Smart Agriculture: IoT-based Irrigation and Nutrient Management

Designed an integrated framework that combines IoT sensors, drones, and machine learning models to optimize irrigation scheduling and nutrient application. Developed approaches that merge evapotranspiration (ET)-based calculations with soil sensor data, enabling real-time decision-making. Proposed hybrid solar–wind energy harvesting for IoT devices and blockchain protocols for farm data integrity. The system aims to increase crop yield by 30–50%, reduce waste of water and fertilizer, and ensure scalability across diverse farm settings.

IoT-driven prediction and management of irrigation and nutrient use for sustainable agriculture