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EchoSpot: Spotting Your Locations via Acoustic Sensing

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Xu YuanAuthors Info & Claims

Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies, Volume 5, Issue 3

Article No.: 113, Pages 1 - 21

https://doi.org/10.1145/3478095

Published: 14 September 2021 Publication History

Abstract

Indoor localization has played a significant role in facilitating a collection of emerging applications in the past decade. This paper presents a novel indoor localization solution via inaudible acoustic sensing, called EchoSpot, which relies on only one speaker and one microphone that are readily available on audio devices at households. We program the speaker to periodically send FMCW chirps at 18kHz-23kHz and leverage the co-located microphone to capture the reflected signals from the body and the wall for analysis. By applying the normalized cross-correlation on the transmitted and received signals, we can estimate and profile their time-of-flights (ToFs). We then eliminate the interference from device imperfection and environmental static objects, able to identify the ToFs corresponding to the direct reflection from human body. In addition, a new solution to estimate the ToF from wall reflection is designed, assisting us in spotting a human location in the two-dimensional space. We implement EchoSpot on three different types of speakers, e.g., Amazon Echo, Edifier R1280DB, and Logitech z200, and deploy them in real home environments for evaluation. Experimental results exhibit that EchoSpot achieves the mean localization errors of 4.1cm, 9.2cm, 13.1cm, 17.9cm, 22.2cm, respectively, at 1m, 2m, 3m, 4m, and 5m, comparable to results from the state-of-the-arts while maintaining favorable advantages.

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Cited By

Fu YZhang YPan HLu YLi XChen LRen JLi XZhang XZhang Y(2024)Pushing the Limits of Acoustic Spatial Perception via Incident Angle EncodingProceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies10.1145/36595838:2(1-28)Online publication date: 15-May-2024
https://dl.acm.org/doi/10.1145/3659583
Zhang JWang J(2024)FusionTrack: Towards Accurate Device-free Acoustic Motion Tracking with Signal FusionACM Transactions on Sensor Networks10.1145/365466620:3(1-30)Online publication date: 6-May-2024
https://dl.acm.org/doi/10.1145/3654666
Lian JYuan XLou JChen LWang HTzeng N(2024)Room-scale Location Trace Tracking via Continuous Acoustic WavesACM Transactions on Sensor Networks10.1145/364913620:3(1-23)Online publication date: 13-Apr-2024
https://dl.acm.org/doi/10.1145/3649136
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Index Terms

EchoSpot: Spotting Your Locations via Acoustic Sensing
1. Human-centered computing
  1. Ubiquitous and mobile computing

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cover image Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies

Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies Volume 5, Issue 3

Sept 2021

1443 pages

EISSN:2474-9567

DOI:10.1145/3486621

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Copyright © 2021 ACM.

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Published: 14 September 2021

Published in IMWUT Volume 5, Issue 3

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Cited By

Fu YZhang YPan HLu YLi XChen LRen JLi XZhang XZhang Y(2024)Pushing the Limits of Acoustic Spatial Perception via Incident Angle EncodingProceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies10.1145/36595838:2(1-28)Online publication date: 15-May-2024
https://dl.acm.org/doi/10.1145/3659583
Zhang JWang J(2024)FusionTrack: Towards Accurate Device-free Acoustic Motion Tracking with Signal FusionACM Transactions on Sensor Networks10.1145/365466620:3(1-30)Online publication date: 6-May-2024
https://dl.acm.org/doi/10.1145/3654666
Lian JYuan XLou JChen LWang HTzeng N(2024)Room-scale Location Trace Tracking via Continuous Acoustic WavesACM Transactions on Sensor Networks10.1145/364913620:3(1-23)Online publication date: 13-Apr-2024
https://dl.acm.org/doi/10.1145/3649136
Li KZhang RChen SChen BSakashita MGuimbretiere FZhang C(2024)EyeEcho: Continuous and Low-power Facial Expression Tracking on GlassesProceedings of the 2024 CHI Conference on Human Factors in Computing Systems10.1145/3613904.3642613(1-24)Online publication date: 11-May-2024
https://dl.acm.org/doi/10.1145/3613904.3642613
Luo WSong QYan ZTan RLin G(2024)Indoor Smartphone SLAM With Acoustic EchoesIEEE Transactions on Mobile Computing10.1109/TMC.2023.332339323:6(6634-6649)Online publication date: Jun-2024
https://doi.org/10.1109/TMC.2023.3323393
Ren YLi SChen CLiu HYu JChen YYang HLi H(2024)Robust Indoor Location Identification for Smartphones Using Echoes From Dominant ReflectorsIEEE Transactions on Mobile Computing10.1109/TMC.2023.330769523:5(5310-5326)Online publication date: May-2024
https://doi.org/10.1109/TMC.2023.3307695
Lin CAhmad AQu RWang YWang LWu GLin QZhang Q(2024)A Handwriting Recognition System With WiFiIEEE Transactions on Mobile Computing10.1109/TMC.2023.327960823:4(3391-3409)Online publication date: Apr-2024
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Sartayeva YChan HHo YChong P(2024)A survey of indoor positioning systems based on a six-layer modelComputer Networks: The International Journal of Computer and Telecommunications Networking10.1016/j.comnet.2023.110042237:COnline publication date: 4-Mar-2024
https://dl.acm.org/doi/10.1016/j.comnet.2023.110042
Xu XZhang XBao ZYu XYin YYang XNiu Q(2023)Training-Free Acoustic-Based Hand Gesture Tracking on Smart SpeakersApplied Sciences10.3390/app13211195413:21(11954)Online publication date: 1-Nov-2023
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Zhang DZhang XLi SXie YLi YWang XZhang D(2023)LT-FallProceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies10.1145/35808357:1(1-24)Online publication date: 28-Mar-2023
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