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.
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Acknowledgment
This work was supported in part by the National Basic Research Program of China (No. 2015CB352400), the National Natural Science Foundation of China (No. 61222209, 61373119, 61332005), and the Specialized Research Fund for the Doctoral Program of Higher Education (No. 20126102110043).
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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: Chang, C., Chiari, L., Cao, Y., Jin, H., Mokhtari, M., Aloulou, H. (eds) Inclusive Smart Cities and Digital Health. ICOST 2016. Lecture Notes in Computer Science(), vol 9677. Springer, Cham. https://doi.org/10.1007/978-3-319-39601-9_20
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DOI: https://doi.org/10.1007/978-3-319-39601-9_20
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