Title: Design of IoT aided prevention and control platform for major public health emergencies

Authors: Yanfang Ma; Chunmeng Lu; Cunhong Li

Addresses: College of Information Engineering, Jiaozuo University, Jiaozuo, 454000, China ' College of Information Engineering, Jiaozuo University, Jiaozuo, 454000, China ' College of Information Engineering, Jiaozuo University, Jiaozuo, 454000, China

Abstract: In view of the low traceability rate of traditional major public health emergency prevention and control platform, a new type of major public health emergency prevention and control platform based on Internet of things is designed. The information of major public health emergencies is collected, and the data is transmitted through the Internet of things. Existing algorithms take more time and memory to process IoT data. The federal learning neural network is used to calculate the risk of major public health emergencies, analyse the data, and visually process the data to determine the type of prevention and control, so as to realise the auxiliary prevention and control of major public health emergencies through the Internet of things. The experimental results show that the traceability rate of the experimental group is significantly higher than that of the control group, which can solve the problem of low traceability rate of traditional prevention and control platform. The percentage of prevention and control is 98.24% which is higher in making public health awareness.

Keywords: auxiliary prevention and control platform; internet of things; major public health emergencies; federated learning neural networks; visual processing.

DOI: 10.1504/IJNT.2023.134035

International Journal of Nanotechnology, 2023 Vol.20 No.5/6/7/8/9/10, pp.731 - 743

Received: 16 Nov 2021
Accepted: 21 Jan 2022
Published online: 10 Oct 2023 *

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