SwingLoc: acoustic indoor localization leveraging doppler effects via wearable computing
Abstract
Indoor localization using mobile sensing platforms has become a ubiquitous service that enables various smart building and health-care related applications. As wearable device becomes an important player in the mobile market, an indoor localization system tailored specifically for it remains absent. In this paper, we present SwingLoc, an indoor positioning system aimed particularly for hand-wear devices. It takes use of the natural arm swinging when the user is walking, and the Doppler effects it triggers while receiving acoustic signals to locate the user. With the need of off-the-shelf speakers, which are already present in most public indoor areas, SwingLoc monitors the wearable device's direction toward the speakers in consecutive gait cycles, and solve a nonlinear least squares problem for the user's position. Our real-world tests involving 6 users at two different locations shows that SwingLoc can achieve overall 85% localization errors under 2m, with extreme conditions where at most 3 speakers are present in the environment. Our experiments demonstrate SwingLoc to be robust and effective, and has great potential for providing fine-grained location-based services and improve human well-being.
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Published In
October 2022
69 pages
ISBN:9781450395182
DOI:10.1145/3556548
- Conference Chairs:
- Yipeng Zhou,
- Lorenzo Bertizzolo,
- Stefano Secci
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Published: 17 October 2022
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