Identyfikatory
Warianty tytułu
Języki publikacji
Abstrakty
We present a novel method of fast and reliable data gathering for the purpose of location services based on radio signal strength services such as WiFi location/ navigation. Our method combines the acquisition of location and mapping based on computer vision methods with WiFi signal strength stochastic data gathering. The output of the method is threefold: 3D metric space model, 2D floor plan map and metric map of stochastic radio signal strength. The binding of location data with radio data is done completely automatically, without any human intervention. The advantage of our solution lies also in a significant speed-up and density increase of Radio Map generation which opens new markets for WiFi navigation services. We have proved that presented solution produces a map allowing location in office space of accuracy 1.06 m.
Rocznik
Tom
Strony
62--73
Opis fizyczny
Bibliogr. 56 poz., rys.
Twórcy
autor
- Industrial Research Institute for Automation and Measurements PIAP, Warsaw, Poland
autor
- Industrial Research Institute for Automation and Measurements PIAP, Warsaw, Poland
Bibliografia
- [1] M. Honary, L. Mihaylova, C. Xydeas, „Practical Classification Methods for Indoor Positioning”, Open Transportation Journal, no. 6, 2012, 31–38.
- [2] J. Biswas, M. Veloso, „WiFi localization, navigation for autonomous indoor mobile robots”. In: 2010 IEEE International Conference on Robotics, Automation – ICRA, 4379–4384. DOI: 10.1109/ROBOT.2010.5509842.
- [3] P. Kemppi et al., „Hybrid positioning system combining angle-based localization, pedestrian dead reckoning, map filtering”. In: IPIN– 2010 International Conference on Indoor Positioning, Indoor Navigation, 2010. DOI: 10.1109/IPIN.2010.5646682.
- [4] P. Mirowski et al., „KL-Divergence Kernel Regression for Non-Gaussian Fingerprint Based Localization”. In: International Conference on Indoor Positioning, Indoor Navigation, Guimaraes, Portugal, 2011.
- [5] N. Le Dortz et al., „WiFi fingerprint indoor positioning system using probability distribution comparison”. In: 2012 IEEE International Conference on Acoustics, Speech, Signal Journal of Automation, Mobile Robotics & Intelligent Systems VOLUME 11, N° 3 201772 Articles Processing – ICASSP, 2301–2304. DOI: 10.1109/ICASSP.2012.6288374.
- [6] D. R. Brown, D. B. Dunn, „Classification schemes of positioning technologies for indoor navigation”.In: 2011 Proceedings of IEEE Southeastcon, 125–130. DOI: 10.1109/SECON.2011.5752919.
- [7] V. Moghtadaiee, A. G. Dempster, „WiFi fingerprinting signal strength error modeling for short distances”. In: International Conference on Indoor Positioning, Indoor Navigation, 1–6, 2012, Sydney, Australia. DOI: 10.1109/IPIN.2012.6418852.
- [8] C. Beder et al., „Predicting the expected accuracy for finger-printing based WiFi localization systems”. In: International Conference on Indoor Positioning, Indoor Navigation, 1–6, 2011, Guimaraes, Portugal. DOI: 10.1109/ IPIN.2011.6071939.
- [9] Z. Hengzhou et al., „Indoor Location Service Based on Finger-printing, Distance Relative Attenuation Model”. In: 2014 Sixth International Conference on Measuring Technology, Mechatronics Automation ICMTMA, 341–344. DOI: 10.1109/ICMTMA.2014.84.
- [10] C. Beder, M. Klepal, „Fingerprinting based localization revisited: A rigorous approach for comparing RSSI measurements coping with missed access points, differing antenna attenuations”. In: International Conference on Indoor Positioning, Indoor Navigation, Sydney, Australia, 1–7,2012. DOI: 10.1109/IPIN.2012.6418940.
- [11] J. Ledlie, „Mole: A scalable, user-generated WiFi positioning engine”. In: International Conference on Indoor Positioning, Indoor Navigation, 1–10, 2011, Guimaraes, Portugal. DOI: 10.1109/IPIN.2011.6071942.
- [12] P. Bolliger, „Redpin –adaptive, zero-configuration indoor localization through user collaboration”. In: Proceedings of the first ACM international workshop on Mobile entity localization and tracking in GPS-less environments – MELT’08,2008, 55–60. DOI: 10.1145/1410012.1410025.
- [13] P. Mirowski et al., „Probability kernel regression for WiFi localisation”, Journal of Location Based Services, vol. 6, 2012, 81–100. DOI:17489725.2012.694723.
- [14] E. Khvedchenya, Feature descriptor comparison report. http://computer-vision-talks.com/articles/2011-08-19-feature-descriptor-comparison-report/,2011. Available on 07.08.2014
- [15] M. A. Fischler, „Random sample consensus: a paradigm for model fitting with applications to image analysis, automated cartography. Communications of the ACM, vol. 24, no. 6, 1981,381–395. DOI: 10.1145/358669.358692.
- [16] H. V. Poor, „Fine quantization in signal detection, estimation”, IEEE Transactions on Information Theory, vol. 34, no. 5, 1988, 960–972. DOI:10.1109/18.21219.
- [17] F. Liese, I. Vajda, „On Divergences, Informations in Statistics”, IEEE Transactions on Information Theory, vol. 52, no. 10, 2006, 4394–4412. DOI:10.1109/TIT.2006.881731.
- [18] M. C. Pardo, I. Vajda, „On asymptotic propertiesof information-theoretic divergences”, IEEETransactions on Information Theory, vol. 49, no.7, 2003, 1860–1867.
- [19] D. L. Donoho, X. Huo, „Large-sample modulation classification using Hellinger representation”. In: First IEEE Signal Processing Workshop on Signal Processing Advances in Wireless Communications, 1997, 133–136.
- [20] J. R. Hershey, „Approximating the Kullback Leibler Divergence Between Gaussian Mixture Models”. In: IEEE International Conference on Acoustics, Speech, Signal Processing – ICASSP 2007, vol. 4, 2007, 317–320. DOI: 10.1109/ICASSP.2007.366913.
- [21] C. Liu, H-Y. Shum, „Kullback-Leibler boosting”. In: Proceedings of 2003 IEEE Computer Society Conference on Computer Vision, Pattern Recognition, vol. 1, 2003, 587–594.
- [22] V. N. Murali, „Autonomous navigation, mapping using monocular low-resolution grayscale vision”. IN: IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshop, 2008. DOI: CVPRW.2008.4563136.
- [23] J. Svihlik, „Model Parameters Estimation Using Jeffrey Divergence”. In: 17th International Conference Radioelektronika, 2007. DOI: 10.1109/RADIOELEK.2007.371654.
- [24] F. Topsoe, „Some inequalities for information divergence, related measures of discrimination”, IEEE Transactions on Information Theory, vol. 46, no. 4, 2000, 1602–1609. DOI: 10.1109/18.850703.
- [25] A. Ferrante, „Hellinger Versus Kullback–Leibler Multivariable Spectrum Approximation”, IEEE Transactions on Automatic Control, vol. 53, no. 4, 2008, 954–967. DOI: 10.1109/TAC.2008.920238.
- [26] Z. Yang et al., „Mobility Increases Localizability: A Survey on Wireless Indoor Localization using Inertial Sensors”, ACM Comput. Surv., vol. 47, no. 3, 2015. DOI: 10.1145/2676430.
- [27] I. Constandache, R.R. Choudhury, I. Rhee, „Towards mobile phone localization without wardriving”. In: 2010 Proceedings IEEE INFOCOM. DOI: 10.1109/INFCOM.2010.5462058.
- [28] M. Alzantot , M. Youssef, „CrowdInside: automatic construction of indoor floorplans”. In: Proceedings of the 20th International Conference on Advances in Geographic Information Systems, 2012. DOI: 10.1145/2424321.2424335.
- [29] S. Ayub et al., „Indoor pedestrian displacement estimation using smartphone inertial sensors”, International Journal of Innovative Computing, Applications, vol. 4, no. 1, 2012, 35–42.
- [30] S. Hilsenbeck et al., „Graph-based data fusion of pedometer, WiFi measurements for mobile indoor positioning”. In: Proceedings of the 2014 ACM International Joint Conference on Pervasive, Ubiquitous Computing, 2014.
- [31] H. Wang et al., „No need to wardrive: unsupervised indoor localization”. In: Proceedings of the 10th international conference on Mobile systems, applications, services, 2012.
- [32] Y. Chen et al., „FM-based indoor localization”. In: Proceedings of the 10th international conference on Mobile systems, applications, services, 2012.
- [33] C. Laoudias et al., „The Airplace Indoor Positioning Platform for Android Smartphone”. In: Proceedings of the 2012 IEEE 13th International Conference on Mobile Data Management, 2012, 312–315. DOI: 10.1109/MDM.2012.68.
- [34] P. Bahl, V. N. Padmanabhan, „RADAR: An InBuilding RF-based User Location, Tracking System”. In: Proceedings of INFOCOM, 2000. DOI:10.1109/INFCOM.2000.832252.
- [35] A. Haeberlen et al., „Practical robust localization over large-scale 802.11 wireless networks”. In: Proceedings of the 10th annual international conference on Mobile computing and networking,2004. DOI: 10.1145/1023720.1023728.
- [36] M. Youssef, A. Agrawala, „The horus WLAN location determination system”. In: Proceedings of the 3rd international conference on Mobile systems, applications and services, 2005. DOI: 10.1145/1067170.1067193.
- [37] A. Varshavsky et al., „Gsm indoor localization”, Pervasive Mob. Comput., vol. 3, no. 6, 2007, 698–720. DOI: 10.1016/j.pmcj.2007.07.004.
- [38] S. Sen, B. Radunovic, R. R. Choudhury, T. Minka, „You are facing the Mona Lisa: spot localization using PHY layer information”. In: Proceedings of the 10th international conference on Mobile systems, applications, services, 2012. DOI:10.1145/2307636.2307654.
- [39] L. M. Ni, Y. Liu, Y. C. Lau, A. P. Patil, „Landmarc: indoor location sensing using active RFID”, Wireless Networks, vol. 10, no. 6, 2004, 701–710.DOI: 10.1023/B:WINE.0000044029.06344.dd.
- [40] R. Bruno, F. Delmastro, Design, analysis of a bluetooth-based indoor localization system, Series: Personal Wireless Communications, Lecture Notes in Computer Science, 2003.
- [41] A. Matic, A. Popleteev, V. Osmani, O. MayoraIbarra, „FM radio for indoor localization with spontaneous recalibration”, Pervasive Mob. Comput., vol. 6, no. 6, 2010, 642–656. DOI: 10.1016/j.pmcj.2010.08.005.
- [42] S. Yoon, K. Lee , I. Rhee, „FM-based indoor localization via automatic fingerprint DB construction, matching”. In: Proceeding of the 11th annual international conference on mobile systems, applications, and services, 2013. DOI: 10.1145/2462456.2464445.
- [43] N. B. Priyantha, A. Chakraborty, H. Balakrishnan, „The cricket location-support system”. In: Proceedings of the 6th annual international conference on mobile computing and networking, 2000. DOI: 10.1145/345910.345917.
- [44] R. Want, A. Hopper, V. Falcão, J. Gibbons, „The active badge location system”, ACM Trans. Inf. Syst, vol. 10, 1992. DOI: 10.1145/128756.128759.
- [45] Z. Yang, Z. Wang, J. Zhang, C. Huang, Q. Zhang, „Wearables Can Afford: Light-weight Indoor Positioning with Visible Light”. In: Proceedings of the 13th annual international conference on mobile systems, applications, and services, 2015. DOI: 10.1145/2742647.2742648.
- [46] Y-S Kuo, P. Pannuto, K-J Hsiao, P. Dutta, „Luxapose: indoor positioning with mobile phones, visible light”. In: Proceedings of the 20th annual international conference on Mobile computing, and networking, 2014. DOI: 10.1145/2639108.2641747.
- [47] L. Li, P. Hu, C. Peng, G. Shen, F. Zhao, „Epsilon: a visible light based positioning system”. In: Proceedings of the 11th USENIX Conference on Networked Systems Design, Implementation, 2014.
- [48] G. B. Prince, T. D. Little, „A two phase hybrid RSS/AoA algorithm for indoor device localization using visible light”. In: 12th IEEE Global Communication Conference, 2012. DOI: 10.1109/GLOCOM.2012.6503631.
- [49] K. Chintalapudi, A. Iyer, V. Padmanabhan, „Indoor localization without the pain”. In: Proceedings of the sixteenth annual international conference on mobile computing, networking, 2010. DOI: 10.1145/1859995.1860016.
- [50] O. Woodman, R. Harle, „Pedestrian localisationfor indoor environments”. In: Proceedings of the 10th international conference on Ubiquitous computing – UbiComp’08, 2008. DOI: 10.1145/1409635.1409651.
- [51] F. Li et al., „A reliable, accurate indoor localization method using phone inertial sensors”. In: Proceedings of the international conference on Ubiquitous computing – UbiComp’12, 2012. DOI: 10.1145/2370216.2370280.
- [52] A. R. Jimenez, F. Seco, C. Prieto, J. Guevara, „A comparison of pedestrian dead-reckoning algorithms using a low-cost MEMS IMU”. In: Proceedings of IEEE International Symposium on Intelligent Signal Processing, 2009. DOI: 10.1109/ WISP.2009.5286542.
- [53] M. Youssef et al., „Gac: Energy-efficient hybrid gps-accelerometer-compass gsm localization”. In: 2010 IEEE Global Telecommunications Conference GLOBECOM 2010. DOI: 10.1109/GLOCOM.2010.5684304.
- [54] J. Liu et al., „Accelerometer assisted robust wireless signal positioning based on a hidden Markov model”. In: Proceedings of the IEEE/ ION Position Location, Navigation Symposium,2009. DOI: 10.1109/PLANS.2010.5507251.
- [55] A. W. S. Au et al., „Indoor Tracking, Navigation Using Received Signal Strength, Compressive Sensing on a Mobile Device”, IEEE Transactions on Mobile Computing, vol. 12, no. 10, 2013, 2050–2062. DOI: 10.1109/TMC.2012.175.
- [56] L. Hongbo et al., „Accurate WiFi Based Localization for Smartphones Using Peer Assistance”, IEEE Transactions on Mobile Computing, vol. 13, no. 10, 2014, 2199– 2214.
Uwagi
PL
Opracowanie ze środków MNiSW w ramach umowy 812/P-DUN/2016 na działalność upowszechniającą naukę (zadania 2017).
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-287a4320-6cf4-4e28-8dea-594b434ce5ad