This project aims to develop and validate a daily-use sensing device to quantify dynamic balance and assess fall risk among older adults in Hong Kong. Artificial intelligence algorithms will be constructed to estimate individualized fall risk from sensor-derived balance parameters, supported by dedicated software and a user-friendly interface. Integrated hardware–software prototypes will be tested in homes and elderly care centres to evaluate feasibility and accuracy. The project further emphasizes dissemination, implementation support, and promotion to facilitate widespread adoption in community and institutional settings.