Activity-Aware Map: Identifying human daily activity pattern using mobile phone data [book chapter]
Being able to understand dynamics of human mobility is essential for urban planning and transportation management. Besides geographic space, in this paper, we characterize mobility in a profile-based space (activity-aware map) that describes most probable activity associated with a specific area of...
| Main Authors: | , , , , |
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| Other Authors: | |
| Format: | Article |
| Language: | en_US |
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Springer-Verlag
2013
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| Online Access: | http://hdl.handle.net/1721.1/79592 https://orcid.org/0000-0003-2026-5631 |
| _version_ | 1826212843065704448 |
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| author | Phithakkitnukoon, Santi Horanont, Teerayut Shibasaki, Ryosuke Ratti, Carlo Di Lorenzo, Giusy |
| author2 | Massachusetts Institute of Technology. Department of Urban Studies and Planning |
| author_facet | Massachusetts Institute of Technology. Department of Urban Studies and Planning Phithakkitnukoon, Santi Horanont, Teerayut Shibasaki, Ryosuke Ratti, Carlo Di Lorenzo, Giusy |
| author_sort | Phithakkitnukoon, Santi |
| collection | MIT |
| description | Being able to understand dynamics of human mobility is essential for urban planning and transportation management. Besides geographic space, in this paper, we characterize mobility in a profile-based space (activity-aware map) that describes most probable activity associated with a specific area of space. This, in turn, allows us to capture the individual daily activity pattern and analyze the correlations among different people’s work area’s profile. Based on a large mobile phone data of nearly one million records of the users in the central Metro-Boston area, we find a strong correlation in daily activity patterns within the group of people who share a common work area’s profile. In addition, within the group itself, the similarity in activity patterns decreases as their work places become apart. |
| first_indexed | 2024-09-23T15:38:48Z |
| format | Article |
| id | mit-1721.1/79592 |
| institution | Massachusetts Institute of Technology |
| language | en_US |
| last_indexed | 2024-09-23T15:38:48Z |
| publishDate | 2013 |
| publisher | Springer-Verlag |
| record_format | dspace |
| spelling | mit-1721.1/795922022-10-02T03:08:16Z Activity-Aware Map: Identifying human daily activity pattern using mobile phone data [book chapter] Phithakkitnukoon, Santi Horanont, Teerayut Shibasaki, Ryosuke Ratti, Carlo Di Lorenzo, Giusy Massachusetts Institute of Technology. Department of Urban Studies and Planning Massachusetts Institute of Technology. SENSEable City Laboratory Phithakkitnukoon, Santi Horanont, Teerayut Lorenzo, Giusy Di Ratti, Carlo Being able to understand dynamics of human mobility is essential for urban planning and transportation management. Besides geographic space, in this paper, we characterize mobility in a profile-based space (activity-aware map) that describes most probable activity associated with a specific area of space. This, in turn, allows us to capture the individual daily activity pattern and analyze the correlations among different people’s work area’s profile. Based on a large mobile phone data of nearly one million records of the users in the central Metro-Boston area, we find a strong correlation in daily activity patterns within the group of people who share a common work area’s profile. In addition, within the group itself, the similarity in activity patterns decreases as their work places become apart. AT & T Foundation National Science Foundation (U.S.) MIT-Portugal Program Volkswagen of America (Electronic Research Lab) 2013-07-12T16:39:17Z 2013-07-12T16:39:17Z 2010 Article http://purl.org/eprint/type/ConferencePaper 0302-9743 1611-3349 http://hdl.handle.net/1721.1/79592 Phithakkitnukoon, Santi, Horanont, Teerayut, Di Lorenzo, Giusy, Shibasaki, Ryosuke, and Ratti, Carlo. (2010) “Activity-Aware Map: Identifying Human Daily Activity Pattern Using Mobile Phone Data.” In Albert Ali Salah, Theo Gevers, Nicu Sebe, and Alessandro Vinciarelli (eds.). "Human Behavior Understanding" (pp. 14-25) Berlin: Springer-Verlag (Lecture Notes in Computer Science; 6219). https://orcid.org/0000-0003-2026-5631 en_US http://link.springer.com/chapter/10.1007%2F978-3-642-14715-9_3 Lecture Notes in Computer Science Creative Commons Attribution-Noncommercial-Share Alike 3.0 http://creativecommons.org/licenses/by-nc-sa/3.0/ application/pdf Springer-Verlag MIT web domain |
| spellingShingle | Phithakkitnukoon, Santi Horanont, Teerayut Shibasaki, Ryosuke Ratti, Carlo Di Lorenzo, Giusy Activity-Aware Map: Identifying human daily activity pattern using mobile phone data [book chapter] |
| title | Activity-Aware Map: Identifying human daily activity pattern using mobile phone data [book chapter] |
| title_full | Activity-Aware Map: Identifying human daily activity pattern using mobile phone data [book chapter] |
| title_fullStr | Activity-Aware Map: Identifying human daily activity pattern using mobile phone data [book chapter] |
| title_full_unstemmed | Activity-Aware Map: Identifying human daily activity pattern using mobile phone data [book chapter] |
| title_short | Activity-Aware Map: Identifying human daily activity pattern using mobile phone data [book chapter] |
| title_sort | activity aware map identifying human daily activity pattern using mobile phone data book chapter |
| url | http://hdl.handle.net/1721.1/79592 https://orcid.org/0000-0003-2026-5631 |
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