On the Optimization of WSN Deployment for Sensing Physical Phenomena: Applications to Urban Air Pollution Monitoring

Abstract

Wireless sensor networks (WSN) are widely used in environmental applications where the aim is to sense a physical phenomenon. Air pollution is one of the main physical phenomena that still need to be studied and characterized. Using WSN for air pollution monitoring usually targets two main applications: regular mapping and the detection of high pollution concentrations. Both of these applications need a careful deployment of sensors in order to get better knowledge of air pollution while ensuring a minimal deployment cost. In this chapter, we present three formulations of the deployment issue of sensor and sink nodes based on integer linear programming modeling (ILP) while tackling the two main applications of air pollution monitoring. In the first ILP model, we target the regular mapping of air pollution based on predicted pollution maps. In the second and third ILP model, we target the detection of pollution threshold crossings. The second model is based on predicted pollution maps as in the first one, whereas the third one is based on pollution emission inventory which describes pollution sources and their emission rates. In addition to the constraints of pollution coverage, we also ensure that the deployed networks are connected and their financial deployment cost is minimized. We perform extensive simulations in order to analyze the performance of the proposed models in terms of coverage and connectivity results.