Inspiration
Farmers often sell crops without knowing future market trends, leading to lower profits. We wanted to build an AI-powered assistant that helps farmers estimate crop prices before selling and make better marketing decisions.
What it does
Crop Price Prediction Assistant predicts the estimated market price of crops using AI. Users enter the crop name, mandi location, quantity, and harvest date, and the system generates intelligent price forecasts along with market insights to support better selling decisions.
How we built it
Backend: Java 17, Spring Boot
Frontend: HTML, CSS, Thymeleaf
AI Engine: Google Gemini API
Deployment: Docker & Render
Challenges we ran into
Designing reliable prompts for consistent AI price predictions
Handling different crops and mandi locations across India
Integrating Gemini API securely using environment variables
Deploying the application with Docker and Render
Accomplishments that we're proud of
Built a complete AI-powered crop price prediction web application
Supports 35+ crops and major Indian mandis
Fast concurrent prediction for multiple crops
Successfully deployed the project online for public access
What we learned
Prompt engineering with Gemini AI
Spring Boot REST API development
Docker containerization and cloud deployment
Building AI-assisted decision support tools for agriculture
What's next
Integrate real-time APMC market data
Add multilingual support (Marathi, Hindi)
Include weather and demand analysis in predictions
Provide confidence scores and historical price trends
Launch a mobile-friendly version for farmers
Built With
- html/css-ai-engine-google-gemini-api-build-tool-maven-deployment-docker
- layer-technology-backend-java-17
- spring-boot-3.2.0-frontend-thymeleaf
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