Optimal Deployment of a Heterogeneous Air Quality Sensor Network

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.

Optimal Wireless Distributed Sensor Network Design and Ad-Hoc Deployment in a Chemical Emergency Situation

“…The cost function can be modified for each specific problem. For example, if sensors are chosen from a specific inventory with known prices and attributes, the cost function can be reformulated accordingly [ 16 ].…”

“…The optimization problem above is NP-hard (by reduction to the knapsack problem [ 16 ]). To solve this type of problem, a heuristic approach is required.…”

“…This type of operation requires considering numerous parameters related to sensor properties, maintenance, placement, and resources. Previous studies solved the location-allocation problem by assuming sensors with known and fixed attributes, for example, [ 12 ] and [ 16 ]. Some theoretical studies assumed the sensors’ attributes exceed the application requirements (ideal sensor), for example [ 17 ].…”

Experimental and modeling studies of the effects of nanoclay on the oil behaviors in a water–sand system

“…The main source of release of toxic gases into the atmosphere is industrial activities (Asif and Chen, 2020;Lerner et al, 2019). The reduction of gaseous pollutants, particularly volatile organic compounds, using thermal oxidation is expensive due to the need of high amount of energy.…”

Lattice‐Based 3‐Dimensional Wireless Sensor Deployment

“…Most terrestrial WSNs adopt two-dimensional (2D) sensor deployment models, and little attention has been paid to threedimensional (3D) sensor deployment models. In recent years, there has been an increase in the WSN application in 3D real-world scenarios due to the development of related technologies and the urgent demands of various industries, such as military monitoring, industrial area monitoring, air pollution monitoring, alpine and underwater monitoring, and emergency response and disaster relief [2][3][4][5][6].…”