Estimation of traffic flow using passive cell-phone data

Frías-Martínez, Vanessa; Moumni, Younes; Frı́as-Martı́nez, Enrique

doi:10.1145/2630729.2630739

Cited by 3 publications

(3 citation statements)

References 3 publications

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“…Of the studies not involved with either of the Orange Data for Development challenges, all studies apart from three [ 38 , 39 , 64 ] stated that the mobile phone CDRs they used in their research were anonymized. Few studies described the anonymization process as this was usually undertaken by the MNO beforehand.…”

Section: Resultsmentioning

confidence: 99%

Challenges and Potential Opportunities of Mobile Phone Call Detail Records in Health Research: Review

Jones¹,

Daniels²,

Heys³

et al. 2018

JMIR Mhealth Uhealth

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BackgroundCall detail records (CDRs) are collected by mobile network operators in the course of providing their service. CDRs are increasingly being used in research along with other forms of big data and represent an emerging data type with potential for public good. Many jurisdictions have infrastructures for health data research that could benefit from the integration of CDRs with health data.ObjectiveThe objective of this study was to review how CDRs have been used in health research and to identify challenges and potential opportunities for their wider use in conjunction with health data.MethodsA literature review was conducted using structured search terms making use of major search engines. Initially, 4066 items were identified. Following screening, 46 full text articles were included in the qualitative synthesis. Information extracted included research topic area, population of study, datasets used, information governance and ethical considerations, study findings, and data limitations.ResultsThe majority of published studies were focused on low-income and middle-income countries. Making use of the location element in CDRs, studies often modeled the transmission of infectious diseases or estimated population movement following natural disasters with a view to implementing interventions. CDRs were used in anonymized or aggregated form, and the process of gaining regulatory approvals varied with data provider and by jurisdiction. None included public views on the use of CDRs in health research.ConclusionsDespite various challenges and limitations, anonymized mobile phone CDRs have been used successfully in health research. The use of aggregated data is a safeguard but also a further limitation. Greater opportunities could be gained if validated anonymized CDRs were integrated with routine health records at an individual level, provided that permissions and safeguards could be put in place. Further work is needed, including gaining public views, to develop an ethically founded framework for the use of CDRs in health research.

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Section: Resultsmentioning

confidence: 99%

Challenges and Potential Opportunities of Mobile Phone Call Detail Records in Health Research: Review

Jones¹,

Daniels²,

Heys³

et al. 2018

JMIR Mhealth Uhealth

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“…Jiang et al reviewed methods for information extraction from triangulated CDR data, spatio-temporal analysis, and urban modeling [29]. Also, other studies reported real-time road traffic information extracted from the CDR data [30], [31], [32]. In [33], Janecek et al proposed a novel approach combining signaling data ('idle' device information) together with CDR (SigCDR) to obtain canonical information of the mobile users in an area.…”

Section: Introductionmentioning

confidence: 99%

Advances in Crowd Analysis for Urban Applications Through Urban Event Detection

Kaiser

Lwin

Mahmud

et al. 2018

IEEE Trans. Intell. Transport. Syst.

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Abstract-The recent expansion of pervasive computing technology has contributed with novel means to pursue human activities in urban space. The urban dynamics unveiled by these means generate an enormous amount of data. These data are mainly endowed by portable and radio-frequency devices, transportation systems, video surveillance, satellites, unmanned aerial vehicles, and social networking services. This has opened a new avenue of opportunities, to understand and predict urban dynamics in detail, and plan various real-time services and applications in response to that. Over the last decade, certain aspects of the crowd, e.g. mobility, sentimental, size estimation and behavioral, have been analyzed in detail and the outcomes have been reported. This article mainly conducted an extensive survey on various data sources used for different urban applications, the state-of-the-art on urban data generation techniques and associated processing methods in order to demonstrate their merits and capabilities. Then, a possible crowd event detection framework is discussed which fuses data from all the available pervasive technology sources. In addition, available open-access crowd datasets for urban event detection are provided along with relevant Application Programming Interfaces, and finally, some open challenges and promising research directions are outlined.Index Terms-Urban sensing, pervasive technology, crowd mobility and management, information fusion, decision support system, benchmark datasets.

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“…The CDRs datasets overcome the acquisition problems (financially, time consuming), but their projection and trajectories tracing still time and resource consuming. The researchers try to solve this limitation by selecting the samples randomly from the CDRs, and obtain the highly frequent records [60,62,30,42,63,64,32,10,33,20,12,28].…”

Section: Introductionmentioning

confidence: 99%

Adaptive Modeling of Urban Dynamics During Ephemeral Event via Mobile Phone Traces

Behadili¹,

Bertelle²,

George³

2016

IEIJ

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The communication devices have produced digital traces for their users either voluntarily or not. This type of collective data can give powerful indications that are affecting the urban systems design and development. In this study mobile phone data during Armada event is investigated. Analyzing mobile phone traces gives conceptual views about individuals densities and their mobility patterns in the urban city. The geo-visualization and statistical techniques have been used for understanding human mobility collectively and individually. The undertaken substantial parameters are inter-event times, travel distances (displacements) and radius of gyration. They have been analyzed and simulated using computing platform by integrating various applications for huge database management, visualization, analysis, and simulation. Accordingly, the general population pattern law has been extracted. The study contribution outcomes have revealed both the individuals densities in static perspective and individuals mobility in dynamic perspective with multi levels of abstraction (macroscopic, mesoscopic, microscopic).

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Estimation of traffic flow using passive cell-phone data

Cited by 3 publications

References 3 publications

Challenges and Potential Opportunities of Mobile Phone Call Detail Records in Health Research: Review

Challenges and Potential Opportunities of Mobile Phone Call Detail Records in Health Research: Review

Advances in Crowd Analysis for Urban Applications Through Urban Event Detection

Adaptive Modeling of Urban Dynamics During Ephemeral Event via Mobile Phone Traces

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