Daksh Kumar Shah@dakshshah05

Smart Energy Monitoring is an AI-based energy management system developed to reduce electricity wastage and improve energy efficiency in college campuses. The project monitors electricity consumption at room and block levels and provides real-time analytics through charts, dashboards, and usage reports. It helps identify which rooms or blocks consume the highest amount of electricity, enabling administrators to make informed decisions for energy optimization. The system uses Arduino UNO, ESP32-CAM, ultrasonic sensors, and motion-based automation to intelligently control electrical appliances such as lights and fans. When motion is detected in a room, the system automatically turns devices ON, and when no activity is detected for a certain period, the devices are switched OFF to prevent unnecessary energy consumption. This automation reduces manual intervention and minimizes power wastage in classrooms, labs, and offices. Collected sensor data is transmitted to a centralized platform where AI algorithms analyze energy usage patterns, detect abnormal consumption, and generate optimized suggestions for reducing electricity usage. The project also visualizes energy trends using graphs and comparative analysis between different rooms and blocks. By combining IoT, automation, and artificial intelligence, the system creates a smart and scalable solution for sustainable campus energy management. The project is cost-effective, easy to deploy, and can be expanded to larger infrastructures such as universities, offices, and smart buildings. Its primary goal is to promote energy conservation, reduce operational costs, and support environmentally responsible infrastructure management through intelligent technology.

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