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

dc.contributor.advisorLeón Sánchez, Camilo Alexander
dc.contributor.advisorLizarazo Salcedo, Ivan Alberto
dc.contributor.authorMontilla Montilla, Yeimy Maryury
dc.date.accessioned2022-11-04T19:34:27Z
dc.date.available2022-11-04T19:34:27Z
dc.date.issued2022-10-30
dc.descriptionilustraciones, fotografias, graficas, mapasspa
dc.description.abstractLa 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)spa
dc.description.abstractIndoor 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.eng
dc.description.degreelevelMaestríaspa
dc.description.degreenameMagíster en Geomáticaspa
dc.description.researchareaTecnologías Geoespacialesspa
dc.format.extentxix, 98 páginasspa
dc.format.mimetypeapplication/pdfspa
dc.identifier.instnameUniversidad Nacional de Colombiaspa
dc.identifier.reponameRepositorio Institucional Universidad Nacional de Colombiaspa
dc.identifier.repourlhttps://repositorio.unal.edu.co/spa
dc.identifier.urihttps://repositorio.unal.edu.co/handle/unal/82649
dc.language.isospaspa
dc.publisherUniversidad Nacional de Colombiaspa
dc.publisher.branchUniversidad Nacional de Colombia - Sede Bogotáspa
dc.publisher.facultyFacultad de Ciencias Agrariasspa
dc.publisher.placeBogotá, Colombiaspa
dc.publisher.programBogotá - Ciencias Agrarias - Maestría en Geomáticaspa
dc.relation.indexedRedColspa
dc.relation.indexedLaReferenciaspa
dc.relation.referencesAfyouni, 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.spa
dc.relation.referencesAl-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).spa
dc.relation.referencesAlattas, 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.spa
dc.relation.referencesAlattas, 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.spa
dc.relation.referencesALCALDÍA MAYOR DE BOGOTÁ D.C. (2014). Bogota - Orthophoto. https://serviciosgis.catastrobogota.gov.co/arcgis/rest/services/imagenes/Ortho2014/MapServer. Accessed: 2019-12-15.spa
dc.relation.referencesALCALDÍA MAYOR DE BOGOTÁ D.C. (2019). Catastro - Construccion. https://serviciosgis.catastrobogota.gov.co/arcgis/rest/services/catastro/construccion/MapServer. Accessed: 2019-12-15.spa
dc.relation.referencesBajaj, R., Ranaweera, S., and Agrawal, D. (2002). GPS: location-tracking technology. Computer, 35(4):92–94.spa
dc.relation.referencesBisio, 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.spa
dc.relation.referencesBuyukdemircioglu, M. and Kocaman, S. (2020). Reconstruction and Efficient Visualization of Heterogeneous 3D City Models. Remote Sensing, 12(13):2128.spa
dc.relation.referencesCesiumJS (2021). 3D geospatial visualization for the web.spa
dc.relation.referencesChan, 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.spa
dc.relation.referencesChen, 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.spa
dc.relation.referencesColeman, D. (2014). Bluetooth Low Energy (BLE) Central plugin for Apache Cordova.spa
dc.relation.referencesCoret 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.spa
dc.relation.referencesDanis, F. and Cemgil, A. (2017). Model-based localization and tracking using bluetooth low-energy beacons. Sensors, 17:2484.spa
dc.relation.referencesDBeaver (2022). About | dbeaver community.spa
dc.relation.referencesDiakité, 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.spa
dc.relation.referencesDíaz-Vilariño, L., Boguslawski, P., Khoshelham, K., and Lorenzo, H. (2019). Obstacle-aware indoor pathfinding using point clouds. ISPRS International Journal of Geo-Information.spa
dc.relation.referencesDijkstra, E. W. (1959). A note on two problems in connexion with graphs. Numerische Mathematik.spa
dc.relation.referencesDocker (2021). About Docker Engine | Docker Documentation.spa
dc.relation.referencesFadli, 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.spa
dc.relation.referencesGolestanian, M., Siva, J., and Poellabauer, C. (2017). Radio Frequency-Based Indoor Localization in Ad-Hoc Networks, pages 115–136. InTech.spa
dc.relation.referencesGomes, 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.spa
dc.relation.referencesGomes, 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.spa
dc.relation.referencesGoogle (2022). Ayuda de google adsense | usar chrome devtools para solucionar problemas con el servicio de anuncios.spa
dc.relation.referencesGröger, G., Kolbe, T., Nagel, C., and Häfele, K.-H. (2012). OGC City Geography Markup Language (CityGML) En-coding Standard. Ogc.spa
dc.relation.referencesGröger, G. and Plümer, L. (2012). CityGML - Interoperable semantic 3D city models. ISPRS Journal of Photogrammetry and Remote Sensing, 71:12–33.spa
dc.relation.referencesHamieh, A., Ben Makhlouf, A., Louhichi, B., and Deneux, D. (2020). A BIM-based method to plan indoor paths. Automation in Construction, 113:103120.spa
dc.relation.referencesHart, 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.spa
dc.relation.referencesHatcher, A. (2002). Algebraic Topology. Cambridge University Press.spa
dc.relation.referencesHernández, 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.spa
dc.relation.referencesHuh, 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.spa
dc.relation.referencesIdeca (2020). La IDE de Bogotá | La IDE de Bogotá. https://www.ideca.gov.co/sobre-ideca/la-idede-bogota. Accessed: 2020-03-14.spa
dc.relation.referencesIsikdag, U., Zlatanova, S., and Underwood, J. (2013). A BIM-Oriented Model for supporting indoor navigation requirements. Computers, Environment and Urban Systems, 41:112–123.spa
dc.relation.referencesISO (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.spa
dc.relation.referencesJamali, 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.spa
dc.relation.referencesJung, 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.spa
dc.relation.referencesKang, 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.spa
dc.relation.referencesKim, 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.spa
dc.relation.referencesKolbe, T. H., Gröger, G., and Plümer, L. (2008). CityGML – 3D City Models and their Potential for Emergency Response, pages 257–274. Taylor & Francis.spa
dc.relation.referencesKontarinis, A., Zeitouni, K., Marinica, C., Vodislav, D., and Kotzinos, D. (2019). Towards a semantic indoor trajectory model. In CEUR Workshop Proceedings.spa
dc.relation.referencesKunhoth, J., Karkar, A. G., Al-Maadeed, S., and Al-Ali, A. (2020). Indoor positioning and wayfinding systems: a survey.spa
dc.relation.referencesLaoudias, C., Moreira, A., Kim, S., Lee, S., Wirola, L., and Fischione, C. (2018). A survey of enabling technologies for network localization, tracking, and navigation.spa
dc.relation.referencesLi, 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).spa
dc.relation.referencesLi, K.-J., Conti, G., Konstantinidis, E., Zlatanova, S., and Bamidis, P. (2019). OGC IndoorGML: A Standard Approach for Indoor Maps, pages 187–207. Elsevier.spa
dc.relation.referencesMahida, 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.spa
dc.relation.referencesMartinez-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).spa
dc.relation.referencesMiao, 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.spa
dc.relation.referencesMinew (2021). E2 Max Beacon - Minew.spa
dc.relation.referencesMontilla, 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.spa
dc.relation.referencesMurata, 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.spa
dc.relation.referencesNaghdi, S. and O’Keefe, K. (2019). Trilateration with ble rssi accounting for pathloss due to human obstacles. pages 1–8. IEEE.spa
dc.relation.referencesNakajima, 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.spa
dc.relation.referencesNelson, J. and Chavez, S. (2017). PostgREST Documentation — PostgREST 7.0.1 documentation.spa
dc.relation.referencesNginx (2021). nginx.spa
dc.relation.referencesOGC (2012). OGC City Geography Markup Language (CityGML) Encoding Standard. Open Geospatial Consortium. Version: 2.0.0.spa
dc.relation.referencesOGC (2014). OGCR IndoorGML. Open Geospatial Consortium. Version: 1.0.0.spa
dc.relation.referencesOGC (2021). OGC City Geography Markup Language (CityGML) 3.0 Conceptual Model Users Guide. Open Geospatial Consortium. Version: 3.0.0.spa
dc.relation.referencesOrujov, F., Maskeli¯unas, R., Damaševicius, R., Wei, W., and Li, Y. (2018). Smartphone based intelligent indoor positioning using fuzzy logic. Future Generation Computer Systems.spa
dc.relation.referencesPark, 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.spa
dc.relation.referencesPérez-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.spa
dc.relation.referencespgRouting (2013). Camino más corto de Dijkstra.spa
dc.relation.referencesPoulose, 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.spa
dc.relation.referencesSafe (2020). Safe Software | FME | Data Integration Platform. https://www.safe.com. Accessed: 2020-05-10.spa
dc.relation.referencesSatan, 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.spa
dc.relation.referencesSerrão, 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.spa
dc.relation.referencesSimões, 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.spa
dc.relation.referencesSrivastava, 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.spa
dc.relation.referencesTakayama, 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.spa
dc.relation.referencesThe Apache Software Foundation (2016). Architectural overview of Cordova platform - Apache Cordova.spa
dc.relation.referencesTimpf, 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).spa
dc.relation.referencesTsirmpas, 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.spa
dc.relation.referencesWirola, 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.spa
dc.relation.referencesWong, 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.spa
dc.relation.referencesYan, 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.spa
dc.relation.referencesYang, 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.spa
dc.relation.referencesYang, C. and Shao, H. R. (2015). WiFi-based indoor positioning. IEEE Communications Magazine.spa
dc.relation.referencesZafari, F., Gkelias, A., and Leung, K. K. (2019). A Survey of Indoor Localization Systems and Technologies. IEEE Communications Surveys and Tutorials.spa
dc.relation.referencesZhou, 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.spa
dc.relation.referencesZhou, Y., Pang, Y., Chen, F., and Zhang, Y. (2020). Three-dimensional indoor fire evacuation routing. ISPRS International Journal of Geo-Information.spa
dc.relation.referencesZhu, 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.spa
dc.relation.referencesZhuang, 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.spa
dc.relation.referencesZou, 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.spa
dc.relation.referencesZou, 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.spa
dc.rights.accessrightsinfo:eu-repo/semantics/openAccessspa
dc.rights.licenseAtribución-NoComercial-SinDerivadas 4.0 Internacionalspa
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/spa
dc.subject.ddc550 - Ciencias de la tierraspa
dc.subject.ddc600 - Tecnología (Ciencias aplicadas)spa
dc.subject.proposalNavegación en espacios cerradosspa
dc.subject.proposalNavegación interior 3Dspa
dc.subject.proposalPosicionamiento Interiorspa
dc.subject.proposalDiscapacidad visualeng
dc.subject.proposalModelamiento 3Dspa
dc.subject.proposalIndoorGMLeng
dc.subject.proposalCityGMLeng
dc.subject.proposalBLEeng
dc.subject.proposalRSSIeng
dc.subject.proposalWPLeng
dc.subject.proposal3D Indoor Navigationeng
dc.subject.proposalIndoor Positioningeng
dc.subject.proposalVisually Impairedeng
dc.subject.proposal3D Modelingeng
dc.titleDiseño e implementación de un sistema de navegación personal orientado al desplazamiento de usuarios con discapacidad visual en ambientes cerradosspa
dc.title.translatedDesign and implementation of a personal navigation system oriented to the movement of visually impaired users in indoor spaceseng
dc.typeTrabajo de grado - Maestríaspa
dc.type.coarhttp://purl.org/coar/resource_type/c_bdccspa
dc.type.coarversionhttp://purl.org/coar/version/c_ab4af688f83e57aaspa
dc.type.contentTextspa
dc.type.driverinfo:eu-repo/semantics/masterThesisspa
dc.type.redcolhttp://purl.org/redcol/resource_type/TMspa
dc.type.versioninfo:eu-repo/semantics/acceptedVersionspa
dcterms.audience.professionaldevelopmentAdministradoresspa
dcterms.audience.professionaldevelopmentEstudiantesspa
dcterms.audience.professionaldevelopmentGrupos comunitariosspa
dcterms.audience.professionaldevelopmentInvestigadoresspa
dcterms.audience.professionaldevelopmentPadres y familiasspa
dcterms.audience.professionaldevelopmentPersonal de apoyo escolarspa
dcterms.audience.professionaldevelopmentPúblico generalspa
dcterms.audience.professionaldevelopmentReceptores de fondos federales y solicitantesspa
oaire.accessrightshttp://purl.org/coar/access_right/c_abf2spa

Archivos

Bloque original

Mostrando 1 - 1 de 1
Cargando...
Miniatura
Nombre:
53931380.2022.pdf
Tamaño:
31.32 MB
Formato:
Adobe Portable Document Format
Descripción:
Tesis de Maestría en Geomática

Bloque de licencias

Mostrando 1 - 1 de 1
Cargando...
Miniatura
Nombre:
license.txt
Tamaño:
5.74 KB
Formato:
Item-specific license agreed upon to submission
Descripción: