| Human-Computer Interaction and Pervasive Computing |
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| Survey on Wi-Fi based contactless activity recognition |
| WANG Yu-xiang, LI Sheng-jie, WANG Hao, MA Jun-yi, WANG Ya-sha, ZHANG Da-qing |
1. Key Laboratory of High Confidence Software Technologies, Ministry of Education, Peking University, Beijing 100871, China;
2. School of Electronics Engineering and Computer Science, Peking University, Beijing 100871, China;
3. National Engineering Research Center of Software Engineering, Peking University, Beijing 100871, China |
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Abstract
Providing accurate information about human’s state and activity is one of the most important elements in ubiquitous computing. Various applications can be enabled if one’s state and activity can be recognized. Due to the low deployment cost and nonintrusive sensing nature, Wi-Fi based activity recognition has become a promising and emerging research area. The state-of-the-art of the area was surveyed from four aspects ranging from historical overview, theories and models, key techniques to applications. In addition to the summary about the principles and achievements of existing work, some open issues and research directions in this emerging area were presented.
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Published: 25 April 2017
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Cite this article:
WANG Yu-xiang, LI Sheng-jie, WANG Hao, MA Jun-yi, WANG Ya-sha, ZHANG Da-qing. Survey on Wi-Fi based contactless activity recognition. JOURNAL OF ZHEJIANG UNIVERSITY (ENGINEERING SCIENCE), 2017, 51(4): 648-654.
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基于Wi-Fi的非接触式行为识别研究综述
准确地获取包括人的状态和动作等情境信息一直以来都是普适计算的重要研究方向,具有很大的应用价值.作为一种廉价、非侵扰型的感知手段,基于Wi-Fi的无接触式行为识别技术已经成为一个新兴的、极具潜力的研究领域.从历史概述、理论研究、模型研究、核心技术到应用场景这四个方面总结该领域的研究现状.在总结现有工作所取得的进展和存在的问题的同时,提出该领域将来可能的研究方向.
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［1］ ZHENG Y, CAPRA L, WOLFSON O, et al. Urban computing: concepts, methodologies, and applications ［J］. ACM Transactions on Intelligent Systems and Technology, 2014, 5(3): 38.
［2］ FOERSTER F, SMEJA M, FAHRENBERG J. Detection of posture and motion by accelerometry: a validation study in ambulatory monitoring ［J］. Computers in Human Behavior, 1999, 15(5): 571-583.
［3］ LARA O D, LABRADOR M A. A survey on human activity recognition using wearable sensors ［J］. IEEE Communications Surveys and Tutorials, 2013, 15(3): 1191-1209.
［4］ AGGARWAL J K, RYOO M S. Human activity analysis: a review ［J］. ACM Computing Surveys, 2011, 43(3): 16.
［5］ SCHOLZ M, SIGG S, SCHMIDTKE H R, et al. Challenges for device-free radio-based activity recognition ［C］∥Workshop on Context Systems, Design, Evaluation and Optimization. Italy: ［s. n.］, 2011.
［6］ TURAGA P, CHELLAPPA R, SUBRAHMANIAN V S, et al. Machine recognition of human activities: a survey ［J］. IEEE Transactions on Circuits and Systems for Video Technology, 2008, 18(11): 1473-1488.
［7］ LAI C-P, NARAYANAN R M. Through-wall imaging and characterization of human activity using ultrawideband (UWB) random noise radar ［C］∥Defense and Security. International Society for Optics and Photonics. California: ［s. n.］, 2005: 186-195.
［8］ POSTOLACHE O, GIRÃO P S, POSTOLACHE G, et al. Cardio-respiratory and daily activity monitor based on FMCW Doppler radar embedded in a wheelchair［C］∥2011 Annual International Conference of the IEEE Engineering in Medicine and Biology Society. Boston: IEEE, 2011: 1917-1920.
［9］ SCHÖLKOPF B, PLATT J C, SHAWE-TAYLOR J, et al. Estimating the support of a high-dimensional distribution ［J］. Neural computation, 2001, 13(7):1443-1471.
［10］ BAHL P, PADMANABHAN V N. RADAR: An in-building RF-based user location and tracking system ［C］∥19th Annual Joint Conference of the IEEE Computer and Communications Societies. Israel: IEEE, 2000:775-784.
［11］ SEIFELDIN M, SAEED A, KOSBA A E, et al. Nuzzer: a large-scale device-free passive localization system for wireless environments ［J］. IEEE Transactions on Mobile Computing, 2009, 12(7): 1321-1334.
［12］ WANG Y, LIU J, CHEN Y, et al. E-eyes: device-free location-oriented activity identification using fine-grained wifi signatures ［C］∥Proceedings of the 20th Annual International Conference on Mobile Computing and Networking. Hawaii: ACM, 2014: 617-628.
［13］ ADIB F, KATABI D. See through walls with WiFi! ［J］.ACM SIGCOMM Computer Communication Review, 2013, 43(4): 75-86.
［14］ WANG G, ZOU Y, ZHOU Z, et al. We can hear you with wi-fi! ［J］. IEEE Transactions on Mobile Computing, 2016, 15(11): 2907-2920.
［15］ PU Q, GUPTA S, GOLLAKOTA S, et al. Whole-home gesture recognition using wireless signals ［C］∥Proceedings of the 19th Annual International Conference on Mobile Computing and Networking. Florida: ACM, 2013: 27-38.
［16］ ADIB F, KABELAC Z, KATABI D, et al. 3D tracking via body radio reflections ［C］∥NSDI. Washington: ［s. n.］, 2014: 317-329.
［17］ ADIB F, MAO H, KABELAC Z, et al. Smart homes that monitor breathing and heart rate ［C］∥Proceedings of the 33rd Annual ACM Conference on Human Factors in Computing Systems. Korea: ACM, 2015: 837-846.
［18］ HALPERIN D. Linux 802.11n CSI tool ［EB/OL］. ［2016-12-02］. http:∥dhalperi.github.io/linux-80211n-csitool/.
［19］ WANG Y, WU K, NI L M. Wifall: device-free fall detection by wireless networks ［J］. IEEE Transactions on Mobile Computing, 2017, 16(2): 581-594.
［20］ WANG H, ZHANG D, WANG Y, et al. RT-Fall: A real-time and contactless fall detection system with commodity WiFi devices ［J］. IEEE Transactions on Mobile Computing, 2017, 16(2): 511-526.
［21］ MELGAREJO P, ZHANG X, RAMANATHAN P, et al. Leveraging directional antenna capabilities for fine-grained gesture recognition ［C］∥Proceedings of the 2014 ACM International Joint Conference on Pervasive and Ubiquitous Computing. Seattle: ACM, 2014:541-551.
［22］ HUANG D, NANDAKUMAR R, GOLLAKOTA S. Feasibility and limits of wi-fi imaging ［C］∥Proceedings of the 12th ACM Conference on Embedded Network Sensor Systems. Memphis: ACM, 2014: 266-279.
［23］ HALPERIN D. Published articles list ［EB/OL］. ［2016-12-02］. http:∥dhalperi.github.io/linux-80211n-csitool/#external.
［24］ WANG W, LIU A X, SHAHZAD M, et al. Understanding and modeling of wifi signal based human activity recognition ［C］∥Proceedings of the 21st Annual International Conference on Mobile Computing and Networking. Paris: ACM, 2015: 65-76.
［25］ YANG Z, ZHOU Z, LIU Y. From RSSI to CSI: indoor localization via channel response ［J］. ACM Computing Surveys (CSUR), 2013, 46(2): 25.
［26］ ZHOU Z, WU C, YANG Z, et al. Sensorless sensing with WiFi ［J］. Tsinghua Science and Technology, 2015, 20(1): 1-6.
［27］ TSE D, VISWANATH P. Fundamentals of wireless communication ［M］. Cambrige: Cambridge University Press, 2005.
［28］ ZHANG D, WANG H, WANG Y, et al. Anti-fall: A non-intrusive and real-time fall detector leveraging CSI from commodity WiFi devices ［C］∥International Conference on Smart Homes and Health Telematics. \[S.l.\]: Springer, 2015: 181-193.
［29］ HELAL S, CHANDRA R, KRAVETS R. Proceedings of the 19th annual international conference on Mobile computing and networking ［C］∥International Conference on Mobile Computing and Networking. Florida: ACM, 2013: 44-54.
［30］ NANDAKUMAR R, KELLOGG B, GOLLAKOTA S. Wi-Fi gesture recognition on existing devices ［J］. Eprint Arxiv, 2014, 3(2): 17.
［31］ SEN S, RADUNOVIC B, CHOUDHURY R R, et al. You are facing the Mona Lisa: spot localization using PHY layer information ［C］∥Proceedings of the 10th International Conference on Mobile Systems, Applications, and Services. UK: ACM, 2012: 183-196.
［32］ WU C, YANG Z, ZHOU Z, et al. Non-invasive detection of moving and stationary human with WiFi［J］. IEEE Journal on Selected Areas in Communications, 2015, 33(11): 2329-2342.
［33］ WU C, YANG Z, ZHOU Z, et al. PhaseU: real-time LOS identification with WiFi ［C］∥Computer Communications. Hong Kong: IEEE, 2015: 2038-2046.
［34］ DAVIES L, GATHER U. The identification of multiple outliers ［J］. Journal of the American Statistical Association, 1993, 88(423): 797-801.
［35］ LIU J, WANG Y, CHEN Y, et al. Tracking vital signs during sleep leveraging off-the-shelf Wifi［C］∥Proceedings of the 16th ACM International Symposium on Mobile Ad Hoc Networking and Computing. Hang Zhou: ACM, 2015: 267-276.
［36］ XIAO J, WU K, YI Y, et al. Fimd: Fine-graineddevice-free motion detection［C］∥Parallel and Distributed Systems (ICPADS), 2012 IEEE 18th International Conference on. Singapore: IEEE, 2012: 229-235.
［37］ QIAN K, WU C, YANG Z, et al. PADS: Passive detection of moving targets with dynamic speed using PHY layer information［C］∥ 2014 20th IEEE International Conference on Parallel and Distributed Systems (ICPADS). Tai Wan: IEEE, 2014: 1-8.
［38］ ALI K, LIU A X, WANG W, et al. Keystroke recognition using wifi signals［C］∥Proceedings of the 21st Annual International Conference on Mobile Computing and Networking. Paris: ACM, 2015: 90-102.
［39］ SHETH A, SESHAN S, WETHERALL D. Geo-fencing: confining Wi-Fi coverage to physical boundaries ［C］∥International conference on Pervasive Computing. Texas: Springer, 2009: 274-290.
［40］ ZENG Y, PATHAK P H, MOHAPATRA P. Analyzing shopper’s behavior through wifi signals ［C］∥Proceedings of the 2nd workshop on Workshop on Physical Analytics. Italy: ACM, 2015: 13-18.
［41］ WANG H, MA J Y, WANG Y X, et al. Fall detection demo ［EB/OL］. ［2016-12-02］. http:∥v.youku.com/v_show/id_XMTM5MzM0MjkzMg.html.
［42］ LIU X, CAO J, TANG S, et al. Wi-Sleep: contactless sleep monitoring via WiFi signals ［C］∥ 2014 IEEE Real-Time Systems Symposium (RTSS). Italy: IEEE, 2014: 346-355.
［43］ ZENG Y, PATHAK P H, MOHAPATRA P. WiWho: wifi-based person identification in smart spaces ［C］∥Proceedings of the 15th International Conference on Information Processing in Sensor Networks. Austria: IEEE, 2016: 4.
［44］ WANG T, ZHANG D, WANG Z, et al. Recognizing gait pattern of Parkinson’s disease patients based on finegrained movement function features［C］∥IEEE International Conference on Ubiquitous Intelligence and Computing. Beijing: IEEE, 2015: 1-10.
［45］ GAO L. Channel state information fingerprinting based indoor localization: a deep learning approach ［D］. Auburn: Auburn University, 2015.
［46］ WANG X, GAO L, MAO S, et al. DeepFi: deep learning for indoor fingerprinting using channel state information ［C］∥ 2015 IEEE Wireless Communications and Networking Conference (WCNC). New Orleans: IEEE, 2015: 1666-1671.
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