No Helmet Detection – Triple Riding Detection
Video Analytics No Helmet Detection and Triple Riding Detection System (TRDS). In real-time it detects those people who are riding triple seats on the two-wheelers. The ultra-powerful technology not only captures the number plate of a two-wheeler with Automatic Number Plate Detection (ANPR) but can also generate an alert with the evidence video.
Two-wheelers accounted for the highest share of total road crashes. Video Analytics Surveillance No Helmet Detection & Triple Riding Detection commit to reducing road accidents and enforcing traffic disciplines amongst citizens.
NO HELMET DETECTION SYSTEM
No Helmet Detection System (NHDS) tracks in real-time two-wheeler riders who are violating traffic laws by not wearing helmets while driving on the road. The solution is intelligent enough to detect riders who pretend to wear helmets by using caps, scarfs, etc. to cover their head. The system is intelligent enough to detect various types of standard helmets to filter out and detect to-standard helmets.
TRIPLE RIDING DETECTION
Triple Riding Detection System (TRDS) detects in real-time those who are doing triple riding on 2-wheelers. The powerful technology not only captures the number plate of the 2-wheeler with ANPR but can also generate an alert with the evidence video. On detection of a triple ride, the system generates events, stores them, and allows their retrieval when required for analysis later on.
Once a violation is detected, an evidentiary image is recorded with a time stamp and vehicle number. The detected event is sent to another application installed at Central Control Room (CCR), and a challan/ ticket is generated. Challan/Ticket generation also involves integration with the RTO/ vehicle owner database to collect the name, address, and other details of the vehicle owner.
AUTOMATIC NUMBER PLATE RECOGNITION SYSTEM
The automatic Number Plate Recognition (ANPR) system automatically captures the license plates of any vehicle(s) in the field of view (FOV) of a camera and stores them in the database, so that details of the vehicles are available at any later point in time along with related video footage.
If there is more than one vehicle in the camera FOV, then all of them are independently processed and their license plates are recognized irrespective of the type of vehicle – private car, taxi, bus, truck, auto rickshaw/ tuk-tuk, motorcycle, etc.
The system supports both single-lane as well as multiple-lane vehicle and license plate detection. It is agnostic to the background and foreground colors of license plates