CFP last date
22 April 2024
Reseach Article

Real-time Indoor Map Generation to Identify Spatial Environment Changes

by J. A. D. C. Anuradha Jayakody, R. H. Suriarachchi, O. W. Samarasinghe, B. A. Chamain, A. H. M. C. M. Abeyrathna
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 180 - Number 5
Year of Publication: 2017
Authors: J. A. D. C. Anuradha Jayakody, R. H. Suriarachchi, O. W. Samarasinghe, B. A. Chamain, A. H. M. C. M. Abeyrathna
10.5120/ijca2017916045

J. A. D. C. Anuradha Jayakody, R. H. Suriarachchi, O. W. Samarasinghe, B. A. Chamain, A. H. M. C. M. Abeyrathna . Real-time Indoor Map Generation to Identify Spatial Environment Changes. International Journal of Computer Applications. 180, 5 ( Dec 2017), 38-43. DOI=10.5120/ijca2017916045

@article{ 10.5120/ijca2017916045,
author = { J. A. D. C. Anuradha Jayakody, R. H. Suriarachchi, O. W. Samarasinghe, B. A. Chamain, A. H. M. C. M. Abeyrathna },
title = { Real-time Indoor Map Generation to Identify Spatial Environment Changes },
journal = { International Journal of Computer Applications },
issue_date = { Dec 2017 },
volume = { 180 },
number = { 5 },
month = { Dec },
year = { 2017 },
issn = { 0975-8887 },
pages = { 38-43 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume180/number5/28800-2017916045/ },
doi = { 10.5120/ijca2017916045 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-07T00:59:51.648254+05:30
%A J. A. D. C. Anuradha Jayakody
%A R. H. Suriarachchi
%A O. W. Samarasinghe
%A B. A. Chamain
%A A. H. M. C. M. Abeyrathna
%T Real-time Indoor Map Generation to Identify Spatial Environment Changes
%J International Journal of Computer Applications
%@ 0975-8887
%V 180
%N 5
%P 38-43
%D 2017
%I Foundation of Computer Science (FCS), NY, USA
Abstract

While there are many well-established techniques for outdoor contexts using technologies such as GPS, GSM and GNSS, they cannot be applied to an indoor environment. Thus, Indoor navigation remains a challenge as the state of an indoor environment is always unpredictable. Geographical co-ordinates can be applied for indoor localization, but they are not useful inside a building with multiple floors. In most of the approaches, a blueprint of the building is needed for mapping purposes. Hence, there is a need for an improved approach for indoor localization and mapping to overcome the drawbacks stated above. This paper presents an approach to generate a real-time indoor map in-order to identify the changes in the spatial environment. In this approach, authors consider an approach where the information is gathered from users’ mobile devices. The position of the user is obtained using iBeacons. Furthermore, this paper discusses how to obtain the sensor data and position of the user by using iBeacons, transferring the data to the database via an API, detecting objects present in the indoor environment and generating the real-time map.

References
  1. K. K. Naik and M. N. G. Prasad, "A system for locating users of WLAN using dynamic mapping in indoor and outdoor environment-LOIDS," 2008 11th International Conference on Computer and Information Technology, Khulna, 2008, pp. 156-160.
  2. V.S.P Vidanapathirana, K.H.M.R Peiris and D. Dhammearatchi, “HospiX: The Hospital Exploring Application for Smart Devices,” in International Journal of Scientific and Research Publications, vol. 5, no. 11, pp. 489-492, Nov. 2015.
  3. C. Wen, L. Qin, Q. Zhu, C. Wang and J. Li, "Three-Dimensional Indoor Mobile Mapping with Fusion of Two-Dimensional Laser Scanner and RGB-D Camera Data," in IEEE Geoscience and Remote Sensing Letters, vol. 11, no. 4, pp. 843-847, April 2014.
  4. J. Aulinas, Y. Petillot, J. Salvi and Xavier Lladó, “The SLAM problem: a survey,” in Proceedings of the 2008 conference on Artificial Intelligence Research and Development: Proceedings of the 11th International Conference of the Catalan Association for Artificial Intelligence, 2008, pp. 363-371.
  5. J. Du, Y. Ou and W. Sheng, "Improving 3D indoor mapping with motion data," 2012 IEEE International Conference on Robotics and Biomimetics (ROBIO), Guangzhou, 2012, pp. 489-494.
  6. C. Wen, L. Qin, Q. Zhu, C. Wang and J. Li, "Three-Dimensional Indoor Mobile Mapping with Fusion of Two-Dimensional Laser Scanner and RGB-D Camera Data," in IEEE Geoscience and Remote Sensing Letters, vol. 11, no. 4, pp. 843-847, April 2014.
  7. A. Janowski and M. Bednarczyk, "Considerations on Indoor Navigation Based on Cheap Mobile Devices," 2016 Baltic Geodetic Congress (BGC Geomatics), Gdansk, 2016, pp. 78-84.
  8. Y. Li, Y. Zhuang, H. Lan, P. Zhang, X. Niu and N. El-Sheimy, "Self-Contained Indoor Pedestrian Navigation Using Smartphone Sensors and Magnetic Features," in IEEE Sensors Journal, vol. 16, no. 19, pp. 7173-7182, Oct.1, 2016.
  9. J. A. D. C. A. Jayakody and I. Murray, "Proposed novel schema design for map generation to assist vision impaired in an indoor navigation environment," 2014 International Conference on Contemporary Computing and Informatics (IC3I), Mysore, 2014, pp. 490-494.
  10. Developer.estimote.com. (2017). Cite a Website - Cite This for Me. [online] Available at: http://developer.estimote.com/ [Accessed 17 Aug. 2017].
  11. Altbeacon.github.io. (2017). Android Beacon Library. [online] Available at: https://altbeacon.github.io/android-beacon-library/distance-calculations.html [Accessed 17 Aug. 2017].
  12. Rodriguez, U., Frisk, F. and Klonowska, K. (2011). Indoor Positioning using Sensor-fusion in Android Devices.
  13. API, C. (2017). Camera API | Android Developers. [online] Developer.android.com. Available at: https://developer.android.com/guide/topics/media/camera.html [Accessed 17 Aug. 2017].
  14. G. Amat, J. Fernandez, A. Arranz and A. Ramos, "Using Open Street Maps data and tools for indoor mapping in a Smart City scenario", in International Conference on Geographic Information Science, Vienna, Austria, 2014.
  15. Altbeacon.github.io. (2017). Android Beacon Library. [online] Available at: http://altbeacon.github.io/android-beacon-library/distance-calculations2.html [Accessed 17 Aug. 2017].
Index Terms

Computer Science
Information Sciences

Keywords

Components indoor navigation localization IBeacons API SLAM