Smart Clothing System With Multiple Sensors Based on Digital Twin Technology

Abstract

Smart clothing is widely used for social safety, health monitoring, and sports monitoring. Current research focuses on the use of various materials or sensors to implement smart clothes with different functions, which implies that the functionality of smart clothing depends on the number of sensors used. For existing smart clothing systems, the greatest attention has been given to information processing algorithms and assembly of sensors, and the interaction between users and systems is ignored. To address this gap, this article considers a multifunctional smart clothing system constructed with several sensors. The smart clothing system proposed in this article mainly consists of a hardware module and a software module. Four types of sensors are incorporated into the hardware module to monitor the heart rate, blood oxygen saturation, body temperature, locating information, and activity states; the software module includes the 3-D model based on the user and the feedback system based on digital twin (DT) technology. The DT technology can map the fundamental states of users in terms of the monitoring indices from the hardware module, and give correspondent advice to users. This novel smart clothing system overcomes the lack of an interaction function in existing methods and introduces DT technology into smart wearable devices for the first time.