a Guided Walk Mutation Operator Based on the Wavelet Transform

PubMed Central

Unaldi, Numan; Temel, Samil; Asari, Vijayan K.

2012-01-01

One of the most critical issues of Wireless Sensor Networks (WSNs) is the deployment of a limited number of sensors in order to achieve maximum coverage on a terrain. The optimal sensor deployment which enables one to minimize the consumed energy, communication time and manpower for the maintenance of the network has attracted interest with the increased number of studies conducted on the subject in the last decade. Most of the studies in the literature today are proposed for two dimensional (2D) surfaces; however, real world sensor deployments often arise on three dimensional (3D) environments. In this paper, a guided wavelet transform (WT) based deployment strategy (WTDS) for 3D terrains, in which the sensor movements are carried out within the mutation phase of the genetic algorithms (GAs) is proposed. The proposed algorithm aims to maximize the Quality of Coverage (QoC) of a WSN via deploying a limited number of sensors on a 3D surface by utilizing a probabilistic sensing model and the Bresenham's line of sight (LOS) algorithm. In addition, the method followed in this paper is novel to the literature and the performance of the proposed algorithm is compared with the Delaunay Triangulation (DT) method as well as a standard genetic algorithm based method and the results reveal that the proposed method is a more powerful and more successful method for sensor deployment on 3D terrains. PMID:22666078

Impact on enzyme activity as a new quality index of wastewater.

PubMed

Balestri, Francesco; Moschini, Roberta; Cappiello, Mario; Del-Corso, Antonella; Mura, Umberto

2013-03-15

The aim of this study was to define a new indicator for the quality of wastewaters that are released into the environment. A quality index is proposed for wastewater samples in terms of the inertness of wastewater samples toward enzyme activity. This involves taking advantage of the sensitivity of enzymes to pollutants that may be present in the waste samples. The effect of wastewater samples on the rate of a number of different enzyme-catalyzed reactions was measured, and the results for all the selected enzymes were analyzed in an integrated fashion (multi-enzymatic sensor). This approach enabled us to define an overall quality index, the "Impact on Enzyme Function" (IEF-index), which is composed of three indicators: i) the Synoptic parameter, related to the average effect of the waste sample on each component of the enzymatic sensor; ii) the Peak parameter, related to the maximum effect observed among all the effects exerted by the sample on the sensor components; and, iii) the Interference parameter, related to the number of sensor components that are affected less than a fixed threshold value. A number of water based samples including public potable tap water, fluids from urban sewage systems, wastewater disposal from leather, paper and dye industries were analyzed and the IEF-index was then determined. Although the IEF-index cannot discriminate between different types of wastewater samples, it could be a useful parameter in monitoring the improvement of the quality of a specific sample. However, by analyzing an adequate number of waste samples of the same type, even from different local contexts, the profile of the impact of each component of the multi-enzymatic sensor could be typical for specific types of waste. The IEF-index is proposed as a supplementary qualification score for wastewaters, in addition to the certification of the waste's conformity to legal requirements. Copyright © 2013 Elsevier Ltd. All rights reserved.

A Quantitative Evaluation of Drive Pattern Selection for Optimizing EIT-Based Stretchable Sensors

PubMed Central

Nefti-Meziani, Samia; Carbonaro, Nicola

2017-01-01

Electrical Impedance Tomography (EIT) is a medical imaging technique that has been recently used to realize stretchable pressure sensors. In this method, voltage measurements are taken at electrodes placed at the boundary of the sensor and are used to reconstruct an image of the applied touch pressure points. The drawback with EIT-based sensors, however, is their low spatial resolution due to the ill-posed nature of the EIT reconstruction. In this paper, we show our performance evaluation of different EIT drive patterns, specifically strategies for electrode selection when performing current injection and voltage measurements. We compare voltage data with Signal-to-Noise Ratio (SNR) and Boundary Voltage Changes (BVC), and study image quality with Size Error (SE), Position Error (PE) and Ringing (RNG) parameters, in the case of one-point and two-point simultaneous contact locations. The study shows that, in order to improve the performance of EIT based sensors, the electrode selection strategies should dynamically change correspondingly to the location of the input stimuli. In fact, the selection of one drive pattern over another can improve the target size detection and position accuracy up to 4.7% and 18%, respectively. PMID:28858252

A Quantitative Evaluation of Drive Pattern Selection for Optimizing EIT-Based Stretchable Sensors.

PubMed

Russo, Stefania; Nefti-Meziani, Samia; Carbonaro, Nicola; Tognetti, Alessandro

2017-08-31

Electrical Impedance Tomography (EIT) is a medical imaging technique that has been recently used to realize stretchable pressure sensors. In this method, voltage measurements are taken at electrodes placed at the boundary of the sensor and are used to reconstruct an image of the applied touch pressure points. The drawback with EIT-based sensors, however, is their low spatial resolution due to the ill-posed nature of the EIT reconstruction. In this paper, we show our performance evaluation of different EIT drive patterns, specifically strategies for electrode selection when performing current injection and voltage measurements. We compare voltage data with Signal-to-Noise Ratio (SNR) and Boundary Voltage Changes (BVC), and study image quality with Size Error (SE), Position Error (PE) and Ringing (RNG) parameters, in the case of one-point and two-point simultaneous contact locations. The study shows that, in order to improve the performance of EIT based sensors, the electrode selection strategies should dynamically change correspondingly to the location of the input stimuli. In fact, the selection of one drive pattern over another can improve the target size detection and position accuracy up to 4.7% and 18%, respectively.

A Survey on Multimedia-Based Cross-Layer Optimization in Visual Sensor Networks

PubMed Central

Costa, Daniel G.; Guedes, Luiz Affonso

2011-01-01

Visual sensor networks (VSNs) comprised of battery-operated electronic devices endowed with low-resolution cameras have expanded the applicability of a series of monitoring applications. Those types of sensors are interconnected by ad hoc error-prone wireless links, imposing stringent restrictions on available bandwidth, end-to-end delay and packet error rates. In such context, multimedia coding is required for data compression and error-resilience, also ensuring energy preservation over the path(s) toward the sink and improving the end-to-end perceptual quality of the received media. Cross-layer optimization may enhance the expected efficiency of VSNs applications, disrupting the conventional information flow of the protocol layers. When the inner characteristics of the multimedia coding techniques are exploited by cross-layer protocols and architectures, higher efficiency may be obtained in visual sensor networks. This paper surveys recent research on multimedia-based cross-layer optimization, presenting the proposed strategies and mechanisms for transmission rate adjustment, congestion control, multipath selection, energy preservation and error recovery. We note that many multimedia-based cross-layer optimization solutions have been proposed in recent years, each one bringing a wealth of contributions to visual sensor networks. PMID:22163908

A design of wireless sensor networks for a power quality monitoring system.

PubMed

Lim, Yujin; Kim, Hak-Man; Kang, Sanggil

2010-01-01

Power grids deal with the business of generation, transmission, and distribution of electric power. Recently, interest in power quality in electrical distribution systems has increased rapidly. In Korea, the communication network to deliver voltage, current, and temperature measurements gathered from pole transformers to remote monitoring centers employs cellular mobile technology. Due to high cost of the cellular mobile technology, power quality monitoring measurements are limited and data gathering intervals are large. This causes difficulties in providing the power quality monitoring service. To alleviate the problems, in this paper we present a communication infrastructure to provide low cost, reliable data delivery. The communication infrastructure consists of wired connections between substations and monitoring centers, and wireless connections between pole transformers and substations. For the wireless connection, we employ a wireless sensor network and design its corresponding data forwarding protocol to improve the quality of data delivery. For the design, we adopt a tree-based data forwarding protocol in order to customize the distribution pattern of the power quality information. We verify the performance of the proposed data forwarding protocol quantitatively using the NS-2 network simulator.

Energy efficient mechanisms for high-performance Wireless Sensor Networks

NASA Astrophysics Data System (ADS)

Alsaify, Baha'adnan

2009-12-01

Due to recent advances in microelectronics, the development of low cost, small, and energy efficient devices became possible. Those advances led to the birth of the Wireless Sensor Networks (WSNs). WSNs consist of a large set of sensor nodes equipped with communication capabilities, scattered in the area to monitor. Researchers focus on several aspects of WSNs. Such aspects include the quality of service the WSNs provide (data delivery delay, accuracy of data, etc...), the scalability of the network to contain thousands of sensor nodes (the terms node and sensor node are being used interchangeably), the robustness of the network (allowing the network to work even if a certain percentage of nodes fails), and making the energy consumption in the network as low as possible to prolong the network's lifetime. In this thesis, we present an approach that can be applied to the sensing devices that are scattered in an area for Sensor Networks. This work will use the well-known approach of using a awaking scheduling to extend the network's lifespan. We designed a scheduling algorithm that will reduce the delay's upper bound the reported data will experience, while at the same time keeps the advantages that are offered by the use of the awaking scheduling -- the energy consumption reduction which will lead to the increase in the network's lifetime. The wakeup scheduling is based on the location of the node relative to its neighbors and its distance from the Base Station (the terms Base Station and sink are being used interchangeably). We apply the proposed method to a set of simulated nodes using the "ONE Simulator". We test the performance of this approach with three other approaches -- Direct Routing technique, the well known LEACH algorithm, and a multi-parent scheduling algorithm. We demonstrate a good improvement on the network's quality of service and a reduction of the consumed energy.

Automatic Multi-sensor Data Quality Checking and Event Detection for Environmental Sensing

NASA Astrophysics Data System (ADS)

LIU, Q.; Zhang, Y.; Zhao, Y.; Gao, D.; Gallaher, D. W.; Lv, Q.; Shang, L.

2017-12-01

With the advances in sensing technologies, large-scale environmental sensing infrastructures are pervasively deployed to continuously collect data for various research and application fields, such as air quality study and weather condition monitoring. In such infrastructures, many sensor nodes are distributed in a specific area and each individual sensor node is capable of measuring several parameters (e.g., humidity, temperature, and pressure), providing massive data for natural event detection and analysis. However, due to the dynamics of the ambient environment, sensor data can be contaminated by errors or noise. Thus, data quality is still a primary concern for scientists before drawing any reliable scientific conclusions. To help researchers identify potential data quality issues and detect meaningful natural events, this work proposes a novel algorithm to automatically identify and rank anomalous time windows from multiple sensor data streams. More specifically, (1) the algorithm adaptively learns the characteristics of normal evolving time series and (2) models the spatial-temporal relationship among multiple sensor nodes to infer the anomaly likelihood of a time series window for a particular parameter in a sensor node. Case studies using different data sets are presented and the experimental results demonstrate that the proposed algorithm can effectively identify anomalous time windows, which may resulted from data quality issues and natural events.

Stability-Aware Geographic Routing in Energy Harvesting Wireless Sensor Networks

PubMed Central

Hieu, Tran Dinh; Dung, Le The; Kim, Byung-Seo

2016-01-01

A new generation of wireless sensor networks that harvest energy from environmental sources such as solar, vibration, and thermoelectric to power sensor nodes is emerging to solve the problem of energy limitation. Based on the photo-voltaic model, this research proposes a stability-aware geographic routing for reliable data transmissions in energy-harvesting wireless sensor networks (EH-WSNs) to provide a reliable routes selection method and potentially achieve an unlimited network lifetime. Specifically, the influences of link quality, represented by the estimated packet reception rate, on network performance is investigated. Simulation results show that the proposed method outperforms an energy-harvesting-aware method in terms of energy consumption, the average number of hops, and the packet delivery ratio. PMID:27187414

A New Calibration Method for Commercial RGB-D Sensors

PubMed Central

Darwish, Walid; Tang, Shenjun; Li, Wenbin; Chen, Wu

2017-01-01

Commercial RGB-D sensors such as Kinect and Structure Sensors have been widely used in the game industry, where geometric fidelity is not of utmost importance. For applications in which high quality 3D is required, i.e., 3D building models of centimeter-level accuracy, accurate and reliable calibrations of these sensors are required. This paper presents a new model for calibrating the depth measurements of RGB-D sensors based on the structured light concept. Additionally, a new automatic method is proposed for the calibration of all RGB-D parameters, including internal calibration parameters for all cameras, the baseline between the infrared and RGB cameras, and the depth error model. When compared with traditional calibration methods, this new model shows a significant improvement in depth precision for both near and far ranges. PMID:28538695

Manufacture and application of RuO2 solid-state metal-oxide pH sensor to common beverages.

PubMed

Lonsdale, W; Wajrak, M; Alameh, K

2018-04-01

A new reproducible solid-state metal-oxide pH sensor for beverage quality monitoring is developed and characterised. The working electrode of the developed pH sensor is based on the use of laser-etched sputter-deposited RuO 2 on Al 2 O 3 substrate, modified with thin layers of sputter-deposited Ta 2 O 5 and drop-cast Nafion for minimisation of redox interference. The reference electrode is manufactured by further modifying a working electrode with a porous polyvinyl butyral layer loaded with fumed SiO 2 . The developed pH sensor shows excellent performance when applied to a selection of beverage samples, with a measured accuracy within 0.08 pH of a commercial glass pH sensor. Copyright © 2017 Elsevier B.V. All rights reserved.

First Experiences with Kinect v2 Sensor for Close Range 3d Modelling

NASA Astrophysics Data System (ADS)

Lachat, E.; Macher, H.; Mittet, M.-A.; Landes, T.; Grussenmeyer, P.

2015-02-01

RGB-D cameras, also known as range imaging cameras, are a recent generation of sensors. As they are suitable for measuring distances to objects at high frame rate, such sensors are increasingly used for 3D acquisitions, and more generally for applications in robotics or computer vision. This kind of sensors became popular especially since the Kinect v1 (Microsoft) arrived on the market in November 2010. In July 2014, Windows has released a new sensor, the Kinect for Windows v2 sensor, based on another technology as its first device. However, due to its initial development for video games, the quality assessment of this new device for 3D modelling represents a major investigation axis. In this paper first experiences with Kinect v2 sensor are related, and the ability of close range 3D modelling is investigated. For this purpose, error sources on output data as well as a calibration approach are presented.

Sleep state classification using pressure sensor mats.

PubMed

Baran Pouyan, M; Nourani, M; Pompeo, M

2015-08-01

Sleep state detection is valuable in assessing patient's sleep quality and in-bed general behavior. In this paper, a novel classification approach of sleep states (sleep, pre-wake, wake) is proposed that uses only surface pressure sensors. In our method, a mobility metric is defined based on successive pressure body maps. Then, suitable statistical features are computed based on the mobility metric. Finally, a customized random forest classifier is employed to identify various classes including a new class for pre-wake state. Our algorithm achieves 96.1% and 88% accuracies for two (sleep, wake) and three (sleep, pre-wake, wake) class identification, respectively.

Biometric image enhancement using decision rule based image fusion techniques

NASA Astrophysics Data System (ADS)

Sagayee, G. Mary Amirtha; Arumugam, S.

2010-02-01

Introducing biometrics into information systems may result in considerable benefits. Most of the researchers confirmed that the finger print is widely used than the iris or face and more over it is the primary choice for most privacy concerned applications. For finger prints applications, choosing proper sensor is at risk. The proposed work deals about, how the image quality can be improved by introducing image fusion technique at sensor levels. The results of the images after introducing the decision rule based image fusion technique are evaluated and analyzed with its entropy levels and root mean square error.

The rational development of molecularly imprinted polymer-based sensors for protein detection.

PubMed

Whitcombe, Michael J; Chianella, Iva; Larcombe, Lee; Piletsky, Sergey A; Noble, James; Porter, Robert; Horgan, Adrian

2011-03-01

The detection of specific proteins as biomarkers of disease, health status, environmental monitoring, food quality, control of fermenters and civil defence purposes means that biosensors for these targets will become increasingly more important. Among the technologies used for building specific recognition properties, molecularly imprinted polymers (MIPs) are attracting much attention. In this critical review we describe many methods used for imprinting recognition for protein targets in polymers and their incorporation with a number of transducer platforms with the aim of identifying the most promising approaches for the preparation of MIP-based protein sensors (277 references).

Energy efficient wireless sensor networks by using a fuzzy-based solution

NASA Astrophysics Data System (ADS)

Tirrito, Salvatore; Nicolosi, Giuseppina

2016-12-01

Wireless Sensor Networks are characterized by a distributed architecture realized by a set of autonomous electronic devices able to sense data from the surrounding environment and to communicate among them. These devices are battery powered since they may be used even to monitor hazardous events in inaccessible areas. As a consequence, it is preferable to assure the adoption of energy management solutions in order to extend the WSN lifetime, as far as possible. Moreover, it is crucial to guarantee that the nodes receive the transmitted data correctly. It is clear that trading off power optimization and quality of service has become one the most important concerns when dealing with modern systems based on WSNs. This paper introduces a solution based on a Fuzzy Logic Controller (FLC) focusing on the minimization of energy consumption of wireless sensor nodes. This is made possible because the sleeping time of these nodes is dynamically regulated by a FLC.

Wafer-scale epitaxial graphene on SiC for sensing applications

NASA Astrophysics Data System (ADS)

Karlsson, Mikael; Wang, Qin; Zhao, Yichen; Zhao, Wei; Toprak, Muhammet S.; Iakimov, Tihomir; Ali, Amer; Yakimova, Rositza; Syväjärvi, Mikael; Ivanov, Ivan G.

2015-12-01

The epitaxial graphene-on-silicon carbide (SiC-G) has advantages of high quality and large area coverage owing to a natural interface between graphene and SiC substrate with dimension up to 100 mm. It enables cost effective and reliable solutions for bridging the graphene-based sensors/devices from lab to industrial applications and commercialization. In this work, the structural, optical and electrical properties of wafer-scale graphene grown on 2'' 4H semi-insulating (SI) SiC utilizing sublimation process were systemically investigated with focus on evaluation of the graphene's uniformity across the wafer. As proof of concept, two types of glucose sensors based on SiC-G/Nafion/Glucose-oxidase (GOx) and SiC-G/Nafion/Chitosan/GOx were fabricated and their electrochemical properties were characterized by cyclic voltammetry (CV) measurements. In addition, a few similar glucose sensors based on graphene by chemical synthesis using modified Hummer's method were also fabricated for comparison.

Biomedical sensing analyzer (BSA) for mobile-health (mHealth)-LTE.

PubMed

Adibi, Sasan

2014-01-01

The rapid expansion of mobile-based systems, the capabilities of smartphone devices, as well as the radio access and cellular network technologies are the wind beneath the wing of mobile health (mHealth). In this paper, the concept of biomedical sensing analyzer (BSA) is presented, which is a novel framework, devised for sensor-based mHealth applications. The BSA is capable of formulating the Quality of Service (QoS) measurements in an end-to-end sense, covering the entire communication path (wearable sensors, link-technology, smartphone, cell-towers, mobile-cloud, and the end-users). The characterization and formulation of BSA depend on a number of factors, including the deployment of application-specific biomedical sensors, generic link-technologies, collection, aggregation, and prioritization of mHealth data, cellular network based on the Long-Term Evolution (LTE) access technology, and extensive multidimensional delay analyses. The results are studied and analyzed in a LabView 8.5 programming environment.

An Uncertainty-Based Distributed Fault Detection Mechanism for Wireless Sensor Networks

PubMed Central

Yang, Yang; Gao, Zhipeng; Zhou, Hang; Qiu, Xuesong

2014-01-01

Exchanging too many messages for fault detection will cause not only a degradation of the network quality of service, but also represents a huge burden on the limited energy of sensors. Therefore, we propose an uncertainty-based distributed fault detection through aided judgment of neighbors for wireless sensor networks. The algorithm considers the serious influence of sensing measurement loss and therefore uses Markov decision processes for filling in missing data. Most important of all, fault misjudgments caused by uncertainty conditions are the main drawbacks of traditional distributed fault detection mechanisms. We draw on the experience of evidence fusion rules based on information entropy theory and the degree of disagreement function to increase the accuracy of fault detection. Simulation results demonstrate our algorithm can effectively reduce communication energy overhead due to message exchanges and provide a higher detection accuracy ratio. PMID:24776937

Design and numerical analysis of highly sensitive Au-MoS2-graphene based hybrid surface plasmon resonance biosensor

NASA Astrophysics Data System (ADS)

Rahman, M. Saifur; Anower, Md. Shamim; Hasan, Md. Rabiul; Hossain, Md. Biplob; Haque, Md. Ismail

2017-08-01

We demonstrate a highly sensitive Au-MoS2-Graphene based hybrid surface plasmon resonance (SPR) biosensor for the detection of DNA hybridization. The performance parameters of the proposed sensor are investigated in terms of sensitivity, detection accuracy and quality factor at operating wavelength of 633 nm. We observed in the numerical study that sensitivity can be greatly increased by adding MoS2 layer in the middle of a Graphene-on-Au layer. It is shown that by using single layer of MoS2 in between gold and graphene layer, the proposed biosensor exhibits simultaneously high sensitivity of 87.8 deg/RIU, high detection accuracy of 1.28 and quality factor of 17.56 with gold layer thickness of 50 nm. This increased performance is due to the absorption ability and optical characteristics of graphene biomolecules and high fluorescence quenching ability of MoS2. On the basis of changing in SPR angle and minimum reflectance, the proposed sensor can sense nucleotides bonding happened between double-stranded DNA (dsDNA) helix structures. Therefore, this sensor can successfully detect the hybridization of target DNAs to the probe DNAs pre-immobilized on the Au-MoS2-Graphene hybrid with capability of distinguishing single-base mismatch.

Assurance of energy efficiency and data security for ECG transmission in BASNs.

PubMed

Ma, Tao; Shrestha, Pradhumna Lal; Hempel, Michael; Peng, Dongming; Sharif, Hamid; Chen, Hsiao-Hwa

2012-04-01

With the technological advancement in body area sensor networks (BASNs), low cost high quality electrocardiographic (ECG) diagnosis systems have become important equipment for healthcare service providers. However, energy consumption and data security with ECG systems in BASNs are still two major challenges to tackle. In this study, we investigate the properties of compressed ECG data for energy saving as an effort to devise a selective encryption mechanism and a two-rate unequal error protection (UEP) scheme. The proposed selective encryption mechanism provides a simple and yet effective security solution for an ECG sensor-based communication platform, where only one percent of data is encrypted without compromising ECG data security. This part of the encrypted data is essential to ECG data quality due to its unequally important contribution to distortion reduction. The two-rate UEP scheme achieves a significant additional energy saving due to its unequal investment of communication energy to the outcomes of the selective encryption, and thus, it maintains a high ECG data transmission quality. Our results show the improvements in communication energy saving of about 40%, and demonstrate a higher transmission quality and security measured in terms of wavelet-based weighted percent root-mean-squared difference.

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

Impact Analysis of Temperature and Humidity Conditions on Electrochemical Sensor Response in Ambient Air Quality Monitoring

PubMed Central

Ning, Zhi; Ye, Sheng; Sun, Li; Yang, Fenhuan; Wong, Ka Chun; Westerdahl, Dane; Louie, Peter K. K.

2018-01-01

The increasing applications of low-cost air sensors promises more convenient and cost-effective systems for air monitoring in many places and under many conditions. However, the data quality from such systems has not been fully characterized and may not meet user expectations in research and regulatory uses, or for use in citizen science. In our study, electrochemical sensors (Alphasense B4 series) for carbon monoxide (CO), nitric oxide (NO), nitrogen dioxide (NO2), and oxidants (Ox) were evaluated under controlled laboratory conditions to identify the influencing factors and quantify their relation with sensor outputs. Based on the laboratory tests, we developed different correction methods to compensate for the impact of ambient conditions. Further, the sensors were assembled into a monitoring system and tested in ambient conditions in Hong Kong side-by-side with regulatory reference monitors, and data from these tests were used to evaluate the performance of the models, to refine them, and validate their applicability in variable ambient conditions in the field. The more comprehensive correction models demonstrated enhanced performance when compared with uncorrected data. One over-arching observation of this study is that the low-cost sensors may promise excellent sensitivity and performance, but it is essential for users to understand and account for several key factors that may strongly affect the nature of sensor data. In this paper, we also evaluated factors of multi-month stability, temperature, and humidity, and considered the interaction of oxidant gases NO2 and ozone on a newly introduced oxidant sensor. PMID:29360749

Impact Analysis of Temperature and Humidity Conditions on Electrochemical Sensor Response in Ambient Air Quality Monitoring.

PubMed

Wei, Peng; Ning, Zhi; Ye, Sheng; Sun, Li; Yang, Fenhuan; Wong, Ka Chun; Westerdahl, Dane; Louie, Peter K K

2018-01-23

The increasing applications of low-cost air sensors promises more convenient and cost-effective systems for air monitoring in many places and under many conditions. However, the data quality from such systems has not been fully characterized and may not meet user expectations in research and regulatory uses, or for use in citizen science. In our study, electrochemical sensors (Alphasense B4 series) for carbon monoxide (CO), nitric oxide (NO), nitrogen dioxide (NO₂), and oxidants (O x ) were evaluated under controlled laboratory conditions to identify the influencing factors and quantify their relation with sensor outputs. Based on the laboratory tests, we developed different correction methods to compensate for the impact of ambient conditions. Further, the sensors were assembled into a monitoring system and tested in ambient conditions in Hong Kong side-by-side with regulatory reference monitors, and data from these tests were used to evaluate the performance of the models, to refine them, and validate their applicability in variable ambient conditions in the field. The more comprehensive correction models demonstrated enhanced performance when compared with uncorrected data. One over-arching observation of this study is that the low-cost sensors may promise excellent sensitivity and performance, but it is essential for users to understand and account for several key factors that may strongly affect the nature of sensor data. In this paper, we also evaluated factors of multi-month stability, temperature, and humidity, and considered the interaction of oxidant gases NO₂ and ozone on a newly introduced oxidant sensor.

Using a gradient boosting model to improve the performance of low-cost aerosol monitors in a dense, heterogeneous urban environment

NASA Astrophysics Data System (ADS)

Johnson, Nicholas E.; Bonczak, Bartosz; Kontokosta, Constantine E.

2018-07-01

The increased availability and improved quality of new sensing technologies have catalyzed a growing body of research to evaluate and leverage these tools in order to quantify and describe urban environments. Air quality, in particular, has received greater attention because of the well-established links to serious respiratory illnesses and the unprecedented levels of air pollution in developed and developing countries and cities around the world. Though numerous laboratory and field evaluation studies have begun to explore the use and potential of low-cost air quality monitoring devices, the performance and stability of these tools has not been adequately evaluated in complex urban environments, and further research is needed. In this study, we present the design of a low-cost air quality monitoring platform based on the Shinyei PPD42 aerosol monitor and examine the suitability of the sensor for deployment in a dense heterogeneous urban environment. We assess the sensor's performance during a field calibration campaign from February 7th to March 25th 2017 with a reference instrument in New York City, and present a novel calibration approach using a machine learning method that incorporates publicly available meteorological data in order to improve overall sensor performance. We find that while the PPD42 performs well in relation to the reference instrument using linear regression (R2 = 0.36-0.51), a gradient boosting regression tree model can significantly improve device calibration (R2 = 0.68-0.76). We discuss the sensor's performance and reliability when deployed in a dense, heterogeneous urban environment during a period of significant variation in weather conditions, and important considerations when using machine learning techniques to improve the performance of low-cost air quality monitors.

A real-time automated quality control of rain gauge data based on multiple sensors

NASA Astrophysics Data System (ADS)

qi, Y.; Zhang, J.

2013-12-01

Precipitation is one of the most important meteorological and hydrological variables. Automated rain gauge networks provide direct measurements of precipitation and have been used for numerous applications such as generating regional and national precipitation maps, calibrating remote sensing data, and validating hydrological and meteorological model predictions. Automated gauge observations are prone to a variety of error sources (instrument malfunction, transmission errors, format changes), and require careful quality controls (QC). Many previous gauge QC techniques were based on neighborhood checks within the gauge network itself and the effectiveness is dependent on gauge densities and precipitation regimes. The current study takes advantage of the multi-sensor data sources in the National Mosaic and Multi-Sensor QPE (NMQ/Q2) system and developes an automated gauge QC scheme based the consistency of radar hourly QPEs and gauge observations. Error characteristics of radar and gauge as a function of the radar sampling geometry, precipitation regimes, and the freezing level height are considered. The new scheme was evaluated by comparing an NMQ national gauge-based precipitation product with independent manual gauge observations. Twelve heavy rainfall events from different seasons and areas of the United States are selected for the evaluation, and the results show that the new NMQ product with QC'ed gauges has a more physically spatial distribution than the old product. And the new product agrees much better statistically with the independent gauges.

Photonic textiles for pulse oximetry.

PubMed

Rothmaier, Markus; Selm, Bärbel; Spichtig, Sonja; Haensse, Daniel; Wolf, Martin

2008-08-18

Biomedical sensors, integrated into textiles would enable monitoring of many vitally important physiological parameters during our daily life. In this paper we demonstrate the design and performance of a textile based pulse oximeter, operating on the forefinger tip in transmission mode. The sensors consisted of plastic optical fibers integrated into common fabrics. To emit light to the human tissue and to collect transmitted light the fibers were either integrated into a textile substrate by embroidery (producing microbends with a nominal diameter of 0.5 to 2 mm) or the fibers inside woven patterns have been altered mechanically after fabric production. In our experiments we used a two-wavelength approach (690 and 830 nm) for pulse wave acquisition and arterial oxygen saturation calculation. We have fabricated different specimens to study signal yield and quality, and a cotton glove, equipped with textile based light emitter and detector, has been used to examine movement artifacts. Our results show that textile-based oximetry is feasible with sufficient data quality and its potential as a wearable health monitoring device is promising.

System approach to distributed sensor management

NASA Astrophysics Data System (ADS)

Mayott, Gregory; Miller, Gordon; Harrell, John; Hepp, Jared; Self, Mid

2010-04-01

Since 2003, the US Army's RDECOM CERDEC Night Vision Electronic Sensor Directorate (NVESD) has been developing a distributed Sensor Management System (SMS) that utilizes a framework which demonstrates application layer, net-centric sensor management. The core principles of the design support distributed and dynamic discovery of sensing devices and processes through a multi-layered implementation. This results in a sensor management layer that acts as a System with defined interfaces for which the characteristics, parameters, and behaviors can be described. Within the framework, the definition of a protocol is required to establish the rules for how distributed sensors should operate. The protocol defines the behaviors, capabilities, and message structures needed to operate within the functional design boundaries. The protocol definition addresses the requirements for a device (sensors or processes) to dynamically join or leave a sensor network, dynamically describe device control and data capabilities, and allow dynamic addressing of publish and subscribe functionality. The message structure is a multi-tiered definition that identifies standard, extended, and payload representations that are specifically designed to accommodate the need for standard representations of common functions, while supporting the need for feature-based functions that are typically vendor specific. The dynamic qualities of the protocol enable a User GUI application the flexibility of mapping widget-level controls to each device based on reported capabilities in real-time. The SMS approach is designed to accommodate scalability and flexibility within a defined architecture. The distributed sensor management framework and its application to a tactical sensor network will be described in this paper.

Learn on the Fly: Quiescent Routing in Wireless Sensor Networks

DTIC Science & Technology

2005-02-01

quality solely based on data traf- fic without employing beacons. Using a realistic sensor network traffic trace and an 802.11b testbed of 195 Stargates ...testbed of 195 Stargates [1] with 802.11b radios. For instance, we investigate the validity of geographic uniformity which is assumed in literature [19...Figure 1), we deploy 29 Stargates in a straight line, with a 45-meter separation between any two consecutive Stargates . The Stargates run Linux with

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

PubMed Central

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

2010-01-01

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

Fuzzy Logic Control Based QoS Management in Wireless Sensor/Actuator Networks

PubMed Central

Xia, Feng; Zhao, Wenhong; Sun, Youxian; Tian, Yu-Chu

2007-01-01

Wireless sensor/actuator networks (WSANs) are emerging rapidly as a new generation of sensor networks. Despite intensive research in wireless sensor networks (WSNs), limited work has been found in the open literature in the field of WSANs. In particular, quality-of-service (QoS) management in WSANs remains an important issue yet to be investigated. As an attempt in this direction, this paper develops a fuzzy logic control based QoS management (FLC-QM) scheme for WSANs with constrained resources and in dynamic and unpredictable environments. Taking advantage of the feedback control technology, this scheme deals with the impact of unpredictable changes in traffic load on the QoS of WSANs. It utilizes a fuzzy logic controller inside each source sensor node to adapt sampling period to the deadline miss ratio associated with data transmission from the sensor to the actuator. The deadline miss ratio is maintained at a pre-determined desired level so that the required QoS can be achieved. The FLC-QM has the advantages of generality, scalability, and simplicity. Simulation results show that the FLC-QM can provide WSANs with QoS support. PMID:28903288

A Max-Flow Based Algorithm for Connected Target Coverage with Probabilistic Sensors

PubMed Central

Shan, Anxing; Xu, Xianghua; Cheng, Zongmao; Wang, Wensheng

2017-01-01

Coverage is a fundamental issue in the research field of wireless sensor networks (WSNs). Connected target coverage discusses the sensor placement to guarantee the needs of both coverage and connectivity. Existing works largely leverage on the Boolean disk model, which is only a coarse approximation to the practical sensing model. In this paper, we focus on the connected target coverage issue based on the probabilistic sensing model, which can characterize the quality of coverage more accurately. In the probabilistic sensing model, sensors are only be able to detect a target with certain probability. We study the collaborative detection probability of target under multiple sensors. Armed with the analysis of collaborative detection probability, we further formulate the minimum ϵ-connected target coverage problem, aiming to minimize the number of sensors satisfying the requirements of both coverage and connectivity. We map it into a flow graph and present an approximation algorithm called the minimum vertices maximum flow algorithm (MVMFA) with provable time complex and approximation ratios. To evaluate our design, we analyze the performance of MVMFA theoretically and also conduct extensive simulation studies to demonstrate the effectiveness of our proposed algorithm. PMID:28587084

A Max-Flow Based Algorithm for Connected Target Coverage with Probabilistic Sensors.

PubMed

Shan, Anxing; Xu, Xianghua; Cheng, Zongmao; Wang, Wensheng

2017-05-25

Coverage is a fundamental issue in the research field of wireless sensor networks (WSNs). Connected target coverage discusses the sensor placement to guarantee the needs of both coverage and connectivity. Existing works largely leverage on the Boolean disk model, which is only a coarse approximation to the practical sensing model. In this paper, we focus on the connected target coverage issue based on the probabilistic sensing model, which can characterize the quality of coverage more accurately. In the probabilistic sensing model, sensors are only be able to detect a target with certain probability. We study the collaborative detection probability of target under multiple sensors. Armed with the analysis of collaborative detection probability, we further formulate the minimum ϵ -connected target coverage problem, aiming to minimize the number of sensors satisfying the requirements of both coverage and connectivity. We map it into a flow graph and present an approximation algorithm called the minimum vertices maximum flow algorithm (MVMFA) with provable time complex and approximation ratios. To evaluate our design, we analyze the performance of MVMFA theoretically and also conduct extensive simulation studies to demonstrate the effectiveness of our proposed algorithm.

Maximization of the Supportable Number of Sensors in QoS-Aware Cluster-Based Underwater Acoustic Sensor Networks

PubMed Central

Nguyen, Thi-Tham; Van Le, Duc; Yoon, Seokhoon

2014-01-01

This paper proposes a practical low-complexity MAC (medium access control) scheme for quality of service (QoS)-aware and cluster-based underwater acoustic sensor networks (UASN), in which the provision of differentiated QoS is required. In such a network, underwater sensors (U-sensor) in a cluster are divided into several classes, each of which has a different QoS requirement. The major problem considered in this paper is the maximization of the number of nodes that a cluster can accommodate while still providing the required QoS for each class in terms of the PDR (packet delivery ratio). In order to address the problem, we first estimate the packet delivery probability (PDP) and use it to formulate an optimization problem to determine the optimal value of the maximum packet retransmissions for each QoS class. The custom greedy and interior-point algorithms are used to find the optimal solutions, which are verified by extensive simulations. The simulation results show that, by solving the proposed optimization problem, the supportable number of underwater sensor nodes can be maximized while satisfying the QoS requirements for each class. PMID:24608009

Maximization of the supportable number of sensors in QoS-aware cluster-based underwater acoustic sensor networks.

PubMed

Nguyen, Thi-Tham; Le, Duc Van; Yoon, Seokhoon

2014-03-07

This paper proposes a practical low-complexity MAC (medium access control) scheme for quality of service (QoS)-aware and cluster-based underwater acoustic sensor networks (UASN), in which the provision of differentiated QoS is required. In such a network, underwater sensors (U-sensor) in a cluster are divided into several classes, each of which has a different QoS requirement. The major problem considered in this paper is the maximization of the number of nodes that a cluster can accommodate while still providing the required QoS for each class in terms of the PDR (packet delivery ratio). In order to address the problem, we first estimate the packet delivery probability (PDP) and use it to formulate an optimization problem to determine the optimal value of the maximum packet retransmissions for each QoS class. The custom greedy and interior-point algorithms are used to find the optimal solutions, which are verified by extensive simulations. The simulation results show that, by solving the proposed optimization problem, the supportable number of underwater sensor nodes can be maximized while satisfying the QoS requirements for each class.

Surface roughness model based on force sensors for the prediction of the tool wear.

PubMed

de Agustina, Beatriz; Rubio, Eva María; Sebastián, Miguel Ángel

2014-04-04

In this study, a methodology has been developed with the objective of evaluating the surface roughness obtained during turning processes by measuring the signals detected by a force sensor under the same cutting conditions. In this way, the surface quality achieved along the process is correlated to several parameters of the cutting forces (thrust forces, feed forces and cutting forces), so the effect that the tool wear causes on the surface roughness is evaluated. In a first step, the best cutting conditions (cutting parameters and radius of tool) for a certain quality surface requirement were found for pieces of UNS A97075. Next, with this selection a model of surface roughness based on the cutting forces was developed for different states of wear that simulate the behaviour of the tool throughout its life. The validation of this model reveals that it was effective for approximately 70% of the surface roughness values obtained.

Indoor air quality analysis based on Hadoop

NASA Astrophysics Data System (ADS)

Tuo, Wang; Yunhua, Sun; Song, Tian; Liang, Yu; Weihong, Cui

2014-03-01

The air of the office environment is our research object. The data of temperature, humidity, concentrations of carbon dioxide, carbon monoxide and ammonia are collected peer one to eight seconds by the sensor monitoring system. And all the data are stored in the Hbase database of Hadoop platform. With the help of HBase feature of column-oriented store and versioned (automatically add the time column), the time-series data sets are bulit based on the primary key Row-key and timestamp. The parallel computing programming model MapReduce is used to process millions of data collected by sensors. By analysing the changing trend of parameters' value at different time of the same day and at the same time of various dates, the impact of human factor and other factors on the room microenvironment is achieved according to the liquidity of the office staff. Moreover, the effective way to improve indoor air quality is proposed in the end of this paper.

Interpreting Mobile and Handheld Air Sensor Readings in Relation to Air Quality Standards and Health Effect Reference Values: Tackling the Challenges.

PubMed

Woodall, George M; Hoover, Mark D; Williams, Ronald; Benedict, Kristen; Harper, Martin; Soo, Jhy-Charm; Jarabek, Annie M; Stewart, Michael J; Brown, James S; Hulla, Janis E; Caudill, Motria; Clements, Andrea L; Kaufman, Amanda; Parker, Alison J; Keating, Martha; Balshaw, David; Garrahan, Kevin; Burton, Laureen; Batka, Sheila; Limaye, Vijay S; Hakkinen, Pertti J; Thompson, Bob

2017-01-01

The US Environmental Protection Agency (EPA) and other federal agencies face a number of challenges in interpreting and reconciling short-duration (seconds to minutes) readings from mobile and handheld air sensors with the longer duration averages (hours to days) associated with the National Ambient Air Quality Standards (NAAQS) for the criteria pollutants-particulate matter (PM), ozone, carbon monoxide, lead, nitrogen oxides, and sulfur oxides. Similar issues are equally relevant to the hazardous air pollutants (HAPs) where chemical-specific health effect reference values are the best indicators of exposure limits; values which are often based on a lifetime of continuous exposure. A multi-agency, staff-level Air Sensors Health Group (ASHG) was convened in 2013. ASHG represents a multi-institutional collaboration of Federal agencies devoted to discovery and discussion of sensor technologies, interpretation of sensor data, defining the state of sensor-related science across each institution, and provides consultation on how sensors might effectively be used to meet a wide range of research and decision support needs. ASHG focuses on several fronts: improving the understanding of what hand-held sensor technologies may be able to deliver; communicating what hand-held sensor readings can provide to a number of audiences; the challenges of how to integrate data generated by multiple entities using new and unproven technologies; and defining best practices in communicating health-related messages to various audiences. This review summarizes the challenges, successes, and promising tools of those initial ASHG efforts and Federal agency progress on crafting similar products for use with other NAAQS pollutants and the HAPs. NOTE: The opinions expressed are those of the authors and do not necessary represent the opinions of their Federal Agencies or the US Government. Mention of product names does not constitute endorsement.

A micro-vibration generated method for testing the imaging quality on ground of space remote sensing

NASA Astrophysics Data System (ADS)

Gu, Yingying; Wang, Li; Wu, Qingwen

2018-03-01

In this paper, a novel method is proposed, which can simulate satellite platform micro-vibration and test the impact of satellite micro-vibration on imaging quality of space optical remote sensor on ground. The method can generate micro-vibration of satellite platform in orbit from vibrational degrees of freedom, spectrum, magnitude, and coupling path. Experiment results show that the relative error of acceleration control is within 7%, in frequencies from 7Hz to 40Hz. Utilizing this method, the system level test about the micro-vibration impact on imaging quality of space optical remote sensor can be realized. This method will have an important applications in testing micro-vibration tolerance margin of optical remote sensor, verifying vibration isolation and suppression performance of optical remote sensor, exploring the principle of micro-vibration impact on imaging quality of optical remote sensor.

Mobile and static sensors in a citizen-based observatory of water

NASA Astrophysics Data System (ADS)

Brauchli, Tristan; Weijs, Steven V.; Lehning, Michael; Huwald, Hendrik

2014-05-01

Understanding and forecasting water resources and components of the water cycle require spatially and temporally resolved observations of numerous water-related variables. Such observations are often obtained from wireless networks of automated weather stations. The "WeSenseIt" project develops a citizen- and community-based observatory of water to improve the water and risk management at the catchment scale and to support decision-making of stakeholders. It is implemented in three case studies addressing various questions related to flood, drought, water resource management, water quality and pollution. Citizens become potential observers and may transmit water-related measurements and information. Combining the use of recent technologies (wireless communication, internet, smartphone) with the development of innovative low cost sensors enables the implementation of heterogeneous observatories, which (a) empower citizens and (b) expand and complement traditional operational sensing networks. With the goal of increasing spatial coverage of observations and decreasing cost for sensors, this study presents the examples of measuring (a) flow velocity in streams using smartphones and (b) sensible heat flux using simple sensors at the nodes of wireless sensor networks.

A Movement-Assisted Deployment of Collaborating Autonomous Sensors for Indoor and Outdoor Environment Monitoring

PubMed Central

Niewiadomska-Szynkiewicz, Ewa; Sikora, Andrzej; Marks, Michał

2016-01-01

Using mobile robots or unmanned vehicles to assist optimal wireless sensors deployment in a working space can significantly enhance the capability to investigate unknown environments. This paper addresses the issues of the application of numerical optimization and computer simulation techniques to on-line calculation of a wireless sensor network topology for monitoring and tracking purposes. We focus on the design of a self-organizing and collaborative mobile network that enables a continuous data transmission to the data sink (base station) and automatically adapts its behavior to changes in the environment to achieve a common goal. The pre-defined and self-configuring approaches to the mobile-based deployment of sensors are compared and discussed. A family of novel algorithms for the optimal placement of mobile wireless devices for permanent monitoring of indoor and outdoor dynamic environments is described. They employ a network connectivity-maintaining mobility model utilizing the concept of the virtual potential function for calculating the motion trajectories of platforms carrying sensors. Their quality and utility have been justified through simulation experiments and are discussed in the final part of the paper. PMID:27649186

Sensor-Web Operations Explorer

NASA Technical Reports Server (NTRS)

Meemong, Lee; Miller, Charles; Bowman, Kevin; Weidner, Richard

2008-01-01

Understanding the atmospheric state and its impact on air quality requires observations of trace gases, aerosols, clouds, and physical parameters across temporal and spatial scales that range from minutes to days and from meters to more than 10,000 kilometers. Observations include continuous local monitoring for particle formation; field campaigns for emissions, local transport, and chemistry; and periodic global measurements for continental transport and chemistry. Understanding includes global data assimilation framework capable of hierarchical coupling, dynamic integration of chemical data and atmospheric models, and feedback loops between models and observations. The objective of the sensor-web system is to observe trace gases, aerosols, clouds, and physical parameters, an integrated observation infrastructure composed of space-borne, air-borne, and in-situ sensors will be simulated based on their measurement physics properties. The objective of the sensor-web operation is to optimally plan for heterogeneous multiple sensors, the sampling strategies will be explored and science impact will be analyzed based on comprehensive modeling of atmospheric phenomena including convection, transport, and chemical process. Topics include system architecture, software architecture, hardware architecture, process flow, technology infusion, challenges, and future direction.

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

NASA Astrophysics Data System (ADS)

Simon, Solomon H.

1992-08-01

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

A Movement-Assisted Deployment of Collaborating Autonomous Sensors for Indoor and Outdoor Environment Monitoring.

PubMed

Niewiadomska-Szynkiewicz, Ewa; Sikora, Andrzej; Marks, Michał

2016-09-14

Using mobile robots or unmanned vehicles to assist optimal wireless sensors deployment in a working space can significantly enhance the capability to investigate unknown environments. This paper addresses the issues of the application of numerical optimization and computer simulation techniques to on-line calculation of a wireless sensor network topology for monitoring and tracking purposes. We focus on the design of a self-organizing and collaborative mobile network that enables a continuous data transmission to the data sink (base station) and automatically adapts its behavior to changes in the environment to achieve a common goal. The pre-defined and self-configuring approaches to the mobile-based deployment of sensors are compared and discussed. A family of novel algorithms for the optimal placement of mobile wireless devices for permanent monitoring of indoor and outdoor dynamic environments is described. They employ a network connectivity-maintaining mobility model utilizing the concept of the virtual potential function for calculating the motion trajectories of platforms carrying sensors. Their quality and utility have been justified through simulation experiments and are discussed in the final part of the paper.

Fiber Optic Raman Sensor to Monitor Concentration Ratio of Nitrogen and Oxygen in a Cryogenic Mixture

NASA Technical Reports Server (NTRS)

Tiwari, Vidhu S.; Kalluru, Rajamohan R.; Yueh, Fang-Yu; Singh, Jagdish P.; SaintCyr, William

2007-01-01

A spontaneous Raman scattering optical fiber sensor is developed for a specific need of NASA/SSC for long-term detection and monitoring of the quality of liquid oxygen (LOX) in the delivery line during ground testing of rocket engines. The sensor performance was tested in the laboratory and with different excitation light sources. To evaluate the sensor performance with different excitation light sources for the LOX quality application, we have used the various mixtures of liquid oxygen and liquid nitrogen as samples. The study of the sensor performance shows that this sensor offers a great deal of flexibility and provides a cost effective solution for the application. However, an improved system response time is needed for the real-time, quantitative monitoring of the quality of cryogenic fluids in harsh environment.

Experimental and Numerical Investigations on the Mechanical Characteristics of Carbon Fiber Sensors

PubMed Central

Siddiqui, Mohammed

2017-01-01

Carbon fiber-based materials possess excellent mechanical properties and show linear piezoresistive behavior, which make them good candidate materials for strain measurements. They have the potential to be used as sensors for various applications such as damage detection, stress analysis and monitoring of manufacturing processes and quality. In this paper, carbon fiber sensors are prepared to perform reliable strain measurements. Both experimental and computational studies were carried out on commercially available carbon fibers in order to understand the response of the carbon fiber sensors due to changes in the axial strain. Effects of parameters such as diameter, length, and epoxy-hardener ratio are discussed. The developed numerical model was calibrated using laboratory-based experimental data. The results of the current study show that sensors with shorter lengths have relatively better sensitivity. This is due to the fact short fibers have low initial resistance, which will increase the change of resistance over initial resistance. Carbon fibers with low number of filaments exhibit linear behavior while nonlinear behavior due to transverse resistance is significant in fibers with large number of filaments. This study will allow researchers to predict the behavior of the carbon fiber sensor in real life and it will serve as a basis for designing carbon fiber sensors to be used in different applications. PMID:28869538

Bluetooth Heart Rate Monitors For Spaceflight

NASA Technical Reports Server (NTRS)

Buxton, R. E.; West, M. R.; Kalogera, K. L.; Hanson, A. M.

2016-01-01

Heart rate monitoring is required for crewmembers during exercise aboard the International Space Station (ISS) and will be for future exploration missions. The cardiovascular system must be sufficiently stressed throughout a mission to maintain the ability to perform nominal and contingency/emergency tasks. High quality heart rate data are required to accurately determine the intensity of exercise performed by the crewmembers and show maintenance of VO2max. The quality of the data collected on ISS is subject to multiple limitations and is insufficient to meet current requirements. PURPOSE: To evaluate the performance of commercially available Bluetooth heart rate monitors (BT_HRM) and their ability to provide high quality heart rate data to monitor crew health aboard the ISS and during future exploration missions. METHODS: Nineteen subjects completed 30 data collection sessions of various intensities on the treadmill and/or cycle. Subjects wore several BT_HRM technologies for each testing session. One electrode-based chest strap (CS) was worn, while one or more optical sensors (OS) were worn. Subjects were instrumented with a 12-lead ECG to compare the heart rate data from the Bluetooth sensors. Each BT_HRM data set was time matched to the ECG data and a +/-5bpm threshold was applied to the difference between the 2 data sets. Percent error was calculated based on the number of data points outside the threshold and the total number of data points. RESULTS: The electrode-based chest straps performed better than the optical sensors. The best performing CS was CS1 (1.6% error), followed by CS4 (3.3% error), CS3 (6.4% error), and CS2 (9.2% error). The OS resulted in 10.4% error for OS1 and 14.9% error for OS2. CONCLUSIONS: The highest quality data came from CS1, but unfortunately it has been discontinued by the manufacturer. The optical sensors have not been ruled out for use, but more investigation is needed to determine how to obtain the best quality data. CS2 will be used in an ISS Bluetooth validation study, because it simultaneously transmits magnetic pulse that is integrated with existing exercise hardware on ISS. The simultaneous data streams allow for beat-to-beat comparison between the current ISS standard and CS2. Upon Bluetooth validation aboard ISS, the research team will down select a new BT_HRM for operational use.

Bluetooth(Registered Trademark) Heart Rate Monitors for Spaceflight

NASA Technical Reports Server (NTRS)

Buxton, Roxanne E.; West, Michael R.; Kalogera, Kent L.; Hanson, Andrea M.

2016-01-01

Heart rate monitoring is required during exercise for crewmembers aboard the International Space Station (ISS) and will be for future exploration missions. The cardiovascular system must be sufficiently stressed throughout a mission to maintain the ability to perform nominal and contingency/emergency tasks. High quality heart rate data is required to accurately determine the intensity of exercise performed by the crewmembers and show maintenance of VO2max. The quality of the data collected on ISS is subject to multiple limitations and is insufficient to meet current requirements. PURPOSE: To evaluate the performance of commercially available Bluetooth® heart rate monitors (BT_HRM) and their ability to provide high quality heart rate data to monitor crew health on board ISS and during future exploration missions. METHODS: Nineteen subjects completed 30 data collection sessions of various intensities on the treadmill and/or cycle. Subjects wore several BT_HRM technologies for each testing session. One electrode-based chest strap (CS) was worn, while one or more optical sensors (OS) was worn. Subjects were instrumented with a 12-lead ECG to compare the heart rate data from the Bluetooth sensors. Each BT_RHM data set was time matched to the ECG data and a +/-5bpm threshold was applied to the difference between the two data sets. Percent error was calculated based on the number of data points outside the threshold and the total number of data points. REULTS: The electrode-based chest straps performed better than the optical sensors. The best performing CS was CS1 (1.6%error), followed by CS4 (3.3%error), CS3 (6.4%error), and CS2 (9.2%error). The OS resulted in 10.4% error for OS1 and 14.9% error for OS2. CONCLUSIONS: The highest quality data came from CS1, unfortunately it has been discontinued by the manufacturer. The optical sensors have not been ruled out for use, but more investigation is needed to determine how to get the best quality data. CS2 will be used in an ISS Bluetooth validation study, because it simultaneously transmits Magnetic Pulse which is integrated with existing exercise hardware on ISS. The simultaneous data streams allow for beat to beat comparison between the current ISS standard and CS2.Upon Bluetooth(Registered Trademark) validation aboard ISS, down select of a new BT_HRM for operational use will be made.

The HUMSAT System: a CubeSat-based Constellation for In-situ and Inexpensive Environmental Measurements

NASA Astrophysics Data System (ADS)

Tubío-Pardavila, R.; Vigil, S. A.; Puig-Suari, J.; Aguado Agelet, F.

2014-12-01

There is a requirement for low cost in-situ measurements of environmental parameters such as air quality, meteorological data, and water quality in remote areas. Currently available solutions for such measurements include remote sensing from satellite and aircraft platforms, and in-situ measurements from mobile and aircraft platforms. Fixed systems such as eddy covariance networks, tall towers, and the Total Carbon Column Observing Network (TCCON) are providing precision greenhouse gas measurements. Within this context, the HUMSAT system designed by the University of Vigo (Spain) will complement existing high-precision measurement systems with low cost in-situ ground based sensors in remote locations using a constellation of CubeSats as a communications relay. The HUMSAT system standardizes radio communications in between deployed sensors and the CubeSats of the constellation, which act as store and forward satellites to ground stations for uploading to the internet. Current ground stations have been established at the University of Vigo (Spain) and California Polytechnic State University (Cal Poly). Users of the system may deploy their own environmental sensors to meet local requirements. The sensors will be linked to a low-cost satellite data transceiver using a standard HUMSAT protocol. The transceiver is capable of receiving data from the HUMSAT constellation to remotely reconfigure sensors without the need of physically going to the sensor location. This transceiver uses a UHF channel around 437 MHz to exchange short data messages with the sensors. These data messages can contain up to 32 bytes of useful information and are transmitted at a speed around 300 bps. The protocol designed for this system handles the access to the channel by all these elements and guarantees a correct transmission of the information in such an scenario. The University of Vigo has launched the first satellite of the constellation, the HUMSAT-D CubeSat in November 2013 and has deployed sensors in Spain and Brazil. Sensors will be also deployed by Cal Poly in the near future. In the following months, the SERPENS CubeSAT Mission, a joint project of the University of Brasilia and the University of Vigo will launch the second CubeSat of the constellation.

Implementation monitoring temperature, humidity and mositure soil based on wireless sensor network for e-agriculture technology

NASA Astrophysics Data System (ADS)

Sumarudin, A.; Ghozali, A. L.; Hasyim, A.; Effendi, A.

2016-04-01

Indonesian agriculture has great potensial for development. Agriculture a lot yet based on data collection for soil or plant, data soil can use for analys soil fertility. We propose e-agriculture system for monitoring soil. This system can monitoring soil status. Monitoring system based on wireless sensor mote that sensing soil status. Sensor monitoring utilize soil moisture, humidity and temperature. System monitoring design with mote based on microcontroler and xbee connection. Data sensing send to gateway with star topology with one gateway. Gateway utilize with mini personal computer and connect to xbee cordinator mode. On gateway, gateway include apache server for store data based on My-SQL. System web base with YII framework. System done implementation and can show soil status real time. Result the system can connection other mote 40 meters and mote lifetime 7 hours and minimum voltage 7 volt. The system can help famer for monitoring soil and farmer can making decision for treatment soil based on data. It can improve the quality in agricultural production and would decrease the management and farming costs.

Communicating Instantaneous Air Quality Data: Pilot Project

EPA Pesticide Factsheets

Communicating Instantaneous Air Quality Data: Pilot ProjectEPA is launching a pilot project to test a new tool for making instantaneous outdoor air quality data useful for the public. The new “sensor scale” is designed to be used with sensors

Differentiation of cumin seeds using a metal-oxide based gas sensor array in tandem with chemometric tools.

PubMed

Ghasemi-Varnamkhasti, Mahdi; Amiri, Zahra Safari; Tohidi, Mojtaba; Dowlati, Majid; Mohtasebi, Seyed Saeid; Silva, Adenilton C; Fernandes, David D S; Araujo, Mário C U

2018-01-01

Cumin is a plant of the Apiaceae family (umbelliferae) which has been used since ancient times as a medicinal plant and as a spice. The difference in the percentage of aromatic compounds in cumin obtained from different locations has led to differentiation of some species of cumin from other species. The quality and price of cumin vary according to the specie and may be an incentive for the adulteration of high value samples with low quality cultivars. An electronic nose simulates the human olfactory sense by using an array of sensors to distinguish complex smells. This makes it an alternative for the identification and classification of cumin species. The data, however, may have a complex structure, difficult to interpret. Given this, chemometric tools can be used to manipulate data with two-dimensional structure (sensor responses in time) obtained by using electronic nose sensors. In this study, an electronic nose based on eight metal oxide semiconductor sensors (MOS) and 2D-LDA (two-dimensional linear discriminant analysis), U-PLS-DA (Partial least square discriminant analysis applied to the unfolded data) and PARAFAC-LDA (Parallel factor analysis with linear discriminant analysis) algorithms were used in order to identify and classify different varieties of both cultivated and wild black caraway and cumin. The proposed methodology presented a correct classification rate of 87.1% for PARAFAC-LDA and 100% for 2D-LDA and U-PLS-DA, indicating a promising strategy for the classification different varieties of cumin, caraway and other seeds. Copyright © 2017 Elsevier B.V. All rights reserved.

Research and design on orthogonal diffraction grating-based 3D nanometer displacement sensor

NASA Astrophysics Data System (ADS)

Liu, Baoshuai; Yuan, Yibao; Yin, Zhehao

2017-10-01

This study concerns an orthogonal diffraction grating-based nanometer displacement sensor. In this study, we performed calculation of displacements in the XYZ directions. In the optical measured path part, we used a two-dimensional orthogonal motion grating and a two-dimensional orthogonal reference grating with the pitch of 0.5um to measure the displacement of XYZ in three directions by detecting ±1st diffraction fringes. The self-collimated structure of the grating greatly extended the Z-axis range. We also simulated the optical path of the sensor with ZEMAX software and verified the feasibility of the scheme. For signal subdivision and processing, we combined large number counting (completed grating line) with small number counting (digital subdivision), realizing high multiples of subdivision of grating interference signals. We used PC to process the interference fringes and greatly improved the processing speed. In the scheme, the theoretical multiples of subdivision could reach 1024 with 10-bit AD conversion, but the actual multiples of subdivision was limited by the quality of the grating interference signals. So we introduced an orthogonal compensation circuit and a filter circuit to improve the signal quality.

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

PubMed

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

2013-04-25

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

Assessing the quality of humidity measurements from global operational radiosonde sensors

NASA Astrophysics Data System (ADS)

Moradi, Isaac; Soden, Brian; Ferraro, Ralph; Arkin, Phillip; Vömel, Holger

2013-07-01

The quality of humidity measurements from global operational radiosonde sensors in upper, middle, and lower troposphere for the period 2000-2011 were investigated using satellite observations from three microwave water vapor channels operating at 183.31±1, 183.31±3, and 183.31±7 GHz. The radiosonde data were partitioned based on sensor type into 19 classes. The satellite brightness temperatures (Tb) were simulated using radiosonde profiles and a radiative transfer model, then the radiosonde simulated Tb's were compared with the observed Tb's from the satellites. The surface affected Tb's were excluded from the comparison due to the lack of reliable surface emissivity data at the microwave frequencies. Daytime and nighttime data were examined separately to see the possible effect of daytime radiation bias on the sonde data. The error characteristics among different radiosondes vary significantly, which largely reflects the differences in sensor type. These differences are more evident in the mid-upper troposphere than in the lower troposphere, mainly because some of the sensors stop responding to tropospheric humidity somewhere in the upper or even in the middle troposphere. In the upper troposphere, most sensors have a dry bias but Russian sensors and a few other sensors including GZZ2, VZB2, and RS80H have a wet bias. In middle troposphere, Russian sensors still have a wet bias but all other sensors have a dry bias. All sensors, including Russian sensors, have a dry bias in lower troposphere. The systematic and random errors generally decrease from upper to lower troposphere. Sensors from China, India, Russia, and the U.S. have a large random error in upper troposphere, which indicates that these sensors are not suitable for upper tropospheric studies as they fail to respond to humidity changes in the upper and even middle troposphere. Overall, Vaisala sensors perform better than other sensors throughout the troposphere exhibiting the smallest systematic and random errors. Because of the large differences between different radiosonde humidity sensors, it is important for long-term trend studies to only use data measured using a single type of sensor at any given station. If multiple sensor types are used then it is necessary to consider the bias between sensor types and its possible dependence on humidity and temperature.

Contact and non-contact ultrasonic measurement in the food industry: a review

NASA Astrophysics Data System (ADS)

Taufiq Mohd Khairi, Mohd; Ibrahim, Sallehuddin; Yunus, Mohd Amri Md; Faramarzi, Mahdi

2016-01-01

The monitoring of the food manufacturing process is vital since it determines the safety and quality level of foods which directly affect the consumers’ health. Companies which produce high quality products will gain trust from consumers. This factor helps the companies to make profits. The use of efficient and appropriate sensors for the monitoring process can also reduce cost. The food assessing process based on an ultrasonic sensor has attracted the attention of the food industry due to its excellent capabilities in several applications. The utilization of low or high frequencies for the ultrasonic transducer has provided an enormous benefit for analysing, modifying and guaranteeing the quality of food. The contact and non-contact ultrasonic modes for measurement also contributed significantly to the food processing. This paper presents a review of the application of the contact and non-contact mode of ultrasonic measurement focusing on safety and quality control areas. The results from previous researches are shown and elaborated.

Measurement of M²-Curve for Asymmetric Beams by Self-Referencing Interferometer Wavefront Sensor.

PubMed

Du, Yongzhao

2016-11-29

For asymmetric laser beams, the values of beam quality factor M x 2 and M y 2 are inconsistent if one selects a different coordinate system or measures beam quality with different experimental conditionals, even when analyzing the same beam. To overcome this non-uniqueness, a new beam quality characterization method named as M²-curve is developed. The M²-curve not only contains the beam quality factor M x 2 and M y 2 in the x -direction and y -direction, respectively; but also introduces a curve of M x α 2 versus rotation angle α of coordinate axis. Moreover, we also present a real-time measurement method to demonstrate beam propagation factor M²-curve with a modified self-referencing Mach-Zehnder interferometer based-wavefront sensor (henceforth SRI-WFS). The feasibility of the proposed method is demonstrated with the theoretical analysis and experiment in multimode beams. The experimental results showed that the proposed measurement method is simple, fast, and a single-shot measurement procedure without movable parts.

Measurement of M2-Curve for Asymmetric Beams by Self-Referencing Interferometer Wavefront Sensor

PubMed Central

Du, Yongzhao

2016-01-01

For asymmetric laser beams, the values of beam quality factor Mx2 and My2 are inconsistent if one selects a different coordinate system or measures beam quality with different experimental conditionals, even when analyzing the same beam. To overcome this non-uniqueness, a new beam quality characterization method named as M2-curve is developed. The M2-curve not only contains the beam quality factor Mx2 and My2 in the x-direction and y-direction, respectively; but also introduces a curve of Mxα2 versus rotation angle α of coordinate axis. Moreover, we also present a real-time measurement method to demonstrate beam propagation factor M2-curve with a modified self-referencing Mach-Zehnder interferometer based-wavefront sensor (henceforth SRI-WFS). The feasibility of the proposed method is demonstrated with the theoretical analysis and experiment in multimode beams. The experimental results showed that the proposed measurement method is simple, fast, and a single-shot measurement procedure without movable parts. PMID:27916845

Sensoring Fusion Data from the Optic and Acoustic Emissions of Electric Arcs in the GMAW-S Process for Welding Quality Assessment

PubMed Central

Alfaro, Sadek Crisóstomo Absi; Cayo, Eber Huanca

2012-01-01

The present study shows the relationship between welding quality and optical-acoustic emissions from electric arcs, during welding runs, in the GMAW-S process. Bead on plate welding tests was carried out with pre-set parameters chosen from manufacturing standards. During the welding runs interferences were induced on the welding path using paint, grease or gas faults. In each welding run arc voltage, welding current, infrared and acoustic emission values were acquired and parameters such as arc power, acoustic peaks rate and infrared radiation rate computed. Data fusion algorithms were developed by assessing known welding quality parameters from arc emissions. These algorithms have showed better responses when they are based on more than just one sensor. Finally, it was concluded that there is a close relation between arc emissions and quality in welding and it can be measured from arc emissions sensing and data fusion algorithms. PMID:22969330

Development of sleep monitoring system for observing the effect of the room ambient toward the quality of sleep

NASA Astrophysics Data System (ADS)

Saad, W. H. M.; Khoo, C. W.; Rahman, S. I. Ab; Ibrahim, M. M.; Saad, N. H. M.

2017-06-01

Getting enough sleep at the right times can help in improving quality of life and protect mental and physical health. This study proposes a portable sleep monitoring device to determine the relationship between the room ambient and quality of sleep. Body condition parameter such as heart rate, body temperature and body movement was used to determine quality of sleep and Audio/video-based monitoring system. The functionality test on all sensors is carried out to make sure that all sensors is working properly. The functionality of the overall system is designed for a better experience with a very minimal intervention to the user. The simple test on the body condition (body temperature and heart rate) while asleep with several different ambient parameters (humidity, brightness and temperature) are varied and the result shows that someone has a better sleep in a dark and colder ambient. This can prove by lower body temperature and lower heart rate.

Whole-cell bioluminescent bioreporter sensing of foodborne toxicants

NASA Astrophysics Data System (ADS)

Ripp, Steve A.; Applegate, Bruce M.; Simpson, Michael L.; Sayler, Gary S.

2001-03-01

The presence of biologically derived toxins in foods is of utmost significance to food safety and human health concerns. Biologically active amines, referred to as biogenic amines, serve as a noteworthy example, having been implicated as the causative agent in numerous food poisoning episodes. Of the various biogenic amines encountered, histamine, putrescine, cadaverine, tyramine, tryptamine, beta-phenylethylamine, spermine, and spermidine are considered to be the most significant, and can be used as hygienic-quality indicators of food. Biogenic amines can be monitored using whole-cell bioluminescent bioreporters, which represent a family of genetically engineered microorganisms that generate visible light in response to specific chemical or physical agents in their environment. The light response occurs due to transcriptional activation of a genetically incorporated lux cassette, and can be measured using standard photomultiplier devices. We have successfully engineered a lux-based bioreporter capable of detecting and monitoring the biogenic amine beta-phenylethylamine. This research represents a biologically-based sensor technology that can be readily integrated into Hazard Analysis Critical Control Point programs to provide a rugged monitoring regime that can be uniformly applied for field-based and in-house laboratory quality control analyses. Since the bioreporter and biosensing elements are completely self-contained within the sensor design, this system provides ease of use, with operational capabilities realized by simply combining the food sample with the bioreporter and allowing the sensor to process the ensuing bioluminescent signal and communicate the results. The application of this technology to the critically important issue of food safety and hygienic quality represents a novel method for detecting, monitoring, and preventing biologically active toxins in food commodities.

Performance Evaluation and Community Application of Low-Cost Sensors for Ozone and Nitrogen Dioxide

PubMed Central

Duvall, Rachelle M.; Long, Russell W.; Beaver, Melinda R.; Kronmiller, Keith G.; Wheeler, Michael L.; Szykman, James J.

2016-01-01

This study reports on the performance of electrochemical-based low-cost sensors and their use in a community application. CairClip sensors were collocated with federal reference and equivalent methods and operated in a network of sites by citizen scientists (community members) in Houston, Texas and Denver, Colorado, under the umbrella of the NASA-led DISCOVER-AQ Earth Venture Mission. Measurements were focused on ozone (O3) and nitrogen dioxide (NO2). The performance evaluation showed that the CairClip O3/NO2 sensor provided a consistent measurement response to that of reference monitors (r2 = 0.79 in Houston; r2 = 0.72 in Denver) whereas the CairClip NO2 sensor measurements showed no agreement to reference measurements. The CairClip O3/NO2 sensor data from the citizen science sites compared favorably to measurements at nearby reference monitoring sites. This study provides important information on data quality from low-cost sensor technologies and is one of few studies that reports sensor data collected directly by citizen scientists. PMID:27754370

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

A Technique to Determine the Self-Noise of Seismic Sensors for Performance Screening

NASA Astrophysics Data System (ADS)

Rademacher, H.; Hart, D.; Guralp, C.

2012-04-01

Seismic noise affects the performance of a seismic sensor and is thereby a limiting factor for the detection threshold of monitoring networks. Among the various sources of noise, the intrinsic self-noise of a seismic sensor is most diffcult to determine, because it is mostly masked by natural and anthropogenic ground noise and is also affected by the noise characteristic of the digitizer. Here we present a new technique to determine the self-noise of a seismic system (digitizer + sensors). It is based on a method introduced by Sleeman et al. (2005) to test the noise performance of digitizers. We infer the self-noise of a triplet of identical sensors by comparing coherent waveforms over a wide spectral band across the set-up. We will show first results from a proof-of-concept study done in a vault near Albuquerque, New Mexico. We will show, how various methods of shielding the sensors affect the results of this technique. This method can also be used as a means of quality control during sensor production, because poorly performing sensors can easily be identified.

Fall Risk Assessment Through Automatic Combination of Clinical Fall Risk Factors and Body-Worn Sensor Data.

PubMed

Greene, Barry R; Redmond, Stephen J; Caulfield, Brian

2017-05-01

Falls are the leading global cause of accidental death and disability in older adults and are the most common cause of injury and hospitalization. Accurate, early identification of patients at risk of falling, could lead to timely intervention and a reduction in the incidence of fall-related injury and associated costs. We report a statistical method for fall risk assessment using standard clinical fall risk factors (N = 748). We also report a means of improving this method by automatically combining it, with a fall risk assessment algorithm based on inertial sensor data and the timed-up-and-go test. Furthermore, we provide validation data on the sensor-based fall risk assessment method using a statistically independent dataset. Results obtained using cross-validation on a sample of 292 community dwelling older adults suggest that a combined clinical and sensor-based approach yields a classification accuracy of 76.0%, compared to either 73.6% for sensor-based assessment alone, or 68.8% for clinical risk factors alone. Increasing the cohort size by adding an additional 130 subjects from a separate recruitment wave (N = 422), and applying the same model building and validation method, resulted in a decrease in classification performance (68.5% for combined classifier, 66.8% for sensor data alone, and 58.5% for clinical data alone). This suggests that heterogeneity between cohorts may be a major challenge when attempting to develop fall risk assessment algorithms which generalize well. Independent validation of the sensor-based fall risk assessment algorithm on an independent cohort of 22 community dwelling older adults yielded a classification accuracy of 72.7%. Results suggest that the present method compares well to previously reported sensor-based fall risk assessment methods in assessing falls risk. Implementation of objective fall risk assessment methods on a large scale has the potential to improve quality of care and lead to a reduction in associated hospital costs, due to fewer admissions and reduced injuries due to falling.

Passive Microwave Precipitation Retrieval Uncertainty Characterized based on Field Campaign Data over Complex Terrain

NASA Astrophysics Data System (ADS)

Derin, Y.; Anagnostou, E. N.; Anagnostou, M.; Kalogiros, J. A.; Casella, D.; Marra, A. C.; Panegrossi, G.; Sanò, P.

2017-12-01

Difficulties in representation of high rainfall variability over mountainous areas using ground based sensors make satellite remote sensing techniques attractive for hydrologic studies over these regions. Even though satellite-based rainfall measurements are quasi global and available at high spatial resolution, these products have uncertainties that necessitate use of error characterization and correction procedures based upon more accurate in situ rainfall measurements. Such measurements can be obtained from field campaigns facilitated by research quality sensors such as locally deployed weather radar and in situ weather stations. This study uses such high quality and resolution rainfall estimates derived from dual-polarization X-band radar (XPOL) observations from three field experiments in Mid-Atlantic US East Coast (NASA IPHEX experiment), the Olympic Peninsula of Washington State (NASA OLYMPEX experiment), and the Mediterranean to characterize the error characteristics of multiple passive microwave (PMW) sensor retrievals. The study first conducts an independent error analysis of the XPOL radar reference rainfall fields against in situ rain gauges and disdrometer observations available by the field experiments. Then the study evaluates different PMW precipitation products using the XPOL datasets (GR) over the three aforementioned complex terrain study areas. We extracted matchups of PMW/GR rainfall based on a matching methodology that identifies GR volume scans coincident with PMW field-of-view sampling volumes, and scaled GR parameters to the satellite products' nominal spatial resolution. The following PMW precipitation retrieval algorithms are evaluated: the NASA Goddard PROFiling algorithm (GPROF), standard and climatology-based products (V 3, 4 and 5) from four PMW sensors (SSMIS, MHS, GMI, and AMSR2), and the precipitation products based on the algorithms Cloud Dynamics and Radiation Database (CDRD) for SSMIS and Passive microwave Neural network Precipitation Retrieval (PNPR) for AMSU/MHS, developed at ISAC-CNR within the EUMETSAT H-SAF. We will present error analysis results for the different PMW rainfall retrievals and discuss dependences on precipitation type, elevation and precipitation microphysics (derived from XPOL).

Differential Binary Encoding Method for Calibrating Image Sensors Based on IOFBs

PubMed Central

Fernández, Pedro R.; Lázaro-Galilea, José Luis; Gardel, Alfredo; Espinosa, Felipe; Bravo, Ignacio; Cano, Ángel

2012-01-01

Image transmission using incoherent optical fiber bundles (IOFBs) requires prior calibration to obtain the spatial in-out fiber correspondence necessary to reconstruct the image captured by the pseudo-sensor. This information is recorded in a Look-Up Table called the Reconstruction Table (RT), used later for reordering the fiber positions and reconstructing the original image. This paper presents a very fast method based on image-scanning using spaces encoded by a weighted binary code to obtain the in-out correspondence. The results demonstrate that this technique yields a remarkable reduction in processing time and the image reconstruction quality is very good compared to previous techniques based on spot or line scanning, for example. PMID:22666023

Mechanical monolithic compact sensors for real-time linear and angular broadband low frequency monitoring and control of spacecrafts and satellites

NASA Astrophysics Data System (ADS)

Barone, F.; Giordano, G.

2017-09-01

In this paper we describe the characteristics and performances of a monolithic sensor designed for low frequency motion measurement of spacecrafts and satellites, whose mechanics is based on the UNISA Folded Pendulum. The latter, developed for ground-based applications, exhibits unique features (compactness, lightness, scalability, low resonance frequency and high quality factor), consequence of the action of the gravitational force on its inertial mass. In this paper we introduce and discuss the general methodology used to extend the application of ground-based folded pendulums to space, also in total absence of gravity, still keeping all their peculiar features and characteristics.

Management Zone Delineation for Winegrape Selective Harvesting Based on Fluorescence-Sensor Mapping of Grape Skin Anthocyanins.

PubMed

Agati, Giovanni; Soudani, Kamel; Tuccio, Lorenza; Fierini, Elisa; Ben Ghozlen, Naïma; Fadaili, El Mostafa; Romani, Annalisa; Cerovic, Zoran G

2018-06-13

We analyzed the potential of non-destructive optical sensing of grape skin anthocyanins for selective harvesting in precision viticulture. We measured anthocyanins by a hand-held fluorescence optical sensor on a 7 ha Sangiovese vineyard plot in central Italy. Optical indices obtained by the sensor were calibrated for the transformation in units of anthocyanins per berry mass, i.e., milligrams per gram of berry fresh weight. A full protocol for optimal data filtration, interpolation, and homogeneous zone delineation based on a very large number of optical measurements is proposed. Both the single signal-based fluorescence index (ANTH R ) and the two signal ratio-based index (ANTH RG ) can be used for Sangiovese grapes. Significant separations of grape-quality batches were obtained by several methods of data classification and zone delineations. Basic statistical criteria were as efficient as the K-means clustering. The best separations were obtained for three classes of grape skin anthocyanin.

Impact of Sensor Misplacement on Dynamic Time Warping Based Human Activity Recognition using Wearable Computers.

PubMed

Kale, Nimish; Lee, Jaeseong; Lotfian, Reza; Jafari, Roozbeh

2012-10-01

Daily living activity monitoring is important for early detection of the onset of many diseases and for improving quality of life especially in elderly. A wireless wearable network of inertial sensor nodes can be used to observe daily motions. Continuous stream of data generated by these sensor networks can be used to recognize the movements of interest. Dynamic Time Warping (DTW) is a widely used signal processing method for time-series pattern matching because of its robustness to variations in time and speed as opposed to other template matching methods. Despite this flexibility, for the application of activity recognition, DTW can only find the similarity between the template of a movement and the incoming samples, when the location and orientation of the sensor remains unchanged. Due to this restriction, small sensor misplacements can lead to a decrease in the classification accuracy. In this work, we adopt DTW distance as a feature for real-time detection of human daily activities like sit to stand in the presence of sensor misplacement. To measure this performance of DTW, we need to create a large number of sensor configurations while the sensors are rotated or misplaced. Creating a large number of closely spaced sensors is impractical. To address this problem, we use the marker based optical motion capture system and generate simulated inertial sensor data for different locations and orientations on the body. We study the performance of the DTW under these conditions to determine the worst-case sensor location variations that the algorithm can accommodate.

Sensitivity Analysis of Different Shapes of a Plastic Optical Fiber-Based Immunosensor for Escherichia coli: Simulation and Experimental Results.

PubMed

Rodrigues, Domingos M C; Lopes, Rafaela N; Franco, Marcos A R; Werneck, Marcelo M; Allil, Regina C S B

2017-12-19

Conventional pathogen detection methods require trained personnel, specialized laboratories and can take days to provide a result. Thus, portable biosensors with rapid detection response are vital for the current needs for in-loco quality assays. In this work the authors analyze the characteristics of an immunosensor based on the evanescent field in plastic optical fibers with macro curvature by comparing experimental with simulated results. The work studies different shapes of evanescent-wave based fiber optic sensors, adopting a computational modeling to evaluate the probes with the best sensitivity. The simulation showed that for a U-Shaped sensor, the best results can be achieved with a sensor of 980 µm diameter by 5.0 mm in curvature for refractive index sensing, whereas the meander-shaped sensor with 250 μm in diameter with radius of curvature of 1.5 mm, showed better sensitivity for either bacteria and refractive index (RI) sensing. Then, an immunosensor was developed, firstly to measure refractive index and after that, functionalized to detect Escherichia coli . Based on the results with the simulation, we conducted studies with a real sensor for RI measurements and for Escherichia coli detection aiming to establish the best diameter and curvature radius in order to obtain an optimized sensor. On comparing the experimental results with predictions made from the modelling, good agreements were obtained. The simulations performed allowed the evaluation of new geometric configurations of biosensors that can be easily constructed and that promise improved sensitivity.

Spatial Distribution of Accuracy of Aerosol Retrievals from Multiple Satellite Sensors

NASA Technical Reports Server (NTRS)

Petrenko, Maksym; Ichoku, Charles

2012-01-01

Remote sensing of aerosols from space has been a subject of extensive research, with multiple sensors retrieving aerosol properties globally on a daily or weekly basis. The diverse algorithms used for these retrievals operate on different types of reflected signals based on different assumptions about the underlying physical phenomena. Depending on the actual retrieval conditions and especially on the geographical location of the sensed aerosol parcels, the combination of these factors might be advantageous for one or more of the sensors and unfavorable for others, resulting in disagreements between similar aerosol parameters retrieved from different sensors. In this presentation, we will demonstrate the use of the Multi-sensor Aerosol Products Sampling System (MAPSS) to analyze and intercompare aerosol retrievals from multiple spaceborne sensors, including MODIS (on Terra and Aqua), MISR, OMI, POLDER, CALIOP, and SeaWiFS. Based on this intercomparison, we are determining geographical locations where these products provide the greatest accuracy of the retrievals and identifying the products that are the most suitable for retrieval at these locations. The analyses are performed by comparing quality-screened satellite aerosol products to available collocated ground-based aerosol observations from the Aerosol Robotic Network (AERONET) stations, during the period of 2006-2010 when all the satellite sensors were operating concurrently. Furthermore, we will discuss results of a statistical approach that is applied to the collocated data to detect and remove potential data outliers that can bias the results of the analysis.

Statistical-QoS Guaranteed Energy Efficiency Optimization for Energy Harvesting Wireless Sensor Networks

PubMed Central

Cheng, Wenchi; Zhang, Hailin

2017-01-01

Energy harvesting, which offers a never-ending energy supply, has emerged as a prominent technology to prolong the lifetime and reduce costs for the battery-powered wireless sensor networks. However, how to improve the energy efficiency while guaranteeing the quality of service (QoS) for energy harvesting based wireless sensor networks is still an open problem. In this paper, we develop statistical delay-bounded QoS-driven power control policies to maximize the effective energy efficiency (EEE), which is defined as the spectrum efficiency under given specified QoS constraints per unit harvested energy, for energy harvesting based wireless sensor networks. For the battery-infinite wireless sensor networks, our developed QoS-driven power control policy converges to the Energy harvesting Water Filling (E-WF) scheme and the Energy harvesting Channel Inversion (E-CI) scheme under the very loose and stringent QoS constraints, respectively. For the battery-finite wireless sensor networks, our developed QoS-driven power control policy becomes the Truncated energy harvesting Water Filling (T-WF) scheme and the Truncated energy harvesting Channel Inversion (T-CI) scheme under the very loose and stringent QoS constraints, respectively. Furthermore, we evaluate the outage probabilities to theoretically analyze the performance of our developed QoS-driven power control policies. The obtained numerical results validate our analysis and show that our developed optimal power control policies can optimize the EEE over energy harvesting based wireless sensor networks. PMID:28832509

Statistical-QoS Guaranteed Energy Efficiency Optimization for Energy Harvesting Wireless Sensor Networks.

PubMed

Gao, Ya; Cheng, Wenchi; Zhang, Hailin

2017-08-23

Energy harvesting, which offers a never-ending energy supply, has emerged as a prominent technology to prolong the lifetime and reduce costs for the battery-powered wireless sensor networks. However, how to improve the energy efficiency while guaranteeing the quality of service (QoS) for energy harvesting based wireless sensor networks is still an open problem. In this paper, we develop statistical delay-bounded QoS-driven power control policies to maximize the effective energy efficiency (EEE), which is defined as the spectrum efficiency under given specified QoS constraints per unit harvested energy, for energy harvesting based wireless sensor networks. For the battery-infinite wireless sensor networks, our developed QoS-driven power control policy converges to the Energy harvesting Water Filling (E-WF) scheme and the Energy harvesting Channel Inversion (E-CI) scheme under the very loose and stringent QoS constraints, respectively. For the battery-finite wireless sensor networks, our developed QoS-driven power control policy becomes the Truncated energy harvesting Water Filling (T-WF) scheme and the Truncated energy harvesting Channel Inversion (T-CI) scheme under the very loose and stringent QoS constraints, respectively. Furthermore, we evaluate the outage probabilities to theoretically analyze the performance of our developed QoS-driven power control policies. The obtained numerical results validate our analysis and show that our developed optimal power control policies can optimize the EEE over energy harvesting based wireless sensor networks.

PERKINELMER ELM

EPA Science Inventory

The PerkinElmer Elm (formerly the AirBase CanarIT) is a multi-sensor air quality monitoring device that measures particulate matter (PM), total volatile organic compounds (VOCs), nitrogen dioxide (NO₂), and several other atmospheric components. PM, VOCs, and NO₂

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.

An Efficient Wireless Sensor Network for Industrial Monitoring and Control.

PubMed

Aponte-Luis, Juan; Gómez-Galán, Juan Antonio; Gómez-Bravo, Fernando; Sánchez-Raya, Manuel; Alcina-Espigado, Javier; Teixido-Rovira, Pedro Miguel

2018-01-10

This paper presents the design of a wireless sensor network particularly designed for remote monitoring and control of industrial parameters. The article describes the network components, protocol and sensor deployment, aimed to accomplish industrial constraint and to assure reliability and low power consumption. A particular case of study is presented. The system consists of a base station, gas sensing nodes, a tree-based routing scheme for the wireless sensor nodes and a real-time monitoring application that operates from a remote computer and a mobile phone. The system assures that the industrial safety quality and the measurement and monitoring system achieves an efficient industrial monitoring operations. The robustness of the developed system and the security in the communications have been guaranteed both in hardware and software level. The system is flexible and can be adapted to different environments. The testing of the system confirms the feasibility of the proposed implementation and validates the functional requirements of the developed devices, the networking solution and the power consumption management.

An Efficient Wireless Sensor Network for Industrial Monitoring and Control

PubMed Central

Aponte-Luis, Juan; Gómez-Bravo, Fernando; Sánchez-Raya, Manuel; Alcina-Espigado, Javier; Teixido-Rovira, Pedro Miguel

2018-01-01

This paper presents the design of a wireless sensor network particularly designed for remote monitoring and control of industrial parameters. The article describes the network components, protocol and sensor deployment, aimed to accomplish industrial constraint and to assure reliability and low power consumption. A particular case of study is presented. The system consists of a base station, gas sensing nodes, a tree-based routing scheme for the wireless sensor nodes and a real-time monitoring application that operates from a remote computer and a mobile phone. The system assures that the industrial safety quality and the measurement and monitoring system achieves an efficient industrial monitoring operations. The robustness of the developed system and the security in the communications have been guaranteed both in hardware and software level. The system is flexible and can be adapted to different environments. The testing of the system confirms the feasibility of the proposed implementation and validates the functional requirements of the developed devices, the networking solution and the power consumption management. PMID:29320466

Detection of premature browning in ground beef using an optical-fibre-based sensor

NASA Astrophysics Data System (ADS)

Sheridan, C.; O'Farrell, M.; Lewis, E.; Flanagan, C.; Kerry, J. F.; Jackman, N.

2007-07-01

This paper reports on an optical fibre based sensor system to detect the occurrence of premature browning in ground beef. Premature browning (PMB) occurs when, at a temperature below the pasteurisation temperature of 71°C, there are no traces of pink meat left in the patty. PMB is more frequent in poorer quality beef or beef that has been stored under imperfect conditions. The experimental work pertaining to this paper involved cooking fresh meat and meat that has been stored in a freezer for, 1 week, 1 month and 3 months and recording the reflected spectra and temperature at the core of the product, during the cooking process, in order to develop a classifier based on the spectral response and using a Self-Organising Map (SOM) to classify the patties into one of four categories, based on their colour. The combination of both the classifier and temperature data can be used to determine the presence of PMB for a given patty and can thus be used for Quality Control by food producers.

Optimal Sensor Placement for Measuring Physical Activity with a 3D Accelerometer

PubMed Central

Boerema, Simone T.; van Velsen, Lex; Schaake, Leendert; Tönis, Thijs M.; Hermens, Hermie J.

2014-01-01

Accelerometer-based activity monitors are popular for monitoring physical activity. In this study, we investigated optimal sensor placement for increasing the quality of studies that utilize accelerometer data to assess physical activity. We performed a two-staged study, focused on sensor location and type of mounting. Ten subjects walked at various walking speeds on a treadmill, performed a deskwork protocol, and walked on level ground, while simultaneously wearing five ProMove2 sensors with a snug fit on an elastic waist belt. We found that sensor location, type of activity, and their interaction-effect affected sensor output. The most lateral positions on the waist belt were the least sensitive for interference. The effect of mounting was explored, by making two subjects repeat the experimental protocol with sensors more loosely fitted to the elastic belt. The loose fit resulted in lower sensor output, except for the deskwork protocol, where output was higher. In order to increase the reliability and to reduce the variability of sensor output, researchers should place activity sensors on the most lateral position of a participant's waist belt. If the sensor hampers free movement, it may be positioned slightly more forward on the belt. Finally, sensors should be fitted tightly to the body. PMID:24553085

A multimodal image sensor system for identifying water stress in grapevines

NASA Astrophysics Data System (ADS)

Zhao, Yong; Zhang, Qin; Li, Minzan; Shao, Yongni; Zhou, Jianfeng; Sun, Hong

2012-11-01

Water stress is one of the most common limitations of fruit growth. Water is the most limiting resource for crop growth. In grapevines, as well as in other fruit crops, fruit quality benefits from a certain level of water deficit which facilitates to balance vegetative and reproductive growth and the flow of carbohydrates to reproductive structures. A multi-modal sensor system was designed to measure the reflectance signature of grape plant surfaces and identify different water stress levels in this paper. The multi-modal sensor system was equipped with one 3CCD camera (three channels in R, G, and IR). The multi-modal sensor can capture and analyze grape canopy from its reflectance features, and identify the different water stress levels. This research aims at solving the aforementioned problems. The core technology of this multi-modal sensor system could further be used as a decision support system that combines multi-modal sensory data to improve plant stress detection and identify the causes of stress. The images were taken by multi-modal sensor which could output images in spectral bands of near-infrared, green and red channel. Based on the analysis of the acquired images, color features based on color space and reflectance features based on image process method were calculated. The results showed that these parameters had the potential as water stress indicators. More experiments and analysis are needed to validate the conclusion.

Grower demand for sensor-controlled irrigation

NASA Astrophysics Data System (ADS)

Lichtenberg, Erik; Majsztrik, John; Saavoss, Monica

2015-01-01

Water scarcity is likely to increase in the coming years, making improvements in irrigation efficiency increasingly important. An emerging technology that promises to increase irrigation efficiency substantially is a wireless irrigation sensor network that uploads sensor data into irrigation management software, creating an integrated system that allows real-time monitoring and control of moisture status that has been shown in experimental settings to reduce irrigation costs, lower plant loss rates, shorten production times, decrease pesticide application, and increase yield, quality, and profit. We use an original survey to investigate likely initial acceptance, ceiling adoption rates, and profitability of this new sensor network technology in the nursery and greenhouse industry. We find that adoption rates for a base system and demand for expansion components are decreasing in price, as expected. The price elasticity of the probability of adoption suggests that sensor networks are likely to diffuse at a rate somewhat greater than that of drip irrigation. Adoption rates for a base system and demand for expansion components are increasing in specialization in ornamental production: growers earning greater shares of revenue from greenhouse and nursery operations are willing to pay more for a base system and are willing to purchase larger numbers of expansion components at any given price. We estimate that growers who are willing to purchase a sensor network expect investment in this technology to generate significant profit, consistent with findings from experimental studies.

Automatic Assessment of Acquisition and Transmission Losses in Indian Remote Sensing Satellite Data

NASA Astrophysics Data System (ADS)

Roy, D.; Purna Kumari, B.; Manju Sarma, M.; Aparna, N.; Gopal Krishna, B.

2016-06-01

The quality of Remote Sensing data is an important parameter that defines the extent of its usability in various applications. The data from Remote Sensing satellites is received as raw data frames at the ground station. This data may be corrupted with data losses due to interferences during data transmission, data acquisition and sensor anomalies. Thus it is important to assess the quality of the raw data before product generation for early anomaly detection, faster corrective actions and product rejection minimization. Manual screening of raw images is a time consuming process and not very accurate. In this paper, an automated process for identification and quantification of losses in raw data like pixel drop out, line loss and data loss due to sensor anomalies is discussed. Quality assessment of raw scenes based on these losses is also explained. This process is introduced in the data pre-processing stage and gives crucial data quality information to users at the time of browsing data for product ordering. It has also improved the product generation workflow by enabling faster and more accurate quality estimation.

TRMM Microwave Imager (TMI) Updates for Final Data Version Release

NASA Technical Reports Server (NTRS)

Kroodsma, Rachael A; Bilanow, Stephen; Ji, Yimin; McKague, Darren

2017-01-01

The Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI) dataset released by the Precipitation Processing System (PPS) will be updated to a final version within the next year. These updates are based on increased knowledge in recent years of radiometer calibration and sensor performance issues. In particular, the Global Precipitation Measurement (GPM) Microwave Imager (GMI) is used as a model for many of the TMI version updates. This paper discusses four aspects of the TMI data product that will be improved: spacecraft attitude, calibration and quality control, along-scan bias corrections, and sensor pointing accuracy. These updates will be incorporated into the final TMI data version, improving the quality of the data product and ensuring accurate geophysical parameters can be derived from TMI.

Theory research of seam recognition and welding torch pose control based on machine vision

NASA Astrophysics Data System (ADS)

Long, Qiang; Zhai, Peng; Liu, Miao; He, Kai; Wang, Chunyang

2017-03-01

At present, the automation requirement of the welding become higher, so a method of the welding information extraction by vision sensor is proposed in this paper, and the simulation with the MATLAB has been conducted. Besides, in order to improve the quality of robot automatic welding, an information retrieval method for welding torch pose control by visual sensor is attempted. Considering the demands of welding technology and engineering habits, the relative coordinate systems and variables are strictly defined, and established the mathematical model of the welding pose, and verified its feasibility by using the MATLAB simulation in the paper, these works lay a foundation for the development of welding off-line programming system with high precision and quality.

Semi-Automatic Determination of Rockfall Trajectories

PubMed Central

Volkwein, Axel; Klette, Johannes

2014-01-01

In determining rockfall trajectories in the field, it is essential to calibrate and validate rockfall simulation software. This contribution presents an in situ device and a complementary Local Positioning System (LPS) that allow the determination of parts of the trajectory. An assembly of sensors (herein called rockfall sensor) is installed in the falling block recording the 3D accelerations and rotational velocities. The LPS automatically calculates the position of the block along the slope over time based on Wi-Fi signals emitted from the rockfall sensor. The velocity of the block over time is determined through post-processing. The setup of the rockfall sensor is presented followed by proposed calibration and validation procedures. The performance of the LPS is evaluated by means of different experiments. The results allow for a quality analysis of both the obtained field data and the usability of the rockfall sensor for future/further applications in the field. PMID:25268916

Simulation of Smart Home Activity Datasets

PubMed Central

Synnott, Jonathan; Nugent, Chris; Jeffers, Paul

2015-01-01

A globally ageing population is resulting in an increased prevalence of chronic conditions which affect older adults. Such conditions require long-term care and management to maximize quality of life, placing an increasing strain on healthcare resources. Intelligent environments such as smart homes facilitate long-term monitoring of activities in the home through the use of sensor technology. Access to sensor datasets is necessary for the development of novel activity monitoring and recognition approaches. Access to such datasets is limited due to issues such as sensor cost, availability and deployment time. The use of simulated environments and sensors may address these issues and facilitate the generation of comprehensive datasets. This paper provides a review of existing approaches for the generation of simulated smart home activity datasets, including model-based approaches and interactive approaches which implement virtual sensors, environments and avatars. The paper also provides recommendation for future work in intelligent environment simulation. PMID:26087371

Advances in multi-sensor data fusion: algorithms and applications.

PubMed

Dong, Jiang; Zhuang, Dafang; Huang, Yaohuan; Fu, Jingying

2009-01-01

With the development of satellite and remote sensing techniques, more and more image data from airborne/satellite sensors have become available. Multi-sensor image fusion seeks to combine information from different images to obtain more inferences than can be derived from a single sensor. In image-based application fields, image fusion has emerged as a promising research area since the end of the last century. The paper presents an overview of recent advances in multi-sensor satellite image fusion. Firstly, the most popular existing fusion algorithms are introduced, with emphasis on their recent improvements. Advances in main applications fields in remote sensing, including object identification, classification, change detection and maneuvering targets tracking, are described. Both advantages and limitations of those applications are then discussed. Recommendations are addressed, including: (1) Improvements of fusion algorithms; (2) Development of "algorithm fusion" methods; (3) Establishment of an automatic quality assessment scheme.

Color sensor and neural processor on one chip

NASA Astrophysics Data System (ADS)

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

1998-10-01

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

Rolling Shutter Effect aberration compensation in Digital Holographic Microscopy

NASA Astrophysics Data System (ADS)

Monaldi, Andrea C.; Romero, Gladis G.; Cabrera, Carlos M.; Blanc, Adriana V.; Alanís, Elvio E.

2016-05-01

Due to the sequential-readout nature of most CMOS sensors, each row of the sensor array is exposed at a different time, resulting in the so-called rolling shutter effect that induces geometric distortion to the image if the video camera or the object moves during image acquisition. Particularly in digital holograms recording, while the sensor captures progressively each row of the hologram, interferometric fringes can oscillate due to external vibrations and/or noises even when the object under study remains motionless. The sensor records each hologram row in different instants of these disturbances. As a final effect, phase information is corrupted, distorting the reconstructed holograms quality. We present a fast and simple method for compensating this effect based on image processing tools. The method is exemplified by holograms of microscopic biological static objects. Results encourage incorporating CMOS sensors over CCD in Digital Holographic Microscopy due to a better resolution and less expensive benefits.

Simulation of Smart Home Activity Datasets.

PubMed

Synnott, Jonathan; Nugent, Chris; Jeffers, Paul

2015-06-16

A globally ageing population is resulting in an increased prevalence of chronic conditions which affect older adults. Such conditions require long-term care and management to maximize quality of life, placing an increasing strain on healthcare resources. Intelligent environments such as smart homes facilitate long-term monitoring of activities in the home through the use of sensor technology. Access to sensor datasets is necessary for the development of novel activity monitoring and recognition approaches. Access to such datasets is limited due to issues such as sensor cost, availability and deployment time. The use of simulated environments and sensors may address these issues and facilitate the generation of comprehensive datasets. This paper provides a review of existing approaches for the generation of simulated smart home activity datasets, including model-based approaches and interactive approaches which implement virtual sensors, environments and avatars. The paper also provides recommendation for future work in intelligent environment simulation.

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.

Bluetooth-based sensor networks for remotely monitoring the physiological signals of a patient.

PubMed

Zhang, Ying; Xiao, Hannan

2009-11-01

Integrating intelligent medical microsensors into a wireless communication network makes it possible to remotely collect physiological signals of a patient, release the patient from being tethered to monitoring medical instrumentations, and facilitate the patient's early hospital discharge. This can further improve life quality by providing continuous observation without the need of disrupting the patient's normal life, thus reducing the risk of infection significantly, and decreasing the cost of the hospital and the patient. This paper discusses the implementation issues, and describes the overall system architecture of our developed Bluetooth sensor network for patient monitoring and the corresponding heart activity sensors. It also presents our approach to developing the intelligent physiological sensor nodes involving integration of Bluetooth radio technology, hardware and software organization, and our solutions for onboard signal processing.

Modeling of low-finesse, extrinsic fiber optic Fabry-Perot white light interferometers

NASA Astrophysics Data System (ADS)

Ma, Cheng; Tian, Zhipeng; Wang, Anbo

2012-06-01

This article introduces an approach for modeling the fiber optic low-finesse extrinsic Fabry-Pérot Interferometers (EFPI), aiming to address signal processing problems in EFPI demodulation algorithms based on white light interferometry. The main goal is to seek physical interpretations to correlate the sensor spectrum with the interferometer geometry (most importantly, the optical path difference). Because the signal demodulation quality and reliability hinge heavily on the understanding of such relationships, the model sheds light on optimizing the sensor performance.

A simulation of air pollution model parameter estimation using data from a ground-based LIDAR remote sensor

NASA Technical Reports Server (NTRS)

Kibler, J. F.; Suttles, J. T.

1977-01-01

One way to obtain estimates of the unknown parameters in a pollution dispersion model is to compare the model predictions with remotely sensed air quality data. A ground-based LIDAR sensor provides relative pollution concentration measurements as a function of space and time. The measured sensor data are compared with the dispersion model output through a numerical estimation procedure to yield parameter estimates which best fit the data. This overall process is tested in a computer simulation to study the effects of various measurement strategies. Such a simulation is useful prior to a field measurement exercise to maximize the information content in the collected data. Parametric studies of simulated data matched to a Gaussian plume dispersion model indicate the trade offs available between estimation accuracy and data acquisition strategy.

The quality of our drinking water: aluminium determination with an acoustic wave sensor.

PubMed

Veríssimo, Marta I S; Gomes, M Teresa S R

2008-06-09

A new methodology based on an inexpensive aluminium acoustic wave sensor is presented. Although the aluminium sensor has already been reported, and the composition of the selective membrane is known, the low detection limits required for the analysis of drinking water, demanded the inclusion of a preconcentration stage, as well as an optimization of the sensor. The necessary coating amount was established, as well as the best preconcentration protocol, in terms of oxidation of organic matter and aluminium elution from the Chelex-100. The methodology developed with the acoustic wave sensor allowed aluminium quantitation above 0.07 mg L(-1). Several water samples from Portugal were analysed using the acoustic wave sensor, as well as by UV-vis spectrophotometry. Results obtained with both methodologies were not statistically different (alpha=0.05), both in terms of accuracy and precision. This new methodology proved to be adequate for aluminium quantitation in drinking water and showed to be faster and less reagent consuming than the UV spectrophotometric methodology.

Evaluation of excitation strategy with multi-plane electrical capacitance tomography sensor

NASA Astrophysics Data System (ADS)

Mao, Mingxu; Ye, Jiamin; Wang, Haigang; Zhang, Jiaolong; Yang, Wuqiang

2016-11-01

Electrical capacitance tomography (ECT) is an imaging technique for measuring the permittivity change of materials. Using a multi-plane ECT sensor, three-dimensional (3D) distribution of permittivity may be represented. In this paper, three excitation strategies, including single-electrode excitation, dual-electrode excitation in the same plane, and dual-electrode excitation in different planes are investigated by numerical simulation and experiment for two three-plane ECT sensors with 12 electrodes in total. In one sensor, the electrodes on the middle plane are in line with the others. In the other sensor, they are rotated 45° with reference to the other two planes. A linear back projection algorithm is used to reconstruct the images and a correlation coefficient is used to evaluate the image quality. The capacitance data and sensitivity distribution with each measurement strategy and sensor model are analyzed. Based on simulation and experimental results using noise-free and noisy capacitance data, the performance of the three strategies is evaluated.

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.

Bio-mimic optimization strategies in wireless sensor networks: a survey.

PubMed

Adnan, Md Akhtaruzzaman; Abdur Razzaque, Mohammd; Ahmed, Ishtiaque; Isnin, Ismail Fauzi

2013-12-24

For the past 20 years, many authors have focused their investigations on wireless sensor networks. Various issues related to wireless sensor networks such as energy minimization (optimization), compression schemes, self-organizing network algorithms, routing protocols, quality of service management, security, energy harvesting, etc., have been extensively explored. The three most important issues among these are energy efficiency, quality of service and security management. To get the best possible results in one or more of these issues in wireless sensor networks optimization is necessary. Furthermore, in number of applications (e.g., body area sensor networks, vehicular ad hoc networks) these issues might conflict and require a trade-off amongst them. Due to the high energy consumption and data processing requirements, the use of classical algorithms has historically been disregarded. In this context contemporary researchers started using bio-mimetic strategy-based optimization techniques in the field of wireless sensor networks. These techniques are diverse and involve many different optimization algorithms. As far as we know, most existing works tend to focus only on optimization of one specific issue of the three mentioned above. It is high time that these individual efforts are put into perspective and a more holistic view is taken. In this paper we take a step in that direction by presenting a survey of the literature in the area of wireless sensor network optimization concentrating especially on the three most widely used bio-mimetic algorithms, namely, particle swarm optimization, ant colony optimization and genetic algorithm. In addition, to stimulate new research and development interests in this field, open research issues, challenges and future research directions are highlighted.

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

NASA Astrophysics Data System (ADS)

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

2014-11-01

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

Shape memory polymer sensors for tracking cumulative environmental exposure

NASA Astrophysics Data System (ADS)

Snyder, Ryan; Rauscher, Michael; Vining, Ben; Havens, Ernie; Havens, Teresa; McFerran, Jace

2010-04-01

Cornerstone Research Group Inc. (CRG) has developed environmental exposure tracking (EET) sensors using shape memory polymers (SMP) to monitor the degradation of perishable items, such as munitions, foods and beverages, or medicines, by measuring the cumulative exposure to temperature and moisture. SMPs are polymers whose qualities have been altered to give them dynamic shape "memory" properties. Under thermal or moisture stimuli, the SMP exhibits a radical change from a rigid thermoset to a highly flexible, elastomeric state. The dynamic response of the SMP can be tailored to match the degradation profile of the perishable item. SMP-based EET sensors require no digital memory or internal power supply and provide the capability of inexpensive, long-term life cycle monitoring of thermal and moisture exposure over time. This technology was developed through Phase I and Phase II SBIR efforts with the Navy. The emphasis of current research centers on transitioning SMP materials from the lab bench to a production environment. Here, CRG presents the commercialization progress of thermally-activated EET sensors, focusing on fabrication scale-up, process refinements, and quality control. In addition, progress on the development of vapor pressure-responsive SMP (VPR-SMP) will be discussed.

Preliminary assessment of several parameters to measure and compare usefulness of the CEOS reference pseudo-invariant calibration sites

USGS Publications Warehouse

Chander, Gyanesh; Angal, Amit; Xiong, Xiaoxiong; Helder, Dennis L.; Mishra, Nischal; Choi, Taeyoung; Wu, Aisheng

2010-01-01

Test sites are central to any future quality assurance and quality control (QA/QC) strategy. The Committee on Earth Observation Satellites (CEOS) Working Group for Calibration and Validation (WGCV) Infrared Visible Optical Sensors (IVOS) worked with collaborators around the world to establish a core set of CEOS-endorsed, globally distributed, reference standard test sites (both instrumented and pseudo-invariant) for the post-launch calibration of space-based optical imaging sensors. The pseudo-invariant calibration sites (PICS) have high reflectance and are usually made up of sand dunes with low aerosol loading and practically no vegetation. The goal of this paper is to provide preliminary assessment of "several parameters" than can be used on an operational basis to compare and measure usefulness of reference sites all over the world. The data from Landsat 7 (L7) Enhanced Thematic Mapper Plus (ETM+) and the Earth Observing-1 (EO-1) Hyperion sensors over the CEOS PICS were used to perform a preliminary assessment of several parameters, such as usable area, data availability, top-of-atmosphere (TOA) reflectance, at-sensor brightness temperature, spatial uniformity, temporal stability, spectral stability, and typical spectrum observed over the sites.

Aircraft Cabin Environmental Quality Sensors

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

Gundel, Lara; Kirchstetter, Thomas; Spears, Michael

2010-05-06

The Indoor Environment Department at Lawrence Berkeley National Laboratory (LBNL) teamed with seven universities to participate in a Federal Aviation Administration (FAA) Center of Excellence (COE) for research on environmental quality in aircraft. This report describes research performed at LBNL on selecting and evaluating sensors for monitoring environmental quality in aircraft cabins, as part of Project 7 of the FAA's COE for Airliner Cabin Environmental Research (ACER)1 effort. This part of Project 7 links to the ozone, pesticide, and incident projects for data collection and monitoring and is a component of a broader research effort on sensors by ACER. Resultsmore » from UCB and LBNL's concurrent research on ozone (ACER Project 1) are found in Weschler et al., 2007; Bhangar et al. 2008; Coleman et al., 2008 and Strom-Tejsen et al., 2008. LBNL's research on pesticides (ACER Project 2) in airliner cabins is described in Maddalena and McKone (2008). This report focused on the sensors needed for normal contaminants and conditions in aircraft. The results are intended to complement and coordinate with results from other ACER members who concentrated primarily on (a) sensors for chemical and biological pollutants that might be released intentionally in aircraft; (b) integration of sensor systems; and (c) optimal location of sensors within aircraft. The parameters and sensors were selected primarily to satisfy routine monitoring needs for contaminants and conditions that commonly occur in aircraft. However, such sensor systems can also be incorporated into research programs on environmental quality in aircraft cabins.« less

A Framework Based on Reference Data with Superordinate Accuracy for the Quality Analysis of Terrestrial Laser Scanning-Based Multi-Sensor-Systems.

PubMed

Stenz, Ulrich; Hartmann, Jens; Paffenholz, Jens-André; Neumann, Ingo

2017-08-16

Terrestrial laser scanning (TLS) is an efficient solution to collect large-scale data. The efficiency can be increased by combining TLS with additional sensors in a TLS-based multi-sensor-system (MSS). The uncertainty of scanned points is not homogenous and depends on many different influencing factors. These include the sensor properties, referencing, scan geometry (e.g., distance and angle of incidence), environmental conditions (e.g., atmospheric conditions) and the scanned object (e.g., material, color and reflectance, etc.). The paper presents methods, infrastructure and results for the validation of the suitability of TLS and TLS-based MSS. Main aspects are the backward modelling of the uncertainty on the basis of reference data (e.g., point clouds) with superordinate accuracy and the appropriation of a suitable environment/infrastructure (e.g., the calibration process of the targets for the registration of laser scanner and laser tracker data in a common coordinate system with high accuracy) In this context superordinate accuracy means that the accuracy of the acquired reference data is better by a factor of 10 than the data of the validated TLS and TLS-based MSS. These aspects play an important role in engineering geodesy, where the aimed accuracy lies in a range of a few mm or less.

Design of a Holonic Control Architecture for Distributed Sensor Management

DTIC Science & Technology

2009-09-01

Tracking tasks require only intermit - tent access to the sensors to maintain a given track quality. The higher the specified quality, the more often...resolution of the sensor (i.e., sensor mode), which can be adjusted to compensate for fast moving targets tracked over long ranges, or slower moving...but provides higher data update rates that are beneficial when tracking fast agile targets (i.e., a fighter). Table A.2 illustrates the dependence of

Enhancement of the Automated Quality Control Procedures for the International Soil Moisture Network

NASA Astrophysics Data System (ADS)

Heer, Elsa; Xaver, Angelika; Dorigo, Wouter; Messner, Romina

2017-04-01

In-situ soil moisture observations are still trusted to be the most reliable data to validate remotely sensed soil moisture products. Thus, the quality of in-situ soil moisture observations is of high importance. The International Soil Moisture Network (ISMN; http://ismn.geo.tuwien.ac.at/) provides in-situ soil moisture data from all around the world. The data is collected from individual networks and data providers, measured by different sensors in various depths. The data sets which are delivered in different units, time zones and data formats are then transformed into homogeneous data sets. An erroneous behavior of soil moisture data is very difficult to detect, due to annual and daily changes and most significantly the high influence of precipitation and snow melting processes. Only few of the network providers have a quality assessment for their data sets. Therefore, advanced quality control procedures have been developed for the ISMN (Dorigo et al. 2013). Three categories of quality checks were introduced: exceeding boundary values, geophysical consistency checks and a spectrum based approach. The spectrum based quality control algorithms aim to detect erroneous measurements which occur within plausible geophysical ranges, e.g. a sudden drop in soil moisture caused by a sensor malfunction. By defining several conditions which have to be met by the original soil moisture time series and their first and second derivative, such error types can be detected. Since the development of these sophisticated methods many more data providers shared their data with the ISMN and new types of erroneous measurements were identified. Thus, an enhancement of the automated quality control procedures became necessary. In the present work, we introduce enhancements of the existing quality control algorithms. Additionally, six completely new quality checks have been developed, e.g. detection of suspicious values before or after NAN-values, constant values and values that lie in a spectrum where a high majority of values before and after is flagged and therefore a sensor malfunction is certain. For the evaluation of the enhanced automated quality control system many test data sets were chosen, and manually validated to be compared to the existing quality control procedures and the new algorithms. Improvements will be shown that assure an appropriate assessment of the ISMN data sets, which are used for validations of soil moisture data retrieved by satellite data and are the foundation many other scientific publications.

An In-Process Surface Roughness Recognition System in End Milling Operations

ERIC Educational Resources Information Center

Yang, Lieh-Dai; Chen, Joseph C.

2004-01-01

To develop an in-process quality control system, a sensor technique and a decision-making algorithm need to be applied during machining operations. Several sensor techniques have been used in the in-process prediction of quality characteristics in machining operations. For example, an accelerometer sensor can be used to monitor the vibration of…

Large Scale Application of Vibration Sensors for Fan Monitoring at Commercial Layer Hen Houses

PubMed Central

Chen, Yan; Ni, Ji-Qin; Diehl, Claude A.; Heber, Albert J.; Bogan, Bill W.; Chai, Li-Long

2010-01-01

Continuously monitoring the operation of each individual fan can significantly improve the measurement quality of aerial pollutant emissions from animal buildings that have a large number of fans. To monitor the fan operation by detecting the fan vibration is a relatively new technique. A low-cost electronic vibration sensor was developed and commercialized. However, its large scale application has not yet been evaluated. This paper presents long-term performance results of this vibration sensor at two large commercial layer houses. Vibration sensors were installed on 164 fans of 130 cm diameter to continuously monitor the fan on/off status for two years. The performance of the vibration sensors was compared with fan rotational speed (FRS) sensors. The vibration sensors exhibited quick response and high sensitivity to fan operations and therefore satisfied the general requirements of air quality research. The study proved that detecting fan vibration was an effective method to monitor the on/off status of a large number of single-speed fans. The vibration sensor itself was $2 more expensive than a magnetic proximity FRS sensor but the overall cost including installation and data acquisition hardware was $77 less expensive than the FRS sensor. A total of nine vibration sensors failed during the study and the failure rate was related to the batches of product. A few sensors also exhibited unsteady sensitivity. As a new product, the quality of the sensor should be improved to make it more reliable and acceptable. PMID:22163544

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.

A novel method to increase LinLog CMOS sensors' performance in high dynamic range scenarios.

PubMed

Martínez-Sánchez, Antonio; Fernández, Carlos; Navarro, Pedro J; Iborra, Andrés

2011-01-01

Images from high dynamic range (HDR) scenes must be obtained with minimum loss of information. For this purpose it is necessary to take full advantage of the quantification levels provided by the CCD/CMOS image sensor. LinLog CMOS sensors satisfy the above demand by offering an adjustable response curve that combines linear and logarithmic responses. This paper presents a novel method to quickly adjust the parameters that control the response curve of a LinLog CMOS image sensor. We propose to use an Adaptive Proportional-Integral-Derivative controller to adjust the exposure time of the sensor, together with control algorithms based on the saturation level and the entropy of the images. With this method the sensor's maximum dynamic range (120 dB) can be used to acquire good quality images from HDR scenes with fast, automatic adaptation to scene conditions. Adaptation to a new scene is rapid, with a sensor response adjustment of less than eight frames when working in real time video mode. At least 67% of the scene entropy can be retained with this method.

Microwave Metamaterial-Based Sensor for Dielectric Characterization of Liquids.

PubMed

Soffiatti, André; Max, Yuri; G Silva, Sandro; M de Mendonça, Laércio

2018-05-11

This article proposed to build a system founded on metamaterial sensor antennas, which can be used to evaluate impurities in aqueous substances according to the quality of transmission between the sensor antennas. In order to do this, a dedicated setup with tests in several frequencies was deployed so as to monitor the behavior of transmission variation between sensors. These sensors are microstrip antennas with a ground plane of resonant cleaved metallic rings; the substrate functions as a metamaterial for the irradiating element. In this study, an analysis was made of transmission between the sensors, looking for variation in angles of incidence of signal and of distance between the antennas. The sensor was tested at various operating frequencies, as such 1.8 GHz, 2.4 GHz, 3.4 GHz and 4.1 GHz, resulting in different values of sensitivity. The prototypes were constructed and tested so as to analyze the dielectric effects of the impurities on NaCl and C₂H₄O₂ substances. The research aims to use these control systems of impurities in industrial premises.

Event-Based Tone Mapping for Asynchronous Time-Based Image Sensor

PubMed Central

Simon Chane, Camille; Ieng, Sio-Hoi; Posch, Christoph; Benosman, Ryad B.

2016-01-01

The asynchronous time-based neuromorphic image sensor ATIS is an array of autonomously operating pixels able to encode luminance information with an exceptionally high dynamic range (>143 dB). This paper introduces an event-based methodology to display data from this type of event-based imagers, taking into account the large dynamic range and high temporal accuracy that go beyond available mainstream display technologies. We introduce an event-based tone mapping methodology for asynchronously acquired time encoded gray-level data. A global and a local tone mapping operator are proposed. Both are designed to operate on a stream of incoming events rather than on time frame windows. Experimental results on real outdoor scenes are presented to evaluate the performance of the tone mapping operators in terms of quality, temporal stability, adaptation capability, and computational time. PMID:27642275

Integrating multisensor satellite data merging and image reconstruction in support of machine learning for better water quality management.

PubMed

Chang, Ni-Bin; Bai, Kaixu; Chen, Chi-Farn

2017-10-01

Monitoring water quality changes in lakes, reservoirs, estuaries, and coastal waters is critical in response to the needs for sustainable development. This study develops a remote sensing-based multiscale modeling system by integrating multi-sensor satellite data merging and image reconstruction algorithms in support of feature extraction with machine learning leading to automate continuous water quality monitoring in environmentally sensitive regions. This new Earth observation platform, termed "cross-mission data merging and image reconstruction with machine learning" (CDMIM), is capable of merging multiple satellite imageries to provide daily water quality monitoring through a series of image processing, enhancement, reconstruction, and data mining/machine learning techniques. Two existing key algorithms, including Spectral Information Adaptation and Synthesis Scheme (SIASS) and SMart Information Reconstruction (SMIR), are highlighted to support feature extraction and content-based mapping. Whereas SIASS can support various data merging efforts to merge images collected from cross-mission satellite sensors, SMIR can overcome data gaps by reconstructing the information of value-missing pixels due to impacts such as cloud obstruction. Practical implementation of CDMIM was assessed by predicting the water quality over seasons in terms of the concentrations of nutrients and chlorophyll-a, as well as water clarity in Lake Nicaragua, providing synergistic efforts to better monitor the aquatic environment and offer insightful lake watershed management strategies. Copyright © 2017 Elsevier Ltd. All rights reserved.

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 ...

Communicating Instantaneous Air Quality Data: Pilot Project Feed Back

EPA Pesticide Factsheets

EPA is launching a pilot project to test a new tool for making instantaneous outdoor air quality data useful for the public. The new “sensor scale” is designed to be used with air quality sensors that provide data in short time increments – often as little

Multi-Sensor Fusion of Infrared and Electro-Optic Signals for High Resolution Night Images

PubMed Central

Huang, Xiaopeng; Netravali, Ravi; Man, Hong; Lawrence, Victor

2012-01-01

Electro-optic (EO) image sensors exhibit the properties of high resolution and low noise level at daytime, but they do not work in dark environments. Infrared (IR) image sensors exhibit poor resolution and cannot separate objects with similar temperature. Therefore, we propose a novel framework of IR image enhancement based on the information (e.g., edge) from EO images, which improves the resolution of IR images and helps us distinguish objects at night. Our framework superimposing/blending the edges of the EO image onto the corresponding transformed IR image improves their resolution. In this framework, we adopt the theoretical point spread function (PSF) proposed by Hardie et al. for the IR image, which has the modulation transfer function (MTF) of a uniform detector array and the incoherent optical transfer function (OTF) of diffraction-limited optics. In addition, we design an inverse filter for the proposed PSF and use it for the IR image transformation. The framework requires four main steps: (1) inverse filter-based IR image transformation; (2) EO image edge detection; (3) registration; and (4) blending/superimposing of the obtained image pair. Simulation results show both blended and superimposed IR images, and demonstrate that blended IR images have better quality over the superimposed images. Additionally, based on the same steps, simulation result shows a blended IR image of better quality when only the original IR image is available. PMID:23112602

Multi-sensor fusion of infrared and electro-optic signals for high resolution night images.

PubMed

Huang, Xiaopeng; Netravali, Ravi; Man, Hong; Lawrence, Victor

2012-01-01

Electro-optic (EO) image sensors exhibit the properties of high resolution and low noise level at daytime, but they do not work in dark environments. Infrared (IR) image sensors exhibit poor resolution and cannot separate objects with similar temperature. Therefore, we propose a novel framework of IR image enhancement based on the information (e.g., edge) from EO images, which improves the resolution of IR images and helps us distinguish objects at night. Our framework superimposing/blending the edges of the EO image onto the corresponding transformed IR image improves their resolution. In this framework, we adopt the theoretical point spread function (PSF) proposed by Hardie et al. for the IR image, which has the modulation transfer function (MTF) of a uniform detector array and the incoherent optical transfer function (OTF) of diffraction-limited optics. In addition, we design an inverse filter for the proposed PSF and use it for the IR image transformation. The framework requires four main steps: (1) inverse filter-based IR image transformation; (2) EO image edge detection; (3) registration; and (4) blending/superimposing of the obtained image pair. Simulation results show both blended and superimposed IR images, and demonstrate that blended IR images have better quality over the superimposed images. Additionally, based on the same steps, simulation result shows a blended IR image of better quality when only the original IR image is available.

Strain sensitivity of carbon nanotube cement-based composites for structural health monitoring

NASA Astrophysics Data System (ADS)

D'Alessandro, Antonella; Ubertini, Filippo; Laflamme, Simon; Rallini, Marco; Materazzi, Annibale L.; Kenny, Josè M.

2016-04-01

Cement-based smart sensors appear particularly suitable for monitoring applications, due to their self-sensing abilities, their ease of use, and their numerous possible field applications. The addition of conductive carbon nanofillers into a cementitious matrix provides the material with piezoresistive characteristics and enhanced sensitivity to mechanical alterations. The strain-sensing ability is achieved by correlating the variation of external loads or deformations with the variation of specific electrical parameters, such as the electrical resistance. Among conductive nanofillers, carbon nanotubes (CNTs) have shown promise for the fabrication of self-monitoring composites. However, some issues related to the filler dispersion and the mix design of cementitious nanoadded materials need to be further investigated. For instance, a small difference in the added quantity of a specific nanofiller in a cement-matrix composite can substantially change the quality of the dispersion and the strain sensitivity of the resulting material. The present research focuses on the strain sensitivity of concrete, mortar and cement paste sensors fabricated with different amounts of carbon nanotube inclusions. The aim of the work is to investigate the quality of dispersion of the CNTs in the aqueous solutions, the physical properties of the fresh mixtures, the electromechanical properties of the hardened materials, and the sensing properties of the obtained transducers. Results show that cement-based sensors with CNT inclusions, if properly implemented, can be favorably applied to structural health monitoring.

Identification of Hot Moments and Hot Spots for Real-Time Adaptive Control of Multi-scale Environmental Sensor Networks

NASA Astrophysics Data System (ADS)

Wietsma, T.; Minsker, B. S.

2012-12-01

Increased sensor throughput combined with decreasing hardware costs has led to a disruptive growth in data volume. This disruption, popularly termed "the data deluge," has placed new demands for cyberinfrastructure and information technology skills among researchers in many academic fields, including the environmental sciences. Adaptive sampling has been well established as an effective means of improving network resource efficiency (energy, bandwidth) without sacrificing sample set quality relative to traditional uniform sampling. However, using adaptive sampling for the explicit purpose of improving resolution over events -- situations displaying intermittent dynamics and unique hydrogeological signatures -- is relatively new. In this paper, we define hot spots and hot moments in terms of sensor signal activity as measured through discrete Fourier analysis. Following this frequency-based approach, we apply the Nyquist-Shannon sampling theorem, a fundamental contribution from signal processing that led to the field of information theory, for analysis of uni- and multivariate environmental signal data. In the scope of multi-scale environmental sensor networks, we present several sampling control algorithms, derived from the Nyquist-Shannon theorem, that operate at local (field sensor), regional (base station for aggregation of field sensor data), and global (Cloud-based, computationally intensive models) scales. Evaluated over soil moisture data, results indicate significantly greater sample density during precipitation events while reducing overall sample volume. Using these algorithms as indicators rather than control mechanisms, we also discuss opportunities for spatio-temporal modeling as a tool for planning/modifying sensor network deployments. Locally adaptive model based on Nyquist-Shannon sampling theorem Pareto frontiers for local, regional, and global models relative to uniform sampling. Objectives are (1) overall sampling efficiency and (2) sampling efficiency during hot moments as identified using heuristic approach.

Understanding Smart Home Sensor Data for Ageing in Place Through Everyday Household Routines: A Mixed Method Case Study.

PubMed

van Kasteren, Yasmin; Bradford, Dana; Zhang, Qing; Karunanithi, Mohan; Ding, Hang

2017-06-13

An ongoing challenge for smart homes research for aging-in-place is how to make sense of the large amounts of data from in-home sensors to facilitate real-time monitoring and develop reliable alerts. The objective of our study was to explore the usefulness of a routine-based approach for making sense of smart home data for the elderly. Maximum variation sampling was used to select three cases for an in-depth mixed methods exploration of the daily routines of three elderly participants in a smart home trial using 180 days of power use and motion sensor data and longitudinal interview data. Sensor data accurately matched self-reported routines. By comparing daily movement data with personal routines, it was possible to identify changes in routine that signaled illness, recovery from bereavement, and gradual deterioration of sleep quality and daily movement. Interview and sensor data also identified changes in routine with variations in temperature and daylight hours. The findings demonstrated that a routine-based approach makes interpreting sensor data easy, intuitive, and transparent. They highlighted the importance of understanding and accounting for individual differences in preferences for routinization and the influence of the cyclical nature of daily routines, social or cultural rhythms, and seasonal changes in temperature and daylight hours when interpreting information based on sensor data. This research has demonstrated the usefulness of a routine-based approach for making sense of smart home data, which has furthered the understanding of the challenges that need to be addressed in order to make real-time monitoring and effective alerts a reality. ©Yasmin van Kasteren, Dana Bradford, Qing Zhang, Mohan Karunanithi, Hang Ding. Originally published in JMIR Mhealth and Uhealth (http://mhealth.jmir.org), 13.06.2017.

Understanding Smart Home Sensor Data for Ageing in Place Through Everyday Household Routines: A Mixed Method Case Study

PubMed Central

van Kasteren, Yasmin; Bradford, Dana; Karunanithi, Mohan; Ding, Hang

2017-01-01

Background An ongoing challenge for smart homes research for aging-in-place is how to make sense of the large amounts of data from in-home sensors to facilitate real-time monitoring and develop reliable alerts. Objective The objective of our study was to explore the usefulness of a routine-based approach for making sense of smart home data for the elderly. Methods Maximum variation sampling was used to select three cases for an in-depth mixed methods exploration of the daily routines of three elderly participants in a smart home trial using 180 days of power use and motion sensor data and longitudinal interview data. Results Sensor data accurately matched self-reported routines. By comparing daily movement data with personal routines, it was possible to identify changes in routine that signaled illness, recovery from bereavement, and gradual deterioration of sleep quality and daily movement. Interview and sensor data also identified changes in routine with variations in temperature and daylight hours. Conclusions The findings demonstrated that a routine-based approach makes interpreting sensor data easy, intuitive, and transparent. They highlighted the importance of understanding and accounting for individual differences in preferences for routinization and the influence of the cyclical nature of daily routines, social or cultural rhythms, and seasonal changes in temperature and daylight hours when interpreting information based on sensor data. This research has demonstrated the usefulness of a routine-based approach for making sense of smart home data, which has furthered the understanding of the challenges that need to be addressed in order to make real-time monitoring and effective alerts a reality. PMID:28611014

Balance Improvement Effects of Biofeedback Systems with State-of-the-Art Wearable Sensors: A Systematic Review.

PubMed

Ma, Christina Zong-Hao; Wong, Duo Wai-Chi; Lam, Wing Kai; Wan, Anson Hong-Ping; Lee, Winson Chiu-Chun

2016-03-25

Falls and fall-induced injuries are major global public health problems. Balance and gait disorders have been the second leading cause of falls. Inertial motion sensors and force sensors have been widely used to monitor both static and dynamic balance performance. Based on the detected performance, instant visual, auditory, electrotactile and vibrotactile biofeedback could be provided to augment the somatosensory input and enhance balance control. This review aims to synthesize the research examining the effect of biofeedback systems, with wearable inertial motion sensors and force sensors, on balance performance. Randomized and non-randomized clinical trials were included in this review. All studies were evaluated based on the methodological quality. Sample characteristics, device design and study characteristics were summarized. Most previous studies suggested that biofeedback devices were effective in enhancing static and dynamic balance in healthy young and older adults, and patients with balance and gait disorders. Attention should be paid to the choice of appropriate types of sensors and biofeedback for different intended purposes. Maximizing the computing capacity of the micro-processer, while minimizing the size of the electronic components, appears to be the future direction of optimizing the devices. Wearable balance-improving devices have their potential of serving as balance aids in daily life, which can be used indoors and outdoors.

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

PubMed

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

2012-01-01

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

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

PubMed Central

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

2012-01-01

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

Balance Improvement Effects of Biofeedback Systems with State-of-the-Art Wearable Sensors: A Systematic Review

PubMed Central

Ma, Christina Zong-Hao; Wong, Duo Wai-Chi; Lam, Wing Kai; Wan, Anson Hong-Ping; Lee, Winson Chiu-Chun

2016-01-01

Falls and fall-induced injuries are major global public health problems. Balance and gait disorders have been the second leading cause of falls. Inertial motion sensors and force sensors have been widely used to monitor both static and dynamic balance performance. Based on the detected performance, instant visual, auditory, electrotactile and vibrotactile biofeedback could be provided to augment the somatosensory input and enhance balance control. This review aims to synthesize the research examining the effect of biofeedback systems, with wearable inertial motion sensors and force sensors, on balance performance. Randomized and non-randomized clinical trials were included in this review. All studies were evaluated based on the methodological quality. Sample characteristics, device design and study characteristics were summarized. Most previous studies suggested that biofeedback devices were effective in enhancing static and dynamic balance in healthy young and older adults, and patients with balance and gait disorders. Attention should be paid to the choice of appropriate types of sensors and biofeedback for different intended purposes. Maximizing the computing capacity of the micro-processer, while minimizing the size of the electronic components, appears to be the future direction of optimizing the devices. Wearable balance-improving devices have their potential of serving as balance aids in daily life, which can be used indoors and outdoors. PMID:27023558

mHealthMon: toward energy-efficient and distributed mobile health monitoring using parallel offloading.

PubMed

Ahnn, Jong Hoon; Potkonjak, Miodrag

2013-10-01

Although mobile health monitoring where mobile sensors continuously gather, process, and update sensor readings (e.g. vital signals) from patient's sensors is emerging, little effort has been investigated in an energy-efficient management of sensor information gathering and processing. Mobile health monitoring with the focus of energy consumption may instead be holistically analyzed and systematically designed as a global solution to optimization subproblems. This paper presents an attempt to decompose the very complex mobile health monitoring system whose layer in the system corresponds to decomposed subproblems, and interfaces between them are quantified as functions of the optimization variables in order to orchestrate the subproblems. We propose a distributed and energy-saving mobile health platform, called mHealthMon where mobile users publish/access sensor data via a cloud computing-based distributed P2P overlay network. The key objective is to satisfy the mobile health monitoring application's quality of service requirements by modeling each subsystem: mobile clients with medical sensors, wireless network medium, and distributed cloud services. By simulations based on experimental data, we present the proposed system can achieve up to 10.1 times more energy-efficient and 20.2 times faster compared to a standalone mobile health monitoring application, in various mobile health monitoring scenarios applying a realistic mobility model.

Body-monitoring with photonic textiles: a reflective heartbeat sensor based on polymer optical fibres

PubMed Central

Braun, Fabian; Ferrario, Damien; Rossi, René M.; Scheel-Sailer, Anke; Wolf, Martin; Bona, Gian-Luca; Hufenus, Rudolf; Scherer, Lukas J.

2017-01-01

Knowledge of an individual's skin condition is important for pressure ulcer prevention. Detecting early changes in skin through perfusion, oxygen saturation values, and pressure on tissue and subsequent therapeutic intervention could increase patients' quality of life drastically. However, most existing sensing options create additional risk of ulcer development due to further pressure on and chafing of the skin. Here, as a first component, we present a flexible, photonic textile-based sensor for the continuous monitoring of the heartbeat and blood flow. Polymer optical fibres (POFs) are melt-spun continuously and characterized optically and mechanically before being embroidered. The resulting sensor shows flexibility when embroidered into a moisture-wicking fabric, and withstands disinfection with hospital-type laundry cycles. Additionally, the new sensor textile shows a lower static coefficient of friction (COF) than conventionally used bedsheets in both dry and sweaty conditions versus a skin model. Finally, we demonstrate the functionality of our sensor by measuring the heartbeat at the forehead in reflection mode and comparing it with commercial finger photoplethysmography for several subjects. Our results will allow the development of flexible, individualized, and fully textile-integrated wearable sensors for sensitive skin conditions and general long-term monitoring of patients with risk for pressure ulcer. PMID:28275123

Body-monitoring with photonic textiles: a reflective heartbeat sensor based on polymer optical fibres.

PubMed

Quandt, Brit M; Braun, Fabian; Ferrario, Damien; Rossi, René M; Scheel-Sailer, Anke; Wolf, Martin; Bona, Gian-Luca; Hufenus, Rudolf; Scherer, Lukas J; Boesel, Luciano F

2017-03-01

Knowledge of an individual's skin condition is important for pressure ulcer prevention. Detecting early changes in skin through perfusion, oxygen saturation values, and pressure on tissue and subsequent therapeutic intervention could increase patients' quality of life drastically. However, most existing sensing options create additional risk of ulcer development due to further pressure on and chafing of the skin. Here, as a first component, we present a flexible, photonic textile-based sensor for the continuous monitoring of the heartbeat and blood flow. Polymer optical fibres (POFs) are melt-spun continuously and characterized optically and mechanically before being embroidered. The resulting sensor shows flexibility when embroidered into a moisture-wicking fabric, and withstands disinfection with hospital-type laundry cycles. Additionally, the new sensor textile shows a lower static coefficient of friction (COF) than conventionally used bedsheets in both dry and sweaty conditions versus a skin model. Finally, we demonstrate the functionality of our sensor by measuring the heartbeat at the forehead in reflection mode and comparing it with commercial finger photoplethysmography for several subjects. Our results will allow the development of flexible, individualized, and fully textile-integrated wearable sensors for sensitive skin conditions and general long-term monitoring of patients with risk for pressure ulcer. © 2017 The Author(s).

A High Performance Torque Sensor for Milling Based on a Piezoresistive MEMS Strain Gauge

PubMed Central

Qin, Yafei; Zhao, Yulong; Li, Yingxue; Zhao, You; Wang, Peng

2016-01-01

In high speed and high precision machining applications, it is important to monitor the machining process in order to ensure high product quality. For this purpose, it is essential to develop a dynamometer with high sensitivity and high natural frequency which is suited to these conditions. This paper describes the design, calibration and performance of a milling torque sensor based on piezoresistive MEMS strain. A detailed design study is carried out to optimize the two mutually-contradictory indicators sensitivity and natural frequency. The developed torque sensor principally consists of a thin-walled cylinder, and a piezoresistive MEMS strain gauge bonded on the surface of the sensing element where the shear strain is maximum. The strain gauge includes eight piezoresistances and four are connected in a full Wheatstone circuit bridge, which is used to measure the applied torque force during machining procedures. Experimental static calibration results show that the sensitivity of torque sensor has been improved to 0.13 mv/Nm. A modal impact test indicates that the natural frequency of torque sensor reaches 1216 Hz, which is suitable for high speed machining processes. The dynamic test results indicate that the developed torque sensor is stable and practical for monitoring the milling process. PMID:27070620

CZT sensors for Computed Tomography: from crystal growth to image quality

NASA Astrophysics Data System (ADS)

Iniewski, K.

2016-12-01

Recent advances in Traveling Heater Method (THM) growth and device fabrication that require additional processing steps have enabled to dramatically improve hole transport properties and reduce polarization effects in Cadmium Zinc Telluride (CZT) material. As a result high flux operation of CZT sensors at rates in excess of 200 Mcps/mm2 is now possible and has enabled multiple medical imaging companies to start building prototype Computed Tomography (CT) scanners. CZT sensors are also finding new commercial applications in non-destructive testing (NDT) and baggage scanning. In order to prepare for high volume commercial production we are moving from individual tile processing to whole wafer processing using silicon methodologies, such as waxless processing, cassette based/touchless wafer handling. We have been developing parametric level screening at the wafer stage to ensure high wafer quality before detector fabrication in order to maximize production yields. These process improvements enable us, and other CZT manufacturers who pursue similar developments, to provide high volume production for photon counting applications in an economically feasible manner. CZT sensors are capable of delivering both high count rates and high-resolution spectroscopic performance, although it is challenging to achieve both of these attributes simultaneously. The paper discusses material challenges, detector design trade-offs and ASIC architectures required to build cost-effective CZT based detection systems. Photon counting ASICs are essential part of the integrated module platforms as charge-sensitive electronics needs to deal with charge-sharing and pile-up effects.

Resistive sensing of gaseous nitrogen dioxide using a dispersion of single-walled carbon nanotubes in an ionic liquid

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

Mishra, Prabhash; Department of Nanoengineering, Samara State Aerospace University, 443086 Samara; Pavelyev, V.S.

2016-06-15

Graphical abstract: Ionic liquid ([C6-mim]PF6) used as dispersant agent for SWCNTs: An investigations were carried out to find the structural quality and surface modification for sensor application. - Highlights: • An effective technique based on Ionic liquids (IL) and their use as a dispersant. • Electron microscopy and spectroscopy for structure characterization. • Covalent linkage of ILs with SWNTs and dispersion of SWCNTs. • The IL-wrapped sensing film, capable for detecting trace levels of gas. - Abstract: Single-walled carbon nanotubes (SWCNTs) were dispersed in an imidazolium-based ionic liquid (IL) and investigated in terms of structural quality, surface functionalization and inter-CNTmore » force. Analysis by field emission electron microscopy and transmission electron microscopy shows the IL layer to coat the SWNTs, and FTIR and Raman spectroscopy confirm strong binding of the ILs to the SWNTs. Two kinds of resistive sensors were fabricated, one by drop casting of IL-wrapped SWCNTs, the other by conventional dispersion of SWCNTs. Good response and recovery to NO{sub 2} is achieved with the IL-wrapped SWCNTs material upon UV-light exposure, which is needed because decrease the desorption energy barrier to increase the gas molecule desorption. NO{sub 2} can be detected in the 1–20 ppm concentration range. The sensor is not interfered by humidity due to the hydrophobic tail of PF6 (ionic liquid) that makes our sensor highly resistant to moisture.« less

Influence of the internal wall thickness of electrical capacitance tomography sensors on image quality

NASA Astrophysics Data System (ADS)

Liang, Shiguo; Ye, Jiamin; Wang, Haigang; Wu, Meng; Yang, Wuqiang

2018-03-01

In the design of electrical capacitance tomography (ECT) sensors, the internal wall thickness can vary with specific applications, and it is a key factor that influences the sensitivity distribution and image quality. This paper will discuss the effect of the wall thickness of ECT sensors on image quality. Three flow patterns are simulated for wall thicknesses of 2.5 mm to 15 mm on eight-electrode ECT sensors. The sensitivity distributions and potential distributions are compared for different wall thicknesses. Linear back-projection and Landweber iteration algorithms are used for image reconstruction. Relative image error and correlation coefficients are used for image evaluation using both simulation and experimental data.

Estimating respiratory rate from FBG optical sensors by using signal quality measurement.

PubMed

Yongwei Zhu; Maniyeri, Jayachandran; Fook, Victor Foo Siang; Haihong Zhang

2015-08-01

Non-intrusiveness is one of the advantages of in-bed optical sensor device for monitoring vital signs, including heart rate and respiratory rate. Estimating respiratory rate reliably using such sensors, however, is challenging, due to body movement, signal variation according to different subjects or body positions, etc. This paper presents a method for reliable respiratory rate estimation for FBG optical sensors by introducing signal quality estimation. The method estimates the quality of the signal waveform by detecting regularly repetitive patterns using proposed spectrum and cepstrum analysis. Multiple window sizes are used to cater for a wide range of target respiratory rates. Furthermore, the readings of multiple sensors are fused to derive a final respiratory rate. Experiments with 12 subjects and 2 body positions were conducted using polysomnography belt signal as groundtruth. The results demonstrated the effectiveness of the method.

Au/Si nanorod-based biosensor for food pathogen detection

USDA-ARS?s Scientific Manuscript database

Technical Abstract Among several potentials of nanotechnology applications for food industry, development of nanoscale sensors for food safety and quality measurement are emerging. A novel biosensor for Salmonella detection was developed using Au/Si nanorods. The Si nanorods were fabricated by gla...

Cone penetrometer equipped with piezoelectric sensors for measurement of soil stiffness in highway pavement.

DOT National Transportation Integrated Search

2005-11-01

The stiffness (elastic modulus and shear modulus) and Poisson's ratio of the base and sublayers are important parameters in the design and quality assurance during construction of highway pavements. The new highway construction guide proposed by AASH...

Wearable Sensor Data Classification for Human Activity Recognition Based on an Iterative Learning Framework.

PubMed

Davila, Juan Carlos; Cretu, Ana-Maria; Zaremba, Marek

2017-06-07

The design of multiple human activity recognition applications in areas such as healthcare, sports and safety relies on wearable sensor technologies. However, when making decisions based on the data acquired by such sensors in practical situations, several factors related to sensor data alignment, data losses, and noise, among other experimental constraints, deteriorate data quality and model accuracy. To tackle these issues, this paper presents a data-driven iterative learning framework to classify human locomotion activities such as walk, stand, lie, and sit, extracted from the Opportunity dataset. Data acquired by twelve 3-axial acceleration sensors and seven inertial measurement units are initially de-noised using a two-stage consecutive filtering approach combining a band-pass Finite Impulse Response (FIR) and a wavelet filter. A series of statistical parameters are extracted from the kinematical features, including the principal components and singular value decomposition of roll, pitch, yaw and the norm of the axial components. The novel interactive learning procedure is then applied in order to minimize the number of samples required to classify human locomotion activities. Only those samples that are most distant from the centroids of data clusters, according to a measure presented in the paper, are selected as candidates for the training dataset. The newly built dataset is then used to train an SVM multi-class classifier. The latter will produce the lowest prediction error. The proposed learning framework ensures a high level of robustness to variations in the quality of input data, while only using a much lower number of training samples and therefore a much shorter training time, which is an important consideration given the large size of the dataset.

Deep-UV sensors based on SAW oscillators using low-temperature-grown AlN films on sapphires.

PubMed

Laksana, Chipta; Chen, Meei-Ru; Liang, Yen; Tzou, An-Jyeg; Kao, Hui-Ling; Jeng, Erik; Chen, Jyh; Chen, Hou-Guang; Jian, Sheng-Rui

2011-08-01

High-quality epitaxial AlN films were deposited on sapphire substrates at low growth temperature using a helicon sputtering system. SAW filters fabricated on the AlN films exhibited excellent characteristics, with center frequency of 354.2 MHz, which corresponds to a phase velocity of 5667 m/s. An oscillator fabricated using AlN-based SAW devices is presented and applied to deep-UV light detection. A frequency downshift of about 43 KHz was observed when the surface of SAW device was illuminated by a UV source with dominant wavelength of around 200 nm. The results indicate the feasibility of developing remote sensors for deep-UV measurement using AlN-based SAW oscillators.

Design and analysis of photonic crystal micro-cavity based optical sensor platform

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

Goyal, Amit Kumar, E-mail: amitgoyal.ceeri@gmail.com; Dutta, Hemant Sankar, E-mail: hemantdutta97@gmail.com; Pal, Suchandan, E-mail: spal@ceeri.ernet.in

2016-04-13

In this paper, the design of a two-dimensional photonic crystal micro-cavity based integrated-optic sensor platform is proposed. The behaviour of designed cavity is analyzed using two-dimensional Finite Difference Time Domain (FDTD) method. The structure is designed by deliberately inserting some defects in a photonic crystal waveguide structure. Proposed structure shows a quality factor (Q) of about 1e5 and the average sensitivity of 500nm/RIU in the wavelength range of 1450 – 1580 nm. Sensing technique is based on the detection of shift in upper-edge cut-off wavelength for a reference signal strength of –10 dB in accordance with the change in refractive index ofmore » analyte.« less

Label-free detection of biomolecules with Ta2O5-based field effect devices

NASA Astrophysics Data System (ADS)

Branquinho, Rita Maria Mourao Salazar

Field-effect-based devices (FEDs) are becoming a basic structural element in a new generation of micro biosensors. Their numerous advantages such as small size, labelfree response and versatility, together with the possibility of on-chip integration of biosensor arrays with a future prospect of low-cost mass production, make their development highly desirable. The present thesis focuses on the study and optimization of tantalum pentoxide (Ta2O5) deposited by rf magnetron sputtering at room temperature, and their application as sensitive layer in biosensors based on field effect devices (BioFEDs). As such, the influence of several deposition parameters and post-processing annealing temperature and surface plasma treatment on the film¡¦s properties was investigated. Electrolyte-insulator-semiconductor (EIS) field-effect-based sensors comprising the optimized Ta2O5 sensitive layer were applied to the development of BioFEDs. Enzyme functionalized sensors (EnFEDs) were produced for penicillin detection. These sensors were also applied to the label free detection of DNA and the monitoring of its amplification via polymerase chain reaction (PCR), real time PCR (RT-PCR) and loop mediated isothermal amplification (LAMP). Ion sensitive field effect transistors (ISFETs) based on semiconductor oxides comprising the optimized Ta2O5 sensitive layer were also fabricated. EIS sensors comprising Ta2O5 films produced with optimized conditions demonstrated near Nernstian pH sensitivity, 58+/-0.3 mV/pH. These sensors were successfully applied to the label-free detection of penicillin and DNA. Penicillinase functionalized sensors showed a 29+/-7 mV/mM sensitivity towards penicillin detection up to 4 mM penicillin concentration. DNA detection was achieved with 30 mV/mugM sensitivity and DNA amplification monitoring with these sensors showed comparable results to those obtained with standard fluorescence based methods. Semiconductor oxides-based ISFETs with Ta2O5 sensitive layer were also produced. Finally, the high quality and sensitivity demonstrated by Ta2O5 thin films produced at low temperature by rf magnetron sputtering allows for their application as sensitive layer in field effect sensors.

Real-time contaminant detection and classification in a drinking water pipe using conventional water quality sensors: techniques and experimental results.

PubMed

Jeffrey Yang, Y; Haught, Roy C; Goodrich, James A

2009-06-01

Accurate detection and identification of natural or intentional contamination events in a drinking water pipe is critical to drinking water supply security and health risk management. To use conventional water quality sensors for the purpose, we have explored a real-time event adaptive detection, identification and warning (READiw) methodology and examined it using pilot-scale pipe flow experiments of 11 chemical and biological contaminants each at three concentration levels. The tested contaminants include pesticide and herbicides (aldicarb, glyphosate and dicamba), alkaloids (nicotine and colchicine), E. coli in terrific broth, biological growth media (nutrient broth, terrific broth, tryptic soy broth), and inorganic chemical compounds (mercuric chloride and potassium ferricyanide). First, through adaptive transformation of the sensor outputs, contaminant signals were enhanced and background noise was reduced in time-series plots leading to detection and identification of all simulated contamination events. The improved sensor detection threshold was 0.1% of the background for pH and oxidation-reduction potential (ORP), 0.9% for free chlorine, 1.6% for total chlorine, and 0.9% for chloride. Second, the relative changes calculated from adaptively transformed residual chlorine measurements were quantitatively related to contaminant-chlorine reactivity in drinking water. We have shown that based on these kinetic and chemical differences, the tested contaminants were distinguishable in forensic discrimination diagrams made of adaptively transformed sensor measurements.

Wearable technology for spine movement assessment: A systematic review.

PubMed

Papi, Enrica; Koh, Woon Senn; McGregor, Alison H

2017-11-07

Continuous monitoring of spine movement function could enhance our understanding of low back pain development. Wearable technologies have gained popularity as promising alternative to laboratory systems in allowing ambulatory movement analysis. This paper aims to review the state of art of current use of wearable technology to assess spine kinematics and kinetics. Four electronic databases and reference lists of relevant articles were searched to find studies employing wearable technologies to assess the spine in adults performing dynamic movements. Two reviewers independently identified relevant papers. Customised data extraction and quality appraisal form were developed to extrapolate key details and identify risk of biases of each study. Twenty-two articles were retrieved that met the inclusion criteria: 12 were deemed of medium quality (score 33.4-66.7%), and 10 of high quality (score >66.8%). The majority of articles (19/22) reported validation type studies. Only 6 reported data collection in real-life environments. Multiple sensors type were used: electrogoniometers (3/22), strain gauges based sensors (3/22), textile piezoresistive sensor (1/22) and accelerometers often used with gyroscopes and magnetometers (15/22). Two sensors units were mainly used and placing was commonly reported on the spine lumbar and sacral regions. The sensors were often wired to data transmitter/logger resulting in cumbersome systems. Outcomes were mostly reported relative to the lumbar segment and in the sagittal plane, including angles, range of motion, angular velocity, joint moments and forces. This review demonstrates the applicability of wearable technology to assess the spine, although this technique is still at an early stage of development. Copyright © 2017 The Authors. Published by Elsevier Ltd.. All rights reserved.

Integrating Predictive Modeling with Control System Design for Managed Aquifer Recharge and Recovery Applications

NASA Astrophysics Data System (ADS)

Drumheller, Z. W.; Regnery, J.; Lee, J. H.; Illangasekare, T. H.; Kitanidis, P. K.; Smits, K. M.

2014-12-01

Aquifers around the world show troubling signs of irreversible depletion and seawater intrusion as climate change, population growth, and urbanization led to reduced natural recharge rates and overuse. Scientists and engineers have begun to re-investigate the technology of managed aquifer recharge and recovery (MAR) as a means to increase the reliability of the diminishing and increasingly variable groundwater supply. MAR systems offer the possibility of naturally increasing groundwater storage while improving the quality of impaired water used for recharge. Unfortunately, MAR systems remain wrought with operational challenges related to the quality and quantity of recharged and recovered water stemming from a lack of data-driven, real-time control. Our project seeks to ease the operational challenges of MAR facilities through the implementation of active sensor networks, adaptively calibrated flow and transport models, and simulation-based meta-heuristic control optimization methods. The developed system works by continually collecting hydraulic and water quality data from a sensor network embedded within the aquifer. The data is fed into an inversion algorithm, which calibrates the parameters and initial conditions of a predictive flow and transport model. The calibrated model is passed to a meta-heuristic control optimization algorithm (e.g. genetic algorithm) to execute the simulations and determine the best course of action, i.e., the optimal pumping policy for current aquifer conditions. The optimal pumping policy is manually or autonomously applied. During operation, sensor data are used to assess the accuracy of the optimal prediction and augment the pumping strategy as needed. At laboratory-scale, a small (18"H x 46"L) and an intermediate (6'H x 16'L) two-dimensional synthetic aquifer were constructed and outfitted with sensor networks. Data collection and model inversion components were developed and sensor data were validated by analytical measurements.

Can single empirical algorithms accurately predict inland shallow water quality status from high resolution, multi-sensor, multi-temporal satellite data?

NASA Astrophysics Data System (ADS)

Theologou, I.; Patelaki, M.; Karantzalos, K.

2015-04-01

Assessing and monitoring water quality status through timely, cost effective and accurate manner is of fundamental importance for numerous environmental management and policy making purposes. Therefore, there is a current need for validated methodologies which can effectively exploit, in an unsupervised way, the enormous amount of earth observation imaging datasets from various high-resolution satellite multispectral sensors. To this end, many research efforts are based on building concrete relationships and empirical algorithms from concurrent satellite and in-situ data collection campaigns. We have experimented with Landsat 7 and Landsat 8 multi-temporal satellite data, coupled with hyperspectral data from a field spectroradiometer and in-situ ground truth data with several physico-chemical and other key monitoring indicators. All available datasets, covering a 4 years period, in our case study Lake Karla in Greece, were processed and fused under a quantitative evaluation framework. The performed comprehensive analysis posed certain questions regarding the applicability of single empirical models across multi-temporal, multi-sensor datasets towards the accurate prediction of key water quality indicators for shallow inland systems. Single linear regression models didn't establish concrete relations across multi-temporal, multi-sensor observations. Moreover, the shallower parts of the inland system followed, in accordance with the literature, different regression patterns. Landsat 7 and 8 resulted in quite promising results indicating that from the recreation of the lake and onward consistent per-sensor, per-depth prediction models can be successfully established. The highest rates were for chl-a (r2=89.80%), dissolved oxygen (r2=88.53%), conductivity (r2=88.18%), ammonium (r2=87.2%) and pH (r2=86.35%), while the total phosphorus (r2=70.55%) and nitrates (r2=55.50%) resulted in lower correlation rates.

Rapid determination of soil quality and earthworm impacts on soil microbial communities using fluorescence-based respirometry

NASA Astrophysics Data System (ADS)

Prendergast-Miller, Miranda T.; Thurston, Josh; Taylor, Joe; Helgason, Thorunn; Ashauer, Roman; Hodson, Mark E.

2017-04-01

We applied a fluorescence-based respirometry method currently devised for aquatic ecotoxicology studies to rapidly measure soil microbial oxygen consumption as a function of soil quality. In this study, soil was collected from an arable wheat field and the field margin. These two soil habitats are known to differ in their soil quality due to differences in their use and management as well as plant, microbial and earthworm community. The earthworm Lumbricus terrestris was incubated in arable or margin soil for three weeks. After this initial phase, a transfer experiment was then conducted to test the hypothesis that earthworm 'migration' alters soil microbial community function and diversity. In this transfer experiment, earthworms incubated in margin soil were transferred to arable soil. The converse transfer (i.e. earthworms incubated in arable soil) was also conducted. Soils of each type with no earthworms were also incubated as controls. After a further four week incubation, the impact of earthworm migration on the soil microbial community was tested by measuring oxygen consumption. Replicated soil slurry subsamples were aliquoted into individual respirometer wells (600 μl volume) on a glass 24-well microplate (Loligo Systems, Denmark) fitted with non-invasive, reusable oxygen sensor spots. The sealed microplate was then attached to an oxygen fluorescence sensor (SDR SensorDish Reader, PreSens, Germany). Oxygen consumption was measured in real-time over a 2 hr period following standard operating procedures. Soil microbial activity was measured with and without an added carbon source (glucose or cellulose, 50 mg C L-1). Using this system, we were able to differentiate between soil type, earthworm treatment and C source. Earthworm-driven impacts on soil microbial oxygen consumption were also supported by changes in soil microbial community structure and diversity revealed using DNA-based sequencing techniques. This method provides a simple and rapid system for measuring soil quality and has the potential for use in a variety of scenarios investigating impacts on soil microbial function.

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

PubMed

Hwang, Jeonghwan; Shin, Changsun; Yoe, Hyun

2010-01-01

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

LASER APPLICATIONS AND OTHER TOPICS IN QUANTUM ELECTRONICS: Holographic sensors for diagnostics of solution components

NASA Astrophysics Data System (ADS)

Kraiskii, A. V.; Postnikov, V. A.; Suitanov, T. T.; Khamidulin, A. V.

2010-02-01

The properties of holographic sensors of two types are studied. The sensors are based on a three-dimensional polymer-network matrix of copolymers of acrylamide, acrylic acid (which are sensitive to the medium acidity and bivalent metal ions) and aminophenylboronic acid (sensitive to glucose). It is found that a change in the ionic composition of a solution results in changes in the distance between layers and in the diffraction efficiency of holograms. Variations in the shape of spectral lines, which are attributed to the inhomogeneity of a sensitive layer, and nonmonotonic changes in the emulsion thickness and diffraction efficiency were observed during transient processes. The composition of the components of a hydrogel medium is selected for systems which can be used as a base for glucose sensors with the mean holographic response in the region of physiological glucose concentration in model solutions achieving 40 nm/(mmol L-1). It is shown that the developed holographic sensors can be used for the visual and instrumental determination of the medium acidity, alcohol content, ionic strength, bivalent metal salts and the quality of water, in particular, for drinking.

#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.

Wafer-scale plasmonic and photonic crystal sensors

NASA Astrophysics Data System (ADS)

George, M. C.; Liu, J.-N.; Farhang, A.; Williamson, B.; Black, M.; Wangensteen, T.; Fraser, J.; Petrova, R.; Cunningham, B. T.

2015-08-01

200 mm diameter wafer-scale fabrication, metrology, and optical modeling results are reviewed for surface plasmon resonance (SPR) sensors based on 2-D metallic nano-dome and nano-hole arrays (NHA's) as well as 1-D photonic crystal sensors based on a leaky-waveguide mode resonance effect, with potential applications in label free sensing, surface enhanced Raman spectroscopy (SERS), and surface-enhanced fluorescence spectroscopy (SEFS). Potential markets include micro-arrays for medical diagnostics, forensic testing, environmental monitoring, and food safety. 1-D and 2-D nanostructures were fabricated on glass, fused silica, and silicon wafers using optical lithography and semiconductor processing techniques. Wafer-scale optical metrology results are compared to FDTD modeling and presented along with application-based performance results, including label-free plasmonic and photonic crystal sensing of both surface binding kinetics and bulk refractive index changes. In addition, SEFS and SERS results are presented for 1-D photonic crystal and 2-D metallic nano-array structures. Normal incidence transmittance results for a 550 nm pitch NHA showed good bulk refractive index sensitivity, however an intensity-based design with 665 nm pitch was chosen for use as a compact, label-free sensor at both 650 and 632.8 nm wavelengths. The optimized NHA sensor gives an SPR shift of about 480 nm per refractive index unit when detecting a series of 0-40% glucose solutions, but according to modeling shows about 10 times greater surface sensitivity when operating at 532 nm. Narrow-band photonic crystal resonance sensors showed quality factors over 200, with reasonable wafer-uniformity in terms of both resonance position and peak height.

Inland-coastal water interaction: Remote sensing application for shallow-water quality and algal blooms modeling

NASA Astrophysics Data System (ADS)

Melesse, Assefa; Hajigholizadeh, Mohammad; Blakey, Tara

2017-04-01

In this study, Landsat 8 and Sea-Viewing Wide Field-of-View Sensor (SeaWIFS) sensors were used to model the spatiotemporal changes of four water quality parameters: Landsat 8 (turbidity, chlorophyll-a (chl-a), total phosphate, and total nitrogen) and Sea-Viewing Wide Field-of-View Sensor (SeaWIFS) (algal blooms). The study was conducted in Florda bay, south Florida and model outputs were compared with in-situ observed data. The Landsat 8 based study found that, the predictive models to estimate chl-a and turbidity concentrations, developed through the use of stepwise multiple linear regression (MLR), gave high coefficients of determination in dry season (wet season) (R2 = 0.86(0.66) for chl-a and R2 = 0.84(0.63) for turbidity). Total phosphate and TN were estimated using best-fit multiple linear regression models as a function of Landsat TM and OLI,127 and ground data and showed a high coefficient of determination in dry season (wet season) (R2 = 0.74(0.69) for total phosphate and R2 = 0.82(0.82) for TN). Similarly, the ability of SeaWIFS for chl-a retrieval from optically shallow coastal waters by applying algorithms specific to the pixels' benthic class was evaluated. Benthic class was determined through satellite image-based classification methods. It was found that benthic class based chl-a modeling algorithm was better than the existing regionally-tuned approach. Evaluation of the residuals indicated the potential for further improvement to chl-a estimation through finer characterization of benthic environments. Key words: Landsat, SeaWIFS, water quality, Florida bay, Chl-a, turbidity

Convolution- and Fourier-transform-based reconstructors for pyramid wavefront sensor.

PubMed

Shatokhina, Iuliia; Ramlau, Ronny

2017-08-01

In this paper, we present two novel algorithms for wavefront reconstruction from pyramid-type wavefront sensor data. An overview of the current state-of-the-art in the application of pyramid-type wavefront sensors shows that the novel algorithms can be applied in various scientific fields such as astronomy, ophthalmology, and microscopy. Assuming a computationally very challenging setting corresponding to the extreme adaptive optics (XAO) on the European Extremely Large Telescope, we present the results of the performed end-to-end simulations and compare the achieved AO correction quality (in terms of the long-exposure Strehl ratio) to other methods, such as matrix-vector multiplication and preprocessed cumulative reconstructor with domain decomposition. Also, we provide a comparison in terms of applicability and computational complexity and closed-loop performance of our novel algorithms to other methods existing for this type of sensor.

Phase aided 3D imaging and modeling: dedicated systems and case studies

NASA Astrophysics Data System (ADS)

Yin, Yongkai; He, Dong; Liu, Zeyi; Liu, Xiaoli; Peng, Xiang

2014-05-01

Dedicated prototype systems for 3D imaging and modeling (3DIM) are presented. The 3D imaging systems are based on the principle of phase-aided active stereo, which have been developed in our laboratory over the past few years. The reported 3D imaging prototypes range from single 3D sensor to a kind of optical measurement network composed of multiple node 3D-sensors. To enable these 3D imaging systems, we briefly discuss the corresponding calibration techniques for both single sensor and multi-sensor optical measurement network, allowing good performance of the 3DIM prototype systems in terms of measurement accuracy and repeatability. Furthermore, two case studies including the generation of high quality color model of movable cultural heritage and photo booth from body scanning are presented to demonstrate our approach.

Greenhouse intelligent control system based on microcontroller

NASA Astrophysics Data System (ADS)

Zhang, Congwei

2018-04-01

As one of the hallmarks of agricultural modernization, intelligent greenhouse has the advantages of high yield, excellent quality, no pollution and continuous planting. Taking AT89S52 microcontroller as the main controller, the greenhouse intelligent control system uses soil moisture sensor, temperature and humidity sensors, light intensity sensor and CO2 concentration sensor to collect measurements and display them on the 12864 LCD screen real-time. Meantime, climate parameter values can be manually set online. The collected measured values are compared with the set standard values, and then the lighting, ventilation fans, warming lamps, water pumps and other facilities automatically start to adjust the climate such as light intensity, CO2 concentration, temperature, air humidity and soil moisture of the greenhouse parameter. So, the state of the environment in the greenhouse Stabilizes and the crop grows in a suitable environment.

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.

SMS-Based Medical Diagnostic Telemetry Data Transmission Protocol for Medical Sensors

PubMed Central

Townsend, Ben; Abawajy, Jemal; Kim, Tai-Hoon

2011-01-01

People with special medical monitoring needs can, these days, be sent home and remotely monitored through the use of data logging medical sensors and a transmission base-station. While this can improve quality of life by allowing the patient to spend most of their time at home, most current technologies rely on hardwired landline technology or expensive mobile data transmissions to transmit data to a medical facility. The aim of this paper is to investigate and develop an approach to increase the freedom of a monitored patient and decrease costs by utilising mobile technologies and SMS messaging to transmit data from patient to medico. To this end, we evaluated the capabilities of SMS and propose a generic communications protocol which can work within the constraints of the SMS format, but provide the necessary redundancy and robustness to be used for the transmission of non-critical medical telemetry from data logging medical sensors. PMID:22163845

Health Monitoring System Technology Assessments: Cost Benefits Analysis

NASA Technical Reports Server (NTRS)

Kent, Renee M.; Murphy, Dennis A.

2000-01-01

The subject of sensor-based structural health monitoring is very diverse and encompasses a wide range of activities including initiatives and innovations involving the development of advanced sensor, signal processing, data analysis, and actuation and control technologies. In addition, it embraces the consideration of the availability of low-cost, high-quality contributing technologies, computational utilities, and hardware and software resources that enable the operational realization of robust health monitoring technologies. This report presents a detailed analysis of the cost benefit and other logistics and operational considerations associated with the implementation and utilization of sensor-based technologies for use in aerospace structure health monitoring. The scope of this volume is to assess the economic impact, from an end-user perspective, implementation health monitoring technologies on three structures. It specifically focuses on evaluating the impact on maintaining and supporting these structures with and without health monitoring capability.

All-Fiber Laser Curvature Sensor Using an In-Fiber Modal Interferometer Based on a Double Clad Fiber and a Multimode Fiber Structure

PubMed Central

Durán-Sánchez, Manuel; Prieto-Cortés, Patricia; Salceda-Delgado, Guillermo; Castillo-Guzmán, Arturo A.; Selvas-Aguilar, Romeo; Ibarra-Escamilla, Baldemar; Kuzin, Evgeny A.

2017-01-01

An all-fiber curvature laser sensor by using a novel modal interference in-fiber structure is proposed and experimentally demonstrated. The in-fiber device, fabricated by fusion splicing of multimode fiber and double-clad fiber segments, is used as wavelength filter as well as the sensing element. By including a multimode fiber in an ordinary modal interference structure based on a double-clad fiber, the fringe visibility of the filter transmission spectrum is significantly increased. By using the modal interferometer as a curvature sensitive wavelength filter within a ring cavity erbium-doped fiber laser, the spectral quality factor Q is considerably increased. The results demonstrate the reliability of the proposed curvature laser sensor with advantages of robustness, ease of fabrication, low cost, repeatability on the fabrication process and simple operation. PMID:29182527

All-Fiber Laser Curvature Sensor Using an In-Fiber Modal Interferometer Based on a Double Clad Fiber and a Multimode Fiber Structure.

PubMed

Álvarez-Tamayo, Ricardo I; Durán-Sánchez, Manuel; Prieto-Cortés, Patricia; Salceda-Delgado, Guillermo; Castillo-Guzmán, Arturo A; Selvas-Aguilar, Romeo; Ibarra-Escamilla, Baldemar; Kuzin, Evgeny A

2017-11-28

An all-fiber curvature laser sensor by using a novel modal interference in-fiber structure is proposed and experimentally demonstrated. The in-fiber device, fabricated by fusion splicing of multimode fiber and double-clad fiber segments, is used as wavelength filter as well as the sensing element. By including a multimode fiber in an ordinary modal interference structure based on a double-clad fiber, the fringe visibility of the filter transmission spectrum is significantly increased. By using the modal interferometer as a curvature sensitive wavelength filter within a ring cavity erbium-doped fiber laser, the spectral quality factor Q is considerably increased. The results demonstrate the reliability of the proposed curvature laser sensor with advantages of robustness, ease of fabrication, low cost, repeatability on the fabrication process and simple operation.

Design of a correlated validated CFD and genetic algorithm model for optimized sensors placement for indoor air quality monitoring

NASA Astrophysics Data System (ADS)

Mousavi, Monireh Sadat; Ashrafi, Khosro; Motlagh, Majid Shafie Pour; Niksokhan, Mohhamad Hosein; Vosoughifar, HamidReza

2018-02-01

In this study, coupled method for simulation of flow pattern based on computational methods for fluid dynamics with optimization technique using genetic algorithms is presented to determine the optimal location and number of sensors in an enclosed residential complex parking in Tehran. The main objective of this research is costs reduction and maximum coverage with regard to distribution of existing concentrations in different scenarios. In this study, considering all the different scenarios for simulation of pollution distribution using CFD simulations has been challenging due to extent of parking and number of cars available. To solve this problem, some scenarios have been selected based on random method. Then, maximum concentrations of scenarios are chosen for performing optimization. CFD simulation outputs are inserted as input in the optimization model using genetic algorithm. The obtained results stated optimal number and location of sensors.

Water Quality Monitoring for Lake Constance with a Physically Based Algorithm for MERIS Data.

PubMed

Odermatt, Daniel; Heege, Thomas; Nieke, Jens; Kneubühler, Mathias; Itten, Klaus

2008-08-05

A physically based algorithm is used for automatic processing of MERIS level 1B full resolution data. The algorithm is originally used with input variables for optimization with different sensors (i.e. channel recalibration and weighting), aquatic regions (i.e. specific inherent optical properties) or atmospheric conditions (i.e. aerosol models). For operational use, however, a lake-specific parameterization is required, representing an approximation of the spatio-temporal variation in atmospheric and hydrooptic conditions, and accounting for sensor properties. The algorithm performs atmospheric correction with a LUT for at-sensor radiance, and a downhill simplex inversion of chl-a, sm and y from subsurface irradiance reflectance. These outputs are enhanced by a selective filter, which makes use of the retrieval residuals. Regular chl-a sampling measurements by the Lake's protection authority coinciding with MERIS acquisitions were used for parameterization, training and validation.

Towards the Development of a Smart Flying Sensor: Illustration in the Field of Precision Agriculture.

PubMed

Hernandez, Andres; Murcia, Harold; Copot, Cosmin; De Keyser, Robin

2015-07-10

Sensing is an important element to quantify productivity, product quality and to make decisions. Applications, such as mapping, surveillance, exploration and precision agriculture, require a reliable platform for remote sensing. This paper presents the first steps towards the development of a smart flying sensor based on an unmanned aerial vehicle (UAV). The concept of smart remote sensing is illustrated and its performance tested for the task of mapping the volume of grain inside a trailer during forage harvesting. Novelty lies in: (1) the development of a position-estimation method with time delay compensation based on inertial measurement unit (IMU) sensors and image processing; (2) a method to build a 3D map using information obtained from a regular camera; and (3) the design and implementation of a path-following control algorithm using model predictive control (MPC). Experimental results on a lab-scale system validate the effectiveness of the proposed methodology.

Towards the Development of a Smart Flying Sensor: Illustration in the Field of Precision Agriculture

PubMed Central

Hernandez, Andres; Murcia, Harold; Copot, Cosmin; De Keyser, Robin

2015-01-01

Sensing is an important element to quantify productivity, product quality and to make decisions. Applications, such as mapping, surveillance, exploration and precision agriculture, require a reliable platform for remote sensing. This paper presents the first steps towards the development of a smart flying sensor based on an unmanned aerial vehicle (UAV). The concept of smart remote sensing is illustrated and its performance tested for the task of mapping the volume of grain inside a trailer during forage harvesting. Novelty lies in: (1) the development of a position-estimation method with time delay compensation based on inertial measurement unit (IMU) sensors and image processing; (2) a method to build a 3D map using information obtained from a regular camera; and (3) the design and implementation of a path-following control algorithm using model predictive control (MPC). Experimental results on a lab-scale system validate the effectiveness of the proposed methodology. PMID:26184205

Water quality monitor. [spacecraft potable water

NASA Technical Reports Server (NTRS)

West, S.; Crisos, J.; Baxter, W.

1979-01-01

The preprototype water quality monitor (WQM) subsystem was designed based on a breadboard monitor for pH, specific conductance, and total organic carbon (TOC). The breadboard equipment demonstrated the feasibility of continuous on-line analysis of potable water for a spacecraft. The WQM subsystem incorporated these breadboard features and, in addition, measures ammonia and includes a failure detection system. The sample, reagent, and standard solutions are delivered to the WQM sensing manifold where chemical operations and measurements are performed using flow through sensors for conductance, pH, TOC, and NH3. Fault monitoring flow detection is also accomplished in this manifold assembly. The WQM is designed to operate automatically using a hardwired electronic controller. In addition, automatic shutdown is incorporated which is keyed to four flow sensors strategically located within the fluid system.

A systematic review of gait analysis methods based on inertial sensors and adaptive algorithms.

PubMed

Caldas, Rafael; Mundt, Marion; Potthast, Wolfgang; Buarque de Lima Neto, Fernando; Markert, Bernd

2017-09-01

The conventional methods to assess human gait are either expensive or complex to be applied regularly in clinical practice. To reduce the cost and simplify the evaluation, inertial sensors and adaptive algorithms have been utilized, respectively. This paper aims to summarize studies that applied adaptive also called artificial intelligence (AI) algorithms to gait analysis based on inertial sensor data, verifying if they can support the clinical evaluation. Articles were identified through searches of the main databases, which were encompassed from 1968 to October 2016. We have identified 22 studies that met the inclusion criteria. The included papers were analyzed due to their data acquisition and processing methods with specific questionnaires. Concerning the data acquisition, the mean score is 6.1±1.62, what implies that 13 of 22 papers failed to report relevant outcomes. The quality assessment of AI algorithms presents an above-average rating (8.2±1.84). Therefore, AI algorithms seem to be able to support gait analysis based on inertial sensor data. Further research, however, is necessary to enhance and standardize the application in patients, since most of the studies used distinct methods to evaluate healthy subjects. Copyright © 2017 Elsevier B.V. All rights reserved.

Image quality assessment using deep convolutional networks

NASA Astrophysics Data System (ADS)

Li, Yezhou; Ye, Xiang; Li, Yong

2017-12-01

This paper proposes a method of accurately assessing image quality without a reference image by using a deep convolutional neural network. Existing training based methods usually utilize a compact set of linear filters for learning features of images captured by different sensors to assess their quality. These methods may not be able to learn the semantic features that are intimately related with the features used in human subject assessment. Observing this drawback, this work proposes training a deep convolutional neural network (CNN) with labelled images for image quality assessment. The ReLU in the CNN allows non-linear transformations for extracting high-level image features, providing a more reliable assessment of image quality than linear filters. To enable the neural network to take images of any arbitrary size as input, the spatial pyramid pooling (SPP) is introduced connecting the top convolutional layer and the fully-connected layer. In addition, the SPP makes the CNN robust to object deformations to a certain extent. The proposed method taking an image as input carries out an end-to-end learning process, and outputs the quality of the image. It is tested on public datasets. Experimental results show that it outperforms existing methods by a large margin and can accurately assess the image quality on images taken by different sensors of varying sizes.

Future electro-optical sensors and processing in urban operations

NASA Astrophysics Data System (ADS)

Grönwall, Christina; Schwering, Piet B.; Rantakokko, Jouni; Benoist, Koen W.; Kemp, Rob A. W.; Steinvall, Ove; Letalick, Dietmar; Björkert, Stefan

2013-10-01

In the electro-optical sensors and processing in urban operations (ESUO) study we pave the way for the European Defence Agency (EDA) group of Electro-Optics experts (IAP03) for a common understanding of the optimal distribution of processing functions between the different platforms. Combinations of local, distributed and centralized processing are proposed. In this way one can match processing functionality to the required power, and available communication systems data rates, to obtain the desired reaction times. In the study, three priority scenarios were defined. For these scenarios, present-day and future sensors and signal processing technologies were studied. The priority scenarios were camp protection, patrol and house search. A method for analyzing information quality in single and multi-sensor systems has been applied. A method for estimating reaction times for transmission of data through the chain of command has been proposed and used. These methods are documented and can be used to modify scenarios, or be applied to other scenarios. Present day data processing is organized mainly locally. Very limited exchange of information with other platforms is present; this is performed mainly at a high information level. Main issues that arose from the analysis of present-day systems and methodology are the slow reaction time due to the limited field of view of present-day sensors and the lack of robust automated processing. Efficient handover schemes between wide and narrow field of view sensors may however reduce the delay times. The main effort in the study was in forecasting the signal processing of EO-sensors in the next ten to twenty years. Distributed processing is proposed between hand-held and vehicle based sensors. This can be accompanied by cloud processing on board several vehicles. Additionally, to perform sensor fusion on sensor data originating from different platforms, and making full use of UAV imagery, a combination of distributed and centralized processing is essential. There is a central role for sensor fusion of heterogeneous sensors in future processing. The changes that occur in the urban operations of the future due to the application of these new technologies will be the improved quality of information, with shorter reaction time, and with lower operator load.

Ontological Representation of Light Wave Camera Data to Support Vision-Based AmI

PubMed Central

Serrano, Miguel Ángel; Gómez-Romero, Juan; Patricio, Miguel Ángel; García, Jesús; Molina, José Manuel

2012-01-01

Recent advances in technologies for capturing video data have opened a vast amount of new application areas in visual sensor networks. Among them, the incorporation of light wave cameras on Ambient Intelligence (AmI) environments provides more accurate tracking capabilities for activity recognition. Although the performance of tracking algorithms has quickly improved, symbolic models used to represent the resulting knowledge have not yet been adapted to smart environments. This lack of representation does not allow to take advantage of the semantic quality of the information provided by new sensors. This paper advocates for the introduction of a part-based representational level in cognitive-based systems in order to accurately represent the novel sensors' knowledge. The paper also reviews the theoretical and practical issues in part-whole relationships proposing a specific taxonomy for computer vision approaches. General part-based patterns for human body and transitive part-based representation and inference are incorporated to an ontology-based previous framework to enhance scene interpretation in the area of video-based AmI. The advantages and new features of the model are demonstrated in a Social Signal Processing (SSP) application for the elaboration of live market researches.

40 CFR 1033.112 - Emission diagnostics for SCR systems.

Code of Federal Regulations, 2012 CFR

2012-07-01

... diagnostic system must monitor reductant quality and tank levels and alert operators to the need to refill... specified in § 1033.110 and an audible alarm. You do not need to separately monitor reductant quality if you include an exhaust NOX sensor (or other sensor) that allows you to determine inadequate reductant quality...

40 CFR 1033.112 - Emission diagnostics for SCR systems.

Code of Federal Regulations, 2014 CFR

2014-07-01

... diagnostic system must monitor reductant quality and tank levels and alert operators to the need to refill... specified in § 1033.110 and an audible alarm. You do not need to separately monitor reductant quality if you include an exhaust NOX sensor (or other sensor) that allows you to determine inadequate reductant quality...