Integrated approach for facility management of existing buildings using point cloud segmentation

Author:

Marzouk MohamedORCID,Zaher MohamedORCID

Abstract

PurposeFacility management gained profound importance due to the increasing complexity of different systems and the cost of operation and maintenance. However, due to the increasing complexity of different systems, facility managers may suffer from a lack of information. The purpose of this paper is to propose a new facility management approach that links segmented assets to the vital data required for managing facilities.Design/methodology/approachAutomatic point cloud segmentation is one of the most crucial processes required for modelling building facilities. In this research, laser scanning is used for point cloud acquisition. The research utilises region growing algorithm, colour-based region-growing algorithm and Euclidean cluster algorithm.FindingsA case study is worked out to test the accuracy of the considered point cloud segmentation algorithms utilising metrics precision, recall and F-score. The results indicate that Euclidean cluster extraction and region growing algorithm revealed high accuracy for segmentation.Originality/valueThe research presents a comparative approach for selecting the most appropriate segmentation approach required for accurate modelling. As such, the segmented assets can be linked easily with the data required for facility management.

Publisher

Emerald

Subject

Building and Construction,Civil and Structural Engineering

Reference87 articles.

1. A Formalism for utilization of sensor systems and integrated project models for active construction quality control;Automation in Construction,2006

2. From BIM to extended reality in AEC industry;Automation in Construction,2020

3. Use of building information modeling technology in the integration of the handover process and facilities management,2014

4. Planning for terrestrial laser scanning in construction: a review;Automation in Construction,2021

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