Identification of road surface conditions using IoT sensors and machine learning

Jin Ren Ng, Jan Shao Wong, Vik Tor Goh*, Wen Jiun Yap, Timothy Tzen Vun Yap, Hu Ng

*Corresponding author for this work

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

39 Citations (Scopus)


The objective of this research is to collect and analyse road surface conditions in Malaysia using Internet-of-Things (IoT) sensors, together with the development of a machine learning model that can identify these conditions. This allows for the facilitation of low cost data acquisition and informed decision making in helping local authorities with repair and resource allocation. The conditions considered in this study include smooth surfaces, uneven surfaces, potholes, speed bumps, and rumble strips. Statistical features such as minimum, maximum, standard deviation, median, average, skewness, and kurtosis are considered, both time and frequency domain forms. Selection of features is performed using Ranker, Greedy Algorithm and Particle Swarm Optimisation (PSO), followed by classification using k-Nearest Neighbour (k-NN), Random Forest (RF), and Support Vector Machine (SVM) with linear and polynomial kernels. The model is able to achieve an accuracy of 99%, underlining the effectiveness of the model to identify these conditions.

Original languageEnglish
Title of host publicationComputational Science and Technology
EditorsRayner Alfred, Ag Asri Ag Ibrahim, Yuto Lim, Patricia Anthony
Number of pages10
ISBN (Electronic)9789811326226
ISBN (Print)9789811326219
Publication statusPublished - 2019
Event5th International Conference on Computational Science and Technology 2018 - Kota Kinabalu, Malaysia
Duration: 29 Aug 201830 Aug 2018

Publication series

NameLecture Notes in Electrical Engineering
ISSN (Print)1876-1100
ISSN (Electronic)1876-1119


Conference5th International Conference on Computational Science and Technology 2018
Abbreviated titleICCST 2018
CityKota Kinabalu


  • Classification
  • Machine learning
  • Road surface conditions

ASJC Scopus subject areas

  • Industrial and Manufacturing Engineering


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