TY - GEN
T1 - Development of Specialized IoT Cloud Platform for Railway Track Condition Monitoring
AU - Memon, Tarique Rafique
AU - Din Memon, Tayab
AU - Chowdhry, Bhawani Shankar
AU - Kalwar, Imtiaz H.
AU - Mal, Khakoo
N1 - Publisher Copyright:
© 2021 IEEE.
PY - 2021
Y1 - 2021
N2 - With the increase of railway transportation in the world and the continuous running of trains, railway tracks are suffering from various defects such as squats, spalling, and corrugation. These defects if ignored may create a dangerous situation that escalates to accidents, usually. In this paper, we have developed an IoT enabled web-based cloud system for the fault detection system with the integration of JavaScript, HTML, and PHP programming languages. The proposed system stores the railway track fault locations in a database and with the integration of the JavaScript Application Programming Interface (API) all points are pinned on google maps so that the faults can be located easily from the control room (i.e., headquarter station). In this system, a detection hardware system installed at the railway inspection vehicle should send the fault parameters with time and coordinates which pinpoint the multiple defected locations on maps for Railway Track condition monitoring. Therefore, wherever, a defect is diagnosed the system will send the location using GPS coordinates and Global System for Mobile Communication (GSM) along with sensor data to this dedicated cloud server. The proposed system is tested with Cross-platform, Apache, MySQL, PHP, and Perl (XAMPP) and can be used to point out multiple defects. Any hardware with GPS can send data on this system for multiple-marker pinpoint locations. The proposed system is very useful for an automatic fault alert system in the railway track condition monitoring perspective.
AB - With the increase of railway transportation in the world and the continuous running of trains, railway tracks are suffering from various defects such as squats, spalling, and corrugation. These defects if ignored may create a dangerous situation that escalates to accidents, usually. In this paper, we have developed an IoT enabled web-based cloud system for the fault detection system with the integration of JavaScript, HTML, and PHP programming languages. The proposed system stores the railway track fault locations in a database and with the integration of the JavaScript Application Programming Interface (API) all points are pinned on google maps so that the faults can be located easily from the control room (i.e., headquarter station). In this system, a detection hardware system installed at the railway inspection vehicle should send the fault parameters with time and coordinates which pinpoint the multiple defected locations on maps for Railway Track condition monitoring. Therefore, wherever, a defect is diagnosed the system will send the location using GPS coordinates and Global System for Mobile Communication (GSM) along with sensor data to this dedicated cloud server. The proposed system is tested with Cross-platform, Apache, MySQL, PHP, and Perl (XAMPP) and can be used to point out multiple defects. Any hardware with GPS can send data on this system for multiple-marker pinpoint locations. The proposed system is very useful for an automatic fault alert system in the railway track condition monitoring perspective.
KW - Google map API
KW - JavaScript
KW - MYSQL
KW - PHP and Accelerometer
KW - Railway track condition monitoring
UR - http://www.scopus.com/inward/record.url?scp=85124319745&partnerID=8YFLogxK
U2 - 10.1109/ICRAI54018.2021.9651411
DO - 10.1109/ICRAI54018.2021.9651411
M3 - Conference contribution
AN - SCOPUS:85124319745
T3 - 2021 International Conference on Robotics and Automation in Industry, ICRAI 2021
BT - 2021 International Conference on Robotics and Automation in Industry, ICRAI 2021
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 4th International Conference on Robotics and Automation in Industry, ICRAI 2021
Y2 - 26 October 2021 through 27 October 2021
ER -