Iot Data Fusion and AI for Enhanced Energy Efficiency in Smart Homes

Abstract

This research aims at investigating the use of Internet of Things (IoT) data fusion, and Artificial Intelligence (AI) in the management of energy efficiency in smart homes. This research will learn and derive complex energy management strategies from the various IoT sensors these include temperature, occupancy, humidity and lighting among others. These dissimilar data sources therefore enhance the overall efficiency of capturing the home environment, which consequently provides a more accurate dynamism in the energy systems. Utilizing the AI algorithms, this research put forward the suggestions on the novel methods of real-time data collecting and processing for the HVAC and lighting control, and dynamic control of these systems based on the fused data. The paper assesses how systems that apply machine learning can be trained for advanced energy prediction and control, thereby improving energy productivity and customers’ comfort. By solving problems, associated with the quality and latency of the used data, this work intends to contribute to the development of smart home technologies and identify possibilities for utilizing them in obtaining sustainable energy management.