Optimisation in the Design of Environmental Sensor Networks with Robustness Consideration

Sensors

Setia Budi¹  Paulo de Souza²  Greg Timms²  Vishv Malhotra¹  Paul Turner¹ 

[1] School of Engineering and ICT, University of Tasmania, Private Bag 87, Hobart, TAS 7001, Australia;Commonwealth Scientific and Industrial Research Organisation, 15 College Road, Sandy Bay, TAS 7005, Australia;

关键词: environmental sensor networks;    sensor networks design;    sensor networks deployment;    optimisation;    evolutionary algorithm;    spatial regression test;    gap filling;    noise detection;    data quality;   

DOI  :  10.3390/s151229765

来源: mdpi

【 摘 要 】

This work proposes the design of Environmental Sensor Networks (ESN) through balancing robustness and redundancy. An Evolutionary Algorithm (EA) is employed to find the optimal placement of sensor nodes in the Region of Interest (RoI). Data quality issues are introduced to simulate their impact on the performance of the ESN. Spatial Regression Test (SRT) is also utilised to promote robustness in data quality of the designed ESN. The proposed method provides high network representativeness (fit for purpose) with minimum sensor redundancy (cost), and ensures robustness by enabling the network to continue to achieve its objectives when some sensors fail.

【 授权许可】

CC BY   
© 2015 by the authors; licensee MDPI, Basel, Switzerland.