Spatio-temporal analysis of mobile phone data for interaction recognition
Document Type
Conference Proceeding
Publication Date
5-18-2018
Abstract
Since the last decade mobile phones have changed people's lives. Mobile phone data can be utilized to derive the spatio-temporal data of subscriptions' whereabouts. It has been possible to study the mobility and traffic estimation with applications ranging from disaster management to disease epidemiology. In this work, we have focused on the use of Call Detail Records (CDRs) to explore and interpret patterns embedded in interaction flows of people through their mobile phone calls. To do so, we consider the geographical context of cell towers to discover structures of spatio-temporal interaction communities in Macau. We have explored the inter and intra-polygon interaction flows. The results suggest that subscriptions tend to communicate within a spatial-proximity community. Understanding such insight is essential for resource optimization in network planning and content distribution.
Identifier
85048229520 (Scopus)
ISBN
[9781538650530]
Publication Title
Icnsc 2018 15th IEEE International Conference on Networking Sensing and Control
External Full Text Location
https://doi.org/10.1109/ICNSC.2018.8361374
First Page
1
Last Page
6
Grant
119/2014/A3
Fund Ref
Fundo para o Desenvolvimento das Ciências e da Tecnologia
Recommended Citation
Ghahramani, Mohammadhossein; Zhou, Mengchu; and Hon, Chi Tin, "Spatio-temporal analysis of mobile phone data for interaction recognition" (2018). Faculty Publications. 8674.
https://digitalcommons.njit.edu/fac_pubs/8674
