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Article type: Research Article
Authors: Zhang, Huitao | Yang, Lib; * | Sun, Jingwua | Liu, Zhiguoa
Affiliations: [a] School of Computer Science, Shijiazhuang University, Shijiazhuang, Hebei, China | [b] School of Electrical and Mechanical, Shijiazhuang University, Shijiazhuang, Hebei, China
Correspondence: [*] Corresponding author: Li Yang, School of Electrical and Mechanical, Shijiazhuang University, Shijiazhuang, Hebei 050035, China. E-mail: 1102027@sjzc.edu.cn.
Abstract: According to the current management status of laboratories, an open laboratory management system based on 2DPCA face recognition technology is developed. Within this system, the environment of the lab is monitored from multiple aspects such as temperature and humidity, light intensity, PM2.5. The ZigBee module is adopted to realize the check-in and access control, which can automatically record the attendance of laboratory personnel and save the inconvenience of recording information manually. 2DPCA face recognition technology is used to ensure the security and theft prevention of the laboratory. The nodes composed of IoT, various sensors and microcontrollers help with the collection, transmission and processing of data between modules. Simultaneously, the IoT website is developed to record and display the environmental information of the lab, and the information will be published to the public network in real time through the ipv6 web server, thus allowing the users to view the usage of the work station through the net page on their cell phones. The innovation of this system design lies in the involvement of 2DPCA face recognition technology, which not only ensures the laboratory safety but also solves the problem of students not being able to enter due to the dim lighting and low resolution in the evening. Besides, the 2DPCA technology’ ability to meet the demand of open laboratory management system is verified by the simulation and experimental verification.
Keywords: Internet of things technology, ZigBee, open laboratory, information collection, 2DPCA
DOI: 10.3233/JCM-226180
Journal: Journal of Computational Methods in Sciences and Engineering, vol. 22, no. 5, pp. 1453-1459, 2022
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