Automated irrigation systems using IoT and AI

Water shortage and inefficient irrigation practices continue to pose significant threats to sustainable agriculture in the world. The chapter presents the design and evaluation of an artificial intelligence (AI)-based, Internet of Things (IoT)-based intelligent irrigation system for maximizing water use while maximizing crop yield. The system consists of soil moisture, temperature, and humidity sensors networked with a microcontroller and wireless communication modules. A machine learning algorithm in real time estimates the irrigation requirement as a function of environmental parameters, and an intelligent valve control system schedules water supply accordingly. Field tests demonstrate 38% water saving, 19.1% yield improvement, and 94.6% accuracy of irrigation requirement detection. Additionally, crop growth observation using Normalized Difference Vegetation Index (NDVI) verified improved growth of the crops. Findings confirm the system’s ability to save water, lower human intervention, and increase crop yields. This research provides a stepping stone for the development of smart farm technology and presents an extensible data-driven precision irrigation and sustainable resources management solution.