Simone Silvestri
ABSTRACT
A key requirement for success of smart home energy management systems is understanding the user's psychological perception of a smart environments, and the design of control strategies that specifically take into account such dimensions in system operation. We discuss how our research develops psychological models and integrates them with optimization and machine learning techniques to realize social and behavioral aware energy optimization methodologies for smart homes.
- Pietro Cottone, Salvatore Gaglio, Giuseppe Lo Re, and Marco Ortolani. 2015. User activity recognition for energy saving in smart homes. Pervasive and Mobile Computing 16 (2015), 156--170. Google Scholar
Digital Library
- Debraj De, Shaojie Tang, Wen-Zhan Song, Diane Cook, and Sajal K Das. 2012. ActiSen: Activity-aware sensor network in smart environments. Pervasive and Mobile Computing 8, 5 (2012), 730--750. Google ScholarDigital Library
- The Networking, Information Technology Research, and Development (NITRD). 2015 (accessed March 9, 2017). Cyber Physical Systems Vision Statement.Google Scholar
Integration of Social Behavioral Modeling for Energy Optimization in Smart Environments
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