This project aims to develop a mobile application that provides a marketplace for farmers and markets to connect and utilizes machine learning to detect crop diseases. The purpose of this project is to address the challenges faced by farmers in selling their produce and the increasing need for early detection of crop diseases to reduce crop losses and increase yields. Small-scale farmers often face challenges in accessing markets and selling their produce, while crop diseases can cause significant losses, reducing yields and income for farmers.
This project seeks to leverage technology, such as mobile applications and machine learning, to improve the livelihoods of farmers. The mobile application will provide a platform for farmers to sell their produce directly to markets, eliminating intermediaries and reducing costs. The machine learning model will help in early detection of crop diseases, reducing crop losses and increasing yields. The project will utilize Kotlin for mobile app development, TensorFlow for machine learning model development, and Firebase for backend and database management.
