Subway rail transit monitoring by built-in sensor platform of smartphone
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 rail transit. Field tests are conducted to verify the accuracy of 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 location is established, and the distance between adjacent stations of the 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 tunnel environment. It is also found that using the proposed vehicle-positioning method, the integral error of displacement of a single section can be controlled to within 5%. This study can make full use of and offer a smart and eco-friendly approach for human life in the field of intelligent transportation systems.
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