research-article

An adaptive approach for online segmentation of multi-dimensional mobile data

Authors:

Karl AbererAuthors Info & Claims

MobiDE '12: Proceedings of the Eleventh ACM International Workshop on Data Engineering for Wireless and Mobile Access

Pages 7 - 14

https://doi.org/10.1145/2258056.2258059

Published: 20 May 2012 Publication History

Abstract

With increasing availability of mobile sensing devices including smartphones, online mobile data segmentation becomes an important topic in reconstructing and understanding mobile data. Traditional approaches like online time series segmentation either use a fixed model or only apply an adaptive model on one dimensional data; it turns out that such methods are not very applicable to build online segmentation for multiple dimensional mobile sensor data (e.g., 3D accelerometer or 11 dimension features like 'mean', 'variance', 'covariance', 'magnitude', etc).

In this paper, we design an adaptive model for segmenting real-time accelerometer data from smartphones, which is able to (a) dynamically select suitable dimensions to build a model, and (b) adaptively pick up a proper model. In addition to using the traditional residual-style regression errors to evaluate time series segmentation, we design a rich metric to evaluate mobile data segmentation results, including (1) traditional regression error, (2) information retrieval style measurements (i.e., precision, recall, F-measure), and (3) segmentation time delay.

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Cited By

Mishra SMohapatra SMishra BSahoo S(2021)Analysis of Mobile Cloud ComputingResearch Anthology on Architectures, Frameworks, and Integration Strategies for Distributed and Cloud Computing10.4018/978-1-7998-5339-8.ch001(1-24)Online publication date: 2021
https://doi.org/10.4018/978-1-7998-5339-8.ch001
Wang XLiao WGuo YYu LWang QPan MLi P(2019)PerRNN: Personalized Recurrent Neural Networks for Acceleration-Based Human Activity RecognitionICC 2019 - 2019 IEEE International Conference on Communications (ICC)10.1109/ICC.2019.8761931(1-6)Online publication date: May-2019
https://doi.org/10.1109/ICC.2019.8761931
Wang XZhang JYu ZMao EPeriaswamy SPatton J(2019)RFThermometer: A Temperature Estimation System with Commercial UHF RFID TagsICC 2019 - 2019 IEEE International Conference on Communications (ICC)10.1109/ICC.2019.8761625(1-6)Online publication date: May-2019
https://doi.org/10.1109/ICC.2019.8761625
Show More Cited By

Index Terms

An adaptive approach for online segmentation of multi-dimensional mobile data
1. Human-centered computing
  1. Collaborative and social computing
    1. Collaborative and social computing systems and tools
  2. Visualization
    1. Visualization application domains
      1. Geographic visualization
2. Information systems
  1. Information systems applications
    1. Data mining
    2. Spatial-temporal systems
  2. World Wide Web

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Information

Published In

cover image ACM Conferences

MobiDE '12: Proceedings of the Eleventh ACM International Workshop on Data Engineering for Wireless and Mobile Access

May 2012

83 pages

ISBN:9781450314428

DOI:10.1145/2258056

General Chairs:
George Kollios
Boston University
,
Yufei Tao
Chinese University of Hong Kong, Hong Kong, China
,
Program Chairs:
Mario A. Nascimento
University of Alberta, Canada
,
Mohamed A. Sharaf
University of Queensland, Australia
,
Publications Chair:
Man Lung Yiu
Hong Kong Polytechnic University, Hong Kong

Copyright © 2012 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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SIGMOD: ACM Special Interest Group on Management of Data

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 20 May 2012

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Seventh Framework Programme

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SIGMOD/PODS '12

Sponsor:

SIGMOD

SIGMOD/PODS '12: International Conference on Management of Data

May 20, 2012

Arizona, Scottsdale

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Overall Acceptance Rate 23 of 59 submissions, 39%

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Citations

Cited By

Mishra SMohapatra SMishra BSahoo S(2021)Analysis of Mobile Cloud ComputingResearch Anthology on Architectures, Frameworks, and Integration Strategies for Distributed and Cloud Computing10.4018/978-1-7998-5339-8.ch001(1-24)Online publication date: 2021
https://doi.org/10.4018/978-1-7998-5339-8.ch001
Wang XLiao WGuo YYu LWang QPan MLi P(2019)PerRNN: Personalized Recurrent Neural Networks for Acceleration-Based Human Activity RecognitionICC 2019 - 2019 IEEE International Conference on Communications (ICC)10.1109/ICC.2019.8761931(1-6)Online publication date: May-2019
https://doi.org/10.1109/ICC.2019.8761931
Wang XZhang JYu ZMao EPeriaswamy SPatton J(2019)RFThermometer: A Temperature Estimation System with Commercial UHF RFID TagsICC 2019 - 2019 IEEE International Conference on Communications (ICC)10.1109/ICC.2019.8761625(1-6)Online publication date: May-2019
https://doi.org/10.1109/ICC.2019.8761625
Wang ZGuo YLi ZTang MQi TWang J(2019)Research on Microblog Rumor Events Detection via Dynamic Time Series Based GRU ModelICC 2019 - 2019 IEEE International Conference on Communications (ICC)10.1109/ICC.2019.8761457(1-6)Online publication date: May-2019
https://doi.org/10.1109/ICC.2019.8761457
Mishra SMohapatra SMishra BSahoo S(2018)Analysis of Mobile Cloud ComputingApplications of Security, Mobile, Analytic, and Cloud (SMAC) Technologies for Effective Information Processing and Management10.4018/978-1-5225-4044-1.ch005(81-104)Online publication date: 2018
https://doi.org/10.4018/978-1-5225-4044-1.ch005
Badawy RRaykov YEvers LBloem BFaber MZhan AClaes KLittle M(2018)Automated Quality Control for Sensor Based Symptom Measurement Performed Outside the LabSensors10.3390/s1804121518:4(1215)Online publication date: 16-Apr-2018
https://doi.org/10.3390/s18041215
Jensen SPedersen TThomsen C(2018)ModelarDBProceedings of the VLDB Endowment10.14778/3236187.323621511:11(1688-1701)Online publication date: 1-Jul-2018
https://dl.acm.org/doi/10.14778/3236187.3236215
Chou GOzay NBerenson D(2018)Incremental Segmentation of ARX ModelsIFAC-PapersOnLine10.1016/j.ifacol.2018.09.22251:15(587-592)Online publication date: 2018
https://doi.org/10.1016/j.ifacol.2018.09.222
Liono JQin ASalim FHara TShigeno H(2016)Optimal time window for temporal segmentation of sensor streams in multi-activity recognitionProceedings of the 13th International Conference on Mobile and Ubiquitous Systems: Computing, Networking and Services10.1145/2994374.2994388(10-19)Online publication date: 28-Nov-2016
https://dl.acm.org/doi/10.1145/2994374.2994388
Lim JKim JKwon D(2016)Multidimensional evaluation and analysis of motion segmentation for inertial measurement unit applicationsMultimedia Tools and Applications10.1007/s11042-015-2812-175:18(10907-10934)Online publication date: 1-Sep-2016
https://dl.acm.org/doi/10.1007/s11042-015-2812-1
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