Mobile Phone Data Analysis: A Spatial Exploration Toward Hotspot Detection

Mohammadhossein Ghahramani, Mengchu Zhou, Chi Tin Hon

Research output: Contribution to journalArticlepeer-review

26 Scopus citations

Abstract

The percentage of processed large-scale heterogeneous data is exploding and technology is the most obvious reason for the big data issue. Nowadays, the results of data expansion are showing up in different fields. The users' contextual data are valuable in engineering and business domains, e.g., transportation, location-based services, and advertisement industry. Take mobile phones as an example. There are billions of subscriptions worldwide and sensor devices are digitizing people interactions. The data volume generated by mobile phones and the need to make better, fact-based, and real-time decisions, are the challenges facing researchers. Recently, new technologies based on cloud computing have emerged to process and analyze a large volume of data. We have utilized such technologies for the analysis of call detail records with the collaboration with a telecommunications company. We present an exploratory spatial data analysis algorithm and its analysis results. To prioritize different areas, detecting hotspots in a fast and accurate way is our objective. The findings of this research work can be helpful for urban planning and development as well as telecommunication infrastructure upgrading.

Original languageEnglish (US)
JournalIEEE Transactions on Automation Science and Engineering
DOIs
StateAccepted/In press - Feb 20 2018

All Science Journal Classification (ASJC) codes

  • Control and Systems Engineering
  • Electrical and Electronic Engineering

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