A Deterministic Sensor Deployment Method for Target Coverage

In order to monitor the gas leakage, the gas sensors are deployed conventionally in chemical industry park, with little considerations given to the gas characteristics and weather conditions, which give rise to the problems of coverage hole and coverage repetition. To solve the problems, this paper...

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Bibliographic Details
Published in:Journal of sensors 2018-01, Vol.2018 (2018), p.1-14
Main Authors: Jiang, Zhaoneng, Zhang, Bangbang, Chen, Bo, Liu, Jian, Xiao, Shuyan, Jiang, Ye, Zhao, Hongzhi
Format: Article
Language:English
Subjects:
Algorithms
Art galleries & museums
Chemical industry
Computer simulation
Diffusion rate
Error detection
Gas sensors
Gaseous diffusion
Influence
International conferences
Linear programming
Localization
Methods
Monitoring
Particle swarm optimization
Sensors
Weather
Wind effects
Wind speed
Wireless networks
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Summary:In order to monitor the gas leakage, the gas sensors are deployed conventionally in chemical industry park, with little considerations given to the gas characteristics and weather conditions, which give rise to the problems of coverage hole and coverage repetition. To solve the problems, this paper proposes a deterministic sensor deployment method with the gas diffusion models which takes into account wind speed and direction and then studies the influence of wind speed and direction on the monitoring error of gas sensors. Then, we research the deterministic deployment method of gas sensors in condition of the main wind speed and direction somewhere. Firstly, we use the CFD theory to simulate the gas diffusion situation so as to obtain the concentration value of the relevant points. Secondly, we put forward a new optimization criterion, namely, the more alarm concentration points covered by gas sensors, the coverage performance is better, and the deployment method is better. Accordingly, a new objection function is built. Thirdly, we obtain the weight values of the function using entropy estimation method. Finally, we deploy the gas sensors determinately using particle swarm optimization (PSO) algorithm. The simulation results show that the proposed method can improve the monitoring efficiency and the coverage performance of gas sensor network.
ISSN:1687-725X
1687-7268
DOI:10.1155/2018/2343891