FYPs/Thesis/Journal from Higher Education Institutions in Hong Kong

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Institution Title Type Date Author(s) Abstract Link
HKUST Developing efficient mechanisms for BIM-to-AR/VR data transfer Journal 06/2020 Chen, K., Chen, W., Wang, Q., and Cheng, J.C.P. Augmented reality/virtual reality (AR/VR) has been increasingly adopted to enhance visualization of building information modeling (BIM) models. However, there is a lack of mechanisms for efficient data transfer from BIM to AR/VR. On one hand, most semantic information is lost while importing BIM models into AR/VR engines. On the other hand, huge and complicated BIM models can increase the time for model transfer, increase the computation work load while rendering, and reduce the fluency when using AR/VR applications. Therefore, this paper aims to develop efficient mechanisms for BIM-to-AR/VR data transfer to better utilize the information of BIM. In this paper, an ontology-based approach is proposed to transfer semantic information of BIM. Building components in geometric models are classified according to their features and simplified with different polygon reduction methods. As shown in the experimental validation, the proposed mechanisms have the capability to efficiently transfer semantic information of BIM to AR/VR, greatly reduce the number of triangles for geometric models while maximizing the consistency of the overall shape, and improve the framerate in corresponding AR/VR applications. N.A.
HKUST Transfer learning enhanced AR spatial registration for facility maintenance management Journal 02/2020 Chen, K., Yang, J., Cheng, J.C.P., Chen, W., and Li, C.T. Augmented reality (AR), which requires a spatial registration technique, has proved to greatly improve the efficiency of facility maintenance management (FMM) activities. Being one of the most promising techniques for indoor localization, Wi-Fi fingerprinting has been widely used for AR spatial registration. However, localization accuracy of Wi-Fi fingerprinting decreases over time due to dynamics of environmental factors. Readings from different mobile devices can also affect the accuracy negatively. In this paper, a transfer learning technique named transferable CNN-LSTM is proposed for improving the robustness of Wi-Fi fingerprinting while implementing AR in FMM activities. Convolutional neural network (CNN), embedded with long short term memory (LSTM) networks, is utilized to predict the location of unlabeled fingerprints. Multiple kernel variant of maximum mean discrepancy (MK-MMD) is adopted to reduce the distribution difference between the source domain and the target domain, so that the location of the newly collected unlabeled fingerprints can be predicted accurately. As shown in the experimental validation, the transferable CNN-LSTM can achieve an accuracy of 97.1% in short-term (without significant environmental changes) spatial registration, 87.8% in long-term (with significant environmental changes) spatial registration, and around 90% in multi-device spatial registration, indicating a higher accuracy and better robustness over other conventional approaches. Link
HKUST Data-driven predictive maintenance planning framework for MEP components based on BIM and IoT using machine learning algorithms Journal 01/2020 Cheng, J.C.P., Chen, W., Chen, K., and Wang, Q. Facility managers usually conduct reactive maintenance or preventive maintenance strategies in building maintenance management. However, there are some limitations that reactive maintenance cannot prevent failure, and preventive maintenance cannot predict the future condition of MEP components and repair in advance to extend the lifetime of facilities. Therefore, this study aims to apply a predictive maintenance strategy with advanced technologies to overcome these limitations. Building information modeling (BIM) and Internet of Things (IoT) have the potential to improve the efficiency of facility maintenance management (FMM). Despite the significant efforts that have been made to apply BIM and IoT to the architecture, engineering, construction, and facility management (AEC/FM) industry, BIM and IoT integration for FMM is still at an initial stage. In order to provide a better maintenance strategy for building facilities, a data-driven predictive maintenance planning framework based on BIM and IoT technologies for FMM was developed, consisting of an information layer and an application layer. Data collection and data integration among the BIM models, FM system, and IoT network are undertaken in the information layer, while the application layer contains four modules to achieve predictive maintenance, namely: (1) condition monitoring and fault alarming module, (2) condition assessment module, (3) condition prediction module, and (4) maintenance planning module. Machine learning algorithms, ANN and SVM, are used to predict the future condition of MEP components. Furthermore, the developed framework was applied in an illustrative example to validate the feasibility of the approach. The results show that the constantly updated data obtained from the information layer together with the machine learning algorithms in the application layer can efficiently predict the future condition of MEP components for maintenance planning. Link
HKUST Study on Legal Aspects of BIM Projects Report 06/2020 Ka Cheong TANG
Tsz Yin CHOW
Building Information Modeling (BIM) is an emerging technology applied in Architecture, Engineering and Construction (AEC) industry. With the increase in the BIM application, some legal uncertainties have appeared and led to a high risk in legal aspects when adopting BIM in design and construction projects. It is vital that BIM users should be aware of the potential legal issues and develop suitable legal documents and contracts to prevent these issues from occurring. Within this context, a critical review on different cases associated with BIM is carried out in order to provide an overview of potential legal issues. Model copyright, right of BIM common data environment control and responsible control were discussed. Furthermore, three protocols and guidelines commissioned by the United Kingdom, the United States and Singapore are compared and analyzed. BIM Protocol published by Construction Industry Council of the United Kingdom is suggested as the most comprehensive and structured protocol in the analysis. Recommendations on the aspects of BIM cyber security, practical completion and contractors’ perspective are made to Hong Kong AEC professional institutes to commission a suitable and comprehensive protocol for the local industry. N.A.
HKUST Study on BIM Project Execution Plan and BIM Uses in Comparison with PMBOK Report 06/2020 Ka Wing Ngan
HUANG Li
Project successful strongly relies on PMBOK. Besides that, BIM is important because it is a powerful tool in delivery of BIM-based project. To implement BIM, BIM uses are defined based on project goals. To effective implement BIM as planned, BIM project execution plan (PXP) is necessary to control BIM. In the first section, this paper compares supporting infrastructure from BIM project execution plan (PXP) to PMBOK to find out the relationship. The categories of supporting infrastructure are BIM PXP overview, project information, key project contacts, project goals / BIM uses, organizational roles / staffing, BIM process design, BIM information exchanges, BIM and facility data requirement, collaboration procedures, quality control, technological infrastructure needs, model structure, project deliverables and delivery strategy / contract whereas PMBOK are integration, scope, time, cost, quality, human resources, communication, risk, procurement and stakeholder management. From the investigation, it is found that risk and cost management is not obviously applied from the categories of supporting infrastructure. In the second section, this paper investigate the relationship of various BIM uses in terms of PMBOK. The considerable BIM uses are design authoring, design review, 3D coordination, cost estimation, phase planning (4D Modelling), digital fabrication and site utilization planning. It is also found that scope, communication and human resources management is not obviously applied from the selected BIM uses. In the third section, we recommend that for BIM PXP additional section including project cost management and BIM risk management should be included; and for BIM uses attention should be paid in drafting BIM PXP to support BIM uses and other BIM uses maybe considered. Manager may benefit from the relationship developed and recommendation in BIM implementation. N.A.
HKUST Risk Management in BIM Projects Report 06/2020 SIO Wai Lam
CHEONG Ka Yi
The objectives of the project are to identify the risks with high risk level and mitigation with higher effectiveness in BIM industry. The survey was conducted to collect the data of risks and mitigations adopted by different groups of people. Overall analysis, by-group analysis and cross-group analysis were performed.

Thus, the risks were analyzed and discussed with two approaches - level of consequence and level of probability. The level of risk was identified combining these two approaches. The assumption and resolution of identified risks were discussed. Mitigation strategies with higher appropriateness were identified and relevant comments were made.

It is found that the level of risk of C6 (Poor participation / contribution from project team in BIM adoption) and M1 (Lack of adequate expertise in BIM) are extreme, and are very high for risk T6 (Design conflict / clashes in BIM was not revealed / unresolved), C1 (Unclear requirements (e.g. EIR / AIR / contract) of BIM uses and specifications), C2 (Unclear roles, responsibility and liability in BIM implementation). As for mitigation strategy, it is found that mitigation #1 (Clear Employer’s Information Requirement) and #11 (BIM Education for Project Team) were mitigation strategies with the 1st and 2nd ranking in appropriateness/effectiveness. Mitigation can minimize risk C6, and mitigation #11 helps to mitigate risk M1.
N.A.