HEMS-IoT: Smart Home Energy Saving with Big Data and Machine Learnings

Controlling energy consumption in residential areas has become essential in the world of heterogeneous Internet-of-Thing (IoT) devices with the aim of cost savings in order to create a workable way of home energy management system (HEMS). Different protocols and norms are now being established for the devices. It is a problem to integrate multiple devices in the exact same HEMS, and numerous ways have been suggested to do so effectively. New system implementation will cost a lot of money, nevertheless. Because of the recent rise in energy use, particularly in the residential sector, energy competence has become a major area of interest for researchers worldwide. New advancements in energy transformation, novel means of communication, and information technology have made possible what are now called “smart homes”. The coming together of multiple diverse technologies with different applications fields to interconnect objects over the Internet, enabling the detection, tracking, and control from afar of multiple devices, is known as the Internet of Things (IoT). HEMS-IoT, a machine learning-and big data-driven energy management in smart homes system for convenience, security, and energy conservation, is presented in this study.