Sidhanth-Mandal/Kisaan-Bandhu

## Tasks Accomplished - [x] **Task 1:** Completed the entire **UI development of the mobile app** using React Native. - [x] **Task 2:** Implemented the **backend logic of the IVR system**, enabling voice-based advisory flow. - [x] **Task 3:** Built and deployed the **backend logic of the AI Chatbot**, integrated with LangGraph and Gemini API. - [x] **Task 4:** Developed the **farming advisory backend**, integrated with weather (Meteo) and location (Google Maps) data. - [x] **Task 5:** Prepared and containerized **server files**, ready for deployment on Azure VM with Docker. - [x] **Task 6:** Trained and validated the **Pest & Disease Detection Model** using TensorFlow ( Accuracy 87 %). - [x] **Task 7:** Connected the **mobile app with PostgreSQL database** for secure data storage and retrieval. ## Technology Stack This project leverages the following technologies: * **React Native:** Cross-platform framework for building the mobile app, delivering a simple and intuitive UI/UX for farmers. * **JavaScript:** Powers frontend logic and interactivity in the mobile app. * **Python:** Core backend language for implementing advisory logic, model inference, and API handling. * **FastAPI:** High-performance Python web framework for building APIs, handling farmer queries, and integrating models. * **Docker:** Containerization platform to package and deploy the backend seamlessly on Azure. * **Microsoft Azure:** Cloud provider hosting our backend on a Virtual Machine with APIs running 24×7. * **PostgreSQL:** Relational database for storing farmer details, preferences, and advisory records. **AI & Models** * **TensorFlow & PyTorch:** Used for training and deploying pest/disease detection and crop recommendation models. * **LangGraph:** Framework for building the AI-driven conversational chatbot and decision workflows. * **Gemini API:** Core intelligence powering the chatbot and personalized farming advisory. **Voice & IVR** * **Asterisk & FreePBX:** Open-source telephon …