Abstract
Because of coronavirus variants, it is necessary to pay attention to epidemic prevention measures in the cultivation or product packaging processes. In addition to giving customers more peace of mind when using the products, it also ensures that operators wear masks, work clothes and gloves in the work area. This paper constructs an access control system for personnel epidemic prevention monitoring, which uses IoTtalk [1] to connect IoT devices (such as magnetic reed switches, intelligent switches, RFID readers, and RFID wristbands), utilizes RFID for personnel identification, and employs real-time streaming protocol [2] to take the image of IP Cam for YOLOv4 [3] identification program. The identification program detects whether the personnel is indeed wearing the required equipment. If the personnel is not wearing the required device, the detector will trigger a push broadcast system constructed by LINE Notify to inform the operator for processing. Moreover, we developed an emergency entry mechanism; if an emergency happens, the personnel can trigger the emergency door opening by swiping the card multiple times within a specified time. This function allows the person to enter without wearing the required equipment.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
References
Lin, Y.B., Lin, Y.W., Huang, C.M., Chih, C.Y., Lin, P.: IoTtalk: a management platform for reconfigurable sensor devices. IEEE Internet Things J. 4(5), 1552–1562 (2017)
Schulzrinne, H., Rao, A., Lanphier, R.: RFC2326: real time streaming protocol (RTSP) (1998)
Bochkovskiy, A., Wang, C.Y., Liao, H.Y.M.: Yolov4: optimal speed and accuracy of object detection. arXiv preprint arXiv:2004.10934 (2020)
Pavelić, M., Lončarić, Z., Vuković, M., Kušek, M.: Internet of Things cyber security: smart door lock system. In: 2018 International Conference on Smart Systems and Technologies (SST) (2018)
Shanthini, M., Vidya, G., Arun, R.: IoT enhanced smart door locking system. In: 2020 Third International Conference on Smart Systems and Inventive Technology (ICSSIT) (2020)
Pradana, R.D.W., et al.: MIdentification system of personal protective equipment using Convolutional Neural Network (CNN) method. In: 2019 International Symposium on Electronics and Smart Devices (ISESD) (2019)
Adusumalli, H., Kalyani, D., Krishna Sri, R., Pratapteja, M., Prasada Rao, P.V.R.D.: Face mask detection using OpenCV. In: 2021 Third International Conference on Intelligent Communication Technologies and Virtual Mobile Networks (ICICV) (2021)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2022 The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
About this paper
Cite this paper
Jiang, SW., Chen, SY., Chen, WE., Wu, HT. (2022). Development of Personnel Epidemic Prevention Monitoring Access Control System. In: Hsieh, SY., Hung, LJ., Klasing, R., Lee, CW., Peng, SL. (eds) New Trends in Computer Technologies and Applications. ICS 2022. Communications in Computer and Information Science, vol 1723. Springer, Singapore. https://doi.org/10.1007/978-981-19-9582-8_20
Download citation
DOI: https://doi.org/10.1007/978-981-19-9582-8_20
Published:
Publisher Name: Springer, Singapore
Print ISBN: 978-981-19-9581-1
Online ISBN: 978-981-19-9582-8
eBook Packages: Computer ScienceComputer Science (R0)