The ncsu/mobilitymodels dataset (v. 2009-07-23)
Human mobility data collected from five different sites.
Contributed by Injong Rhee, Minsu Shin, Seongik Hong, Kyunghan Lee, Seongjoon Kim, Song Chong.
We collected human mobilicty traces from five different sites - two university campuses (NCSU and KAIST), New York City, Disney World (Orlando), and North Carolina state fair.
details of the ncsu/mobilitymodels dataset (v. 2009-07-23)
- last modified
-
2009-07-21
- reason for most recent change
-
the initial version
- release date
-
2009-07-23
- date/time of measurement start
-
2006-08-26
- date/time of measurement end
-
2008-04-18
- website
-
netsrv.csc.ncsu.edu/twiki/bin/view/Main/MobilityModels
- network type
-
GPS (Global Positioning System)
- network type
-
DTN (Delay or Disruption Tolerant Network)
- collection environment
-
Five sites are chosen for collecting human mobility traces. These are two university campuses (NCSU and KAIST), New York City, Disney World (Orlando), and North Carolina state fair.
- network configuration
-
Garmin GPS 60CSx handheld receivers are used for data collection which are WAAS (Wide Area Augmentation System) capable with a position accuracy of better than three meters 95 percent of the time, in North America.
- data collection methodology
-
The GPS receivers take reading of their current positions at every 10 seconds and record them into a daily track log.
- limitation
-
Occasionally, track information has discontinuity mainly when bearers move indoor where GPS signals cannot be received.
- note
-
The Campus I traces are taken by 20 students. The participants
in Campus I were randomly selected students who took a course
in the computer science department. Every week, 2 or 3 randomly
chosen students carried the GPS receivers for their daily regular
activities.
The Campus II traces are taken by 32 students who live in a campus
dormitory.
The New York City traces were obtained from 12 volunteers living in
Manhattan or its vicinity. Most of the participants have offices
in Manhattan. Their track logs contain relatively long distance
travels because of their long commuting paths. Their means of
travel include subway trains, buses and mostly walking.
The State fair track logs were collected from 8 volunteers who
visited a local state fair that includes many street arcades, small
street food stands and showcases. The event was very popular
and attended by more than one thousand people daily for two
weeks. The site is completely outdoor and is smallest among
all the sites. Each participant in the State fair scenario spent
less than three hours in the site.
The Disney World traces were obtained from nineteen volunteers
who spent their thanksgiving or Christmas holidays in Disney World,
Florida, USA. For our study, we use only the track logs from
the inside of the theme parks. The participants mainly walked
in the parks and occasionally rode trolleys.
This dataset contains the following traceset:
GPS
Daily GPS track log collected from five different sites.
quick access to download the traceset
- download the Readme.txt (from the ncsu/mobilitymodels/GPS trace) file
- from a CRAWDAD mirror: US
UK
size="4.0KB" type="txt" md5="d4dd64f7cb18f8db20af994278fc5b35"
- download the Traces_TimeXY_30sec_txt.tar.gz (from the ncsu/mobilitymodels/GPS trace) file
- from a CRAWDAD mirror: US
UK
size="3.9MB" type="gz" md5="6e806490002fa91ef6d8e4016423faf9"
- Injong Rhee
rhee@ncsu.edu
North Carolina State University
Computer Science
Associate Professor
Department of computer Science North Carolina State University, NC 27606.
www4.ncsu.edu/~rhee/
- Minsu Shin
Hanoro Telecom
- Seongik Hong
shong@ncsu.edu
North Carolina State University
Computer Science
Ph.D Student
2240 EBII Centennial Campus, North Carolina State University, Raleigh, NC 27695
www4.ncsu.edu/~shong/
- Kyunghan Lee
khlee@unist.ac.kr
UNIST (Ulsan National Institute of Science and Technology)
School of ECE
Rm 301-5, EB 106, UNIST-gil 50, Ulsan, Korea
sites.google.com/site/khanleepage/
- Seongjoon Kim
North Carolina State University
Computer Science
Postdoc
Department of computer Science North Carolina State University, NC 27606.
- Song Chong
song@ee.kaist.ac.kr
KAIST
Electrical Engineering
Professor
School of EECS, KAIST, 373-1 Guseong-Dong, Yuseong-Gu, Daejeon 305-701, Korea
netsys.kaist.ac.kr/~song/
how to cite this dataset
When writing a paper that uses CRAWDAD datasets, we would appreciate it if you could cite both the authors of the dataset and CRAWDAD itself, and identify the exact dataset using the appropriate version number. For this dataset, this citation would look like:
Injong Rhee, Minsu Shin, Seongik Hong, Kyunghan Lee, Seongjoon Kim, Song Chong, CRAWDAD dataset ncsu/mobilitymodels (v. 2009‑07‑23), downloaded from https://crawdad.org/ncsu/mobilitymodels/20090723, https://doi.org/10.15783/C7X302, Jul 2009.
We also provide bibliographic information in common citation formats below:
@misc{ncsu-mobilitymodels-20090723,
author = {Injong Rhee and Minsu Shin and Seongik Hong and Kyunghan Lee and Seongjoon Kim and Song Chong},
title = {{CRAWDAD} dataset ncsu/mobilitymodels (v. 2009-07-23)},
howpublished = {Downloaded from \url{https://crawdad.org/ncsu/mobilitymodels/20090723}},
doi = {10.15783/C7X302},
month = jul,
year = 2009
}
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TY - DATA
TI - CRAWDAD dataset ncsu/mobilitymodels (v. 2009-07-23)
UR - https://crawdad.org/ncsu/mobilitymodels/20090723
PY - 2009/07/23/
AU - Injong Rhee
AU - Minsu Shin
AU - Seongik Hong
AU - Kyunghan Lee
AU - Seongjoon Kim
AU - Song Chong
DO - 10.15783/C7X302
ER -
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