Welcome to the Earthquake Emergency Response Robots project! This project aims to create, develop, and implement systems specifically designed to handle post-earthquake situations using adaptable robots equipped with sensors and communication capabilities.
The Earthquake Emergency Response Robots project is a capstone project undertaken by a team of 8 individuals. The main focus of this project is to build adaptable robots capable of post-earthquake response tasks. These robots are equipped with various sensors and communication capabilities to aid in their operations.
- Route Optimization: Utilizes the A* algorithm to optimize routes for efficient navigation in post-earthquake scenarios.
- Voice Detection: Enables the robot to recognize voice commands for enhanced interaction and control.
- Human Detection: Utilizes YOLO (You Only Look Once) for real-time object detection, allowing the robot to identify and respond to objects in its environment.
- Building Damage Classification: Utilizes Convolutional Neural Networks (CNN) to classify building damage, providing valuable information for rescue operations.
- Raspberry Pi 5 (8GB) as the core controller.
- Camera for capturing visual data.
- Microphone for voice detection.
- PIR Sensor for detecting motion.
- Neo-6m GPS Module for location tracking.
- 2 DC Motors for movement.
- L298N Voltage Regulator for power management.
- 4 Batteries for powering the system.
- Python: The primary programming language used for development.
- Django: Used for building the web application framework.
- Apache Server: Hosting the web application.
- PostgreSQL: Relational database for storing structured data.
- MongoDB: NoSQL database for storing unstructured data.
- Apache Airflow: Used for orchestrating workflows and scheduling tasks.
- Docker: Used for containerization to ensure consistent deployment across different environments.
We welcome contributions from the community. If you're interested in contributing to the Earthquake Emergency Response Robots project, please follow these guidelines:
- Fork the repository.
- Create a new branch for your feature or bug fix.
- Make your changes and ensure the code passes all tests.
- Submit a pull request detailing your changes.
This project is licensed under the MIT License.
For any inquiries or feedback, please contact the project team at:
@Egemen Eroglu
@Ece Akdeniz