Project AgriSage Tech: Federated Learning-Driven Agricultural Innovations for Precision Agriculture

Agriculture in Bangladesh faces numerous challenges, including suboptimal crop selection, disease susceptibility, frequent natural disasters, fluctuating market prices, budgetary mismanagement, and inadequate soil classification. To tackle these issues, a mobile application has been developed under this project, designed to revolutionize traditional farming practices through the use of advanced artificial intelligence (AI) technologies. This application integrates decades of agricultural data with Federated Learning to improve accuracy in crop prediction and recommendations. It features real-time disease and soil detection capabilities, similar to Google Lens, allowing for quick identification and resolution of agricultural problems. Additionally, the application includes a proprietary budget distribution algorithm that offers customized financial planning based on crop type, geographical area, and location. Weather forecasts and SMS-based natural disaster alerts help mitigate the effects of environmental disruptions, ensuring farmers are better prepared. To address the digital divide in rural areas, the application offers limited functionalities via a USSD interface, allowing access for non-smartphone users. This comprehensive AI-powered solution aims to enhance agricultural productivity, promote sustainability, and support farmers in making informed decisions, aligning with the goals of sustainable development.