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The AI-Based Smart Microgrid Energy Management System aims to improve energy utilization and power management using IoT and machine learning. The system integrates solar power, battery storage, and transformer supply, with an ESP32 monitoring electrical and environmental parameters. MQTT enables real-time data communication, while a web dashboard supports remote monitoring and load control. Relay-based switching manages power sources according to predefined operating conditions. An LCD displays system status, and a Python-based backend stores data and generates alerts. Machine learning is proposed for estimating battery and transformer health to support predictive maintenance. The system provides a cost-effective approach to smart energy monitoring, automated power management, and reliable microgrid operation
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landge et al. (2026) studied this question.
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