The 5th Asia Exhibition of Innovations and Inventions Hong Kong (AEII)

PD-001R: A New Breakthrough for the Treatment of Neurodegenerative Diseases

Principal Investigator:

Prof. LEE Ming-yuen, Simon, Cally Kwong Mei Wan Professor in Biomedical Sciences and Chinese Medicine Innovation; Chair Professor of Biomedical Sciences, Department of Food Science and Nutrition; Founder, AIM Pharmaceutical International Limited (a PolyU start-up)
Dr ZHAO Chen, Postdoc Fellow, Department of Food Science and Nutrition; Chief Technology Officer, AIM Pharmaceutical International Limited (a PolyU start-up)

 

Intelligent Construction Site Layout Design Platform

Principal Investigator:

Dr WANG Dong, Postdoctoral Fellow, Department of Building and Real Estate; Founder, ICC (Hong Kong) Limited (a PolyU start-up)

This invention is the world’s first generative AI-powered design platform for generating optimal crane and site layouts in construction projects. This innovative tool streamlines the traditionally labour-intensive decision-making process, offering the following significant benefits:
• Accelerates the design process by over 90%
• Lowers collision risks on site by 59%
• Improves operator visibility by 49%
• Enhances crane operation efficiency by 27%
• Reduces module installation degrees by 26%
• Reduces carbon emissions by 800kg 

The platform provides engineers with multiple design channels, including local software, online platforms and CAD plugins. Engineers can further customise their designs based on the real-time visualised effects of the AI-generated solutions. 
This invention is set to revolutionise traditional manual site layout design practices, advancing the construction industry towards enhanced safety, increased productivity and greater sustainability.

 

PolyPi: Edge-AI Empowered Autonomous Robot for Pipeline Inspection and Maintenance

Principal Investigators:

Prof. CAO Jiannong, Vice President (Education), Otto Poon Charitable Foundation Professor in Data Science; Chair Professor of Distributed and Mobile Computing; Founder & Chief Scientist, UbiquiTech Innovations Limited (a PolyU Start-up)
Dr LIANG Zhixuan, Postdoctoral Fellow, Department of Computing; Founder & CEO, UbiquiTech Innovations Limited (a PolyU Start-up)

PolyPi-bot is an edge-AI robot for autonomous inspection and cleaning in confined spaces such as pipelines, ducts, and underground infrastructure. It combines real-time AI defect detection, a deformable structure, and full autonomy. Compressed AI models run directly on the robot, enabling real-time identification of cracks, corrosion, and debris without cloud connectivity. Its adaptive design allows it to traverse complex, curved, or collapsed pipelines with ease. The robot also supports modular cleaning tools for removing sediment and obstructions. With no human intervention required, PolyPi enhances safety in hazardous environments.

 

WING: Wireless Infrastructure for Next-Generation EV Charging

Principal Investigators:

Prof. CHAU Kwok-tong, Chair Professor of Electrical Energy Engineering, Department of Electrical and Electronic Engineering
Prof. LIU Wei Lucian, Assistant Professor, Department of Electrical and Electronic Engineering

 

Intelligent Driving Training and Evaluation System for Heavy-Duty Trucks

Principal Investigators:

Prof. FU Xiaowen, Professor, Head of Department of Industrial and Systems Engineering
Dr TANG Yuk Ming, Senior Lecturer, Department of Industrial and Systems Engineering

The intelligent driving training & evaluation system is an advanced simulator platform designed to revolutionise commercial driver training. Utilising a 6-degree-of-freedom motion platform and a real truck cabin, the system delivers highly realistic driving experiences. Integrated sensors capture real-time data from pedals, steering, and in-cabin depth cameras, enabling precise tracking of driver behaviour, including head, hand, and eye movements. This data-driven approach supports objective assessment, targeted feedback, and rapid skill improvement. The platform enhances safety and efficiency for logistics, emergency services, and fleet operators by providing scalable, repeatable, and cost-effective training. 

BodyMate: A Smart Textile-Based Health Monitoring Vest for Continuous Elderly Vital Sign Detection

Principal Investigator:

Ms Sisi TANG, PhD Candidate, School of Fashion and Textiles; Founder, Leopitorca Global Limited (a PolyU Start-up)

BodyMate is an innovative smart health monitoring vest designed for elderly users, integrating washable, textile-based sensors into comfortable daily wear. Unlike traditional wearables that require manual operation or frequent charging, BodyMate passively monitors vital signs such as heart rate, respiration, body temperature, posture, and fall risk—all without disrupting daily routines. The system is designed for long-term, all-day use, with real-time data transmission to caregivers or healthcare platforms. Ideal for ageing-in-place, chronic disease management, and remote care, BodyMate addresses the growing demand for non-intrusive, elder-friendly health solutions. It combines smart textiles, AI algorithms, and adaptive design to offer a seamless, scalable, and human-centred approach to elderly care. The vest has been developed with support from leading Hong Kong innovation programs and is ready for pilot deployment in smart communities and eldercare settings.

 

ProMuki - Wearable Ultrasound Monitoring and Analysing of Muscle Activities for Fitness, Sports, and Rehabilitation

Principal Investigator:

Prof. ZHENG Yongping, Henry G. Leong Professor in Biomedical Engineering; Chair Professor of Biomedical Engineering, Department of Biomedical Engineering

The invention is a cutting-edge platform that seamlessly integrates advanced technologies to monitor, analyse, interpret and feedback various signals related to muscle activity and performance in real-time. 
By combining data from multiple electrophysiological and biomechanical modalities, ProMuki delivers a comprehensive overview of muscle health and function. It draws clinicians, trainers, or patients’ attention to dynamic muscle functions and immediately adjusts intervention based on the results. 
Its AI-driven sonomyography algorithm instantly quantifies and visualises dynamic muscle architectural changes from ultrasound images, enabling precise tracking of fluctuations in muscle structural parameters and trends. The platform features wireless, palm-sized ultrasound hardware and adaptable transducer designs, ensuring comfort and mobility without compromising human motion. The innovation gains freedom from traditional cable and operator constraints to enhance time-cost-effectiveness and expand assessment possibilities across diverse environments.

 

MetaBridge: A 3D Gaussian Splatting and Blockchain Platform for Cultural Heritage Digital Assetization and Immersive Experience

Principal Investigator:

Prof. NG Hiu Fung, Peter
Assistant Professor, Department of Computing and Department of Rehabilitation Sciences

MetaBridge is an innovative platform that integrates 3D Gaussian Splatting (3DGS) and blockchain authentication to digitise, secure, and share cultural heritage. Using multi-sensor 3D reconstruction, MetaBridge generates highly realistic digital twins of relics and environments. Each asset is secured with blockchain-based certificates, ensuring authenticity, ownership, and traceability. The platform features Web-based editing and one-click deployment to VR, WebXR, or LED immersive systems, enabling creators and institutions to publish cultural experiences without technical barriers easily.
MetaBridge supports flagship projects such as Ferryman Academy, where students and communities co-create VR heritage stories, and the Grand Canal Time-Travel Experience, an immersive cultural tourism showcase. By combining advanced rendering, secure asset management, and accessible dissemination, MetaBridge provides a sustainable model for heritage preservation, immersive education, cultural tourism, and creative industries, positioning Hong Kong as a global leader in cultural innovation and digital economy.

A Proactive Early Warning System for Structural Health Monitoring of Wind Turbine Blades and Towers Based on Finite Element Simulation, Fiber Bragg Grating Sensing and Reinforcement Learning

Principal Investigator:

Prof. YU Changyuan, Professor, Department of Electrical and Electronic Engineering Dr MA Zhiqin, PhD Candidate, Department of Electrical and Electronic Engineering

 

Natural and Eco-friendly External Preservation Technology

Principal Investigator:

Mr HE Shuidong
Doctor Student of Food Science and Management, Department of Food Science and Nutrition; Co-founder, Dr Fresh Biotech Limited (a PolyU start-up)

 

PipeInspect: Cutting-Edge Inspection on water distribution network with Fiber-Optic Positioning

Principal Investigator:

Prof. DING Xiao-li, Chair Professor of Geomatics, Department of Land Surveying and Geo-Informatics

PipeInspect revolutionises the inspection of underground water distribution systems. Traditional approaches rely on periodic checks or reactive repairs, often missing early signs of corrosion, leakage, or contamination. PipeInspect introduces a new paradigm by combining a remotely controlled robotic platform with fibre-optic positioning and sensing, enabling real-time, accurate monitoring over distances of up to 100 km.
The system collects diverse data—high-resolution imagery, acoustic signals, and water quality samples—directly within pipelines. This multi-layered sensing allows a far more detailed and reliable understanding of infrastructure health than conventional techniques. The fibre-optic positioning network ensures precise robot localisation, even in complex pipeline systems, and provides a backup to enhance robustness.
The innovation lies in this fusion of robotics, sensing, and fibre-optics, creating the first scalable system capable of continuous, non-intrusive, and data-driven inspection. By shifting the focus from time-based or emergency-driven interventions to predictive maintenance, PipeInspect enables utilities to act before failures occur. This reduces costs, prevents service interruptions, and directly improves public safety.

ORal-motor Assessment and Rehabilitation mobile App (ORAR App)

Principal Investigator:

Dr WONG Wing Sze, Research Assistant Professor, Department of Language Science and Technology; Clinical Consultant and Co-inventor, Feelings Group Ltd (a PolyU start-up)
Ms YIP Chi Hay, Founder, Feelings Group Ltd (a PolyU start-up)

This invention can enhance the efficiency and accuracy of tongue keypoint detection models for speech therapy by leveraging intelligent and adaptive annotation process, while minimizing the need for manual annotation. It is specifically designed to support patients requiring speech therapy, such as those with aphasia, stroke, or neurodegenerative conditions. By integrating advanced computer vision technologies with an intelligent adaptive annotation process, it offers an efficient and precise solution for tongue keypoint detection and speech therapy. This innovation not only enables high-quality model training with fewer annotated samples but also significantly improves model accuracy and operational efficiency, delivering substantial benefits for both clinical applications and research advancements.

 

Automated freeform eyeglass for instant refractive control

Principal Investigators:

Dr Elie Aymard Jonathan de LESTRANGE-ANGINIEUR, Research Fellow, School of Optometry
Prof. George WOO, Senior Advisor, School of Optometry

This invention is the first freeform eyeglass that automatically adjusts its optical power to correct and prevent refractive errors such as presbyopia and myopia. A slim, ergonomic mechatronic frame drives freeform lenses with silent, sensorless microstepping motors through a precision leadscrew, enabling micrometer level lens translation and low cost adaptive correction. A time of flight sensor continuously measures viewing distance to deliver automated focus changes and interactive biofeedback. Combined with an ocular monitoring app, this eyeglass offers a transformative approach to manage defocus-related visual problems.

 

Non-invasive, Ultrasensitive and Portable Saliva Glucose Sensors

Principal Investigators:

Prof. YAN Feng, Chair Professor of Organic Electronics, Department of Applied Physics; Co-Founder, Intellisense & Cognisense Technology Ltd. (a PolyU start-up)
Dr ZHAO Zeyu, Postdoctoral Fellow, Department of Applied Physics; Co-Founder, Intellisense & Cognisense Technology Ltd.  (a PolyU start-up)