Smart Campus Energy Usage Analysis And Prediction

This project presents the design and development of a Smart Campus Energy Usage Analysis and Prediction system that monitors and forecasts energy consumption across campus facilities. The system collects energy usage data from different buildings such as hostels, academic blocks, and libraries, and processes it using data analytics and machine learning techniques. A predictive model based on linear regression is used to estimate future energy consumption patterns. The system also provides interactive dashboards for real-time visualization, including consumption trends, building-wise distribution, and forecast insights. The proposed system aims to improve energy efficiency, reduce wastage, and support sustainable energy management in smart campus environments.