This course project, Autonomous Mobile Robot (AR-511), undertaken at CAIR, IIT Mandi, is centered on the development of a drone-based system designed to detect crop diseases in agricultural fields and present the diagnostic results through a dedicated user interface.
# Farm Drone Inspection System
## 🎥 Simulation Demos
Check out the system in action:
| **Drone Deployment & Flight** | **AI Disease Detection View** |
|:-----------------------------:|:-----------------------------:|
| | |
| *Autonomous sweep pattern execution* | *Real-time YOLOn, GNN & SAM+LoRA* |
## Overview
The Farm Drone Inspection System is a comprehensive full-stack web application designed for autonomous agricultural drone management and monitoring. The system integrates a PyBullet-based physics simulation engine with a Flask RESTful API backend and a responsive web-based frontend interface. It enables users to define inspection zones, deploy autonomous drones, and monitor real-time mission progress through an intuitive web interface.
## System Architecture
### Technology Stack
- **Backend**: Python 3.8+, Flask 3.0.0, PyBullet 3.2.5
- **Frontend**: HTML5, CSS3, JavaScript (ES6+)
- **Physics Engine**: PyBullet with custom PID control implementation
- **Communication**: RESTful API with JSON payloads
- **Concurrency**: Multi-threaded simulation management
## Project Structure
```
Farm_drone_inspection_simulator/
├── backend/
│ ├── app.py # Flask API server
│ ├── drone_sweeper.py # Simulation orchestration
│ ├── BaseControl.py # Abstract control interface
│ ├── DSLPIDControl.py # PID controller implementation
│ ├── enums.py # System enumerations
│ ├── cf2p.urdf # Crazyflie 2.0 model definition
│ └── ..............
│
├── frontend/
│ ├── index.html # User interface markup
│ ├── style.css # Stylesheet definitions
│ └── script.js # Client-side application logic
│
├── requirements.txt # Python dependencies
├── quick_setup.md
└── README.md # System documentation
```
## Features
### Farm Management
- Define inspection zones with configurable boundaries
- Visual representation of …