README.md

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title: Generative AI With Poultry Disease Detection System V2
emoji: 🐨
colorFrom: pink
colorTo: gray
sdk: docker
pinned: false
license: mit
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Here’s the updated `README.md` with an improved structure and updated to-do list:

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# 🐔 Poultry Farming Assistance and Management System

This project combines a **Poultry Farming Assistance System** and a **Poultry Management System**, streamlining health
monitoring, task management, inventory tracking, and disease detection using AI. Designed for farmers and farm admins,
this system enables effective poultry health management, provides real-time alerts, and generates actionable insights to
enhance productivity.

## Key Features

1. **User Authentication and Role-Based Access**: Secure registration and login for farmers and admins.
2. **Health Management with AI-Driven Disease Detection**: Fecal image analysis for common poultry diseases and
   personalized treatment recommendations.
3. **To-Do List and Task Management**: Track daily farm tasks and share across groups.
4. **Inventory Management**: Monitor feed, medication, and supply levels with automated alerts.
5. **Data Logging and Reporting**: Real-time dashboards, export options, and health reports.
6. **Notification System**: Email alerts for tasks, health conditions, and inventory updates.

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## System Overview

### Poultry Farming Assistance System

- **AI-Powered Disease Detection**: Uses pre-trained models (e.g., `Final_Chicken_disease_model.h5`) to analyze fecal
  images and identify poultry diseases.
- **Health Monitoring**: Tracks metrics such as weight loss, mortality rate, and feed intake for proactive care.
- **Treatment Recommendations**: Offers tailored suggestions based on detected health issues.

### Poultry Management System

- **Task and To-Do List Management**: Allows farm admins to assign tasks and track completion across groups.
- **Inventory Tracking**: Manages inventory levels and provides alerts for low-stock items.
- **Health Records**: Logs poultry health data and tracks disease outbreaks.
- **Reporting**: Generates farm performance reports and health metrics.

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## Use Cases

- **Farmers**: Access disease detection, complete tasks, view health records, and receive alerts.
- **Admins**: Create tasks, monitor group activities, manage inventory, and ensure flock health.

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## 📝 To-Do List

### 1. Setup and Configuration

- [x] Set up a virtual environment and install required packages (`FastAPI`, `TensorFlow`, `MongoDB`, `transformers`,
  etc.).
- [x] Configure MongoDB and test CRUD operations.
- [x] Establish environment variables for MongoDB, email credentials, and Hugging Face API token.

### 2. Authentication System

- [x] Develop user registration for farmers and admins.
- [x] Implement login/logout with JWT.
- [x] Set up password encryption (`bcrypt`) for secure storage.

### 3. Poultry Farming Assistance System

- [x] Integrate the poultry disease detection model (`Final_Chicken_disease_model.h5`).
- [x] Set up image preprocessing for disease detection.
- [x] Build endpoints for image upload and disease analysis.
- [x] Generate health-related notifications and recommendations.
- [x] Implement real-time health monitoring and alerts.

### 4. To-Do List Management

- [x] Design MongoDB schema for to-do lists.
- [x] Create routes for farmers to view and mark to-do items.
- [x] Build functionality for admins to assign tasks.
- [x] Develop an **AdminLTE 4**-based UI for managing tasks.

### 5. Data Logging and Reporting

- [x] Implement data logging for activities and health records.
- [x] Build reporting dashboards using **AdminLTE**.
- [x] Enable export functionality (PDF, XLS).
- [x] Integrate real-time visualization tools for health and productivity insights.

### 6. Health Management

- [x] Define MongoDB schema for health records.
- [x] Integrate disease detection data into health management.
- [x] Develop an **AdminLTE** dashboard for disease and health tracking.
- [x] Automate health alerts and treatment recommendations.

### 7. Inventory Management

- [x] Design MongoDB schema for inventory tracking.
- [x] Implement routes for adding, updating, and managing inventory items.
- [x] Create an **AdminLTE** dashboard for inventory status.
- [x] Set up email alerts for low-stock items.

### 8. Notification System

- [x] Configure email service for notifications (`smtplib` or `nodemailer`).
- [x] Implement notifications for:
    - [x] Task completion.
    - [x] Health alerts and recommendations.
    - [x] Inventory updates and low stock alerts.
- [x] Test the notification system across scenarios.

### 9. Group Management

- [x] Create MongoDB schema for managing user groups.
- [x] Allow admins to create groups and share tasks.
- [x] Enable farmers to join groups and track shared tasks.

### 10. Testing and Debugging

- [ ] Write unit tests for modules (authentication, to-do lists, health management, inventory, etc.).
- [ ] Conduct integration testing to validate end-to-end functionality.
- [ ] Debug MongoDB transactions, pytorch predictions, and AdminLTE dashboards.

### 11. Deployment

- [ ] Deploy the application on Hugging Face Spaces or other cloud platforms.
- [ ] Configure production settings (environment variables, security).
- [ ] Set up CI/CD pipeline for automatic testing and deployment.

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## Future Enhancements

- **Mobile Application**: Develop a mobile app using `Flutter` for remote management.
- **AI-Based Inventory Forecasting**: Predict inventory needs based on usage trends.
- **Multi-Language Support**: Localize the interface for global users.
- **Extended Disease Detection**: Add models for additional poultry diseases to improve health management.

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