Passive Wireless Sensing of Temperature Using RF Technology

2007 ◽  
Author(s):  
Miaogeng Zhang ◽  
Luis Gonzalez-Argueta ◽  
V. Sundararajan
Keyword(s):  
Low Cost ◽  
Voltage Divider ◽  
Sensor Nodes ◽  
Measured Signal ◽  
Wireless Sensing ◽  
Function Generator ◽  
Variable Resistor ◽  
Power Characteristics ◽  
Rf Design ◽  
Loop Antennas

Sensor networks are emerging as an attractive technology for deployment in monitoring applications due to their flexibility, small size, ease of installation, low cost and low power characteristics. Since the wireless nodes use batteries as energy sources, their operating lives are limited by the life of the batteries. Replacing batteries periodically in a sensor network can be a burden as the nodes may be dispersed over a wide area. Moreover the battery increases the size of the sensor nodes and offsets one of the primary advantages of such networks. This study proposes a design for wireless sensing of temperature based on passive RF-technology. The experimental setup includes: 1) signal generator 2) sensor tag 3) receiver. The carrier signal is produced by function generator. The sensor tag consists of a voltage divider circuit combined with loop antennas. The sensor tag filters the carrier signal and transmits back a modulated signal of the same frequency. The variable resistor acting as a thermistor is connected as a voltage divider. The change in amplitude of the output signal is relative to the temperature change. Experimental results show that the passive RF design can be effective way for wireless temperature monitoring. The results can be generalized to any sensor that converts the measured signal into a change of resistance.

A Simplified Indirect Technique for the Measurement of Mechanical Power in Three-Phase Asynchronous Motors

2019 ◽  
Vol 20 (2) ◽  
Author(s):  
Giovanni Bucci ◽  
Fabrizio Ciancetta ◽  
Edoardo Fiorucci ◽  
Antonio Ometto ◽  
Maria Anna Segreto
Keyword(s):  
Induction Motors ◽  
Low Cost ◽  
Electrical Power ◽  
Voltage Divider ◽  
Mechanical Power ◽  
Phase Current ◽  
Power Characteristics ◽  
Asynchronous Motors ◽  
Three Phase ◽  
Indirect Technique

Abstract This paper presents an indirect method for measuring the mechanical power produced by three-phase induction motors. The proposed technique is based on the hypothesis that three-phase induction motors are balanced systems that transform electrical power into mechanical one. The measurement of a single phase current is used to estimate the mechanical power generated at the axis. The relationship between electric current and mechanical power is generally non-linear. By expressing the quantities in p.u., this trend is approximated with a second order polynomial. From the analysis of the mechanical power characteristics related to 13 motors we obtained the parameters of the interpolating parabolic curves of motors from 1.1 kW to 75 kW rated power. The proposed technique can be easily adopted in order to monitor the mechanical power of three phase induction motors using only one phase current transducer. Starting from the motor nameplate no experimental measurement or other data are necessary to estimate the mechanical power. This technique can be widely used in low cost multipoint measurement system able to monitor the mechanical power where no other transducer or voltage divider are necessary.

scholarly journals Robust Silent Localization of Underwater Acoustic Sensor Network Using Mobile Anchor(s)

Sensors ◽  
2021 ◽  
Vol 21 (3) ◽  
pp. 727
Author(s):  
Rahul Mourya ◽  
Mauro Dragone ◽  
Yvan Petillot
Keyword(s):  
Channel Model ◽  
Low Cost ◽  
Sensor Nodes ◽  
Noise Model ◽  
Robust Estimator ◽  
Acoustic Sensor ◽  
Underwater Acoustic ◽  
Acoustic Channel ◽  
Localization Scheme ◽  
Mobile Anchor

Underwater acoustic sensor networks (UWASNs) can revolutionize the subsea domain by enabling low-cost monitoring of subsea assets and the marine environment. Accurate localization of the UWASNs is essential for these applications. In general, range-based localization techniques are preferred for their high accuracy in estimated locations. However, they can be severely affected by variable sound speed, multipath spreading, and other effects of the acoustic channel. In addition, an inefficient localization scheme can consume a significant amount of energy, reducing the effective life of the battery-powered sensor nodes. In this paper, we propose robust, efficient, and practically implementable localization schemes for static UWASNs. The proposed schemes are based on the Time-Difference-of-Arrival (TDoA) measurements and the nodes are localized passively, i.e., by just listening to beacon signals from multiple anchors, thus saving both the channel bandwidth and energy. The robustness in location estimates is achieved by considering an appropriate statistical noise model based on a plausible acoustic channel model and certain practical assumptions. To overcome the practical challenges of deploying and maintaining multiple permanent anchors for TDoA measurements, we propose practical schemes of using a single or multiple surface vehicles as virtual anchors. The robustness of localization is evaluated by simulations under realistic settings. By combining a mobile anchor(s) scheme with a robust estimator, this paper presents a complete package of efficient, robust, and practically usable localization schemes for low-cost UWASNs.

Detecting Wormhole Attack on Data Aggregation in Hierarchical WSN

2017 ◽  
Vol 11 (1) ◽  
pp. 35-51 ◽  
Author(s):  
Mukesh Kumar ◽  
Kamlesh Dutta
Keyword(s):  
Energy Efficiency ◽  
Data Aggregation ◽  
Low Cost ◽  
Attack Detection ◽  
Sensor Nodes ◽  
Network Data ◽  
Light Weight ◽  
Malicious Node ◽  
Combine Data ◽  
Wormhole Attack

Wireless networks are used by everyone for their convenience for transferring packets from one node to another without having a static infrastructure. In WSN, there are some nodes which are light weight, small in size, having low computation overhead, and low cost known as sensor nodes. In literature, there exists many secure data aggregation protocols available but they are not sufficient to detect the malicious node. The authors require a better security mechanism or a technique to secure the network. Data aggregation is an essential paradigm in WSN. The idea is to combine data coming from different source nodes in order to achieve energy efficiency. In this paper, the authors proposed a protocol for worm hole attack detection during data aggregation in WSN. Main focus is on wormhole attack detection and its countermeasures.

scholarly journals Fatigue Load Spectrum of Highway Bridge Vehicles in Plateau Mountainous Area Based on Wireless Sensing

2021 ◽  
Vol 2021 ◽  
pp. 1-8
Author(s):  
Li Rui ◽  
Xie Xiaoyu ◽  
Duan Xueyan
Keyword(s):  
Low Cost ◽  
Mineral Resources ◽  
Highway Bridges ◽  
Equivalent Model ◽  
Distribution Model ◽  
Mountainous Area ◽  
Wireless Sensing ◽  
Mountainous Areas ◽  
Load Spectrum ◽  
Fatigue Load

In Yunnan and other plateau mountainous areas, hydropower and mineral resources are abundant, and there are relatively many vehicles used for the transportation of large hydropower facilities. The widespread phenomenon of vehicle overload causes severe fatigue among the drivers. However, there is no reference vehicle load spectrum for fatigue analysis in the existing research. The application of wireless sensing technology to bridge health monitoring is favorable for the entire monitoring system’s low-cost and intelligent development. In this study, wireless sensors are used to collect sensing data in the measured area and perform preliminary filtering processing. The data collected by the sensing layer is aggregated at the TD gateway layer to realize local short-term storage of monitoring data, and 3G wireless transmission is used for the effective processing of the data. The clustering method is used to classify the vehicle models based on investigating the most representative expressway traffic flow information in Yunnan Province. Moreover, the weighted probability distribution model of different vehicle models is established through statistical analysis, which simplifies the composition’s fatigue intensity spectrum model. The selection of five vehicles of the equivalent model followed by a six-axle vehicle has the most significant impact on bridge damage as the standard fatigue vehicle. The research results establish a basis for the fatigue design of highway bridges in plateau and mountainous areas and provide data to establish vehicle fatigue load spectra in national highway regions.

scholarly journals DOS Attacks on TCP/IP Layers in WSN

2013 ◽  
Vol 1 (2013) ◽  
pp. 40-45
Keyword(s):  
Wireless Sensor Network ◽  
Sensor Networks ◽  
Sensor Network ◽  
Low Cost ◽  
Denial Of Service ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Renewable Energy Resources ◽  
Dos Attack ◽  
Dos Attacks

The emergence of sensor networks as one of the dominant technology trends in the coming decades has posed numerous unique challenges on their security to researchers. These networks are likely to be composed of thousands of tiny sensor nodes, which are low-cost devices equipped with limited memory, processing, radio, and in many cases, without access to renewable energy resources. While the set of challenges in sensor networks are diverse, we focus on security of Wireless Sensor Network in this paper. First, we propose some of the security goal for Wireless Sensor Network. To perform any task in WSN, the goal is to ensure the best possible utilization of sensor resources so that the network could be kept functional as long as possible. In contrast to this crucial objective of sensor network management, a Denial of Service (DoS) attack targets to degrade the efficient use of network resources and disrupts the essential services in the network. DoS attack could be considered as one of th

Stand-alone low-cost sensor network in the inner city of Munich for modeling urban air pollutants

2021 ◽  
Author(s):  
Adrian Wenzel ◽  
Jia Chen ◽  
Florian Dietrich ◽  
Sebastian T. Thekkekara ◽  
Daniel Zollitsch ◽  
...  
Keyword(s):  
Air Quality ◽  
High Resolution ◽  
Sensor Network ◽  
Air Pollutants ◽  
Low Cost ◽  
Air Pollutant ◽  
Sensor Nodes ◽  
Sensor Data ◽  
Small Scale ◽  
Urban Air

<p>Modeling urban air pollutants is a challenging task not only due to the complicated, small-scale topography but also due to the complex chemical processes within the chemical regime of a city. Nitrogen oxides (NOx), particulate matter (PM) and other tracer gases, e.g. formaldehyde, hold information about which chemical regime is present in a city. As we are going to test and apply chemical models for urban pollution – especially with respect to spatial and temporally variability – measurement data with high spatial and temporal resolution are critical.</p><p>Since governmental monitoring stations of air pollutants such as PM, NOx, ozone (O<sub>3</sub>) or carbon monoxide (CO) are large and costly, they are usually only sparsely distributed throughout a city. Hence, the official monitoring sites are not sufficient to investigate whether small-scale variability and its integrated effects are captured well by models. Smart networks consisting of small low-cost air pollutant sensors have the ability to provide the required grid density and are therefore the tool of choice when it comes to setting up or validating urban modeling frameworks. Such sensor networks have been established and run by several groups, achieving spatial and temporal high-resolution concentration maps [1, 2].</p><p>After having conducted a measurement campaign in 2016 to create a high-resolution NO<sub>2</sub> concentration map for Munich [3], we are currently setting up a low-cost sensor network to measure NOx, PM, O<sub>3</sub> and CO concentrations as well as meteorological parameters [4]. The sensors are stand-alone, so that they do not demand mains supply, which gives us a high flexibility in their deployment. Validating air quality models not only requires dense but also high-accuracy measurements. Therefore, we will calibrate our sensor nodes on a weekly basis using a mobile reference instrument and apply the gathered sensor data to a Machine Learning model of the sensor nodes. This will help minimize the often occurring drawbacks of low-cost sensors such as sensor drift, environmental influences and sensor cross sensitivities.</p><p> </p><p>[1] Bigi, A., Mueller, M., Grange, S. K., Ghermandi, G., and Hueglin, C.: Performance of NO, NO2 low cost sensors and three calibration approaches within a real world application, Atmos. Meas. Tech., 11, 3717–3735, https://doi.org/10.5194/amt-11-3717-2018, 2018</p><p>[2] Kim, J., Shusterman, A. A., Lieschke, K. J., Newman, C., and Cohen, R. C.: The BErkeley Atmospheric CO2 Observation Network: field calibration and evaluation of low-cost air quality sensors, Atmos. Meas. Tech., 11, 1937–1946, https://doi.org/10.5194/amt-11-1937-2018, 2018</p><p>[3] Zhu, Y., Chen, J., Bi, X., Kuhlmann, G., Chan, K. L., Dietrich, F., Brunner, D., Ye, S., and Wenig, M.: Spatial and temporal representativeness of point measurements for nitrogen dioxide pollution levels in cities, Atmos. Chem. Phys., 20, 13241–13251, https://doi.org/10.5194/acp-20-13241-2020, 2020</p><p>[4] Zollitsch, D., Chen, J., Dietrich, F., Voggenreiter, B., Setili, L., and Wenig, M.: Low-Cost Air Quality Sensor Network in Munich, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-19276, https://doi.org/10.5194/egusphere-egu2020-19276, 2020</p>

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