PL EN


Preferencje help
Widoczny [Schowaj] Abstrakt
Liczba wyników
Powiadomienia systemowe
  • Sesja wygasła!
Tytuł artykułu

An indoor campus navigation system for users with disabilities

Treść / Zawartość
Identyfikatory
Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
While supporting navigation outside buildings is currentlywell solved through GPS-based systems, only a few solutions support indoor navigation and user positioning in large buildings. In this paper, we propose a solution to support such navigation by creating a dedicated hierarchical map of the building and associating it with the infrastructure of Bluetooth Low Energy (BLE) transmitters installed in the building. Then a user equipped with a smartphone can easily read the signals of these transmitters and, thanks to the map, can determine their position in space.We use our method in a system that supports navigation and user safety, emphasizing users with special needs, which we are implementing on our academic campus. We describe the idea, architecture, and implementation of this system.
Rocznik
Strony
81--93
Opis fizyczny
Bibliogr. 37 poz., rys., tab., wykr.
Twórcy
autor
  • University of Siedlce, Faculty of Exact and Natural Sciences, Institute of Computer Science, ul. 3 Maja 54, 08-110 Siedlce, Poland
  • University of Siedlce, Faculty of Exact and Natural Sciences, Institute of Computer Science, ul. 3 Maja 54, 08-110 Siedlce, Poland
  • University of Siedlce, Faculty of Exact and Natural Sciences, Institute of Computer Science, ul. 3 Maja 54, 08-110 Siedlce, Poland
Bibliografia
  • 1. S. A.Cheraghi et al. GuideBeacon: Beacon-based indoor wayfinding for the blind, visually impaired, anddisoriented. In 2017 IEEEinternational conference on pervasive computing and communications (PerCom), page 121–130, 2017.
  • 2. D. Ahmetovic et al. NavCog: A navigational cognitive assistant for the blind. In Proceedings of the 18th International Conference on HumanComputer Interaction with Mobile Devices and Services, pages 90–99. ACM, 2016.
  • 3. A. Alnafessah et al. Developing an ultra wideband indoor navigation system for visually impaired people. International Journal of Distributed Sensor Networks, 12:6152342–6152342, 07 2016.
  • 4. S. Ambroszkiewicz et al. Blind-enT; an approach to support orientation and navigation for blind people. Studia Informatica. Systems and Information Technology, (2):7–29, 2004.
  • 5. J. P. Bigham et al. Vizwiz: Nearly real-time answers to visual questions. Proceedings of the 23nd annual ACM symposium on User interface software and Technology, pages 333–342, 2010.
  • 6. Blind Help Project. Dot walker pro. https://blindhelp.net/software/dotwalker-pro. Last accessed: 01.07.2023.
  • 7. S. Chai et al. An indoor positioning algorithm using bluetooth low energy rssi. In Proceedings of the 2016 International Conference on Advanced Materials Science and Environmental Engineering, Chiang Mai, Thailand, pages 26–27, 2016.
  • 8. K. Curran et al. An evaluation of indoor location determination technologies. Journal of Location Based Services, 5 (2):61–78, 2011.
  • 9. K. Gao, H. Wang, J. Nazarko and G. Chobanov: Indoor Trajectory Prediction Algorithm Based on Communication Analysis of Built-In Sensors in Mobile Terminals. IEEE Sensors Journal, vol. 21, no. 22, pp. 25234-25242, 15 Nov.15, 2021.
  • 10. J. Gomez and F. Sandnes. RoboGuideDog: Guiding Blind Users Through Physical Environments with Laser Range Scanners. In Procedia Computer Science, volume 14, 07 2012.
  • 11. D. E. Grzechca et al. Analysis of Object Location Accuracy for iBeacon Technology based on the RSSI Path Loss Model and Fingerprint Map. International Journal of Electronics and Telecommunications, 62, 2016.
  • 12. J. Haverinen and A. Kemppainen. Global indoor self-localization based on the ambient magnetic field. Robotics and Autonomous Systems, 57(10):1028–1035, October 2009.
  • 13. J. Hileman et al. Mustache. Logic-less templates. https://mustache.github.io/. Last accessed: 01.07.2023.
  • 14. Interact.Indoor navigation. https://www.interactlighting.com/global/capabilities/indoor-navigation. Last accessed: 01.07.2023.
  • 15. Y.Javed and Z.Khan. Evaluating indoor location triangulation using wifi signals. Nutzwertanalysen in Marketing und Vertrieb, pages 180–186, 2019.
  • 16. J. R. Jiang et al. Fingerprint Feature Extraction for Indoor Localization. Sensors, 21:5434, August 2021.
  • 17. A. J. Jokar et al. An Introduction to OpenStreetMap in Geographic Information Science: Experiences, Research, and Applications, pages 1–15. 03 2015.
  • 18. M. Kaluza and B. Vukelic. Analysis of an indoor positioning systems. Zbornik Veleucilista u Rijeci y, 5:13–32, jan 2017.
  • 19. W. Kang and Y. Han. Smartpdr: Smartphone-based pedestrian dead reckoning for indoor localization. IEEE Sensors Journal, 15(5):2906– 2916, 2015.
  • 20. M. Konarski and W. Zabierowski. Using Google Maps API along with technology .NET. January 2010.
  • 21. G. A. Kumar et al. A LiDAR and IMU Integrated Indoor Navigation System for UAVs and Its Application in Real-Time Pipeline Classification. Sensors (Basel, Switzerland), 17, June 2017.
  • 22. A. LaMarca et al. Place Lab: Device Positioning Using Radio Beacons in the Wild. In Pervasive Computing, volume 3468, pages 116–133. Springer Berlin Heidelberg, Berlin, Heidelberg, 2005. Series Title: Lecture Notes in Computer Science.
  • 23. B. Li et al. Using barometers to determine the height for indoor positioning. 2013 International Conference on Indoor Positioning and Indoor Navigation (IPIN), pages 1–7, 2013.
  • 24. F. Li et al. A reliable and accurate indoor localization method using phone inertial sensors. In Proceedings of the 2012 ACM Conference on Ubiquitous Computing- UbiComp ’12, page 421, Pittsburgh, Pennsylvania, 2012. ACM Press.
  • 25. Indoor Atlas Ltd. Ambient magnetic field-based indoor location technology. Bringing the compass to the next level. http://web.indooratlas.com/web/WhitePaper.pdf,July2012.Lastaccessed:01.07.2023.
  • 26. F. Luiz et al. Accessibility analysis for the visually impaired using LazarilloApp. International Journal for Innovation Education and Research, 7, 12 2019.
  • 27. J. Kim M. Ji et al. Analysis of positioning accuracy corresponding to the number of ble beacons in indoor positioning system. 17th International Conference on Advanced Communication Technology (ICACT), pages 92–95, 2015.
  • 28. M. L. Mekhalfi et al. Recovering the sight to blind people in indoor environments with smart technologies. Expert Systems with Applications, 46:129–138, 2016.
  • 29. United Nations. United nations sustainable development 17 goals to transform our world. https://www.un.org/sustainabledevelopment/. Last accessed: 01.07.2023.
  • 30. M. Pilski. Technologies supporting independent moving inside buildings for people with visual impairment. Studia Informatica. Systems and Information Technology, 24:85–97, 2020.
  • 31. M. Pilski and M. Aleksandrowicz. Optimizing the placement of ble transmitters for indoor positioning systems. Studia Informatica. Systems and Information Technology, 27:95–107, 2022.
  • 32. M. F. Saaid et al. Radio frequency identification walking stick (RFIWS): A device for the blind. In 5th International Colloquium on Signal Processing & Its Applications, pages 250–253, 2009.
  • 33. M. Shchekotov and N. Shilov. Semi-Automatic Self-Calibrating Indoor Localization Using BLE Beacon Multilateration. In Proceeding of the 23rd Conference of Fruct Association, pages 346–355. Fruct Association 2018, 11 2018.
  • 34. S. Subedi et al. Beacon based indoor positioning system using weighted centroid localization approach. In 2016 Eighth International Conference on Ubiquitous and Future Networks (ICUFN), pages 1016–1019. IEEE, 2016.
  • 35. H.Tang and Z.Zhu. A segmentation-based stereovision approach for assisting visually impaired people. In International Conference on Computers for Handicapped Persons, pages 581–587. Springer, 2012.
  • 36. The Open API Initiative. Open API Specification. https://www.openapis.org/. Last accessed: 01.07.2023.
  • 37. B. Tognazzini et al. Ux guidelines for recommended content.https://www.nngroup.com/articles/recommendation-guidelines/. Last accessed: 01.07.2023.
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-d3ba879b-fa67-4899-9d27-bf74344885d3
JavaScript jest wyłączony w Twojej przeglądarce internetowej. Włącz go, a następnie odśwież stronę, aby móc w pełni z niej korzystać.