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FYPs/Thesis/Journal from Higher Education Institutions in Hong Kong
| Institution | Title | Type | Date | Author(s) | Abstract | 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 | A state-of-the-art review on mixed reality (MR) applications in the AECO industry | Journal | 11/2019 | Cheng, J.C.P., Chen, K., and Chen, W. | The ability to combine digital information with the real world enables mixed reality (MR) technology to provide a better display of information, resulting in its increasing popularity in various fields. The architecture, engineering, construction, and operation (AECO) industry is no exception. However, existing reviews on the use of MR technology can hardly keep up with the rapid development of MR applications. Therefore, a state-of-the-art review focusing on MR technology applications in the AECO industry is needed to reflect the current status of MR implementation in the AECO industry. This review is based on articles retrieved from well-acknowledged academic journals within the domain of the AECO industry. In this paper, 87 journal papers on MR applications are identified and classified into four categories: (1) applications in architecture and engineering, (2) applications in construction, (3) applications in operation, and (4) applications in multiple stages. Five basic components of MR, including spatial registration, display, user interaction, data storage, and multiuser collaboration, in each of the aforementioned 87 journal papers are identified and discussed. After reviewing the selected applications and corresponding MR components, this paper summarizes the challenges of MR development and provides insights into future trends of the MR technology in four aspects, namely: (1) accuracy of spatial registration, (2) user interface (UI), (3) data storage and transfer, and (4) multiuser collaboration. | Link |
| HKUST | A BIM-based system for demolition and renovation waste estimation and planning | Journal | 03/2013 | Cheng, J.C.P., and Ma, L.Y.H. | Due to the rising worldwide awareness of green environment, both government and contractors have to consider effective construction and demolition (C&D) waste management practices. The last two decades have witnessed the growing importance of demolition and renovation (D&R) works and the growing amount of D&R waste disposed to landfills every day, especially in developed cities like Hong Kong. Quantitative waste prediction is crucial for waste management. It can enable contractors to pinpoint critical waste generation processes and to plan waste control strategies. In addition, waste estimation could also facilitate some government waste management policies, such as the waste disposal charging scheme in Hong Kong. Currently, tools that can accurately and conveniently estimate the amount of waste from construction, renovation, and demolition projects are lacking. In the light of this research gap, this paper presents a building information modeling (BIM) based system that we have developed for estimation and planning of D&R waste. BIM allows multi-disciplinary information to be superimposed within one digital building model. Our system can extract material and volume information through the BIM model and integrate the information for detailed waste estimation and planning. Waste recycling and reuse are also considered in our system. Extracted material information can be provided to recyclers before demolition or renovation to make recycling stage more cooperative and more efficient. Pick-up truck requirements and waste disposal charging fee for different waste facilities will also be predicted through our system. The results could provide alerts to contractors ahead of time at project planning stage. This paper also presents an example scenario with a 47-floor residential building in Hong Kong to demonstrate our D&R waste estimation and planning system. As the BIM technology has been increasingly adopted in the architectural, engineering and construction industry and digital building information models will likely to be available for most buildings (including historical buildings) in the future, our system can be used in various demolition and renovation projects and be extended to facilitate project control. |
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| HKUST | A review of the efforts and roles of the public sector for BIM adoption worldwide | Journal | 07/2015 | Cheng, J.C.P., and Lu, Q. | Building Information Modeling (BIM) adoption is spreading through the public sector (including government bodies and non-profit organizations) around the globe in the architecture, engineering and construction (AEC) industry. The public sector plays a key role in supporting and encouraging the adoption of BIM in the industry. Currently there is no comprehensive study on the efforts and roles of the public sector for BIM adoption. In this paper, different kinds of the efforts that the public sector has put for BIM adoption worldwide are reviewed to highlight the successful implementations of BIM and to identify the gaps in some countries. The countries covered in this paper are grouped into four regions - the United States, Europe, Asia, and Australasia. In each region, efforts of the public sector in different countries to BIM implementations including establishment of BIM programs and committees, organization of BIM activities and seminars, setting up of different BIM goals and promises, and preparation of BIM guidelines and standards are described and compared. This paper also identifies six major possible roles of the public sector for BIM adoption. The roles played by the public sector in each selected country are summarized and evaluated. | Link |
| HKUST | A BIM-based web service framework for green building energy simulation and code checking | Journal | 06/2014 | Cheng, J.C.P., and Das, M. | Green building design has been a major trend in the last decade which has largely affected the AEC industry. As of 2013, for example, there were over 13,000 green buildings certified with LEED (Leadership in Energy and Environment Design) in the United States alone. Building Information Modeling (BIM) technolo- gy and computer simulations are adopted largely for green building design. However, while information sharing and automated, collaborative design review are important for the design of green buildings, the current way of BIM-based green building design relies mainly on individual file transfer and does not support collaboration in the distributed environment of construction projects. On the other hand, as the Internet becomes ubiquitous, the web provides convenient and cost-efficient means for multi-location cross-organizational collaboration. Energy analysis and validation against standard building codes are two major processes in green building design evaluation. This paper presents a modular web service based framework which integrates the information necessary for green building design, automates the building design evaluation processes, and facilitates simple updates on the building model on a common but distributed platform. This framework is based on BIM data models like gbXML (Green Building XML) which contain information for green building design like geometry of the building, material, and sensor information from more than one source. The BIM data models act as a single source of building information for all processes. Building design evaluation and updating are iterative in green building design and require information and inputs dispersed among various project participants. Since our framework follows a distributed architecture and is easily accessible from the Internet, it makes the information required to facilitate the iterative process and its results conveniently available to a multi-participant environment. The paper also presents an example scenario demonstrating the developed framework. | Link |
| HKUST | BIM-based framework for automatic scheduling of facility maintenance work orders | Journal | 03/2018 | Chen, W., Chen, K., Cheng, J.C.P., Wang, Q., and Gan, V.J.L. | Although more than 65% of the total cost in facility management (FM) comes from facility maintenance management (FMM), there is a lack of efficient maintenance strategies and right decision making approaches to reduce FMM costs. Building information modeling (BIM) has been developed as a potential technology for FMM in buildings. This study proposes an FMM framework based on BIM and facility management systems (FMSs), which can provide automatic scheduling of maintenance work orders (MWOs) to enhance good decision making in FMM. In this framework, data are mapped between BIM and FMSs according to the Industry Foundation Classes (IFC) extension of maintenance tasks and MWO information in order to achieve data integration. After bi-directional data transmission between the BIM models and FMSs, work order information is visualized in BIM via API to identify components that have failed. Second, geometric and semantic information of the failure components is extracted from the BIM models to calculate the sub-optimal maintenance path in the BIM environment. Third, the MWO schedule is automatically generated using a modified Dijkstra algorithm that considers four factors, namely, problem type, emergency level, distance among components, and location. Illustrative examples are given in the paper to validate the feasibility and effectiveness of the proposed framework in indoor and outdoor 3D environments. | Link |