Published Paper Details:

Water scarcity is a serious challenge for agriculture, which heavily relies on insufficient monsoon rains. To address this issue, an Internet of Things (IoT) and Machine Learning (ML) based smart irrigation system is proposed. This system predicts irrigation requirements using environmental parameters and weather forecasting, optimized by an ensemble ML method. The system reduces water, labour, and plant nutrient usage with a low-cost prototype achieving above 90% accuracy. A flexible IoT platform is designed to enable developers to easily integrate IoT and ML components for customized analytical methods in precision irrigation. This platform benefits both IoT specialists and farmers by reducing water waste, lowering costs, and ensuring safer crop yields. An intelligent irrigation system is implemented using an IoT-enabled ML-trained system for optimal water consumption. IoT sensors capture real-time ground and environmental data, which is analyzed by ML to provide irrigation minimizing human intervention.