research-article

Surfaces categorization based on data collected by bike sensors

Authors:

Gerson V. A. Neto,

Johnattan D. F. Viana,

Reinaldo B. Braga,

Carina T. OliveiraAuthors Info & Claims

EATIS '18: Proceedings of the Euro American Conference on Telematics and Information Systems

Article No.: 32, Pages 1 - 7

https://doi.org/10.1145/3293614.3293625

Published: 12 November 2018 Publication History

Abstract

Today computing is being applied in several areas of knowledge and, when it is used with dynamic technologies as Internet of Things and Artificial Intelligence, can take users experience to a higher level. This work, for example, proposes an application in the context of smart cities to analyze data intelligently, knowing that, the concept of Smart Cities involves a wide range of innovations created for the comfort of the citizens. This paper proposes, through data collection, the recognition of vibratory patterns for the classification of surfaces using machine learning techniques. This is an important issue, as it offers a proposal for greater security of bicycle circulation points with the identification of possible irregularities. The analysis of roads surface quality is possible with the use of an accelerometer to collect data important for the audition of tracks. This data is then classified generating information, classified as patterns (asphalt and pavement surfaces). We have performed field data gathering and applied algorithms calculations to classify data to identify the surface the bicycle ridden, with results in percentages of accuracy up to more than 96%.

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Cited By

Beeking MWies HSteinmaßl MRehrl K(2024)How smooth is your ride? Comparison of sensors and methods for surface quality assessment using IMUsTraffic Safety Research10.55329/guai22757(e000076)Online publication date: 17-Dec-2024
https://doi.org/10.55329/guai2275
Jarry VApparicio PGelb J(2022)Bumpy Rides: An Extensive Accelerometer-Based Cycling Infrastructure SurveyTransportation Research Record: Journal of the Transportation Research Board10.1177/036119812211227772677:3(1217-1229)Online publication date: 20-Sep-2022
https://doi.org/10.1177/03611981221122777
Gadsby AWatkins K(2020)Instrumented bikes and their use in studies on transportation behaviour, safety, and maintenanceTransport Reviews10.1080/01441647.2020.176922740:6(774-795)Online publication date: 25-May-2020
https://doi.org/10.1080/01441647.2020.1769227

Index Terms

Surfaces categorization based on data collected by bike sensors
1. Computing methodologies
  1. Machine learning
    1. Cross-validation
    2. Learning paradigms
      1. Supervised learning
        Supervised learning by classification
      2. Unsupervised learning
        Cluster analysis
2. Information systems
  1. Information systems applications
    1. Decision support systems
      1. Data analytics

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cover image ACM Other conferences

EATIS '18: Proceedings of the Euro American Conference on Telematics and Information Systems

November 2018

297 pages

ISBN:9781450365727

DOI:10.1145/3293614

Co-chairs:
Gabriel Paillard
Federal University of Ceará (UFC), Brazil
,
Francisco Milton Mendes Neto
Rural Federal University of the Semiarid (UFERSA), Brazil
,
Program Chairs:
Emanuel Ferreira Coutinho
Federal University of Ceará (UFC), Brazil
,
Rogério Patrício Chagas do Nascimento
Federal University of Sergipe (UFS), Brazil

Copyright © 2018 ACM.

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EATIS: Euro American Association on Telematics and Information Systems

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New York, NY, United States

Publication History

Published: 12 November 2018

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EATIS '18

EATIS '18: Euro American Conference on Telematics and Information Systems

November 12 - 15, 2018

Fortaleza, Brazil

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Overall Acceptance Rate 17 of 64 submissions, 27%

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Cited By

Beeking MWies HSteinmaßl MRehrl K(2024)How smooth is your ride? Comparison of sensors and methods for surface quality assessment using IMUsTraffic Safety Research10.55329/guai22757(e000076)Online publication date: 17-Dec-2024
https://doi.org/10.55329/guai2275
Jarry VApparicio PGelb J(2022)Bumpy Rides: An Extensive Accelerometer-Based Cycling Infrastructure SurveyTransportation Research Record: Journal of the Transportation Research Board10.1177/036119812211227772677:3(1217-1229)Online publication date: 20-Sep-2022
https://doi.org/10.1177/03611981221122777
Gadsby AWatkins K(2020)Instrumented bikes and their use in studies on transportation behaviour, safety, and maintenanceTransport Reviews10.1080/01441647.2020.176922740:6(774-795)Online publication date: 25-May-2020
https://doi.org/10.1080/01441647.2020.1769227

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