FarmCast

Project Explanation:

Farmcast is an innovative mobile application aimed at supporting rainfed rice farmers by providing them with advanced technology for making informed decisions. The app uses artificial intelligence (AI) to forecast rainfall up to four months in advance, utilizing data from the SEAS5 API. This information allows farmers to plan ahead for planting, irrigation, and harvesting, reducing the risk of crop failure caused by unpredictable weather. The application also provides personalized recommendations on crop selection and care routines to optimize yield and increase overall productivity.

Farmcast stands out by integrating OpenAI’s API, which powers tailored strategies to prevent crop failure and improve farm management practices. Additionally, the app employs YOLOv11, a state-of-the-art computer vision model that can detect plant diseases through images, enabling farmers to take quick action and minimize damage to their crops. The application’s robust tech stack, including NestJS for the backend and MVVM (Model-View-ViewModel) architecture, ensures that the app is both scalable and efficient, making it a powerful tool for farmers in managing day-to-day operations and long-term strategies.

The primary goal of Farmcast is to reduce the risks that farmers face, especially those reliant on rainfed agriculture, by providing tools that help them anticipate challenges. With access to accurate weather forecasts and actionable insights on crop care, farmers can avoid costly mistakes and increase their yields. Farmcast acts as a valuable resource, enabling users to mitigate risks associated with weather volatility, crop diseases, and suboptimal farming practices, ultimately helping them achieve greater agricultural success and improved livelihoods.