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Online Model for Suspension Faults Diagnostics Using IoT and Analytics

Publication Type : Conference Paper

Publisher : Springer, Singapore

Source : International Conference on Advanced Computing Networking and Informatics

Url : https://link.springer.com/chapter/10.1007/978-981-13-2673-8_17

Keywords : Faults Fault prediction Machine learning Suspension Fault detection Internet of things

Campus : Coimbatore

School : School of Engineering

Department : Computer Science

Year : 2019

Abstract : Automobile world and technologies are advancing with rapid pace. A lot of resources are pouring into evolution of technologies considering safety, ride, and comfort of passengers. Suspension systems have also changed from just a mechanical assembly to active suspensions with multi-sensors for enhancing the actuations. Detecting faults in the suspension system early and categorizing them not only reduce the maintenance cost but add comfort and safety. In this paper, suspension faults have been studied and investigated. Approaches toward detecting suspension faults have been discussed. Internet of things and analytics-based online model for suspension fault detection are proposed. © Springer Nature Singapore Pte Ltd. 2019.

Cite this Research Publication : Kokane P., Bagavathi Sivakumar P. (2019) Online Model for Suspension Faults Diagnostics Using IoT and Analytics. In: Kamal R., Henshaw M., Nair P. (eds) International Conference on Advanced Computing Networking and Informatics. Advances in Intelligent Systems and Computing, vol 870.

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