Project Details
Description
This is a Knowledge Transfer Partnership (KTP) project based on vision computing. The project uses video cameras and image recognition software to automatically check whether vehicles entering or leaving a construction site are following the rules. For example, a lorry carrying flammable materials must display the correct safety sign. Instead of a person standing at the gate to check every vehicle — which can cause queues and delays — the system scans the video stream in real time, recognises vehicles and their signs, and instantly flags any that do not comply. This makes the process faster, safer, and more reliable.
The project is led by Edge Hill University (c/o Nonso Nnamoko, Amr Ahmed,& Adhendu Behera) in collaboration with Business Insight 3 (Bi3) - Experts in Human, Vehicle and Object Detection; and has been awarded £279,946 by Innovate UK.
The project is led by Edge Hill University (c/o Nonso Nnamoko, Amr Ahmed,& Adhendu Behera) in collaboration with Business Insight 3 (Bi3) - Experts in Human, Vehicle and Object Detection; and has been awarded £279,946 by Innovate UK.
| Status | Active |
|---|---|
| Effective start/end date | 1/03/24 → 30/11/26 |
Collaborative partners
- Edge Hill University (lead)
- BI3
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