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The Hong Kong Productivity Council (HKPC) has been recognized for its efforts in promoting smart tunnel inspection and slowing the progression of myopia in children with the Edge-AI powered multi-sensor aerial inspector for the surface of tunnels and the MY-O-Analyzer (My-Optical-Analyzer), co-developed with partners from different sectors, winners of the “Emerging Technology – Industrial Construction” and “IoT – Healthcare” categories respectively.

The recognition was made to honor technology companies that pioneered breakthrough computing products and companies from different industries with the most innovative technology initiatives that impacted their business.

Co-developed with the Hong Kong SAR Government’s Civil Engineering and Development Department (CEDD) and Hyder-Meinhardt Joint Venture, “Edge-AI Powered Multi-Sensor Aerial Inspector for Tunnel Surface” is the first Hong Kong tunnel inspection based on drone and on-board AI processing technologies.

It digitally upgrades tunnel inspection, allowing professional engineers and inspection supervisors to perform smart and safe tunnel lining inspections directly on site. Without setting up substantial working platforms, the system saves a lot of time, reduces the space required for inspection, and improves construction flexibility, safety and efficiency.

Additionally, the system automatically generates digital defect reports for digitizing the entire inspection process, facilitating future asset management. This system has been successfully developed and applied in the T2 main road and Cha Kwo Ling tunnel project (T2 main road project) managed by CESD.

The CESD Eastern Development Office Project Manager said that the development and application of the system is fulfilling a commitment to improving the work process and ensuring industry safety. The successful use of this innovative solution in the Trunk Road T2 project has laid a solid foundation for the use of AI and robotic technology in other tunnel projects.

The tunnel fault dataset collected by the system provides big data for building the AI ​​detection model and serves as a good reference for future infrastructure projects. The system is expected to have enormous potential for extended use in other projects with similar requirements and could inspire other similar innovations, thereby benefiting the sustainable development of Hong Kong’s construction industry as a whole.

Another of HKPC’s winning projects, “MY-O-Analyzer (My-Optical-Analyzer)”, was developed in collaboration with the Department of Ophthalmology and Visual Sciences, Faculty of Medicine, Chinese University of Hong Kong (CUHK ).

The solution collects data on children’s viewing habits and monitors their risk factors for myopia. It was designed to provide a long-term, continuous and personalized myopia monitoring solution for ophthalmologists and the market to help change children’s habits and slow the progression of myopia.

With multiple sensors on the temple components of the smart glasses, this innovation enables automated detection of children’s viewing habits such as reading distance, environmental brightness and darkness, viewing angle status, the head, etc.

Relevant data is collected and stored in an online cloud database by a mobile device via Bluetooth Low Energy. It provides a highly effective solution for parents and ophthalmologists to monitor children’s habits and risk factors for myopia without spending an extended observation period, allowing them to take immediate action to resolve problems. The first version of the product prototype has been completed and will be marketed soon.

Dr. Jason Yam, Associate Professor, Department of Ophthalmology and Visual Sciences, Faculty of Medicine, CUHK said Hong Kong has one of the highest prevalences of myopia in the world. People with high myopia. Unfortunately, during the COVID-19 pandemic, the incidence of myopia increased 2.5 times. This is attributed to a significant decrease in time spent outdoors and an increase in screen time.

MY-O-Analyzer, co-developed by CUHK and HKPC, monitors time spent outside and near work, as well as reading posture. The data helps predict the development of myopia and provides guidance and recommendations to the user on eye usage. It helps to change student behavior for a healthy lifestyle modification.