Understanding WiFi-based connectivity from moving vehicles

R Mahajan, J Zahorjan, B Zill - Proceedings of the 7th ACM SIGCOMM …, 2007 - dl.acm.org
Using measurements from VanLAN, a modest-size testbed that we have deployed, we
analyze the fundamental characteristics of WiFi-based connectivity between basestations …

The TimeGeo modeling framework for urban mobility without travel surveys

S Jiang, Y Yang, S Gupta… - Proceedings of the …, 2016 - National Acad Sciences
Well-established fine-scale urban mobility models today depend on detailed but
cumbersome and expensive travel surveys for their calibration. Not much is known …

[PDF][PDF] Towards estimating the presence of visitors from the aggregate mobile phone network activity they generate

F Girardin, A Vaccari, A Gerber, A Biderman… - Intl. Conference on …, 2009 - girardin.org
This paper illustrates how aggregated mobile phone network activity logs provide
anonymous information that reveals valuable insight into the presence of tourists visiting a …

Edge-based passive crowd monitoring through WiFi Beacons

K Gebru, M Rapelli, R Rusca, C Casetti… - Computer …, 2022 - Elsevier
Tracking people's flows has become crucial, not only for safety and security, but also for
numerous practical business applications and better management of urban spaces, facilities …

[HTML][HTML] Human mobility characterization from cellular network data

R Becker, R Cáceres, K Hanson, S Isaacman… - Communications of the …, 2013 - dl.acm.org
Human mobility characterization from cellular network data Page 1 74 CoMMuNiCatioNs of
tHe aCM | jAnuARY 2013 | voL. 56 | no. 1 contributed articles Ill us t R a t IO nb ya lICI a Kub Is …

[HTML][HTML] Inferring human mobility using communication patterns

V Palchykov, M Mitrović, HH Jo, J Saramäki, RK Pan - Scientific reports, 2014 - nature.com
Understanding the patterns of mobility of individuals is crucial for a number of reasons, from
city planning to disaster management. There are two common ways of quantifying the …

Activity-based human mobility patterns inferred from mobile phone data: A case study of Singapore

S Jiang, J Ferreira, MC Gonzalez - IEEE Transactions on Big …, 2017 - ieeexplore.ieee.org
In this study, with Singapore as an example, we demonstrate how we can use mobile phone
call detail record (CDR) data, which contains millions of anonymous users, to extract …

Analysis methods for extracting knowledge from large-scale wifi monitoring to inform building facility planning

AJ Ruiz-Ruiz, H Blunck, TS Prentow… - 2014 IEEE …, 2014 - ieeexplore.ieee.org
The optimization of logistics in large building complexes with many resources, such as
hospitals, require realistic facility management and planning. Current planning practices rely …

Understanding aggregate human mobility patterns using passive mobile phone location data: A home-based approach

Y Xu, SL Shaw, Z Zhao, L Yin, Z Fang, Q Li - Transportation, 2015 - Springer
Advancements of information, communication and location-aware technologies have made
collections of various passively generated datasets possible. These datasets provide new …

From traces to trajectories: How well can we guess activity locations from mobile phone traces?

C Chen, L Bian, J Ma - Transportation Research Part C: Emerging …, 2014 - Elsevier
Passively generated mobile phone dataset is emerging as a new data source for research in
human mobility patterns. Information on individuals' trajectories is not directly available from …