In recent years, smart cities have been an emerging area of interest across the world. Due to this, numerous technologies and tools, such as building information modeling (BIM) and digital twins, have been developed to help achieve smart cities. To ensure research is continuously up to date and new technologies are considered within the field, further study is required. The Research Anthology on BIM and Digital Twins in Smart Cities considers the uses, challenges, and opportunities of BIM and digital twins within smart cities. Covering key topics such as data, design, urban areas, technology, and sustainability, this major reference work is ideal for industry professionals, government officials, computer scientists, policymakers, researchers, scholars, practitioners, instructors, and students.

The advent of connected, smart technologies for the built environment may promise a significant value that has to be reached to develop digital city models. At the international level, the role of digital twin is strictly related to massive amounts of data that need to be processed, which proposes several challenges in terms of digital technologies capability, computing, interoperability, simulation, calibration, and representation. In these terms, the development of 3D parametric models as digital twins to evaluate energy assessment of private and public buildings is considered one of the main challenges of the last years. The ability to gather, manage, and communicate contents related to energy saving in buildings for the development of smart cities must be considered a specificity in the age of connection to increase citizen awareness of these fields. The Handbook of Research on Developing Smart Cities Based on Digital Twins contains in-depth research focused on the description of methods, processes, and tools that can be adopted to achieve smart city goals. The book presents a valid medium for disseminating innovative data management methods related to smart city topics. While highlighting topics such as data visualization, a web-based ICT platform, and data-sharing methods, this book is ideally intended for researchers in the building industry, energy, and computer science fields; public administrators; building managers; and energy professionals along with practitioners, stakeholders, researchers, academicians, and students interested in the implementation of smart technologies for the built environment.

Digital Twins: Making Sense of Smarter Resilient and Sustainable Cities evaluates smart city case studies and insights from the 100 IEEE IoT Global Cities Alliance (GCA) and describes best practices and standards for designing secure architecture using IoT, IoP, and AI. Showcasing success stories while also examining common issues from smart city projects around the world, this guide unpacks lessons learned and identifies where to further integrate standards into city frameworks and processes. Featuring chapters on water, food, energy, mobility, health, waste, education, economies and work, the environment, social wellbeing, ethics, security and privacy, this demonstrates the impact of smart cities on our daily lives. The authors describe the sustainable needs for our next generation and identify the challenges and changes needed to implement smart cities. Readers will learn about Smart City Digital Twins (SCDT), and international Urban Twins (UT), based on architecture, BIM and big data, which support municipalities to digitally simulate 3D models and test strategies and plans for urban planning, mobility, and disaster management. Smart City Digital Twins will use real-time big data from IoT devices and user application transactions to feed models of cities and permit the simulation of new strategies, policies and solutions before physical deployment and negative consequences on citizens and the environment. They also allow monitoring of the effect of decisions and activities once deployed; and offer opportunities, though AI and ML to predict problems, forecast actions which need to be taken and provide trials of modifications. Aimed at practitioners within the field of smart cities as well as those working more broadly on sustainability and technology, readers will learn about the benefits of a smart city currency, new best practices identified through real use cases, digital twins for cities and what they look like, and strategies, policies, and requirements.

Supply chains are experiencing a seismic shift towards customer-centricity and sustainability and the challenges that are bound to arise will require innovative solutions. The escalating complexities of logistics, exacerbated by the profound impacts of the pandemic, underscore the urgency for a paradigm shift. Every industry is grappling with unprecedented disruptions from shortages in essential components to workforce deficits. Navigating Cyber Threats and Cybersecurity in the Logistics Industry serves as a beacon of insight and solutions in this transformative landscape. This groundbreaking book, a result of an in-depth study evaluating 901 startups and scale-ups globally, delves into the Top Logistics Industry Trends & Startups. It unveils the pivotal role of the Insights Discovery Platform, powered by Big Data and Artificial Intelligence, covering over 2 million startups and scale-ups worldwide. This platform offers an immediate and comprehensive assessment of innovations, facilitating the early identification of startups and scale-ups that hold the key to revolutionizing logistics.

This book provides a holistic perspective on Digital Twin (DT) technologies, and presents cutting-edge research in the field. It assesses the opportunities that DT can offer for smart cities, and covers the requirements for ensuring secure, safe and sustainable smart cities. Further, the book demonstrates that DT and its benefits with regard to: data visualisation, real-time data analytics, and learning leading to improved confidence in decision making; reasoning, monitoring and warning to support accurate diagnostics and prognostics; acting using edge control and what-if analysis; and connection with back-end business applications hold significant potential for applications in smart cities, by employing a wide range of sensory and data-acquisition systems in various parts of the urban infrastructure. The contributing authors reveal how and why DT technologies that are used for monitoring, visualising, diagnosing and predicting in real-time are vital to cities’ sustainability and efficiency. The concepts outlined in the book represents a city together with all of its infrastructure elements, which communicate with each other in a complex manner. Moreover, securing Internet of Things (IoT) which is one of the key enablers of DT’s is discussed in details and from various perspectives. The book offers an outstanding reference guide for practitioners and researchers in manufacturing, operations research and communications, who are considering digitising some of their assets and related services. It is also a valuable asset for graduate students and academics who are looking to identify research gaps and develop their own proposals for further research.

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.