Landmines continue to pose a serious threat in conflict and post-conflict regions, causing significant risks to human life and hindering safe land utilization. This project presents an advanced AI-based Landmine Detection Rover that integrates the YOLOv8 object detection algorithm with a Raspberry Pi 4 to provide a safer and more efficient solution for landmine identification. The system combines computer vision, embedded systems, and IoT technologies to enhance detection accuracy while minimizing human involvement in hazardous environments. The rover is designed to operate in both manual and autonomous modes, which can be controlled through a web-based interface. In manual mode, users can remotely navigate the rover with real-time video streaming, whereas in autonomous mode, the rover uses an ultrasonic sensor (SR04) to detect and avoid obstacles intelligently. A metal sensor continuously scans the ground for the presence of metallic objects, and upon detection, the Raspberry Pi activates the Pi Camera to capture images of the suspected area. These images are processed using the YOLOv8 algorithm to classify whether the detected object is a landmine. If a landmine is identified, the system immediately sends alerts via email with the captured image and GPS coordinates, along with SMS notifications using a GSM module. This ensures timely communication and quick response for safety measures. The integration of artificial intelligence, real-time monitoring, and wireless communication makes the system highly effective for Défense operations, minefield detection, and exploration of hazardous zones. Overall, this project significantly reduces human risk, improves detection reliability, and enhances operational efficiency in dangerous environments.      

The main objectives of this project are:  

  To design and develop a smart rover capable of detecting landmines remotely to reduce human risk.

  To integrate the YOLOv8 algorithm for accurate identification and classification of landmines using image processing.

  To implement both manual and autonomous navigation modes for flexible operation.

  To enable real-time monitoring and control of the rover through a web-based interface.

  To incorporate an ultrasonic sensor (SR04) for obstacle detection and avoidance in autonomous mode.

  To use a metal detection sensor for initial detection of buried metallic objects.

  To capture and process images using a Raspberry Pi camera for AI-based analysis.

  To provide instant alerts via email and GSM-based SMS with image and GPS location when a landmine is detected.

  To ensure efficient communication using IoT technologies for remote surveillance.

  To enhance safety, accuracy, and response time in hazardous and defense environments.        

The major building blocks of this project are:  

1. Battery power supply.
2. Raspberry pi4.
3. SD card.
4. Pi camera.
5. L298 motor driver with DC motors.
6. Metal sensor.
7. Ultrasonic sensor.
8. GSM.
9. GPS.

      Software’s used:  

• Raspbian OS.

• Express SCH for Circuit design.
• Image processing Algorithm.
• IoT technology for sending mail.
• WEB application.

     

video: