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Activity-Aware Energy-Efficient Automation of Smart Buildings

School of Electrical Engineering and Computer Science, Washington State University, Pullman, WA 99163, USA
Author to whom correspondence should be addressed.
Academic Editor: Hossam A. Gabbar (Gaber)
Energies 2016, 9(8), 624;
Received: 3 June 2016 / Accepted: 4 June 2016 / Published: 9 August 2016
(This article belongs to the Special Issue Energy Conservation in Infrastructures 2016)
This paper introduces the idea of activity-aware cyber-physical systems (CPS). Activity-aware systems allow smart city services to adapt to the needs of individual residents by being sensitive to their daily tasks. The paper first defines activity recognition and activity prediction algorithms that form the foundation of activity-aware CPS and implement a prototype activity-aware building automation system, called CASAS activity aware resource learning (CARL). Evaluation of CARL on real sensor data shows not only an accurate ability to sense and predict activities but an effective means of automation buildings that reduces energy consumption while being sensitive to user activities in the building. Our ideas are demonstrated in the context of a smart home but can be utilized in a variety of smart city settings including smart offices, smart hospitals, and smart communities. View Full-Text
Keywords: smart cities; cyber-physical systems (CPS); activity recognition; activity prediction; building automation smart cities; cyber-physical systems (CPS); activity recognition; activity prediction; building automation
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MDPI and ACS Style

Thomas, B.L.; Cook, D.J. Activity-Aware Energy-Efficient Automation of Smart Buildings. Energies 2016, 9, 624.

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