Driving event recognition using machine learning and smartphones.

ABSTRACT: Background: The lack of real-time monitoring is one of the reasons for the lack of awareness among drivers of their dangerous driving behavior. This work aims to develop a driver profiling system where a smartphone's built-in sensors are used alongside machine learning algorithms to classify different driving behaviors. Methods: We attempt to determine the optimal combination of smartphone sensors such as accelerometer, gyroscope, and GPS in order to develop an accurate machine learning algorithm capable of identifying different driving events (e.g. turning, accelerating, or braking). Results: In our preliminary studies, we encountered some difficulties in obtaining consistent driving events, which had the potential to add "noise" to the observations, thus reducing the

SUBMITTER: Bin Jamal Mohd Lokman EH 

PROVIDER: S-EPMC10111143 | biostudies-literature | 2022

REPOSITORIES: biostudies-literature