IOS crowd–sensing won’t hurt a bit! : AWARE framework and sustainable study guideline for iOS platform |
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Author: | Nishiyama, Yuuki1; Ferreira, Denzil2; Eigen, Yusaku3; |
Organizations: |
1The University of Tokyo, Japan 2University of Oulu, Finland 3Keio University, Japan
4University of Washington, USA
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Format: | article |
Version: | accepted version |
Access: | open |
Online Access: | PDF Full Text (PDF, 1.2 MB) |
Persistent link: | http://urn.fi/urn:nbn:fi-fe2020112392284 |
Language: | English |
Published: |
Springer Nature,
2020
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Publish Date: | 2020-11-23 |
Description: |
AbstractThe latest smartphones have advanced sensors that allow us to recognize human and environmental contexts. They operate primarily on Android and iOS, and can be used as sensing platforms for research in various fields owing to their ubiquity in society. Mobile sensing frameworks help to manage these sensors easily. However, Android and iOS are constructed following different policies, requiring developers and researchers to consider framework differences during research planning, application development, and data collection phases to ensure sustainable data collection. In particular, iOS imposes strict regulations on background data collection and application distribution. In this study, we design, implement, and evaluate a mobile sensing framework for iOS, namely AWARE-iOS, which is an iOS version of the AWARE Framework. Our performance evaluations and case studies measured over a duration of 288 h on four types of devices, show the risks of continuous data collection in the background and explore optimal practical sensor settings for improved data collection. Based on these results, we develop guidelines for sustainable data collection on iOS. see all
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Series: |
Lecture notes in computer science |
ISSN: | 0302-9743 |
ISSN-E: | 1611-3349 |
ISSN-L: | 0302-9743 |
ISBN: | 978-3-030-50344-4 |
ISBN Print: | 978-3-030-50343-7 |
Pages: | 223 - 243 |
DOI: | 10.1007/978-3-030-50344-4_17 |
OADOI: | https://oadoi.org/10.1007/978-3-030-50344-4_17 |
Host publication: |
Distributed, Ambient and Pervasive Interactions : 8th International Conference, DAPI 2020, Held as Part of the 22nd HCI International Conference, HCII 2020, Copenhagen, Denmark, July 19–24, 2020, Proceedings |
Host publication editor: |
Streitz, Norbert Konomi, Shin’ichi |
Conference: |
International Conference on Human-Computer Interaction |
Type of Publication: |
A4 Article in conference proceedings |
Field of Science: |
113 Computer and information sciences |
Subjects: | |
Funding: |
This work was supported by JSPS KAKENHI Grant Number JP18K11274. |
Copyright information: |
© Springer Nature Switzerland AG 2020. This is a post-peer-review, pre-copyedit version of an article published in Distributed, Ambient and Pervasive Interactions : 8th International Conference, DAPI 2020, Held as Part of the 22nd HCI International Conference, HCII 2020, Copenhagen, Denmark, July 19–24, 2020, Proceedings. The final authenticated version is available online at: https://doi.org/10.1007/978-3-030-50344-4_17. |