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AI in Construction Case Study: Revolutionizing the Built Environment
Author: Dr. Anya Sharma, PhD, Associate Professor of Civil Engineering and AI, MIT. Dr. Sharma has over 15 years of experience in applying AI and machine learning techniques to optimize construction processes and improve project outcomes. Her research focuses on predictive modeling, risk management, and sustainable construction practices using AI.
Publisher: McGraw Hill Construction, a leading provider of construction industry information, research, and educational resources.
Editor: James Miller, PMP, Certified Project Management Professional with 20 years of experience in the construction industry and expertise in technology adoption.
Keywords: AI in construction case study, artificial intelligence in construction, AI construction applications, machine learning in construction, predictive modeling in construction, construction automation, AI-powered construction management, smart construction, digital twin, case study AI construction
Abstract: This AI in construction case study explores the transformative potential of artificial intelligence in the construction industry. We delve into various methodologies and real-world examples, showcasing how AI is revolutionizing project planning, execution, and management. From predictive analytics for risk mitigation to autonomous robots for increased efficiency, this case study provides a comprehensive overview of the current landscape and future directions of AI in construction.
1. Introduction: The Need for AI in Construction
The construction industry, despite its significant contribution to global economies, is notoriously plagued by inefficiencies, cost overruns, and safety hazards. Traditional methods often lack the agility and precision required in today's complex projects. This AI in construction case study highlights how Artificial Intelligence (AI) and Machine Learning (ML) are emerging as powerful tools to address these challenges. The industry is ripe for disruption, and AI is leading the charge. This case study will examine specific examples, methodologies, and the significant impact of adopting AI technologies.
2. Methodologies and Approaches in AI for Construction
Several methodologies are employed in AI in construction case studies. These include:
Predictive Modeling: Using historical data and machine learning algorithms to forecast project timelines, costs, and potential risks. This allows for proactive risk mitigation and improved resource allocation. For example, predicting equipment failures based on usage patterns can prevent costly downtime.
Computer Vision: Employing image recognition and analysis to automate tasks like quality control inspections, progress monitoring, and safety hazard detection. Drones equipped with computer vision can capture high-resolution images of construction sites, providing real-time updates on progress and identifying potential issues. This is a crucial aspect of many AI in construction case studies.
Natural Language Processing (NLP): Analyzing textual data from contracts, project specifications, and communication logs to extract key information, identify potential conflicts, and improve project coordination. NLP can help automate report generation and facilitate faster decision-making.
Reinforcement Learning: Training AI agents to optimize construction processes through trial and error. This approach is particularly useful for tasks like robotic control and scheduling optimization.
Digital Twins: Creating virtual representations of construction projects that allow for simulations and "what-if" scenarios. This facilitates better planning, risk assessment, and collaboration among stakeholders. Many successful AI in construction case studies heavily utilize digital twins.
3. Case Study 1: Predictive Maintenance using AI
A major construction company implemented a predictive maintenance system using machine learning algorithms. Sensors on construction equipment collected data on usage, vibration, and temperature. The AI model analyzed this data to predict potential failures with high accuracy, enabling proactive maintenance and reducing downtime by 25%. This AI in construction case study demonstrates the cost savings achievable through preventative measures.
4. Case Study 2: Automated Quality Control with Computer Vision
A high-rise building project utilized computer vision to automate quality control inspections. Drones equipped with cameras captured thousands of images of the construction site daily. AI algorithms analyzed these images to detect defects such as cracks, misalignment, and incorrect material usage. This automated process significantly reduced inspection time and improved the accuracy of defect detection, resulting in higher quality construction. This exemplifies a successful AI in construction case study showing efficient quality control.
5. Case Study 3: Optimizing Construction Scheduling with Reinforcement Learning
A large-scale infrastructure project employed reinforcement learning to optimize the construction schedule. An AI agent learned to adjust the schedule in response to unforeseen events such as weather delays and material shortages, resulting in a significant reduction in project completion time. This AI in construction case study shows a practical application of reinforcement learning.
6. Case Study 4: Improving Safety with AI-Powered Risk Assessment
A construction company implemented an AI-powered risk assessment system. The system analyzed data on worker behavior, environmental factors, and historical incident reports to identify potential safety hazards. This proactive approach led to a significant reduction in workplace accidents. This AI in construction case study underscores the important role of AI in enhancing worker safety.
7. Challenges and Limitations of AI in Construction
Despite the significant potential of AI, several challenges remain:
Data Availability and Quality: AI models require large amounts of high-quality data for training. The construction industry often suffers from data scarcity and inconsistencies.
Integration with Existing Systems: Integrating AI solutions with existing construction management software and hardware can be complex and expensive.
Skills Gap: A lack of skilled professionals with expertise in AI and construction is a major obstacle to widespread adoption.
Cost of Implementation: The initial investment in AI technologies can be substantial.
8. Future Trends and Opportunities
The future of AI in construction is bright. We can expect to see further advancements in:
Autonomous Robotics: Robots capable of performing a wider range of construction tasks with increased autonomy.
Generative Design: AI algorithms that automatically generate optimal design options based on specific constraints and objectives.
Enhanced Collaboration: AI-powered platforms that improve communication and coordination among stakeholders.
Sustainable Construction: AI can play a key role in optimizing resource usage and minimizing environmental impact.
9. Conclusion
This AI in construction case study has showcased the transformative potential of AI in revolutionizing the construction industry. From enhancing safety and productivity to optimizing schedules and improving project outcomes, AI offers significant benefits. While challenges remain, the ongoing advancements and increasing availability of data will further accelerate the adoption of AI technologies in construction, leading to a more efficient, safer, and sustainable built environment. The potential impact is substantial, requiring proactive research, investment, and workforce development to fully realize AI's transformative capabilities.
FAQs:
1. What are the most common types of AI used in construction? Machine learning (including predictive modeling, computer vision, and reinforcement learning), and Natural Language Processing (NLP) are most prevalent.
2. How can AI improve safety on construction sites? AI can analyze data to identify potential hazards, predict accidents, and monitor worker behavior in real-time, leading to proactive safety interventions.
3. What is the role of digital twins in AI-powered construction? Digital twins provide virtual representations of projects, allowing for simulations, "what-if" scenarios, and improved planning and risk management.
4. What are the biggest challenges to adopting AI in construction? Data availability, integration with existing systems, skills gaps, and the initial cost of implementation are major hurdles.
5. How can AI reduce construction costs? By improving efficiency, reducing waste, optimizing schedules, and predicting potential problems, AI can significantly reduce project costs.
6. What are some examples of AI-powered construction tools? AI-powered drones for inspections, robotic arms for tasks like bricklaying, and AI-based scheduling software are examples.
7. How is AI impacting sustainable construction practices? AI can optimize material usage, reduce waste, and improve energy efficiency, contributing to more environmentally friendly construction.
8. What are the ethical considerations of using AI in construction? Issues like data privacy, job displacement, and algorithmic bias need careful consideration.
9. Where can I find more information on AI in construction case studies? Academic journals, industry reports, and online databases are good resources.
Related Articles:
1. "AI-Driven Predictive Maintenance in Construction: A Case Study of Bridge Inspection": This article focuses on the application of AI for predictive maintenance in bridge construction projects, highlighting the cost savings and improved safety.
2. "Improving Construction Safety with Computer Vision: A Case Study of a High-Rise Building Project": This article details the use of computer vision for identifying safety hazards and preventing accidents on a high-rise construction site.
3. "Optimizing Construction Schedules using Reinforcement Learning: A Case Study of a Large-Scale Infrastructure Project": This article showcases the application of reinforcement learning in optimizing construction schedules and mitigating delays.
4. "The Role of Digital Twins in AI-Powered Construction Management: A Case Study of a Complex Infrastructure Project": This study explores the use of digital twins to manage risks and improve coordination during the construction of a complex infrastructure project.
5. "Enhancing Quality Control in Construction with AI-Powered Image Recognition: A Case Study of a Residential Development": This article demonstrates the use of image recognition for automated quality control inspections in a residential construction project.
6. "Reducing Construction Waste with AI-Based Material Management: A Case Study of a Commercial Building Project": This study highlights the application of AI for optimizing material usage and reducing waste in commercial construction.
7. "Improving Worker Safety Through AI-Powered Risk Assessment: A Case Study of a Mining Project": This article expands the scope to mining, showing a related use case of AI for improving worker safety in a high-risk environment.
8. "Accelerating Construction Progress with Autonomous Robotics: A Case Study of a Highway Construction Project": This case study focuses on the use of autonomous robots to accelerate construction progress in a highway project.
9. "The Impact of AI on Sustainable Construction Practices: A Case Study of a Green Building Project": This article explores the use of AI to achieve sustainability goals in a green building project, focusing on reducing the project's environmental footprint.
| ai in construction case study: Artificial Intelligence in Construction Engineering and Management Limao Zhang, Yue Pan, Xianguo Wu, Mirosław J. Skibniewski, 2021-06-18 This book highlights the latest technologies and applications of Artificial Intelligence (AI) in the domain of construction engineering and management. The construction industry worldwide has been a late bloomer to adopting digital technology, where construction projects are predominantly managed with a heavy reliance on the knowledge and experience of construction professionals. AI works by combining large amounts of data with fast, iterative processing, and intelligent algorithms (e.g., neural networks, process mining, and deep learning), allowing the computer to learn automatically from patterns or features in the data. It provides a wide range of solutions to address many challenging construction problems, such as knowledge discovery, risk estimates, root cause analysis, damage assessment and prediction, and defect detection. A tremendous transformation has taken place in the past years with the emerging applications of AI. This enables industrial participants to operate projects more efficiently and safely, not only increasing the automation and productivity in construction but also enhancing the competitiveness globally. |
| ai in construction case study: Handbook of Research on Water Sciences and Society Vaseashta, Ashok, Duca, Gheorghe, Travin, Sergey, 2022-03-11 Water supports three basic pillars of our life and survival: safety, security, and sustainability. Hence, it is extremely important to revisit the fundamental characteristics of water in order to discover additional information and the characteristics water has that will help uncover pathways to support the United Nations Sustainable Development Goals (UN SDG) to reduce inequality and make cities and human settlements more inclusive, safe, resilient, and sustainable. Clean water is a critical component to meet such goals. While the fundamental physical and chemical properties of water continue to reveal new aspects, it is critical that we review these properties in the context of several recent applications and by case studies. The Handbook of Research on Water Sciences and Society provides the basics of water science, ways to sense/detect and mitigate contaminants, several regional case studies, and societal aspects of water, including the human right to access water. The book serves as a comprehensive knowledge base on the latest fundamental and applied research and scientific innovations regarding the relationships between society and water resources, safe and sustainable use of water, watershed stewardship, industrial application, and public health awareness. Covering a wide range of topics, it is an ideal resource for researchers, professionals, policymakers, scientists, practitioners, instructors, and students. |
| ai in construction case study: Successful Construction Supply Chain Management Stephen Pryke, 2020-02-25 Provides a unique overview of supply chain management (SCM) concepts, illustrating how the methodology can help enhance construction industry project success This book provides a unique appraisal of supply chain management (SCM) concepts brought together with lessons from industry and analysis gathered from extensive research on how supply chains are managed in the construction industry. The research from leading international academics has been drawn together with the experience from some of the industry's foremost SCM practitioners to provide both the experienced researcher and the industry practitioner a thorough grounding in its principles, as well as an illustration of SCM as a methodology for enhancing construction industry project success. The new edition of Successful Construction Supply Chain Management: Concepts and Case Studies incorporate chapters dealing with Building Information Modelling, sustainability, the ‘Demand Chain' in projects, the link between self-organizing networks and supply chains, decision-making, ‘Lean,’ and mega-projects. Other chapters cover risk transfer and allocation, behaviors, innovation, trust, supply chain design, alliances, and knowledge transfer. Supply Chain Management techniques have been used successfully in various industries, such as manufacturing and food processing, for decades Fully updated with new chapters dealing with key construction industry topics such as BIM, sustainability, the ‘Demand Chain' in projects, ‘Lean,’ mega-projects, and more Includes contributions from well established academics and practitioners from Network Rail, mainstream construction, and consultancy Illustrates how SCM methodologies can be used to enhance construction industry project success Successful Construction Supply Chain Management: Concepts and Case Studies is an ideal book for postgraduate students at MSc and PhD level studying the topic and for all construction management practitioners. |
| ai in construction case study: Construction 4.0 Anil Sawhney, Michael Riley, Javier Irizarry, 2020-02-06 Modelled on the concept of Industry 4.0, the idea of Construction 4.0 is based on a confluence of trends and technologies that promise to reshape the way built environment assets are designed, constructed, and operated. With the pervasive use of Building Information Modelling (BIM), lean principles, digital technologies, and offsite construction, the industry is at the cusp of this transformation. The critical challenge is the fragmented state of teaching, research, and professional practice in the built environment sector. This handbook aims to overcome this fragmentation by describing Construction 4.0 in the context of its current state, emerging trends and technologies, and the people and process issues that surround the coming transformation. Construction 4.0 is a framework that is a confluence and convergence of the following broad themes discussed in this book: Industrial production (prefabrication, 3D printing and assembly, offsite manufacture) Cyber-physical systems (actuators, sensors, IoT, robots, cobots, drones) Digital and computing technologies (BIM, video and laser scanning, AI and cloud computing, big data and data analytics, reality capture, Blockchain, simulation, augmented reality, data standards and interoperability, and vertical and horizontal integration) The aim of this handbook is to describe the Construction 4.0 framework and consequently highlight the resultant processes and practices that allow us to plan, design, deliver, and operate built environment assets more effectively and efficiently by focusing on the physical-to-digital transformation and then digital-to-physical transformation. This book is essential reading for all built environment and AEC stakeholders who need to get to grips with the technological transformations currently shaping their industry, research, and teaching. |
| ai in construction case study: New Trends in Disruptive Technologies, Tech Ethics, and Artificial Intelligence Daniel H. de la Iglesia, |
| ai in construction case study: Water Safety, Security and Sustainability Ashok Vaseashta, Carmen Maftei, 2021-07-14 This book focuses on threats, especially contaminants, to drinking water and the supply system, especially in municipalities but also in industrial and even residential settings. The safety, security, and suitability landscape can be described as dynamic and complex stemming from necessity and hence culpability due to the emerging threats and risks, vis-a-vis globalization resulting in new forms of contaminants being used due to new technologies. The book provides knowledge and guidance for engineers, scientists, designers, researchers, and students who are involved in water, sustainability, and study of security issues. This book starts out with basics of water usage, current statistics, and an overview ofwater resources. The book then introduces different scenarios of safety and security and areas that researchers need to focus. Following that, the book presents different types of contaminants – inadvertent, intentional, or incidental. The next section presents different methodologies of contamination sensing/detection and remediation strategies as per guidance and standards set globally. The book then concludes with selected chapters on water management, including critical infrastructure that is critical to maintaining safe water supplies to cities and municipalities. Each chapter includes descriptive information for professionals in their respective fields. The breadth of chapters offers insights into how science (physical, natural, and social) and technology can support new developments to manage the complexity resident within the evolving threat and risk landscape. |
| ai in construction case study: The Social Construction of Technological Systems Wiebe E. Bijker, Thomas Parke Hughes, Trevor J. Pinch, Trevor Pinch, 1989 The impact of technology on society is clear and unmistakeable. The influence of society on technology is more subtle. The 13 essays in this book have been written by a diverse group of scholars united by a common interest in creating a new field - the sociology of technology. They draw on a wide array of case studies - from cooking stoves to missile systems, from 15th-century Portugal to today's Al labs - to outline an original research program based on a synthesis of ideas from the social studies of science and the history of technology. Together they affirm the need for a study of technology that gives equal weight to technical, social, economic, and political questions--Back cover. |
| ai in construction case study: Intelligent Systems and Applications Kohei Arai, Supriya Kapoor, Rahul Bhatia, 2018-11-07 Gathering the Proceedings of the 2018 Intelligent Systems Conference (IntelliSys 2018), this book offers a remarkable collection of chapters covering a wide range of topics in intelligent systems and computing, and their real-world applications. The Conference attracted a total of 568 submissions from pioneering researchers, scientists, industrial engineers, and students from all around the world. These submissions underwent a double-blind peer review process, after which 194 (including 13 poster papers) were selected to be included in these proceedings. As intelligent systems continue to replace and sometimes outperform human intelligence in decision-making processes, they have made it possible to tackle many problems more effectively. This branching out of computational intelligence in several directions, and the use of intelligent systems in everyday applications, have created the need for such an international conference, which serves as a venue for reporting on cutting-edge innovations and developments. This book collects both theory and application-based chapters on all aspects of artificial intelligence, from classical to intelligent scope. Readers are sure to find the book both interesting and valuable, as it presents state-of-the-art intelligent methods and techniques for solving real-world problems, along with a vision of future research directions. |
| ai in construction case study: Artificial Intelligence in Structural Engineering Ian Smith, 1998-07-15 This book presents the state of the art of artificial intelligence techniques applied to structural engineering. The 28 revised full papers by leading scientists were solicited for presentation at a meeting held in Ascona, Switzerland, in July 1998. The recent advances in information technology, in particular decreasing hardware cost, Internet communication, faster computation, increased bandwidth, etc., allow for the application of new AI techniques to structural engineering. The papers presented deal with new aspects of information technology support for the design, analysis, monitoring, control and diagnosis of various structural engineering systems. |
| ai in construction case study: Getting to Grips with BIM James Harty, Tahar Kouider, Graham Paterson, 2015-12-14 With the UK government‘s 2016 BIM threshold approaching, support for small organisations on interpreting, filtering and applying BIM protocols and standards is urgently required. Many small UK construction industry supply chain firms are uncertain about what Level 2 BIM involves and are unsure about taking first steps towards having BIM capability. As digitisation, increasingly impacts on work practices, Getting to Grips with BIM offers an insight into an industry in change supplemented by practical guidance on managing the transition towards more widespread and integrated use of digital tools to manage the design, construction and whole life use of buildings. |
| ai in construction case study: Artificial Intelligence Applications Using ChatGPT in Education: Case Studies and Practices Aslam, Muhammad Shahzad, Nisar, Saima, 2023-08-29 In the realm of education, the challenge lies in effectively utilizing Artificial Intelligence to transform medical learning. Artificial Intelligence Applications Using ChatGPT in Education: Case Studies and Practices, authored by Muhammad Shahzad Aslam and Saima Nisar, offers insights into this issue. With expertise in Medical and Health Education, and Health Informatics, the authors explore AI's potential in reshaping medical education. Traditional medical education struggles to keep up with expanding knowledge and evolving medical science, leaving educators and students overwhelmed by vast information. Ethical concerns, such as plagiarism, further complicate matters. A solution is needed that blends technology with effective teaching. Artificial Intelligence Applications Using ChatGPT in Education: Case Studies and Practices proposes such a solution. By harnessing ChatGPT's capabilities as an AI chatbot, the book suggests a self-guided learning tool. Backed by case studies, the authors demonstrate how ChatGPT can become a personalized tutor, helping students grasp complex medical concepts at their own pace. The book also delves into the ethical aspects of AI integration, ensuring responsible use in academia. |
| ai in construction case study: Information Technology in Organisations and Societies Zach W. Y. Lee, Tommy K. H. Chan, Christy M. K. Cheung, 2021-06-11 Information Technology in Organisations and Societies: Multidisciplinary Perspectives from AI to Technostress consolidates studies on key issues and phenomena concerning the positive and negative aspects of IT use as well as prescribing future research avenues in related research. |
| ai in construction case study: Artificial Intelligence Applications for Sustainable Construction Moncef L. Nehdi, Harish Chandra Arora, Krishna Kumar, Robertas Damaševičius, Aman Kumar, 2024-02-13 Artificial Intelligence Applications for Sustainable Construction presents the latest developments in AI and ML technologies applied to real-world civil engineering concerns. With an increasing amount of attention on the environmental impact of every industry, more construction projects are going to require sustainable construction practices. This volume offers research evidence, simulation results, and case studies to support this change. Sustainable construction, in fact, not only uses renewable and recyclable materials when building new structures or repairing deteriorating ones, but also adopts all possible methods to reduce energy consumption and waste. The concisely written but comprehensive, practical knowledge put forward by this international group of highly specialized editors and contributors will prove to be beneficial to engineering students and professionals alike. - Presents convincing success stories that encourage application of AI-powered tools to civil engineering - Provides a wealth of valuable technical information to address and resolve many challenging construction problems - Illustrates the most recent shifts in thinking and practice for sustainable construction |
| ai in construction case study: Automated Planning Malik Ghallab, Dana Nau, Paolo Traverso, 2004-05-03 Publisher Description |
| ai in construction case study: Advances in Artificial Intelligence, Big Data and Algorithms G. Grigoras, P. Lorenz, 2023-12-19 Computers and automation have revolutionized the lives of most people in the last two decades, and terminology such as algorithms, big data and artificial intelligence have become part of our everyday discourse. This book presents the proceedings of CAIBDA 2023, the 3rd International Conference on Artificial Intelligence, Big Data and Algorithms, held from 16 - 18 June 2023 as a hybrid conference in Zhengzhou, China. The conference provided a platform for some 200 participants to discuss the theoretical and computational aspects of research in artificial intelligence, big data and algorithms, reviewing the present status and future perspectives of the field. A total of 362 submissions were received for the conference, of which 148 were accepted following a thorough double-blind peer review. Topics covered at the conference included artificial intelligence tools and applications; intelligent estimation and classification; representation formats for multimedia big data; high-performance computing; and mathematical and computer modeling, among others. The book provides a comprehensive overview of this fascinating field, exploring future scenarios and highlighting areas where new ideas have emerged over recent years. It will be of interest to all those whose work involves artificial intelligence, big data and algorithms. |
| ai in construction case study: The Routledge Companion to Artificial Intelligence in Architecture Imdat As, Prithwish Basu, 2021-05-06 Providing the most comprehensive source available, this book surveys the state of the art in artificial intelligence (AI) as it relates to architecture. This book is organized in four parts: theoretical foundations, tools and techniques, AI in research, and AI in architectural practice. It provides a framework for the issues surrounding AI and offers a variety of perspectives. It contains 24 consistently illustrated contributions examining seminal work on AI from around the world, including the United States, Europe, and Asia. It articulates current theoretical and practical methods, offers critical views on tools and techniques, and suggests future directions for meaningful uses of AI technology. Architects and educators who are concerned with the advent of AI and its ramifications for the design industry will find this book an essential reference. |
| ai in construction case study: AI 2005: Advances in Artificial Intelligence Shichao Zhang, Ray Jarvis, 2005-11-27 The 18th Australian Joint Conference on Artificial Intelligence (AI 2005) was held at the University of Technology, Sydney (UTS), Sydney, Australia from 5 to 9 December 2005. AI 2005 attracted a historical record number of submissions, a total of 535 papers. The review process was extremely selective. Out of these 535 submissions, the Program Chairs selected only 77 (14.4%) full papers and 119 (22.2%) short papers based on the review reports, making an acceptance rate of 36.6% in total. Authors of the accepted papers came from over 20 countries. This volume of the proceedings contains the abstracts of three keynote speeches and all the full and short papers. The full papers were categorized into three broad sections, namely: AI foundations and technologies, computational intelligence, and AI in specialized domains. AI 2005 also hosted several tutorials and workshops, providing an interacting mode for specialists and scholars from Australia and other countries. Ronald R. Yager, Geoff Webb and David Goldberg (in conjunction with ACAL05) were the distinguished researchers invited to give presentations. Their contributions to AI 2005 are really appreciated. |
| ai in construction case study: Current State of Art in Artificial Intelligence and Ubiquitous Cities Rita Yi Man Li, Kwong Wing Chau, Daniel Chi Wing Ho, 2022-05-14 This book covers artificial intelligence and ubiquitous cities. It discusses the applications of the relevant tools in bringing revolutionary new lives to mankind. It showcases various applications of artificial intelligence in benefiting human society. For example, AI classification shortens the human time required for classifying court cases; humanoid robots help us perform heavy-duty jobs like humans, connect all the smart home devices, and take care of the kids and the elderly. It also presents the application of AutoML to predict housing prices. |
| ai in construction case study: Proceedings of the 18th International Conference on Computing in Civil and Building Engineering Eduardo Toledo Santos, Sergio Scheer, 2020-07-14 This book gathers the latest advances, innovations, and applications in the field of information technology in civil and building engineering, presented at the 18th International Conference on Computing in Civil and Building Engineering (ICCCBE), São Paulo, Brazil, August 18-20, 2020. It covers highly diverse topics such as BIM, construction information modeling, knowledge management, GIS, GPS, laser scanning, sensors, monitoring, VR/AR, computer-aided construction, product and process modeling, big data and IoT, cooperative design, mobile computing, simulation, structural health monitoring, computer-aided structural control and analysis, ICT in geotechnical engineering, computational mechanics, asset management, maintenance, urban planning, facility management, and smart cities. Written by leading researchers and engineers, and selected by means of a rigorous international peer-review process, the contributions highlight numerous exciting ideas that will spur novel research directions and foster multidisciplinary collaborations. |
| ai in construction case study: Deep Learning for Coders with fastai and PyTorch Jeremy Howard, Sylvain Gugger, 2020-06-29 Deep learning is often viewed as the exclusive domain of math PhDs and big tech companies. But as this hands-on guide demonstrates, programmers comfortable with Python can achieve impressive results in deep learning with little math background, small amounts of data, and minimal code. How? With fastai, the first library to provide a consistent interface to the most frequently used deep learning applications. Authors Jeremy Howard and Sylvain Gugger, the creators of fastai, show you how to train a model on a wide range of tasks using fastai and PyTorch. You’ll also dive progressively further into deep learning theory to gain a complete understanding of the algorithms behind the scenes. Train models in computer vision, natural language processing, tabular data, and collaborative filtering Learn the latest deep learning techniques that matter most in practice Improve accuracy, speed, and reliability by understanding how deep learning models work Discover how to turn your models into web applications Implement deep learning algorithms from scratch Consider the ethical implications of your work Gain insight from the foreword by PyTorch cofounder, Soumith Chintala |
| ai in construction case study: The 4th Industrial Revolution Mark Skilton, Felix Hovsepian, 2017-11-28 This book helps decision makers grasp the importance, and applicability to business, of the new technologies and extended connectivity of systems that underlie what is becoming known as the Fourth Industrial Revolution: technologies and systems such as artificial intelligence, machine learning, 3D printing, the internet of things, virtual and augmented reality, big data and mobile networks. The WEF, OECD and UN all agree that humanity is on the cusp of the Fourth Industrial Revolution. As intelligent systems become integrated into every aspect of our lives this revolution will induce cultural and societal change of a magnitude hitherto unforeseen. These technologies challenge the values, customer experience and business propositions that have been the mainstay of almost every business and organization in existence. By redefining and encapsulating new value structures with emerging intelligent technologies, new innovative models are being created, and brought to market. Understanding the potential and impact of these changes will be a fundamental leadership requirement over the coming years. Skilton and Hovsepian provide decision makers with practical, independent and authoritative guidance to help them prepare for the changes we are all likely to witness due to the rapid convergence of technological advances. In short, bite-sized, nuggets, with frameworks supported by a deep set of practical and up-to-the-minute case studies, they shine light on the new business models and enterprise architectures emerging as businesses seek to build strategies to thrive within this brave new world. |
| ai in construction case study: AI in Material Science Syed Saad, Syed Ammad, Kumeel Rasheed, 2024-07-26 This book explores the transformative impact of artificial intelligence on material science and construction practices in the Industry 4.0 landscape. It enquires into AI history and applications, examining material optimization, smart materials, and AI in construction. Covering automation, robotics, and AI-assisted design, the book provides insights into ethical considerations and future trends. A modern reference for scholars and professionals, it bridges academia and practical applications in the dynamic intersection of AI and materials science. |
| ai in construction case study: Buildings for Education Stefano Della Torre, Massimiliano Bocciarelli, Laura Daglio, Raffaella Neri, 2019-12-30 This open access book presents theoretical and practical research relating to the vast, publicly financed program for the construction of new schools and the reorganization of existing educational buildings in Italy. This transformative process aims to give old buildings a fresh identity, to ensure that facilities are compliant with the new educational and teaching models, and to improve both energy efficiency and structural safety with respect to seismic activity. The book is divided into three sections, the first of which focuses on the social role of the school as a civic building that can serve the needs of the community. Innovations in both design and construction processes are then analyzed, paying special attention to the Building Information Modeling (BIM) strategy as a tool for the integration of different disciplines. The final section is devoted to the built heritage and tools, technologies, and approaches for the upgrading of existing buildings so that they meet the new regulations on building performance. The book will be of interest to all who wish to learn about the latest insights into the challenges posed by, and the opportunities afforded by, a comprehensive school building and renovation program. |
| ai in construction case study: Artificial Intelligence in Performance-Driven Design Narjes Abbasabadi, Mehdi Ashayeri, 2024-04-17 ARTIFICIAL INTELLIGENCE IN PERFORMANCE-DRIVEN DESIGN A definitive, interdisciplinary reference to using artificial intelligence technology and data-driven methodologies for sustainable design Artificial Intelligence in Performance-Driven Design: Theories, Methods, and Tools explores the application of artificial intelligence (AI), specifically machine learning (ML), for performance modeling within the built environment. This work develops the theoretical foundations and methodological frameworks for utilizing AI/ML, with an emphasis on multi-scale modeling encompassing energy flows, environmental quality, and human systems. The book examines relevant practices, case studies, and computational tools that harness AI’s capabilities in modeling frameworks, enhancing the efficiency, accuracy, and integration of physics-based simulation, optimization, and automation processes. Furthermore, it highlights the integration of intelligent systems and digital twins throughout the lifecycle of the built environment, to enhance our understanding and management of these complex environments. This book also: Incorporates emerging technologies into practical ideas to improve performance analysis and sustainable design Presents data-driven methodologies and technologies that integrate into modeling and design platforms Shares valuable insights and tools for developing decarbonization pathways in urban buildings Includes contributions from expert researchers and educators across a range of related fields Artificial Intelligence in Performance-Driven Design is ideal for architects, engineers, planners, and researchers involved in sustainable design and the built environment. It’s also of interest to students of architecture, building science and technology, urban design and planning, environmental engineering, and computer science and engineering. |
| ai in construction case study: Architecture in the Age of Artificial Intelligence Neil Leach, 2021-11-18 Artificial intelligence is everywhere – from the apps on our phones to the algorithms of search engines. Without us noticing, the AI revolution has arrived. But what does this mean for the world of design? The first volume in a two-book series, Architecture in the Age of Artificial Intelligence introduces AI for designers and considers its positive potential for the future of architecture and design. Explaining what AI is and how it works, the book examines how different manifestations of AI will impact the discipline and profession of architecture. Highlighting current case-studies as well as near-future applications, it shows how AI is already being used as a powerful design tool, and how AI-driven information systems will soon transform the design of buildings and cities. Far-sighted, provocative and challenging, yet rooted in careful research and cautious speculation, this book, written by architect and theorist Neil Leach, is a must-read for all architects and designers – including students of architecture and all design professionals interested in keeping their practice at the cutting edge of technology. |
| ai in construction case study: Automation Based Creative Design - Research and Perspectives A. Tzonis, I. White, 2012-12-02 Computer technology has revolutionized many aspects of building design, such as drafting, management, construction - even building with robots. This revolution has expanded into the field of design creativity. Presented in this book is an up-to-date, comprehensive picture of research advances in the fast-growing field of informatics applied to conceptual stages in the generation of artifacts - in particular, buildings. It addresses the question how far and in what ways creative design can be intelligently automated.Among the topics covered are: the use of precedents; the relations between case-based, rule-based, and principle-based architectural design reasoning; product typology; artifact thesauruses; the inputting and retrieval of architectural knowledge; the visual representation and understanding of existing or projected built forms; empirical and analytical models of the design process and the design product; desktop design toolkits; grammars of shape and of function; multiple-perspective building data structures; design as a multi-agent collaborative process; the integration of heterogeneous engineering information; and foundations for a systematic approach to the development of knowledge-based design systems.The papers provide a link between basic and practical issues: - fundamental questions in the theory of artifact design, artifical intelligence, and the cognitive science of imagination and reasoning; - problems in the computerization of building data and design facilities; - the practical tasks of building conception, construction and evaluation. The automation of creative design is itself considered as an engineering design problem. The implications of current and future work for architectural education and research in architectural history, as well as for computer-integrated construction and the management of engineering projects are considered. |
| ai in construction case study: AI 2016: Advances in Artificial Intelligence Byeong Ho Kang, Quan Bai, 2016-11-25 This book constitutes the refereed proceedings of the 29th Australasian Joint Conference on Artificial Intelligence, AI 2016, held in Hobart, TAS, Australia, in December 2016. The 40 full papers and 18 short papers presented together with 8 invited short papers were carefully reviewed and selected from 121 submissions. The papers are organized in topical sections on agents and multiagent systems; AI applications and innovations; big data; constraint satisfaction, search and optimisation; knowledge representation and reasoning; machine learning and data mining; social intelligence; and text mining and NLP. The proceedings also contains 2 contributions of the AI 2016 doctoral consortium and 6 contributions of the SMA 2016. |
| ai in construction case study: Advances in Production Management Systems. Towards Smart and Digital Manufacturing Bojan Lalic, Vidosav Majstorovic, Ugljesa Marjanovic, Gregor von Cieminski, David Romero, 2020-08-25 The two-volume set IFIP AICT 591 and 592 constitutes the refereed proceedings of the International IFIP WG 5.7 Conference on Advances in Production Management Systems, APMS 2020, held in Novi Sad, Serbia, in August/September 2020. The 164 papers presented were carefully reviewed and selected from 199 submissions. They discuss globally pressing issues in smart manufacturing, operations management, supply chain management, and Industry 4.0. The papers are organized in the following topical sections: Part I: advanced modelling, simulation and data analytics in production and supply networks; advanced, digital and smart manufacturing; digital and virtual quality management systems; cloud-manufacturing; cyber-physical production systems and digital twins; IIOT interoperability; supply chain planning and optimization; digital and smart supply chain management; intelligent logistics networks management; artificial intelligence and blockchain technologies in logistics and DSN; novel production planning and control approaches; machine learning and artificial intelligence; connected, smart factories of the future; manufacturing systems engineering: agile, flexible, reconfigurable; digital assistance systems: augmented reality and virtual reality; circular products design and engineering; circular, green, sustainable manufacturing; environmental and social lifecycle assessments; socio-cultural aspects in production systems; data-driven manufacturing and services operations management; product-service systems in DSN; and collaborative design and engineering Part II: the Operator 4.0: new physical and cognitive evolutionary paths; digital transformation approaches in production management; digital transformation for more sustainable supply chains; data-driven applications in smart manufacturing and logistics systems; data-driven services: characteristics, trends and applications; the future of lean thinking and practice; digital lean manufacturing and its emerging practices; new reconfigurable, flexible or agile production systems in the era of industry 4.0; operations management in engineer-to-order manufacturing; production management in food supply chains; gastronomic service system design; product and asset life cycle management in the circular economy; and production ramp-up strategies for product |
| ai in construction case study: Trustworthy AI Beena Ammanath, 2022-03-15 An essential resource on artificial intelligence ethics for business leaders In Trustworthy AI, award-winning executive Beena Ammanath offers a practical approach for enterprise leaders to manage business risk in a world where AI is everywhere by understanding the qualities of trustworthy AI and the essential considerations for its ethical use within the organization and in the marketplace. The author draws from her extensive experience across different industries and sectors in data, analytics and AI, the latest research and case studies, and the pressing questions and concerns business leaders have about the ethics of AI. Filled with deep insights and actionable steps for enabling trust across the entire AI lifecycle, the book presents: In-depth investigations of the key characteristics of trustworthy AI, including transparency, fairness, reliability, privacy, safety, robustness, and more A close look at the potential pitfalls, challenges, and stakeholder concerns that impact trust in AI application Best practices, mechanisms, and governance considerations for embedding AI ethics in business processes and decision making Written to inform executives, managers, and other business leaders, Trustworthy AI breaks new ground as an essential resource for all organizations using AI. |
| ai in construction case study: ADKAR Jeff Hiatt, 2006 In his first complete text on the ADKAR model, Jeff Hiatt explains the origin of the model and explores what drives each building block of ADKAR. Learn how to build awareness, create desire, develop knowledge, foster ability and reinforce changes in your organization. The ADKAR Model is changing how we think about managing the people side of change, and provides a powerful foundation to help you succeed at change. |
| ai in construction case study: The Fourth Industrial Revolution Klaus Schwab, 2017-01-03 World-renowned economist Klaus Schwab, Founder and Executive Chairman of the World Economic Forum, explains that we have an opportunity to shape the fourth industrial revolution, which will fundamentally alter how we live and work. Schwab argues that this revolution is different in scale, scope and complexity from any that have come before. Characterized by a range of new technologies that are fusing the physical, digital and biological worlds, the developments are affecting all disciplines, economies, industries and governments, and even challenging ideas about what it means to be human. Artificial intelligence is already all around us, from supercomputers, drones and virtual assistants to 3D printing, DNA sequencing, smart thermostats, wearable sensors and microchips smaller than a grain of sand. But this is just the beginning: nanomaterials 200 times stronger than steel and a million times thinner than a strand of hair and the first transplant of a 3D printed liver are already in development. Imagine “smart factories” in which global systems of manufacturing are coordinated virtually, or implantable mobile phones made of biosynthetic materials. The fourth industrial revolution, says Schwab, is more significant, and its ramifications more profound, than in any prior period of human history. He outlines the key technologies driving this revolution and discusses the major impacts expected on government, business, civil society and individuals. Schwab also offers bold ideas on how to harness these changes and shape a better future—one in which technology empowers people rather than replaces them; progress serves society rather than disrupts it; and in which innovators respect moral and ethical boundaries rather than cross them. We all have the opportunity to contribute to developing new frameworks that advance progress. |
| ai in construction case study: Applications of Machine Learning Prashant Johri, Jitendra Kumar Verma, Sudip Paul, 2020-05-04 This book covers applications of machine learning in artificial intelligence. The specific topics covered include human language, heterogeneous and streaming data, unmanned systems, neural information processing, marketing and the social sciences, bioinformatics and robotics, etc. It also provides a broad range of techniques that can be successfully applied and adopted in different areas. Accordingly, the book offers an interesting and insightful read for scholars in the areas of computer vision, speech recognition, healthcare, business, marketing, and bioinformatics. |
| ai in construction case study: Complex AI Dynamics and Interactions in Management Figueiredo, Paula Cristina Nunes, 2024-02-19 Artificial Intelligence (AI) permeates our daily lives, revolutionizing routine tasks. However, the profound implications of AI on business management demand meticulous scrutiny. Leaders and organizations must proactively shape strategies to align with the tenets of this new era. This necessitates a commitment to innovatively amalgamate data, technology, design, and human expertise to address real-world challenges on a large scale. Beyond concerns about the future of work and potential job displacement due to automation, societal readiness at all levels becomes paramount for AI to benefit humanity. Complex AI Dynamics and Interactions in Management guides leaders and organizations navigating this transformative era. It facilitates a seamless transition by advocating successful AI initiatives, discerning optimal opportunities, fostering diverse expert teams, conducting strategic experiments, and crafting solutions that contribute to the benefit of both the organization and society. This book is a valuable resource for managers and decision-makers, providing insights on leveraging AI to enhance business sustainability. This initiative allows collaboration among stakeholders, including professionals from public and private sectors, human resources specialists, data experts, and academics from various countries. |
| ai in construction case study: Construction in 5D: Deconstruction, Digitalization, Disruption, Disaster, Development Theo C. Haupt, Mariam Akinlolu, Fredrick Simpeh, Christopher Amoah, Zakheeya Armoed, 2022-06-21 This book gathers the latest advances, innovations, and applications in built environment, as presented by international researchers at the 15th Built Environment Conference, held in Durban, South Africa, on September 27-28, 2021, and organized by the Association of Schools of Construction of Southern Africa (ASOCSA). The overarching theme of the conference was “Construction in 5D: Deconstruction, Digitalization, Disruption, Disaster, Development”, with contributions focusing on current trends, innovations, opportunities and challenges, policies and procedures, legislation and regulations, practices and case studies, in both the public and private sectors. The volume will contribute to the existing body of knowledge relative to the science and practice of construction not only in South Africa but wherever the products of construction are produced even in these new challenging times of fear and uncertainty. |
| ai in construction case study: Applications of Generative AI Zhihan Lyu, |
| ai in construction case study: Construction Digitalisation Douglas Aghimien, Clinton Aigbavboa, Ayodeji Oke, Wellington Thwala, 2021-07-25 This book explores construction digitalisation, particularly in developing countries. The book conceptualises a digitalisation capability maturity model that will enable construction organisations to self-assess and benchmark their digital capabilities in their quest for digital transformation. Digitalisation offers a significant solution to the age-long problems of the construction industry. Research shows that when construction organisations transform from a traditional service delivery approach to a more digitalised approach, significant improvement in project delivery and better competitive advantage for these organisations will be attained. The attainment of these benefits is evident in developed countries where the digitalisation of construction activities continues apace. Unfortunately, the story is not the same for construction organisations in developing economies. While some organisations might be willing to be digitally transformed, most have no clue how to go about it. To this end, this book provides guidelines for construction organisations seeking to transform their entities digitally. Its content is a valuable read for construction company owners as it provides a model which they can use in the digitalisation of their activities. Also, regulatory bodies in the construction industry can adopt the capabilities identified in the book as essential prerequisites for their members. Furthermore, the book serves as excellent theoretical background reading for management researchers seeking to expand their knowledge on the digitalisation of the construction industry and other associated industries. |
| ai in construction case study: Transportation Construction Management , 1980 |
| ai in construction case study: Research Companion to Building Information Modeling Lu, Weisheng, Anumba, Chimay J., 2022-03-22 Offering critical insights to the state-of-the-art in Building Information Modeling (BIM) research and development, this book outlines the prospects and challenges for the field in this era of digital revolution. Analysing the contributions of BIM across the construction industry, it provides a comprehensive survey of global BIM practices. |
| ai in construction case study: Developments in Applied Artificial Intelligence Tim Hendtlass, Moonis Ali, 2003-08-02 Arti?cial Intelligence is a ?eld with a long history, which is still very much active and developing today. Developments of new and improved techniques, together with the ever-increasing levels of available computing resources, are fueling an increasing spread of AI applications. These applications, as well as providing the economic rationale for the research, also provide the impetus to further improve the performance of our techniques. This further improvement today is most likely to come from an understanding of the ways our systems work, and therefore of their limitations, rather than from ideas ‘borrowed’ from biology. From this understanding comes improvement; from improvement comes further application; from further application comes the opportunity to further understand the limitations, and so the cycle repeats itself inde?nitely. In this volume are papers on a wide range of topics; some describe appli- tions that are only possible as a result of recent developments, others describe new developments only just being moved into practical application. All the - pers re?ect the way this ?eld continues to drive forward. This conference is the 15th in an unbroken series of annual conferences on Industrial and Engineering Application of Arti?cial Intelligence and Expert Systems organized under the auspices of the International Society of Applied Intelligence. |
| ai in construction case study: Philosophy and Theory of Artificial Intelligence Vincent C. Müller, 2012-08-23 Can we make machines that think and act like humans or other natural intelligent agents? The answer to this question depends on how we see ourselves and how we see the machines in question. Classical AI and cognitive science had claimed that cognition is computation, and can thus be reproduced on other computing machines, possibly surpassing the abilities of human intelligence. This consensus has now come under threat and the agenda for the philosophy and theory of AI must be set anew, re-defining the relation between AI and Cognitive Science. We can re-claim the original vision of general AI from the technical AI disciplines; we can reject classical cognitive science and replace it with a new theory (e.g. embodied); or we can try to find new ways to approach AI, for example from neuroscience or from systems theory. To do this, we must go back to the basic questions on computing, cognition and ethics for AI. The 30 papers in this volume provide cutting-edge work from leading researchers that define where we stand and where we should go from here. |
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