Image Recognition based Smart Plant Care System

Abstract

This paper introduces a novel automated plant care system designed to autonomously water plants by identifying them and assessing their individual watering needs. The system utilizes the YOLOv5 object detection model to accurately identify various plant species and integrates moisture sensors to monitor soil conditions, ensuring optimal hydration levels. The primary aim of this work is to streamline plant care processes, significantly reduce water wastage, and promote sustainable gardening practices. The integration of advanced object detection with real-time moisture assessment allows the system to deliver precise amounts of water to different plants, catering to their specific requirements. Simulation results validate the identification of plants and effectiveness of the system in optimizing water usage while maintaining plant health. This approach demonstrates the feasibility of using machine learning for environmental sustainability.