SmartAgroWeb: A Multi-Module AI-Driven Agriculture Platform

Agriculture is a essential driver of economic development and food security, but farmers are still confronted with many obstacles such as unpredictable climate, the wrong crop choice, plant diseases, and the inability to access information about price, government scheme or market in real-time. The purpose of this paper is to introduce and present SmartAgroWeb: An intelligent web-based agricultural support system, built using AI, ML and real-time APIs into one cohesive solution. The proposed solution is established using a multi-layer architecture which includes the presentation, application, service/API, and data layers. The system provides numerous features such as crop recommendation based on soil parameters, plant disease detection using image processing, weather forecasting in real-time, monitoring of market prices, government scheme recommendations, and consultation from experts. The system also incorporates an AI-based chatbot which provides instant advisory support based on a hybrid of rule-based logic and large language models. The system is developed on a client-server architecture using modern web technologies such as React.js for the frontend, Spring Boot for backend processing, and MongoDB for data storage. It also relies on third party APIs to provide real-time data, thus helping to improve the accuracy and reliability of its recommendations. The aim of this project is to integrate multiple services into a single user-friendly platform.