Exploring Home and Work Locations in a City from Mobile Phone Data

被引：10

作者：

Tongsinoot, Lumpsum ^{[1
]}

Muangsin, Veera ^{[2
]}

机构：

[1] Chulalongkorn Univ, Dept Comp Engn, Fac Engn, Bangkok, Thailand

[2] Chulalongkorn Univ, CU Big Data Analyt & IoT Ctr CUBIC, Dept Comp Engn, Fac Engn, Bangkok, Thailand

来源：

2017 19TH IEEE INTERNATIONAL CONFERENCE ON HIGH PERFORMANCE COMPUTING AND COMMUNICATIONS (HPCC) / 2017 15TH IEEE INTERNATIONAL CONFERENCE ON SMART CITY (SMARTCITY) / 2017 3RD IEEE INTERNATIONAL CONFERENCE ON DATA SCIENCE AND SYSTEMS (DSS) | 2017年

关键词：

Location data; Call Detail Records;

D O I：

10.1109/HPCC-SmartCity-DSS.2017.16

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

Recently, mobile phone call detail records (CDR) have been used to study mobility patterns in cities. Since home and workplace are the most important places in people's lives and define the structure and activity patterns of the city, identifying home and work locations and home-work commuting patterns are of much interest. However, due to decreasing usage of voice calls and SMS, and low usage while people staying at home, identifying home and work locations are getting more difficult. In this paper, we develop a method to exploit daily-aggregated internet usage data (G-CDR) in addition to CDR for identifying work locations. We also develop a method for identifying home locations based on detecting sleeping time. This method can significantly increase home detection success rate and accuracy. From the identified home and work locations, we have explored the population distribution and commuting patterns of people in Bangkok.

引用

页码：123 / 129

页数：7

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