Abstract

<p>An access/entry control system usually consists of many subsystems. These subsystems have different Application Programming Interfaces (APIs), but they need to be integrated and interacted well. Without a good integrated platform, the communications between subsystems will be very complicated. In addition, except user name and password, Radio Frequency Identification (RFID), and the human’s biometrics (e.g., fingerprint and face) are used to identify users. Wireless Local Area Network (WLAN), mobile communications (e.g. 4G/5G) and Bluetooth are adopted as the remote access technologies. In addition, with the COVID-19 pandemic, public health and personal safety are getting more concerns. People are required to wear personal protective equipment (PPE) in some special areas (e.g., barns and factories) to ensure the personal healthy and food’s safety. To identify the user and detect whether the PPE is correctly worn, this paper proposes an access/entry control system by using an Internet of Things (IoT) platform. Through the proposed IoT system architecture, different identification mechanisms and communication technologies can be adopted, and the messages can be exchanged between two mechanisms. This paper elaborates the architecture design of the IoT platform and discusses the implementation/deployment issues of the PPE detection by using machine learning mechanisms.</p> <p> </p>

Full Text
Published version (Free)

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call