Innovative Machine Learning and the Internet of Things for Smart Buildings with Low Energy Use: A Revolutionary Learning Optimization Framework

Abstract

The increasing urbanization and energy demand necessitate state-of-the-art building management systems that can maximize energy efficiency while maintaining tenant comfort. Internet of Things (IoT) smart buildings constantly log data on occupancy, operations, and the surrounding environment. In order to derive useful insights from this mountain of data, sophisticated analytical frameworks are required. Modern optimization frameworks that integrate Machine Learning (ML) and the Internet of Things (IoT) lessen the energy consumption of smart buildings without sacrificing performance, sustainability, or user happiness. In the proposed system, sensors that are part of the Internet of Things track things like illumination, temperature, humidity, air quality, occupancy, and equipment performance. Machine learning algorithms examine the data sent by these networked devices, which might be located in a centralised or edge-based analytics platform.