SMART LAB: Scalable Multi-disciplinary AI-enabled Real-time Training Laboratories for Healthcare Education

SMART LAB: Scalable Multi-disciplinary AI-enabled Real-time Training Laboratories for Healthcare Education

Traditional healthcare education has long grappled with a persistent paradox: the mastery of hands-on skills require intensive, one-on-one supervision, yet the reality of modern academia involves burgeoning student cohorts and overstretched faculty. For students in medical laboratory sciences or radiography, the path to proficiency is often hindered by limited access to expert feedback and the logistical hurdles of high-stakes clinical environments. These bottlenecks can lead to inconsistent learning outcomes, where the nuances of a precise pipetting technique or the critical alignment of patient positioning are missed in the absence of a watchful eye.

To bridge this gap, Prof. Helen LAW, Associate Head and Associate Professor, Department of Health Technology and Informatics, has introduced SMART LAB –a transformative, AI-enabled ecosystem across four core healthcare disciplines. By outfitting laboratories with multi-angle camera systems and integrated hardware, the project captures every movement and command within the training space. Whether it is the delicate coordination of a medical imaging procedure or the high-pressure communication of a crisis management team, advanced computer vision and natural language processing models act as a tireless digital mentor. This system provides students with immediate, objective feedback on safety protocols and procedural accuracy, allowing them to refine their techniques in real time and at a personalised pace that traditional schedules simply cannot accommodate.

At the heart of this initiative is a central annotated database that serves as both the engine for AI refinement and a comprehensive progress map for learners. By involving over 800 healthcare students in pilot studies, the project ensures that the integration of AI is not merely a technological addition but a pedagogically sound evolution. The result is a scalable model that alleviates the strain on clinical placements and human resources, ensuring that even as the class size grows, the quality of individualised instruction remains uncompromised.

The implications of SMART LAB extend far beyond the laboratory walls, offering a modular, open-source framework ready for adaptation across diverse academic fields. This visionary approach serves as a cornerstone of PolyU Education 4.0, manifesting an AI-empowered, student-centred model that redefines the educational landscape. By fostering a generation of technologically savvy healthcare professionals who are as confident in their digital literacy as they are in their clinical skills, the University reinforces its standing as a world-class innovative institution dedicated to the future of societal wellbeing.

This project is awarded under the Teaching Development Grant 2025–28 in the Theme-based Projects category (Individual Project).