Abstract
Mobility has become one of the most difficult challenges that cities must face. More than half of world’s population resides in urban areas and with the continuously growing population it is imperative that cities use their resources more efficiently. Obtaining and gathering data from different sources can be extremely important to support new solutions that will help building a better mobility for the citizens. Crowdsensing has become a popular way to share data collected by sensing devices with the goal to achieve a common interest. Data collected by crowdsensing applications can be a promising way to obtain valuable mobility information from each citizen. In this paper, we study the current work on the integrated mobility services exploring the crowdsensing applications that were used to extract and provide valuable mobility data. Also, we analyze the main current techniques used to characterize urban mobility.
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Notes
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http://www.nlpir.org/ [Accessed: 11-Dec-2017].
- 4.
https://developers.google.com/maps/documentation/javascript/geocoding [Accessed: 11-Dec-2017].
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URBY.Sense is co-financed by COMPETE 2020, Portugal 2020 - Programa Operacional Competitividade e Internacionalização (POCI), FEDER and FCT.
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Simões, J., Gomes, R., Alves, A., Bernardino, J. (2019). Urban Mobility: Mobile Crowdsensing Applications. In: Novais, P., et al. Ambient Intelligence – Software and Applications –, 9th International Symposium on Ambient Intelligence. ISAmI2018 2018. Advances in Intelligent Systems and Computing, vol 806. Springer, Cham. https://doi.org/10.1007/978-3-030-01746-0_21
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DOI: https://doi.org/10.1007/978-3-030-01746-0_21
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