A spatial intelligence enabled framework to digitalize and reconfigure confined workplaces and facilities for improved safety, reliability and resilience

Efficient, reliable and safe workplaces and facilities are crucial to citizens’ well-being. However, growing complexities and interactions among humans, machines and the environments in confined workplaces in facilities, infrastructure workspaces, laboratories, etc. pose grand challenges to ensure their normal operations, safety, reliability and resilience. Of various emerging technologies, spatial intelligence including digital twin and artificial intelligence are regarded as promising enablers to tackle these challenges.Nevertheless, automating confined workplaces and facilities and improving their operational and spatial intelligence is challenging as it is difficult to digitalize heterogeneous entities; sense and communicate ambient environment changes; process and analyze the data; monitor and infer human behaviors and their interactions with machines and environments, not to mention about making adaptive decisions against disruptions and hazards. A holistic framework that guides stakeholders developing or deploying spatial intelligence technology may open up new ways to achieve better safety, reliability and resilience.This research aims to develop a spatial intelligence enabled framework to improve the total efficiency, safety, reliability and resilience of confined construction workplaces and facilities. The framework consists of a digital twin model for representing confined workplaces as a man-machine-environment system (MMES); a service-oriented mechanism to share and exchange digital twin data; a spatial intelligence enabled model to quantify, predict and infer total safety, reliability and resilience; a scenario-based approach to make automation and reconfiguration plans for employing spatial intelligence and digital twin; and a cloud-native prototype system to illustrate how to use the proposed framework to implement spatial intelligence solutions for confined workplace and facility management. The research begins with a series of interviews, case studies and focus group meetings to unveil the obstacles and requirements of applying spatial intelligence to reconfigure and optimize confined construction workplaces and facilities; along with identifyingfeasible strategies and roadmaps for stakeholders to digitalize the MMES and embed intelligence into the system for enhancing safety and reliability. A software reference architecture will then be designed to facilitate the implementation of the proposed framework. Finally, case studies will be conducted to validate the framework and the developed prototype system.The novelty of this investigation lies in the integration of spatial intelligence, digital twin middleware as developed by team, and theories and practices in MMES to delineate the problems, capacities and solutions associated with safety, reliability and resilience of confined workplaces. The findings should provide a solid foundation for the development of a smart, safe and reliable society