AgriSolar AI

AgriSolar AI was inspired by the real challenges faced by Indian farmers, especially those in rural areas where frequent power cuts, lack of expert support, and difficulty identifying crop diseases early often lead to huge losses. Many farmers also struggle with text-heavy applications due to low literacy levels, which motivated us to create a simple, image-based, solar-powered AI solution that works anywhere, anytime. AgriSolar AI is a mobile application that allows farmers to capture or upload a leaf image and instantly receive AI-based disease detection along with symptoms, causes, treatments, and preventive measures. The app includes voice search, multi-language support, image-based crop selection, a feedback system, and dynamic crop loading from the database, making it extremely farmer-friendly. We built it using an AI model trained on crop leaf datasets, a colorful and simple UI with large image cards, a structured backend, and solar-powered functionality to ensure usage even without electricity. During development, we faced challenges such as designing an intuitive UI for uneducated farmers, improving AI accuracy, ensuring low-power usage for solar operation, managing dynamic crop data, and supporting multiple languages. Despite these challenges, we are proud that AgriSolar AI provides accurate disease detection, works in areas without electricity, supports farmers of all literacy levels, and offers a clean, visually guided interface that farmers truly understand. Throughout the process, we learned how to build accessible technology, train AI models effectively, design for inclusivity, and integrate renewable energy with agriculture. Moving forward, we plan to expand AgriSolar AI by adding more crops and diseases, enabling offline AI detection, integrating sensors for continuous monitoring, introducing GPS-based disease alerts, adding more Indian languages, creating a farmer community with chatbot support, and connecting the app with government agriculture schemes to better empower farmers.

Built With

• css
• html
• javascript
• python