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Gaussian Model Approach for Identifying Car Engine Malfunctions Based on Embedded Sound System

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

Abstract

One important aspect for car owners is to maintain their vehicles in optimal and well-maintained condition. This includes tasks such as regular oil changes and system inspections. It is crucial for car owners to periodically maintain their vehicles through recommended manufacturer services. By relying solely on scheduled maintenance, it is possible that cars can provide indications of malfunction through engine sounds, which, if ignored without the owner's knowledge, can have negative consequences. Therefore, the identification of car engine issues using deep learning is essential for owners to receive early warnings of malfunctioning vehicles. Hence, the focus is on identifying car malfunctions based on engine sounds, utilizing MFCC and GMM for classifying normal and abnormal engine sounds. Consequently, a practical system is developed that can be implemented using the Raspberry Pi 3 B+ minicomputer.

Original languageEnglish
Title of host publicationSIET 2023 - Proceedings of the 8th International Conference on Sustainable Information Engineering and Technology
PublisherAssociation for Computing Machinery
Pages545-550
Number of pages6
ISBN (Electronic)9798400708503
DOIs
Publication statusPublished - 24 Oct 2023
Event8th International Conference on Sustainable Information Engineering and Technology, SIET 2023 - Bali, Indonesia
Duration: 24 Oct 202325 Oct 2023

Publication series

NameACM International Conference Proceeding Series

Conference

Conference8th International Conference on Sustainable Information Engineering and Technology, SIET 2023
Country/TerritoryIndonesia
CityBali
Period24/10/2325/10/23

Keywords

  • Car Engine
  • Embedded System
  • GMM
  • Malfunctions
  • MFCC
  • Raspberry Pi
  • Sound

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