Intelligent Edge-Based Recommender System for Internet of Energy Applications

Preserving energy in households and office buildings is a significant challenge, mainly due to the recent shortage of resources, uprising current environmental problems, global lack utilizing energy-saving technologies. Not mention, within some regions, COVID-19 social distancing measures have led temporary transfer demand from commercial urban centers residential areas, causing an increased use higher charges, turn, creating economic impacts on customers. Therefore, marketplace could benefit developing Internet Things ecosystem that monitors consumption habits promptly recommends action facilitate efficiency. This article aims present full integration proposed efficiency framework into Home-Assistant platform using edge-based architecture. End users can visualize their patterns as well ambient data user interface. More notably, explainable recommendations are delivered end form notifications via mobile application habit change. In this context, best authors’ knowledge, first attempt develop implement recommender system edge devices. Thus, ensuring better privacy preservation since processed locally edge, without need transmit them remote servers, case with cloudlet platforms.