Title
An Interval Type-2 Fuzzy-based System to Create Building Information Management Models from 2D Floor Plan Images
Abstract
Building Information Modelling (BIM) is a process that contain all the necessary information to manage the construction project across all its lifecycle. This benefits not only the construction industry but other industries such as utility companies that need to perform tasks inside of buildings and will need to access information about its elements. However, one of the biggest challenges is the digitalisation of the existing infrastructure. The use of semantic segmentation techniques could enable the transformation of infrastructure legacy data, such as 2D floor plans images, to open-standard BIM models. In this paper, we propose a processing pipeline to transform 2D floor plan images into BIM models. The pipeline makes use of an interval Type-2 Fuzzy Rule-based System (FRBS) that has an Intersection over Union metric value of 98.62% outperforming the Type-1 version of the model. Moreover, the proposed model is highly transparent, and it allows end-users to augment it using expert knowledge, something that is not possible in deep learning opaque-box models.
Year
DOI
Venue
2021
10.1109/FUZZ45933.2021.9494464
2021 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE)
Keywords
DocType
ISSN
semantic segmentation,BIM,floor plans,patch-based segmentation,interval type-2 fuzzy logic,rule-based systems
Conference
1544-5615
ISBN
Citations 
PageRank 
978-1-6654-4408-8
0
0.34
References 
Authors
0
5
Name
Order
Citations
PageRank
Hugo Leon-Garza110.69
Hani Hagras21747129.26
Anasol Peña-Ríos300.34
Anthony Conway400.34
Gilbert Owusu500.34