Ferrari, L.[Laura],
Mamei, M.[Marco],
Discovering City Dynamics through Sports Tracking Applications,
Computer(44), No. 12, December 2011, pp. 63-68.
IEEE DOI
1112
Tracking data from the phone directly.
BibRef
Calabrese, F.,
Colonna, M.,
Lovisolo, P.,
Parata, D.,
Ratti, C.,
Real-Time Urban Monitoring Using Cell Phones: A Case Study in Rome,
ITS(12), No. 1, March 2011, pp. 141-151.
IEEE DOI
1103
BibRef
Pan, J.J.F.[Jeffrey Jun-Feng],
Pan, S.J.L.[Sinno Jia-Lin],
Yin, J.[Jie],
Ni, L.M.[Lionel M.],
Yang, Q.A.[Qi-Ang],
Tracking Mobile Users in Wireless Networks via Semi-Supervised
Colocalization,
PAMI(34), No. 3, March 2012, pp. 587-600.
IEEE DOI
1201
BibRef
Caceres, N.,
Romero, L.M.,
Benitez, F.G.,
del Castillo, J.M.,
Traffic Flow Estimation Models Using Cellular Phone Data,
ITS(13), No. 3, September 2012, pp. 1430-1441.
IEEE DOI
1209
BibRef
Gisdakis, S.,
Manolopoulos, V.,
Tao, S.,
Rusu, A.,
Papadimitratos, P.,
Secure and Privacy-Preserving Smartphone-Based Traffic Information
Systems,
ITS(16), No. 3, June 2015, pp. 1428-1438.
IEEE DOI
1506
Authentication
BibRef
Engelbrecht, J.,
Booysen, M.J.,
van Rooyen, G.J.,
Bruwer, F.J.,
Survey of smartphone-based sensing in vehicles for intelligent
transportation system applications,
IET-ITS(9), No. 10, 2015, pp. 924-935.
DOI Link
1512
computerised monitoring
BibRef
Wahlström, J.,
Skog, I.,
Händel, P.,
Smartphone-Based Vehicle Telematics: A Ten-Year Anniversary,
ITS(18), No. 10, October 2017, pp. 2802-2825.
IEEE DOI
1710
Internet of Things, Smartphones, driver classification, telematics,
usage-based-insurance, vehicle, navigation
BibRef
Janecek, A.,
Valerio, D.,
Hummel, K.A.,
Ricciato, F.,
Hlavacs, H.,
The Cellular Network as a Sensor:
From Mobile Phone Data to Real-Time Road Traffic Monitoring,
ITS(16), No. 5, October 2015, pp. 2551-2572.
IEEE DOI
1511
cellular radio
BibRef
Lv, M.,
Chen, L.,
Wu, X.,
Chen, G.,
A Road Congestion Detection System Using Undedicated Mobile Phones,
ITS(16), No. 6, December 2015, pp. 3060-3072.
IEEE DOI
1512
Accelerometers
BibRef
Demissie, M.G.,
Phithakkitnukoon, S.,
Sukhvibul, T.,
Antunes, F.,
Gomes, R.,
Bento, C.,
Inferring Passenger Travel Demand to Improve Urban Mobility in
Developing Countries Using Cell Phone Data: A Case Study of Senegal,
ITS(17), No. 9, September 2016, pp. 2466-2478.
IEEE DOI
1609
Africa
BibRef
Xu, Y.[Yang],
Shaw, S.L.[Shih-Lung],
Fang, Z.X.[Zhi-Xiang],
Yin, L.[Ling],
Estimating Potential Demand of Bicycle Trips from Mobile Phone Data:
An Anchor-Point Based Approach,
IJGI(5), No. 8, 2016, pp. 131.
DOI Link
1609
BibRef
Lai, W.K.[Wei-Kuang],
Kuo, T.H.[Ting-Huan],
Vehicle Positioning and Speed Estimation Based on Cellular Network
Signals for Urban Roads,
IJGI(5), No. 10, 2016, pp. 181.
DOI Link
1610
BibRef
Yang, X.P.[Xi-Ping],
Fang, Z.X.[Zhi-Xiang],
Xu, Y.[Yang],
Shaw, S.L.[Shih-Lung],
Zhao, Z.Y.[Zhi-Yuan],
Yin, L.[Ling],
Zhang, T.[Tao],
Lin, Y.[Yunong],
Understanding Spatiotemporal Patterns of Human Convergence and
Divergence Using Mobile Phone Location Data,
IJGI(5), No. 10, 2016, pp. 177.
DOI Link
1610
BibRef
Lu, S.W.[Shi-Wei],
Fang, Z.X.[Zhi-Xiang],
Zhang, X.R.[Xi-Rui],
Shaw, S.L.[Shih-Lung],
Yin, L.[Ling],
Zhao, Z.Y.[Zhi-Yuan],
Yang, X.P.[Xi-Ping],
Understanding the Representativeness of Mobile Phone Location Data in
Characterizing Human Mobility Indicators,
IJGI(6), No. 1, 2017, pp. xx-yy.
DOI Link
1702
BibRef
Zhong, G.,
Wan, X.,
Zhang, J.,
Yin, T.,
Ran, B.,
Characterizing Passenger Flow for a Transportation Hub Based on
Mobile Phone Data,
ITS(18), No. 6, June 2017, pp. 1507-1518.
IEEE DOI
1706
Base stations, Matrix converters, Mobile communication,
Mobile handsets, Time series analysis, Transportation, Urban areas,
Base station, mobile phone data, passenger transportation hub,
temporal-spatial clustering, wireless, communication
BibRef
Zhou, C.,
Jia, H.,
Juan, Z.,
Fu, X.,
Xiao, G.,
A Data-Driven Method for Trip Ends Identification Using Large-Scale
Smartphone-Based GPS Tracking Data,
ITS(18), No. 8, August 2017, pp. 2096-2110.
IEEE DOI
1708
Big data, Data models, Global Positioning System, Internet, Timing,
Transportation, GPS tracking data processing, data-driven method,
random forest, trip, ends, identification
BibRef
Basyoni, Y.[Yarah],
Abbas, H.M.[Hazem M.],
Talaat, H.[Hoda],
El Dimeery, I.[Ibrahim],
Speed prediction from mobile sensors using cellular phone-based traffic
data,
IET-ITS(11), No. 7, September 2017, pp. 387-396.
DOI Link
1710
BibRef
Lemmens, R.[Rob],
Lungo, J.[Juma],
Georgiadou, Y.[Yola],
Verplanke, J.[Jeroen],
Monitoring Rural Water Points in Tanzania with Mobile Phones:
The Evolution of the SEMA App,
IJGI(6), No. 10, 2017, pp. xx-yy.
DOI Link
1710
BibRef
Michau, G.,
Nantes, A.,
Bhaskar, A.,
Chung, E.,
Abry, P.,
Borgnat, P.,
Bluetooth Data in an Urban Context: Retrieving Vehicle Trajectories,
ITS(18), No. 9, September 2017, pp. 2377-2386.
IEEE DOI
1709
vehicular ad hoc networks, Bluetooth data sensor,
spatially constrained shortest path analysis,
traffic information gathering, travel time analysis,
trip information extraction, vehicle trajectory retrieval,
Roads, Trajectory, Vehicles,
constrained shortest path, trajectories.
BibRef
Jin, C.J.[Cheng-Jie],
Knoop, V.L.[Victor L.],
Jiang, R.[Rui],
Wang, W.[Wei],
Wang, H.[Hao],
Calibration and validation of cellular automaton traffic flow model
with empirical and experimental data,
IET-ITS(12), No. 5, June 2018, pp. 359-365.
DOI Link
1805
BibRef
Yin, M.,
Sheehan, M.,
Feygin, S.,
Paiement, J.F.,
Pozdnoukhov, A.,
A Generative Model of Urban Activities from Cellular Data,
ITS(19), No. 6, June 2018, pp. 1682-1696.
IEEE DOI
1806
Activity recognition, Analytical models, Context modeling,
Data models, Global Positioning System, Hidden Markov models,
latent variables
BibRef
Rupi, F.[Federico],
Schweizer, J.[Joerg],
Evaluating cyclist patterns using GPS data from smartphones,
IET-ITS(12), No. 4, May 2018, pp. 279-285.
DOI Link
1804
BibRef
Wang, X.O.[Xi-Ong],
Zhang, J.B.[Jin-Bei],
Tian, X.H.[Xiao-Hua],
Gan, X.Y.[Xiao-Ying],
Guan, Y.F.[Yun-Feng],
Wang, X.B.[Xin-Bing],
Crowdsensing-Based Consensus Incident Report for Road Traffic
Acquisition,
ITS(19), No. 8, August 2018, pp. 2536-2547.
IEEE DOI
1808
Roads, Reliability, Sensors, Mobile communication,
Inference algorithms, Smart phones, Wireless sensor networks,
incentive
BibRef
Batran, M.[Mohamed],
Mejia, M.G.[Mariano Gregorio],
Kanasugi, H.[Hiroshi],
Sekimoto, Y.[Yoshihide],
Shibasaki, R.[Ryosuke],
Inferencing Human Spatiotemporal Mobility in Greater Maputo via
Mobile Phone Big Data Mining,
IJGI(7), No. 7, 2018, pp. xx-yy.
DOI Link
1808
BibRef
Senaratne, H.,
Mueller, M.,
Behrisch, M.,
Lalanne, F.,
Bustos-Jiménez, J.,
Schneidewind, J.,
Keim, D.,
Schreck, T.,
Urban Mobility Analysis With Mobile Network Data: A Visual Analytics
Approach,
ITS(19), No. 5, May 2018, pp. 1537-1546.
IEEE DOI
1805
Antennas, Data visualization, GSM, Mobile communication, Trajectory,
Urban areas, Visual analytics, Visual analytics,
urban dynamics
BibRef
Kim, Y.S.[Young-Sung],
Ghorpade, A.[Ajinkya],
Zhao, F.[Fang],
Pereira, F.C.[Francisco C.],
Zegras, P.C.[P. Christopher],
Ben-Akiva, M.[Moshe],
Activity Recognition for a Smartphone and Web-Based Human Mobility
Sensing System,
IEEE_Int_Sys(33), No. 4, July 2018, pp. 5-23.
IEEE DOI
1810
BibRef
Earlier: A1, A4, A3, A2, A5, A6:
Activity Recognition for a Smartphone Based Travel Survey Based on
Cross-User History Data,
ICPR14(432-437)
IEEE DOI
1412
Frequency modulation, Quantization (signal),
Activity recognition, Global Positioning System, Sociology,
interactive data collection.
Accuracy. Transport models, why the trip is made.
BibRef
Zhou, Z.P.[Zhu-Ping],
Yang, J.[Jiwei],
Qi, Y.[Yong],
Cai, Y.F.[Yi-Fei],
Support vector machine and back propagation neutral network approaches
for trip mode prediction using mobile phone data,
IET-ITS(12), No. 10, December 2018, pp. 1220-1226.
DOI Link
1812
BibRef
Ghahramani, M.,
Zhou, M.,
Hon, C.T.,
Extracting Significant Mobile Phone Interaction Patterns Based on
Community Structures,
ITS(20), No. 3, March 2019, pp. 1031-1041.
IEEE DOI
1903
Mobile handsets, Urban areas, Data analysis, Clustering methods,
Transportation, Planning, Spatial databases, Big data,
spatio-temporal analysis
BibRef
Gao, Z.Q.[Zhi-Qiang],
Liu, D.W.[Da-Wei],
Huang, K.[Kaizhu],
Huang, Y.[Yi],
Context-Aware Human Activity and Smartphone Position-Mining with
Motion Sensors,
RS(11), No. 21, 2019, pp. xx-yy.
DOI Link
1911
BibRef
Demissie, M.G.,
Phithakkitnukoon, S.,
Kattan, L.,
Trip Distribution Modeling Using Mobile Phone Data:
Emphasis on Intra-Zonal Trips,
ITS(20), No. 7, July 2019, pp. 2605-2617.
IEEE DOI
1907
Mobile handsets, Poles and towers, Data models, Estimation, Gravity,
Transportation, Sociology, Gravity model, intra-zonal trips,
trip distribution model
BibRef
He, S.L.[Shang-Lu],
Ding, F.[Fan],
Zhou, Y.[Yang],
Cheng, Y.[Yang],
Ran, B.[Bin],
Investigating and modelling the relationship between traffic volume and
extracts from cellphone activity data,
IET-ITS(13), No. 8, August 2019, pp. 1299-1308.
DOI Link
1908
BibRef
Wu, H.[Hao],
Liu, L.B.[Ling-Bo],
Yu, Y.[Yang],
Peng, Z.H.[Zheng-Hong],
Jiao, H.Z.[Hong-Zan],
Niu, Q.A.[Qi-Ang],
An Agent-based Model Simulation of Human Mobility Based on Mobile
Phone Data: How Commuting Relates to Congestion,
IJGI(8), No. 7, 2019, pp. xx-yy.
DOI Link
1908
BibRef
Rupi, F.[Federico],
Poliziani, C.[Cristian],
Schweizer, J.[Joerg],
Data-driven Bicycle Network Analysis Based on Traditional Counting
Methods and GPS Traces from Smartphone,
IJGI(8), No. 8, 2019, pp. xx-yy.
DOI Link
1909
BibRef
Gore, N.[Ninad],
Arkatkar, S.[Shriniwas],
Joshi, G.[Gaurang],
Bhaskar, A.[Ashish],
Exploring credentials of Wi-Fi sensors as a complementary transport
data: an Indian experience,
IET-ITS(13), No. 12, December 2019, pp. 1860-1869.
DOI Link
1912
BibRef
Derrmann, T.,
Frank, R.,
Viti, F.,
Engel, T.,
How Road and Mobile Networks Correlate:
Estimating Urban Traffic Using Handovers,
ITS(21), No. 2, February 2020, pp. 521-530.
IEEE DOI
2002
Handover, Roads, Data models, Mobile handsets, Urban areas,
Mobile network, cellular, traffic state, traffic flow theory,
macroscopic fundamental diagram
BibRef
Ebrahimpour, Z.[Zeinab],
Wan, W.G.[Wang-Gen],
García, J.L.V.[José Luis Velázquez],
Cervantes, O.[Ofelia],
Hou, L.[Li],
Analyzing Social-Geographic Human Mobility Patterns Using Large-Scale
Social Media Data,
IJGI(9), No. 2, 2020, pp. xx-yy.
DOI Link
2003
BibRef
Liu, X.D.[Xu-Dong],
Tian, Y.Z.[Yong-Zhong],
Zhang, X.Q.[Xue-Qian],
Wan, Z.[Zuyi],
Identification of Urban Functional Regions in Chengdu Based on Taxi
Trajectory Time Series Data,
IJGI(9), No. 3, 2020, pp. xx-yy.
DOI Link
2004
BibRef
Mei, Z.Y.[Zhen-Yu],
Ding, W.C.[Wen-Chao],
Feng, C.[Chi],
Shen, L.[Liting],
Identifying commuters based on random forest of smartcard data,
IET-ITS(14), No. 4, April 2020, pp. 207-212.
DOI Link
2004
BibRef
Kim, K.,
Identifying the Structure of Cities by Clustering Using a New
Similarity Measure Based on Smart Card Data,
ITS(21), No. 5, May 2020, pp. 2002-2011.
IEEE DOI
2005
Urban areas, Public transportation, Smart cards,
Clustering algorithms, Feature extraction, Detection algorithms,
data mining
BibRef
Gong, L.S.[Lun-Sheng],
Jin, M.H.[Mei-Han],
Liu, Q.A.[Qi-Ang],
Gong, Y.X.[Yong-Xi],
Liu, Y.[Yu],
Identifying Urban Residents' Activity Space at Multiple Geographic
Scales Using Mobile Phone Data,
IJGI(9), No. 4, 2020, pp. xx-yy.
DOI Link
2005
BibRef
Sakamanee, P.[Pitchaya],
Phithakkitnukoon, S.[Santi],
Smoreda, Z.[Zbigniew],
Ratti, C.[Carlo],
Methods for Inferring Route Choice of Commuting Trip From Mobile
Phone Network Data,
IJGI(9), No. 5, 2020, pp. xx-yy.
DOI Link
2005
BibRef
Bicakci, Y.S.[Yunus Serhat],
Seker, D.Z.[Dursun Zafer],
Demirel, H.[Hande],
Location-Based Analyses for Electronic Monitoring of Parolees,
IJGI(9), No. 5, 2020, pp. xx-yy.
DOI Link
2005
BibRef
Yazdizadeh, A.,
Patterson, Z.,
Farooq, B.,
Ensemble Convolutional Neural Networks for Mode Inference in
Smartphone Travel Survey,
ITS(21), No. 6, June 2020, pp. 2232-2239.
IEEE DOI
2006
Global Positioning System, Trajectory, Transportation,
Predictive models, Feature extraction,
machine learning
BibRef
Peng, Z.H.[Zheng-Hong],
Wang, R.[Ru],
Liu, L.B.[Ling-Bo],
Wu, H.[Hao],
Fine-Scale Dasymetric Population Mapping with Mobile Phone and
Building Use Data Based on Grid Voronoi Method,
IJGI(9), No. 6, 2020, pp. xx-yy.
DOI Link
2006
BibRef
He, L.[Li],
Páez, A.[Antonio],
Jiao, J.M.[Jian-Min],
An, P.[Ping],
Lu, C.T.[Chun-Tian],
Mao, W.[Wen],
Long, D.P.[Dong-Ping],
Ambient Population and Larceny-Theft: A Spatial Analysis Using Mobile
Phone Data,
IJGI(9), No. 6, 2020, pp. xx-yy.
DOI Link
2006
BibRef
Zhang, G.Y.[Guang-Yuan],
Rui, X.P.[Xiao-Ping],
Poslad, S.[Stefan],
Song, X.F.[Xian-Feng],
Fan, Y.[Yonglei],
Wu, B.[Bang],
A Method for the Estimation of Finely-Grained Temporal Spatial Human
Population Density Distributions Based on Cell Phone Call Detail
Records,
RS(12), No. 16, 2020, pp. xx-yy.
DOI Link
2008
BibRef
Zheng, L.J.[Lin-Jiang],
Xia, D.[Dong],
Chen, L.[Li],
Sun, D.H.[Di-Hua],
Understanding Citywide Resident Mobility Using Big Data of Electronic
Registration Identification of Vehicles,
ITS(21), No. 10, October 2020, pp. 4363-4377.
IEEE DOI
2010
Trajectory, Automobiles, Public transportation, Roads,
Global Positioning System, Urban areas,
attractive area
BibRef
Chen, L.[Li],
Zheng, L.J.[Lin-Jiang],
Xia, D.[Dong],
Cai, X.L.[Xiao-Lin],
Sun, D.H.[Di-Hua],
Liu, W.N.[Wei-Ning],
Recognizing and Analyzing Private Car Commuters Using Big Data of
Electronic Registration Identification of Vehicles,
ITS(23), No. 9, September 2022, pp. 15629-15643.
IEEE DOI
2209
Automobiles, Public transportation, Roads, Feature extraction,
Trajectory, Urban areas, RFID tags, Hierarchical clustering,
mobility pattern
BibRef
Carboni, A.[Angela],
Deflorio, F.[Francesco],
Chiara, B.D.[Bruno Dalla],
Monitoring truck's operations at freight intermodal terminals: traffic
observation by scanning on-board devices,
IET-ITS(14), No. 12, December 2020, pp. 1638-1646.
DOI Link
2011
BibRef
Das, R.D.,
Purves, R.S.,
Exploring the Potential of Twitter to Understand Traffic Events and
Their Locations in Greater Mumbai, India,
ITS(21), No. 12, December 2020, pp. 5213-5222.
IEEE DOI
2012
Twitter, Roads, Sensors, Task analysis, Urban areas, Accidents,
Georeference, jaccard distance, placename, toponym, traffic, tweet,
geographical information science (GIS)
BibRef
Scholz, J.[Johannes],
Jeznik, J.[Janja],
Evaluating Geo-Tagged Twitter Data to Analyze Tourist Flows in
Styria, Austria,
IJGI(9), No. 11, 2020, pp. xx-yy.
DOI Link
2012
BibRef
Tu, L.,
Wang, S.,
Zhang, D.,
Zhang, F.,
He, T.,
ViFi-MobiScanner: Observe Human Mobility via Vehicular Internet
Service,
ITS(22), No. 1, January 2021, pp. 280-292.
IEEE DOI
2012
Wireless fidelity, Global Positioning System, Sensors,
Web and internet services, Urban areas, Observability,
multi-source data mining
BibRef
Sun, R.,
Cheng, Q.,
Xie, F.,
Zhang, W.,
Lin, T.,
Ochieng, W.Y.,
Combining Machine Learning and Dynamic Time Wrapping for Vehicle
Driving Event Detection Using Smartphones,
ITS(22), No. 1, January 2021, pp. 194-207.
IEEE DOI
2012
Smart phones, Sensors, Event detection,
Machine learning algorithms, Vehicles, Bagging, Acceleration,
dynamic time wrapping
BibRef
Wei, M.,
Liu, T.,
Sun, B.,
Optimal Routing Design of Feeder Transit With Stop Selection Using
Aggregated Cell Phone Data and Open Source GIS Tool,
ITS(22), No. 4, April 2021, pp. 2452-2463.
IEEE DOI
2104
Routing, Mathematical model, Transportation, Analytical models,
Programming, Tools, Mathematical programming,
open source GIS tool
BibRef
Liu, J.[Jian],
Meng, B.[Bin],
Wang, J.[Juan],
Chen, S.[Siyu],
Tian, B.[Bin],
Zhi, G.Q.[Guo-Qing],
Exploring the Spatiotemporal Patterns of Residents' Daily Activities
Using Text-Based Social Media Data: A Case Study of Beijing, China,
IJGI(10), No. 6, 2021, pp. xx-yy.
DOI Link
2106
BibRef
Wang, B.Q.[Bing-Qing],
Meng, B.[Bin],
Wang, J.[Juan],
Chen, S.[Siyu],
Liu, J.[Jian],
Perceiving Residents' Festival Activities Based on Social Media Data:
A Case Study in Beijing, China,
IJGI(10), No. 7, 2021, pp. xx-yy.
DOI Link
2108
BibRef
Zhang, X.M.[Xiao-Ming],
Gao, F.[Feng],
Liao, S.[Shunyi],
Zhou, F.[Fan],
Cai, G.F.[Guan-Fang],
Li, S.Y.[Shao-Ying],
Portraying Citizens' Occupations and Assessing Urban Occupation
Mixture with Mobile Phone Data: A Novel Spatiotemporal Analytical
Framework,
IJGI(10), No. 6, 2021, pp. xx-yy.
DOI Link
2106
BibRef
Wan, W.[Wei],
Cai, M.[Ming],
Phone-vehicle trajectory matching framework based on ALPR and
cellular signalling data,
IET-ITS(15), No. 1, 2021, pp. 107-118.
DOI Link
2106
BibRef
Cumbane, S.P.[Silvino Pedro],
Gidófalvi, G.[Gyozo],
Spatial Distribution of Displaced Population Estimated Using Mobile
Phone Data to Support Disaster Response Activities,
IJGI(10), No. 6, 2021, pp. xx-yy.
DOI Link
2106
BibRef
Zhu, X.Y.[Xiao-Yu],
Luo, Y.Y.[Yue-Yi],
Liu, A.F.[An-Feng],
Tang, W.J.[Wen-Juan],
Bhuiyan, M.Z.A.[Md. Zakirul Alam],
A Deep Learning-Based Mobile Crowdsensing Scheme by Predicting
Vehicle Mobility,
ITS(22), No. 7, July 2021, pp. 4648-4659.
IEEE DOI
2107
Sensors, Urban areas, Trajectory, Task analysis, Recruitment,
Prediction algorithms, Data centers, Mobile crowdsensing,
data collection
BibRef
Shit, R.C.[Rathin Chandra],
Sharma, S.[Suraj],
Yelamarthi, K.[Kumar],
Puthal, D.[Deepak],
AI-Enabled Fingerprinting and Crowdsource-Based Vehicle Localization
for Resilient and Safe Transportation Systems,
ITS(22), No. 7, July 2021, pp. 4660-4669.
IEEE DOI
2107
Location awareness, Fingerprint recognition, Machine learning,
Training, Databases, Machine learning algorithms, fingerprinting
BibRef
Antar, A.D.[Anindya Das],
Ahmed, M.[Masud],
Ahad, M.A.R.[Md Atiqur Rahman],
Recognition of human locomotion on various transportations fusing
smartphone sensors,
PRL(148), 2021, pp. 146-153.
Elsevier DOI
2107
Activity recognition, Deep learning, Feature selection,
Mode technique, Post processing, Statistical classification,
Smartphone sensors impact
BibRef
Liu, S.J.[Shao-Jun],
Long, Y.[Yi],
Zhang, L.[Ling],
Liu, H.[Hao],
Semantic Enhancement of Human Urban Activity Chain Construction Using
Mobile Phone Signaling Data,
IJGI(10), No. 8, 2021, pp. xx-yy.
DOI Link
2108
BibRef
Wang, C.X.[Chen-Xing],
Luo, H.Y.[Hai-Yong],
Zhao, F.[Fang],
Qin, Y.J.[Yan-Jun],
Combining Residual and LSTM Recurrent Networks for Transportation
Mode Detection Using Multimodal Sensors Integrated in Smartphones,
ITS(22), No. 9, September 2021, pp. 5473-5485.
IEEE DOI
2109
Feature extraction, Global Positioning System, Smart phones,
Public transportation, Intelligent sensors, Context awareness,
activity recognition
BibRef
Determe, J.F.[Jean-François],
Singh, U.[Utkarsh],
Horlin, F.[François],
de Doncker, P.[Philippe],
Forecasting Crowd Counts With Wi-Fi Systems: Univariate, Non-Seasonal
Models,
ITS(22), No. 10, October 2021, pp. 6407-6419.
IEEE DOI
2110
Wireless fidelity, Sensors, Forecasting, Predictive models, Probes,
Monitoring, Computational modeling, Crowd monitoring and control,
Box-Cox transformation
BibRef
Wilby, M.R.[Mark Richard],
González, A.B.R.[Ana Belén Rodríguez],
Pozo, R.F.[Rubén Fernández],
Díaz, J.J.V.[Juan José Vinagre],
Short-Term Prediction of Level of Service in Highways Based on
Bluetooth Identification,
ITS(23), No. 1, January 2022, pp. 142-151.
IEEE DOI
2201
Bluetooth, Roads, Measurement, Vehicles, Estimation, Data models,
Level of service, traffic prediction, Bluetooth identification,
travel time
BibRef
He, B.[Bing],
Hu, J.X.[Jin-Xing],
Liu, K.[Kang],
Xue, J.Z.[Jian-Zhang],
Ning, L.[Li],
Fan, J.P.[Jian-Ping],
Exploring Park Visit Variability Using Cell Phone Data in Shenzhen,
China,
RS(14), No. 3, 2022, pp. xx-yy.
DOI Link
2202
BibRef
Garrido-Valenzuela, F.[Francisco],
Raveau, S.[Sebastián],
Herrera, J.C.[Juan C.],
Bayesian Route Choice Inference to Address Missed Bluetooth
Detections,
ITS(23), No. 3, March 2022, pp. 1865-1874.
IEEE DOI
2203
Sensors, Bluetooth, Wireless fidelity, Trajectory, Roads,
Bayes methods, Directed graphs, Wi-Fi technology, MAC address
BibRef
Zhang, H.T.[Hai-Tao],
Shen, H.X.[Hui-Xian],
Ji, K.[Kang],
Song, R.[Rui],
Liu, J.Y.[Jin-Yuan],
Yang, Y.X.[Yu-Xin],
An Urban Hot/Cold Spot Detection Method Based on the Page Rank Value
of Spatial Interaction Networks Constructed from Human Communication
Records,
IJGI(11), No. 3, 2022, pp. xx-yy.
DOI Link
2204
BibRef
Wang, X.H.[Xiao-Han],
Zhang, Z.[Zepei],
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Clustering Methods Based on Stay Points and Grid Density for Hotspot
Detection,
IJGI(11), No. 3, 2022, pp. xx-yy.
DOI Link
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BibRef
Li, P.[Pei],
Abdel-Aty, M.[Mohamed],
Cai, Q.[Qing],
Islam, Z.[Zubayer],
A Deep Learning Approach to Detect Real-Time Vehicle Maneuvers Based
on Smartphone Sensors,
ITS(23), No. 4, April 2022, pp. 3148-3157.
IEEE DOI
2204
Accelerometers, Magnetic sensors, Gyroscopes,
Global Positioning System, Magnetometers, Cameras,
sensor fusion
BibRef
Zhang, K.[Kaisa],
Chuai, G.[Gang],
Zhang, J.X.[Jin-Xi],
Chen, X.Y.[Xiang-Yu],
Si, Z.W.[Zhi-Wei],
Maimaiti, S.[Saidiwaerdi],
DIC-ST: A Hybrid Prediction Framework Based on Causal Structure
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Ferreira, G.[Gonçalo],
Alves, A.[Ana],
Veloso, M.[Marco],
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Identification and Classification of Routine Locations Using
Anonymized Mobile Communication Data,
IJGI(11), No. 4, 2022, pp. xx-yy.
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BibRef
Lin, Y.H.[Yen-Hsun],
Chen, Y.C.[Yi-Chung],
Chiu, S.M.[Sheng-Min],
Lee, C.A.[Chi-Ang],
Wang, F.C.[Fu-Cheng],
Applying Check-in Data and User Profiles to Identify Optimal Store
Locations in a Road Network,
IJGI(11), No. 5, 2022, pp. xx-yy.
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2206
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Lu, D.[Danni],
Li, Y.[Ye],
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Evaluating Spatial and Temporal Characteristics of Population Density
Using Cellular Data,
ITS(23), No. 6, June 2022, pp. 5717-5726.
IEEE DOI
2206
Statistics, Sociology, Poles and towers, Urban areas, Transportation,
Correlation, Planning, Cellular call detail record, traffic demand,
megacities
BibRef
Advani, C.[Chintan],
Bhaskar, A.[Ashish],
Haque, M.M.[Md. Mazharul],
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STATER: Slit-Based Trajectory Reconstruction for Dense Urban Network
With Overlapping Bluetooth Scanning Zones,
ITS(23), No. 7, July 2022, pp. 8316-8326.
IEEE DOI
2207
Trajectory, Roads, Bluetooth, Databases,
Radiofrequency identification,
slit based trajectory reconstruction (STATER) algorithm
BibRef
Yang, L.T.[Lin-Tao],
Zhu, Y.[Yashu],
Mei, Q.K.[Qi-Kai],
Zeng, Y.Y.[Yuan-Yuan],
Jiang, H.[Hao],
Individual Differentiated Multidimensional Hawkes Model:
Uncovering Urban Spatial Interaction Using Mobile-Phone Data,
ITS(23), No. 7, July 2022, pp. 7987-7997.
IEEE DOI
2207
Urban areas, Data models, Trajectory, Gravity,
Spatiotemporal phenomena, Spatial databases, Urban planning, urban planning
BibRef
Grujic, N.[Nastasija],
Brdar, S.[Sanja],
Osinga, S.[Sjoukje],
Hofstede, G.J.[Gert Jan],
Athanasiadis, I.N.[Ioannis N.],
Pljakic, M.[Miloš],
Obrenovic, N.[Nikola],
Govedarica, M.[Miro],
Crnojevic, V.[Vladimir],
Combining Telecom Data with Heterogeneous Data Sources for Traffic
and Emission Assessments: An Agent-Based Approach,
IJGI(11), No. 7, 2022, pp. xx-yy.
DOI Link
2208
BibRef
Hadachi, A.[Amnir],
Pourmoradnasseri, M.[Mozhgan],
A Survey on the Advancement of Travel Time Estimation Using Mobile
Phone Network Data,
ITS(23), No. 8, August 2022, pp. 11779-11788.
IEEE DOI
2208
Estimation, Sensors, Roads, Mobile handsets,
Global Positioning System, Cellular networks, Handover,
urban mobility dynamics
BibRef
Cai, M.[Ming],
Zhang, Z.X.[Zi-Xuan],
Xiong, C.[Chen],
Gou, C.[Chao],
An Adaptive Staying Point Recognition Algorithm Based on
Spatiotemporal Characteristics Using Cellular Signaling Data,
ITS(23), No. 8, August 2022, pp. 10458-10468.
IEEE DOI
2208
Spatiotemporal phenomena, Trajectory, Clustering algorithms,
Modeling, Cleaning, Cellular phones, Base stations,
clustering method
BibRef
Li, Z.S.[Zhi-Shuai],
Xiong, G.[Gang],
Wei, Z.B.[Ze-Bing],
Zhang, Y.[Yu],
Zheng, M.[Meng],
Liu, X.L.[Xiao-Li],
Tarkoma, S.[Sasu],
Huang, M.[Min],
Lv, Y.S.[Yi-Sheng],
Wu, C.[Chuheng],
Trip Purposes Mining From Mobile Signaling Data,
ITS(23), No. 8, August 2022, pp. 13190-13202.
IEEE DOI
2208
Cellular networks, Trajectory, Semantics, Unsupervised learning,
Supervised learning, Resource management, Public transportation, big data
BibRef
Zia, M.[Mohammed],
Fürle, J.[Johannes],
Ludwig, C.[Christina],
Lautenbach, S.[Sven],
Gumbrich, S.[Stefan],
Zipf, A.[Alexander],
SocialMedia2Traffic: Derivation of Traffic Information from Social
Media Data,
IJGI(11), No. 9, 2022, pp. xx-yy.
DOI Link
2209
BibRef
Fu, X.[Xiao],
Yu, G.[Guanyi],
Liu, Z.Y.[Zhi-Yuan],
Spatial-Temporal Convolutional Model for Urban Crowd Density
Prediction Based on Mobile-Phone Signaling Data,
ITS(23), No. 9, September 2022, pp. 14661-14673.
IEEE DOI
2209
Predictive models, Convolution, Hidden Markov models,
Task analysis, Data models, Data mining, Deep learning,
activity choice behavior
BibRef
Jiang, H.H.[Hai-Hang],
Yang, F.[Fei],
Su, W.J.[Wei-Jie],
Yao, Z.X.[Zhen-Xing],
Dai, Z.[Zhuang],
Activity location recognition from mobile phone data using improved
HAC and Bi-LSTM,
IET-ITS(16), No. 10, 2022, pp. 1364-1379.
DOI Link
2209
BibRef
Wei, Y.J.[Yi-Jun],
Mahnaz, F.[Faria],
Bulan, O.[Orhan],
Mengistu, Y.[Yehenew],
Mahesh, S.[Sheetal],
Losh, M.A.[Michael A.],
Creating Semantic HD Maps From Aerial Imagery and Aggregated Vehicle
Telemetry for Autonomous Vehicles,
ITS(23), No. 9, September 2022, pp. 15382-15395.
IEEE DOI
2209
Roads, Image edge detection, Feature extraction, Telemetry,
Image segmentation, Navigation, Soft sensors, Autonomous vehicles,
telemetry
BibRef
Pintér, G.[Gergo],
Felde, I.[Imre],
Commuting Analysis of the Budapest Metropolitan Area Using Mobile
Network Data,
IJGI(11), No. 9, 2022, pp. xx-yy.
DOI Link
2209
BibRef
Daraio, E.[Elena],
Cagliero, L.[Luca],
Chiusano, S.[Silvia],
Garza, P.[Paolo],
Complementing Location-Based Social Network Data With Mobility Data:
A Pattern-Based Approach,
ITS(23), No. 11, November 2022, pp. 21216-21227.
IEEE DOI
2212
Urban areas, Social networking (online), Data models, Soft sensors,
Data mining, Public transportation, Automobiles,
sequential pattern mining
BibRef
Yang, C.[Chao],
Guo, T.Y.[Tang-Yi],
Wang, Y.[Yinhai],
The Smartphone-Based Person Travel Survey System: Data Collection,
Trip Extraction, and Travel Mode Detection,
ITS(23), No. 12, December 2022, pp. 23399-23407.
IEEE DOI
2212
Legged locomotion, Global Positioning System, Smart phones,
Trajectory, Data collection, Interviews, Data mining, Travel survey,
smartphone
BibRef
Berjisian, E.[Elmira],
Bigazzi, A.[Alexander],
Evaluation of map-matching algorithms for smartphone-based active
travel data,
IET-ITS(17), No. 1, 2023, pp. 227-242.
DOI Link
2301
BibRef
Wang, F.[Fuyou],
Gao, C.F.[Cheng-Fa],
Shang, R.[Rui],
Zhang, R.C.[Rui-Cheng],
Gan, L.[Lu],
Liu, Q.[Qi],
Wang, J.C.[Jian-Chao],
An In-Vehicle Smartphone RTK/DR Positioning Method Combined with OSM
Road Network,
RS(15), No. 2, 2023, pp. xx-yy.
DOI Link
2301
BibRef
Chen, X.Y.[Xiang-Yu],
Zhang, K.[Kaisa],
Chuai, G.[Gang],
Gao, W.D.[Wei-Dong],
Si, Z.W.[Zhi-Wei],
Hou, Y.J.[Yi-Jian],
Liu, X.W.[Xue-Wen],
Urban Area Characterization and Structure Analysis: A Combined
Data-Driven Approach by Remote Sensing Information and
Spatial-Temporal Wireless Data,
RS(15), No. 4, 2023, pp. xx-yy.
DOI Link
2303
BibRef
Zhang, J.[Jielu],
Mu, L.[Lan],
Zhang, D.[Donglan],
Rajbhandari-Thapa, J.[Janani],
Chen, Z.[Zhuo],
Pagán, J.A.[José A.],
Li, Y.[Yan],
Son, H.[Heejung],
Liu, J.X.[Jun-Xiu],
Spatiotemporal Optimization for the Placement of Automated External
Defibrillators Using Mobile Phone Data,
IJGI(12), No. 3, 2023, pp. xx-yy.
DOI Link
2303
BibRef
Li, J.Z.[Jun-Zhuo],
Li, W.Y.[Wen-Yong],
Lian, G.[Guan],
Urban Resident Travel Survey Method Based on Cellular Signaling Data,
IJGI(12), No. 8, 2023, pp. 304.
DOI Link
2309
BibRef
Rodrigues, C.[Cláudia],
Veloso, M.[Marco],
Alves, A.[Ana],
Bento, C.[Carlos],
Sensing Mobility and Routine Locations through Mobile Phone and
Crowdsourced Data: Analyzing Travel and Behavior during COVID-19,
IJGI(12), No. 8, 2023, pp. 308.
DOI Link
2309
BibRef
Qu, L.[Lin],
Zhou, Y.[Yue],
Li, J.X.[Jiang-Xin],
Yu, Q.[Qiong],
Jiang, X.G.[Xin-Guo],
HMM-Based Map Matching and Spatiotemporal Analysis for Matching
Errors with Taxi Trajectories,
IJGI(12), No. 8, 2023, pp. 330.
DOI Link
2309
BibRef
Servizi, V.[Valentino],
Persson, D.R.[Dan Roland],
Pereira, F.C.[Francisco Camara],
Villadsen, H.[Hannah],
Bækgaard, P.[Per],
Peled, I.[Inon],
Nielsen, O.A.[Otto Anker],
'Is Not the Truth the Truth?': Analyzing the Impact of User
Validations for Bus In/Out Detection in Smartphone-Based Surveys,
ITS(24), No. 11, November 2023, pp. 11905-11920.
IEEE DOI
2311
BibRef
Guo, Y.D.[Yu-Dong],
Yang, F.[Fei],
Yan, H.M.[Hao-Min],
Xie, S.Y.[Si-Yuan],
Liu, H.[Haode],
Dai, Z.[Zhuang],
Activity-based model based on multi-day cellular data:
Considering the lack of personal attributes and activity type,
IET-ITS(17), No. 12, 2023, pp. 2474-2492.
DOI Link
2312
demand forecasting, traffic, traffic and demand managing, traveller information
BibRef
Chen, X.C.[Xing-Can],
Zou, Y.[Yi],
Li, C.L.[Cheng-Lin],
Xiao, W.D.[Wen-Dong],
A Deep Learning Based Lightweight Human Activity Recognition System
Using Reconstructed WiFi CSI,
HMS(54), No. 1, February 2024, pp. 68-78.
IEEE DOI
2402
Wireless fidelity, Tensors, Human activity recognition,
Signal representation, Convolutional neural networks,
WiFi channel state information (CSI)
BibRef
Lou, L.L.[Liang-Liang],
Song, M.X.[Ming-Xin],
Chen, X.Q.[Xin-Quan],
Zhao, X.M.[Xiao-Ming],
Zhang, S.Q.[Shi-Qing],
Optimized Wireless Sensing and Deep Learning for Enhanced
Human-Vehicle Recognition,
ITS(25), No. 7, July 2024, pp. 7508-7521.
IEEE DOI Code:
WWW Link.
2407
Wireless communication, Wireless sensor networks, Sensors,
Antennas, Roads, Attenuation, Propagation losses, received signal strength
BibRef
Mendoza-Hurtado, M.[Manuel],
Romero-del-Castillo, J.A.[Juan A.],
Ortiz-Boyer, D.[Domingo],
SAMPLID: A New Supervised Approach for Meaningful Place
Identification Using Call Detail Records as an Alternative to
Classical Unsupervised Clustering Techniques,
IJGI(13), No. 8, 2024, pp. 289.
DOI Link
2408
BibRef
Chapter on Motion -- Feature-Based, Long Range, Motion and Structure Estimates, Tracking, Surveillance, Activities continues in
Traffic Flow Analysis, GPS, GNSS .