An automated 3D modeling of topological indoor navigation network

Indoor navigation is important for various applications such as disaster management, building modeling, safety analysis etc. In the last decade, indoor environment has been a focus of wide research that includes development of indoor data acquisition techniques, 3D data modeling and indoor navigatio...

Full description

Saved in:
Bibliographic Details
Main Authors: Jamali, A., Abdul Rahman, A., Boguslawski, P., Kumar, P., Gold, C. M.
Format: Article
Published: Springer Netherlands 2017
Subjects:
Online Access:http://eprints.utm.my/id/eprint/76198/
https://www.scopus.com/inward/record.uri?eid=2-s2.0-84944526255&doi=10.1007%2fs10708-015-9675-x&partnerID=40&md5=2b83f7933cd31c8de871b74b88c7f2b6
Tags: Add Tag
No Tags, Be the first to tag this record!
Institution: Universiti Teknologi Malaysia
id my.utm.76198
record_format eprints
spelling my.utm.761982018-06-26T07:52:42Z http://eprints.utm.my/id/eprint/76198/ An automated 3D modeling of topological indoor navigation network Jamali, A. Abdul Rahman, A. Boguslawski, P. Kumar, P. Gold, C. M. G70.212-70.215 Geographic information system Indoor navigation is important for various applications such as disaster management, building modeling, safety analysis etc. In the last decade, indoor environment has been a focus of wide research that includes development of indoor data acquisition techniques, 3D data modeling and indoor navigation. In this research, an automated method for 3D modeling of indoor navigation network has been presented. 3D indoor navigation modeling requires a valid 3D model that can be represented as a cell complex: a model without any gap or intersection such that two cells (e.g. room, corridor) perfectly touch each other. This research investigates an automated method for 3D modeling of indoor navigation network using a geometrical model of indoor building environment. In order to reduce time and cost of surveying process, Trimble LaserAce 1000 laser rangefinder was used to acquire indoor building data which led to the acquisition of an inaccurate geometry of building. The connection between surveying benchmarks was established using Delaunay triangulation. Dijkstra algorithm was used to find shortest path in between building floors. The modeling results were evaluated against an accurate geometry of indoor building environment which was acquired using highly-accurate Trimble M3 total station. This research intends to investigate and propose a novel method of topological navigation network modeling with a less accurate geometrical model to overcome the need of required an accurate geometrical model. To control the uncertainty of the calibration and of the reconstruction of the building from the measurements, interval analysis and homotopy continuation will be investigated in the near future. Springer Netherlands 2017 Article PeerReviewed Jamali, A. and Abdul Rahman, A. and Boguslawski, P. and Kumar, P. and Gold, C. M. (2017) An automated 3D modeling of topological indoor navigation network. GeoJournal, 82 (1). pp. 157-170. ISSN 0343-2521 https://www.scopus.com/inward/record.uri?eid=2-s2.0-84944526255&doi=10.1007%2fs10708-015-9675-x&partnerID=40&md5=2b83f7933cd31c8de871b74b88c7f2b6
institution Universiti Teknologi Malaysia
building UTM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Teknologi Malaysia
content_source UTM Institutional Repository
url_provider http://eprints.utm.my/
topic G70.212-70.215 Geographic information system
spellingShingle G70.212-70.215 Geographic information system
Jamali, A.
Abdul Rahman, A.
Boguslawski, P.
Kumar, P.
Gold, C. M.
An automated 3D modeling of topological indoor navigation network
description Indoor navigation is important for various applications such as disaster management, building modeling, safety analysis etc. In the last decade, indoor environment has been a focus of wide research that includes development of indoor data acquisition techniques, 3D data modeling and indoor navigation. In this research, an automated method for 3D modeling of indoor navigation network has been presented. 3D indoor navigation modeling requires a valid 3D model that can be represented as a cell complex: a model without any gap or intersection such that two cells (e.g. room, corridor) perfectly touch each other. This research investigates an automated method for 3D modeling of indoor navigation network using a geometrical model of indoor building environment. In order to reduce time and cost of surveying process, Trimble LaserAce 1000 laser rangefinder was used to acquire indoor building data which led to the acquisition of an inaccurate geometry of building. The connection between surveying benchmarks was established using Delaunay triangulation. Dijkstra algorithm was used to find shortest path in between building floors. The modeling results were evaluated against an accurate geometry of indoor building environment which was acquired using highly-accurate Trimble M3 total station. This research intends to investigate and propose a novel method of topological navigation network modeling with a less accurate geometrical model to overcome the need of required an accurate geometrical model. To control the uncertainty of the calibration and of the reconstruction of the building from the measurements, interval analysis and homotopy continuation will be investigated in the near future.
format Article
author Jamali, A.
Abdul Rahman, A.
Boguslawski, P.
Kumar, P.
Gold, C. M.
author_facet Jamali, A.
Abdul Rahman, A.
Boguslawski, P.
Kumar, P.
Gold, C. M.
author_sort Jamali, A.
title An automated 3D modeling of topological indoor navigation network
title_short An automated 3D modeling of topological indoor navigation network
title_full An automated 3D modeling of topological indoor navigation network
title_fullStr An automated 3D modeling of topological indoor navigation network
title_full_unstemmed An automated 3D modeling of topological indoor navigation network
title_sort automated 3d modeling of topological indoor navigation network
publisher Springer Netherlands
publishDate 2017
url http://eprints.utm.my/id/eprint/76198/
https://www.scopus.com/inward/record.uri?eid=2-s2.0-84944526255&doi=10.1007%2fs10708-015-9675-x&partnerID=40&md5=2b83f7933cd31c8de871b74b88c7f2b6
_version_ 1643657244770828288