research-article

GPS and accelerometer time stamps: proper data handling and avoiding pitfalls

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Philip M. HurvitzAuthors Info & Claims

UrbanGIS'15: Proceedings of the 1st International ACM SIGSPATIAL Workshop on Smart Cities and Urban Analytics

Pages 94 - 100

https://doi.org/10.1145/2835022.2835038

Published: 03 November 2015 Publication History

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Abstract

Introduction.

Maintaining correct time stamp values is critical for management and analysis of time-indexed data, including GPS and accelerometry.

Methods.

Objective location and activity data were collected for one week periods in four projects, for 1551 subjects, using Qstarz BT1000 GPS data loggers and Actigraph GT3X accelerometers, in King County, WA. Data collection spanned September, 2011 to April, 2014, with analysis in May, 2014. GPS data were exported using QTravel and Actilife software, and processed under Windows XP and 7, using Microsoft Excel and Access, as well as two free and open-source applications, the R statistical programming environment and the database package, PostgreSQL.

Results and conclusion.

Time stamp errors resulted from the export of GPS data from QTravel and accelerometry data from Actilife for files spanning the Daylight Savings Time (DST) transition. QTravel has a specific problem in its interaction with Windows' default time zone settings. Excel and Access did not properly handle either time zone or DST, whereas both R and PostgreSQL did. Practices for preventing time stamp errors from Actigraph accelerometers and Qstarz GPS units are presented.

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Cited By

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Mohan JRanganathan P(2023)False Data Injection (FDI) Modeling and Detection in Global Positioning Systems (GPS) for UAS Environments2023 Congress in Computer Science, Computer Engineering, & Applied Computing (CSCE)10.1109/CSCE60160.2023.00157(929-936)Online publication date: 24-Jul-2023
https://doi.org/10.1109/CSCE60160.2023.00157
Gough CLewis LBarr CMaeder AGeorge S(2021)Community participation of community dwelling older adults: a cross-sectional studyBMC Public Health10.1186/s12889-021-10592-421:1Online publication date: 29-Mar-2021
https://doi.org/10.1186/s12889-021-10592-4
Friedrich TKrejca MLagodzinski JRizzo MZahn A(2020)Memetic Genetic Algorithms for Time Series Compression by Piecewise Linear ApproximationNeural Information Processing10.1007/978-3-030-63836-8_49(592-604)Online publication date: 19-Nov-2020
https://doi.org/10.1007/978-3-030-63836-8_49
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Index Terms

GPS and accelerometer time stamps: proper data handling and avoiding pitfalls
1. Information systems
  1. Information systems applications
2. Software and its engineering
  1. Software notations and tools
    1. General programming languages
      1. Language features
        Data types and structures

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Published In

UrbanGIS'15: Proceedings of the 1st International ACM SIGSPATIAL Workshop on Smart Cities and Urban Analytics

November 2015

128 pages

ISBN:9781450339735

DOI:10.1145/2835022

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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SIGGRAPH: ACM Special Interest Group on Computer Graphics and Interactive Techniques

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 03 November 2015

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Research-article
Research
Refereed limited

Funding Sources

National Institute on Aging
National Heart, Blood, and Lung Institute
National Institute of Diabetes and Digestive and Kidney Diseases

Conference

SIGSPATIAL'15

Sponsor:

SIGSPATIAL

SIGSPATIAL'15: 23rd SIGSPATIAL International Conference on Advances in Geographic Information Systems

November 3 - 6, 2015

WA, Bellevue, USA

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Cited By

View all

Mohan JRanganathan P(2023)False Data Injection (FDI) Modeling and Detection in Global Positioning Systems (GPS) for UAS Environments2023 Congress in Computer Science, Computer Engineering, & Applied Computing (CSCE)10.1109/CSCE60160.2023.00157(929-936)Online publication date: 24-Jul-2023
https://doi.org/10.1109/CSCE60160.2023.00157
Gough CLewis LBarr CMaeder AGeorge S(2021)Community participation of community dwelling older adults: a cross-sectional studyBMC Public Health10.1186/s12889-021-10592-421:1Online publication date: 29-Mar-2021
https://doi.org/10.1186/s12889-021-10592-4
Friedrich TKrejca MLagodzinski JRizzo MZahn A(2020)Memetic Genetic Algorithms for Time Series Compression by Piecewise Linear ApproximationNeural Information Processing10.1007/978-3-030-63836-8_49(592-604)Online publication date: 19-Nov-2020
https://doi.org/10.1007/978-3-030-63836-8_49
McCrorie PWalker DEllaway A(2018)The Unanticipated Challenges Associated With Implementing an Observational Study Protocol in a Large-Scale Physical Activity and Global Positioning System Data CollectionJMIR Research Protocols10.2196/resprot.95377:4(e110)Online publication date: 30-Apr-2018
https://doi.org/10.2196/resprot.9537

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