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https://doi.org/10.1007/978-3-...
Part of book or chapter of book . 2018 . Peer-reviewed
License: Springer TDM
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Urban Mobility: Mobile Crowdsensing Applications

Authors: João Simões; Rui Gomes; Ana Alves 0001; Jorge Bernardino;

Urban Mobility: Mobile Crowdsensing Applications

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.

Country
Portugal
Keywords

Urban Mobility, mobile applications

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
1
Average
Average
Average
Green
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