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


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Institution Title Type Date Author(s) Abstract Link
HKUST Developing an BIM and Augmented Reality-based Framework for Construction Monitoring and Facility Management FYP 06/2018 CHIU, San Fung
KWOK, Wai Shing
Augmented reality (AR) is an innovative technology, which allows the real-world environment to be augmented by virtual information. In construction industry, the mobile accessibility of building information through building information modelling (BIM) is still limited, a practical AR system with the integration of building information modelling (BIM) to realize real-time collaboration is yet to be developed. In addressing this gap, this project developed an integrated Augmented Reality (AR) and Building Information Modeling (BIM) framework to achieve the real-time collaboration in construction monitoring and facility management. The function of the developed framework is shown in two scenarios about pipe repairing tutorial and real-time collaboration on remoting computer and mobile device. N.A.
HKUST Developing an evacuation evaluation model for offshore oil and gas platforms using BIM and agent-based model Journal 02/2018 Cheng, J.C.P., Tan, Y., Song, Y., Mei, Z., Gan, V.J.L., and Wang, X. Accidents on offshore oil and gas platforms (OOGPs) usually cause serious fatalities and financial losses considering the demanding environment where such platforms are located and the complicated topsides structure that the platforms have. Conducting evacuation planning on OOGPs is challenging. Computational tools are considered as a good way to plan evacuation by emergency simulation. However, the complex structure of OOGPs and various evacuation behaviors can weaken the advantages of computational simulation. Therefore, this study develops a simulation model for OOGPs to evaluate different evacuation plans to improve evacuation performance by integrating building information modeling (BIM) technology and agent-based model (ABM). The developed model consists of four parts: evacuation model input, simulation environment modeling, agent definition, and simulation and comparison. Necessary platform information is extracted from BIM and then used to model the simulation environment by integrating matrix model and network model. In addition to essential attributes, environment sensing and dynamic escape path planning functions are developed and assigned to agents in order to improve simulation performance. Total evacuation time for all agents on an offshore platform is used to evaluate the evacuation performance of each simulation. An example OOGP BIM topsides with different emergency scenarios is used to illustrate the developed evacuation evaluation model. The results show that the developed model can accurately simulate evacuation and improve evacuation performance on OOGPs. The developed model is also applicable to other industries such as the architecture, engineering, and construction industry, where there is an increasing demand for evacuation planning and simulation. Link
HKUST Developing an Integrated Location-based Collaborative Building Information Modeling Framework for Building Facility Management FYP 06/2018 LEUNG, Tsz Fung
MAN, Tsz Lok
This project reviews some of the existing Indoor positioning system (IPS) and finds that Wi-Fi would be a suitable choice to be incorporated with Building Information Modelling (BIM) for the purpose of facility management. Indoor localization and finding of the shortest path are two major aspects which could combine with facility management and this project is going to investigate into them.

As Wi-Fi positioning is controlled by some factors like k-means clustering and the number of fingerprints, an experiment was conducted to see how these factors would affect the accuracy of indoor localization. The result would be discussed also. In an experiment of finding the shortest path, visibility graph and Dijkstra algorithm are two techniques used for path-generation and path-finding respectively. They would be written as codes and implemented into a mobile App. The App would be the product to test the above experiments and East Point City, which is a shopping mall, would be the chosen for the field test.

The simulation of the interaction between building management system and pathfinding system android devices was carried out successfully, which reveals the high possibility of the application of BIM on indoor navigation system for the purpose of facility management, which could potential enhance human productivity.
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 Development of Approaches in Embodied Carbon of Buildings: From Construction Materials to Building Structural Design Thesis 08/2016 Jielong GAN Global warming has been considered as a major environmental challenge nowadays. Among various sources of anthropogenic greenhouse gas (GHG) emissions, the building sector is one of the major contributors to global warming, in which a substantial amount of the GHG emissions are embodied carbon from construction material production and transportation. Embodied carbon can account for 50% of the life cycle GHG emissions in buildings, and this percentage can become more significant for those buildings with shorter service life or higher energy efficiency. Therefore, reducing the embodied carbon in buildings is critically important and can help decrease the life cycle GHG emissions in buildings, thereby pushing human’s living environment towards a sustainable and low carbon future.

This thesis uses two approaches to reducing the embodied carbon in buildings. The first approach focuses on the construction material aspect and aims to reduce the embodied carbon from the manufacturing processes and transportations of construction materials. In this thesis, only the cement-based material (i.e., concrete) and quarried material (i.e., aggregate) are studied using the construction materials approach, as they account for more than 60% of the embodied carbon in a reinforced concrete (RC) building. Methods to the reduction of embodied carbon of aggregate and concrete are proposed, considering the feature of each material. Aggregate is very heavy and generates a large amount of emissions during transportation, therefore the aggregate study presents a mathematical model based on life cycle assessment (LCA) and multi-objective optimization (MOO) in order to plan the optimal amount of aggregate from different supply sources. The model can help stakeholders formulate sustainable material supply strategies that minimize the embodied carbon and material cost. For the concrete study, embodied carbon from concrete mix proportions is more important. Thus, a systematic embodied carbon quantification and mitigation framework is proposed for low carbon concrete mix design. The parameters that significantly affect the mix design and embodied carbon of concrete, namely the compressive strength class, the cement type, the supplementary cementitious materials (SCMs) and the maximum aggregate size, are considered. The proposed framework can be used to identify the low carbon mix design for concrete, and the results serves as a basis for reducing the embodied carbon emissions in buildings.

Another approach to reducing the embodied carbon in buildings considers different kinds of construction materials together, and focuses on building design aspect in order to minimize the total amounts of construction materials and embodied carbon in buildings. While the previous studies in this particular stream concentrated on low-rise building, they overlooked the analysis on high-rise buildings. However, the structural forms, construction materials and component designs in high-rise buildings are different from those in low-rise buildings, which can cause a large variability in the embodied carbon estimates. Therefore, an embodied carbon accounting methodology based on building information modeling (BIM) for high-rise buildings is proposed in this thesis, and relationships between embodied carbon and the critical parameters in high-rise building design are evaluated through BIM and CFD technologies. A 60-story composite core-outrigger building is designed based on the structure of a typical high-rise building in Hong Kong (i.e., Cheung Kong Center), and then used as a reference for the comparative studies. The results of embodied carbon are expressed in terms of carbon dioxide equivalent (CO2-e). The first comparative study focuses on the material procurement strategies. The embodied carbon in the reference building is evaluated with different assumptions for the material manufacturing processes, the amounts of recycled scrap and cement substitutes, and the transportation distance. It is found that structural steel and rebar from traditional blast furnace account for 76% of the embodied carbon in high-rise buildings. If a contractor chooses to use steel from electric arc furnace (with 100% recycled scrap as the feedstock), the embodied carbon of a high-rise building can be decreased by 60%. As for concrete, 10-20% embodied carbon reduction is achieved by using 35% fly ash (FA) or 75% ground granulated blast-furnace slag (GGBS) in mix design. Comparative studies are also carried out to determine the embodied carbon associated with different construction materials, building heights and structural forms. The 60-story composite core-outrigger reference building has a unitary embodied carbon of 557 kg CO2-e/m2 gross floor area (GFA). If the construction material changes to structural steel, the unitary embodied carbon increases to 759 kg CO2-e/m2 GFA, while the value of embodied carbon decreases to 537 kg CO2-e/m2 GFA if RC is used in construction. Core-frame structures are suitable for buildings of 40 stories or below, with the minimum embodied carbon at 525 kg CO2-e/m2 GFA. The optimal height range for core-outrigger structures is from 50-story to 70-story with 530 kg CO2-e/m2 GFA, whereas tubular structures are in the range between 70-story and 90-story at 540 kg CO2-e/m2 GFA. The results serve as a basis for more environmentally friendly building design, thereby improving our built environment towards a sustainable and low carbon future.
HKUST Development of BIM-assisted Access Point Placement Optimization and Deep Learning based Multi-floor Identification Algorithms for Enhancing Indoor Positioning to Support Construction Applications Thesis 08/2019 Kenneth Chun Ting LI Over the past decades, indoor positioning has been drawing wide attention in different fields of engineering. Indoor positioning technologies are complementary to the mature outdoor positioning technology such that the indoor positioning technologies can provide a real-time positioning service in any environment where there is a blockage of GNSS signals. In the fields of construction and facility management, indoor positioning technologies enable promising applications that can considerably enhance the productivity, efficiency and safety on construction sites, supporting five major applications, which are (1) construction safety management, (2) construction process monitoring and control, (3) inspection of construction structures and materials, (4) construction automation with robotics, and (5) the use of building information modelling (BIM) technology for construction progress management.

Currently, there is no single perfect indoor positioning system that can perform optimally under any circumstances. In addition, due to the large variety of indoor positioning technologies and principles, as well as the complex and dynamic environment on construction sites, developing suitable indoor positioning systems on construction sites is a challenging task. Applying indoor positioning systems is essentially user-oriented and environment-specific. This thesis thus analyses the challenges to apply indoor positioning systems on construction sites, and then proposes six indoor positioning performance metrics, namely APP-CAT, for evaluating suitable on-site indoor positioning systems. Subsequently, the top 10 indoor positioning technologies, which are selected according to their evaluation results using APP-CAT and their popularity amongst the indoor positioning literature studies, are thoroughly discussed and compared. The promising recent trends of developing on-site indoor positioning systems, such as infrastructure-free positioning, collaborative positioning, game theory positioning, and device-free positioning, as well as integration of indoor positioning technologies with BIM models, are also highlighted. In this research work, the comprehensive discussion of current development in indoor positioning from different aspects is intended to help academics, researchers, and industry practitioners develop high-performing and suitable on-site indoor positioning systems for supporting various engineering and construction applications.

Among various positioning technologies, Wi-Fi fingerprinting has emerged as a popular technique due to the wide coverage of Wi-Fi signals and its high compatibility with smartphones. Wi-Fi fingerprinting utilizes the patterns of the Wi-Fi signal strengths, which are measured by the Received Signal Strength Index (RSSI), for position estimation. Normally, Wi-Fi access points are placed arbitrarily, which causes a poor positioning accuracy. In fact, positioning accuracy can be considerably enhanced by optimizing the access point (AP) placement strategy. In light of the high popularity of Wi-Fi fingerprinting and the liberty to design AP placemnent strategies on construction sites, this thesis aims to conduct AP placement optimization is by finding the optimal AP placement strategy that maximizes the distinctiveness between individual Wi-Fi fingerprints in a 3D virtual environment. The use of BIM technology provides 3D geometric and semantic information to accurately reproduce the virtual environment for realistic simulation of Wi-Fi signal propagation. Wi-Fi signal propagation is usually modelled by a modified indoor radio wave path loss model, but such models cannot easily consider the multipath effect in an indoor environment. Therefore, in this thesis, an accurate Deep Belief Network (DBN) based path loss model, which considers the multipath effect emulated by the ray-tracing method using particle swarm optimization (PSO), is proposed and implemented to predict the indoor Wi-Fi signal strengths. Based on the results of the simulation, the optimal AP placement strategy as well as the geometrically-constrained optimal AP placement strategy can be obtained by using the genetic algorithm (GA). The test results in a university library have shown that the developed AP placement optimization algorithm could consistently enhance the accuracy of 3D indoor positioning under the circumstances of different numbers of APs and the presence of geometric constraints.

Facility management is often performed in a multi-floor indoor environment such as shopping malls and airports. However, one of the major challenges facing the received signal strength indicator (RSSI) based fingerprinting is the inability to perform accurate indoor positioning in a multi-floor environment, despite their popularity. The multi-floor environment poses a large challenge to RSSI fingerprint-based indoor positioning because the uniqueness of RSSI fingerprints is largely lost in a multi-floor environment, especially when ring structure exists in the building. Such a ring structure is commonly found in large airports and shopping malls. In this thesis, in light of the analogy between visual images and a radio map, a novel twofold multi-floor localization algorithm based on convolutional neural network (CNN) is developed to perform robust and accurate multi-floor localization. To support the twofold CNN model and to improve the localization accuracy, the similar selective search algorithm and data augmentation algorithm are proposed. Lastly, with the support of inertial measuring units (IMUs), the snapping algorithm is proposed to convert a random trajectory to a grid shape for the purpose of localization. Per the validation results, the proposed multi-floor localization algorithm is capable of identifying on which floor the user is located such that the “floor jumping” problem is mitigated, and thus the overall indoor positioning accuracy on RSSI fingerprint-based indoor positioning is substantially improved during indoor navigation.

To summarise, this thesis provides a comprehsive review of the top 10 indoor positioning technologies for their usage on construction sites, and aims to develop a BIM-assisted access point placement optimization and deep learning based multi-floor identification algorithms for enhancing indoor positioning to support construction applications for both construction management and facility managment.