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Research on the Application of RFID Technology in Medical Smart Manufacturing

Published: 20 December 2022 Publication History

Abstract

Nowadays, China's information technology is constantly developing and healthcare smart manufacturing is being rapidly promoted in China. This paper focuses on the development and application of RFID systems and briefly describes the basic theory of RFID. At the same time, this paper presents a systematic study of the current situation of RFID technology in healthcare smart manufacturing and proposes an architecture for RFID TECHNOLOGY in healthcare smart manufacturing. Based on this, this paper presents the future directions and implementation methods of RFID TECHNOLOGY in healthcare smart manufacturing in terms of basic development aspects, development limitations and future development. This is the concept, the solution and the selection of relevant technologies and research methods to realise the interactive sharing of medical information.

References

[1]
Lei Wang, Lin Qiao, Luzhao Xu, Yue Li,Zhonghe Sun. Application of RFID-based disposable consumables supervision scheme design in health emergency work in medical institutions [A] Nanjing Hospital Affiliated to Nanjing Medical University (Nanjing First Hospital), 1674- 1633 (2019) 11-0150-04
[2]
Jing Li, Lei Zhang and Qiang Dong.Design of intelligent management platform for hospital medical equipment with RFID technology【A】.Nanjing Jiangning Hospital, 1009-2552)2021(10-0081-06
[3]
Jialu Gan. Research on the Application of RFID Technology in Medical Equipment Management System【A】.Wuming Hospital Affiliated to Guangxi Medical University, 1003-9767)2020(12-169-03
[4]
Lingling Li. Application of medical equipment information management system in medical equipment management【C】.Department of Equipment, Third People's Hospital of Yancheng City, 1002-2376)2021(03-0061-02
[5]
Baoli Gao, Ran Ge, Dongchen Zhang, Xifeng Liu, Xudong Ma. Design and implementation of RFID technology-based disinfection quality and safety traceability system for multiplexed medical devices [A]. The First Central Hospital of Baoding City, Hebei Province, 1671-7104.2021.02.010
[6]
Xiaohua Liu,Jin Tian and Feng Xu. Application and prospect of RFID positioning technology in medical device management【J】.Medical Engineering Division, Peking University Third Hospital, BeiJing 100191
[7]
Dong Liu, Beibei Jin. Design and implementation of RFID-based medical equipment management system [A]. China Digital Medicine, 1673-7571.2017.06.009
[8]
Wang Dan. Research on the inventory model of medical consumables based on RFID technology [D]. Hefei University of Technology Master's Thesis. April 2017

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      cover image ACM Other conferences
      CSSE '22: Proceedings of the 5th International Conference on Computer Science and Software Engineering
      October 2022
      753 pages
      ISBN:9781450397780
      DOI:10.1145/3569966
      Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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      Association for Computing Machinery

      New York, NY, United States

      Publication History

      Published: 20 December 2022

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      Author Tags

      1. RFID technology
      2. RFID technology in healthcare smart manufacturing
      3. healthcare smart manufacturing

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      • Research-article
      • Research
      • Refereed limited

      Funding Sources

      • Research on Key Technologies of Internet + medical intelligent manufacturing system of Guangxi colleges Young and middle-aged teachers' scientific research basic ability improvement project

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      CSSE 2022

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      Overall Acceptance Rate 33 of 74 submissions, 45%

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