Design and implementation of a high-fidelity AC metering network
IPSN '09 Proceedings of the 2009 International Conference on Information Processing in Sensor Networks
Experiences with a high-fidelity wireless building energy auditing network
Proceedings of the 7th ACM Conference on Embedded Networked Sensor Systems
@scale: insights from a large, long-lived appliance energy WSN
Proceedings of the 11th international conference on Information Processing in Sensor Networks
Strip, bind, and search: a method for identifying abnormal energy consumption in buildings
Proceedings of the 12th international conference on Information processing in sensor networks
POEM: power-efficient occupancy-based energy management system
Proceedings of the 12th international conference on Information processing in sensor networks
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Demand side management (DSM) has emerged as a promising way to balance the electrical grid's demand and supply in an economical and environmentally friendly manner. For successful DSM, it is crucial to automate the analysis of building energy usage with respect to important factors that drive it, such as occupancy. In this paper, we present a sensor-driven energy use analysis system, EnergyTrack, that continuously analyzes, evaluates, and interprets building energy use in real-time. We develop an energy usage model in EnergyTrack that simultaneously considers device-specific energy consumption, occupancy changes, and occupant utility. We also design a low-cost occupancy estimation algorithm with a lightweight training requirement. The EnergyTrack testbed is implemented in a commercial building office space. Through this testbed, we demonstrate the performance of our occupancy estimation algorithm and the application of EnergyTrack in energy use analysis.