IoT-Based ML Model to Sense Selection of Seed Crops in Changing Climatic Conditions of Punjab

In past two decade’s farmers of Punjab suffering huge losses in farming due to changing climatic patterns. Irregular rainfalls, hail storms, windstorms, drought, heat waves, cold waves, etc. are the major factors. Farmers are facing challenges in adapting new farming practices to the ever-changing climate conditions, all while incorporating advanced agricultural technologies and innovative seed varieties. The Internet of Things (IoT) presents a promising solution to address future challenges. Traditionally, agricultural production heavily relied on weather patterns. However, the current climate crisis has significantly disrupted this norm. While older seed types still yield high outputs when properly cared for, newer seed varieties have adapted to specific climatic and moisture requirements. In this research, our objective was to train machinery to identify crucial developmental stages in the crop's life cycle. This way, it can provide farmers with guidance on how to effectively manage the equipment based on the crop's thriving conditions. Rather than aiming to establish predetermined thresholds, this enhanced agricultural initiative strives to preserve the environment while catering to the shifting needs of the crop throughout its entire life cycle. Depending on the crop's current stage and anticipated duration, farmers may explore new approaches. Any device equipped with Internet connectivity and sensor capabilities can be employed to carry out these procedures. We achieved 95.89% accuracy with our proposed model.