Low accuracy of the existing license plate identification system has resulted
in significant manual effort on the part of Traffic Police officers. How
might we improve the accuracy of identifying license plate details, so
that Traffic Police officers can do other higher value-added work?
RoadBuster uses Optical Character Recognition (OCR) to identify licence
plate numbers and reduce the time taken for Traffic Police officers to
confirm red light and speeding offences, making the roads safer for everyone.
The prototype is a back-end admin interface and dashboard for officers
to confirm licence plate details from traffic camera images.
See our slides here:
We have done a preliminary check with Traffic Police, and have gotten
their feedback that the prototype, if it works as intended, will allow
them to save time and manpower. We are pending a wider trial with Traffic
Roadbuster was also shared at Demo Day during Hackathon 2024, and another
agency has expressed interest in collaborating with us.
Further potential developments on Roadbuster include:
Refining the existing image processing workflow with Traffic Police
Improving the model with more images
API integration with existing systems
Other than Roadbuster, Traffic Police is keen to work with us on two further
Shortening the current waiting time to send out notices, which currently
Streamlining the appeals process
We’re in talks with Traffic Police to develop these ideas further.
Roadbuster was brought to you by the ERP X team, a multi-disciplinary
team of engineers, designers, product ops and policy officers.
Left to right: Daryl Chan, Justyn Oh, Stephanie Siow, Blake Gong, Christabel
Png, Mike Chen, Samuel Koh (not in picture)