Information Model Research Articles

Advanced Tuberculosis Detection System for Preserving Public Health

Tuberculosis is a major public health threat that requires efficient and early detection technologies. Challenges associated with real-world implementation include information variability, model availability, and operations in different clinical circumstances. In this paper, we introduce a Crow Search Driven Tuned Logistic Regression (CS-TLR) tuberculosis identification system to sustain early identification of the disease and increase the levels of diagnostic accuracy to help sustain public health. The model attempts to enhance the overall prediction performance of logistic regression by optimizing its parameters by using CSA's optimization capability. We gathered the Kaggle dataset with a variety of clinical and demographic characteristics of tuberculosis patients. We evaluate the performance of the suggested method employing standard parameters including AUC (90.5%), precision (89.9%), recall (90.1%), and F1-score (89.7%). The findings suggest that it could be an important public health surveillance tool by enabling early diagnosis and treatment of TB.

Building Information Modeling and AI Algorithms for Optimizing Energy Performance in Hot Climates: A Comparative Study of Riyadh and Dubai

In response to increasing global temperatures and energy demands, optimizing buildings’ energy efficiency, particularly in hot climates, is an urgent challenge. While current research often relies on conventional energy estimation methods, there has been a decrease in the efforts dedicated to leveraging AI-based methodologies as technology advances. This implies a dearth of multiparameter examinations in AI-driven extreme case studies. For this reason, this study aimed to enhance the energy performance of residential buildings in the hot climates of Dubai and Riyadh by integrating Building Information Modeling (BIM) and Machine Learning (ML). Detailed BIM models of a typical residential villa in these regions were created using Revit, incorporating conventional, modern, and green building envelopes (BEs). These models served as the basis for energy simulations conducted with Green Building Studio (GBS) and Insight, focusing on crucial building features such as floor area, external and internal walls, windows, flooring, roofing, building orientation, infiltration, daylighting, and more. To predict Energy Use Intensity (EUI), four ML algorithms, namely, Gradient Boosting Machine (GBM), Random Forest (RF), Support Vector Machine (SVM), and Lasso Regression (LR), were employed. GBM consistently outperformed the others, demonstrating superior prediction accuracy with an R2 of 0.989. This indicates that the model explains 99% of the variance in EUI, highlighting its effectiveness in capturing the relationships between building features and energy consumption. Feature importance analysis (FIA) revealed that roofs (29% in Dubai scenarios (DS) and 40% in Riyadh scenarios (RS)), external walls (19% in DS and 29% in RS), and windows (15% in DS and 9% in RS) have the most impact on energy consumption. Additionally, the study explored the potential for energy optimization, such as cavity green walls and green roofs in RS and double brick walls with VIP insulation and green roofs in DS. The findings of the paper should be interpreted in light of certain limitations but they underscore the effectiveness of combining BIM and ML for sustainable building design, offering actionable insights for enhancing energy efficiency in hot climates.

Developing a BIM based digital twin system for structural health monitoring of civil infrastructure

Abstract The utilization of building information modeling (BIM) within digital technology facilitates the creation of three-dimensional representations for monitoring data in large-scale civil infrastructure. In response to the need for intelligent structural management, this study establishes a structural health monitoring (SHM) system and foundational framework based on digital twins. This framework integrates information from various sources and facilitates collaborative efforts for structural operation and maintenance. Additionally, the SHM system integrates actual monitoring measurements and early warning mechanisms to consolidate multi-source monitoring data with BIM. Through real-time analysis, the system provides insights into the operational status of bridges, capturing geometric, physical, and performance evolution characteristics. To construct the system, engineering challenges are initially digitized, with appropriate sensors deployed on real bridge structures to monitor dynamic (acceleration) and static (strain, displacement) physical information during bridge operation. Subsequently, through wireless communication and data storage technologies, the monitored physical data serves as input for mode identification and early warning algorithms, facilitating the acquisition of structural performance information. Finally, three-dimensional display technology enables real-time calculation and rendering of BIM models, fostering the exchange and interaction of monitoring and BIM information, thus enhancing the intelligence of SHM system.

Parallel multi-scale dynamic graph neural network for multivariate time series forecasting

Accurately modeling and predicting multivariate time series (MTS) are crucial in real-world scenarios, where precise predictions aid decision-making. MTS exhibit complex variable relationships and dynamic evolution patterns across various time scales, posing significant modeling challenges. To address these, a parallel multi-scale dynamic graph neural network (PMEDGN) is proposed for parallel modeling of dynamic information across multiple time scales. Spatial-temporal embedding module based on spatial-temporal attention mechanisms and multi-scale dynamic graph generation module are designed. These modules capture implicit spatial-temporal dependencies and self-learn to generate multi-scale dynamic graph structures from MTS without predefined graphs, automatically obtaining the importance of different time scale patterns. Additionally, a global graph convolution module is developed to integrate parallel multi-scale information, enhancing collaboration across time scales for final predictions. Comprehensive experiments on real-world datasets demonstrate the effectiveness and superiority of PMEDGN over state-of-the-art methods, underscoring its potential for practical applications.

Global perspectives on organizational information systems issues: An enigma in search of a theoretical framework

Information Systems (IS) research paradigms, models and findings are largely developed in the context of the United States and Western Europe and thus are largely applicable to the Western world and have limited relevance elsewhere. One area of IS research interest to both practitioners and academics is the elicitation of organizational/management issues related to the use of information technology (IT). The US-based Society for Information Management conducts an annual survey on these issues, but its findings are limited to the US. Given the current ethnocentric approach, the World IT Project, among other topics, examined the organizational IS issues in 37 countries and found that, as expected, the organizational IS issues varied widely from one organization to another and from one country to another. To better understand the nature of these issues and their driving factors, we have developed a multitiered theoretical framework to unravel these factors. This framework comprises three layers: an outer layer with three national-level factors, a middle layer with two macro-IT factors, and an inner layer with three organizational-level factors. Furthermore, 17 propositions are supported by the World IT Project data and secondary data. Such a framework has been long overdue and offers both practitioners and researchers value in understanding the global IS landscape.

Enhancing Cost Management in Construction: The Role of 5D Building Information Modeling (BIM)

Enhancing Cost Management in Construction: The Role of 5D Building Information Modeling (BIM)

Integration of distributed PV into smart grids: A comprehensive analysis for Germany

Modern smart grids typically combine physical and communication networks for efficient information exchange and innovative applications. Aligned with digitalization and advancements in smart grids, the integration of photovoltaic (PV) systems comprises a variety of regulatory and technological aspects. However, no previous study has conducted an extensive and systematic analysis of the PV-grid integration framework, particularly for one country. To fill this gap, this paper uses Germany as an example to present a comprehensive, state-of-the-art analysis of integrating distributed PV systems into smart grids, focusing on the regulation and technical implementation of the German Smart Meter Infrastructure and PV control interfaces. Starting from a standardization perspective, this analysis utilizes the Smart Grid Architecture Model to identify crucial roles, components and processes specifically in Germany. Furthermore, it outlines the current implementation of PV integration into distribution networks at a national level. The results of this study show the overall complexity of PV integration in the smart grid context, confirm the feasibility of the German integration approach, and highlight the necessity of deploying standardized information models and communication technologies. These key findings can help market participants with different roles to identify potential technical bottlenecks or other critical points in the regulation and technical implementation. For instance, the proposed in-depth analysis framework provides an orientation for characterizing the PV integration or, more generally, the grid integration scenario of renewables in other countries.

Barriers to achieving satisfactory dropped objects safety performance in the UK construction sector

In 1980 a deadly explosion occurred at a nuclear missile base precipitated by a dropped object. The potential for major catastrophe, an industry call to action and a research gap forms the rationale for this research into dropped objects. The aim of the research was to devise guidance to assist United Kingdom (UK) based construction sector companies to reduce the frequency of dropped object incidents. A mixed research approach that includes literature review, semi-structured interviews and case studies were used to achieve the purpose of this research. The trend data revealed that dropped object incident rates have remained flat in recent years. The quantitative incident reports and qualitative feedback from interviews concluded that design is a contributory factor in a significant number of incidents and possibly in many cases but more research with a larger quantitative research sample is required. The interviews and literature review revealed several useful recommendations to sector bodies, construction sector companies and for further academic research. Recommendations to Individual Construction Sector Companies are grouped into different themes including manage, eliminate and control. The main recommendations to regulators included ensuring that tool tethering and containers are marked and inspected in line with other lifting equipment. Industry bodies could consider liaising with the energy industry to develop a suitable general construction exclusion zone calculator. Initiatives to improve the design of Mast Climbing Work Platforms to provide integral storage and enclosure solutions could be initiated with the vendors of this equipment. Practitioners and companies could consider offsite construction as a strategic means to reduce the number of dropped objects and consider work scopes that could be executed at ground level rather than at height. Consideration could be given to the more commonly deployed off-site fabrication options such as façade panels and bathroom pods. During detailed design, companies could have a high focus on the mechanism of reducing fixings in facades using Building Information Modelling.There are a number of areas which can be investigated further such as the implications of offsite construction on dropped objects accidents when compared with traditional methods. The research findings hint that Business Information Modelling might be a useful tool to reduce dropped objects on construction sites especially related to facades.While there were several limitations of the research including a limited amount of quantitative data and availability of the specific interview group, the findings of the research will still be useful for the construction sector in the UK and overseas to improve safety performance in construction.

A Review of Negligible Factors Inimical to Building Failures in Nigeria: Architectural View

Building failures pose significant risks to public safety, property, and the environment, making it imperative to identify and address the negligible factors contributing to such failures in Nigeria. This review examines the architectural perspective of building failures in Nigeria, focusing on factors that play a role in mitigating risks and promoting safer construction practices. Through an analysis of recent literature and empirical evidence, the study highlights key findings, conclusions, and recommendations aimed at enhancing construction safety standards nationwide. The findings of the review reveal the multifaceted nature of building failures, influenced by regulatory frameworks, construction materials, skilled labor, community engagement, technological integration, economic incentives, and environmental considerations. Strengthening regulatory enforcement, promoting the use of high-quality construction materials, and investing in skilled labor development emerge as critical strategies for mitigating risks and improving construction safety outcomes. Community engagement initiatives and technological innovations, such as building information modeling (BIM) and real-time monitoring systems, are also identified as effective measures for enhancing transparency and accountability in construction projects. Based on the findings, the study concludes that addressing the negligible factors inimical to building failures requires a holistic approach, encompassing regulatory reforms, capacity building, and technological advancements. Furthermore, the study emphasizes the importance of fostering collaboration between government agencies, industry stakeholders, and local communities to promote construction safety and sustainable development goals. The recommendations proposed include enhancing regulatory enforcement mechanisms, promoting the use of high-quality construction materials, and investing in skilled labor development programs. Additionally, leveraging technological innovations and fostering community engagement initiatives are identified as key strategies for enhancing construction safety standards and fostering sustainable development in Nigeria. Overall, this review provides valuable insights and actionable recommendations for policymakers, construction professionals, and community stakeholders seeking to address the negligible factors contributing to building failures in Nigeria. By implementing the recommendations outlined in this study, stakeholders can work collaboratively to create safer, more resilient built environments that promote the well-being of communities and support sustainable development goals.

IFC CLASS ASSIGNMENT ADD-ON: BIM MODELLING FOR ARCHITECTURAL AND ENGINEERING PROJECTS USING BLENDER

Building Information Modelling (BIM) is a working methodology for the design and management of construction projects that facilitates collaboration and communication between the different parties involved. It is based on the digital three-dimensional representation of infrastructures within the field of architecture and civil engineering. The generated models are true data containers, capable of storing the geometric and semantic information necessary to support the design, construction and maintenance operations of the assets. This methodology promotes data exchange between different software tools through interoperability and the use of standards. Usually in the development of projects throughout their life cycle, commercial, closed-source BIM software is used. This generally leads to limitations in interoperability and data reuse. This paper details advances in the use of Blender, a free and open-source software (FOSS), to support BIM workflows in construction projects. The paper addresses the automation of the process to export a 3D Blender model to a BIM model in IFC (Industry Foundation Classes). The IFC Class Assignment add-on is developed, which allows the automated assignment of IFC classes to the different elements of the 3D model in Blender to convert it into a BIM model, using scripts written in Python. The proposed extension is able to generate, in an agile and simple way, digital models in IFC4, adequately storing the geometric and semantic information of its components. The results provide a tool that contributes to automate the creation of BIM models in an open-source software such as Blender, simplifying modelling processes and supporting collaboration and standardisation in architectural and engineering projects. Keywords: BIM, IFC, Automation, Free and Open-Source Software, Blender, Python.

Modular Structure and BIM-Enabled Automation in Design and Construction

Abstract The construction industry is experiencing a profound transformation, driven by rapid technological advancements that aim to improve efficiency, sustainability, and precision across all stages of the building process. Among these advancements, Building Information Modeling (BIM) and automation technologies stand out as crucial innovations, particularly within the realm of modular construction. This paper delves into the integration of BIM with modular construction techniques and automation processes, exploring the ways in which these technologies are revolutionizing the industry. By conducting a detailed comparison between traditional modular construction methods and those enabled by BIM, this study demonstrates the significant enhancements in design accuracy, manufacturing efficiency, and on-site assembly quality. Furthermore, the paper addresses the sustainability benefits that arise from the adoption of BIM-enabled modular construction, including reduced waste, optimized resource use, and lower carbon footprints. Drawing upon case studies, industry practices, and real-world applications, this research offers a comprehensive analysis of how BIM-enabled automation is reshaping the construction landscape, setting new standards for future projects.

Negligible Building Failures in Rivers State — A Literature Review

Through an in-depth literature review, this study explores the factors influencing the minimal building failures in Rivers State, Nigeria. Unlike many other regions, Rivers State is renowned for its exceptionally low rate of structural failures, highlighting a stark contrast to widespread construction safety issues elsewhere. The study identifies several critical factors behind this achievement: strict legal frameworks, premium building materials, skilled labor, successful community collaboration, favorable environmental conditions, and technological integration. The findings emphasize the importance of upholding strict building regulations and norms to maintain high construction standards. Regular inspections and compliance checks ensure adherence to defined safety protocols, significantly reducing the likelihood of structural problems. The study also underscores the significance of superior building materials and advanced technologies, such as Building Information Modeling (BIM) and smart construction tools, in enhancing project planning and execution. A proficient labor force, continuously trained and certified, is essential for achieving construction excellence. Ongoing professional development programs keep workers updated on the latest methods and safety precautions. Additionally, positive community engagement is crucial for monitoring construction activities, with residents actively reporting deviations from approved plans and unsafe practices, fostering a culture of accountability and vigilance. Favorable environmental conditions, including stable geographical and climatic factors, contribute to the rarity of building failures. Mandatory environmental impact assessments for new projects ensure potential risks are identified and mitigated early in the planning process. Rivers State’s economic stability supports sustained investment in infrastructure and maintenance, facilitated by government initiatives that encourage the use of high-quality building materials. Technological integration, particularly through real-time monitoring and data-driven decision-making, further enhances construction safety by enabling continuous oversight and timely interventions, thus reducing the risk of failures. Rivers State’s approach to construction safety offers valuable lessons for other regions aiming to improve building standards and reduce structural failure rates. This comprehensive analysis highlights the necessity of a multifaceted strategy to enhance and maintain building integrity, resulting in safer and more resilient built environments.

A comparison between CAD system and building information modelling (BIM)

Abstract Building Information Modeling (BIM) has gained widespread recognition as a collaboration process in the construction industry, leading to increased investment by construction companies across all construction stages. in recent years, engineers and project managers have encountered various challenges. These challenges include communication gaps among stakeholders and decision-makers, frequent design changes during implementation resulting in repetitive work, increased project costs, delays, and compromised project quality. This research proposes a methodology that compares BIM technology with traditional CAD methods by applying both systems to the same project. It aims to highlight the problems associated with the traditional system and demonstrate how BIM resolves them. Clash detection, for instance, addresses implementation issues and reduces the need for rework. Studies have shown that BIM significantly reduces errors and omissions in documents by up to 64%, repetitive work by up to 43%, project costs and project duration. Considering these advantages, it is highly recommended to incorporate Building Information Modeling (BIM) technology in all construction projects.

Comparative study on energy efficient green building with conventional building

Abstract Green Building concept is an environmental building practice followed by the construction engineers since the years 2000s. Green building concept is the imperative of time with respect to economic, social and environment aspects. Green building techniques can mainly classify under six categories, waste management, water efficiency, energy efficiency, location, configuration and green materials, where under each technique countless solutions can be developed based on the requirements and the proposed project. Hence, this paper targets to redesign Barka Marina Mall, Oman as a green building considering building configuration, renewable energy and green materials, with the help of Building Information Modelling (BIM) technology and Photovoltaic System software as simulation tools. Aim of the present study is to redesign the Barka Marina Mall, Oman as a green building by considering the building configuration, renewable energy and green materials, with the help of BIM and Photovoltaic System software and compared the results with the conventional building. The criteria considered for the comparative analysis are, annual carbon emission, annual energy use, monthly fuel consumption and monthly energy consumption between the conventional and the green building. Based on the comparative study it is noticed that applying the green building concept has a great potential to save the nation’s resources and the environment by reducing the consumption as well as the cost.

Investigating the Use of 3D Printing and the Integration of BIM in Manufacturing Furniture Units

Abstract 3D printing is an emerging technology and one of the main aspects that can help in its success is BIM (Building Information Modelling). Despite recent interest in this topic, research indicates that to date no framework is in place that highlights the integration of BIM with 3D printing technology in the furniture design and production industry. This research delves deep into the use of 3D printing with the aid of BIM tools to produce furniture units. Through an analytical and experimental approach, this study aims to develop a conceptual framework that integrates BIM within the 3D printing process of small-scale furniture units. To gather data, the existing literature has been reviewed thoroughly and a framework was developed and adopted in the experimental study; where a BIM software was used to simulate a piece of furniture and measure the printing process against a set of criteria such as cost, material, and energy consumption. Results of the experiment were analysed and validated by applying comparative analysis between the interview with an expert in the interior 3D printing field and the results of the simulation. The research provided key aspects to be considered in the 3D printing of interior furniture pieces in addition to outlining the relevant limitations as well as the possible opportunities for further research.

Intelligent building construction cost optimization and prediction by integrating BIM and elman neural network

This study aims to address the challenges of capturing design changes, supply chain fluctuations, and labor cost variations to improve the accuracy and real-time nature of intelligent building construction cost predictions. It seeks to accurately forecast and optimize project costs. The study innovatively constructs an intelligent building construction cost prediction model based on Building Information Modeling (BIM) and Elman neural networks (ENNs), denoted as the BIM-ENN model. The BIM-ENN model first introduces BIM technology to digitize and visualize information related to building structures, electromechanical systems, and pipelines. The digitized data obtained through BIM technology is then used as input data for the ENN, which optimizes the neural network parameters to predict and optimize intelligent building construction costs. Finally, the BIM-ENN model is experimentally evaluated. The results demonstrate that the prediction value of the construction cost of the intelligent building by this model closely matches the original information price, with a prediction accuracy of 95.83 %. Compared with the single ENN, the root mean squared error of the BIM-ENN model is less than 75, and the determination coefficient is above 0.95. This indicates that this model can explain more than 95 % of the construction cost prediction results, making it a feasible solution for actual prediction problems and achieving satisfactory results. The intelligent building construction cost prediction model reported here exhibits high accuracy and reliability. It can successfully forecast construction costs, providing robust decision support for the digitalization and intelligent development of construction enterprises. The practical significance of this study lies in providing the construction industry with an accurate cost management tool that helps enterprises optimize budget control and resource allocation, enhancing risk assessment and management capabilities. Moreover, the potential impact of the BIM-ENN model is its ability to elevate prediction standards within the construction industry, promote technological integration and innovation, enhance enterprise competitiveness, and drive the industry's transition towards digitalization and intelligent sustainable development.

Building Information Modeling Adoption, Implementation, and Challenges in the Ethiopian Construction Industry

Building Information Modeling Adoption, Implementation, and Challenges in the Ethiopian Construction Industry

Unveiling BIM Core: Enhancing Long-Term Usability of Digital Building Documentation with an Advanced Representation Information Repository

The long-term usability of digital building documentation is essential for the maintenance and optimization of infrastructure portfolios. It supports the preservation of building-specific knowledge and the cultural heritage hidden within. However, having to do this throughout the entire lifecycle of a building—or even indefinitely—remains a major challenge. This is especially true for organizations responsible for large collections of digital building documents and datasets, such as public administrations or archives. In this article, we first describe the challenges and requirements associated with preservation tasks and then introduce the concept of representation information within Building Information Modeling (BIM) and all types of related data and documents. This type of information is important to give meaning to the stored bit sequences for a particular community. We then design a repository for representation information and propose some 23 so-called BIM Core content elements. Finally, we focus on BIM and the construction sector and explain how the proposed repository can be used to implement the two concepts introduced in the ISO reference model Open Archival Information System (OAIS), namely the representation information and the context information, as well as the concept of significant properties, which has not yet been explicitly modeled in OAIS.

A Bibliometric Review of the Trends of Construction Digitalization Research in the Past Ten Years

The adoption of digital technologies into construction practices has become a critical area of interest, particularly in addressing challenges related to efficiency, quality, and sustainability. This study focuses on the impacts of digital technologies such as building information modeling (BIM), automation, and blockchain on the construction industry. An in-depth bibliometric analysis of the literature from 2013 to 2023 was conducted using data from the Elsevier Scopus database. Employing the key terms “Construction” and “Digitalization” in the Scopus database ensured that this research systematically identified and examined relevant articles related to digital technologies in construction. Advanced tools like the VOS viewer were used to analyze bibliometric networks, providing insights into current research trends within the built environment sector. The findings strongly focused on digital modeling, automation, and blockchain technologies. The findings also revealed new paradigms such as smart contracts and modular construction. This investigation enhances the academic discourse by elucidating the various nuances, ongoing developments, and future directions in the evolving field of construction digitalization research.

A Building Information Modeling driven approach for improving building envelope energy efficiency in hot arid climates

As a response to growing energy demand and greenhouse gas emissions, enhancing the energy performance of buildings has become a global focus. Studies have shown that building openings are responsible for 40–50% of their energy loss, and these percentages are growing steadily. Silica aerogel represents a potential energy-saving technology for buildings. It has demonstrated its effectiveness as an insulating material in various climates; especially cold climates, however its success in hot arid climates has not been examined yet. Therefore, this paper aims to assess the thermal properties of silica aerogel to determine the dominant parameters that impact its thermal performance in a hot, arid climate. A numerical model of the silica aerogel is conducted using Autodesk Ecotect Analysis. The impact of different factors (thermal conductivity, density, specific heat, and thickness of silica aerogel) on the energy efficiency of the glass window was investigated. Results show that the thickness of silica aerogel has the highest impact on the thermal behavior of silica aerogel, followed by thermal conductivity. Meanwhile, density and specific heat showed a negligible effect on the energy performance of the material. Results showed that a 5 mm-thick aerogel layer and a thermal conductivity of 0.014 W/(mK) exploit the energy performance of the proposed material in hot, arid climates and could provide energy savings of around 63% and 15% in heating and cooling demands, respectively.