Design and implementation of an office standby–power management system through physical and virtual management by user–device habitual pattern analysis in energy–Internet of Things environments

Abstract

In the changing environment of the Internet of Things, optimal energy management in smart spaces requires intelligent and reliable energy-aware-based context sensing and technologies that are capable of recognizing and analyzing the big-data user pattern. In this article, we propose an intelligent and reliable standby power management system. The system uses physical and virtual user behavioral pattern analysis based on energy-aware management to cut-off the standby power of office appliances in the office environment. We propose a two-step priority power-aware method. The first step entails physical perception and management that controls devices through user recognition and device relationship scenarios. The second step is virtual perception and management that controls the standby power by collecting user behavioral patterns and performs an analysis based on a rule mechanism. The proposed system was applied to three locations (offices A, B, and C) in the university test-bed. Power consumption was reduced to 23% of the original consumption through the elimination of unnecessary standby power consumption.