Smart Sensing and End-Users' Behavioral Change in Residential Buildings: An Edge-Based Internet of Energy Perspective

Abstract

Internet of Energy (IoE) is revolutionizing the building energy industry by introducing numerous innovations that help in data collection, interpretation, and behavioural improvement. Consequently, collecting and analyzing big data is fiercely impacting every field and research area in the context of energy utilization, and therefore, the concept of micro-moments is a timed encapsulation of the user's interaction with the building's appliances. In this article, a high-performance yet cost-efficient edge-based IoE platform for Energy Efficiency in buildings, called Edge-IoE3 is presented, which allows sensing, processing and analyzing energy data in residential buildings. The proposed platform, in the form of a smart plug, consists of two units: a data collection unit and a data processing unit. The data collection unit includes multiple sensors that measure energy consumption along with temperature, humidity, luminosity, and room occupancy. Innovative micro-moment analysis based on ensemble bagging trees is performed to extract pertinent energy consumption micro-moments, which aid in improving consumption behavior with recommender systems. Obtained results have shown a classification accuracy up to 99% of the sensed data and a computation time of 0.1 sec. A number of case studies is presented as guidance on the applications of the proposed solution, and as a building block for improving energy efficiency in buildings. 2001-2012 IEEE.