Design and implementation of a fire detection and control system for automobiles using fuzzy logic

Robert Sowah, Kwame O. Ampadu, Abdul Ofoli, Koudjo Koumadi, Godfrey A. Mills, Joseph Nortey

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

38 Citations (Scopus)

Abstract

The immense benefits of fire in road transport cannot be overemphasized. However more than two thousand vehicles are damaged by unwanted fire on a daily basis. On a global scale, incendiary losses to the automobile and insurance industries have ran into billions of dollars over the last decade. A not-so-distant contributory factor is the lack of a sophisticated fire safety system on the automobile. This has been addressed by designing and implementing fuzzy logic control system with feedback over an Arduino micro-controller system. The automatic system consisting of flame sensors, temperature sensors, smoke sensors and a re-engineered mobile carbon dioxide air-conditioning unit was tested on a medium sized physical car. Results show that the automobile fire detection and control system devoid of false alarms, detects and extinguishes fire under 20 seconds. An innovative, very promising solution module for hardware implementation in fire detection and control for automobiles has been developed by using new algorithms and fuzzy logic.

Original languageEnglish
Title of host publicationIEEE Industry Application Society, 52nd Annual Meeting
Subtitle of host publicationIAS 2016
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781467386715
DOIs
Publication statusPublished - 2 Nov 2016
Event52nd Annual Meeting on IEEE Industry Application Society, IAS 2016 - Portland
Duration: 2 Oct 20166 Oct 2016

Publication series

NameIEEE Industry Application Society, 52nd Annual Meeting: IAS 2016

Conference

Conference52nd Annual Meeting on IEEE Industry Application Society, IAS 2016
Country/TerritoryUnited States
CityPortland
Period2/10/166/10/16

Keywords

  • Data fusion
  • air-conditioning
  • fire detection
  • fuzzy logic control
  • reengineering

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