Abstract
Human mobility knowledge is key for urban planning or mobility model's design. Therefore, estimating reliable mobility parameters is crucial to lay an unbiased foundation. However, most works estimating such features rely on datasets made up of the history of mobile network cells where the user is located when she makes active use of the network, known as Call Data Records (CDRs), or every time their device connects to a new cell, without taking into account cell changes not caused by movement. Could we accurately characterize human mobility with such datasets? In this work we consider three approaches to collect network-based mobility data, propose three filtering techniques to delete cell changes not caused by movement and compare mobility features extracted from the traces collected with each approach. The analysis unveils the need for a filtering step to avoid important biases, and the negative impact that using CDRs may have in estimating mobility parameters. © 2014 IEEE.
Recommended Citation
A. Rodriguez-Carrion et al., "Impact of Location History Collection Schemes on Observed Human Mobility Features," 2014 IEEE International Conference on Pervasive Computing and Communication Workshops, PERCOM WORKSHOPS 2014, pp. 254 - 259, article no. 6815213, Institute of Electrical and Electronics Engineers, Jan 2014.
The definitive version is available at https://doi.org/10.1109/PerComW.2014.6815213
Department(s)
Computer Science
Document Type
Article - Conference proceedings
Document Version
Citation
File Type
text
Language(s)
English
Rights
© 2024 Institute of Electrical and Electronics Engineers, All rights reserved.
Publication Date
01 Jan 2014
