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

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Institution Title Type Date Author(s) Abstract Link
HKUST Minimization of Construction Waste through BIM-based Clash Detection and Quantification Report 06/2016 Baoshan KUANG
Pik Kei LAM
Nowadays the construction industry is under pressure to explore effective and efficient techniques and tools to decrease its escalating waste generation. However, the current approaches, techniques and tools focus on separate projects on site and limited effort is invested to put attention on pre-construction waste generation related to design stages. Waste that is induced by improper design accounts for a major proportion of the total construction waste. Therefore, this report aims to develop a BIM-based approach in the aspect of waste minimization.

With the clash detection tool in Navisworks, this report demonstrates the clash classification, resolution and the corresponding waste generation of 3 pairs of general component models of a villa, which are architectural model vs. structural model, structural model vs. mechanical model and mechanical vs. plumbing model. Then, compare the result obtained with BIM and that estimated with the current waste factor approach and find out whether the BIM-based waste minimization can be better realized. Consequently, coordinating the models of each building components with clash detection enables efficient management of construction waste.
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HKUST Developing a Facility Monitoring and Management Framework for Buildings Based on BIM and Sensor Technologies Report 06/2016 Fehong HE
Jiaying HUANG
Guishan LI
Building Information Modeling (BIM) is a global trend which is gaining significant benefits in facility management. It can reduce cost and time to address building management problems. Currently there is little information on how to realize the benefits from BIM with monitoring the real time state of a building environment.

In this thesis, a sensor based BIM framework is presented for building controlling and management. Building environment, space, equipment and safety information can be captured by unique sensors automatically instead of human detect. We have simulated the sensor installation in a popular BIM software Autodesk Revit, and use HKUST Hall 7 as an example model to perform our platform. We use SQL database to store all the sensor ID because it have a good linkage with BIM model. With the pragmatic sensor management plugin we can realize visualization interface in BIM model to management those sensors and get the specific information. After realize the real time data acquisition, we have researched some relative criteria and build an assessment system for further facility management.
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HKUST BIM Application for Construction and Demolition Waste Minimization Report 06/2015 TAO Jiali Nowadays the construction industry is under pressure to explore effective and efficient techniques and tools to decrease its escalating waste production. Many countries have taken initiatives to reduce the construction and demolition waste. However, the current approaches, techniques and tools focus on separate projects onsite and limited effort is invested to put attention on pre-construction waste generation related to supply chain management issues and procurement, design and tender stages.

Therefore this study aims to develop the BIM-based approaches for C&D waste in the aspect of waste estimation, 3R, prefabrication and clash detection. Besides, this study will also demonstrate and validate the developed approaches for C&D waste minimization using example scenarios. All in all, the application of BIM in C&D waste minimization can be better realized. C&D Waste estimation via the quantity takeoff tool and waste index can clearly show the accurate amount of the waste before the commencement of the works. Classifying the different construction material in BIM model and set up suitable C&D waste management planning definitely improve the efficiency of the waste management. Providing accurate information of precast units ahead of time and assisting the supply chain management can be achieved in BIM model. Visual clash detection reduces rework to some extent.
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HKUST Integration of BIM and GIS for City Planning Report 06/2014 LI Zhi With the popularity of 3D digital maps for computers and mobile phones, the development of 3D city models has grown substantially in the last decades. 3D maps can not only support navigation, but also allow people to perform city planning and architectural and engineering designs with the consideration of the surrounding environment. Moreover, many other advanced applications have been studied to be equipped in 3D models, like disaster management, noise and pollutant diffusion analysis and so on. Earliest research on 3D digital city models was in 1990s and now there are about a total number of 1252 3D digital city models worldwide already.

Since the early 1990’s, lots of researchers have conducted studies in creation, application and maintenance of 3D city models. The study results indicate that the modeling construction techniques and application exploitability has improved significantly in last decades. However, the level of development of existing models varies widely in view of geographic locality (either city or country), creation time and many other factors. A standardized evaluation framework of the existing 3D city models is still in need.

Based on the purpose of setting up an evaluation framework, this review work was conducted. Mainly through literature review and searching on project websites, we collected original sources of more than 70 projects of 3D city models and 23 are chosen for detailed study and analysis. These city models are mainly categorized in four continents (North America, Europe, Asia and Oceania) and in four aspects (model coverage, modeling technology, application and maintenance).

To the point, a preliminary model estimation method is created, considering the maturity of five aspects during modeling procedures, i.e. data capturing, data processing, data storing and managing, data presenting and data updating. According to the evaluation framework, city models can be categorized into four maturity levels as 3D GIS as a Scene, 3D GIS as a Service, 3D GIS as an Infrastructure and 3D GIS as a Platform. Finally, based on the analysis results, some limitations of 3D city models in current situation are summarized, and recommendations of possible resolutions are presented correspondingly.
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HKUST Mapping of 3D GIS Digital Building Models in CityGML Across Levels of Details (LoD) Report 06/2013 DU Qianru GIS, a traditional technology used in many fields in the past hundreds years, now develops to a new height. With the fast development of 3D GIS technology, many new data formats established based on this kind of technology. Being a new format, CityGML is mainly used to represent the city models. It is really convenient due to the fact that different levels of detail exist in this kind of model format. Different LoDs have different attributes and used in diverse situations. Now, the models are often built in different LoDs. Therefore, to achieve one model which is in different LoDs, a translator needs to be published. However, until now neither OGC standard nor previous researchers provide an efficient translator for the transformation between different LoDs. Furthermore, the detailed definition for different LoDs was not provided either.

Based on these motivations, this project decided to focus on these two goals. The first part of this project focuses on the differences among different LoDs. Based on the differences, a translator is published and its methodology is also shown in the later part of this report. By using the translator established according to the method in this report, a 3D model sample is provided at the end of the report. This project not only provides a tool to realize the translation between different LoDs, but also offers a convenient method for further research.
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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.
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