Okmi, Mohammed and Por, Lip Yee and Ang, Tan Fong and Ku, Chin Soon (2023) Mobile phone data: A survey of techniques, features, and applications. Sensors, 23 (2). ISSN 1424-8220, DOI https://doi.org/10.3390/s23020908.
Full text not available from this repository.Abstract
Due to the rapid growth in the use of smartphones, the digital traces (e.g., mobile phone data, call detail records) left by the use of these devices have been widely employed to assess and predict human communication behaviors and mobility patterns in various disciplines and domains, such as urban sensing, epidemiology, public transportation, data protection, and criminology. These digital traces provide significant spatiotemporal (geospatial and time-related) data, revealing people's mobility patterns as well as communication (incoming and outgoing calls) data, revealing people's social networks and interactions. Thus, service providers collect smartphone data by recording the details of every user activity or interaction (e.g., making a phone call, sending a text message, or accessing the internet) done using a smartphone and storing these details on their databases. This paper surveys different methods and approaches for assessing and predicting human communication behaviors and mobility patterns from mobile phone data and differentiates them in terms of their strengths and weaknesses. It also gives information about spatial, temporal, and call characteristics that have been extracted from mobile phone data and used to model how people communicate and move. We survey mobile phone data research published between 2013 and 2021 from eight main databases, namely, the ACM Digital Library, IEEE Xplore, MDPI, SAGE, Science Direct, Scopus, SpringerLink, and Web of Science. Based on our inclusion and exclusion criteria, 148 studies were selected.
| Item Type: | Article |
|---|---|
| Funders: | Malaysian Ministry of Higher Education through the Fundamental Research Grant Scheme (FRGS) (Grant No: FRGS/1/2018/ICT04/UM/02/17) |
| Uncontrolled Keywords: | Mobile phone data; Call detail records (CDRs); Mobility patterns; Communication behaviors; Urban crime patterns; Urban sensors; Smartphones |
| Subjects: | H Social Sciences > HE Transportation and Communications Q Science > QA Mathematics > QA75 Electronic computers. Computer science |
| Divisions: | Faculty of Computer Science & Information Technology > Department of Computer System & Technology |
| Depositing User: | Ms Zaharah Ramly |
| Date Deposited: | 30 Nov 2023 02:29 |
| Last Modified: | 30 Nov 2023 02:37 |
| URI: | http://eprints.um.edu.my/id/eprint/39080 |
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