IOT-Based Machine Learning for Crop Pattern Analysis

The agricultural sector is grappling with a decline attributed to entrenched traditional practices, leading to low productivity and diminishing farmer morale, which in turn fuels youth migration abroad. Despite its portrayal as an agricultural hub, Agriculture sector faces challenges in enhancing productivity, emphasizing the need to optimize labor efficiency and boost arable land fertility. Smart agriculture, facilitated by IoT-based systems, emerges as a viable solution to address these issues, aiming to retain skilled youth and revitalize the sector. The study aimed to develop an IoT-driven monitoring system for arable land and utilize machine learning for crop prediction and recommendation. Through the integration of IoT and machine learning, farmers can access crucial insights for informed decision-making, potentially reversing the trend of youth emigration and fostering agricultural resurgence within Maharashtra.