Energy Auditing and Management Using IOT and Machine Learning

This work aims to push forward in conducting energy audits and their proper management in the department building in our campus, incorporating technologies of the Internet of Things and machine learning into energy auditing and management processes. For this work, an overall energy audit is conducted where sensors from Internet-enabled facilities were placed throughout various rooms so that energy consumption is monitored in real-time with the help of cloud. This information is then evaluated using machine learning-based algorithms that determine consumption behaviors and locate the best position for the implementation of efficient energy conservation measures. Other than that, this work will use predictive models to forecast future energy demands based on historical data thus making better-informed decisions that are meant to guide and manage energy. The basic objective of this project shall be to reduce energy costs in addition to improving operational effectiveness while also reducing the footprint of energy consumption on the environment. It is scalable and data-driven, thus represents the best possible innovative energy management strategy in academic and industrial settings.