Abstract
Sudden public health and medical education events have tested the stability of society to a great extent. The government need to strengthen capacity building, make use of system dynamic supervision, warn public health events in advance, and minimize the impact scope and related harmfulness of events. This not only facilitates the rapid mobilization of resources by the later government but also facilitates the comprehensive and detailed deployment and arrangement of decision-makers. As we all know, the Internet of Things is used by all walks of life because of its outstanding advantages of low power consumption, low cost, and wide range. Therefore, this article takes the Internet of Things as the technical basis of the system. According to the actual demand and resource design, it includes two system functions: detection and early warning. The results show that: (1) considering the practical principle, the evaluation system interface found that the scores of font size and color style are all below 80%, which need to be optimized and adjusted; the overall interface basically meets the needs of users. (2) The throughput of the three methods is different. The CoAP-E has superior throughput. (3) With the increase in packet loss rate, the request success rate of the CoAP method decreases in a “drop” manner. The CoAP-E method in this article has the best performance. (4) When the packet loss rate is 25%, the network adaptability of this method is the strongest, and the retransmission rate is less than 18%; the CoAP method is as high as 35%. (5) When the number of concurrent requests is less than 2500, there is no obvious difference between the three methods; the optimal performance of the dynamic load balancing method is 10.1 s. (6) The system comprehensively considers various factors of five site selections. The highest comprehensive score of Final Site, 5 is 8.7, which can be used as the resettlement place of emergency rescue facilities. This article starts from the characteristics and needs of public emergencies, and the final set of the system runs well. It can quickly reflect public health emergencies and medical education events. Use the most effective system functions for risk control, and maximize the analysis, organization, and coordination of events. The follow-up optimization of system details needs to be studied.
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