AI Buildings:Design of Artificially Intelligent Buildings in the Energy Sector with an Autonomous Federated Learning Approach

In Recent Years Intelligent buildings are a part of Smart Environments, with the ability to adapt their behavior on their own to meet the requirements of the occupants. Intelligent buildings require AI to be included in their systems so that they can reason and make decisions on the fly. In order for a structure to act like an intelligent one, it must monitor its energy use and have an automatic on/off system for all of its lights, fans, doors, windows, and other electrical components. Reducing a building’s energy use in a cognitively enabled manner requires first collecting and analyzing data on the building’s power consumption over a significant sample period of time. Cluster the data into distinct groups according to the time period, power consumption, and user behavior using support vector machines and logic regression approaches. Insights gained from such patterns will be invaluable in determining where to focus efforts to reduce energy consumption. It guarantees that our observed outcomes are suitable for a one-year predictive study based on the data sample worked with the data. Moreover, compared our results to those of other machine learning algorithms and were pleased with the overall performance of our approach.