AgroSense II: Smart Plant Disease Detection and Treatment Recommender

Abstract: Plant diseases are one of the major causes of crop loss and reduced agricultural productivity worldwide. Farmers, especially in rural regions, often struggle to identify diseases at an early stage due to limited access to expert support and modern agricultural tools. Traditional diagnosis methods depend on manual observation, which is time- consuming and prone to errors in large-scale farming. This paper presents AgroSense-II: AI-Powered Plant Disease Detection and Treatment Recommender, a unified web-based platform that integrates machine learning-based disease prediction, treatment recommendation, analytics dashboards, and historical record management into a single lightweight framework. The system employs a Random Forest classifier trained on agricultural datasets, a FastAPI-powered backend, ReactJS frontend, and MongoDB for data storage. By combining these technologies into one deployable architecture, AgroSense-II helps farmers identify diseases faster, receive actionable treatment guidance, and make smarter crop management decisions without depending on expensive hardware infrastructure.

Keywords: Plant Disease Detection, Precision Agriculture, Machine Learning, Random Forest Classifier, Smart Farming, FastAPI, ReactJS, MongoDB, Crop Monitoring, Treatment Recommendation.