Average speed camera system built on Ubuntu
Budget: $30 – $250 USD
I am looking for an experienced developer to create a real-time average speed camera system running on Ubuntu. The system will use live video feeds to detect vehicles at Point A and Point B, measure the time taken between these two points, calculate average speed, and determine whether the vehicle has exceeded a preset speed limit.
If a violation occurs, the system must log the vehicle automatically. Additionally, the system should provide a cloud dashboard where users can:
• Monitor live video feeds &
• View and filter violation logs
• Access basic statistics (e.g., daily/weekly violation counts)
This dashboard can be web-based and simple but should make the system monitorable remotely, increasing its value and usability.
Core Requirements:
• Real-time vehicle detection using a USB camera
• Detect and track vehicles at Point A "Entry" to Point B "Exit"
• Measure timestamp differences to calculate average speed
• Compare calculated speed against a configurable speed limit
• Automatically log violations with time, captured frame, and vehicle tracking ID
• Stream live video to the web-based cloud dashboard
• Ability to run continuously on Ubuntu
• Adjust configured speed limit
• On-screen visualization of detections (optional but preferred)
If a violation occurs, the system must log the vehicle automatically. Additionally, the system should provide a cloud dashboard where users can:
• Monitor live video feeds &
• View and filter violation logs
• Access basic statistics (e.g., daily/weekly violation counts)
This dashboard can be web-based and simple but should make the system monitorable remotely, increasing its value and usability.
Core Requirements:
• Real-time vehicle detection using a USB camera
• Detect and track vehicles at Point A "Entry" to Point B "Exit"
• Measure timestamp differences to calculate average speed
• Compare calculated speed against a configurable speed limit
• Automatically log violations with time, captured frame, and vehicle tracking ID
• Stream live video to the web-based cloud dashboard
• Ability to run continuously on Ubuntu
• Adjust configured speed limit
• On-screen visualization of detections (optional but preferred)
Related categories:
Python
Linux
C++ Programming
OpenCV
Tensorflow
Pytorch
NumPy
Computer Vision
Automatic Number Plate Recognition (ANPR)
YOLO