From Sensor Network To Social NetworkÐ A Study On The Energy Impact In Buildings

Abstract

Graphical models built on sensor networks have been used extensively in smart home projects to improve occupancy comfort and building energy use. Simulation tools use profiles of occupants to predict future building energy use. Previous research focused on past or present occupancy and mobility. But the social interactions are often ignored. In this study, we model occupancy activities by constructing a social network from information provided by physical sensor networks in an open-plan office building. We propsed a Time Series Maximum Margin Markov Network model (TM3N) to incorporate information from evolving networks, e.g., number of occupants, occupant activities and indoor and outdoor CO2 changes. We then constructed an energy simulation model of the building from inference results. Simulation results show that energy savings reached 20% in the demonstration building while maintaining indoor occupancy thermal comfort.

Citation:
Xiaoqian Jiang, Bing Dong, and Latanya Sweeney. From Sensor Network To Social NetworkÐ A Study On The Energy Impact In Buildings. NIPS Workshop Analyzing Networks and Learning with Graphs, 2009. (PDF).

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