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院校 题目 类型 日期 作者 摘要 网页
HKUST A BIM-based location aware AR collaborative framework for facility maintenance management Journal 07/2019 Chen, K., Chen, W., Li, C.T., and Cheng, J.C.P. Facility maintenance management (FMM) accounts for a large amount of the total cost of facilities’ lifecycle, illustrating the importance of improving FMM efficiency. Many mechanical facilities, like ventilation ducts above ceilings, are normally hidden, indicating the necessity of applying certain technology that can enable users to visualize and update the information of hidden facilities. Real-time location information is also needed so
that users can be aware of their current location and the surrounding facility can be displayed accordingly. Therefore, this paper aims to develop location aware augmented reality (AR) framework for FMM, with building information modeling (BIM) as the data source, AR for the interaction between users and facilities, and Wi-Fi fingerprinting for providing real-time location information. The developed framework has the following features: (1) a proposed softmax-based weighted K nearest neighbour (S-WKNN) algorithm is used for Wi-Fi fingerprinting to obtain the current location of users; (2) a room identification method, based on BIM, the obtained location, and ray casting algorithm, is proposed to identify which room the user is currently in; (3) according to the obtained location and the identified room, users can visualize and interact with their surrounding facilities through the AR devices; and (4) users in a remote location can visualize site situation and interact with site facilities in real time through video streaming and the shared database. At the end of the paper, an experiment was designed to evaluate the effectiveness of the developed system. As shown by the experiment, the developed AR collaborative system can reduce the completion time of the designed task by around 65% compared with traditional 2D drawing-based method, and can provide a localization accuracy of around 1m
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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. 连结
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. 连结
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. 连结
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. 连结