AgriSol is a smart agriculture platform designed to empower farmers with modern technology to optimize farming practices, enhance productivity, and ensure sustainability. In an era marked by climate change, food insecurity, and rising population demands, AgriSol offers an integrated digital solution to tackle agricultural challenges head-on.
Agriculture today faces numerous challenges:
- 🌡️ Climate change
- 🧱 Soil degradation
- 💧 Water scarcity
- 📉 Limited market access
- 📚 Lack of modern agricultural knowledge
AgriSol addresses these through a comprehensive web application that combines real-time data, AI-based analysis, and a user-friendly interface.
-
📍 Personalized Farming Advice
Tailored crop recommendations and best practices based on region, soil, and weather. -
🌦️ Real-Time Weather Forecasting
Integration with weather APIs to help farmers plan their activities efficiently. -
🌾 Crop Health Monitoring
Upload crop images to detect diseases and pests using AI & image processing. -
📈 Market Price Updates
Live market data and price trends to help farmers get better returns. -
📚 Educational Resources
Access to tutorials, sustainable farming guides, and government schemes. -
🧑🌾 Farmer Community Network
A space for farmers to collaborate, ask questions, and share knowledge.
- HTML5 – Semantic structuring of web content.
- CSS3 – Responsive and accessible layout design.
- JavaScript – Dynamic and interactive user interface.
- Node.js – JavaScript runtime for server-side development.
- Express.js – Web framework for building RESTful APIs and routing.
- Python – Core language for AI and ML integration.
- Flask – Lightweight Python web framework to serve AI endpoints.
- OpenCV – For image analysis and disease detection using computer vision.
- Kaggle - A source for crop pest detection dataset.
- MongoDB – NoSQL database used for storing user data, crop information, and market insights.
🗂️ Download the Crop-Pest-Detection Dataset from here.
AgriSol integrates a dedicated AI module using Flask and Python, which allows real-time:
- 🐛 Pest detection
- 🍃 Crop disease diagnosis
- 🧠 Image classification using trained ML models
Farmers can upload images of affected crops and receive insights based on pre-trained computer vision models.
- 📲 Mobile-friendly UI for on-the-go access
- 🛰️ Satellite data integration for soil and weather analysis
- 🌍 Regional language support for better accessibility
- 📩 Notification & alert system for climate and price changes
- Node.js and npm
- Python 3.x
- MongoDB (local or cloud URI)
- Git