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Vehicle Remote Health Monitoring and Prognostic Maintenance System
Joint Authors
Saleem, Muhammad Qaiser
Shafi, Uferah
Safi, Asad
Shahid, Ahmad Raza
Ziauddin, Sheikh
Source
Journal of Advanced Transportation
Issue
Vol. 2018, Issue 2018 (31 Dec. 2018), pp.1-10, 10 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2018-01-18
Country of Publication
Egypt
No. of Pages
10
Main Subjects
Abstract EN
In many industries inclusive of automotive vehicle industry, predictive maintenance has become more important.
It is hard to diagnose failure in advance in the vehicle industry because of the limited availability of sensors and some of the designing exertions.
However with the great development in automotive industry, it looks feasible today to analyze sensor’s data along with machine learning techniques for failure prediction.
In this article, an approach is presented for fault prediction of four main subsystems of vehicle, fuel system, ignition system, exhaust system, and cooling system.
Sensor is collected when vehicle is on the move, both in faulty condition (when any failure in specific system has occurred) and in normal condition.
The data is transmitted to the server which analyzes the data.
Interesting patterns are learned using four classifiers, Decision Tree, Support Vector Machine, K Nearest Neighbor, and Random Forest.
These patterns are later used to detect future failures in other vehicles which show the similar behavior.
The approach is produced with the end goal of expanding vehicle up-time and was demonstrated on 70 vehicles of Toyota Corolla type.
Accuracy comparison of all classifiers is performed on the basis of Receiver Operating Characteristics (ROC) curves.
American Psychological Association (APA)
Shafi, Uferah& Safi, Asad& Shahid, Ahmad Raza& Ziauddin, Sheikh& Saleem, Muhammad Qaiser. 2018. Vehicle Remote Health Monitoring and Prognostic Maintenance System. Journal of Advanced Transportation،Vol. 2018, no. 2018, pp.1-10.
https://search.emarefa.net/detail/BIM-1181707
Modern Language Association (MLA)
Shafi, Uferah…[et al.]. Vehicle Remote Health Monitoring and Prognostic Maintenance System. Journal of Advanced Transportation No. 2018 (2018), pp.1-10.
https://search.emarefa.net/detail/BIM-1181707
American Medical Association (AMA)
Shafi, Uferah& Safi, Asad& Shahid, Ahmad Raza& Ziauddin, Sheikh& Saleem, Muhammad Qaiser. Vehicle Remote Health Monitoring and Prognostic Maintenance System. Journal of Advanced Transportation. 2018. Vol. 2018, no. 2018, pp.1-10.
https://search.emarefa.net/detail/BIM-1181707
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1181707