Real-Time Vehicle Detection, Tracking, Number Plate Detection, and Speed Estimation using Raspberry Pi HQ Camera
As we are going for a walk, escorting our kids to school, or going to our work in the morning, we’ve all experienced unsafe, fast-moving vehicles operated by inattentive drivers that nearly mow us down. We feel almost powerless. These drivers disregard speed limits, crosswalk areas, school zones, and “children at play” signs altogether. When there is a speed bump, they speed up almost as if they are trying to catch some air!
But what if we could catch these reckless neighborhood miscreants in action and provide video evidence of the vehicle, speed, number plate, and time of day to authorities?
So here comes the technology of camera in action.
Hello Everyone, my name is Akshita Gupta and for my entry, I will be creating a VEHICLE-X project that will be a real-time vehicle detection, tracking, number plate detection as well as speed estimation.
To build the VEHICLE-X, I will use the following components
- Raspberry Pi 4
- 7" touch display for a proper preview
- Raspberry HQ Camera
Implementation
- Pi will detect vehicles in video using a MobileNet SSD and Intel Movidius Neural Compute Stick (NCS)
- Tracks the vehicles
- Estimates the speed along with the number plate of a vehicle and stores the evidence in the cloud.
Advantages
- The smart system can help track people, vehicles traveling from Point A to Point B.
- The solution encompasses a mechanism by which law enforcement agencies can track if there is a deviation from a specific route, the speed of the vehicles can also be detected.
- This solution will ensure that vehicles do not cross a speed limit to minimize accidents with animals, who cross the road, especially during monsoon.
- For nighttime use, we may need infrared cameras and infrared lights and/or adjustments to our camera parameters.
This is a small image of the solution which I have performed using a pre-recorded video and have used only Open Cv for it without a pi camera.
Vehicle-x have a look at this gif
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