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CLC number: U216.3

On-line Access: 2020-08-10

Received: 2019-05-13

Revision Accepted: 2020-01-03

Crosschecked: 2020-06-19

Cited: 0

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Citations:  Bibtex RefMan EndNote GB/T7714


Jian-li Cong


Yuan Wang


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Frontiers of Information Technology & Electronic Engineering  2020 Vol.21 No.8 P.1226-1238


Subway rail transit monitoring by built-in sensor platform of smartphone

Author(s):  Jian-li Cong, Ming-yuan Gao, Yuan Wang, Rong Chen, Ping Wang

Affiliation(s):  School of Civil Engineering, Southwest Jiaotong University, Chengdu 610031, China; more

Corresponding email(s):   jlcong2019@my.swjtu.edu.cn, gaomingyuan@swu.edu.cn, wangy39@sustech.edu.cn, chenrong@home.swjtu.edu.cn, wping@home.swjtu.edu.cn

Key Words:  Acceleration signals, Smart monitoring, Embedded sensors, Smartphones, Subway

Jian-li Cong, Ming-yuan Gao, Yuan Wang, Rong Chen, Ping Wang. Subway rail transit monitoring by built-in sensor platform of smartphone[J]. Frontiers of Information Technology & Electronic Engineering, 2020, 21(8): 1226-1238.

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Smartphone, as a smart device with multiple built-in sensors, can be used for collecting information (e.g., vibration and location). In this paper, we propose an approach for using the smartphone as a sensing platform to obtain real-time data on vehicle acceleration, velocity, and location through the development of the corresponding application software and thereby achieve the green concept based monitoring of the track condition during subway rail transit. Field tests are conducted to verify the accuracy of smartphones in terms of the obtained data’s standard deviation (SD), Sperling index (SI), and International Organization for Standardization (ISO)-2631 weighted acceleration index (WAI). A vehicle-positioning method, together with the coordinate alignment algorithm for a Global Positioning System (GPS) free tunnel environment, is proposed. Using the time-domain integration method, the relationship between the longitudinal acceleration of a vehicle and the subway location is established, and the distance between adjacent stations of the subway is calculated and compared with the actual values. The effectiveness of the method is verified, and it is confirmed that this approach can be used in the GPS-free subway tunnel environment. It is also found that using the proposed vehicle-positioning method, the integral error of displacement of a single subway section can be controlled to within 5%. This study can make full use of smartphones and offer a smart and eco-friendly approach for human life in the field of intelligent transportation systems.





Darkslateblue:Affiliate; Royal Blue:Author; Turquoise:Article


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