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Exploring a New Model for Mobile Positioning Based on CDR Data of The Cellular Networks [article]

Amnir Hadachi, Artjom Lind
2019 arXiv   pre-print
The emerging technologies related to mobile data especially CDR data has great potential for mobility and transportation applications.  ...  For example by introducing more sophisticated movement model based on data-driven modeling and a map matching that uses the movement model type detected by matching "Stay" location to buildings and "Move  ...  The data used for testing contains 649 CDR records provided by the mobile operator for six different users for almost a period of one month.  ... 
arXiv:1902.09399v1 fatcat:dc66wjgpn5cgzdjos2ltnn7s7y

Applying Big Data Analytics to Monitor Tourist Flow for the Scenic Area Operation Management

Siyang Qin, Jie Man, Xuzhao Wang, Can Li, Honghui Dong, Xinquan Ge
2019 Discrete Dynamics in Nature and Society  
The analysis shows that the big data analysis method based on the CDR data of mobile phones can provide real-time information about tourist behaviours in a timely and effective manner.  ...  In this paper, the author uses the Big Data technology and Call Detail Record (CDR) data with the mobile phone real-time location information to monitor the tourist flow and analyse the travel behaviour  ...  Based on the continuous development of positioning technology in mobile communication, the tourist flow analysis with Call Detail Record (CDR) data can provide real-time valid data for scenic flow control  ... 
doi:10.1155/2019/8239047 fatcat:s25v3py3n5eyxcalwthh4wmlpu

Transport mode detection based on mobile phone network data: A systematic review

Haosheng Huang, Yi Cheng, Robert Weibel
2019 Transportation Research Part C: Emerging Technologies  
This paper provides an in-depth, systematic review of transport mode detection based on mobile phone network data.  ...  This paper provides an in-depth, systematic review of transport mode detection based on mobile phone network data.  ...  There are two categories of search terms, and at least one term from each category must be matched: 1) mobile phone network data*, mobile phone networking data*, call detail record*, CDR, cellular network  ... 
doi:10.1016/j.trc.2019.02.008 fatcat:hlmjnl7imjbj5hkjyu4vchbdja

MODELING CITY PULSATION VIA MOBILE DATA

Suhad Faisal Behadili, Cyrille Bertelle, Loay George
2020 International Journal of Engineering Technologies and Management Research  
on CDRs (Call Detail Records) data.  ...  How life patterns and individuals' mobility could be extracted for this region from mobile DB (CDRs)?  ...  The adaptive and non-parametric method for identification of dense areas is based on using the ubiquitous infrastructure provided by cell phone network [1] .  ... 
doi:10.29121/ijetmr.v5.i4.2018.215 fatcat:kda64ekbxnho5mx6durczk23gi

Modeling City Pulsation Via Mobile Data

Suhad Faisal Behadili *1, Cyrille Bertelle 2, Loay E. George 1
2018 Zenodo  
on CDRs (Call Detail Records) data.  ...  How life patterns and individuals' mobility could be extracted for this region from mobile DB (CDRs)?  ...  The adaptive and non-parametric method for identification of dense areas is based on using the ubiquitous infrastructure provided by cell phone network [1] .  ... 
doi:10.5281/zenodo.1250517 fatcat:drlds76fefhvzn3ziiwwv6rkbi

Measuring similarity of mobile phone user trajectories– a Spatio-temporal Edit Distance method

Yihong Yuan, Martin Raubal
2013 International Journal of Geographical Information Science  
records (CDRs).  ...  This paper contributes to this research area by developing the Spatio-temporal Edit Distance measure, an extended algorithm to determine the similarity between user trajectories based on call detailed  ...  the same mobile phone tower.  ... 
doi:10.1080/13658816.2013.854369 fatcat:mfunti2b7baafpiixgvay5vrpe

On Recommending Opportunistic Rides

Nicola Bicocchi, Marco Mamei, Andrea Sassi, Franco Zambonelli
2017 IEEE transactions on intelligent transportation systems (Print)  
Research on social and mobile technologies recently provided tools to collect and mine massive amounts of mobility data. Ride sharing is one of the most prominent applications in this area.  ...  We present a set of algorithms to analyse urban mobility traces and to recognise matching rides along similar routes. These rides are amenable for ride sharing recommendations.  ...  Detail Records (CDR) collected over the cellular network as the main source of localization and mobility data.  ... 
doi:10.1109/tits.2017.2684625 fatcat:2qgcx4wbxzhedmttbqnptc7mni

Bayesian Inference for Localization in Cellular Networks

Hui Zang, Francois Baccelli, Jean Bolot
2010 2010 Proceedings IEEE INFOCOM  
We study important parameters used in this Bayesian method through mining call data records and matching GPS records and obtain their distribution or typical values.  ...  In this paper, we present a general technique based on Bayesian inference to locate mobiles in cellular networks.  ...  Another data set is referred to as "Call Data Records" (CDRs). This is a separate data set and we match the E911 calls to records in this set.  ... 
doi:10.1109/infcom.2010.5462018 dblp:conf/infocom/ZangBB10 fatcat:eer4drpddve7pj2y3mibofymea

The promises of big data and small data for travel behavior (aka human mobility) analysis

Cynthia Chen, Jingtao Ma, Yusak Susilo, Yu Liu, Menglin Wang
2016 Transportation Research Part C: Emerging Technologies  
One field comprises transportation researchers who have been working in the field for decades and the other involves new comers from a wide range of disciplines, but primarily computer scientists and physicists  ...  It is thus the purpose of this paper to introduce datasets, concepts, knowledge and methods used in these two fields, and most importantly raise cross-discipline ideas for conversations and collaborations  ...  Acknowledgements Funding for this research is provided by a NSF (National Science Foundation) Grant (CMMI 1200275) and a NIH (National Institute of Health) grant (1R01GM108731-01A1) to Cynthia Chen.  ... 
doi:10.1016/j.trc.2016.04.005 pmid:27182125 pmcid:PMC4862004 fatcat:yumi6fcin5enhoffqabhp4erny

Identification and Prediction of Large Pedestrian Flow in Urban Areas Based on a Hybrid Detection Approach

Kaisheng Zhang, Mei Wang, Bangyang Wei, Daniel(Jian) Sun
2016 Sustainability  
In particular, a hybrid pedestrian flow detection model was constructed by analyzing real data from major mobile phone operators in China, including information from smartphones and base stations (BS).  ...  With the hybrid model, the Log Distance Path Loss (LDPL) model was used to estimate the pedestrian density from raw network data, and retrieve information with the Gaussian Progress (GP) through supervised  ...  K.Z. integrated the RSS method into the analysis, and wrapped up each component of the model, so as to achieve one formal research paper.  ... 
doi:10.3390/su9010036 fatcat:e6gybjnxc5hxtdtmaqropvk7l4

Commentary: Containing the Ebola Outbreak - the Potential and Challenge of Mobile Network Data

Amy Wesolowski, Caroline O. Buckee, Linus Bengtsson, Erik Wetter, Xin Lu, Andrew J. Tatem
2014 PLOS Currents  
In this commentary, we outline the utility of CDRs for understanding human mobility in the context of the Ebola, and highlight the need to develop protocols for rapid sharing of operator data in response  ...  In this commentary, we outline the utility of CDRs for understanding human mobility in the context of the Ebola, and highlight the need to develop protocols for rapid sharing of operator data in response  ...  APPENDIX 1 Containing the Ebola outbreak -the potential and challenge of mobile network data: Appendix 1 Materials and Methods We analyzed a number of existing data sources from national census microdata  ... 
doi:10.1371/currents.outbreaks.0177e7fcf52217b8b634376e2f3efc5e pmid:25642369 pmcid:PMC4205120 fatcat:u4yzp7zr6vhsjegv47fep3bbgu

The fallacy of the closest antenna: Towards an adequate view of device location in the mobile network [article]

Aleksey Ogulenko, Itzhak Benenson, Marina Toger, John Östh, Alexey Siretskiy
2021 arXiv   pre-print
This view is shared by numerous papers that exploit mobile phone data for studying human spatial mobility.  ...  The partition of the Mobile Phone Network (MPN) service area into the cell towers' Voronoi polygons (VP) may serve as a coordinate system for representing the location of the mobile phone devices.  ...  Billing of the MPN services is based on Call-Detail Records (CDR) of the Mobile Phone (MP) connections recorded by an MPN operator.  ... 
arXiv:2109.02154v1 fatcat:nesyxkt2cnffpoob5kn2ptb3je

Exploring Group Movement Pattern through Cellular Data: A Case Study of Tourists in Hainan

Xinning Zhu, Tianyue Sun, Hao Yuan, Zheng Hu, Jiansong Miao
2019 ISPRS International Journal of Geo-Information  
To address such challenges, we propose a method called group movement pattern mining based on similarity (GMPMS) to discover tourist groups.  ...  In this paper, we present a framework to discover tourist groups and investigate the tourist behaviors using mobile phone call detail records (CDRs).  ...  We propose a method called group movement pattern mining based on similarity (GMPMS) to identify tourist groups with sparse CDR data.  ... 
doi:10.3390/ijgi8020074 fatcat:q5gaj6xz4rdxlndzdnp74mzp2m

Route classification using cellular handoff patterns

Richard A. Becker, Ramon Caceres, Karrie Hanson, Ji Meng Loh, Simon Urbanek, Alexander Varshavsky, Chris Volinsky
2011 Proceedings of the 13th international conference on Ubiquitous computing - UbiComp '11  
Second, we present two accurate classification algorithms for matching cellular handoff patterns to routes: one requires test drives on the routes while the other uses signal strength data collected by  ...  Distance.  ...  ACKNOWLEDGEMENTS We thank Mike Orth for providing us with the Nova RF data and Colin Goodall and Siva Prakasam for collecting and anonymizing the CDR data we used in this paper.  ... 
doi:10.1145/2030112.2030130 dblp:conf/huc/BeckerCHLUVV11 fatcat:hze6pn47wvgp7aa4covsy2cvyi

Bayesian Framework For Mobility Pattern Discovery Using Mobile Network Events

Somayeh Danafar, Krzysztof Kryszczuk, Michal Piorkowski
2018 Zenodo  
Fillekes [10] developed individual trajectory reconstruction techniques based on Call Detail Record (CDR) data.  ...  In this research, focusing solely on network signals, accurate GPS-based anchor locations for individual movements like [13] can not be used.  ... 
doi:10.5281/zenodo.1160149 fatcat:e6rz5dekyjedbm7atvhhzuct2y
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