Ibrahim Yitmen – författare

The book provides knowledge in the Building Information Model (BIM)-enabled cognitive computing methods for smart built environment involving cognitive network capabilities for smart buildings, integrating Augmented Reality/Mixed Reality in cognitive building concepts, cognitive Internet of Things (CIoT) for smart cities, Artificial Intelligence applications for cognitive cities, and cognitive smart cities using big data and machine learning. It focuses on the potential, requirements and implementation of CIoT paradigm to buildings, Artificial Intelligence techniques, reasoning, and Augmented Reality/Mixed Reality in cognitive building concepts, the concept of cognitive smart cities in its complexity, heterogeneity, and scope, and the challenge of utilizing the big data generated by smart cities from a machine learning perspective. The book comprises BIM-based and data-analytic research on cognitive IoT for smart buildings and cognitive cities using big data and machine learning as complex and dynamic systems. It presents applied theoretical contributions fostering a better understanding of such systems and the synergistic relationships between the motivating physical and informational settings. It reviews ongoing development of BIM-based and data science technologies for the processing, analysis, management, modeling, and simulation of big and context data and the associated applicability to cognitive systems that will advance different aspects of future cognitive cities. The book also analyses the required material to inform pertinent research communities of the state-of-the-art research and the latest development in the area of cognitive smart cities development, as well as a valuable reference for planners, designers, strategists, and ICT experts who are working towards the development and implementation of CIoT based on big data analytics and context–aware computing.

The book provides knowledge in the Building Information Model (BIM)-enabled cognitive computing methods for smart built environment involving cognitive network capabilities for smart buildings, integrating Augmented Reality/Mixed Reality in cognitive building concepts, cognitive Internet of Things (CIoT) for smart cities, Artificial Intelligence applications for cognitive cities, and cognitive smart cities using big data and machine learning. It focuses on the potential, requirements and implementation of CIoT paradigm to buildings, Artificial Intelligence techniques, reasoning, and Augmented Reality/Mixed Reality in cognitive building concepts, the concept of cognitive smart cities in its complexity, heterogeneity, and scope, and the challenge of utilizing the big data generated by smart cities from a machine learning perspective. The book comprises BIM-based and data-analytic research on cognitive IoT for smart buildings and cognitive cities using big data and machine learning as complex and dynamic systems. It presents applied theoretical contributions fostering a better understanding of such systems and the synergistic relationships between the motivating physical and informational settings. It reviews ongoing development of BIM-based and data science technologies for the processing, analysis, management, modeling, and simulation of big and context data and the associated applicability to cognitive systems that will advance different aspects of future cognitive cities. The book also analyses the required material to inform pertinent research communities of the state-of-the-art research and the latest development in the area of cognitive smart cities development, as well as a valuable reference for planners, designers, strategists, and ICT experts who are working towards the development and implementation of CIoT based on big data analytics and context–aware computing.

This book provides knowledge into Cognitive Digital Twins for smart lifecycle management of built environment and infrastructure focusing on challenges and opportunities. It focuses on the challenges and opportunities of data-driven cognitive systems by integrating the heterogeneous data from multiple resources that can easily be used in a machine learning model and adjust the algorithms. It comprises Digital Twins incorporating cognitive features that will enable sensing complex and unpredicted behavior and reason about dynamic strategies for process optimization to support decision-making in lifecycle management of the built environment and infrastructure. The book introduces the Knowledge Graph (KG)-centric framework for Cognitive Digital Twins involving process modeling and simulation, ontology-based Knowledge Graph, analytics for process optimizations, and interfaces for data operability. It offers contributions of Cognitive Digital Twins for the integration of IoT, Big data, AI, smart sensors, machine learning and communication technologies, all connected to a novel paradigm of self-learning hybrid models with proactive cognitive capabilities. The book presents the topologies of models described for autonomous real time interpretation and decision-making support of complex system development based on Cognitive Digital Twins with applications in critical domains such as maintenance of complex engineering assets in built environment and infrastructure. It offers the essential material to enlighten pertinent research communities of the state-of-the-art research and the latest development in the area of Cognitive Digital Twins, as well as a valuable reference for planners, designers, developers, and ICT experts who are working towards the development and implementation of autonomous Cognitive IoT based on big data analytics and context–aware computing.

This book provides knowledge into Cognitive Digital Twins for smart lifecycle management of built environment and infrastructure focusing on challenges and opportunities. It focuses on the challenges and opportunities of data-driven cognitive systems by integrating the heterogeneous data from multiple resources that can easily be used in a machine learning model and adjust the algorithms. It comprises Digital Twins incorporating cognitive features that will enable sensing complex and unpredicted behavior and reason about dynamic strategies for process optimization to support decision-making in lifecycle management of the built environment and infrastructure. The book introduces the Knowledge Graph (KG)-centric framework for Cognitive Digital Twins involving process modeling and simulation, ontology-based Knowledge Graph, analytics for process optimizations, and interfaces for data operability. It offers contributions of Cognitive Digital Twins for the integration of IoT, Big data, AI, smart sensors, machine learning and communication technologies, all connected to a novel paradigm of self-learning hybrid models with proactive cognitive capabilities. The book presents the topologies of models described for autonomous real time interpretation and decision-making support of complex system development based on Cognitive Digital Twins with applications in critical domains such as maintenance of complex engineering assets in built environment and infrastructure. It offers the essential material to enlighten pertinent research communities of the state-of-the-art research and the latest development in the area of Cognitive Digital Twins, as well as a valuable reference for planners, designers, developers, and ICT experts who are working towards the development and implementation of autonomous Cognitive IoT based on big data analytics and context–aware computing.

This book combines Construction 6.0 with AEC principles for designing sustainable, health-focused Martian habitats. It unveils innovative architectural designs ideal for Mars, utilizing 3D printing, autonomous robotics, and regolith, alongside renewable energy and life support systems. With an emphasis on well-being, it integrates biophilic design and digital technologies to enhance operational efficiency. Exploring various habitat models, it advocates a multidisciplinary approach to extraterrestrial colonization that balances technological advancement with environmental and ethical stewardship, aiming to make human life on Mars a healthy and sustainable reality.

Placing vernacular knowledge at the forefront of climate-responsive design, this book deals with the UN’s SDG 11 mandate for inclusive, safe, and resilient cities. The volume also reviews how millennia-old building traditions can decarbonise construction and fortify communities against escalating climate risks. Comprising case studies, and pertinent infographics, it equips practitioners, educators, and decision-makers with the scientific rigour and persuasive language necessary to leverage vernacular intelligence for decarbonisation, equity, and cultural continuity. It is simultaneously an academic contribution, a design manual, and an urgent rallying cry for a planet-positive built environment.

This book offers a comprehensive exploration of research methodology, providing invaluable insights for students and researchers in the AEC industry and engineering fields. Through this book, readers learn the theoretical and practical aspects of research design and academic writing, making it an indispensable resource for anyone engaged in scholarly investigation.This book covers a wide range of topics essential to robust research practices. Readers explore identifying research gaps, formulating problem statements, crafting precise research questions, objectives, and aims. This book delves into the philosophical foundations of different research paradigms—ontological and epistemological factors that impact methodological decisions. It also provides an in-depth examination of qualitative methods such as ethnography, grounded theory, narrative analysis; quantitative methods including experimental design, survey techniques; as well as mixed-methods approaches that combine both to yield comprehensive results.In addition to theoretical content, this book offers practical tools like templates for research proposals and checklists for data collection. These resources are designed to aid researchers in efficiently applying their knowledge in real-world settings. The authors emphasize clarity, coherence, and scholarly rigor in academic writing while providing practical techniques to overcome common obstacles faced by researchers.This book is essential for researchers, scholars, students at all levels who seek to enhance their understanding of research methodology. It provides clear guidance on structuring and organizing research articles, performing literature reviews, presenting findings with scholarly rigor. Whether you are a novice researcher or an experienced academician looking to refine your skills or gain new perspectives on methodological practices—this book is tailored to meet your needs.Researchers in fields such as architecture, engineering construction (AEC), environmental design find this work particularly beneficial. Its comprehensive scope guarantees its authenticity usefulness rendering it indispensable literary essential study academic writing methodological investigation.