AgriSence uses AI and machine learning for crop disease detection, crop recommendations, weather intelligence, and smart farming.
AgriSence was built to solve critical delays in crop disease identification. By leveraging GCP serverless functions and Gemini AI, it analyzes crop imagery and provides real-time, localized actionable advice to farmers across India.
Problem
Farmers often lose critical time identifying crop diseases, interpreting weather risk, and choosing the right advisory action for local conditions.
Solution
AgriSence uses AI crop intelligence to analyze crop imagery, recommend actions, combine weather context, and deliver multilingual farming guidance.
Features
Crop disease detection from field images
Crop recommendation and advisory workflows
Weather-aware farming intelligence
Multilingual guidance for regional accessibility
Screenshots
AgriSence crop intelligence workflow
Architecture
1Farmer submits crop image and context from the web app
2Serverless API validates input and enriches it with location/weather context
3AI workflow classifies disease risk and generates advisory steps
4Firebase-backed persistence stores history and user-facing recommendations
Tech Stack
Next.jsGeminiFirebaseGoogle CloudGenkit
Future Roadmap
- Add disease severity scoring and treatment tracking
- Improve regional crop coverage with more labeled samples
- Add satellite and soil signals for precision recommendations
