A camera-integrated Arduino-based autonomous drone system combining computer vision, embedded motor control, and geospatial data processing for real-time disaster monitoring and damage assessment.
The project integrates OpenCV-based image analytics with Arduino Uno flight control, enabling low-cost aerial imaging and semi-autonomous navigation for emergency response and terrain analysis.
In disaster-affected zones, rapid assessment is essential for effective relief operations.
This project aims to develop a vision-assisted drone system that can detect, analyze, and map disaster-prone regions such as fires, floods, or collapsed structures.
Using a Python-based computer vision module for real-time object detection and an Arduino Uno–controlled quadcopter for flight operations, the system offers aerial imaging, data visualization, and autonomous control support for rescue missions.
The Drone Imaging and Disaster Management Drone integrates a ground-based image processing unit with an Arduino Uno–driven aerial platform.
- The onboard camera captures live video streams that are analyzed using OpenCV and TensorFlow Lite for hazard detection (e.g., fire, smoke, human figures).
- The Arduino Uno, interfaced through serial communication, controls the drone’s motors via a motor driver or ESCs.
- GPS and IMU (MPU6050) sensors provide location, orientation, and stability feedback.
- The system allows both autonomous and manual override via a remote controller or serial commands.
| Component | Description |
|---|---|
| Arduino Uno | Core flight controller managing motor control and sensor interfacing. |
| Brushless Motors + ESCs / Motor Driver | Provides propulsion and directional thrust. |
| Drone Frame + Propellers | Aerodynamic frame supporting motors and sensors. |
| GPS Module (NEO-6M) | Enables location tracking and coordinate mapping. |
| IMU (MPU6050) | Provides accelerometer and gyroscope readings for stabilization. |
| Camera (USB / Pi Camera) | Captures live video feed for vision-based detection. |
| Python (OpenCV + TensorFlow Lite) | Handles object detection, mapping, and serial communication. |
| Serial USB Connection | Data link between PC (vision module) and Arduino Uno. |
| RC Transmitter / Joystick | Optional manual override for pilot control. |
- Board: Arduino Uno
- Port: Select your Arduino COM port in the IDE.
- Required Libraries:
Servo.hTinyGPS++MPU6050SoftwareSerial
Upload the firmware Drone_Uno_Controller.ino to your Arduino Uno.
Ensure all motor connections and ESC calibrations are properly configured.
00a04439bc28c7acffd395989091fd31dac0cff7
Install required dependencies:
pip install -r requirements.txt