research-article

IndoTrack: Device-Free Indoor Human Tracking with Commodity Wi-Fi

Authors:

Hong MeiAuthors Info & Claims

Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies, Volume 1, Issue 3

Article No.: 72, Pages 1 - 22

https://doi.org/10.1145/3130940

Published: 11 September 2017 Publication History

Abstract

Indoor human tracking is fundamental to many real-world applications such as security surveillance, behavioral analysis, and elderly care. Previous solutions usually require dedicated device being carried by the human target, which is inconvenient or even infeasible in scenarios such as elderly care and break-ins. However, compared with device-based tracking, device-free tracking is particularly challenging because the much weaker reflection signals are employed for tracking. The problem becomes even more difficult with commodity Wi-Fi devices, which have limited number of antennas, small bandwidth size, and severe hardware noise.

In this work, we propose IndoTrack, a device-free indoor human tracking system that utilizes only commodity Wi-Fi devices. IndoTrack is composed of two innovative methods: (1) Doppler-MUSIC is able to extract accurate Doppler velocity information from noisy Wi-Fi Channel State Information (CSI) samples; and (2) Doppler-AoA is able to determine the absolute trajectory of the target by jointly estimating target velocity and location via probabilistic co-modeling of spatial-temporal Doppler and AoA information. Extensive experiments demonstrate that IndoTrack can achieve a 35cm median error in human trajectory estimation, outperforming the state-of-the-art systems and provide accurate location and velocity information for indoor human mobility and behavioral analysis.

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Cited By

Li SLiu ZLv QZou YZhang YZhang D(2025)WiLife: Long-Term Daily Status Monitoring and Habit Mining of the Elderly Leveraging Ubiquitous Wi-Fi SignalsACM Transactions on Computing for Healthcare10.1145/36893736:1(1-29)Online publication date: 23-Jan-2025
https://dl.acm.org/doi/10.1145/3689373
Li YWu DChen JShi WWang LSu LLi WZhang D(2025)SigCan: Toward Reliable ToF Estimation Leveraging Multipath Signal Cancellation on Commodity WiFi DevicesIEEE Transactions on Mobile Computing10.1109/TMC.2024.349133724:3(1895-1912)Online publication date: 1-Mar-2025
https://dl.acm.org/doi/10.1109/TMC.2024.3491337
Zhu HXiao YLi YShi GKrunz M(2025)SANSee: A Physical-Layer Semantic-Aware Networking Framework for Distributed Wireless SensingIEEE Transactions on Mobile Computing10.1109/TMC.2024.348327224:3(1636-1653)Online publication date: Mar-2025
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Index Terms

IndoTrack: Device-Free Indoor Human Tracking with Commodity Wi-Fi
1. Human-centered computing
  1. Ubiquitous and mobile computing
    1. Ubiquitous and mobile computing systems and tools

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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 1, Issue 3

September 2017

2023 pages

EISSN:2474-9567

DOI:10.1145/3139486

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Copyright © 2017 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Publication History

Published: 11 September 2017

Accepted: 01 July 2017

Revised: 01 May 2017

Received: 01 February 2017

Published in IMWUT Volume 1, Issue 3

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Peking University Information Technology Institute (Tianjin Binhai)

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https://dl.acm.org/doi/10.1145/3689373
Li YWu DChen JShi WWang LSu LLi WZhang D(2025)SigCan: Toward Reliable ToF Estimation Leveraging Multipath Signal Cancellation on Commodity WiFi DevicesIEEE Transactions on Mobile Computing10.1109/TMC.2024.349133724:3(1895-1912)Online publication date: 1-Mar-2025
https://dl.acm.org/doi/10.1109/TMC.2024.3491337
Zhu HXiao YLi YShi GKrunz M(2025)SANSee: A Physical-Layer Semantic-Aware Networking Framework for Distributed Wireless SensingIEEE Transactions on Mobile Computing10.1109/TMC.2024.348327224:3(1636-1653)Online publication date: Mar-2025
https://doi.org/10.1109/TMC.2024.3483272
Zheng NLi YJiang SLi YYao RDong CChen TYang YYin ZLiu Y(2025)AdaWiFi, Collaborative WiFi Sensing for Cross-Environment AdaptationIEEE Transactions on Mobile Computing10.1109/TMC.2024.347485324:2(845-858)Online publication date: Feb-2025
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Wang JWu JQu YXiao QGao QFang Y(2025)Multi-Target Device-Free Positioning Based on Spatial-Temporal mmWave Point CloudIEEE Transactions on Mobile Computing10.1109/TMC.2024.347467124:2(1163-1180)Online publication date: Feb-2025
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Wang XYang SZhai HMasouros CAndrew Zhang J(2025)Windowing Optimization for Fingerprint-Spectrum-Based Passive Sensing in Perceptive Mobile NetworksIEEE Transactions on Communications10.1109/TCOMM.2024.344661073:2(1367-1382)Online publication date: Feb-2025
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Wang ZZhang JZhang HXu MGuo J(2025)Passive Human Tracking With WiFi Point CloudsIEEE Internet of Things Journal10.1109/JIOT.2024.348719312:5(5528-5543)Online publication date: 1-Mar-2025
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Chen WCheng JWang LZhao WMatusik W(2024)Sensor2Text: Enabling Natural Language Interactions for Daily Activity Tracking Using Wearable SensorsProceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies10.1145/36997478:4(1-26)Online publication date: 21-Nov-2024
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