ITM Web Conf.
Volume 24, 2019AMCSE 2018 - International Conference on Applied Mathematics, Computational Science and Systems Engineering
|Number of page(s)||9|
|Published online||01 February 2019|
- The World Bank, “Average mobile cellular subscriptions,” [Online]. Available: https://data.worldbank.org/indicator/IT.CEL.SETS.P2. [Accessed: 01-Nov-2018]. . [Google Scholar]
- A. Guillen-Perez and M.-D. Cano, “A WiFi-based method to count and locate pedestrians in urban traffic scenarios,” in WiMob 2018, 2018, vol. 02230. [Google Scholar]
- R. Sanchez-Iborra and M.-D. Cano, “On the similarities between urban traffic management and communication networks: Application of the random early detection algorithm for self-regulating intersections,” IEEE Intell. Transp. Syst. Mag., 9, 4 (2017). [CrossRef] [Google Scholar]
- NumPy.org, NumPy Website. (2018). Available at: http://www.numpy.org/ [Accessed 23 Oct. 2018]. [Google Scholar]
- E. Jones, T. Oliphant, P. Peterson, and others, “SciPy: Open source scientific tools for Python,” Computing in Science and Engineering, 9, 10–20 (2007). [Google Scholar]
- W. McKinney and P. D. Team, “Pandas,” Pandas Powerful Python Data Anal. Toolkit, 1625, (2015). [Google Scholar]
- A. E. C. Redondi and M. Cesana, “Building up knowledge through passive WiFi probes,” Comput. Commun., 117, 1–12 (2018). [CrossRef] [Google Scholar]
- E. Cianca, M. De Sanctis, and S. Di Domenico, “Radios as Sensors,” IEEE Internet Things J., 4, 363–373 (2017). [CrossRef] [Google Scholar]
- Y. Yuan, “Crowd Monitoring Using Mobile Phones,” in Sixth International Conference on Intelligent Human-Machine Systems and Cybernetics, 261–264 (2014) [Google Scholar]
- L. Schauer, M. Werner, and P. Marcus, “Estimating Crowd Densities and Pedestrian Flows Using Wi-Fi and Bluetooth,” in MOBIQUITOUS, 1–8 (2017). [Google Scholar]
- W. Pattanusorn, I. Nilkhamhang, S. Kittipiyakul, K. Ekkachai, and A. Takahashi, “Passenger estimation system using Wi-Fi probe request,” 7th Int. Conf. Inf. Commun. Technol. Embed. Syst. 2016, IC-ICTES 2016, 2016, 67–72 (2016). [Google Scholar]
- E. Vattapparamban, B. S. Çiftler, I. Güvenç, K. Akkaya, and A. Kadri, “Indoor occupancy tracking in smart buildings using passive sniffing of probe requests,” 2016 IEEE Int. Conf. Commun. Work. ICC 2016, 38–44, (2016). [CrossRef] [Google Scholar]
- L. Sun, S. Chen, Z. Zheng, and L. Xu, “Mobile Device Passive Localization based on IEEE 802 . 11 Probe Request Frames,”. 2017, 1, (2017). [Google Scholar]
- A.-C. Petre, C. Chilipirea, M. Baratchi, C. Dobre, and M. Van Steen, “WiFi Tracking of Pedestrian behavior,” in Smart Sensors Networks, Elsevier, 309–337 (2017). [CrossRef] [Google Scholar]
- Y. Fukuzaki, N. Nishio, M. Mochizuki, and K. Murao, “A pedestrian flow analysis system using Wi-Fi packet sensors to a real environment,” Proc. 2014 ACM Int. Jt. Conf. Pervasive Ubiquitous Comput. Adjun. Publ. UbiComp ’14 Adjun., 721–730 (2014). [Google Scholar]
- V. Acuna, A. Kumbhar, E. Vattapparamban, F. Rajabli, and I. Güvenç, “Localization of WiFi devices using probe requests captured at unmanned aerial vehicles,” IEEE Wirel. Commun. Netw. Conf. WCNC, (2017). [Google Scholar]
- A. B. M. Musa and J. Eriksson, “Tracking unmodified smartphones using wi-fi monitors,” Proc. 10th ACM Conf. Embed. Netw. Sens. Syst. SenSys ’12, 281 (2012). [Google Scholar]
- A. Basalamah, “Crowd Mobility Analysis using WiFi Sniffers,” Int. J. Adv. Comput. Sci. Appl., 7, 374–378 (2016). [Google Scholar]
- O. Kramer, “Scikit-Learn,” in Machine Learning for Evolution Strategies, (2016). [Google Scholar]
- S. H. Walker and D. B. Duncan, “Estimation of the probability of an event as a function of several independent variables.,” Biometrika, 54, 167–179 (1967). [CrossRef] [PubMed] [Google Scholar]
- C. Cortes and V. Vapnik, “Support-Vector Networks,” Mach. Learn., 20, 273–297 (1995). [Google Scholar]
- I. Rish, “An empirical study of the naive Bayes classifier,” in Workshop on empirical methods in artificial intelligence, 22230, pp. 41–46 (2001). [Google Scholar]
- T. K. Ho, “Random Decision Forests Tin Kam Ho Perceptron training,” in Proceedings of the 3rd International Conference on Document Analysis and Recognition, 278–282 (1995). [Google Scholar]
- B. W. Silverman and M. C. Jones, “E. Fix and J.L. Hodges (1951): An Important Contribution to Nonparametric Discriminant Analysis and Density Estimation: Commentary on Fix and Hodges (1951),” Int. Stat. Rev., 57, 233–238 (1989). [CrossRef] [Google Scholar]
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