Research on performance evaluation system based on online monitoring of Internet of things technology, taking medical imaging equipment as an example. Build the performance management platform of the Internet of things through four aspects: data acquisition, network architecture, CPU, and display output. Select 100 medical imaging devices in clinical use in the hospital and divide them into the control group (50 sets) and the observation group (50 sets) according to different management modes. The control group adopts conventional performance management mode, and the observation group implements Internet of things performance management mode. Compare the differences of equipment operation performance, cost-effectiveness, and service effect between the two groups. The experimental results showed that the equipment utilization rate, operation rate, inspection schedule balance, and technician schedule balance of the observation group were better than those of the control group, and the difference was statistically significant (P < 0.05). The quarterly cost-benefit increase of x-ray examination equipment, CT equipment, Mr equipment, interventional radiotherapy equipment, color ultrasound instrument, and nuclear medicine equipment in the observation group was higher than that in the control group (P < 0.05). The satisfaction of imaging doctors, technicians, engineers, and patients with the equipment service quality of the observation group was higher than that of the control group; the difference was statistically significant (P < 0.05). It is proved that the Internet of things performance management platform of medical imaging equipment can solve the problems of untimely information collection and unscientific scheduling during equipment operation, realize the real-time display and statistics of equipment operation performance, and improve the operation efficiency and service level of medical imaging equipment.
CITATION STYLE
Li, N., Zhang, Q., & Zhao, Z. (2022). Performance Evaluation System Based on Online Monitoring of Internet of Things. Security and Communication Networks, 2022. https://doi.org/10.1155/2022/7745227
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