Citation

Jamal Mohd Lokman, Eilham Hakimie and Goh, Vik Tor and Choo, Kan Yeep (2022) Driving style recognition using machine learning and smartphone. Faculty of Engineering, Multimedia University, Malaysia. (Unpublished)

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Abstract

Driver behaviour strongly influences road safety and is currently the main contributor to traffic fatalities We propose a machine learning based system that harnesses smartphone sensors to classify driving events and score driver’s performance. The system consists of an app that classifies the driving events using a trained machine learning model, and an algorithm that classifies driver behaviour. This system can accurately classify driving events performed such as safe and aggressive turns, acceleration, braking, and idling.

Item Type:	Other
Subjects:	Q Science > QA Mathematics > QA71-90 Instruments and machines > QA75.5-76.95 Electronic computers. Computer science > QA76.75-76.765 Computer software
Divisions:	Faculty of Engineering (FOE)
Depositing User:	Assoc. Dr Chee Pun Ooi
Date Deposited:	25 Nov 2022 02:43
Last Modified:	25 Nov 2022 02:47
URII:	http://shdl.mmu.edu.my/id/eprint/10633

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