Abstract

There has been a significant change in the management and operation of buildings as a result of the incorporation of Distributed Intelligence into Building Management Systems. This paper analyzes the revolutionary potential of this integration, concentrating on the suggested technique, which amalgamates Decentralized Sensor Networks, Federated Learning, and Predictive Maintenance algorithms. The approach uses real-time data, machine learning, and decentralized decision-making to improve building operations. The new technique is shown to perform better on all of the most important performance criteria when compared to the six original approaches. The suggested technique greatly improves upon conventional methods with regards to energy efficiency, occupant comfort, system responsiveness, maintenance cost reduction, security effectiveness, and flexibility. It is much easier to understand the comparative analysis and how the suggested solution outperforms the separate methods by using visual representations.