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Erschienen in:
Mapping the Territory for a Knowledge-Based System Kapitel lesen Erstes Kapitel lesen

2017 | OriginalPaper | Buchkapitel

Real-Life Validation of Methods for Detecting Locations, Transition Periods and Travel Modes Using Phone-Based GPS and Activity Tracker Data

verfasst von : Adnan Manzoor, Julia S. Mollee, Aart T. van Halteren, Michel C. A. Klein

Erschienen in: Computational Collective Intelligence

Verlag: Springer International Publishing

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Abstract

Insufficient physical activity is a major health concern. Choosing for active transport, such as cycling and walking, can contribute to an increase in activity. Fostering a change in behavior that prefers active transport could start with automated self-monitoring of travel choices. This paper describes an experiment to validate existing algorithms for detecting significant locations, transition periods and travel modes using smartphone-based GPS data and an off-the-shelf activity tracker. A real-life pilot study was conducted to evaluate the feasibility of the approach in the daily life of young adults. A clustering algorithm is used to locate people’s important places and an analysis of the sensitivity of the different parameters used in the algorithm is provided. Our findings show that the algorithms can be used to determine whether a user travels actively or passively based on smartphone-based GPS speed data, and that a slightly higher accuracy is achieved when it is combined with activity tracker data.

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Vorheriges Kapitel WINE: Web Integrated Navigation Extension; Conceptual Design, Model and Interface
Nächstes Kapitel Adaptive Runtime Middleware: Everything as a Service
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Metadaten
Titel
Real-Life Validation of Methods for Detecting Locations, Transition Periods and Travel Modes Using Phone-Based GPS and Activity Tracker Data
verfasst von
Adnan Manzoor
Julia S. Mollee
Aart T. van Halteren
Michel C. A. Klein
Copyright-Jahr
2017
Buch
Computational Collective Intelligence

Print ISBN: 978-3-319-67073-7

Electronic ISBN: 978-3-319-67074-4

Copyright-Jahr: 2017

DOI
https://doi.org/10.1007/978-3-319-67074-4_46