Spatio-temporal analysis of mobile phone data for interaction recognition

Mohammadhossein Ghahramani, Mengchu Zhou, Chi Tin Hon

Research output: Chapter in Book/Report/Conference proceedingConference contribution

4 Scopus citations

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.

Original languageEnglish (US)
Title of host publicationICNSC 2018 - 15th IEEE International Conference on Networking, Sensing and Control
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1-6
Number of pages6
ISBN (Electronic)9781538650530
DOIs
StatePublished - May 18 2018
Event15th IEEE International Conference on Networking, Sensing and Control, ICNSC 2018 - Zhuhai, China
Duration: Mar 27 2018Mar 29 2018

Publication series

NameICNSC 2018 - 15th IEEE International Conference on Networking, Sensing and Control

Other

Other15th IEEE International Conference on Networking, Sensing and Control, ICNSC 2018
CountryChina
CityZhuhai
Period3/27/183/29/18

All Science Journal Classification (ASJC) codes

  • Instrumentation
  • Artificial Intelligence
  • Computer Networks and Communications
  • Control and Optimization
  • Modeling and Simulation

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