Computer Science ›› 2020, Vol. 47 ›› Issue (10): 63-68.doi: 10.11896/jsjkx.200600014
Special Issue: Mobile Crowd Sensing and Computing
• Mobile Crowd Sensing and Computing • Previous Articles Next Articles
JIA Yu-fu1, LI Ming-lei1, LIU Wen-ping1, HU Sheng-hong2, JIANG Hong-bo3
CLC Number:
[1]YU Z W,WANG Z.Human Behavior Analysis:Sensing and Understanding[M].Singapore:Springer,2020:139-218. [2]BOUBICHE D E,IMRAN M,MAQSOOD A,et al.Mobilecrowd sensing-Taxonomy,applications,challenges,and solutions [J].Computers in Human Behavior,2019,101(12):352-370. [3]YU N,HAN Q.Grace:Recognition of proximity-based inten-tional groups using collaborative mobile devices[C] //Procee-dings of the 2014 IEEE 11th International Conference on Mobile Ad Hoc and Sensor Systems.IEEE Computer Society,2014:10-18. [4]WIRZ M,PSCHLÄPFER,KJAERGAARD M B.Towards an online detection of pedestrian flocks in urban canyons by smoothed spatio-temporal clustering of GPS trajectories[C]//Proceedings of the 3rd ACM SIGSPATIAL International Workshop on Location-Based Social Networks.Association for Computing Machinery,2011:17-24. [5]SEN R,LEE Y,JAYARAJAH K,et al.GruMon:Fast and accurate group monitoring for heterogeneous urban spaces[C]//Proceedings of the 12th ACM Conference.Embedded Network.Sensor System.Association for Computing Machinery,2014:46-60. [6]SANCHEZ-CORTES D,ARAN O,MAST M S,et al.Gatica-Perez,A nonverbal behavior approach to identify emergentlea-ders in small groups[J].IEEE Transactions on Multimedia,2012,14(3):816-832. [7]KJAERGAARD M B,WIRZ M,ROGGEN D,et al.Mobile sensing of pedestrian flocks in indoor environments using WiFi signals[C]//Proceedings of the 2012 IEEE International Confe-rence on Pervasive Computing and Communications.Springer-Verlag,2012:95-102. [8]COSTA M.Interpersonal distances in group walking[J].Journal of Nonverbal Behavior,2010,34(1):15-26. [9]CHEN H,GUO B,YU Z W,et al.A generic framework for constraint-driven data selection in mobile crowd photographing[J].IEEE Internet of Things Journal,2017,4(1):284-296. [10]LI Q,HAN Q,CHENG X,et al.Collaborative Recognition of Queuing Behavior on Mobile Phones[J].IEEE Transactions on Mobile Computing,2016,15(1):60-73. [11]WU F,SOLMAZ G.Are you in the line? rssi-based queue detection in crowds[C]//Proceedings of the 2017 IEEE International Conference on Communications.IEEE Communications Society,2017:21-25. [12]DU H,YU Z W,YI F,et al.Recognition of group mobility level and group structure with mobile devices[J].IEEE Transactions on Mobile Computing,2018,17(4):884-897. [13]DU H,YU Z W,YI F,et al.Group mobility classification and structure recognition using mobile devices[C]//Proceedings of the 2016 IEEE International Conference on Pervasive Computing and Communications.IEEE computer Society,2016:1-9. [14]KJAERGAARD M B,BLUNCK H,WÜSTENBERG M.Time-lag method for detecting following and leadership behavior of pedestrians from mobile sensing data[C]//Proceedings of the IEEE International Conference on Pervasive Computing and Communications.IEEE computer Society,2013:18-22. [15]KJAERGAARD M B,WIRZ M,ROGGEN D.Detecting pedestrian flocks by fusion of multi-modal sensors in mobile phones[C]//Proceedings of the Acm Conference on Ubiquitous Computing,September.Association for Computing Machinery,2012:240-249. [16]YU Z,XU H,YANG Z,et al.Personalized travel package with multi-point-of-interest recommendation based on crowdsourceduser footprints[J].IEEE Transactions on Human-Machine Sys-tems,2016,46(1):151-158. [17]LI Q,HAN Q,CHENG X,et al.Collaborative Recognition of Queuing Behavior on Mobile Phones[J].IEEE Transactions on Mobile Computing,2016,15(1):60-73. [18]XU E,YUZ W,DU H,et al.User profile system based on mobile sensing data [J].Journal of Zhengzhou University(Natural Science Edition),2019(4):30-36. [19]RAY A,MALLICK S,MONDAL S,et al.A Framework forMobile Crowd Sensing and Computing based Systems[C]//Proceedings of the 2018 IEEE International Conference on Advanced Networks and Telecommunications Systems (ANTS).2018:1-6. [20] LIU W P,JIA Y F,JIANG G Y,et al.WiFifi-sensing based person-to-person distance estimation using deep learning[C]//Proceedings of the 2018 IEEE 24th International Conference on Parallel and Distributed Systems (ICPADS).2018:236-243. [21]SHEN G B,CHEN Z,ZHANG P C.Walkie-Markie:indoorpathway mapping made easy[C] //Proceedings of the 10th USENIX conference on Networked Systems Design and Implementation.USENIX Association,2013:85-98. [22]DABEK F,COX R,KAASHOEK F,et al.Vivaldi:A decentralized network coordinate system[C]//Proceedings of the 2004 Conference on Applications,Technologies,Architectures,and Protocols for Computer Communications.Association for Computing Machinery,2004:15-26. [23]HOWARD A,MATARIC M,SUKHATME G.Relaxation on a mesh:a formalism for generalized localization[C] //Proceedings 2001 IEEE/RSJ International Conference on Intelligent Robots and Systems.IEEE Robotics & Automation Magazine,2001:1055-1060. [24]PRIYANTHA N B,BALAKRISHNAN H,DEMAINE E,et al.Anchor-free distributed localization in sensor networks[R].Technical Report,MIT CSail,2003. [25]YEDAVALLI K,KRISHNAMACHARI B,RAVULA S,et al.Ecolocation:A technique for RF based localization in wireless sensor networks[C] //Proceedings of Information Processing in Sensor Networks.IEEE Signal Processing Society,2005:285-292. |
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