State-of-the-art Activity Recognition and Prediction Techniques Applicable to the Home Energy Management System

Abstract

Owing to the tendency to convert ordinary homes to smart ones, there are novel opportunities for home energy management systems to exploit the binary and analog sensors collected information to enhance their performance. Having accurate forecasting about the behavior of house inhabitants, and their preferences could help the system be more efficient and reliable. In this paper, some state-of-the-art activity recognition and prediction techniques are reviewed and we introduce a conceptual platform for interactive collaboration between smart homes and energy management systems.