This report appeared in the academic journal Actuators (April 2021). The authors propose a predictive-learning framework based on contextual feature selection and an optimal actuator control mechanism, with the goal of minimizing energy consumption in smart homes. The analysis also addresses how optimal control can reduce energy cost and improve performance resulting from lesser learning cycles and decreased error rates.
Keywords: Architecture/Engineering, Audio/Video, Controls/Sensors, Energy Management, Intelligent Building, Research & Development, Smart Cities, Smart Grid, Training