Design and Implementation of Real-Time Wearable Devices for a Safety-Critical Track Warning System

Author(s):  
Andrea Ceccarelli ◽  
Andrea Bondavalli ◽  
Joao Figueiras ◽  
Boris Malinowsky ◽  
Jurij Wakula ◽  
...  
2011 ◽  
Vol 30 (4) ◽  
pp. 945-948
Author(s):  
Shao-hua Liu ◽  
Zhi-hui Xiong ◽  
Wei-dong Bao ◽  
Mao-jun Zhang

Author(s):  
Jun-hua Chen ◽  
Da-hu Wang ◽  
Cun-yuan Sun

Objective: This study focused on the application of wearable technology in the safety monitoring and early warning for subway construction workers. Methods: With the help of real-time video surveillance and RFID positioning which was applied in the construction has realized the real-time monitoring and early warning of on-site construction to a certain extent, but there are still some problems. Real-time video surveillance technology relies on monitoring equipment, while the location of the equipment is fixed, so it is difficult to meet the full coverage of the construction site. However, wearable technologies can solve this problem, they have outstanding performance in collecting workers’ information, especially physiological state data and positioning data. Meanwhile, wearable technology has no impact on work and is not subject to the inference of dynamic environment. Results and conclusion: The first time the system applied to subway construction was a great success. During the construction of the station, the number of occurrences of safety warnings was 43 times, but the number of occurrences of safety accidents was 0, which showed that the safety monitoring and early warning system played a significant role and worked out perfectly.


Author(s):  
Wenqiang Chen ◽  
Lin Chen ◽  
Meiyi Ma ◽  
Farshid Salemi Parizi ◽  
Shwetak Patel ◽  
...  

Wearable devices, such as smartwatches and head-mounted devices (HMD), demand new input devices for a natural, subtle, and easy-to-use way to input commands and text. In this paper, we propose and investigate ViFin, a new technique for input commands and text entry, which harness finger movement induced vibration to track continuous micro finger-level writing with a commodity smartwatch. Inspired by the recurrent neural aligner and transfer learning, ViFin recognizes continuous finger writing, works across different users, and achieves an accuracy of 90% and 91% for recognizing numbers and letters, respectively. We quantify our approach's accuracy through real-time system experiments in different arm positions, writing speeds, and smartwatch position displacements. Finally, a real-time writing system and two user studies on real-world tasks are implemented and assessed.


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