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IoT-Based Onboard Prognostic Health Evaluation System for Automotive Suspensions

EasyChair Preprint no. 10065

3 pagesDate: May 10, 2023


We consider the problem of developing functionally safe suspension components and sub-assemblies for automotive systems. Safety is prominent in all modes of transportation. Failure of suspension components represents a significant reason for car accidents. We develop an IoT-based continuous monitoring solution to predict the impending degradation of suspension through real-time detection and analysis of abnormal vibrations in these parts in real-time. Our system includes onboard sensors and computation modules for real-time detection, together with an offline analyzer in the cloud for the refinement of prediction accuracy through the lifetime of the part. We present a prototype of the system and discuss the architecture and implementation concerns involved in its design.

Keyphrases: Automotive, IoT, suspension

BibTeX entry
BibTeX does not have the right entry for preprints. This is a hack for producing the correct reference:
  author = {Bhagawat Baanav Yedla Ravi and Md Rafiul Kabir and Sumaiya Afroz Mila and Sandip Ray},
  title = {IoT-Based Onboard Prognostic Health Evaluation System for Automotive Suspensions},
  howpublished = {EasyChair Preprint no. 10065},

  year = {EasyChair, 2023}}
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