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Online Model for Suspension Faults Diagnostics Using IoT and Analytics

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International Conference on Advanced Computing Networking and Informatics

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 870))

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.

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Author information

Authors and Affiliations

  1. Department of Electronics and Communication Engineering, Amrita School of Engineering, Amrita Vishwa Vidyapeetham, Coimbatore, India

    Pravin Kokane

  2. Department of Computer Science and Engineering, Amrita School of Engineering, Amrita Vishwa Vidyapeetham, Coimbatore, India

    P. Bagavathi Sivakumar

Authors
  1. Pravin Kokane
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  2. P. Bagavathi Sivakumar
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Corresponding author

Correspondence to P. Bagavathi Sivakumar .

Editor information

Editors and Affiliations

  1. Medi-Caps University, Indore, Madhya Pradesh, India

    Raj Kamal

  2. Loughborough University, Loughborough, UK

    Michael Henshaw

  3. Medi-Caps Group of Institutions, Indore, Madhya Pradesh, India

    Pramod S. Nair

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© 2019 Springer Nature Singapore Pte Ltd.

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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. Springer, Singapore. https://doi.org/10.1007/978-981-13-2673-8_17

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  • DOI: https://doi.org/10.1007/978-981-13-2673-8_17

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-13-2672-1

  • Online ISBN: 978-981-13-2673-8

  • eBook Packages: EngineeringEngineering (R0)

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