IoT-Based Onboard Prognostic Health Evaluation System for Automotive Suspensions

EasyChair Preprint 10065

Abstract

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

@booklet{EasyChair:10065,
  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 10065},
  year      = {EasyChair, 2023}}