Built with ❤️ by Team The_Debuggers
KrishiConnect is a full-stack, modular smart farming ecosystem that integrates IoT hardware, machine learning models, and a responsive web dashboard to enable precision agriculture. From soil nutrient detection to real-time climate monitoring and ML-based crop recommendations — it's all-in-one.
PLANTVILLAGE dataset for crop disease detection : https://www.kaggle.com/datasets/mohitsingh1804/plantvillage
Crop Production dataset : https://www.kaggle.com/datasets/nikhilmahajan29/crop-production-statistics-india
NPK values dataset for crop recommendation : https://www.kaggle.com/datasets/atharvaingle/crop-recommendation-dataset
- 🌱 Real-time Soil & Environmental Monitoring
- 📊 Live data visualization via a modern web interface
- 🧠 ML-driven insights for smart farming
- ☁️ Seamless cloud connectivity via MongoDB Atlas
- 🧩 Modular hardware for plug-and-play sensors
| Technology | Description |
|---|---|
| React.js | Component-based frontend library |
| TypeScript | Strongly typed JavaScript |
| Tailwind CSS | Utility-first CSS for design |
| Technology | Role / Usage |
|---|---|
| Node.js | Server-side runtime |
| Express.js | REST API creation |
| MongoDB | NoSQL Database |
| MongoDB Atlas | Cloud-hosted database |
| Flask | Python-based ML endpoints |
| FastAPI | High-performance async Python backend for ML APIs |
| Library / Framework | Usage |
|---|---|
| TensorFlow | Deep learning models |
| Scikit-learn | Classification, regression, preprocessing |
| Python | Core ML scripting and API integration |
| API | Purpose |
|---|---|
| Gemini | AI-based knowledge/insight generation (optional feature) |
| Component | Details |
|---|---|
| Microcontroller | ESP32-WROOM-32 Dev Kit V1 |
| Processor | Dual-core Xtensa LX6 32-bit |
| Connectivity | Integrated 2.4 GHz Wi-Fi (802.11 b/g/n) |
| Language | Programmed in C++ |
| Sensor Type | Sensor Name | Parameters | Interface |
|---|---|---|---|
| Soil Multiparameter | JXBS-3001-TR | Soil pH, EC, Temperature | RS485 (Modbus via MAX485) |
| Macronutrient Sensor | RS485 NPK Sensor (3-Prong) | Nitrogen, Phosphorus, Potassium (NPK) | RS485 Modbus |
| Air Conditions | DHT22 / AM2302 | Air Temperature, Humidity | 1-Wire Digital |
| Soil Moisture Sensor | Capacitive Soil Moisture Sensor v1.2 | Volumetric Water Content | Analog |
| Component | Description |
|---|---|
| OLED Display | SSD1306 - 0.96 inch, 128x64 pixels, I2C Interface |
| Component | Description |
|---|---|
| Power Architecture | Dual 12V DC input with dedicated voltage regulators |
| Voltage Regulators | LM2596 (5V), AMS1117 (3.3V) |
| Distribution Board | Custom-built board for clean, isolated power delivery |
| Component | Description |
|---|---|
| Main Board | Perfboard with soldered connections |
| Connectors | Screw terminals, Dupont connectors |
| Enclosure | Custom protective case for field deployment |
- 📡 LoRa/Long-range Communication
- 🌐 Offline Data Logging via SD card
- 📱 Mobile App Integration
- 🤖 Crop Disease Prediction using image data
| Name | Role |
|---|---|
| SubhaBilash Das | Hardware Integration Lead |
| Arpan Chowdhury | Front End Developer |
| Syed Md. Musharraf | ML/AI Developer |
| Srinjoy Pramanik | Cloud & API Integrations |
This project is licensed under the MIT License. Feel free to use and build upon it with proper attribution to Team The_Debuggers.
📧 For collaborations or queries, reach out at:
[📨 [email protected]] (Replace with actual email)