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FreeSense: A Robust Approach for Indoor Human Detection Using Wi-Fi Signals

Authors:

Jacqueline Chi Kei Lam,

Zhiwen YuAuthors Info & Claims

Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies, Volume 2, Issue 3

Article No.: 143, Pages 1 - 23

https://doi.org/10.1145/3264953

Published: 18 September 2018 Publication History

Abstract

Human detection aims to monitor how people are moving in an area of interest. There are many potential applications such as asset security monitoring, emergency management, and elderly care, etc. With the development of wireless sensing technique, Wi-Fi-based human detection method carries great potential due to advantages of pervasive accessibility and coverage flexibility. Previous studies have investigated the detection of human movements via signal variations. However, affected by noises, such as multi-path effect and device difference, existing approaches cannot achieve high accuracy and low false alarm rate at the same time. In this paper, we propose FreeSense, a novel Wi-Fi-based approach for human detection. Different from previous studies that characterize the variation of temporal wireless signals or calculate the deviation of Channel State Information (CSIs) from a normal profile, we will detect human movements by identifying whether there is any phase difference between the amplitude waveforms of multiple receiving antennas. In addition, we also model the sensing coverage for movements of different granularities in open space and propose a method to estimate the coverage range. Extensive experiments demonstrate that FreeSense can achieve an average false positive rate (FP) of 0.53% and an average false negative rate (FN) of 1.40%. The coverage range estimation method can achieve an average accuracy of 1.36 m, sufficient to guide the deployment of devices for human detection indoors.

References

[1]

Fadel Adib, Zachary Kabelac, Dina Katabi, and Robert C. Miller. 2014. 3D Tracking via Body Radio Reflections. In Proceedings of the 11th USENIX Conference on Networked Systems Design and Implementation (NSDI'14). USENIX Association, Berkeley, CA, USA, 317--329. http://dl.acm.org/citation.cfm?id=2616448.2616478

Digital Library

[2]

Fadel Adib and Dina Katabi. 2013. See Through Walls with Wi-Fi!. In Proceedings of the ACM SIGCOMM 2013 Conference on SIGCOMM (SIGCOMM '13). ACM, New York, NY, USA, 75--86.

Digital Library

[3]

Kamran Ali, Alex X. Liu, Wei Wang, and Muhammad Shahzad. 2015. Keystroke Recognition Using Wi-Fi Signals. In Proceedings of the 21st Annual International Conference on Mobile Computing and Networking (MobiCom '15). ACM, New York, NY, USA, 90--102.

Digital Library

[4]

Ian Anderson and Henk Muller. 2006. Context Awareness via GSM Signal Strength Fluctuation? Pervasive Late Breaking Results (2006), 27--31.

[5]

Ling Bao and Stephen S. Intille. 2004. Activity Recognition from User-Annotated Acceleration Data. In Pervasive Computing, Alois Ferscha and Friedemann Mattern (Eds.). Springer Berlin Heidelberg, Berlin, Heidelberg, 1--17.

[6]

D. J. Costello. 2009. Fundamentals of Wireless Communication (Tse, D. and Viswanath, P.) {Book review}. IEEE Transactions on Information Theory 55, 2 (Feb 2009), 919--920.

Digital Library

[7]

Liangyi Gong, Wu Yang, Zimu Zhou, Dapeng Man, Haibin Cai, Xiancun Zhou, and Zheng Yang. 2016. An Adaptive Wireless Passive Human Detection via Fine-grained Physical Layer Information. Ad Hoc Netw. 38, C (March 2016), 38--50.

Digital Library

[8]

Daniel Halperin, Wenjun Hu, Anmol Sheth, and David Wetherall. 2010. Predictable 802.11 Packet Delivery from Wireless Channel Measurements. In Proceedings of the ACM SIGCOMM 2010 Conference (SIGCOMM '10). ACM, New York, NY, USA, 159--170.

Digital Library

[9]

Daniel Halperin, Wenjun Hu, Anmol Sheth, and David Wetherall. 2011. Tool Release: Gathering 802.11N Traces with Channel State Information. SIGCOMM Comput. Commun. Rev. 41, 1 (Jan. 2011), 53--53.

Digital Library

[10]

C. Han, K. Wu, Y. Wang, and L. M. Ni. 2014. WiFall: Device-free fall detection by wireless networks. In IEEE INFOCOM 2014 - IEEE Conference on Computer Communications. 271--279.

[11]

Ju Han and Bir Bhanu. 2005. Human Activity Recognition in Thermal Infrared Imagery. In Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Workshops - Volume 03 (CVPR '05). IEEE Computer Society, Washington, DC, USA, 17--.

Digital Library

[12]

Konstantinos Kleisouris, Bernhard Firner, Richard Howard, Yanyong Zhang, and Richard P. Martin. 2010. Detecting Intra-room Mobility with Signal Strength Descriptors. In Proceedings of the Eleventh ACM International Symposium on Mobile Ad Hoc Networking and Computing (MobiHoc '10). ACM, New York, NY, USA, 71--80.

Digital Library

[13]

A. E. Kosba, A. Saeed, and M. Youssef. 2012. RASID: A robust WLAN device-free passive motion detection system. In 2012 IEEE International Conference on Pervasive Computing and Communications. 180--189.

[14]

J. Krumm, S. Harris, B. Meyers, B. Brumitt, M. Hale, and S. Shafer. 2000. Multi-camera multi-person tracking for EasyLiving. In Proceedings Third IEEE International Workshop on Visual Surveillance. 3--10.

Digital Library

[15]

Hong Li, Wei Yang, Jianxin Wang, Yang Xu, and Liusheng Huang. 2016. Wi-Finger: Talk to Your Smart Devices with Finger-grained Gesture. In Proceedings of the 2016 ACM International Joint Conference on Pervasive and Ubiquitous Computing (UbiComp '16). ACM, New York, NY, USA, 250--261.

Digital Library

[16]

Xiang Li, Shengjie Li, Daqing Zhang, Jie Xiong, Yasha Wang, and Hong Mei. 2016. Dynamic-MUSIC: Accurate Device-free Indoor Localization. In Proceedings of the 2016 ACM International Joint Conference on Pervasive and Ubiquitous Computing (UbiComp '16). ACM, New York, NY, USA, 196--207.

Digital Library

[17]

Xiang Li, Daqing Zhang, Qin Lv, Jie Xiong, Shengjie Li, Yue Zhang, and Hong Mei. 2017. IndoTrack: Device-Free Indoor Human Tracking with Commodity Wi-Fi. Proc. ACM Interact. Mob. Wearable Ubiquitous Technol. 1, 3, Article 72 (Sept. 2017), 22 pages.

Digital Library

[18]

Wenyuan Liu, Xi Gao, Lin Wang, and Danyang Wang. 2015. Bfp: Behavior-Free Passive Motion Detection Using PHY Information. Wireless Personal Communications 83, 2 (01 Jul 2015), 1035--1055.

Digital Library

[19]

Yunhao Liu, Yiyang Zhao, Lei Chen, Jian Pei, and Jinsong Han. 2012. Mining Frequent Trajectory Patterns for Activity Monitoring Using Radio Frequency Tag Arrays. IEEE Trans. Parallel Distrib. Syst. 23, 11 (Nov. 2012), 2138--2149.

Digital Library

[20]

Zhenyu Liu, Zhiqiang Li, Guolong Li, Xueyan Zhang, and Haiying Zhang. 2012. A Novel Motion-Detection and Edge-Detection Algorithm Based on Motion Estimation. Springer Berlin Heidelberg, Berlin, Heidelberg, 295--308.

[21]

T. Luhandjula, K. Djouani, Y. Hamam, B. J. van Wyk, and Q. Williams. 2012. A Visual Hand Motion Detection Algorithm for Wheelchair Motion. Springer Berlin Heidelberg, Berlin, Heidelberg, 433--452.

[22]

J. Lv, D. Man, W. Yang, X. Du, and M. Yu. 2018. Robust WLAN-Based Indoor Intrusion Detection Using PHY Layer Information. IEEE Access 6 (2018), 30117--30127.

[23]

Dan Ma, Chen Qian, Wenpu Li, Jinsong Han, and Jizhong Zhao. 2013. GenePrint: Generic and accurate physical-layer identification for UHF RFID tags. In 2013 21st IEEE International Conference on Network Protocols (ICNP). 1--10.

[24]

Robert S Moore, Richard Howard, Pavel Kuksa, and Richard P Martin. 2010. A geometric approach to device-free motion localization using signal strength. Technical Report, Rutgers University (2010).

[25]

H. Muller and C. Randell. 2000. Context Awareness by Analyzing Accelerometer Data. In Digest of Papers. Fourth International Symposium on Wearable Computers(ISWC), Vol. 00. 175.

Digital Library

[26]

N. Patwari and J. Wilson. 2011. Spatial Models for Human Motion-Induced Signal Strength Variance on Static Links. IEEE Transactions on Information Forensics and Security 6, 3 (Sept 2011), 791--802.

[27]

Qifan Pu, Sidhant Gupta, Shyamnath Gollakota, and Shwetak Patel. 2013. Whole-home Gesture Recognition Using Wireless Signals. In Proceedings of the 19th Annual International Conference on Mobile Computing 8 Networking (MobiCom '13). ACM, New York, NY, USA, 27--38.

Digital Library

[28]

K. Qian, C. Wu, Z. Yang, Y. Liu, and Z. Zhou. 2014. PADS: Passive detection of moving targets with dynamic speed using PHY layer information. In 2014 20th IEEE International Conference on Parallel and Distributed Systems (ICPADS). 1--8.

[29]

S. S. Ram, Y. Li, A. Lin, and H. Ling. 2007. Human Tracking Using Doppler Processing and Spatial Beamforming. In 2007 IEEE Radar Conference. 546--551.

[30]

Sankar Rangarajan, Assegid Kidane, Gang Qian, Stjepan Rajko, and David Birchfield. 2007. The Design of a Pressure Sensing Floor for Movement-based Human Computer Interaction. In Proceedings of the 2Nd European Conference on Smart Sensing and Context (EuroSSC'07). Springer-Verlag, Berlin, Heidelberg, 46--61. http://dl.acm.org/citation.cfm?id=1775377.1775382

Digital Library

[31]

R. Schmidt. 1986. Multiple emitter location and signal parameter estimation. IEEE Transactions on Antennas and Propagation 34, 3 (March 1986), 276--280.

[32]

Souvik Sen, Jeongkeun Lee, Kyu-Han Kim, and Paul Congdon. 2013. Avoiding Multipath to Revive Inbuilding Wi-Fi Localization. In Proceeding of the 11th Annual International Conference on Mobile Systems, Applications, and Services (MobiSys '13). ACM, New York, NY, USA, 249--262.

Digital Library

[33]

Michael Wallbaum and Stefan Diepolder. 2006. A Motion Detection Scheme For Wireless LAN Stations. In In The 3rd International Conference on Mobile Computing and Ubiquitous Networking.

[34]

Guanhua Wang, Yongpan Zou, Zimu Zhou, Kaishun Wu, and Lionel M. Ni. 2014. We Can Hear You with Wi-Fi!. In Proceedings of the 20th Annual International Conference on Mobile Computing and Networking (MobiCom '14). ACM, New York, NY, USA, 593--604.

Digital Library

[35]

Hao Wang, Daqing Zhang, Junyi Ma, Yasha Wang, Yuxiang Wang, Dan Wu, Tao Gu, and Bing Xie. 2016. Human Respiration Detection with Commodity Wifi Devices: Do User Location and Body Orientation Matter?. In Proceedings of the 2016 ACM International Joint Conference on Pervasive and Ubiquitous Computing (UbiComp '16). ACM, New York, NY, USA, 25--36.

Digital Library

[36]

Hao Wang, Daqing Zhang, Yasha Wang, Junyi Ma, Yuxiang Wang, and Shengjie Li. 2017. RT-Fall: A Real-Time and Contactless Fall Detection System with Commodity Wi-Fi Devices. IEEE Transactions on Mobile Computing 16, 2 (Feb. 2017), 511--526.

Digital Library

[37]

Z. Wang, B. Guo, Z. Yu, and X. Zhou. 2018. Wi-Fi CSI-Based Behavior Recognition: From Signals and Actions to Activities. IEEE Communications Magazine 56, 5 (May 2018), 109--115.

[38]

Joey Wilson and Neal Patwari. 2012. A Fade-Level Skew-Laplace Signal Strength Model for Device-Free Localization with Wireless Networks. IEEE Transactions on Mobile Computing 11, 6 (June 2012), 947--958.

Digital Library

[39]

C. Wu, Z. Yang, Z. Zhou, X. Liu, Y. Liu, and J. Cao. 2015. Non-Invasive Detection of Moving and Stationary Human With Wi-Fi. IEEE Journal on Selected Areas in Communications 33, 11 (Nov 2015), 2329--2342.

[40]

D. Wu, D. Zhang, C. Xu, H. Wang, and X. Li. 2017. Device-Free Wi-Fi Human Sensing: From Pattern-Based to Model-Based Approaches. IEEE Communications Magazine 55, 10 (October 2017), 91--97.

[41]

Dan Wu, Daqing Zhang, Chenren Xu, Yasha Wang, and Hao Wang. 2016. WiDir: Walking Direction Estimation Using Wireless Signals. In Proceedings of the 2016 ACM International Joint Conference on Pervasive and Ubiquitous Computing (UbiComp '16). ACM, New York, NY, USA, 351--362.

Digital Library

[42]

K. Wu, Jiang Xiao, Youwen Yi, Min Gao, and L. M. Ni. 2012. FILA: Fine-grained indoor localization. In 2012 Proceedings IEEE INFOCOM. 2210--2218.

[43]

Lu Xia and J. K. Aggarwal. 2013. Spatio-temporal Depth Cuboid Similarity Feature for Activity Recognition Using Depth Camera. In Proceedings of the 2013 IEEE Conference on Computer Vision and Pattern Recognition (CVPR '13). IEEE Computer Society, Washington, DC, USA, 2834--2841.

Digital Library

[44]

J. Xiao, K. Wu, Y. Yi, L. Wang, and L. M. Ni. 2012. FIMD: Fine-grained Device-free Motion Detection. In 2012 IEEE 18th International Conference on Parallel and Distributed Systems. 229--235.

Digital Library

[45]

J. Yang, Y. Ge, H. Xiong, Y. Chen, and H. Liu. 2010. Performing Joint Learning for Passive Intrusion Detection in Pervasive Wireless Environments. In 2010 Proceedings IEEE INFOCOM. 1--9.

Digital Library

[46]

Moustafa Youssef, Matthew Mah, and Ashok Agrawala. 2007. Challenges: Device-free Passive Localization for Wireless Environments. In Proceedings of the 13th Annual ACM International Conference on Mobile Computing and Networking (MobiCom '07). ACM, New York, NY, USA, 222--229.

Digital Library

[47]

D. Zhang, H. Wang, and D. Wu. 2017. Toward Centimeter-Scale Human Activity Sensing with Wi-Fi Signals. Computer 50, 1 (Jan 2017), 48--57.

[48]

Fusang Zhang, Daqing Zhang, Jie Xiong, Hao Wang, Kai Niu, Beihong Jin, and Yuxiang Wang. 2018. From Fresnel Diffraction Model to Fine-grained Human Respiration Sensing with Commodity Wi-Fi Devices. IMWUT 2, 1 (2018), 53:1--53:23.

Digital Library

[49]

Z. Zhou, Z. Yang, C. Wu, L. Shangguan, and Y. Liu. 2013. Towards omnidirectional passive human detection. In 2013 Proceedings IEEE INFOCOM. 3057--3065.

[50]

Z. Zhou, Z. Yang, C. Wu, L. Shangguan, and Y. Liu. 2014. Omnidirectional Coverage for Device-Free Passive Human Detection. IEEE Transactions on Parallel and Distributed Systems 25, 7 (July 2014), 1819--1829.

Digital Library

Cited By

Wang CFu XYang ZLi S(2025)NeuralWiGait: an accurate WiFi-based gait recognition system using hybrid deep learning frameworkThe Journal of Supercomputing10.1007/s11227-024-06878-081:2Online publication date: 7-Jan-2025
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Wang ZGeng CSun ZChen ZLiu SGuo BYu Z(2024)Size Matters: Characterizing the Effect of Target Size on Wi-Fi Sensing Based on the Fresnel Zone ModelProceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies10.1145/36997268:4(1-22)Online publication date: 21-Nov-2024
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Published In

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 2, Issue 3

September 2018

1536 pages

EISSN:2474-9567

DOI:10.1145/3279953

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Copyright © 2018 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: 18 September 2018

Accepted: 01 September 2018

Revised: 01 April 2018

Received: 01 February 2018

Published in IMWUT Volume 2, Issue 3

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Cited By

Wang CFu XYang ZLi S(2025)NeuralWiGait: an accurate WiFi-based gait recognition system using hybrid deep learning frameworkThe Journal of Supercomputing10.1007/s11227-024-06878-081:2Online publication date: 7-Jan-2025
https://doi.org/10.1007/s11227-024-06878-0
Wang ZGeng CSun ZChen ZLiu SGuo BYu Z(2024)Size Matters: Characterizing the Effect of Target Size on Wi-Fi Sensing Based on the Fresnel Zone ModelProceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies10.1145/36997268:4(1-22)Online publication date: 21-Nov-2024
https://dl.acm.org/doi/10.1145/3699726
Li JDavuluri KMottakin KSong ZDou FLu JGanesan DLane NShi W(2024)Proximal Federated Learning for Body Mass Index Monitoring using Commodity WiFiProceedings of the 30th Annual International Conference on Mobile Computing and Networking10.1145/3636534.3694735(2061-2065)Online publication date: 4-Dec-2024
https://dl.acm.org/doi/10.1145/3636534.3694735
Yao ZWang XNiu KZheng RWang JZhang DGanesan DShi W(2024)WiProfile: Unlocking Diffraction Effects for Sub-Centimeter Target Profiling Using Commodity WiFi DevicesProceedings of the 30th Annual International Conference on Mobile Computing and Networking10.1145/3636534.3649355(185-199)Online publication date: 29-May-2024
https://dl.acm.org/doi/10.1145/3636534.3649355
Wang ZGuo YRen ZSong WSun ZChen CGuo BYu Z(2024)LiqDetectorProceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies10.1145/36314437:4(1-24)Online publication date: 12-Jan-2024
https://dl.acm.org/doi/10.1145/3631443
Ren ZWang ZSun ZGuo YSong WZhang HChen CGuo BYu ZZhou XZhang D(2024)Characterizing the Through-Wall Sensing Mechanism of Wi-Fi Signals With a Refraction-Aware Fresnel Zone ModelIEEE Transactions on Mobile Computing10.1109/TMC.2024.342584723:12(13438-13454)Online publication date: Dec-2024
https://doi.org/10.1109/TMC.2024.3425847
Sun ZYu ZWang QWang ZGuo BZhang H(2024)CovertEye: Gait-based Human Identification under Weakly Constrained TrajectoryIEEE Transactions on Mobile Computing10.1109/TMC.2023.3310508(1-13)Online publication date: 2024
https://doi.org/10.1109/TMC.2023.3310508
Xie YLi YDjurić PDas SStanaćević M(2024)Optimized Channel Phase Estimation in Passive RF Tag Network2024 IEEE International Conference on RFID (RFID)10.1109/RFID62091.2024.10582689(1-6)Online publication date: 4-Jun-2024
https://doi.org/10.1109/RFID62091.2024.10582689
Lyons NSantra ARamanna VUln KTaori RPandey A(2024)WIFIACT: Enhancing Human Sensing Through Environment Robust Preprocessing And Bayesian Self-Supervised LearningICASSP 2024 - 2024 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)10.1109/ICASSP48485.2024.10446566(13391-13395)Online publication date: 14-Apr-2024
https://doi.org/10.1109/ICASSP48485.2024.10446566
Zhang YWang XWen JZhu X(2024)WiFi-based non-contact human presence detection technologyScientific Reports10.1038/s41598-024-54077-x14:1Online publication date: 13-Feb-2024
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