Automatic Pothole Detection System Using Deep Learning
Budget: ₹600 – ₹1,500 INR
1. **Survey Car with Dashcam**: The survey car will be equipped with a dashcam to capture live video footage of the road ahead. This footage will be continuously streamed to the pothole detection system.
2. **Pothole Detection System**:
- **Input**: Live video feed from the dashcam.
- **Processing**: Utilize a deep learning model, such as Faster R-CNN, to analyze the video frames in real-time and detect potholes.
- **Output**: If a pothole is detected, extract the coordinates of the pothole from the video frame.
3. **Map Server**:
- **Input**: Coordinates of detected potholes from the pothole detection system.
- **Processing**: Store the coordinates in a database and provide an API for accessing this data.
- **Output**: Serve the pothole coordinates to the user application.
4. **User Application**:
- **Functionality**: Allows users to receive alerts about potholes ahead of their current location.
- **Input**: Current location of the user obtained from GPS.
- **Processing**: Calculate the distance between the user's location and the coordinates of detected potholes obtained from the Map Server.
- **Output**: If the user is within a certain distance (e.g., 20 meters) of a pothole, send an alert to the user's application.
5. **Integration**:
- The Pothole Detection System should be integrated with the Map Server to automatically send detected pothole coordinates.
- The User Application should fetch pothole coordinates from the Map Server and provide alerts to users based on their current location.
Lastly, create a detailed report outlining the methodology, algorithms used, and results obtained. Furthermore, a PowerPoint presentation summarizing the project's objectives, process, and findings will be required.
2. **Pothole Detection System**:
- **Input**: Live video feed from the dashcam.
- **Processing**: Utilize a deep learning model, such as Faster R-CNN, to analyze the video frames in real-time and detect potholes.
- **Output**: If a pothole is detected, extract the coordinates of the pothole from the video frame.
3. **Map Server**:
- **Input**: Coordinates of detected potholes from the pothole detection system.
- **Processing**: Store the coordinates in a database and provide an API for accessing this data.
- **Output**: Serve the pothole coordinates to the user application.
4. **User Application**:
- **Functionality**: Allows users to receive alerts about potholes ahead of their current location.
- **Input**: Current location of the user obtained from GPS.
- **Processing**: Calculate the distance between the user's location and the coordinates of detected potholes obtained from the Map Server.
- **Output**: If the user is within a certain distance (e.g., 20 meters) of a pothole, send an alert to the user's application.
5. **Integration**:
- The Pothole Detection System should be integrated with the Map Server to automatically send detected pothole coordinates.
- The User Application should fetch pothole coordinates from the Map Server and provide alerts to users based on their current location.
Lastly, create a detailed report outlining the methodology, algorithms used, and results obtained. Furthermore, a PowerPoint presentation summarizing the project's objectives, process, and findings will be required.