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Prefabricated construction is an emerging construction approach to produce prefabricated components in the off-site factory and transport them to the construction site for assembly, which provides enhanced quality, productivity, and sustainability. On-site assembly is an uncertain and complex stage in prefabrication projects, due to high variability of outside conditions, organization of multi-contractors, and geographic dispersion of activities. Information technology is adopted for the management of precast on-site assembly, such as Internet-of-Things (IoT), Cyber-Physical Internet (CPS), and cloud computing, which generate massive digital twins of construction resources and activities. This tech talk introduces a digital twin-enabled real-time synchronization system (DT-SYNC) with a robotic testbed demonstration for smart prefabricated on-site assembly. On-site resources are converted into Smart Construction Objects (SCOs) attaching with UWB and RFID devices to collect and integrate real-time nD data (e.g. identity, location, cost, and construction progress). Through smart mobile gateway, various on-site resources and activities could be real-timely interoperated with their corresponding digital twins. Cloud-based services are provided for real-time monitoring through high-fidelity virtual models, and robotic control with automatic navigations and alerts. Supported by the cyber-physical visibility and traceability provided by digital twins, a real-time synchronization model is designed to organize and coordinate operations and resources with simplicity and resilience, which guarantees that the appropriate resources are spatiotemporally allocated to the appropriate activities.

Balance ability is human’s basic physiological ability that ensures stable standing and walking. Falls are major threats to the health and independent living of the elderly. 10% of the falls in the elderly are associated with fractures, and some can lead to head injuries and deaths. A highly effective human balance sensor is invented, which can capture high-resolution dynamic pressure distribution under human feet. The variation of the pressure distribution can be used to solve the dynamics of human motion while standing on the balance sensor. The algorithms using artificial intelligence are developed to assess the risk of falling for elderly people to help them prevent falls. Furthermore, this sensor can be used to measure balance ability of athletes, such as weightlifting, golf and gymnastics. In medical diagnosis, balance ability tests can provide important information for diagnostics of neural disease. It can also be used to identify drunk driving.