Deep learning application to roughness classification of road surface conditions through an e-scooter’s ride quality

Deep learning application to roughness classification of road surface conditions through an e-scooter’s ride quality

This study integrates e-scooter vibrational data with smartphone sensors, employing machine learning to evaluate road surfaces. The goal is to classify the road surface roughness level(s) equivalent to the high cycle fatigue threshold(s) experienced by the e-scooter. This information is fundamentall...

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Bibliographic Details
Main Authors: Asher Virin, Lalitphat Khongsomchit, Sakdirat Kaewunruen
Format: Article
Language:English
Published: Frontiers Media S.A. 2025-06-01
Series:Frontiers in Built Environment
Subjects:
machine learning
random forest
extreme gradient boosting
support vector machine
e-scooter
road surface roughness level
Online Access:https://www.frontiersin.org/articles/10.3389/fbuil.2025.1497331/full
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