Security-oriented sensor placement in intelligent buildings

Abstract

Intelligent buildings are beginning to utilize sensor networks for monitoring and protecting indoor air quality against contamination events. This paper presents a methodology for determining where to install such sensors. In particular, a multi-objective optimization problem is formulated for minimizing the sensor cost, the average and the worst-case impact damage corresponding to a set of contamination event scenarios. Each contamination scenario is comprised of parameters characterized by some given probability distribution. Based on these distributions, a set of representative contamination scenarios is constructed through grid and random sampling, and the overall impact of each scenario is computed, thus providing a solution to the sensor placement problem. The proposed methodology is illustrated by two case studies, a simple building with five rooms and a realistic building with 14 rooms.