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doi:10.3808/jei.201800399
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Optimal Deployment of a Heterogeneous Air Quality Sensor Network

U. Lerner1, O. Hirshfeld2, and B. Fishbain1,*

  1. Technion Enviromatics Laboratory (TechEL) and the Technion Center of Excellence in Exposure Science and Environmental Health (TCEEH), Department of Environmental, Water and Agricultural Engineering, Faculty of Civil & Environmental Engineering, The Technion - Israel Institute of Technology, Haifa 320003, Israel
  2. Department of Environmental, Water and Agricultural Engineering, Faculty of Civil & Environmental Engineering, The Technion - Israel Institute of Technology, Haifa 320003, Israel

*Corresponding author. Tel.: +97248293177; fax: +97248229989. E-mail address: fishbain@technion.ac.il (B. Fishbain).

Abstract


Accurate assessment of air pollution exposure is crucial to better public health. Routine monitoring is done by standardized Air Quality Monitoring (AQM) stations, which are spread thinly due to size and cost. Recent technological developments have made Wireless Distributed Environmental Sensor Networks (WDESNs) that consist of low-cost Micro Sensing Units (MSUs) feasible. These MSUs can be spread more densely and provide higher spatial resolution data. The availability of MSUs, however, poses the challenge of selecting optimal sensors’ locations. Previous attempts assumed prior knowledge on pollution levels in the region of interest, and considered MSUs which measured only one pollutant. This paper presents a scheme for finding an optimal deployment of heterogeneous WDESN, which is based only on MSUs characteristics and land use analysis. To this end, a set of optional deployment locations (OLs) is defined. Each OL is characterized by a set of utilities of placing the various MSUs in that location. The optimization process seeks for the set of locations, under budget and resources constraints, that maximizes the overall utility. Using the suggested method leads to an intelligent deployment under a set of given premises. This is demonstrated vs. a real-world deployment scenario, with multiple types of MSUs.

Keywords: air pollution; wireless distributed environmental sensor network; optimal deployment; monitoring


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