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Activity-Based Human Mobility Patterns Inferred from Mobile Phone Data: A Case Study of Singapore

Activity-Based Human Mobility Patterns Inferred from Mobile Phone Data: A Case Study of Singapore

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 Activity-Based Human Mobility Patterns Inferred from Mobile Phone Data: A Case Study of Singapore

Singapore as an example, we demonstrate how we can use mobile phone call detail record (CDR) data,which contains millions of anonymous users, to extract individual mobility networks comparable to the activity-based approach. Suchan approach is widely used in the transportation planning practice to develop urban micro simulations of individual daily activities andtravel; yet it depends highly on detailed travel survey data to capture individual activity-based behavior. We provide an innovative data mining framework that synthesizes the state-of-the-art techniques in extracting mobility patterns from raw mobile phone CDR data, and design a pipeline that can translate the massive and passive mobile phone records to meaningful spatial human mobility patterns readily interpretable for urban and transportation planning purposes. With growing ubiquitous mobile sensing, and shrinking labor and fiscal resources in the public sector globally, the method presented in this research can be used as a low-cost alternative for transportation and planning agencies to understand the human activity patterns in cities, and provide targeted plans for future sustainable development.


 


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  • Model: PROJ7619
  • 999 Units in Stock
  • Manufactured by: ClickMyProjects

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This product was added to our catalog on Tuesday 08 August, 2017.

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