TIME TRAVEL ESTIMATIONS USING MAC ADDRESSES OF BUS, PASSENGERS: A POINT TO PATH-QGIS ANALYSIS

*Arief Hidayat orcid scopus  -  Urban and Transportation Planning Laboratory-Department of Civil Engineering-Tokyo University of Science, Japan
Shintaro Terabe  -  Urban and Transportation Planning Laboratory, Department of Civil Engineering, , Japan
Hideki Yaginuma  -  Urban and Transportation Planning Laboratory, Department of Civil Engineering, , Japan
Received: 26 Jul 2018; Published: 25 Oct 2018.
Open Access License URL: http://creativecommons.org/licenses/by-nc-sa/4.0

Citation Format:
Article Info
Section: Articles
Language: EN
Statistics: 783 93
Abstract

Currently, the developmentof wifi is proliferating. Especially in the field of transportation and smart cities. At the same time, wifi is a low-cost technology, which offers a longer survey time and is able to support the big data era. This paper describes our study, which first uses a wifi scanner to capture media access control (MAC) address data of bus passengers wifi devices and then identifies each MAC address travel time to confirm the bus passengers. The MAC address is a unique ID for aech device used suchh as moble phones, smartphones, laptops, tablets, and other wifi-enabled equipment. The wifi scanner was placed inside the bus to capture all tthe MAC addresses inside and around the bus. The survey was conducted for one day (eight hours). The paper describes the procedure of the time travel estimation for each MAC address using the “point to path” analysis in QGIS open source software. This procedure, using point to path-GIS, produced 70.000-80.000 raw data points cleaned into 100-130 new data point. The procedure determined how many passengers traveled and explained which bus passengers used based on travel time.

Keywords: WiFi scanner; Point to Path; GIS; Travel Time; Procedure; MAC address

Article Metrics:

  1. Abbott-jard, M., Shah, H., & Bhaskar, A. (2013). Empirical evaluation of Bluetooth and Wifi scanning for road transport. Proceedings of the Australasian Transport Research Forum, (October), 1–14.

  2. Abedi, N. (2014). Monitoring Spatiotemporal Dynamics of Human Movement Based On Mac Address Data. Queensland University of Technology.

  3. Abedi, N., Bhaskar, A., Chung, E., & Miska, M. (2015). Assessment of antenna characteristic effects on pedestrian and cyclists travel-time estimation based on Bluetooth and WiFi MAC addresses. Transportation Research Part C: Emerging Technologies, 60, 124–141. [https://doi.org/10.1016/j.trc.2015.08.010">Crossref]

  4. Abousaeidi, M., Fauzi, R., & Muhamad, R. (2016). Geographic Information System (GIS) modeling approach to determine the fastest delivery routes. Saudi Journal of Biological Sciences, 23(5), 555–564. [https://doi.org/10.1016/j.sjbs.2015.06.004">Crossref]

  5. Al-Husainy, D., & Fadhil, M. (2013). MAC Address as a Key for Data Encryption. (IJCSIS) International Journal of Computer Science and Information Security, 83–87.

  6. Aldasouqi, I., & Salameh, W. A. (2014). Using GIS in Designing and Deploying Wireless Network in City Plans. International Journal of Computer Networks (IJCN), 6(4), 66–75.

  7. Araghi, B. N., Hammershøj Olesen, J., Krishnan, R., Tørholm Christensen, L., & Lahrmann, H. (2015). Reliability of Bluetooth Technology for Travel Time Estimation. Journal of Intelligent Transportation Systems, 19(3), 240–255. [https://doi.org/10.1080/15472450.2013.856727">Crossref]

  8. Asija, M. (2016). MAC Address. IRA-International Journal of Technology & Engineering, 03(01), 41–60.

  9. Böhm, M. F., Ryeng, E. O., & Haugen, T. (2016). Evaluating the Usage of Wi-Fi and Bluetooth Based Sensors for Pedestrian Counting in Urban Areas. European Transport Conference, 24p–24p.

  10. Cisco. (2008). 802.11 Security Summary. Wireless and Network Security Integration Solution Design Guide, Chapter 3, 1–20.

  11. Cunche, M. (2014). I know your MAC address: targeted tracking of individual using Wi-Fi. Journal of Computer Virology and Hacking Techniques, 10(4), 219–227. [https://doi.org/10.1007/s11416-013-0196-1">Crossref]

  12. Dunlap, M., Li, Z., Henrickson, K., & Wang, Y. (2016). Estimation of Origin and Destination Information from Bluetooth and Wi-Fi Sensing for Transit. Transportation Research Record: Journal of the Transportation Research Board, 2595(2595), 11–17.[https://doi.org/10.3141/2595-02">Crossref]

  13. Feng, J., & Liu, Y. (2012). Wifi-based indoor navigation with mobile GIS and speech recognition. IJCSI International Journal of Computer Science Issues, 9(6), 256–263.

  14. Hidayat, A., Terabe, S., & Yaginuma, H. (2017a). Mapping of MAC Address with Moving WiFi Scanner. International Journal of Artificial Intelligence Research, 1(2), 34–29. [https://doi.org/10.29099/ijair.v1i2.27">Crossref]

  15. Hidayat, A., Terabe, S., & Yaginuma, H. (2017b). WiFi Scanner for Obtaining Pedestrian Data. Plano Madani, 6(2), 128–136.

  16. Hidayat, A., Terabe, S., & Yaginuma, H. (2018a). Determine Non-Passenger Data from WiFi Scanner Data (MAC Address), A Case Study: Romango Bus, Obuse, Nagano Prefecture, Japan. International Review for Spatial Planning and Sustainable Development, 6(3), 154–167. [https://doi.org/10.1177/0361198118776153">Crossref]

  17. Hidayat, A., Terabe, S., & Yaginuma, H. (2018b). WiFi Scanner Technologies for Obtaining Travel Data about Circulator Bus Passengers: Case Study in Obuse, Nagano Prefecture, Japan. Transportation Research Record: Journal of the Transportation Research Board. [Crossref]

  18. Ilayaraja, K. (2013). Road network analysis in Neyveli Township , Cuddalore District by using Quantum GIS. Indian Journal of Computer Science and Engineering (IJCSE), 4(1), 56–61.

  19. Jackson, S., Lesani, A., & Moreno, L. F. (2014). Towards a WIFI system for traffic monitoring in different transportation facilities. Transportation Research Board, 93rd Annual Meeting, (January), 1–19.

  20. Martin, J., Mayberry, T., Donahue, C., Foppe, L., Brown, L., Riggins, C., … Brown, D. (2017). A Study of MAC Address Randomization in Mobile Devices and When it Fails. Proceedings on Privacy Enhancing Technologies, 2017(4), 268–286. [https://doi.org/10.1515/popets-2017-0054">Crossref]

  21. Matte, C. (2017). Wi-Fi Tracking: Fingerprinting Attacks and Counter-Measures. Universite de Lyon.

  22. Meng-Lung Lin, Chien-Min Chu, C.-H., & Tsai, C.-C. C. and C.-Y. C. (2009). Geovisualization of Tourist Activity Travel Patterns Using 3D GIS: An empirical study of Tamsui, Taiwan. International Journal of Civil and Architectural Engineering, 3(12), 394–398.

  23. Musa, A. B. M., & Eriksson, J. (2012). Tracking unmodified smartphones using wi-fi monitors. Proceedings of the 10th ACM Conference on Embedded Network Sensor Systems - SenSys ’12, 281. [https://doi.org/10.1145/2426656.2426685">Crossref]

  24. Najafi, P., Georgiou, A., Shachneva, D., & Vlavianos, I. (2014). Privacy Leaks from Wi-Fi Probing. London.

  25. Odiyo, M. O. (2014). Use of GIS in Mapping the Spatial Distribution and Security of Wi-Fi Networks. Geospatial and Space Technology.

  26. Ohmori, N., Muromachi, Y., Harata, N., & Ohta, K. (2002). Analysis of Day-to-Day Variations of Travel Time Using GPS and GIS. Proceedings of the Conference on Traffic and Transportation Studies, ICTTS, 1–8.

  27. QGIS. (2011). Points to path.

  28. Ryeng, E. O., Haugen, T., Grønlund, H., & Overå, S. B. (2016). Evaluating Bluetooth and Wi-Fi Sensors as a Tool for Collecting Bicycle Speed at Varying Gradients. Transportation Research Procedia, 14(2352), 2289–2296. [https://doi.org/10.1016/j.trpro.2016.05.245">Crossref]

  29. Sapiezynski, P., Stopczynski, A., Gatej, R., & Lehmann, S. (2015). Tracking Human Mobility Using WiFi Signals. PLOS ONE, 10(7), e0130824. [https://doi.org/10.1371/journal.pone.0130824">Crossref]

  30. Sherman, G. (2011). QGIS Plugin: Points to Paths.

  31. Shiravi, S., Hossain, K., Fu, L., & Ghods, A. (2016). Evaluation of Using Wifi Signals to Estimate Intersection Travel Time. Proceedings, Annual Conference - Canadian Society for Civil Engineering (2016) 4, (August), 1–9.

  32. Shlayan, N., Kurkcu, A., & Ozbay, K. (2016). Exploring pedestrian Bluetooth and WiFi detection at public transportation terminals. 2016 IEEE 19th International Conference on Intelligent Transportation Systems (ITSC), 229–234. [https://doi.org/10.1109/ITSC.2016.7795559">Crossref]

  33. Sridhar, T. (2008). Wi-Fi, Bluetooth and WiMax - Technology and Implementation. The Internet Protocol Journal, 11(4), 2–17.

  34. Sun, L., Chen, S., Zheng, Z., & Xu, L. (2017). Mobile Device Passive Localization Based on IEEE 802.11 Probe Request Frames. Mobile Information Systems, 2017, 1–10. [https://doi.org/10.1155/2017/7821585">Crossref]

  35. Terabe, S., Hidayat, A., & Yaginuma, H. (2017). WiFi Sensing Technologies for Affordable Travel Data Collection from Bus Passengers. The 11th International Conference on Transport Survey Methods, 1–11.

  36. Verbree, E., Zlatanova, S., van Winden, K. B. A., van der Laan, E. B., Makri, A., Taizhou, L., & Haojun, A. (2013). To localise or to be localised with WiFi in the Hubei museum? ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, XL-4/W4(4W4), 31–35. [https://doi.org/10.5194/isprsarchives-XL-4-W4-31-2013">Crossref]

  37. Xia, H., Qiao, Y., Jian, J., & Chang, Y. (2014). Using Smart Phone Sensors to Detect Transportation Modes. Sensors, 14(11), 20843–20865. [https://doi.org/10.3390/s141120843">Crossref]

  38. Xu, Z., Sandrasegaran, K., Kong, X., Zhu, X., Zhao, J., Hu, B., & Chung Lin, C.-. (2013). Pedestrain Monitoring System using Wi-Fi Technology And RSSI Based Localization. International Journal of Wireless & Mobile Networks, 5(4), 17–34. [https://doi.org/10.5121/ijwmn.2013.5402">Crossref]

  39. Yaik, O. B., Wai, K. Z., K.T.Tan, I., & Sheng, O. B. (2016). Measuring the Accuracy of Crowd Counting using Wi-Fi Probe-Request-Frame Counting Technique. Journal of Telecommunication, Electronic and Computer Engineering (JTEC), 8(2), 79–81.

  40. Yu, H., & Shaw, S. (2004). Representing and visualizing travel diary data: a spatio-temporal GIS approach. 2004 ESRI International User Conference, (April), 1–13.

  41. Zambrano, G. R., Tepán, F. M., Jaime, A. P., & Guevara, J. M. (2016). Visualization and analysis of vehicle paths with QGis and Weka. International Journal of Innovation and Applied Studies, 18(4), 9324.


No citation recorded.