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Interpretation, Modeling and Visualization of Crowdsourced Road Condition Data

Research output: Chapter in Book/Report/Conference proceedingChapterScientificpeer-review

Standard

Interpretation, Modeling and Visualization of Crowdsourced Road Condition Data. / Sillberg, Pekka; Saari, Mika; Grönman, Jere; Rantanen, Petri; Kuusisto, Markku.

Intelligent Systems: Theory, Research and Innovation in Applications. ed. / Ricardo Jardim-Goncalves; Vassil Sgurev; Vladimir Jotsov; Janusz Kacprzyk. Springer, 2020. p. 99-119 (Studies in Computational Intelligence; Vol. 864).

Research output: Chapter in Book/Report/Conference proceedingChapterScientificpeer-review

Harvard

Sillberg, P, Saari, M, Grönman, J, Rantanen, P & Kuusisto, M 2020, Interpretation, Modeling and Visualization of Crowdsourced Road Condition Data. in R Jardim-Goncalves, V Sgurev, V Jotsov & J Kacprzyk (eds), Intelligent Systems: Theory, Research and Innovation in Applications. Studies in Computational Intelligence, vol. 864, Springer, pp. 99-119. https://doi.org/10.1007/978-3-030-38704-4_5

APA

Sillberg, P., Saari, M., Grönman, J., Rantanen, P., & Kuusisto, M. (2020). Interpretation, Modeling and Visualization of Crowdsourced Road Condition Data. In R. Jardim-Goncalves, V. Sgurev, V. Jotsov, & J. Kacprzyk (Eds.), Intelligent Systems: Theory, Research and Innovation in Applications (pp. 99-119). (Studies in Computational Intelligence; Vol. 864). Springer. https://doi.org/10.1007/978-3-030-38704-4_5

Vancouver

Sillberg P, Saari M, Grönman J, Rantanen P, Kuusisto M. Interpretation, Modeling and Visualization of Crowdsourced Road Condition Data. In Jardim-Goncalves R, Sgurev V, Jotsov V, Kacprzyk J, editors, Intelligent Systems: Theory, Research and Innovation in Applications. Springer. 2020. p. 99-119. (Studies in Computational Intelligence). https://doi.org/10.1007/978-3-030-38704-4_5

Author

Sillberg, Pekka ; Saari, Mika ; Grönman, Jere ; Rantanen, Petri ; Kuusisto, Markku. / Interpretation, Modeling and Visualization of Crowdsourced Road Condition Data. Intelligent Systems: Theory, Research and Innovation in Applications. editor / Ricardo Jardim-Goncalves ; Vassil Sgurev ; Vladimir Jotsov ; Janusz Kacprzyk. Springer, 2020. pp. 99-119 (Studies in Computational Intelligence).

Bibtex - Download

@inbook{ccf8d1e782a44525b6389e0a6f774b52,
title = "Interpretation, Modeling and Visualization of Crowdsourced Road Condition Data",
abstract = "Nowadays almost everyone has a mobile phone and even the most basic smartphones often come embedded with a variety of sensors. These sensors, in combination with a large user base, offer huge potential in the realization of crowdsourcing applications. The crowdsourcing aspect is of interest especially in situations where users’ everyday actions can generate data usable in more complex scenarios. The research goal in this paper is to introduce a combination of models for data gathering and analysis of the gathered data, enabling effective data processing of large data sets. Both models are applied and tested in the developed prototype system. In addition, the paper presents the test setup and results of the study, including a description of the web user interface used to illustrate road condition data. The data were collected by a group of users driving on roads in western Finland. Finally, it provides a discussion on the challenges faced in the implementation of the prototype system and a look at the problems related to the analysis of the collected data. In general, the collected data were discovered to be more useful in the assessment of the overall condition of roads, and less useful for finding specific problematic spots on roads, such as potholes.",
author = "Pekka Sillberg and Mika Saari and Jere Gr{\"o}nman and Petri Rantanen and Markku Kuusisto",
year = "2020",
doi = "10.1007/978-3-030-38704-4_5",
language = "English",
isbn = "978-3-030-38703-7",
series = "Studies in Computational Intelligence",
publisher = "Springer",
pages = "99--119",
editor = "Ricardo Jardim-Goncalves and Vassil Sgurev and Vladimir Jotsov and Janusz Kacprzyk",
booktitle = "Intelligent Systems: Theory, Research and Innovation in Applications",

}

RIS (suitable for import to EndNote) - Download

TY - CHAP

T1 - Interpretation, Modeling and Visualization of Crowdsourced Road Condition Data

AU - Sillberg, Pekka

AU - Saari, Mika

AU - Grönman, Jere

AU - Rantanen, Petri

AU - Kuusisto, Markku

PY - 2020

Y1 - 2020

N2 - Nowadays almost everyone has a mobile phone and even the most basic smartphones often come embedded with a variety of sensors. These sensors, in combination with a large user base, offer huge potential in the realization of crowdsourcing applications. The crowdsourcing aspect is of interest especially in situations where users’ everyday actions can generate data usable in more complex scenarios. The research goal in this paper is to introduce a combination of models for data gathering and analysis of the gathered data, enabling effective data processing of large data sets. Both models are applied and tested in the developed prototype system. In addition, the paper presents the test setup and results of the study, including a description of the web user interface used to illustrate road condition data. The data were collected by a group of users driving on roads in western Finland. Finally, it provides a discussion on the challenges faced in the implementation of the prototype system and a look at the problems related to the analysis of the collected data. In general, the collected data were discovered to be more useful in the assessment of the overall condition of roads, and less useful for finding specific problematic spots on roads, such as potholes.

AB - Nowadays almost everyone has a mobile phone and even the most basic smartphones often come embedded with a variety of sensors. These sensors, in combination with a large user base, offer huge potential in the realization of crowdsourcing applications. The crowdsourcing aspect is of interest especially in situations where users’ everyday actions can generate data usable in more complex scenarios. The research goal in this paper is to introduce a combination of models for data gathering and analysis of the gathered data, enabling effective data processing of large data sets. Both models are applied and tested in the developed prototype system. In addition, the paper presents the test setup and results of the study, including a description of the web user interface used to illustrate road condition data. The data were collected by a group of users driving on roads in western Finland. Finally, it provides a discussion on the challenges faced in the implementation of the prototype system and a look at the problems related to the analysis of the collected data. In general, the collected data were discovered to be more useful in the assessment of the overall condition of roads, and less useful for finding specific problematic spots on roads, such as potholes.

U2 - 10.1007/978-3-030-38704-4_5

DO - 10.1007/978-3-030-38704-4_5

M3 - Chapter

SN - 978-3-030-38703-7

T3 - Studies in Computational Intelligence

SP - 99

EP - 119

BT - Intelligent Systems: Theory, Research and Innovation in Applications

A2 - Jardim-Goncalves, Ricardo

A2 - Sgurev, Vassil

A2 - Jotsov, Vladimir

A2 - Kacprzyk, Janusz

PB - Springer

ER -