Development and Implementation of An Intelligent Tire Monitoring System

Kuan Lin Chen*, Tian Yi Chen, Li Tzu Yeh, Sheng Jing Yang, Shashank Mishra, Jia Ming Liang, Jen Jee Chen

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

The traditional tire pressure monitoring systems can only determine the condition of tires by detecting tire pressure and temperature, lacking the capability to detect realtime anomalies such as wheel deformation, abnormal tire tread wear, foreign objects adhering to the tire, abnormal vibrations, and skidding. Neglecting such conditions while driving can lead to serious accidents. In this paper, we develop and implement an intelligent tire monitoring system that utilizes inertial sensors mounted on the tires to capture real-time tire operating conditions. By integrating machine learning technology, the system dynamically detects abnormal tire conditions and provides instant notifications and displays through a Bluetooth-enabled application on a smartphone.

Original languageEnglish
Title of host publicationProceedings - 2023 VTS Asia Pacific Wireless Communications Symposium, APWCS 2023
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9798350316803
DOIs
StatePublished - 2023
Event2023 VTS Asia Pacific Wireless Communications Symposium, APWCS 2023 - Tainan City, Taiwan
Duration: 23 Aug 202325 Aug 2023

Publication series

NameProceedings - 2023 VTS Asia Pacific Wireless Communications Symposium, APWCS 2023

Conference

Conference2023 VTS Asia Pacific Wireless Communications Symposium, APWCS 2023
Country/TerritoryTaiwan
CityTainan City
Period23/08/2325/08/23

Keywords

  • Internet of things
  • machine learning
  • tire abnormality
  • wireless network

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