Diseño e implementación de un sistema de navegación personal orientado al desplazamiento de usuarios con discapacidad visual en ambientes cerrados

ilustraciones, fotografias, graficas, mapas

Autores:: Montilla Montilla, Yeimy Maryury

Tipo de recurso:

Fecha de publicación:: 2022

Institución:: Universidad Nacional de Colombia

Repositorio:: Universidad Nacional de Colombia

Idioma:: spa

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dc.title.spa.fl_str_mv	Diseño e implementación de un sistema de navegación personal orientado al desplazamiento de usuarios con discapacidad visual en ambientes cerrados
dc.title.translated.eng.fl_str_mv	Design and implementation of a personal navigation system oriented to the movement of visually impaired users in indoor spaces
title	Diseño e implementación de un sistema de navegación personal orientado al desplazamiento de usuarios con discapacidad visual en ambientes cerrados
spellingShingle	Diseño e implementación de un sistema de navegación personal orientado al desplazamiento de usuarios con discapacidad visual en ambientes cerrados 550 - Ciencias de la tierra 600 - Tecnología (Ciencias aplicadas) Navegación en espacios cerrados Navegación interior 3D Posicionamiento Interior Modelamiento 3D Discapacidad visual IndoorGML CityGML BLE RSSI WPL 3D Indoor Navigation Indoor Positioning Visually Impaired 3D Modeling
title_short	Diseño e implementación de un sistema de navegación personal orientado al desplazamiento de usuarios con discapacidad visual en ambientes cerrados
title_full	Diseño e implementación de un sistema de navegación personal orientado al desplazamiento de usuarios con discapacidad visual en ambientes cerrados
title_fullStr	Diseño e implementación de un sistema de navegación personal orientado al desplazamiento de usuarios con discapacidad visual en ambientes cerrados
title_full_unstemmed	Diseño e implementación de un sistema de navegación personal orientado al desplazamiento de usuarios con discapacidad visual en ambientes cerrados
title_sort	Diseño e implementación de un sistema de navegación personal orientado al desplazamiento de usuarios con discapacidad visual en ambientes cerrados
dc.creator.fl_str_mv	Montilla Montilla, Yeimy Maryury
dc.contributor.advisor.none.fl_str_mv	León Sánchez, Camilo Alexander Lizarazo Salcedo, Ivan Alberto
dc.contributor.author.none.fl_str_mv	Montilla Montilla, Yeimy Maryury
dc.subject.ddc.spa.fl_str_mv	550 - Ciencias de la tierra 600 - Tecnología (Ciencias aplicadas)
topic	550 - Ciencias de la tierra 600 - Tecnología (Ciencias aplicadas) Navegación en espacios cerrados Navegación interior 3D Posicionamiento Interior Modelamiento 3D Discapacidad visual IndoorGML CityGML BLE RSSI WPL 3D Indoor Navigation Indoor Positioning Visually Impaired 3D Modeling
dc.subject.proposal.spa.fl_str_mv	Navegación en espacios cerrados Navegación interior 3D Posicionamiento Interior Modelamiento 3D
dc.subject.proposal.eng.fl_str_mv	Discapacidad visual IndoorGML CityGML BLE RSSI WPL 3D Indoor Navigation Indoor Positioning Visually Impaired 3D Modeling
description	ilustraciones, fotografias, graficas, mapas
publishDate	2022
dc.date.accessioned.none.fl_str_mv	2022-11-04T19:34:27Z
dc.date.available.none.fl_str_mv	2022-11-04T19:34:27Z
dc.date.issued.none.fl_str_mv	2022-10-30
dc.type.spa.fl_str_mv	Trabajo de grado - Maestría
dc.type.driver.spa.fl_str_mv	info:eu-repo/semantics/masterThesis
dc.type.version.spa.fl_str_mv	info:eu-repo/semantics/acceptedVersion
dc.type.content.spa.fl_str_mv	Text
dc.type.redcol.spa.fl_str_mv	http://purl.org/redcol/resource_type/TM
status_str	acceptedVersion
dc.identifier.uri.none.fl_str_mv	https://repositorio.unal.edu.co/handle/unal/82649
dc.identifier.instname.spa.fl_str_mv	Universidad Nacional de Colombia
dc.identifier.reponame.spa.fl_str_mv	Repositorio Institucional Universidad Nacional de Colombia
dc.identifier.repourl.spa.fl_str_mv	https://repositorio.unal.edu.co/
url	https://repositorio.unal.edu.co/handle/unal/82649 https://repositorio.unal.edu.co/
identifier_str_mv	Universidad Nacional de Colombia Repositorio Institucional Universidad Nacional de Colombia
dc.language.iso.spa.fl_str_mv	spa
language	spa
dc.relation.indexed.spa.fl_str_mv	RedCol LaReferencia
dc.relation.references.spa.fl_str_mv	Afyouni, I., Ray, C., and Claramunt, C. (2012). Spatial models for context-aware indoor navigation systems: A survey. Journal of Spatial Information Science, 4(4):85–123. Al-Madani, B., Orujov, F., Maskeli¯unas, R., Damaševicius, R., and Venckauskas, A. (2019). Fuzzy logic type-2 based wireless indoor localization system for navigation of visually impaired people in buildings. Sensors (Switzerland). Alattas, A., van Oosterom, P., Zlatanova, S., Hoeneveld, D., and Verbree, E. (2020). LADMIndoorGML for exploring user movements in evacuation exercise. Land Use Policy, 98:104219. Alattas, A., Zlatanova, S., Oosterom, P. V., Chatzinikolaou, E., Lemmen, C., and Li, K. J. (2017). Supporting indoor navigation using access rights to spaces based on combined use of IndoorGML and LADM models. ISPRS International Journal of Geo-Information. ALCALDÍA MAYOR DE BOGOTÁ D.C. (2014). Bogota - Orthophoto. https://serviciosgis.catastrobogota.gov.co/arcgis/rest/services/imagenes/Ortho2014/MapServer. Accessed: 2019-12-15. ALCALDÍA MAYOR DE BOGOTÁ D.C. (2019). Catastro - Construccion. https://serviciosgis.catastrobogota.gov.co/arcgis/rest/services/catastro/construccion/MapServer. Accessed: 2019-12-15. Bajaj, R., Ranaweera, S., and Agrawal, D. (2002). GPS: location-tracking technology. Computer, 35(4):92–94. Bisio, I., Lavagetto, F., Marchese, M., and Sciarrone, A. (2016). Smart probabilistic fingerprinting for WiFi-based indoor positioning with mobile devices. Pervasive and Mobile Computing, 31:107–123. Buyukdemircioglu, M. and Kocaman, S. (2020). Reconstruction and Efficient Visualization of Heterogeneous 3D City Models. Remote Sensing, 12(13):2128. CesiumJS (2021). 3D geospatial visualization for the web. Chan, K. Y., Engelke, U., and Abhayasinghe, N. (2017). An edge detection framework conjoining with IMU data for assisting indoor navigation of visually impaired persons. Expert Systems with Applications, 67:272–284. Chen, R. C., Huang, S. W., Lin, Y. C., and Zhao, Q. F. (2015). An indoor location system based on neural network and genetic algorithm. International Journal of Sensor Networks, 19(3-4):204–216. Coleman, D. (2014). Bluetooth Low Energy (BLE) Central plugin for Apache Cordova. Coret Gorgonio, F. J., Pérez Bou, J., and Alcantud Marín, F. (2015). Sistemas de orientación en el interior edificios de concurrencia pública. Prototipo ISMO. In V Congreso Internacional de Turismo para Todos + VI Congreso Internacional de Diseño, Redes de Investigación y Tecnología para todos DRT4ALL, 2015, pages 313–339. Danis, F. and Cemgil, A. (2017). Model-based localization and tracking using bluetooth low-energy beacons. Sensors, 17:2484. DBeaver (2022). About \| dbeaver community. Diakité, A. A., Zlatanova, S., and Li, K.-J. (2017). ABOUT THE SUBDIVISION OF INDOOR SPACES IN INDOORGML. ISPRS Annals of Photogrammetry, Remote Sensing and Spatial Information Sciences, IV-4/W5(4W5):41–48. Díaz-Vilariño, L., Boguslawski, P., Khoshelham, K., and Lorenzo, H. (2019). Obstacle-aware indoor pathfinding using point clouds. ISPRS International Journal of Geo-Information. Dijkstra, E. W. (1959). A note on two problems in connexion with graphs. Numerische Mathematik. Docker (2021). About Docker Engine \| Docker Documentation. Fadli, F., Kutty, N., Wang, Z., Zlatanova, S., Mahdjoubi, L., Boguslawski, P., and Zverovich, V. (2018). Extending indoor open street mapping environments to navigable 3D citygml building models: Emergency response assessment. In International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences - ISPRS Archives. Golestanian, M., Siva, J., and Poellabauer, C. (2017). Radio Frequency-Based Indoor Localization in Ad-Hoc Networks, pages 115–136. InTech. Gomes, A., Pinto, A., Soares, C., Torres, J. M., Sobral, P., and Moreira, R. S. (2018a). Indoor location using bluetooth low energy beacons. Advances in Intelligent Systems and Computing, 746:565–580. Gomes, J. P., Sousa, J. P., Cunha, C. R., and Morais, E. P. (2018b). An indoor navigation architecture using variable data sources for blind and visually impaired persons. Iberian Conference on Information Systems and Technologies, CISTI, 2018-June:1–5. Google (2022). Ayuda de google adsense \| usar chrome devtools para solucionar problemas con el servicio de anuncios. Gröger, G., Kolbe, T., Nagel, C., and Häfele, K.-H. (2012). OGC City Geography Markup Language (CityGML) En-coding Standard. Ogc. Gröger, G. and Plümer, L. (2012). CityGML - Interoperable semantic 3D city models. ISPRS Journal of Photogrammetry and Remote Sensing, 71:12–33. Hamieh, A., Ben Makhlouf, A., Louhichi, B., and Deneux, D. (2020). A BIM-based method to plan indoor paths. Automation in Construction, 113:103120. Hart, P. E., Nilsson, N. J., and Raphael, B. (1968). A Formal Basis for the Heuristic Determination of Minimum Cost Paths. IEEE Transactions on Systems Science and Cybernetics. Hatcher, A. (2002). Algebraic Topology. Cambridge University Press. Hernández, N., Alonso, J. M., and Ocaña, M. (2017). Fuzzy classifier ensembles for hierarchical WiFi-based semantic indoor localization. Expert Systems with Applications, 90:394–404. Huh, J.-H. and Seo, K. (2017). An indoor location-based control system using Bluetooth beacons for IoT systems. Sensors 2017, Vol. 17, Page 2917, 17:2917. Ideca (2020). La IDE de Bogotá \| La IDE de Bogotá. https://www.ideca.gov.co/sobre-ideca/la-idede-bogota. Accessed: 2020-03-14. Isikdag, U., Zlatanova, S., and Underwood, J. (2013). A BIM-Oriented Model for supporting indoor navigation requirements. Computers, Environment and Urban Systems, 41:112–123. ISO (2018). ISO 16739-1:2018 Preview Industry Foundation Classes (IFC) for data sharing in the construction and facility management industries – Part 1: Data schema. Technical report, International Organization for Standardization, Geneva, Switzerland. Jamali, A., Abdul Rahman, A., Boguslawski, P., Kumar, P., and Gold, C. M. (2017). An automated 3D modeling of topological indoor navigation network. GeoJournal, 82(1):157–170. Jung, H. and Lee, J. (2015). INDOOR SUBSPACING TO IMPLEMENT INDOORGML FOR INDOOR NAVIGATION. ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, XL-2/W4(2W4):25–27. Kang, H. K. and Li, K. J. (2017). A standard indoor spatial data model - OGC IndoorGML and implementation approaches. ISPRS International Journal of Geo-Information, 6(4):116. Kim, J. S., Yoo, S. J., and Li, K. J. (2014). Integrating IndoorGML and CityGML for indoor space. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), volume 8470 LNCS, pages 184–196. Springer Verlag. Kolbe, T. H., Gröger, G., and Plümer, L. (2008). CityGML – 3D City Models and their Potential for Emergency Response, pages 257–274. Taylor & Francis. Kontarinis, A., Zeitouni, K., Marinica, C., Vodislav, D., and Kotzinos, D. (2019). Towards a semantic indoor trajectory model. In CEUR Workshop Proceedings. Kunhoth, J., Karkar, A. G., Al-Maadeed, S., and Al-Ali, A. (2020). Indoor positioning and wayfinding systems: a survey. Laoudias, C., Moreira, A., Kim, S., Lee, S., Wirola, L., and Fischione, C. (2018). A survey of enabling technologies for network localization, tracking, and navigation. Li, K. J. (2008). Indoor space: A new notion of space. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Li, K.-J., Conti, G., Konstantinidis, E., Zlatanova, S., and Bamidis, P. (2019). OGC IndoorGML: A Standard Approach for Indoor Maps, pages 187–207. Elsevier. Mahida, P. T., Shahrestani, S., and Cheung, H. (2017). Localization techniques in indoor navigation system for visually impaired people. In 2017 17th International Symposium on Communications and Information Technologies (ISCIT), volume 2018-January, pages 1–6. IEEE. Martinez-Sala, A. S., Losilla, F., Sánchez-Aarnoutse, J. C., and García-Haro, J. (2015). Design, implementation and evaluation of an indoor navigation system for visually impaired people. Sensors (Switzerland). Miao, M., Spindler, M., and Weber, G. (2011). Requirements of indoor navigation system from blind users. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), volume 7058 LNCS, pages 673–679. Springer, Berlin, Heidelberg. Minew (2021). E2 Max Beacon - Minew. Montilla, Y. M. and León-Sánchez, C. (2020). 3d modelling of a building oriented to indoor navigation system for users with different mobility conditions. ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, VI-4/W2-2020:103–109. Murata, M., Ahmetovic, D., Sato, D., Takagi, H., Kitani, K. M., and Asakawa, C. (2019). Smartphonebased localization for blind navigation in building-scale indoor environments. Pervasive and Mobile Computing, 57:14–32. Naghdi, S. and O’Keefe, K. (2019). Trilateration with ble rssi accounting for pathloss due to human obstacles. pages 1–8. IEEE. Nakajima, M. and Haruyama, S. (2013). New indoor navigation system for visually impaired people using visible light communication. Eurasip Journal on Wireless Communications and Networking, 2013(1):1–10. Nelson, J. and Chavez, S. (2017). PostgREST Documentation — PostgREST 7.0.1 documentation. Nginx (2021). nginx. OGC (2012). OGC City Geography Markup Language (CityGML) Encoding Standard. Open Geospatial Consortium. Version: 2.0.0. OGC (2014). OGCR IndoorGML. Open Geospatial Consortium. Version: 1.0.0. OGC (2021). OGC City Geography Markup Language (CityGML) 3.0 Conceptual Model Users Guide. Open Geospatial Consortium. Version: 3.0.0. Orujov, F., Maskeli¯unas, R., Damaševicius, R., Wei, W., and Li, Y. (2018). Smartphone based intelligent indoor positioning using fuzzy logic. Future Generation Computer Systems. Park, S., Yu, K., and Kim, J. (2020). Data Model for IndoorGML Extension to Support Indoor Navigation of People with Mobility Disabilities. ISPRS International Journal of Geo-Information, 9(2):66. Pérez-Navarro, A., Torres-Sospedra, J., Montoliu, R., Conesa, J., Berkvens, R., Caso, G., Costa, C., Dorigatti, N., Hernández, N., Knauth, S., Lohan, E. S., Machaj, J., Moreira, A., and Wilk, P. (2018). Challenges of Fingerprinting in Indoor Positioning and Navigation. In Geographical and Fingerprinting Data to Create Systems for Indoor Positioning and Indoor/Outdoor Navigation, pages 1–20. Academic Press. pgRouting (2013). Camino más corto de Dijkstra. Poulose, A. and Han, D. S. (2019). Indoor localization using pdr with wi-fi weighted path loss algorithm. ICTC 2019 - 10th International Conference on ICT Convergence: ICT Convergence Leading the Autonomous Future, pages 689–693. Safe (2020). Safe Software \| FME \| Data Integration Platform. https://www.safe.com. Accessed: 2020-05-10. Satan, A. and Toth, Z. (2018). Development of bluetooth based indoor positioning application. In 2018 IEEE International Conference on Future IoT Technologies, Future IoT 2018, volume 2018-January, pages 1–6. Institute of Electrical and Electronics Engineers Inc. Serrão, M., Rodrigues, J. M., Rodrigues, J. I., and Du Buf, J. M. (2012). Indoor localization and navigation for blind persons using visual landmarks and a GIS. In Procedia Computer Science. Simões, W. C., Machado, G. S., Sales, A. M., de Lucena, M. M., Jazdi, N., and de Lucena, V. F. (2020). A review of technologies and techniques for indoor navigation systems for the visually impaired. Srivastava, S., Maheshwari, N., and Rajan, K. S. (2018). TOWARDS GENERATING SEMANTICALLY-RICH INDOORGML DATA FROM ARCHITECTURAL PLANS. ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, XLII-4(4):591–595. Takayama, T., Umezawa, T., Komuro, N., and Osawa, N. (2018). An indoor positioning method based on regression models with compound location fingerprints. In Proceedings of 5th IEEE Conference on Ubiquitous Positioning, Indoor Navigation and Location-Based Services, UPINLBS 2018. The Apache Software Foundation (2016). Architectural overview of Cordova platform - Apache Cordova. Timpf, S., Volta, G. S., Pollock, D. W., and Egenhofer, M. J. (1992). A conceptual model of wayfinding using multiple levels of abstraction. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Tsirmpas, C., Rompas, A., Fokou, O., and Koutsouris, D. (2015). An indoor navigation system for visually impaired and elderly people based on Radio Frequency Identification (RFID). Information Sciences. Wirola, L., Laine, T. A., and Syrjärinne, J. (2010). Mass-market requirements for indoor positioning and indoor navigation. In 2010 International Conference on Indoor Positioning and Indoor Navigation, IPIN 2010 - Conference Proceedings. Wong, M. O. and Lee, S. (2019). A Technical Review on Developing BIM-Oriented Indoor Route Planning. In Computing in Civil Engineering 2019: Visualization, Information Modeling, and Simulation - Selected Papers from the ASCE International Conference on Computing in Civil Engineering 2019. Yan, J., Diakité, A. A., Zlatanova, S., and Aleksandrov, M. (2019). Top-bounded spaces formed by the built environment for navigation systems. ISPRS International Journal of Geo-Information. Yang, B., Guo, L., Guo, R., Zhao, M., and Zhao, T. (2020). A novel trilateration algorithm for rssi-based indoor localization. IEEE Sensors Journal, 20:8164–8172. Yang, C. and Shao, H. R. (2015). WiFi-based indoor positioning. IEEE Communications Magazine. Zafari, F., Gkelias, A., and Leung, K. K. (2019). A Survey of Indoor Localization Systems and Technologies. IEEE Communications Surveys and Tutorials. Zhou, Y., Chen, H., Huang, Y., Luo, Y., Zhang, Y., and Xie, X. (2018). An indoor route planning method with environment awareness. In IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium, volume 2018-July, pages 2906–2909. IEEE. Zhou, Y., Pang, Y., Chen, F., and Zhang, Y. (2020). Three-dimensional indoor fire evacuation routing. ISPRS International Journal of Geo-Information. Zhu, N., Zhao, H., Feng, W., and Wang, Z. (2015). A novel particle filter approach for indoor positioning by fusing WiFi and inertial sensors. Chinese Journal of Aeronautics. Zhuang, Y., Syed, Z., Li, Y., and El-Sheimy, N. (2016). Evaluation of Two WiFi Positioning Systems Based on Autonomous Crowdsourcing of Handheld Devices for Indoor Navigation. IEEE Transactions on Mobile Computing. Zou, H., Wang, H., Xie, L., and Jia, Q.-S. (2013a). An rfid indoor positioning system by using weighted path loss and extreme learning machine. In 2013 IEEE 1st International Conference on Cyber-Physical Systems, Networks, and Applications (CPSNA), pages 66–71. IEEE. Zou, H., Xie, L., Jia, Q.-S., and Wang, H. (2013b). An integrative weighted path loss and extreme learning machine approach to rfid based indoor positioning. In International Conference on Indoor Positioning and Indoor Navigation, pages 1–5. IEEE.
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dc.format.extent.spa.fl_str_mv	xix, 98 páginas
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dc.publisher.spa.fl_str_mv	Universidad Nacional de Colombia
dc.publisher.program.spa.fl_str_mv	Bogotá - Ciencias Agrarias - Maestría en Geomática
dc.publisher.faculty.spa.fl_str_mv	Facultad de Ciencias Agrarias
dc.publisher.place.spa.fl_str_mv	Bogotá, Colombia
dc.publisher.branch.spa.fl_str_mv	Universidad Nacional de Colombia - Sede Bogotá
institution	Universidad Nacional de Colombia
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spelling	Atribución-NoComercial-SinDerivadas 4.0 Internacionalhttp://creativecommons.org/licenses/by-nc-nd/4.0/info:eu-repo/semantics/openAccesshttp://purl.org/coar/access_right/c_abf2León Sánchez, Camilo Alexander5babbcf04c4bb0d0a22aeca66ef8b56cLizarazo Salcedo, Ivan Albertoeac37626247254f9b7d1672d9219153bMontilla Montilla, Yeimy Maryury8b8ec2c6c268c6f6c2edd82439e589dd2022-11-04T19:34:27Z2022-11-04T19:34:27Z2022-10-30https://repositorio.unal.edu.co/handle/unal/82649Universidad Nacional de ColombiaRepositorio Institucional Universidad Nacional de Colombiahttps://repositorio.unal.edu.co/ilustraciones, fotografias, graficas, mapasLa navegación en ambientes cerrados puede llegar a ser compleja, especialmente para personas con discapacidad visual. Para asistir la navegación en ambientes cerrados se han propuesto sistemas de navegación interior (SNIs) que involucran tecnologías como WiFi, Bluetooth, RFID entre otras, las cuales son diferentes a los habituales Sistemas Globales de Navegación por Satélite (GNSS) porque estos son ineficientes por la pérdida de la señal que provoca la estructura de los edificios. Por otra parte, para asistir la navegación de personas con discapacidad se han propuesto soluciones que involucran el reconocimiento de obstáculos y espacios por medio de cámaras y sensores, lo cual resulta costoso de implementar. Por lo mencionado, se requiere la exploración de metodologías para el desarrollo de SNIs que logren un equilibrio entre costo de implementación, rendimiento, exactitud en la ubicación y sobre todo que proporcione información útil a las personas con discapacidad. El propósito de esta investigación fue proponer un sistema de navegación interior (SNI) orientado a usuarios con discapacidad visual, integrando los estándares del OGC IndoorGML y CityGML, para la construcción de los modelos semánticos y de representación 3D; en conjunto con el uso de la tecnología BLE, el valor de pérdida de señal RSSI y la técnica Weighted Path Loss (WPL) para calcular la ubicación del usuario. El desarrollo del SNI se inició con la definición de los requerimientos, posteriormente se desarrolló cada componente hasta obtener como resultado tangible el prototipo funcional de una aplicación web móvil, con la cual se desarrollaron diferentes pruebas para determinar la precisión y exactitud de la ubicación calculada. Los resultados indican que se logró un error de 0.63m en un escenario sin obstáculos y sin diferencias de altura; un error de 0.86m en un escenario con obstáculos y sin diferencia de altura y un error de 1.06m en un escenario con obstáculos y con diferencia de altura. Dichos resultados confirman el potencial del prototipo desarrollado para evolucionar en un sistema operacional. (Texto tomado de la fuente)Indoor navigation can become complex, especially for visually impaired people. To assist indoor navigation, systems have been proposed that involve technologies such as WiFi, Bluetooth, RFID, among others, which are different from the usual Global Navigation Satellite Systems (GNSS) because they are inefficient due to the loss of signal caused by the structure of buildings. On the other hand, to assist the navigation of people with disabilities, solutions have been proposed that involve the recognition of obstacles and spaces by means of cameras and sensors, which is costly to implement. Therefore, it is required the exploration of methodologies for the development of indoor navigation systems that achieve a balance between implementation cost, performance, location accuracy and above all that provide useful information to people with disabilities. The purpose of this research was to propose an indoor navigation system oriented to visually impaired users, integrating the OGC IndoorGML and CityGML standards, for the construction of semantic models and 3D representation; together with the use of BLE technology, the RSSI signal loss value and the Weighted Path Loss (WPL) technique to calculate the user's location. The development of the system started with the definition of the requirements, then each component was developed until obtaining as a tangible result the functional prototype of a mobile web application, with which different tests were developed to determine the precision and accuracy of the calculated location. The results indicate that an error of 0.63m was achieved in a scenario without obstacles and without height difference; an error of 0.86m in a scenario with obstacles and without height difference and an error of 1.06m in a scenario with obstacles and with height difference. These results confirm the potential of the developed prototype to evolve into an operational system.MaestríaMagíster en GeomáticaTecnologías Geoespacialesxix, 98 páginasapplication/pdfspaUniversidad Nacional de ColombiaBogotá - Ciencias Agrarias - Maestría en GeomáticaFacultad de Ciencias AgrariasBogotá, ColombiaUniversidad Nacional de Colombia - Sede Bogotá550 - Ciencias de la tierra600 - Tecnología (Ciencias aplicadas)Navegación en espacios cerradosNavegación interior 3DPosicionamiento InteriorModelamiento 3DDiscapacidad visualIndoorGMLCityGMLBLERSSIWPL3D Indoor NavigationIndoor PositioningVisually Impaired3D ModelingDiseño e implementación de un sistema de navegación personal orientado al desplazamiento de usuarios con discapacidad visual en ambientes cerradosDesign and implementation of a personal navigation system oriented to the movement of visually impaired users in indoor spacesTrabajo de grado - Maestríainfo:eu-repo/semantics/masterThesisinfo:eu-repo/semantics/acceptedVersionTexthttp://purl.org/redcol/resource_type/TMRedColLaReferenciaAfyouni, I., Ray, C., and Claramunt, C. (2012). Spatial models for context-aware indoor navigation systems: A survey. Journal of Spatial Information Science, 4(4):85–123.Al-Madani, B., Orujov, F., Maskeli¯unas, R., Damaševicius, R., and Venckauskas, A. (2019). Fuzzy logic type-2 based wireless indoor localization system for navigation of visually impaired people in buildings. Sensors (Switzerland).Alattas, A., van Oosterom, P., Zlatanova, S., Hoeneveld, D., and Verbree, E. (2020). LADMIndoorGML for exploring user movements in evacuation exercise. Land Use Policy, 98:104219.Alattas, A., Zlatanova, S., Oosterom, P. V., Chatzinikolaou, E., Lemmen, C., and Li, K. J. (2017). Supporting indoor navigation using access rights to spaces based on combined use of IndoorGML and LADM models. ISPRS International Journal of Geo-Information.ALCALDÍA MAYOR DE BOGOTÁ D.C. (2014). Bogota - Orthophoto. https://serviciosgis.catastrobogota.gov.co/arcgis/rest/services/imagenes/Ortho2014/MapServer. Accessed: 2019-12-15.ALCALDÍA MAYOR DE BOGOTÁ D.C. (2019). Catastro - Construccion. https://serviciosgis.catastrobogota.gov.co/arcgis/rest/services/catastro/construccion/MapServer. Accessed: 2019-12-15.Bajaj, R., Ranaweera, S., and Agrawal, D. (2002). GPS: location-tracking technology. Computer, 35(4):92–94.Bisio, I., Lavagetto, F., Marchese, M., and Sciarrone, A. (2016). Smart probabilistic fingerprinting for WiFi-based indoor positioning with mobile devices. Pervasive and Mobile Computing, 31:107–123.Buyukdemircioglu, M. and Kocaman, S. (2020). Reconstruction and Efficient Visualization of Heterogeneous 3D City Models. Remote Sensing, 12(13):2128.CesiumJS (2021). 3D geospatial visualization for the web.Chan, K. Y., Engelke, U., and Abhayasinghe, N. (2017). An edge detection framework conjoining with IMU data for assisting indoor navigation of visually impaired persons. Expert Systems with Applications, 67:272–284.Chen, R. C., Huang, S. W., Lin, Y. C., and Zhao, Q. F. (2015). An indoor location system based on neural network and genetic algorithm. International Journal of Sensor Networks, 19(3-4):204–216.Coleman, D. (2014). Bluetooth Low Energy (BLE) Central plugin for Apache Cordova.Coret Gorgonio, F. J., Pérez Bou, J., and Alcantud Marín, F. (2015). Sistemas de orientación en el interior edificios de concurrencia pública. Prototipo ISMO. In V Congreso Internacional de Turismo para Todos + VI Congreso Internacional de Diseño, Redes de Investigación y Tecnología para todos DRT4ALL, 2015, pages 313–339.Danis, F. and Cemgil, A. (2017). Model-based localization and tracking using bluetooth low-energy beacons. Sensors, 17:2484.DBeaver (2022). About \| dbeaver community.Diakité, A. A., Zlatanova, S., and Li, K.-J. (2017). ABOUT THE SUBDIVISION OF INDOOR SPACES IN INDOORGML. ISPRS Annals of Photogrammetry, Remote Sensing and Spatial Information Sciences, IV-4/W5(4W5):41–48.Díaz-Vilariño, L., Boguslawski, P., Khoshelham, K., and Lorenzo, H. (2019). Obstacle-aware indoor pathfinding using point clouds. ISPRS International Journal of Geo-Information.Dijkstra, E. W. (1959). A note on two problems in connexion with graphs. Numerische Mathematik.Docker (2021). About Docker Engine \| Docker Documentation.Fadli, F., Kutty, N., Wang, Z., Zlatanova, S., Mahdjoubi, L., Boguslawski, P., and Zverovich, V. (2018). Extending indoor open street mapping environments to navigable 3D citygml building models: Emergency response assessment. In International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences - ISPRS Archives.Golestanian, M., Siva, J., and Poellabauer, C. (2017). Radio Frequency-Based Indoor Localization in Ad-Hoc Networks, pages 115–136. InTech.Gomes, A., Pinto, A., Soares, C., Torres, J. M., Sobral, P., and Moreira, R. S. (2018a). Indoor location using bluetooth low energy beacons. Advances in Intelligent Systems and Computing, 746:565–580.Gomes, J. P., Sousa, J. P., Cunha, C. R., and Morais, E. P. (2018b). An indoor navigation architecture using variable data sources for blind and visually impaired persons. Iberian Conference on Information Systems and Technologies, CISTI, 2018-June:1–5.Google (2022). Ayuda de google adsense \| usar chrome devtools para solucionar problemas con el servicio de anuncios.Gröger, G., Kolbe, T., Nagel, C., and Häfele, K.-H. (2012). OGC City Geography Markup Language (CityGML) En-coding Standard. Ogc.Gröger, G. and Plümer, L. (2012). CityGML - Interoperable semantic 3D city models. ISPRS Journal of Photogrammetry and Remote Sensing, 71:12–33.Hamieh, A., Ben Makhlouf, A., Louhichi, B., and Deneux, D. (2020). A BIM-based method to plan indoor paths. Automation in Construction, 113:103120.Hart, P. E., Nilsson, N. J., and Raphael, B. (1968). A Formal Basis for the Heuristic Determination of Minimum Cost Paths. IEEE Transactions on Systems Science and Cybernetics.Hatcher, A. (2002). Algebraic Topology. Cambridge University Press.Hernández, N., Alonso, J. M., and Ocaña, M. (2017). Fuzzy classifier ensembles for hierarchical WiFi-based semantic indoor localization. Expert Systems with Applications, 90:394–404.Huh, J.-H. and Seo, K. (2017). An indoor location-based control system using Bluetooth beacons for IoT systems. Sensors 2017, Vol. 17, Page 2917, 17:2917.Ideca (2020). La IDE de Bogotá \| La IDE de Bogotá. https://www.ideca.gov.co/sobre-ideca/la-idede-bogota. Accessed: 2020-03-14.Isikdag, U., Zlatanova, S., and Underwood, J. (2013). A BIM-Oriented Model for supporting indoor navigation requirements. Computers, Environment and Urban Systems, 41:112–123.ISO (2018). ISO 16739-1:2018 Preview Industry Foundation Classes (IFC) for data sharing in the construction and facility management industries – Part 1: Data schema. Technical report, International Organization for Standardization, Geneva, Switzerland.Jamali, A., Abdul Rahman, A., Boguslawski, P., Kumar, P., and Gold, C. M. (2017). An automated 3D modeling of topological indoor navigation network. GeoJournal, 82(1):157–170.Jung, H. and Lee, J. (2015). INDOOR SUBSPACING TO IMPLEMENT INDOORGML FOR INDOOR NAVIGATION. ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, XL-2/W4(2W4):25–27.Kang, H. K. and Li, K. J. (2017). A standard indoor spatial data model - OGC IndoorGML and implementation approaches. ISPRS International Journal of Geo-Information, 6(4):116.Kim, J. S., Yoo, S. J., and Li, K. J. (2014). Integrating IndoorGML and CityGML for indoor space. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), volume 8470 LNCS, pages 184–196. Springer Verlag.Kolbe, T. H., Gröger, G., and Plümer, L. (2008). CityGML – 3D City Models and their Potential for Emergency Response, pages 257–274. Taylor & Francis.Kontarinis, A., Zeitouni, K., Marinica, C., Vodislav, D., and Kotzinos, D. (2019). Towards a semantic indoor trajectory model. In CEUR Workshop Proceedings.Kunhoth, J., Karkar, A. G., Al-Maadeed, S., and Al-Ali, A. (2020). Indoor positioning and wayfinding systems: a survey.Laoudias, C., Moreira, A., Kim, S., Lee, S., Wirola, L., and Fischione, C. (2018). A survey of enabling technologies for network localization, tracking, and navigation.Li, K. J. (2008). Indoor space: A new notion of space. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics).Li, K.-J., Conti, G., Konstantinidis, E., Zlatanova, S., and Bamidis, P. (2019). OGC IndoorGML: A Standard Approach for Indoor Maps, pages 187–207. Elsevier.Mahida, P. T., Shahrestani, S., and Cheung, H. (2017). Localization techniques in indoor navigation system for visually impaired people. In 2017 17th International Symposium on Communications and Information Technologies (ISCIT), volume 2018-January, pages 1–6. IEEE.Martinez-Sala, A. S., Losilla, F., Sánchez-Aarnoutse, J. C., and García-Haro, J. (2015). Design, implementation and evaluation of an indoor navigation system for visually impaired people. Sensors (Switzerland).Miao, M., Spindler, M., and Weber, G. (2011). Requirements of indoor navigation system from blind users. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), volume 7058 LNCS, pages 673–679. Springer, Berlin, Heidelberg.Minew (2021). E2 Max Beacon - Minew.Montilla, Y. M. and León-Sánchez, C. (2020). 3d modelling of a building oriented to indoor navigation system for users with different mobility conditions. ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, VI-4/W2-2020:103–109.Murata, M., Ahmetovic, D., Sato, D., Takagi, H., Kitani, K. M., and Asakawa, C. (2019). Smartphonebased localization for blind navigation in building-scale indoor environments. Pervasive and Mobile Computing, 57:14–32.Naghdi, S. and O’Keefe, K. (2019). Trilateration with ble rssi accounting for pathloss due to human obstacles. pages 1–8. IEEE.Nakajima, M. and Haruyama, S. (2013). New indoor navigation system for visually impaired people using visible light communication. Eurasip Journal on Wireless Communications and Networking, 2013(1):1–10.Nelson, J. and Chavez, S. (2017). PostgREST Documentation — PostgREST 7.0.1 documentation.Nginx (2021). nginx.OGC (2012). OGC City Geography Markup Language (CityGML) Encoding Standard. Open Geospatial Consortium. Version: 2.0.0.OGC (2014). OGCR IndoorGML. Open Geospatial Consortium. Version: 1.0.0.OGC (2021). OGC City Geography Markup Language (CityGML) 3.0 Conceptual Model Users Guide. Open Geospatial Consortium. Version: 3.0.0.Orujov, F., Maskeli¯unas, R., Damaševicius, R., Wei, W., and Li, Y. (2018). Smartphone based intelligent indoor positioning using fuzzy logic. Future Generation Computer Systems.Park, S., Yu, K., and Kim, J. (2020). Data Model for IndoorGML Extension to Support Indoor Navigation of People with Mobility Disabilities. ISPRS International Journal of Geo-Information, 9(2):66.Pérez-Navarro, A., Torres-Sospedra, J., Montoliu, R., Conesa, J., Berkvens, R., Caso, G., Costa, C., Dorigatti, N., Hernández, N., Knauth, S., Lohan, E. S., Machaj, J., Moreira, A., and Wilk, P. (2018). Challenges of Fingerprinting in Indoor Positioning and Navigation. In Geographical and Fingerprinting Data to Create Systems for Indoor Positioning and Indoor/Outdoor Navigation, pages 1–20. Academic Press.pgRouting (2013). Camino más corto de Dijkstra.Poulose, A. and Han, D. S. (2019). Indoor localization using pdr with wi-fi weighted path loss algorithm. ICTC 2019 - 10th International Conference on ICT Convergence: ICT Convergence Leading the Autonomous Future, pages 689–693.Safe (2020). Safe Software \| FME \| Data Integration Platform. https://www.safe.com. Accessed: 2020-05-10.Satan, A. and Toth, Z. (2018). Development of bluetooth based indoor positioning application. In 2018 IEEE International Conference on Future IoT Technologies, Future IoT 2018, volume 2018-January, pages 1–6. Institute of Electrical and Electronics Engineers Inc.Serrão, M., Rodrigues, J. M., Rodrigues, J. I., and Du Buf, J. M. (2012). Indoor localization and navigation for blind persons using visual landmarks and a GIS. In Procedia Computer Science.Simões, W. C., Machado, G. S., Sales, A. M., de Lucena, M. M., Jazdi, N., and de Lucena, V. F. (2020). A review of technologies and techniques for indoor navigation systems for the visually impaired.Srivastava, S., Maheshwari, N., and Rajan, K. S. (2018). TOWARDS GENERATING SEMANTICALLY-RICH INDOORGML DATA FROM ARCHITECTURAL PLANS. ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, XLII-4(4):591–595.Takayama, T., Umezawa, T., Komuro, N., and Osawa, N. (2018). An indoor positioning method based on regression models with compound location fingerprints. In Proceedings of 5th IEEE Conference on Ubiquitous Positioning, Indoor Navigation and Location-Based Services, UPINLBS 2018.The Apache Software Foundation (2016). Architectural overview of Cordova platform - Apache Cordova.Timpf, S., Volta, G. S., Pollock, D. W., and Egenhofer, M. J. (1992). A conceptual model of wayfinding using multiple levels of abstraction. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics).Tsirmpas, C., Rompas, A., Fokou, O., and Koutsouris, D. (2015). An indoor navigation system for visually impaired and elderly people based on Radio Frequency Identification (RFID). Information Sciences.Wirola, L., Laine, T. A., and Syrjärinne, J. (2010). Mass-market requirements for indoor positioning and indoor navigation. In 2010 International Conference on Indoor Positioning and Indoor Navigation, IPIN 2010 - Conference Proceedings.Wong, M. O. and Lee, S. (2019). A Technical Review on Developing BIM-Oriented Indoor Route Planning. In Computing in Civil Engineering 2019: Visualization, Information Modeling, and Simulation - Selected Papers from the ASCE International Conference on Computing in Civil Engineering 2019.Yan, J., Diakité, A. A., Zlatanova, S., and Aleksandrov, M. (2019). Top-bounded spaces formed by the built environment for navigation systems. ISPRS International Journal of Geo-Information.Yang, B., Guo, L., Guo, R., Zhao, M., and Zhao, T. (2020). A novel trilateration algorithm for rssi-based indoor localization. IEEE Sensors Journal, 20:8164–8172.Yang, C. and Shao, H. R. (2015). WiFi-based indoor positioning. IEEE Communications Magazine.Zafari, F., Gkelias, A., and Leung, K. K. (2019). A Survey of Indoor Localization Systems and Technologies. IEEE Communications Surveys and Tutorials.Zhou, Y., Chen, H., Huang, Y., Luo, Y., Zhang, Y., and Xie, X. (2018). An indoor route planning method with environment awareness. In IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium, volume 2018-July, pages 2906–2909. IEEE.Zhou, Y., Pang, Y., Chen, F., and Zhang, Y. (2020). Three-dimensional indoor fire evacuation routing. ISPRS International Journal of Geo-Information.Zhu, N., Zhao, H., Feng, W., and Wang, Z. (2015). A novel particle filter approach for indoor positioning by fusing WiFi and inertial sensors. Chinese Journal of Aeronautics.Zhuang, Y., Syed, Z., Li, Y., and El-Sheimy, N. (2016). Evaluation of Two WiFi Positioning Systems Based on Autonomous Crowdsourcing of Handheld Devices for Indoor Navigation. IEEE Transactions on Mobile Computing.Zou, H., Wang, H., Xie, L., and Jia, Q.-S. (2013a). An rfid indoor positioning system by using weighted path loss and extreme learning machine. In 2013 IEEE 1st International Conference on Cyber-Physical Systems, Networks, and Applications (CPSNA), pages 66–71. IEEE.Zou, H., Xie, L., Jia, Q.-S., and Wang, H. (2013b). An integrative weighted path loss and extreme learning machine approach to rfid based indoor positioning. In International Conference on Indoor Positioning and Indoor Navigation, pages 1–5. IEEE.AdministradoresEstudiantesGrupos comunitariosInvestigadoresPadres y familiasPersonal de apoyo escolarPúblico generalReceptores de fondos federales y solicitantesORIGINAL53931380.2022.pdf53931380.2022.pdfTesis de Maestría en Geomáticaapplication/pdf32844445https://repositorio.unal.edu.co/bitstream/unal/82649/4/53931380.2022.pdf57f7074caebb15a9e5811d6dcc9af89bMD54LICENSElicense.txtlicense.txttext/plain; charset=utf-85879https://repositorio.unal.edu.co/bitstream/unal/82649/5/license.txteb34b1cf90b7e1103fc9dfd26be24b4aMD55THUMBNAIL53931380.2022.pdf.jpg53931380.2022.pdf.jpgGenerated Thumbnailimage/jpeg4761https://repositorio.unal.edu.co/bitstream/unal/82649/6/53931380.2022.pdf.jpg39c232c34c3ca4abdb0f2173419efaedMD56unal/82649oai:repositorio.unal.edu.co:unal/826492024-08-12 02:00:52.772Repositorio Institucional Universidad Nacional de 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