“Digital Twin” Intelligent Management of Large Medical Equipment Based On Internet of Things Platform

Background

The implementation of China's Healthy China strategy and the development of new medical infrastructure have led to the widespread deployment of various medical equipment across all levels of healthcare institutions. These instruments serve critical functions such as health checkups, disease screening, diagnosis, treatment, and therapeutic evaluation, forming the essential backbone for a hospital's normal operation. Nevertheless, the challenge persists in transitioning from Breakdown Maintenance to Prejudgment due to the vast and diverse array of medical equipment.

Method

Utilizing Internet of Things (IoT) digital twin technology, a comprehensive evaluation management system for large medical equipment is established. The system parses operational logs to fully reconstruct the dynamic usage patterns of the equipment. Standard data interfaces are interconnected with existing information systems to create a real, objective, automated, and normalized platform for analyzing equipment operation, usage, quality control, and efficiency data. This platform facilitates equipment monitoring, early warning, quality control management, and decision-making applications.

Result

Real-time remote monitoring of equipment operating status is achieved 24/7, providing immediate awareness of current equipment states such as shutdown, standby, and downtime. This enhances the quality and efficiency of equipment operation and maintenance. Different levels of risk warnings are pushed, guiding biomedical engineers to take timely and effective measures. Predictive estimation of the lifespan of core components enables proactive, foresighted equipment maintenance management, effectively controlling maintenance costs. Real-time remote monitoring of core parameters allows for efficient intelligent inspections, enhancing maintenance efficiency and reducing downtime.

Conclusion

The system enables real-time remote monitoring of medical equipment, achieving dynamic and refined management. It enhances operational quality, efficiency, and decision-making capabilities by integrating IoT and cloud platforms into the management and early warning system for major medical equipment in large hospitals.