ARCOM

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Almeida, L, Tam, V W, Le, K N and She, Y (2020) Effects of occupant behaviour on energy performance in buildings: a green and non-green building comparison. Engineering, Construction and Architectural Management, 27(08), 1939–62.

Hu, W, Dong, J, Hwang, B, Ren, R and Chen, Z (2020) Network planning of urban underground logistics system with hub-and-spoke layout: two phase cluster-based approach. Engineering, Construction and Architectural Management, 27(08), 2079–105.

Jeelani, I, Han, K and Albert, A (2020) Development of virtual reality and stereo-panoramic environments for construction safety training. Engineering, Construction and Architectural Management, 27(08), 1853–76.

Ji, Y, Qi, K, Qi, Y, Li, Y, Li, H X, Lei, Z and Liu, Y (2020) BIM-based life-cycle environmental assessment of prefabricated buildings. Engineering, Construction and Architectural Management, 27(08), 1703–25.

Li, H X, Ma, Z, Liu, H, Wang, J, Al-Hussein, M and Mills, A (2020) Exploring and verifying BIM-based energy simulation for building operations. Engineering, Construction and Architectural Management, 27(08), 1679–702.

Li, Q, Sun, Q, Tao, S and Gao, X (2019) Multi-skill project scheduling with skill evolution and cooperation effectiveness. Engineering, Construction and Architectural Management, 27(08), 2023–45.

Li, X, Li, J, Zhang, X, Gao, J and Zhang, C (2020) Simplified analysis of cable-stayed bridges with longitudinal viscous dampers. Engineering, Construction and Architectural Management, 27(08), 1993–2022.

Lu, H, Qi, J, Li, J, Xie, Y, Xu, G and Wang, H (2020) Multi-agent based safety computational experiment system for shield tunneling projects. Engineering, Construction and Architectural Management, 27(08), 1963–91.

Meng, Q, Zhang, Y, Li, Z, Shi, W, Wang, J, Sun, Y, Xu, L and Wang, X (2020) A review of integrated applications of BIM and related technologies in whole building life cycle. Engineering, Construction and Architectural Management, 27(08), 1647–77.

Stride, M, Hon, C K, Liu, R and Xia, B (2020) The use of building information modelling by quantity surveyors in facilities management roles. Engineering, Construction and Architectural Management, 27(08), 1795–812.

Tang, L, Griffith, L, Stevens, M and Hardie, M (2020) Social media analytics in the construction industry comparison study between China and the United States. Engineering, Construction and Architectural Management, 27(08), 1877–89.

Wu, H, Shen, G, Lin, X, Li, M, Zhang, B and Li, C Z (2020) Screening patents of ICT in construction using deep learning and NLP techniques. Engineering, Construction and Architectural Management, 27(08), 1891–912.

Xie, X, Lu, Q, Rodenas-Herraiz, D, Parlikad, A K and Schooling, J M (2020) Visualised inspection system for monitoring environmental anomalies during daily operation and maintenance. Engineering, Construction and Architectural Management, 27(08), 1835–52.

• Type: Journal Article
• Keywords: Digital twin; Anomaly detection; Augmented reality; Operations and maintenance;
• ISBN/ISSN: 0969-9988
• URL: https://doi.org/10.1108/ECAM-11-2019-0640
• Abstract:
  Visual inspection and human judgement form the cornerstone of daily operations and maintenance (O&M) services activities carried out by facility managers nowadays. Recent advances in technologies such as building information modelling (BIM), distributed sensor networks, augmented reality (AR) technologies and digital twins present an immense opportunity to radically improve the way daily O&M is conducted. This paper aims to describe the development of an AR-supported automated environmental anomaly detection and fault isolation method to assist facility managers in addressing problems that affect building occupants’ thermal comfort. The developed system focusses on the detection of environmental anomalies related to the thermal comfort of occupants within a building. The performance of three anomaly detection algorithms in terms of their ability to detect indoor temperature anomalies is compared. Based on the fault tree analysis (FTA), a decision-making tree is developed to assist facility management (FM) professionals in identifying corresponding failed assets according to the detected anomalous symptoms. The AR system facilitates easy maintenance by highlighting the failed assets hidden behind walls/ceilings on site to the maintenance personnel. The system can thus provide enhanced support to facility managers in their daily O&M activities such as inspection, recording, communication and verification. Taking the indoor temperature inspection as an example, the case study demonstrates that the O&M management process can be improved using the proposed AR-enhanced inspection system. Comparative analysis of different anomaly detection algorithms reveals that the binary segmentation-based change point detection is effective and efficient in identifying temperature anomalies. The decision-making tree supported by FTA helps formalise the linkage between temperature issues and the corresponding failed assets. Finally, the AR-based model enhanced the maintenance process by visualising and highlighting the hidden failed assets to the maintenance personnel on site. The originality lies in bringing together the advances in augmented reality, digital twins and data-driven decision-making to support the daily O&M management activities. In particular, the paper presents a novel binary segmentation-based change point detection for identifying temperature anomalous symptoms, a decision-making tree for matching the symptoms to the failed assets, and an AR system for visualising those assets with related information.

Xu, M, Mei, Z, Luo, S and Tan, Y (2020) Optimization algorithms for construction site layout planning: a systematic literature review. Engineering, Construction and Architectural Management, 27(08), 1913–38.

Xu, W and Wang, T (2020) Dynamic safety prewarning mechanism of human–machine–environment using computer vision. Engineering, Construction and Architectural Management, 27(08), 1813–33.

Xu, Z, Wang, X, Xiao, Y and Yuan, J (2020) Modeling and performance evaluation of PPP projects utilizing IFC extension and enhanced matter-element method. Engineering, Construction and Architectural Management, 27(08), 1763–94.

Yuan, J, Li, X, Ke, Y, Xu, W and Xu, Z (2020) Developing a building information modeling–based performance management system for public–private partnerships. Engineering, Construction and Architectural Management, 27(08), 1727–62.

Zhang, J, Ouyang, Y, Li, H, Ballesteros-Pérez, P and Skitmore, M (2020) Simulation analysis of incentives on employees' acceptance of foreign joint venture management practices: a case study. Engineering, Construction and Architectural Management, 27(08), 2047–78.