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Mobile Computing: Aggregated Human Mobility Patterns

S. John Grasias1

Section:Research Paper, Product Type: Journal Paper
Volume-6 , Issue-7 , Page no. 1271-1273, Jul-2018

CrossRef-DOI:   https://doi.org/10.26438/ijcse/v6i7.12711273

Online published on Jul 31, 2018

Copyright © S. John Grasias . This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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IEEE Style Citation: S. John Grasias, “Mobile Computing: Aggregated Human Mobility Patterns,” International Journal of Computer Sciences and Engineering, Vol.6, Issue.7, pp.1271-1273, 2018.

MLA Style Citation: S. John Grasias "Mobile Computing: Aggregated Human Mobility Patterns." International Journal of Computer Sciences and Engineering 6.7 (2018): 1271-1273.

APA Style Citation: S. John Grasias, (2018). Mobile Computing: Aggregated Human Mobility Patterns. International Journal of Computer Sciences and Engineering, 6(7), 1271-1273.

BibTex Style Citation:
@article{Grasias_2018,
author = {S. John Grasias},
title = {Mobile Computing: Aggregated Human Mobility Patterns},
journal = {International Journal of Computer Sciences and Engineering},
issue_date = {7 2018},
volume = {6},
Issue = {7},
month = {7},
year = {2018},
issn = {2347-2693},
pages = {1271-1273},
url = {https://www.ijcseonline.org/full_paper_view.php?paper_id=2598},
doi = {https://doi.org/10.26438/ijcse/v6i7.12711273}
publisher = {IJCSE, Indore, INDIA},
}

RIS Style Citation:
TY - JOUR
DO = {https://doi.org/10.26438/ijcse/v6i7.12711273}
UR - https://www.ijcseonline.org/full_paper_view.php?paper_id=2598
TI - Mobile Computing: Aggregated Human Mobility Patterns
T2 - International Journal of Computer Sciences and Engineering
AU - S. John Grasias
PY - 2018
DA - 2018/07/31
PB - IJCSE, Indore, INDIA
SP - 1271-1273
IS - 7
VL - 6
SN - 2347-2693
ER -

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Abstract

Location-based mobile applications are steadily gaining popularity across the world. These applications require information about user’s current location to access different kind of services. This paper discover aggregated mobility and place visiting patterns of people in developing countries using one CDR (Call Detail Records) dataset collected in Ivory Coast and two finegrained location information datasets collected in India and Switzerland. We have compared these mobility patterns with existing studies for developed countries and found several differences. One of the difference is that people in developing countries are less likely to travel long distance on weekends as compared to developed countries. This paper tries to fill that gap and provide practical and promising solutions to enable location-based services on both feature phones and smartphones using low energy location interfaces.

Key-Words / Index Term

Aggregated, Call Detail Records, Clustering, WIFI

References

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