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.