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院校 題目 類型 日期 作者 摘要 網頁
HKUST Mapping between BIM and 3D GIS in different levels of detail using schema mediation and instance comparison Journal 04/2016 Deng, Y., Cheng, J.C.P., and Anumba, C.J. The Building Information Modeling (BIM) domain and the Geographic Information System (GIS) domain share a mutual need for information from each other. Information from GIS can facilitate BIM applications such as site selection and onsite material layout, while BIM models could help generate detailed models in GIS and achieve better utility management. The mapping between the key schemas in the BIM domain and the GIS domain is the most critical step towards interoperability between the two domains. In this study, Industry Foundation Classes (IFC) and City Geography Markup Language (CityGML) were chosen as the key schemas due to their wide applications in the BIM domain and the GIS domain, respectively. We used an instance-based method to generate the mapping rules between IFC and CityGML based on the inspection of entities representing the same component in the same model. It ensures accurate mapping between the two schemas. The transformation of coordinate systems and geometry are two major issues addressed in the instance-based method. Considering the difference in schema structure and information richness between the two schemas, a reference ontology called Semantic City Model was developed and an instance-based method was adopted. The Semantic City Model captures all the relevant information from BIM models and GIS models during the mapping process. Since CityGML is defined in five levels of detail (LoD), the harmonization among LoDs in CityGML was also developed in order to complete the mapping. The test results show that the developed framework can achieve automatic data mapping between IFC and CityGML in different LoDs. Furthermore, the developed Semantic City Model is extensible and can be the basis for other schema mappings between the BIM domain and the GIS domain. 連結
HKU Is Building Information Modelling (BIM) a Tool or a Substitute to Quantity Surveyors? Thesis 04/2015 FU Ka Chun -- N.A.
HKUST Integration of Building Information Modeling and Internet of Things for Facility Maintenance Management Thesis 03/2019 Weiwei CHEN Facility management (FM) accounts for more than two thirds of the total cost of the whole life cycle of a building. FM staff do have inadequate visualization and often have difficulty in querying information using 2D drawings and traditional facility management systems. Currently, building information modeling (BIM) is increasingly applied to FM in the operations and maintenance (O&M) stage. BIM represents the geometric and semantic information of building facilities in 3D object-based digital models and enables facility managers to manage building facilities better in the O&M stage. At the same time, the Internet of Things (IoT) technology can be used to acquire operational data of building facilities and real-time environmental data to support FM. However, few studies have used BIM and IoT technologies together for automated management and maintenance of building facilities. Around 65%~80% of the FM comes from facility maintenance management (FMM). However, there is a lack of efficient maintenance strategies and appropriate decision making approaches that can reduce FMM costs. Facility managers usually undertake reactive maintenance or preventive maintenance strategies in the O&M stage. However, reactive maintenance cannot prevent failures and preventive maintenance cannot predict the future condition of building components, which leads to maintenance actions being performed after failure has occurred and it cannot keep the functionality of a building consistent. This study aims to apply a predictive maintenance strategy with BIM and IoT technologies to overcome these limitations. In addition, there is an information interoperability problem among BIM, IoT and the FM system. Therefore, this study aims to leverage the BIM and IoT technologies to improve the efficiency of FMM and to address the information interoperability problem of integrating BIM, IoT and the FM system.

In order to improve the efficiency of FMM, an FMM framework is proposed 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 developed Industry Foundation Classes (IFC) extension of maintenance tasks and MWO information in order to achieve data integration. Geometric and semantic information of the failure components is extracted from the BIM models in order to calculate the optimal maintenance path in the BIM environment. Moreover, 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.

In order to provide a better maintenance strategy for building facilities, a data-driven predictive maintenance framework based on BIM and IoT technologies for FMM has been developed. The framework consists of an information layer and an application layer. Data collection and data integration among the BIM models, FM system, and IoT system are undertaken in the information layer, while the application layer contains four modules to achieve predictive maintenance, namely: (1) condition monitoring and sensor data acquisition, (2) condition assessment module, (3) condition prediction module, and (4) maintenance planning module. In addition, machine learning algorithms, i.e. artificial neural network (ANN) and support vector machine (SVM), are used to predict the future condition of building components.

For the information interoperability problem among BIM, IoT and FM system, an ontology-based methodology framework is proposed for data integration among the BIM, IoT and FM domains. The ontology-based approach is developed as a tool to facilitate knowledge management in BIM- and IoT-based FMM and improve the data integration process. First, three ontologies are developed for BIM, IoT, and FMM respectively according to the ontology development process and facility information requirement. Second, an ontology mapping method is designed to integrate the three developed ontologies based on mapping rules. Moreover, ontology reasoning rules are developed based on description logics to infer implicit facts from the integrated ontology and support quick information querying on FMM. The developed framework is validated through an illustrative example.

This research provides an automatic work order scheduling approach in FMM and predictive maintenance strategy for building facilities, thereby enabling great saving in time and labor costs for facility staff. In addition, the proposed ontology-based methodology can address the information interoperability problem and integrate data from BIM, IoT and FM system for facility maintenance activities. In the future, the ontology-based methodology will be applied for the operation management of building facilities.
N.A.
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.
N.A.
HKUST Integrating Building Information Modeling and Internet of Things for Building Facility Management FYP 06/2019 CHAN, Sum Chau
DWIVEDY, Sampriti
In Hong Kong’s Smart City Blueprint, promoting ‘Green and Intelligent Buildings, and Energy Efficiency’ is one of the most important initiatives. HKUST, as the leading university in Hong Kong, has been working for years to build a better, smarter and greener campus. Keeping in line with HKUST’s “Sustainable Smart Campus as a Living Lab (SSC)” initiative, this project seeks to enable the Facilities Management Office to make better decisions with respect to balancing the trade-off between human thermal comfort and energy costs. This can be done by optimizing the operational controls of the existing heating, ventilation and air-conditioning systems (HVAC) to the occupancy level of the facility. The research was divided into two case studies, one that focuses on occupancy prediction with the use of machine learning and the other seeks to demonstrate how building information modelling (BIM) and Internet of Things (IoT) can be used to visualize the tradeoff between user thermal comfort and energy costs.

This project also discusses a flowchart to integrate the various technologies being suggested. and identifies certain software tools that can be used to assist in the integration process, for instance Autodesk’s Forge. A web-based graphical user interface for an integrated smart facility management system was also constructed in order to provide a direction for future works on this topic.
N.A.
HKUST Integrating BIM and Internet of Things for Building Facility Management and Energy Management Report 06/2019 Yaoming HU
Bonan Zhang
This project studies sensor location determination in a complex conference room as a part of Smart HVAC system. It describes the background of HVAC system and how the system can be upgraded as a smart system, automated system, to save energy. The project mainly studies the methodology and uses some factors in IAQ, indoor air quality, to illustrate possible locations for sensor placement. In this project, Autodesk Revit is used to build a BIM model of a conference room. The building of BIM of the room is important since it will reflect the true structural setup of the room. Autodesk CFD is then introduced to run simulations. For CFD simulation, materials and boundary conditions are applied to the model in order to run simulations that can reflect distribution as realistic as possible. In the CFD simulations, some major IAQ factors such as, temperature, air velocity, thermal comfort, CO2, VOC (formaldehyde) and dust (PM 2.5) are predicted in the environment. To analyze the temperature distribution, different numbers of people are introduced to examine the difference of heat distribution due to number of people. Pollutants are examined using assumed values according to average emission values. The goal is not to determine whether or not the room is polluted but the distribution of pollutants inside the room. Eventually, the results of all simulations are collected and analyzed to determine the areas with high density of heat, pollutants where those high concentration areas are the prior locations sensors have to monitor. It is concluded that the simulation of air movement, heat, pollutant distribution, etc. is useful methodology to determine sensor locations. With the sensor placed in correct locations, HVAC system can run with higher efficiency and prevent hazardous environment. N.A.