Smart Sprinkler IoT System for Plants: Real Time Plant Detection & Water-Nutrition Supply Management Robot Using IoT & Computer Vision

Conventional irrigation techniques notably contribute to water waste, ineffective resource usage and laborintensive processes, hampering agricultural productivity and sustainability. In response to these challenges, this paper presents a smart sprinkler IoT system for plants, a low cost and autonomous solution application for the management of precision water and nutrition supply. It utilizes IoT, computer vision, and robotics to maximize farming efficiency. Using an ESP32 camera module, ESP32 development board and Yolo (You Only look Once) object detection model to identify the plants, the robot is able to know the moisture content in the soil and then able to deliver water or nutrients wherever it is needed. An IoT platform connects the system, which allows monitoring in real-time, gathering historical data, and making data-driven decisions. Positive results seen in field trials include drastic water reduction, increased yield, reduced cost to operate and environmental sustainability. In particular, this solution tackles the urgent problems of water or nutrients waste and human poorly utilizing agricultural resources, creating the foundation for scalable, data-driven, sustainable agriculture.