Abstracts – Browse Results
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Doukari, O, Kassem, M, Scoditti, E, Aguejdad, R and Greenwood, D (2024) A BIM based tool for evaluating building renovation strategies: the case of three demonstration sites in different European countries. Construction Innovation, 24(01), 365-83.
Faraji, A, Homayoon Arya, S, Ghasemi, E, Rashidi, M, Perera, S, Tam, V and Rahnamayiezekavat, P (2024) A conceptual framework of decentralized blockchain integrated system based on building information modeling to steering digital administration of disputes in the IPD contracts. Construction Innovation, 24(01), 384-406.
Garip, S B, Güzelci, O Z, Garip, E and Kocabay, S (2024) A genetic algorithm-based design model to provide reduced risk areas for housing interiors. Construction Innovation, 24(01), 49-66.
Gledson, B, Zulu, S L, Saad, A M and Ponton, H (2024) Digital leadership framework to support firm-level digital transformations for Construction 4.0. Construction Innovation, 24(01), 341-64.
Jowett, B, Edwards, D J and Kassem, M (2024) Field BIM and mobile BIM technologies: a requirements taxonomy and its interactions with construction management functions. Construction Innovation, 24(01), 134-63.
Likita, A J, Jelodar, M B, Vishnupriya, V and Rotimi, J O B (2024) Lean and BIM integration benefits construction management practices in New Zealand. Construction Innovation, 24(01), 106-33.
Lisco, M and Aulin, R (2024) Taxonomy supporting design strategies for reuse of building parts in timber-based construction. Construction Innovation, 24(01), 221-41.
Mahamedi, E, Wonders, M, Gerami Seresht, N, Woo, W L and Kassem, M (2024) A reinforcing transfer learning approach to predict buildings energy performance. Construction Innovation, 24(01), 242-55.
Matoseiro Dinis, F, Rodrigues, R and Pedro da Silva Poças Martins, J (2024) Development and validation of natural user interfaces for semantic enrichment of BIM models using open formats. Construction Innovation, 24(01), 196-220.
Parisi, F, Sangiorgio, V, Parisi, N, Mangini, A M, Fanti, M P and Adam, J M (2024) A new concept for large additive manufacturing in construction: tower crane-based 3D printing controlled by deep reinforcement learning. Construction Innovation, 24(01), 8-32.
Philip, B and AlJassmi, H (2024) Time-series forecasting of road distress parameters using dynamic Bayesian belief networks. Construction Innovation, 24(01), 317-40.
Rampini, L and Re Cecconi, F (2024) Synthetic images generation for semantic understanding in facility management. Construction Innovation, 24(01), 33-48.
- Type: Journal Article
- Keywords: artificial intelligence; asset management; computer vision; digital twin; object detection
- ISBN/ISSN:
- URL: https://doi.org/10.1108/CI-09-2022-0232
- Abstract:
Purpose: This study aims to introduce a new methodology for generating synthetic images for facility management purposes. The method starts by leveraging the existing 3D open-source BIM models and using them inside a graphic engine to produce a photorealistic representation of indoor spaces enriched with facility-related objects. The virtual environment creates several images by changing lighting conditions, camera poses or material. Moreover, the created images are labeled and ready to be trained in the model. Design/methodology/approach: This paper focuses on the challenges characterizing object detection models to enrich digital twins with facility management-related information. The automatic detection of small objects, such as sockets, power plugs, etc., requires big, labeled data sets that are costly and time-consuming to create. This study proposes a solution based on existing 3D BIM models to produce quick and automatically labeled synthetic images. Findings: The paper presents a conceptual model for creating synthetic images to increase the performance in training object detection models for facility management. The results show that virtually generated images, rather than an alternative to real images, are a powerful tool for integrating existing data sets. In other words, while a base of real images is still needed, introducing synthetic images helps augment the model’s performance and robustness in covering different types of objects. Originality/value: This study introduced the first pipeline for creating synthetic images for facility management. Moreover, this paper validates this pipeline by proposing a case study where the performance of object detection models trained on real data or a combination of real and synthetic images are compared. © 2023, Luca Rampini and Fulvio Re Cecconi.
Saif, W and Alshibani, A (2024) A close-range photogrammetric model for tracking and performance-based forecasting earthmoving operations. Construction Innovation, 24(01), 164-95.
Sati, A and Al-Tabtabai, H (2024) A paradigm shift toward the application of blockchain in enhancing quality information management. Construction Innovation, 24(01), 407-24.
Singh, A, Kumar, V, Mittal, A and Verma, P (2024) Identifying critical challenges to lean construction adoption. Construction Innovation, 24(01), 67-105.
Yu, J, Zhong, H and Bolpagni, M (2024) Integrating blockchain with building information modelling (BIM): a systematic review based on a sociotechnical system perspective. Construction Innovation, 24(01), 280-316.
Zani, A, Speroni, A, Mainini, A G, Zinzi, M, Caldas, L and Poli, T (2024) Customized shading solutions for complex building façades: the potential of an innovative cement-textile composite material through a performance-based generative design. Construction Innovation, 24(01), 256-79.