11th International Conference on ICT for Sustainable Development

Authors - Arnav Rahul Jade, Jatin Santosh Jaiswal, Nishad Sachin Kamat, Vedant Mahesh Kandarkar, Amruta Pabarekar
Abstract - The Cloud-Based Plant Health Monitoring System is designed to help farmers and agricultural experts precisely identify plant diseases using artificial intelligence and cloud technology. Traditional plant health assessments rely on manual inspection, which can be time-consuming and prone to errors. This project automates the process by allowing users to upload images of plant leaves, analyzed by a machine learning model hosted on a cloud platform. The system identifies whether the plant is healthy or has a disease, providing instant results through a simple mobile or web application. To achieve this, the system uses a Convolutional Neural Network (CNN) trained on a dataset of plant leaf images, covering both healthy and diseased conditions. The application is designed to be user-friendly, allowing even non experts to access plant health information easily. This approach reduces the need for excessive pesticide use, saves time, and supports sustainable farming practices by helping users respond to plant health issues promptly. Keywords-plant health monitoring, artificial intelligence, convolutional neural network (CNN), plant disease detection, cloud computing, mobile application and machine learning.