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15 pages, 8838 KiB

Open AccessArticle

Underground Parking Layout Generation Based on the WaveFunctionCollapse Algorithm

by Di Lan, Kezhen Chen and Zhen Xu

Buildings 2023, 13(11), 2898; https://doi.org/10.3390/buildings13112898 - 20 Nov 2023

Viewed by 744

During the design process, architectural layout configuration is subject to complex constraints such as site conditions and design requirements, resulting in limited design efficiency. This research aims to provide architects with an effective design tool that can generate reference-worthy underground parking layout solutions [...] Read more.

During the design process, architectural layout configuration is subject to complex constraints such as site conditions and design requirements, resulting in limited design efficiency. This research aims to provide architects with an effective design tool that can generate reference-worthy underground parking layout solutions based on the given site information. In this research, we extract spatial modules from underground parking layouts, and transform the design constraints into adjacency rules based on the analysis of the configuration process for underground parking layout, then develop a generation and optimization model of the underground parking layout based on the WaveFunctionCollapse algorithm (WFC) and Multi-objective Optimization (MOO), and verify the effectiveness of the model through experiments. The results show that with given plan contour and entrance/exit locations as inputs, the model can efficiently generate architectural layout solutions that meet the design objectives. Full article

(This article belongs to the Special Issue Application of Computer Technology in Buildings)

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22 pages, 4484 KiB

Open AccessArticle

Research on the Application and Performance Optimization of GPU Parallel Computing in Concrete Temperature Control Simulation

by Xuerui Zheng, Jiping Jin, Yajun Wang, Min Yuan and Sheng Qiang

Buildings 2023, 13(10), 2657; https://doi.org/10.3390/buildings13102657 - 21 Oct 2023

Viewed by 809

Abstract

With the development of engineering technology, engineering has higher requirements for the accuracy and the scale of simulation calculation. The computational efficiency of traditional serial programs cannot meet the requirements of engineering. Therefore, reducing the calculation time of the temperature control simulation program [...] Read more.

With the development of engineering technology, engineering has higher requirements for the accuracy and the scale of simulation calculation. The computational efficiency of traditional serial programs cannot meet the requirements of engineering. Therefore, reducing the calculation time of the temperature control simulation program has important engineering significance for real-time simulation of temperature field and stress field, and then adopting more reasonable temperature control and crack prevention measures. GPU parallel computing is introduced into the temperature control simulation program of massive concrete to solve this problem and the optimization is carried out. Considering factors such as GPU clock rate, number of cores, parallel overhead and Parallel Region, the improved GPU parallel algorithm analysis indicator formula is proposed. It makes up for the shortcomings of traditional formulas that focus only on time. According to this formula, when there are enough threads, the parallel effect is limited by the size of the parallel domain, and when the parallel domain is large enough, the efficiency is limited by the parallel overhead and the clock rate. This paper studies the optimal Kernel execution configuration. Shared memory is utilized to improve memory access efficiency by 155%. After solving the problem of bank conflicts, an accelerate rate of 437.5× was realized in the subroutine of the matrix transpose of the solver. The asynchronous parallel of data access and logical operation is realized on GPU by using CUDA Stream, which can overlap part of the data access time. On the basis of GPU parallelism, asynchronous parallelism can double the computing efficiency. Compared with the serial program, the accelerate rate of inner product matrix multiplication of the GPU asynchronous parallel program is 61.42×. This study further proposed a theoretical formula of data access overlap rate to guide the selection of the number of CUDA streams to achieve the optimal computing conditions. The GPU parallel program compiled and optimized by the CUDA Fortran platform can effectively improve the computational efficiency of the simulation program for concrete temperature control, and better serve engineering computing. Full article

(This article belongs to the Special Issue Application of Computer Technology in Buildings)

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27 pages, 17846 KiB

Open AccessArticle

Interoperability between Deep Neural Networks and 3D Architectural Modeling Software: Affordances of Detection and Segmentation

by Chialing Wei, Mohit Gupta and Thomas Czerniawski

Buildings 2023, 13(9), 2336; https://doi.org/10.3390/buildings13092336 - 14 Sep 2023

Cited by 2 | Viewed by 922

Abstract

Building owners are working on converting their legacy documentation 2D floor plans into digital 3D representations, but the manual process is labor-intensive and time-consuming. In this paper, deep learning is leveraged to automate the process. This automation requires interoperability between artificial neural networks [...] Read more.

Building owners are working on converting their legacy documentation 2D floor plans into digital 3D representations, but the manual process is labor-intensive and time-consuming. In this paper, deep learning is leveraged to automate the process. This automation requires interoperability between artificial neural networks and prevailing 3D modeling software. The system processes 2D floor plans and outputs parameters of recognized walls, single doors, double doors, and columns. The parameters include the start point and end point of the wall and the center point of the door and column. These parameters are input into Revit 2022 through the Revit API 2022 after post-processing. The dimensional parameter integration affordances of object detection and instance segmentation are studied and compared using Faster R-CNN and Mask R-CNN models. Instance segmentation was found to require more time for data labeling but was more capable of informing the modeling of irregularly shaped objects. The mean Average Precision (mAP) of object detection and instance segmentation are 71.7% and 69.3%, respectively. Apart from single doors, the average precision for other categories falls within the range of 74% to 96%. The results provide software developers with guidance on choosing between object detection and instance segmentation strategies for processing legacy building documents. These types of systems are anticipated to be pivotal to the industry’s transition from 2D to 3D information modalities and advise practitioners to carefully choose suitable models and consider the recommendations provided in this study to mitigate potential failure cases. Full article

(This article belongs to the Special Issue Application of Computer Technology in Buildings)

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18 pages, 65322 KiB

Open AccessArticle

Generating Interior Design from Text: A New Diffusion Model-Based Method for Efficient Creative Design

by Junming Chen, Zichun Shao and Bin Hu

Buildings 2023, 13(7), 1861; https://doi.org/10.3390/buildings13071861 - 22 Jul 2023

Cited by 6 | Viewed by 4913

Abstract

Because interior design is subject to inefficiency, more creativity is imperative. Due to the development of artificial intelligence diffusion models, the utilization of text descriptions for the generation of creative designs has become a novel method for solving the aforementioned problem. Herein, we [...] Read more.

Because interior design is subject to inefficiency, more creativity is imperative. Due to the development of artificial intelligence diffusion models, the utilization of text descriptions for the generation of creative designs has become a novel method for solving the aforementioned problem. Herein, we build a unique interior decoration style dataset. Thus, we solve the problem pertaining to the need for datasets, propose a new loss function that considers the decoration style, and retrain the diffusion model using this dataset. The trained model learns interior design knowledge and can generate an interior design through text. The proposed method replaces the designer’s drawing with computer-generated creative design, thereby enhancing the design efficiency and creative generation. Specifically, the proposed diffusion model can generate interior design images of specific decoration styles and spatial functions end to end from text descriptions, and the generated designs are easy to modify. This novel and creative design method can efficiently generate various interior designs, promote the generation of creative designs, and enhance the design and decision-making efficiency. Full article

(This article belongs to the Special Issue Application of Computer Technology in Buildings)

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14 pages, 3523 KiB

Open AccessArticle

Building Surface Crack Detection Using Deep Learning Technology

by Yulong Chen, Zilong Zhu, Zhijie Lin and Youmei Zhou

Buildings 2023, 13(7), 1814; https://doi.org/10.3390/buildings13071814 - 17 Jul 2023

Cited by 4 | Viewed by 2398

Abstract

Cracks in building facades are inevitable due to the age of the building. Cracks found in the building facade may be further exacerbated if not corrected immediately. Considering the extensive size of some buildings, there is definitely a need to automate the inspection [...] Read more.

Cracks in building facades are inevitable due to the age of the building. Cracks found in the building facade may be further exacerbated if not corrected immediately. Considering the extensive size of some buildings, there is definitely a need to automate the inspection routine to facilitate the inspection process. The incorporation of deep learning technology for the classification of images has proven to be an effective method in many past civil infrastructures like pavements and bridges. There is, however, limited research in the built environment sector. In order to align with the Smart Nation goals of the country, the use of Smart technologies is necessary in the building and construction industry. The focus of the study is to identify the effectiveness of deep learning technology for image classification. Deep learning technology, such as Convolutional Neural Networks (CNN), requires a large amount of data in order to obtain good performance. It is, however, difficult to collect the images manually. This study will cover the transfer learning approach, where image classification can be carried out even with limited data. Using the CNN method achieved an accuracy level of about 89%, while using the transfer learning model achieved an accuracy of 94%. Based on this, it can be concluded that the transfer learning method achieves better performance as compared to the CNN method with the same amount of data input. Full article

(This article belongs to the Special Issue Application of Computer Technology in Buildings)

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25 pages, 69902 KiB

Open AccessArticle

Applying Evolutionary Computation to Optimize the Design of Urban Blocks

by Ling Yang, Hsiao-Tung Chang, He Ma, Tao Wang, Jian Xu and Jingjing Chen

Buildings 2023, 13(3), 755; https://doi.org/10.3390/buildings13030755 - 13 Mar 2023

Cited by 2 | Viewed by 1111

Abstract

This empirical study in this paper focuses on the application of evolutionary computation in parametric urban block design to solve the problem of how to effectively find the optimal design solution set among a large number of schemes obtained through parametric urban block [...] Read more.

This empirical study in this paper focuses on the application of evolutionary computation in parametric urban block design to solve the problem of how to effectively find the optimal design solution set among a large number of schemes obtained through parametric urban block design. Through the application of evolutionary computation, a set of parameterized intelligent generation methods of urban blocks under the guidance of multi-conflict objective optimization can be established. The empirical study presented is based on a typical Russian block redevelopment design along the Chinese Eastern Railway. The design aims to transform and redevelop the original block on the basis of protecting its historical buildings and street pattern, taking into account environmental and economic considerations. The final results show that under the premise of reasonable overall evolution, a large number of block design schemes with complex design objectives can be obtained. Furthermore, according to the index data analysis of Pareto’s overall optimal, mean value, median value, extreme value, etc., it provides designers with methods to select a series of optimal schemes quickly and efficiently based on different factors such as comprehensive balance, average and middle ranking, and individual best. Full article

(This article belongs to the Special Issue Application of Computer Technology in Buildings)

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25 pages, 353 KiB

Open AccessArticle

Benefits and Obstacles to the Adoption of Reality Capture Technologies in the U.S. Commercial and Infrastructure Construction Sectors

by Jonathan W. Elliott and Svetlana Olbina

Buildings 2023, 13(3), 576; https://doi.org/10.3390/buildings13030576 - 21 Feb 2023

Viewed by 1292

Abstract

Most previous Reality Capture Technology (RCT) research in construction focuses on the technical aspects of data collection, processing, and post-processing, while fewer studies have explored stakeholder perceptions about adopting and implementing RCT. This research investigated the perceptions of various construction project stakeholders in [...] Read more.

Most previous Reality Capture Technology (RCT) research in construction focuses on the technical aspects of data collection, processing, and post-processing, while fewer studies have explored stakeholder perceptions about adopting and implementing RCT. This research investigated the perceptions of various construction project stakeholders in the commercial and infrastructure sectors regarding the benefits of, and obstacles hindering, the adoption of RCTs. A survey was distributed to the membership of U.S.-based professional organizations. Exploratory Factor Analysis was implemented to investigate and confirm logical and consistent empirical groupings of the benefits and obstacles listed in the survey. In general, mean comparisons revealed consistency across stakeholder perceptions of the benefits and obstacles of RCTs. However, significantly different perceptions about the increased accuracy of prefabricated elements, RCTs not being a company priority, lack of company budget, and data collection being too time consuming were observed between stakeholder groups. The study identified several benefits to RCT adoption (including, but not limited to, reduced project risk, increased accuracy of prefabricated elements and installed work as well as increased speed of as-built document creation) that were not noted in previous studies. Several obstacles to RCT (including, but not limited to, RCT not being a company priority, lack of Owner/Client demand, inability to bill RCT costs to the project, and cost of hiring employees with the required skills) were not observed in previous studies. Full article

(This article belongs to the Special Issue Application of Computer Technology in Buildings)

33 pages, 13389 KiB

Open AccessArticle

SwarmL: A Language for Programming Fully Distributed Intelligent Building Systems

by Wenjie Chen, Qiliang Yang, Ziyan Jiang, Jianchun Xing, Shuo Zhao, Qizhen Zhou, Deshuai Han and Bowei Feng

Buildings 2023, 13(2), 499; https://doi.org/10.3390/buildings13020499 - 12 Feb 2023

Viewed by 1149

Abstract

Fully distributed intelligent building systems can be used to effectively reduce the complexity of building automation systems and improve the efficiency of the operation and maintenance management because of its self-organization, flexibility, and robustness. However, the parallel computing mode, dynamic network topology, and [...] Read more.

Fully distributed intelligent building systems can be used to effectively reduce the complexity of building automation systems and improve the efficiency of the operation and maintenance management because of its self-organization, flexibility, and robustness. However, the parallel computing mode, dynamic network topology, and complex node interaction logic make application development complex, time-consuming, and challenging. To address the development difficulties of fully distributed intelligent building system applications, this paper proposes a user-friendly programming language called SwarmL. Concretely, SwarmL (1) establishes a language model, an overall framework, and an abstract syntax that intuitively describes the static physical objects and dynamic execution mechanisms of a fully distributed intelligent building system, (2) proposes a physical field-oriented variable that adapts the programming model to the distributed architectures by employing a serial programming style in accordance with human thinking to program parallel applications of fully distributed intelligent building systems for reducing programming difficulty, (3) designs a computational scope-based communication mechanism that separates the computational logic from the node interaction logic, thus adapting to dynamically changing network topologies and supporting the generalized development of the fully distributed intelligent building system applications, and (4) implements an integrated development tool that supports program editing and object code generation. To validate SwarmL, an example application of a real scenario and a subject-based experiment are explored. The results demonstrate that SwarmL can effectively reduce the programming difficulty and improve the development efficiency of fully distributed intelligent building system applications. SwarmL enables building users to quickly understand and master the development methods of application tasks in fully distributed intelligent building systems, and supports the intuitive description and generalized, efficient development of application tasks. The created SwarmL support tool supports the downloading and deployment of applications for fully distributed intelligent building systems, which can improve the efficiency of building control management and promote the application and popularization of new intelligent building systems. Full article

(This article belongs to the Special Issue Application of Computer Technology in Buildings)

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19 pages, 26063 KiB

Open AccessArticle

An Enhancement Strategy for Macau’s Largos from a Syntactic Perspective

by Senyu Lou, Yaou Zhang, Chao Li and Jingjing Chen

Buildings 2023, 13(2), 411; https://doi.org/10.3390/buildings13020411 - 02 Feb 2023

Viewed by 1233

Abstract

This paper takes the “Largos” of the Macau Peninsula as the object of study. By applying historical combing and field research, the main functions of Largos are categorized as follows: serving the community, facilitating traffic and promoting religious culture. The paper applied a [...] Read more.

This paper takes the “Largos” of the Macau Peninsula as the object of study. By applying historical combing and field research, the main functions of Largos are categorized as follows: serving the community, facilitating traffic and promoting religious culture. The paper applied a spatial syntactic theory to establish a model, and three syntactic parameters were used, synergy, integration and choice, to interpret the results of the analysis. Based on the results of the syntactic parameters of Largos, results are divided into four categories. From this, the spaces that require improvements are selected, and corresponding improvement strategies are proposed. Taking Macau’s Largos as an example, this paper aimed to apply a space syntax to analyze the Largos in Macau so as to play a reference role in the effective renewal of urban micro-spaces and small public spaces. Full article

(This article belongs to the Special Issue Application of Computer Technology in Buildings)

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19 pages, 1818 KiB

Open AccessArticle

Automatic Construction Hazard Identification Integrating On-Site Scene Graphs with Information Extraction in Outfield Test

by Xuan Liu, Xiaochuan Jing, Quan Zhu, Wanru Du and Xiaoyin Wang

Buildings 2023, 13(2), 377; https://doi.org/10.3390/buildings13020377 - 29 Jan 2023

Cited by 3 | Viewed by 1574

Abstract

Construction hazards occur at any time in outfield test sites and frequently result from improper interactions between objects. The majority of casualties might be avoided by following on-site regulations. However, workers may be unable to comply with the safety regulations fully because of [...] Read more.

Construction hazards occur at any time in outfield test sites and frequently result from improper interactions between objects. The majority of casualties might be avoided by following on-site regulations. However, workers may be unable to comply with the safety regulations fully because of stress, fatigue, or negligence. The development of deep-learning-based computer vision and on-site video surveillance facilitates safety inspections, but automatic hazard identification is often limited due to the semantic gap. This paper proposes an automatic hazard identification method that integrates on-site scene graph generation and domain-specific knowledge extraction. A BERT-based information extraction model is presented to automatically extract the key regulatory information from outfield work safety requirements. Subsequently, an on-site scene parsing model is introduced for detecting interaction between objects in images. An automatic safety checking approach is also established to perform PPE compliance checks by integrating detected textual and visual relational information. Experimental results show that our proposed method achieves strong performance in various metrics on self-built and widely used public datasets. The proposed method can precisely extract relational information from visual and text modalities to facilitate on-site hazard identification. Full article

(This article belongs to the Special Issue Application of Computer Technology in Buildings)

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23 pages, 3160 KiB

Open AccessArticle

Using the Dual Concept of Evolutionary Game and Reinforcement Learning in Support of Decision-Making Process of Community Regeneration—Case Study in Shanghai

by Youmei Zhou, Hao Lei, Xiyu Zhang, Shan Wang, Yingying Xu, Chao Li and Jie Zhang

Buildings 2023, 13(1), 175; https://doi.org/10.3390/buildings13010175 - 09 Jan 2023

Cited by 1 | Viewed by 1709

Abstract

Under the digital revolution that spawned in recent years, AI support is raised in the context of urban design and governance as it aims to match the operation of the urban developing process. It offers more chances for ensuring equality in public participation [...] Read more.

Under the digital revolution that spawned in recent years, AI support is raised in the context of urban design and governance as it aims to match the operation of the urban developing process. It offers more chances for ensuring equality in public participation and empowerment, with the possibility of projection and computation of integrated social, cultural, and physical spaces. Therefore, this research explored how scenario simulation of social attributes and social interaction dimensions can be incorporated into digital twin city research and development, which is seen as a problem to be addressed in the refinement and planning of future digital platforms and management in terms of decision-making. To achieve the research aim, this paper examined the evolution of social governance state and strain decision models, built a simulation method for the evolution of complex systems of social governance driven by the fusion of data and knowledge, and proposed a system response to residents’ ubiquitous perception and ubiquitous participation. The findings can help inspire the application of computational decision-making support in urban governance, and enhance the internal drive for comprehensive and sustainable urban regeneration. Moreover, they imply the role of the updated iterations of physical space and social interaction on social attributes. Full article

(This article belongs to the Special Issue Application of Computer Technology in Buildings)

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15 pages, 735 KiB

Open AccessArticle

Automated Generation of an Energy Simulation Model for an Existing Building from UAV Imagery

by Philip Gorzalka, Jacob Estevam Schmiedt, Christian Schorn and Bernhard Hoffschmidt

Buildings 2021, 11(9), 380; https://doi.org/10.3390/buildings11090380 - 26 Aug 2021

Cited by 5 | Viewed by 2417

Abstract

An approach to automatically generate a dynamic energy simulation model in Modelica for a single existing building is presented. It aims at collecting data about the status quo in the preparation of energy retrofits with low effort and costs. The proposed method starts [...] Read more.

An approach to automatically generate a dynamic energy simulation model in Modelica for a single existing building is presented. It aims at collecting data about the status quo in the preparation of energy retrofits with low effort and costs. The proposed method starts from a polygon model of the outer building envelope obtained from photogrammetrically generated point clouds. The open-source tools TEASER and AixLib are used for data enrichment and model generation. A case study was conducted on a single-family house. The resulting model can accurately reproduce the internal air temperatures during synthetical heating up and cooling down. Modelled and measured whole building heat transfer coefficients (HTC) agree within a 12% range. A sensitivity analysis emphasises the importance of accurate window characterisations and justifies the use of a very simplified interior geometry. Uncertainties arising from the use of archetype U-values are estimated by comparing different typologies, with best- and worst-case estimates showing differences in pre-retrofit heat demand of about ±20% to the average; however, as the assumptions made are permitted by some national standards, the method is already close to practical applicability and opens up a path to quickly estimate possible financial and energy savings after refurbishment. Full article

(This article belongs to the Special Issue Application of Computer Technology in Buildings)

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19 pages, 5313 KiB

Open AccessArticle

Computational Simulation of Wind Microclimate in Complex Urban Models and Mitigation Using Trees

by Azin Hosseinzadeh and Amir Keshmiri

Buildings 2021, 11(3), 112; https://doi.org/10.3390/buildings11030112 - 11 Mar 2021

Cited by 14 | Viewed by 3079

Abstract

Due to a rapid increase in urbanisation, accurate wind microclimate assessment is of crucial importance. Evaluating wind flows around buildings is part of the planning application process in the design of new developments. In this study, computational fluid dynamics (CFD) simulations are carried [...] Read more.

Due to a rapid increase in urbanisation, accurate wind microclimate assessment is of crucial importance. Evaluating wind flows around buildings is part of the planning application process in the design of new developments. In this study, computational fluid dynamics (CFD) simulations are carried out for a case study, representing the East Village in the London Olympic Park. Following a validation test against experimental data for a simpler urban configuration, the key input parameters, including appropriate boundary conditions, mesh setting and type of turbulence model, are selected for the Olympic Park model. All the simulations are conducted using the commercial code STARCCM+ under steady-state conditions with the Reynolds-averaged Navier–Stokes (RANS) method. The turbulence is modelled using different common variants of eddy-viscosity models (EVMs) including standard k-

ε

, realizable k-

ε

and standard and shear stress transport (SST) k-

ω

. The results demonstrate that standard and realisable k-

ε

models correlate very well with the experimental data, while some discrepancies are found with standard and SST k-

ω

. Following the determination of areas of high velocity, appropriate tree planting is proposed to overcome the effect of corner and downwash acceleration. With the optimised arrangement of trees and using specific types of tree (e.g., birch), wind speeds at the pedestrian level are reduced by 3.5, 25 and 66% in three main regions of interest. Moreover, we investigate the effects of tree heights. The obtained results illustrate that the wind velocity reduces when the crowns of the trees are located closer to the buildings and the ground. Our high-resolution CFD simulation and results offer a quantitative tool for wind microclimate assessment and optimised design and arrangement of trees around buildings to improve pedestrian comfort. Full article

(This article belongs to the Special Issue Application of Computer Technology in Buildings)

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26 pages, 5931 KiB

Open AccessArticle

Automated Positioning of Anchors for Personal Fall Arrest Systems for Steep-Sloped Roofs

by Azin Heidari, Svetlana Olbina and Scott Glick

Buildings 2021, 11(1), 10; https://doi.org/10.3390/buildings11010010 - 25 Dec 2020

Cited by 4 | Viewed by 3009

Abstract

Falls account for about one-third of all construction fatalities with most fatalities in the roofing trade. Even though a personal fall arrest system (PFAS) is required for fall protection, proper placement of PFAS anchor points is an issue evidenced by the high number [...] Read more.

Falls account for about one-third of all construction fatalities with most fatalities in the roofing trade. Even though a personal fall arrest system (PFAS) is required for fall protection, proper placement of PFAS anchor points is an issue evidenced by the high number of fatalities caused by incorrect anchor positioning. The research goal was to proof the concept of optimizing the location of the PFAS anchor points on steep-sloped roofs. This goal was achieved by: (1) Developing an algorithm for converting the required local jurisdiction construction regulations and standards for PFAS anchor positioning into machine-readable rules; and (2) Developing and validating an algorithm for optimizing the location of PFAS anchor points. The K-Nearest Neighbor Search (KNNS) optimization algorithm was selected in this research and was implemented into a standalone computer tool using Python programming language. The tool calculates the potential anchor locations that satisfy the fall clearance and swing hazard requirements and then displays the anchor locations both graphically and numerically. The optimization algorithm was validated using the K-fold Cross-Validation method, which proved the algorithm was adequately accurate and consistent. The research contribution is the proof of the concept that the development of an optimization algorithm and automated field-level tool for optimal selection of PFAS anchor points is possible, further research and refinement could help steep-sloped roofing companies improve their safety practices. Full article

(This article belongs to the Special Issue Application of Computer Technology in Buildings)

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12 pages, 3398 KiB

Open AccessArticle

Natural Language Processing Model for Managing Maintenance Requests in Buildings

by Yassine Bouabdallaoui, Zoubeir Lafhaj, Pascal Yim, Laure Ducoulombier and Belkacem Bennadji

Buildings 2020, 10(9), 160; https://doi.org/10.3390/buildings10090160 - 07 Sep 2020

Cited by 21 | Viewed by 5276

Abstract

In recent years, facility management (FM) has adopted many computer technology solutions for building maintenance, such as building information modelling (BIM) and computerized maintenance management systems (CMMS). However, maintenance requests management in buildings remains a manual and a time-consuming process that depends on [...] Read more.

In recent years, facility management (FM) has adopted many computer technology solutions for building maintenance, such as building information modelling (BIM) and computerized maintenance management systems (CMMS). However, maintenance requests management in buildings remains a manual and a time-consuming process that depends on human management. In this paper, a machine-learning algorithm based on natural language processing (NLP) is proposed to classify maintenance requests. This algorithm aims to assist the FM teams in managing day-to-day maintenance activities. A healthcare facility is addressed as a case study in this work. Ten-year maintenance records from the facility contributed to the design and development of the algorithm. Multiple NLP methods were used in this study, and the results reveal that the NLP model can classify work requests with an average accuracy of 78%. Furthermore, NLP methods have proven to be effective for managing unstructured text data. Full article

(This article belongs to the Special Issue Application of Computer Technology in Buildings)

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13 pages, 386 KiB

Open AccessEditor’s ChoiceArticle

Potential Application of Blockchain Technology for Embodied Carbon Estimating in Construction Supply Chains

by Muhandiramge Nimashi Navodana Rodrigo, Srinath Perera, Sepani Senaratne and Xiaohua Jin

Buildings 2020, 10(8), 140; https://doi.org/10.3390/buildings10080140 - 06 Aug 2020

Cited by 51 | Viewed by 7187

Abstract

Carbon emissions are categorised as Embodied Carbon (EC) occurring in the production phase and Operational Carbon (OC) occurring in the operational phase of buildings. The current focus on producing zero-carbon buildings, emphasises reducing OC and ignores the importance of reducing EC emissions. This [...] Read more.

Carbon emissions are categorised as Embodied Carbon (EC) occurring in the production phase and Operational Carbon (OC) occurring in the operational phase of buildings. The current focus on producing zero-carbon buildings, emphasises reducing OC and ignores the importance of reducing EC emissions. This study focuses on EC. Methods available in EC estimating currently produce estimates that often do not complement each other. This makes it important to develop a robust and accurate methodology for estimating EC. Blockchain is an emerging technology that has significant potential for transaction processing in supply chains. The construction industry being the second least digitalised industry, the adoption of innovative technologies is predominantly important. This paper explores the potential application of blockchain for accurate estimation of EC in construction supply chains. A detailed literature review and expert interviews revealed that, compared to traditional information systems, blockchain systems could eliminate issues in EC estimating highlighting its potential credible application for EC estimating. Scalability was identified as a feature that was lacking in a blockchain system, however, for EC estimating, its impact was identified as minimal. It will be difficult to generalise the findings of the study due to interview based qualitative methodology adopted in this study along with the fact that blockchain is an emerging and fairly new technology. However, a similar process could be followed by other studies to compare blockchain with traditional information systems, to evaluate the suitability of blockchain technology to develop prototype systems. Full article

(This article belongs to the Special Issue Application of Computer Technology in Buildings)

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Review

Jump to: Research

15 pages, 291 KiB

Open AccessReview

A Review: How Deep Learning Technology Impacts the Evaluation of Traditional Village Landscapes

by Tao Wang, Jingjing Chen, Li Liu and Lingling Guo

Buildings 2023, 13(2), 525; https://doi.org/10.3390/buildings13020525 - 15 Feb 2023

Cited by 4 | Viewed by 1790

Abstract

Recently, the deep learning technology has been adopted in the study of traditional village landscape. More precisely, it’s usually used to explore the representation of cultural heritage and the diversity of heritage information. In this study, we comprehensively reviewed these deep learning-related literatures [...] Read more.

Recently, the deep learning technology has been adopted in the study of traditional village landscape. More precisely, it’s usually used to explore the representation of cultural heritage and the diversity of heritage information. In this study, we comprehensively reviewed these deep learning-related literatures for the evaluation of traditional village landscapes. E.g., the landscape image recognition led by the pixel-level semantic segmentation algorithm and image feature extraction technology enable user-centred exploration and make cultural heritage digitally and visually accessible. By suggesting a analytic framework using the pixel-level semantic segmentation algorithm and extracting image features, we attempted to identify the physical attributes and spatial characteristics of traditional village landscapes and further simulate the value perception thinking of experts and the public. Besides, we analysed the impact factors and correlation mechanism of spatial attributes to provide a scientific basis and technical support for the protection and utilization of traditional villages. Full article

(This article belongs to the Special Issue Application of Computer Technology in Buildings)

28 pages, 6176 KiB

Open AccessReview

Applications of Computer Vision in Monitoring the Unsafe Behavior of Construction Workers: Current Status and Challenges

by Wenyao Liu, Qingfeng Meng, Zhen Li and Xin Hu

Buildings 2021, 11(9), 409; https://doi.org/10.3390/buildings11090409 - 14 Sep 2021

Cited by 30 | Viewed by 5869

Abstract

The unsafe behavior of construction workers is one of the main causes of safety accidents at construction sites. To reduce the incidence of construction accidents and improve the safety performance of construction projects, there is a need to identify risky factors by monitoring [...] Read more.

The unsafe behavior of construction workers is one of the main causes of safety accidents at construction sites. To reduce the incidence of construction accidents and improve the safety performance of construction projects, there is a need to identify risky factors by monitoring the behavior of construction workers. Computer vision (CV) technology, which is a powerful and automated tool used for extracting images and video information from construction sites, has been recognized and adopted as an effective construction site monitoring technology for the identification of risky factors resulting from the unsafe behavior of construction workers. In this article, we introduce the research background of this field and conduct a systematic statistical analysis of the relevant literature in this field through the bibliometric analysis method. Thereafter, we adopt a content-based analysis method to depict the historical explorations in the field. On this basis, the limitations and challenges in this field are identified, and future research directions are proposed. It is found that CV technology can effectively monitor the unsafe behaviors of construction workers. The research findings can enhance people’s understanding of construction safety management. Full article

(This article belongs to the Special Issue Application of Computer Technology in Buildings)

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18 pages, 2063 KiB

Open AccessReview

Decision Support in Building Construction: A Systematic Review of Methods and Application Areas

by Carmen Marcher, Andrea Giusti and Dominik T. Matt

Buildings 2020, 10(10), 170; https://doi.org/10.3390/buildings10100170 - 24 Sep 2020

Cited by 17 | Viewed by 4160

Abstract

Decision making is a relevant task in the building construction sector, and various systems and methods for decision support are emerging. By means of a systematic literature review, this article identifies the methods for decision making in building construction and the lifecycle phases [...] Read more.

Decision making is a relevant task in the building construction sector, and various systems and methods for decision support are emerging. By means of a systematic literature review, this article identifies the methods for decision making in building construction and the lifecycle phases for which decision support systems are proposed. The selected articles are analyzed and grouped according to the adopted decision-making methods and the defined lifecycle phases. The findings show that multiple criteria decision analysis is the most used method for decision support in building construction and that the construction phase is the most addressed phase within the relevant existing works. The findings related to the construction phase are further refined by grouping the articles into application areas and by reviewing in detail the proposed methods therein. The scarce availability of data and project cases is identified as the most common barrier for the successful development and implementation of decision support systems in the building construction sector. This work provides a basis for scientists and practitioners for identifying suitable methods for decision-making support in a specific lifecycle phase of a building. Full article

(This article belongs to the Special Issue Application of Computer Technology in Buildings)

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Building Information Modelling (BIM) to Enhance Occupational Safety in Construction Activities: Research Trends Emerging from One Decade of Studies

by Mario Fargnoli and Mara Lombardi

Buildings 2020, 10(6), 98; https://doi.org/10.3390/buildings10060098 - 28 May 2020

Cited by 57 | Viewed by 15740

Abstract

In recent years, the use of new technologies is rapidly transforming the way working activities are managed and carried out. In the construction industry, in particular, the use of Building Information Modelling (BIM) is ever increasing as a means to improve the performances [...] Read more.

In recent years, the use of new technologies is rapidly transforming the way working activities are managed and carried out. In the construction industry, in particular, the use of Building Information Modelling (BIM) is ever increasing as a means to improve the performances of numerous activities. In such a context, several studies have proposed BIM as a key process to augment occupational safety effectively, considering that the construction industry still remains one of the most hazardous working sectors. The purpose of the present study is to investigate the recent research addressing the use of BIM to improve construction safety. A systematic review was performed considering journal papers that appeared in literature in the last decade. The results showed that the most viable and promising research directions concern knowledge-based solutions, design for safety improvement through BIM solutions, transversal applications of BIM, and dynamic visualization and feedback. The findings of this study also indicated that more practical BIM applications are needed, especially focusing on safety training and education, the use of BIM to augment safety climate and resilience, and the development of quantitative risk analysis to better support safety management. Overall, the study provided a comprehensive research synthesis augmenting knowledge on the role of BIM-based tools in construction safety, which can be considered a reference framework to enhance workers’ safety by means of these new technologies. Full article

(This article belongs to the Special Issue Application of Computer Technology in Buildings)

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