MFC Based Smart Irrigation System Using IoT and Machine Learning

This research study proposes a novel Smart Irrigation System that integrates Microbial Fuel Cells (MFCs) with IoT and Machine Learning for sustainable agricultural practices. The system uses MFCs to generate electricity from soil microorganisms, providing a renewable energy source for irrigation. IoT sensors monitor real-time environmental parameters such as temperature, humidity, and soil moisture, and transmit data to cloud platforms for analysis. Machine learning algorithms are used to process the historical data, weather forecast, and sensor information in real-time to predict the irrigation requirement and optimize water usage. Renewable energy generation, IoT-based monitoring, and machine learning-driven decision support strategy are integrated in this system to improve water efficiency, reduce energy consumption, and support sustainable agricultural practice.