This invention provides an intelligent inspection
system and method for chemical laboratories based on digital twins, belonging to the field of
industrial Internet of Things and intelligent safety management technology. The
system includes a physical sensing layer, a digital twin engine layer, an intelligent
processing layer, and an application
interaction layer. The physical sensing layer collects real-
time data of the laboratory environment and equipment through a sensor network; the digital twin engine layer constructs a three-dimensional
virtual model corresponding to the
physical laboratory and displays the data
overlay; the intelligent
processing layer dynamically plans inspection paths and generates alarms based on real-time and historical data through anomaly
pattern recognition and
reinforcement learning; the application
interaction layer provides a
visual inspection interface and safety emergency handling functions. The method includes
data acquisition, 3D driving, intelligent analysis, and
visualization steps. This invention achieves global
perception of
laboratory safety status, intelligent risk early warning, and
automation of the inspection process, improving the real-time performance, accuracy, and intelligence level of
chemical laboratory safety management.