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  • thema EDItEUR::U Computing and Information Technology  (21)
  • Firenze University Press  (21)
  • English  (21)
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  • English  (21)
  • French
  • Portuguese
  • Italian  (4)
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  • 1
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    Chapter A Systematic Literature Review to Identify a Methodological Approach for Use in the Modelling and Forecasting of Capital Expenditure of Hyperscale Data Centres (2024)
    Firenze University Press
    Details
    Publication Date: 2024-04-06
    Description: The theme of ‘Managing the digital transformation of the construction industry’ emphasises the importance of considering various dimensions of digitalisation and optimising the built environment. This review aims to present methodological approaches from existing literature that elucidate location-related factors impacting the capital cost of data centres. These findings facilitate adjustments to historical cost data when estimating total costs for new data centres. A systematic literature review method was employed to ensure an objective and comprehensive synthesis. In conjunction with Bayes's theory, this review identifies that a Delphi methodology is the most suitable methodological approach for forecasting and modelling capital expenditure for hyper-scale data centres. The methodology enables collective decision-making and consensus building, recognising the stakeholder's pivotal role in shaping the future of data centres. These findings offer valuable insights for researchers and practitioners in forming a methodological approach for further investigations into the location-related factors impacting the capital cost of data centres. Embracing this knowledge allows us to align research and practice, ensuring that these practices become integral to shaping the future of data centres and the digitalisation and optimisation of the built environment
    Keywords: cost ; decision analysis ; forecasting ; data centres ; thema EDItEUR::U Computing and Information Technology
    Language: English
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  • 2
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    Chapter Integrating Green Roofs into Building Information Modeling (BIM): A Computational Approach for Sustainable Building Design (2024)
    Firenze University Press
    Details
    Publication Date: 2024-04-03
    Description: The construction industry is currently witnessing a transformative period characterized by the convergence of the green and digital transitions. The green transition seeks to address environmental challenges such as climate change and resource depletion, while the digital transition leverages advanced technologies to enhance construction processes. This paper specifically explores the integration of green roofs, as component of sustainable buildings, into the Building Information Modeling (BIM) framework, a key enabler of the digital transition. Green roofs, known for their environmental benefits, consist of layers that contribute to energy efficiency, stormwater management, and biodiversity enhancement. To optimize their design and performance, this research employs Dynamo Visual Programming Language (VPL) within Autodesk Revit to create parametric models of green roofs. These models facilitate the evaluation of thermal and structural characteristics under varying water content conditions (dry and saturated). Results reveal that the choice of substrate and drainage materials significantly impacts thermal resistance, particularly in dry conditions. However, in saturated conditions, the influence on thermal performance converges, emphasizing the importance of structural considerations in both scenarios. The research also highlights various limitations and outlines avenues for future studies, including expanding the range of materials, exploring additional performance metrics, and incorporating AI and machine learning techniques. By addressing these aspects, this research contributes to a comprehensive understanding of the integration of green roofs and BIM. It provides designers and researchers with a practical tool for optimizing green roof designs, aligning with contemporary sustainable construction practices, and promoting the holistic development of green buildings
    Keywords: Sustainability integration ; Parametric modeling ; Digital Transformation ; thema EDItEUR::U Computing and Information Technology
    Language: English
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  • 3
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    Chapter A Robotic Method to Insert Batt Insulation into Light-Frame Wood Wall for Panel Prefabrications (2024)
    Firenze University Press
    Details
    Publication Date: 2024-04-07
    Description: Currently, industrial robot arms are trending in prefabricated building construction; however, a notable gap exists in established automated processes and related research specifically for the insertion of batt thermal insulation. The current method for accomplishing this task relies on manual insertion, which is labour-intensive for the workers and poses long-term health and safety concerns. This research presents an ongoing research project aimed at developing a feasible robotic process for the automated insertion of batt thermal insulation into prefabricated light-frame wood wall frames. This research focuses on the utilization of a single 6-degree-of-freedom robot arm for the insertion process, complimented by the design of a custom-built end-effector. The proposed robotic insertion process, named GLITPP, comprises of six major steps: (1) Grasp, (2) Lift, (3) Insert, (4) Tilt, (5) Push, and (6) Press. The GLITPP insertion process, along with the custom-built end-effector effectively mitigates the influence of the insulation’s nonlinear mechanical properties, while also taking collision avoidance into consideration. This ensures a tight-fitting insulation within the frame cavity, without visible gaps and deficiencies. The necessary physical operating parameters for the insertion process, such as angles, offset, and force requirements, are identified to ensure the precision, efficiency, and repeatability of insertion. A prototype of the designed end-effector is used to demonstrate and validate the robotic method, achieved a high success rate of 93.3%. The development of this research will further advance the complete automation of light-frame wood wall panel prefabrication, offering the industry a wider range of options for selecting thermal insulation for their processes
    Keywords: Robotic Building Prefabrication ; Robotic Insertion ; Light-frame Wood Construction ; Robotic End-effector ; Automation in Construction ; Thermal Insulation ; thema EDItEUR::U Computing and Information Technology
    Language: English
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  • 4
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    Chapter Extracting Information from Construction Safety Requirements Using Large Language Model (2024)
    Firenze University Press
    Details
    Publication Date: 2024-04-07
    Description: The construction industry has long been recognized for its complex safety regulations, which are essential to ensure the well-being of on-site employees. However, navigating these regulations and ensuring compliance can be challenging due to the volume and complexity of the documents involved. This study proposes a novel approach to extracting information from construction safety documents utilizing Large Language Models (LLM), called CSQA, to provide real-time, precise answers to queries related to safety regulations. The approach comprises three modules: (1) the construction safety investigation module (CSI) collects safety regulations for building the information needed. By leveraging a collection of safety regulation PDFs, the system follows a process of text extraction, preprocessing, and global indexing for efficient search. (2) The safety condition identification module (SCI) retrieves the CSI database; after that, the LLM, with its extensive training, processes user queries, searches the indexed regulations, and retrieves pertinent information. (3) the safety information delivery (SID) would provide the answer to the user and incorporate a feedback mechanism to further refine system accuracy based on user responses. Preliminary evaluations reveal the system's superior performance over traditional search engines, owing to its ability to grasp query context and nuances. The CSQA presents a promising method for accessing safety regulations, with potential benefits including reduced non-compliance incidents, enhanced worker safety, and streamlined regulatory consultations in construction
    Keywords: Construction safety document ; extraction ; LLM ; thema EDItEUR::U Computing and Information Technology
    Language: English
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  • 5
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    Chapter A Value Stream Mapping Approach to the Identification of Lean Management Opportunities for Off-Site Construction Production: A Case of Reinforced Concrete Slabs (2024)
    Firenze University Press
    Details
    Publication Date: 2024-04-06
    Description: Off-site construction (OSC), including prefabrication and Modular-integrated Construction (MiC), is gaining popularity as a school of sustainable construction methods that can improve productivity, quality, and waste reduction. However, OSC projects face challenges related to technical integration, collaboration among stakeholders, and dynamic uncertainties. As a result, high-quality standards throughout the manufacturing process of OSC products are difficult to ensure, leading to costly rework, delays, and safety issues. This paper applies a value stream mapping (VSM) approach based on lean principles to OSC production for identifying lean management opportunities for off-site construction production. The case studied in this paper is reinforced concrete slabs. First, we employed a combination of field investigations and interviews to formalize the flow of materials and information for the case. Then, VSM processed the flow for the current state map, which highlights twelve opportunities to prioritize for slab production, e.g., the adoption of digital technology (VR, BIM) in information flows. The findings in value-added activities improvement of the opportunities demonstrate the potential of lean management in the slab production case. Furthermore, the VSM approach in this paper can identify the ‘wastes’ in lean theory, which are the control points of OSC production, for enhancing quality, efficiency, and resource utilization. The findings contribute to the existing body of knowledge by providing empirical evidence of the VSM approach to the identification of lean management opportunities for OSC production
    Keywords: Off-site construction ; Prefabricated products ; Lean management ; Value stream mapping ; Quality assurance ; Construction industrialization ; Lean construction ; thema EDItEUR::U Computing and Information Technology
    Language: English
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  • 6
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    AXMEDIS 2007 Conference Proceedings (2022)
    Firenze University Press
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    Publication Date: 2024-04-14
    Description: The AXMEDIS International Conference series has been established since 2005 and is focused on the research, developments and applications in the cross-media domain, exploring innovative technologies to meet the challenges of the sector. AXMEDIS2007 deals with all subjects and topics related to cross-media and digital-media content production, processing, management, standards, representation, sharing, interoperability, protection and rights management. It addresses the latest developments and future trends of the technologies and their applications, their impact and exploitation within academic, business and industrial communities.
    Keywords: Informatica ; Tecnologia dell'informazione ; Pubblicazioni elettroniche ; Archivi aperti ; thema EDItEUR::U Computing and Information Technology
    Language: English
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  • 7
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    Chapter Visualization of Weather-Aware Ambient Heat Risks With Global Illumination in Game Engine (2024)
    Firenze University Press
    Details
    Publication Date: 2024-04-06
    Description: In recent years, the risk of heat stroke has been increasing due to global warming and other factors, and the Ministry of the Environment has been using the heat index to alert people in urban areas. Still, citizens need help knowing the detailed risk information for their neighborhoods. The heat index considers the human body's heat balance and is measured with specialized instruments, so comprehensive and high-density measurement is difficult. In this research, by using global illumination (GI) and primary weather data obtained from the Open Weather Map API for each area, we can realistically render the sunlight condition considering the weather and map and visualize the heat index per pixel based on shaded CG. Furthermore, by reconstructing urban 3D geometry from Google Maps, we have developed a system that visualizes the ever-changing heat index distribution for an arbitrary location in real time. The system has shown the possibility of reducing the number of heat stroke patients by using this system
    Keywords: heat index ; WBGT (wet bulb globe temperature) ; real-time global illumination ; game engine ; thema EDItEUR::U Computing and Information Technology
    Language: English
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  • 8
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    Chapter Blockchain-BPMN Integrated Framework for Construction Management (2024)
    Firenze University Press
    Details
    Publication Date: 2024-04-03
    Description: Implementing blockchain benefits various construction management processes, such as securing payments, enabling traceable design process, and enhancing information transparency in supply chain. However, blockchain implementation in construction is still in its infancy due to weak functionality of smart contracts, which are self-enforceable programs allowing iteration between external data and blockchain. In the context of construction management that embraces complex and dynamic business processes, smart contracts are currently designed based on specific and isolated functional requirements without considering the connection and execution logic between these functions. It leads to inefficient collaboration and even execution errors, thereby corrupting data quality and even causing business failure. Therefore, this paper proposes a Blockchain-BPMN (Business Process Model and Notation) integrated (BBI) framework for construction management. The framework poses two contributions. First, a BPMN-driven method is developed to design smart contracts supporting executing linked and logically connected business activities. Second, an access control strategy is integrated into smart contracts to safeguard the accessibility of sensitive business data in a blockchain environment. The BBI framework is validated in an actual BIM design collaboration scenario, and results show its feasibility and computational performance are acceptable. Several aspects for improvement and future directions are discussed in the end
    Keywords: Smart contract ; Blockchain ; BPMN ; Construction business process ; thema EDItEUR::U Computing and Information Technology
    Language: English
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  • 9
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    Chapter iSafe Welding System: Computer Vision-Based Monitoring System for Safe Welding Work (2024)
    Firenze University Press
    Details
    Publication Date: 2024-04-07
    Description: The construction industry faces significant challenges, including a high prevalence of occupational incidents, often involving fires, explosions, and burn-related accidents due to worker non-compliance with safety protocols. Adherence to safety guidelines and proper utilization of safety equipment are critical to preventing such incidents and safeguarding workers in hazardous work environments. Consequently, a monitoring system tailored for construction safety during welding operations becomes imperative to mitigate the risk of fire accidents. This paper conducts a brief analysis of OSHA rules pertaining to welding work and introduces the iSafe Welding system, an advanced real-time safety monitoring and compliance enforcement solution designed specifically for construction site welding operations. Harnessing the real-time object detection algorithm YOLOv7 in conjunction with rule-based scene classification, the system excels in identifying potential safety violations. Rigorous evaluation, encompassing precision, recall, mean Average Precision (mAP), accuracy, and the F1-Score, sheds light on its strengths and areas for improvement. The system showcases robust performance in rule-based scene classification, achieving high accuracy, precision, and recall rates. Notably, the iSafe Welding system demonstrates a formidable potential for enhancing construction site safety and regulatory compliance. Ongoing enhancements, including dataset expansion and model refinement, underscore its commitment to real-world deployment and its strength in ensuring worker safety
    Keywords: Safety monitoring ; scene classification ; welding work ; fire prevention ; construction safety ; OSHA rules compliance ; thema EDItEUR::U Computing and Information Technology
    Language: English
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  • 10
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    Chapter Early Detection and Reconstruction of Abnormal Data Using Hybrid VAE-LSTM Framework (2024)
    Firenze University Press
    Details
    Publication Date: 2024-04-04
    Description: Early failure detection and abnormal data reconstruction in sensor data provided by building ventilation control systems are critical for public health. Early detection of abnormal data can help prevent failures in crucial components of ventilation systems, which can result in a variety of issues, from energy wastage to catastrophic outcomes. However, conventional fault detection models ignore valuable features of dynamic fluctuations in indoor air quality (IAQ) measurements and early warning signals of faulty sensor data. This study introduces a hybrid framework for early failure detection and abnormal data reconstruction applying variance analysis and variational autoencoders (VAE) coupled with the long short-term memory network (VAE-LSTM). The periodicity and stable fluctuation of IAQ data are exploited by variance analysis to detect unusual variations before failure occurs. The IAQ dataset which is corrupted by introducing complete failure, bias failure and precision degradation fault is then used to verify the feasibility of the VAE-LSTM model. The results of variance analysis reveal that unusual behavior of the data can be detected as early as 12 hours before failure occurs. The reconstruction performance of the developed method is shown to be superior to other methods under different abnormal data scenarios
    Keywords: Early failure detection ; Abnormal data reconstruction ; Variational autoencoder (VAE) ; Long short-term memory network (LSTM) ; Sustainable IAQ management ; thema EDItEUR::U Computing and Information Technology
    Language: English
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  • 11
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    Chapter Towards Construction Safety Management Maturity Model in the Industry 4.0 Era: A State-of-the-Art Review (2024)
    Firenze University Press
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    Publication Date: 2024-04-04
    Description: While the advantages of leveraging advanced technologies and Industry 4.0 for effective safety management have been extensively recognized, the journey towards a more mature integration of Industry 4.0 technologies into safety management practices often lacks a well-defined and systematic guidance map. This research is a step towards providing organizations with a structured approach to navigate and achieve successful safety management transformation, enabling them to fully harness the potential of industry 4.0 technologies in the workplace. Two rounds of systematic literature reviews (SLRs) are conducted to narrow down the number of articles based on the PRISMA method, which are then subjected to further content analysis. The study highlights the integration of Industry 4.0 technologies within the domains of People, Process, and Policy and their significance in advancing safety maturity. This research uncovered key themes, providing valuable insights that will shape the conceptual maturity model structure of safety management based on the innovative nature of Industry 4.0 to enhance their safety culture to align with. The results provide a fertile ground for a Smart Safety Maturity Model, to integrate technologies to elevate safety drivers in construction safety management
    Keywords: Industry 4.0 ; Maturity model ; safety management ; construction industry ; thema EDItEUR::U Computing and Information Technology
    Language: English
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  • 12
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    E4 Thematic Network (2022)
    Firenze University Press
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    Publication Date: 2024-03-23
    Description: This Thematic Network aims at developing the European dimension of Higher Engineering Education by enhancing the compatibility of the many diverse routes to the profession of engineer, by facilitating greater mobility and integration of skilled personnel throughout Europe, by favouring a mutual exchange of skills and competences and providing a platform for communication between academics and professionals. Five main activities have been organised under the overall umbrella of the Thematic Network.The work contains 6 volumes.
    Keywords: Ingegneria ; Formazione ; Atti di convegno ; thema EDItEUR::A The Arts::AM Architecture ; thema EDItEUR::K Economics, Finance, Business and Management::KN Industry and industrial studies ; thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues::TBC Engineering: general ; thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TN Civil engineering, surveying and building ; thema EDItEUR::U Computing and Information Technology
    Language: English
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  • 13
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    Chapter The Impacts of Digital Fabrication on the Construction Industry: A Systematic Review (2024)
    Firenze University Press
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    Publication Date: 2024-04-03
    Description: The building industry is a major consumer of natural resources and a large contributor to environmental degradation, leading to a need to rethink current building practices. Digital fabrication (Dfab) technologies, which transform design and engineering data into physical products, are gaining traction in the Architecture, Engineering and Construction (AEC) industry. This study aimed to evaluate the implications of digital fabrication in the construction industry, by identifying the current Dfab applications and the hindrances that are limiting its implementation. The research questions addressed were why Dfab is essential in the construction sector, the current state-of-the-art of Dfab in the construction industry, and how Dfab is improving the construction industry. Through a systematic literature review, the findings proposed that Dfab can revolutionize the construction sector, enabling freeform architecture, reducing construction costs, cutting material waste, and increasing worker safety. Nevertheless, further research is needed to overcome obstacles such as high costs and the lack of digital skills in the construction industry
    Keywords: Digital fabrication ; Construction industry ; Project management ; Digital technology ; Systematic review. ; thema EDItEUR::U Computing and Information Technology
    Language: English
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  • 14
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    Chapter Localizing and Visualizing the Degree of People Crowding with an Omnidirectional Camera by Different Times (2024)
    Firenze University Press
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    Publication Date: 2024-04-07
    Description: The Corona Disaster increased the demand for information on the degree of human crowding, as it was essential to balance avoiding restricting behavior and reducing the risk of crowding. Although there are many technologies for detecting people using monitoring cameras, the number of cameras installed in a wide area is costly, and coverage is limited. In this study, we propose a method to qualitatively visualize the distribution of people by using images captured by a moving omnidirectional camera from the viewpoint of facility management during regular security patrols. Omnidirectional images are used for both 3D modeling of the target space based on SfM (structure from motion) and person detection/tracking by machine learning. The distribution of people is visualized qualitatively by obtaining the positions of the extracted people on the 3D model of the site and mapping them. The parallel software processing of visitor observation and mapping is expected to be highly cost-effective in terms of implementation and operation. On the other hand, although there are time deviations in the mapping depending on the location, the visualization and the updated time show their usefulness in understanding the distribution of congestion
    Keywords: COVID-19 ; people's congestion ; omnidirectional camera ; SfM (Structure from Motion) ; machine-learning ; thema EDItEUR::U Computing and Information Technology
    Language: English
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  • 15
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    Chapter Cognitive Dynamics for Construction Management Learning Tasks in Mixed Reality Environments (2024)
    Firenze University Press
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    Publication Date: 2024-05-09
    Description: Technologies to communicate construction project information (engineering designs, schedules) have evolved into a wider range of innovative ecosystems for engineering practices (e.g., cloud-based 3D representations and advanced immersive environments). There is a lack of exploration of effective user interaction for learning and training in relation to how presented information influences cognition in these ecosystems. The presented research investigates the users’ cognitive and attentional differences using the interactive capabilities of Mixed reality (MX) technology. The enhanced user-situation interactions are analyzed by measuring cognitive dynamics with an emphasis on two processes (attentional focus and cognitive load) in relation to the challenge of the engineering learning task— defined by its complexity (limited time frame for observations of the situations, number of required observations) and nature (episodic). Cognitive dynamics were measured using an electroencephalography (EEG) device that senses electrical activity in response to changing levels of cognitive stimuli via electrodes placed on the scalp. Measuring fluctuations in cognitive processing (related to the intensity of various task demands) allows associating efforts on semantic information processing for learning and training tasks (e.g., walkthroughs for safety checks in job site in MX). The approach enhances opportunities to design technology that best adapts to the user needs for engineering practices with an efficient comprehensive performance assessment
    Keywords: Electroencephalography (EEG) ; Dynamics of attention ; Cognitive load ; Cognitive processing ; thema EDItEUR::U Computing and Information Technology
    Language: English
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  • 16
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    Bioinformatics of genome evolution: from ancestral to modern metabolism (2022)
    Firenze University Press
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    Publication Date: 2024-04-04
    Description: Bioinformatics, that is the interdisciplinary field that blends computer science and biostatistics with biological and biomedical sciences, is expected to gain a central role in next feature. Indeed, it has now affected several fields of biology, providing crucial hints for the understanding of biological systems and also allowing a more accurate design of wet lab experiments. In this work, the analysis of sequence data has be used in different fields, such as evolution (e.g. the assembly and evolution of metabolism), infections control (e.g. the horizontal flow of antibiotic resistance), ecology (bacterial bioremediation).
    Keywords: thema EDItEUR::P Mathematics and Science::PB Mathematics ; thema EDItEUR::P Mathematics and Science::PS Biology, life sciences ; thema EDItEUR::U Computing and Information Technology
    Language: English
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  • 17
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    Chapter Efficient Data Curation Using Active Learning for a Video-Based Fire Detection (2024)
    Firenze University Press
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    Publication Date: 2024-05-11
    Description: Video-based fire detection is a crucial object detection problem that relies on accurate and reliable data to detect fires. However, collecting and labeling fire-related data can be time-consuming and expensive, making it difficult to obtain sufficient data for training machine learning models. To address this challenge, uncertainty-based active learning techniques can be used to iteratively select the most informative samples for labeling. This can reduce the amount of labeled data needed to achieve high model performance and has the potential to even prune the training data with fewer informative samples. The traditional sampling-based uncertainty estimation methods are computationally expensive. Hence, an efficient prior network-based ensemble distillation State-of-the-Art approach is evaluated on an internal dataset which still requires relatively higher overhead computation making it difficult for production deployment. A biased softmax differencing-based uncertainty approach and a feature-based hard data mining approach are proposed and compared with the distillation approach. The novel approaches are found to have a very low overhead uncertainty estimation time compared to the ensemble distillation approach and traditional sampling techniques. The methods are evaluated in the context of curating the unlabeled pool data and improving the training data. For completeness, the experiments are performed on three different data sizes, and overall, the frame-wise selection strategy is proved to be better than the sequence-wise querying strategy. The Principal Component Analysis (PCA)-based hard data mining outperformed other methods and improved the model performance by 16.33% with AUC2% metric when compared with the random selection of data. The approach even outperformed the main network trained on full data by 7.33%, henceforth improving the training data by using informative 26.39% data. The results indicate that novel data mining provides efficient training and pool data curation
    Keywords: Uncertainty Estimation ; Active Learning ; Object Detection ; Outlier Detection ; Feature-based cluster analysis ; Video-based Fire Detection ; thema EDItEUR::U Computing and Information Technology
    Language: English
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  • 18
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    Chapter Deep Learning Based Pose Estimation of Scaffold Fall Accident Safety Monitoring (2024)
    Firenze University Press
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    Publication Date: 2024-05-13
    Description: According to the Ministry of Manpower, falling and slipping accidents are one of the most common accidents in addition, falls from heights (FFH), including accidents during scaffolding work, are still a major cause of death in the construction industry. Regular safety checks are currently being carried out on construction sites, but scaffold-related accidents continue to occur. Sensing technology is being attempted in many industrial sites for safety monitoring, but there are still limitations in terms of the cost of sensors and object detection, which are limited to certain risks. Therefore, this paper proposes a deep learning-based pose estimation approach to identify the risk of falling during scaffolding work in the construction industry. Through analysis of the correlation between unstable behavior during scaffold work and the angle of keypoints of workers, the proposed approach demonstrates the ability to detect the risk of falling. The proposed approach can prevent falling accidents not only by detecting construction site workers, but also by detecting specific risky behaviors. In addition, in limited work environments other than scaffolding work, the information on unstable behavior can be provided to safety managers who may not be aware of the risk, thus contributing to preventing falling accidents
    Keywords: deep learning ; pose estimation ; keypoint angle calculate ; construction site safe monitoring ; falls from heights ; thema EDItEUR::U Computing and Information Technology
    Language: English
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  • 19
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    Chapter Ontology-Based Construction Inspection Planning: A Case Study of Thermal Building Insulation (2024)
    Firenze University Press
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    Publication Date: 2024-05-12
    Description: Poor construction quality is one of the most significant challenges for the construction industry. However, failures can be avoided or minimized by inspections based on detailed quality inspection plans as a part of quality assurance. Therefore, structured and project-specific planning of inspection plans is required to provide inspectors with the right information. Nevertheless, inspection planning is mainly manual, dependent on the individual’s experience and high level of effort. As a result, inspection planning is often neglected and limited to providing general checklists that often lack semantically rich descriptions and are unspecific concerning individual project requirements. Furthermore, proper planning of inspections requires multiple information sources, such as building design, schedules, contractual and supplier guidelines, and standards, all of which must be provided or linked via an information model. Current research lacks an adequate formalized knowledge model to provide the knowledge-driven inspection planning process with the necessary domain knowledge to support inspection planning with heterogeneous information defined in isolated systems. Therefore, this paper extends the Ontology for Construction Quality Assurance (OCQA) with the OCQA-Thermal Insulation (OCQA-TI) to formalize thermal insulation inspection planning knowledge. The OCQA offers a new linked data model that provides explicit knowledge of quality inspection planning. The development of the OCQA-TI follows the Linked Open Terms (LOT) methodology and is implemented using the Web Ontology Language (OWL). The proposed ontology is evaluated using various approaches, including automatic consistency checking, answering competency questions, and criteria-based evaluation. The results indicate that the OCQA-TI can provide inspectors with relevant inspection planning knowledge and integrate various related information streams, thus providing a more comprehensive and efficient approach to insulation inspection planning. The functionality of OCQA-TI enables the fulfillment of increased sustainability and energy efficiency requirements by providing insulation inspection knowledge
    Keywords: semantic web ; building insulation ; ontology ; quality assurance in construction ; inspection planning ; thema EDItEUR::U Computing and Information Technology
    Language: English
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  • 20
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    Chapter Integrating ESG Factors into Construction Projects: A Blockchain-Based Data Management Approach (2024)
    Firenze University Press
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    Publication Date: 2024-04-08
    Description: Environmental, Social, and Governance (ESG) investing has become increasingly significant in the Architecture, Engineering, and Construction (AEC) industry. However, the AEC industry faces challenges such as non-uniform standards, complex information sources, and data security concerns when collecting and verifying ESG data. At the same time, as one of the key points of carbon emission in AEC projects, the ESG management of construction projects is still lacking. This paper proposed a blockchain-based ESG data management framework, which designed to address these challenges in the AEC industry. The framework and the smart contract and transaction data model applied in it realize data collection and information verification in construction projects. By leveraging blockchain technology's key features of transparency, immutability, and traceability, the framework ensures secure and efficient ESG data management. Additionally, the InterPlanetary File System (IPFS) technology enables access to original files for data verification and comparison, further enhancing authenticity. By integrating blockchain and IPFS technologies, our proposed solution enhances the reliability and traceability of ESG data in the construction projects, paving the way for more sustainable and transparent practices
    Keywords: AEC ; Blockchain ; Construction Project ; ESG ; IPFS ; Smart contract ; thema EDItEUR::U Computing and Information Technology
    Language: English
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  • 21
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    Chapter Image Segmentation Applied to Urban Surface and Aerial Constraints Analysis (2024)
    Firenze University Press
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    Publication Date: 2024-04-04
    Description: The rapid progress of artificial intelligence (AI) has prompted the exploration of its potential applications in the construction industry, although at a slower rate. Since the starting point of a design is the analysis of the site’s constraints, the purpose of the ongoing research is the application of artificial intelligence in risk assessment for site areas. The primary objective of this research project is to develop an interactive map that employs AI to identify potential surface and aerial interferences. This map aims to support planners, engineers, and architects during the site context analysis phase by providing real-time visualization of obstacles. The interactive map allows users to explore and analyze identified obstacles, enabling cluster markers and filtering of features. The results obtained from applying this approach in Milan, Italy, demonstrate its functionality and usability, highlighting the tool's ability to provide valuable information in both localized and citywide scenarios. Potential improvements such as size assessment and advanced marker generation are also being examined to enhance the management of surface and air interferences. The goal is to enhance the tool's functionality, accuracy, and planning efficiency in construction projects
    Keywords: Image Segmentation ; Risk Assessment ; Construction Site ; Clustering Techniques ; thema EDItEUR::U Computing and Information Technology
    Language: English
    Format: image/jpeg
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