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  • thema EDItEUR::U Computing and Information Technology  (21)
  • Firenze University Press  (21)
  • English  (21)
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  • 1
    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
    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
    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
    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
    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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    Firenze University Press
    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
    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
    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
    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
    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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