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Project Database
Project Reference: ITP/064/19LP
Project Title: Video-based Vehicle Surrounding Awareness for Air Cargo Transit Security under All-Weather Conditions
Hosting Institution: LSCM R&D Centre (LSCM)
Abstract: In September 2016, the International Civil Aviation Organization announced a new policy direction to require 100 percent of outgoing air cargo for security screening before loading onto aircrafts starting on July 1, 2021. In Hong Kong, the Civil Aviation Department (CAD) has set up a gradual multi-stage implementation schedule between January 2020 and June 2021 to help the local air cargo industry gear up the screening capability starting with 25 percent of total tonnage. To complement the anticipated gradual increase in screening demand, the CAD introduced the Regulated Air Cargo Screening Facilities (RACSF) Scheme in October 2018 to enable and regulate air cargo screening inside RACSF at off-airport locations. Once air cargoes are screened and secured at RACSF, they will be securely transported to cargo terminal operators (CTO) in airport.
With the setting of having air cargoes being security screened outside the Airport, this seed project attempts to develop a video-based intrusion monitoring and management method to enable an open-top flatbed trailer to provide secure road transportation between two secured premises. The proposed solution offers a one-time capital investment to embed intrusion monitoring capability on a flatbed trailer truck as part of the transportation and logistics services. The solution also saves time and cost to put on consumable-based protective net per air cargo pallet.
The proposed Onboard Secure Transportation Monitoring and Management System solution has 3 core components installing on a trailer truck. The first is a set of camera modules designing and developing for securely installing on an open-top flatbed trailer to provide full visual coverage of all 5 open sides – 4 lateral and top sides.
The second component is a video analytics intrusion detection module being developed using deep learning methods for performing onboard intrusion detection. The third component is a management console module to let a truck driver to manage the intrusion monitoring process during road transportation to communicate with online intrusion monitoring service regarding truck location and any detected intrusion incidents.

Project Coordinator: Dr Dorbin Ng
Approved Funding Amount: HK$2.79M
Project Period: 16 Mar 2020 - 15 Mar 2021
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