SmartSwim: An infrastructure-free swimmer localization system based on smartphone sensors

Dong Xiao; Zhiwen Yu; Fei Yi; Liang Wang; Chiu C. Tan; Bin Guo

doi:10.1007/978-3-319-39601-9_20

SmartSwim: An infrastructure-free swimmer localization system based on smartphone sensors

Dong Xiao, Zhiwen Yu, Fei Yi, Liang Wang, Chiu C. Tan, Bin Guo

School of Computer Science

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

6 Scopus citations

Abstract

Many works have focused their attention on the sports activity monitoring and recognition using inherit sensors on the smartphone. However, distinct from many on-the-ground activities, swimming is not only hard to monitor but also dangerous in the water. Knowing the position of a swimmer is crucial which can help a lot in rescuing people. In this paper, we propose a system called SmartSwim employing smartphone as a sensor for swimming tracking and localization. In detail, we first present a sensor based swimming status classification and moving length estimation. A swimmer locating algorithm is then proposed drawing on the experience of pedestrian dead reckoning (PDR) concept. We implemented the system on commercial smartphones and designed two prototype applications named WeSwim and SafeSwim. Experimental results showed the accuracy of swimming status classification reaches more than 99% and the Error Rate value for length estimation is lower than 7% overall.

Original language	English
Title of host publication	Inclusive Smart Cities and Digital Health - 14th International Conference on Smart Homes and Health Telematics, ICOST 2016, Proceedings
Editors	Carl K. Chang, Hamdi Aloulou, Hai Jin, Yu Cao, Mounir Mokhtari, Lorenzo Chiari
Publisher	Springer Verlag
Pages	222-234
Number of pages	13
ISBN (Print)	9783319396002
DOIs	https://doi.org/10.1007/978-3-319-39601-9_20
State	Published - 2016
Event	14th International Conference on Smart Homes and Health Telematics, ICOST 2016 - Wuhan, China Duration: 25 May 2016 → 27 May 2016

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	9677
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	14th International Conference on Smart Homes and Health Telematics, ICOST 2016
Country/Territory	China
City	Wuhan
Period	25/05/16 → 27/05/16

Keywords

Drown detection
Localization
Social Network
Swimmer tracking

Access to Document

10.1007/978-3-319-39601-9_20

Cite this

Xiao, D., Yu, Z., Yi, F., Wang, L., Tan, C. C., & Guo, B. (2016). SmartSwim: An infrastructure-free swimmer localization system based on smartphone sensors. In C. K. Chang, H. Aloulou, H. Jin, Y. Cao, M. Mokhtari, & L. Chiari (Eds.), Inclusive Smart Cities and Digital Health - 14th International Conference on Smart Homes and Health Telematics, ICOST 2016, Proceedings (pp. 222-234). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 9677). Springer Verlag. https://doi.org/10.1007/978-3-319-39601-9_20

Xiao, Dong ; Yu, Zhiwen ; Yi, Fei et al. / SmartSwim : An infrastructure-free swimmer localization system based on smartphone sensors. Inclusive Smart Cities and Digital Health - 14th International Conference on Smart Homes and Health Telematics, ICOST 2016, Proceedings. editor / Carl K. Chang ; Hamdi Aloulou ; Hai Jin ; Yu Cao ; Mounir Mokhtari ; Lorenzo Chiari. Springer Verlag, 2016. pp. 222-234 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

@inproceedings{c8906f1c7bca4b909eba0c492d4b94ed,

title = "SmartSwim: An infrastructure-free swimmer localization system based on smartphone sensors",

abstract = "Many works have focused their attention on the sports activity monitoring and recognition using inherit sensors on the smartphone. However, distinct from many on-the-ground activities, swimming is not only hard to monitor but also dangerous in the water. Knowing the position of a swimmer is crucial which can help a lot in rescuing people. In this paper, we propose a system called SmartSwim employing smartphone as a sensor for swimming tracking and localization. In detail, we first present a sensor based swimming status classification and moving length estimation. A swimmer locating algorithm is then proposed drawing on the experience of pedestrian dead reckoning (PDR) concept. We implemented the system on commercial smartphones and designed two prototype applications named WeSwim and SafeSwim. Experimental results showed the accuracy of swimming status classification reaches more than 99% and the Error Rate value for length estimation is lower than 7% overall.",

keywords = "Drown detection, Localization, Social Network, Swimmer tracking",

author = "Dong Xiao and Zhiwen Yu and Fei Yi and Liang Wang and Tan, {Chiu C.} and Bin Guo",

note = "Publisher Copyright: {\textcopyright} Springer International Publishing Switzerland 2016.; 14th International Conference on Smart Homes and Health Telematics, ICOST 2016 ; Conference date: 25-05-2016 Through 27-05-2016",

year = "2016",

doi = "10.1007/978-3-319-39601-9_20",

language = "英语",

isbn = "9783319396002",

series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",

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pages = "222--234",

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}

Xiao, D, Yu, Z, Yi, F, Wang, L, Tan, CC & Guo, B 2016, SmartSwim: An infrastructure-free swimmer localization system based on smartphone sensors. in CK Chang, H Aloulou, H Jin, Y Cao, M Mokhtari & L Chiari (eds), Inclusive Smart Cities and Digital Health - 14th International Conference on Smart Homes and Health Telematics, ICOST 2016, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 9677, Springer Verlag, pp. 222-234, 14th International Conference on Smart Homes and Health Telematics, ICOST 2016, Wuhan, China, 25/05/16. https://doi.org/10.1007/978-3-319-39601-9_20

SmartSwim: An infrastructure-free swimmer localization system based on smartphone sensors. / Xiao, Dong; Yu, Zhiwen; Yi, Fei et al.
Inclusive Smart Cities and Digital Health - 14th International Conference on Smart Homes and Health Telematics, ICOST 2016, Proceedings. ed. / Carl K. Chang; Hamdi Aloulou; Hai Jin; Yu Cao; Mounir Mokhtari; Lorenzo Chiari. Springer Verlag, 2016. p. 222-234 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 9677).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - SmartSwim

T2 - 14th International Conference on Smart Homes and Health Telematics, ICOST 2016

AU - Xiao, Dong

AU - Yu, Zhiwen

AU - Yi, Fei

AU - Wang, Liang

AU - Tan, Chiu C.

AU - Guo, Bin

N1 - Publisher Copyright: © Springer International Publishing Switzerland 2016.

PY - 2016

Y1 - 2016

N2 - Many works have focused their attention on the sports activity monitoring and recognition using inherit sensors on the smartphone. However, distinct from many on-the-ground activities, swimming is not only hard to monitor but also dangerous in the water. Knowing the position of a swimmer is crucial which can help a lot in rescuing people. In this paper, we propose a system called SmartSwim employing smartphone as a sensor for swimming tracking and localization. In detail, we first present a sensor based swimming status classification and moving length estimation. A swimmer locating algorithm is then proposed drawing on the experience of pedestrian dead reckoning (PDR) concept. We implemented the system on commercial smartphones and designed two prototype applications named WeSwim and SafeSwim. Experimental results showed the accuracy of swimming status classification reaches more than 99% and the Error Rate value for length estimation is lower than 7% overall.

AB - Many works have focused their attention on the sports activity monitoring and recognition using inherit sensors on the smartphone. However, distinct from many on-the-ground activities, swimming is not only hard to monitor but also dangerous in the water. Knowing the position of a swimmer is crucial which can help a lot in rescuing people. In this paper, we propose a system called SmartSwim employing smartphone as a sensor for swimming tracking and localization. In detail, we first present a sensor based swimming status classification and moving length estimation. A swimmer locating algorithm is then proposed drawing on the experience of pedestrian dead reckoning (PDR) concept. We implemented the system on commercial smartphones and designed two prototype applications named WeSwim and SafeSwim. Experimental results showed the accuracy of swimming status classification reaches more than 99% and the Error Rate value for length estimation is lower than 7% overall.

KW - Drown detection

KW - Localization

KW - Social Network

KW - Swimmer tracking

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DO - 10.1007/978-3-319-39601-9_20

M3 - 会议稿件

AN - SCOPUS:84976648577

SN - 9783319396002

T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

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EP - 234

BT - Inclusive Smart Cities and Digital Health - 14th International Conference on Smart Homes and Health Telematics, ICOST 2016, Proceedings

A2 - Chang, Carl K.

A2 - Aloulou, Hamdi

A2 - Jin, Hai

A2 - Cao, Yu

A2 - Mokhtari, Mounir

A2 - Chiari, Lorenzo

PB - Springer Verlag

Y2 - 25 May 2016 through 27 May 2016

ER -

Xiao D, Yu Z, Yi F, Wang L, Tan CC, Guo B. SmartSwim: An infrastructure-free swimmer localization system based on smartphone sensors. In Chang CK, Aloulou H, Jin H, Cao Y, Mokhtari M, Chiari L, editors, Inclusive Smart Cities and Digital Health - 14th International Conference on Smart Homes and Health Telematics, ICOST 2016, Proceedings. Springer Verlag. 2016. p. 222-234. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-319-39601-9_20

SmartSwim: An infrastructure-free swimmer localization system based on smartphone sensors

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