Deakin University
Browse

File(s) under permanent embargo

ShareLikesCrowd: mobile analytics for participatory sensing and crowd-sourcing applications

Version 2 2024-06-05, 01:33
Version 1 2019-06-27, 14:48
conference contribution
posted on 2013-01-01, 00:00 authored by Arkady ZaslavskyArkady Zaslavsky, P P Jayaraman, S Krishnaswamy
Data and continuous data streams from mobile users/devices are becoming increasingly important for numerous applications including urban modelling, transportation, and more recently for mobile crowd-sensing to support citizen journalism and participatory sensing where sensor informatics and social networking meet. While significant efforts have focused towards the analysis of mobile user data, a key challenge that needs to be addressed in order to realize the full-potential is to address the scalability issues of real-time data collection and processing at run time. By scalability, we refer to both the challenges of data capture from a large number of users, as well as the issues of energy consumed on individual devices as a result of that capture. In this paper, we present mobile/on-board data stream mining as an effective approach to address the scalability issues of mobile data collection and run-time processing and as a significant component of mobile run-time analytics. We present experimental evaluation using the Nokia mobile data challenge open track dataset to show the significant energy and bandwidth savings that mobile data stream mining can achieve with no significant loss of useful information in this process.

History

Event

IEEE Computer Society. Conference (29th : 2013 : Brisbane, Qld.)

Series

IEEE Computer Society Conference

Pagination

128 - 135

Publisher

Institute of Electrical and Electronics Engineers

Location

Brisbane, Qld.

Place of publication

Piscataway, N.J.

Start date

2013-04-08

End date

2013-04-11

ISSN

1084-4627

ISBN-13

9781467353021

Language

eng

Publication classification

E1.1 Full written paper - refereed

Copyright notice

2013, IEEE

Editor/Contributor(s)

[Unknown]

Title of proceedings

ICDE 2013 : Proceedings of the 2013 IEEE 29th International Conference on Data Engineering Workshops

Usage metrics

    Research Publications

    Categories

    No categories selected

    Exports

    RefWorks
    BibTeX
    Ref. manager
    Endnote
    DataCite
    NLM
    DC