An automated system for Accident Detection

Asad Ali, Mohamad Eid

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Major accidents on highways, freeways and local roads can lead to huge social and economic impacts. Minor accidents may be resolved by the passengers themselves and do not require escorting to hospitals whereas major accidents where airbags are deployed require immediate attention of authorities. Automatic Smart Accident Detection (ASAD) is an auto-detection unit system that immediately notifies an Emergency Contact through a text message when an instant change in acceleration, rotation and an impact force in an end of the vehicle is detected by the system, detailing the location and time of the accident. The idea is that as soon as an accident is detected by the system, the authorities should immediately be notified to prevent further car congestion as well as allow the passengers to be escorted to the hospital in a timely fashion. The system involves the use of fuzzy logic as a decision support built into the smartphone application that analyzes the incoming data from the sensors and makes a decision based on a set of rules. The simulated results show a 98.67% accuracy of the system with failures resulting from the 'gray regions' of the variable values.

Original languageEnglish (US)
Title of host publication2015 IEEE International Instrumentation and Measurement Technology Conference - The "Measurable" of Tomorrow
Subtitle of host publicationProviding a Better Perspective on Complex Systems, I2MTC 2015 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1608-1612
Number of pages5
Volume2015-July
ISBN (Electronic)9781479961139
DOIs
StatePublished - Jan 1 2015
Event2015 IEEE International Instrumentation and Measurement Technology Conference, I2MTC 2015 - Pisa, Italy
Duration: May 11 2015May 14 2015

Other

Other2015 IEEE International Instrumentation and Measurement Technology Conference, I2MTC 2015
CountryItaly
CityPisa
Period5/11/155/14/15

Fingerprint

Accidents
Smartphones
Highway systems
Fuzzy logic
Railroad cars
Economics
Sensors

Keywords

  • Accident
  • Accident response time
  • Crash detection
  • Fuzzy logic

ASJC Scopus subject areas

  • Electrical and Electronic Engineering

Cite this

Ali, A., & Eid, M. (2015). An automated system for Accident Detection. In 2015 IEEE International Instrumentation and Measurement Technology Conference - The "Measurable" of Tomorrow: Providing a Better Perspective on Complex Systems, I2MTC 2015 - Proceedings (Vol. 2015-July, pp. 1608-1612). [7151519] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/I2MTC.2015.7151519

An automated system for Accident Detection. / Ali, Asad; Eid, Mohamad.

2015 IEEE International Instrumentation and Measurement Technology Conference - The "Measurable" of Tomorrow: Providing a Better Perspective on Complex Systems, I2MTC 2015 - Proceedings. Vol. 2015-July Institute of Electrical and Electronics Engineers Inc., 2015. p. 1608-1612 7151519.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Ali, A & Eid, M 2015, An automated system for Accident Detection. in 2015 IEEE International Instrumentation and Measurement Technology Conference - The "Measurable" of Tomorrow: Providing a Better Perspective on Complex Systems, I2MTC 2015 - Proceedings. vol. 2015-July, 7151519, Institute of Electrical and Electronics Engineers Inc., pp. 1608-1612, 2015 IEEE International Instrumentation and Measurement Technology Conference, I2MTC 2015, Pisa, Italy, 5/11/15. https://doi.org/10.1109/I2MTC.2015.7151519
Ali A, Eid M. An automated system for Accident Detection. In 2015 IEEE International Instrumentation and Measurement Technology Conference - The "Measurable" of Tomorrow: Providing a Better Perspective on Complex Systems, I2MTC 2015 - Proceedings. Vol. 2015-July. Institute of Electrical and Electronics Engineers Inc. 2015. p. 1608-1612. 7151519 https://doi.org/10.1109/I2MTC.2015.7151519
Ali, Asad ; Eid, Mohamad. / An automated system for Accident Detection. 2015 IEEE International Instrumentation and Measurement Technology Conference - The "Measurable" of Tomorrow: Providing a Better Perspective on Complex Systems, I2MTC 2015 - Proceedings. Vol. 2015-July Institute of Electrical and Electronics Engineers Inc., 2015. pp. 1608-1612
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