International Journal of Advanced Research in Computer and Communication Engineering

Abstract: Plants play an important role in maintaining ecological balance and supporting human life. However, maintaining healthy plants requires proper care, timely monitoring, and early disease detection. Many plant owners lack the knowledge and tools needed to identify plant diseases and manage plant care activities effectively. This project proposes GreenCare, a smart web-based platform designed to assist plant enthusiasts in managing plant care and detecting plant diseases using artificial intelligence.
The platform integrates modern web technologies and machine learning to create an intelligent plant management system. The system is developed using the MERN stack, which includes MongoDB, Express.js, React.js, and Node.js. GreenCare allows users to register, create profiles, share plant-related posts, and interact with other users through likes and comments. The system also includes a plant care reminder module that helps users schedule activities such as watering, fertilizing, and pruning plants.
A key feature of the platform is the AI-based plant disease detection system, where users upload images of plant leaves. The system analyzes these images using a machine learning model developed with TensorFlow and Google Teachable Machine to identify plant diseases and provide predictions along with confidence scores.
The GreenCare platform demonstrates how full-stack web development and machine learning technologies can be integrated to create an intelligent plant care management system that supports plant health monitoring, community interaction, and efficient plant care scheduling.

Keywords: Plant Disease Detection, MERN Stack, Machine Learning, Plant Care Management, Image Classification, Smart Agriculture.

Downloads: | DOI: 10.17148/IJARCCE.2026.15246