Workshops - UbiComp

(a) Actual traces.(a) Actual traces.101099Y Coordinate (unit: m)8765Y Coordinate (unit: m)87654O2N95Cluster30 4 8 12 16 20 24 28 32X Coordinate (unit: m)(b) Tracking traces and cluster trace.4O2N95Cluster30 4 8 12 16 20 24 28 32X Coordinate (unit: m)(b) Tracking traces and cluster trace.Figure 4. Two persons go straight forward side by side.Figure 5. One person turns apart halfway.apart from each other, the Bluetooth signals are blocked bythe wall and these two mobile phones can not get in touchagain. Figure 5(b) presents the tracking result of this trace.Each single trace is still rough due to the noisy signals whilethe cluster trace is relatively smooth. Moreover, as the twophones exceed the range of Bluetooth, the cluster is brokenup and the cluster trace stops at the turning point accordingly.It indicates that our cooperative localization can dividethe mobile phones into exact clusters, make sure themembers in a cluster have similar mobile trends.CONCLUSION AND FUTURE WORKIn this paper, we originally propose a new cooperative localizationtechnique in Wi-Fi based networks to learn trafficstate. Unlike the cooperative localization in robots and wirelesssensor networks, our cooperative localization makes useof collaboration of mobile phones to separate them into differentclusters. Then their behaviors can be represented bythe cluster trace. We simulate it in wireless environment andthe simulation results show the effectiveness. In the future,we will make actual traffic experiments and improvement onthe algorithms further.REFERENCES1. P. Bahl, A. Balachandran, and V. Padmanabhan. Enhancements to theradar user location and tracking system. 2000.2. E. S. Bhasker, S. W. Brown, and W. G. Griswold. Employing userfeedback for fast, accurate, low-maintenance geolocationing. InPERCOM ’04: Proceedings of the Second IEEE InternationalConference on Pervasive Computing and Communications(PerCom’04), page 111, Washington, DC, USA, 2004. IEEEComputer Society.3. F. Gustafsson, F. Gunnarsson, N. Bergman, U. Forssell, J. Jansson,R. Karlsson, and P. Nordlund. Particle filters for positioning,navigation, and tracking. 2002.4. A. M. Ladd, K. E. Bekris, A. Rudys, L. E. Kavraki, and D. S.Wallach. Robotics-based location sensing using wireless Ethernet.Wireless Networks, 11(1), 2005.5. C. L. F. Mayorga, F. D. Rosa, S. A. W. G. Simone, M. C. N. Raynal,J. Figueiras, and S. Frattasi. Cooperative positioning techniques formobile localization in 4g cellular networks. In Proceedings of IEEEInternational Conference on Pervasive Services (ICPS’07), 2007.6. L. M. Ni, Y. Liu, Y. C. Lau, and A. P. Patil. Landmarc: Indoorlocation sensing using active rfid. In PERCOM ’03: Proceedings ofthe First IEEE International Conference on Pervasive Computing andCommunications, page 407, Washington, DC, USA, 2003. IEEEComputer Society.7. L. R. Rabiner. A tutorial on hidden markov models and selectedapplications in speech recognition. pages 267–296, 1990.8. I. Rekleitis, G. Dudek, and E. Milios. Multi-robot collaboration forrobust exploration. Annals of Mathematics and Artificial Intelligence,31(1-4):7–40, 2001.9. T. Roos, P. Myllymaki, H. Tirri, P. Misikangas, , and J. Sievanen. Aprobabilistic approach to wlan user location estimation. In Intl J.Wireless Information Networks, vol. 9, no. 3, pp. 155-164, July, 2002.10. S. Y, R. W, and Z. Y. Localization from mere connectivity. InProceedings of the fourth ACM international symposium on Mobilead hoc networking and computing (MOBIHOC 2003),Annapolis,MD,USA, 2003.11. M. Youssef and A. Agrawala. The horus wlan location determinationsystem. In MobiSys ’05: Proceedings of the 3rd internationalconference on Mobile systems, applications, and services, pages205–218, New York, NY, USA, 2005. ACM.33