This book discusses various machine learning applications and models, developed using heterogeneous data, which helps in a comprehensive prediction, optimization, association analysis, cluster analysis and classification-related applications for various activities in urban area. It details multiple types of data generating from urban activities and suitability of various machine learning algorithms for handling urban data. The book is helpful for researchers, academicians, faculties, scientists and geospatial industry professionals for their research work and sets new ideas in the field of urban computing.

An authoritative treatment of urban computing, offering an overview of the field, fundamental techniques, advanced models, and novel applications. Urban computing brings powerful computational techniques to bear on such urban challenges as pollution, energy consumption, and traffic congestion. Using today's large-scale computing infrastructure and data gathered from sensing technologies, urban computing combines computer science with urban planning, transportation, environmental science, sociology, and other areas of urban studies, tackling specific problems with concrete methodologies in a data-centric computing framework. This authoritative treatment of urban computing offers an overview of the field, fundamental techniques, advanced models, and novel applications. Each chapter acts as a tutorial that introduces readers to an important aspect of urban computing, with references to relevant research. The book outlines key concepts, sources of data, and typical applications; describes four paradigms of urban sensing in sensor-centric and human-centric categories; introduces data management for spatial and spatio-temporal data, from basic indexing and retrieval algorithms to cloud computing platforms; and covers beginning and advanced topics in mining knowledge from urban big data, beginning with fundamental data mining algorithms and progressing to advanced machine learning techniques. Urban Computing provides students, researchers, and application developers with an essential handbook to an evolving interdisciplinary field.

This edited book is a collection of quality research articles reporting research advances in the area of deep learning, IoT and urban computing. It describes new insights based on deep learning and IoT for urban computing and is useful for architects, engineers, policymakers, facility managers, academicians, and researchers who are interested in expanding their knowledge of the applications of deep learning trends involving urban computing.

Machine Learning and the City Explore the applications of machine learning and artificial intelligence to the built environment Machine Learning and the City: Applications in Architecture and Urban Design delivers a robust exploration of machine learning (ML) and artificial intelligence (AI) in the context of the built environment. Relevant contributions from leading scholars in their respective fields describe the ideas and techniques that underpin ML and AI, how to begin using ML and AI in urban design, and the likely impact of ML and AI on the future of city design and planning. Each section couples theoretical and technical chapters, authoritative references, and concrete examples and projects that illustrate the efficacy and power of machine learning in urban design. The book also includes: An introduction to the probabilistic logic that underpins machine learning Comprehensive explorations of the applications of machine learning and artificial intelligence to urban environments Practical discussions of the consequences of applied machine learning and the future of urban design Perfect for designers approaching machine learning and AI for the first time, Machine Learning and the City: Applications in Architecture and Urban Design will also earn a place in the libraries of urban planners and engineers involved in urban design.

What are the means to create a paradigm shift from conventional to intelligent companies? Industry 6.0: Technology, Practices, Challenges and Applications shows how integrating Industry 6.0 technology with data creates a framework for that shift. The book discusses the limitations, pitfalls, and open research questions in Industry 6.0, as well as the most recent advances, architectures, frameworks, applications, and novel practices, methods, and techniques. These are vital for resolving intelligent Internet of Things issues. There is a special focus on sustainable growth, humanization and environmentally friendly intelligent system applications, and an emphasis on the latest innovations in intelligent systems in classical machine learning, deep learning, Internet of Things (IoT), Industrial Internet of Things (IIoT), blockchain, knowledge representation, knowledge management, big data, and natural language processing (NLP). Features: Presents the latest trends in the fields of intelligent systems, machine intelligence, deep learning, and Industrial Internet of Things for smart environments. Discusses securing the mobile ad hoc network (MANET) by detecting the Intrusions using CSO and XGBoost model. Highlights the methods of smart things in collaborative autonomous fleets and platforms for integrating applications across different business and industry domains. Focuses on intelligent process manufacturing, automation using robotics, development of robotic appliances, and smart manufacturing. Covers data-driven agriculture, crop disease prediction, drip irrigation systems, pesticide and fertilizer sprinkling using the Industrial Internet of Things, and water estimation systems. With many contemporary articles from both scientists and practitioners working in many fields where intelligent systems and the IIoT can break new ground, the text is assembled to aim at a readership that includes researchers, statisticians, practitioners, scientists, and developers.

This book constitutes the refereed proceedings of the 15th International Conference on Advances in Computational Collective Intelligence, ICCCI 2023, held in Budapest, Hungary, during September 27–29, 2023. The 59 full papers included in this book were carefully reviewed and selected from 218 submissions. They were organized in topical sections as follows: Collective Intelligence and Collective Decision-Making, Deep Learning Techniques, Natural Language Processing, Data Minning and Machine learning, Social Networks and Speek Communication, Cybersecurity and Internet of Things, Cooperative Strategies for Decision Making and Optimization, Digital Content Understanding and Apllication for Industry 4.0 and Computational Intelligence in Medical Applications.

This book constitutes the thoroughly refereed proceedings of the First Big Social Data and Urban Computing Workshop, BiDU 2018, held in Rio de Janeiro, Brazil, in August 2018. The 11 full papers presented were carefully reviewed and selected from 40 submissions. The papers are organized in topical sections on urban mobility, urban sensing, contemporary social problems, collaboration and crowdsourcing.

METAVERSE AND IMMERSIVE TECHNOLOGIES The book covers the multidimensional perspectives of the metaverse through the prism of virtual reality, augmented reality, blockchain, artificial intelligence, and IoT, ranging from rudimentary to advanced applications. This book provides a thorough explanation of how the technology behind metaverse and other virtual reality technologies are changing the world. The primary objective is to present the revolutionary innovation of the 21st century—the metaverse—and exhibit its wide range of applications in different domains. Although blockchain and VR/AR were the first popularly known applications of the metaverse, several other applications also exist. While some still believe the metaverse is overhyped, in reality, it is transforming almost every industry—healthcare, 3D, 4D, industry, game industry, business management, artificial intelligence, and IoT, just to name a few. This technological breakthrough not only paved the way for virtual reality but also provided useful solutions for other areas of technology. The unique nature of the technology, which is a single, shared, immersive, persistent, 3D virtual space where humans experience life in ways not possible in the physical world, makes it suitable for all real-world applications; it has great potential to transform business, and companies are already in the race for different product offerings. Audience AI and computer science researchers, engineers and graduate students, IT personnel in business as well as entrepreneurs and policymakers.

This book provides insights into research in the field of artificial intelligence in combination with robotics technologies. The integration of artificial intelligence and robotic technologies is a highly topical area for researchers and developers from academia and industry around the globe, and it is likely that artificial intelligence will become the main approach for the next generation of robotics research. The tremendous number of artificial intelligence algorithms and big data solutions has significantly extended the range of potential applications for robotic technologies, and has also brought new challenges for the artificial intelligence community. Sharing recent advances in the field, the book features papers by young researchers presented at the 4th International Symposium on Artificial Intelligence and Robotics 2019 (ISAIR2019), held in Daegu, Korea, on August 20–24, 2019.

This book constitutes the proceedings of the Second International Conference on Security-Enriched Urban Computing and Smart Grid, held in Hualien, Taiwan, in September 2011. The 35 revised full papers presented together with two invited papers were carefully reviewed and selected from 97 submissions. Among the topics covered are the internet of things, mobile networks, wireless networks, service-oriented computing, data-centric computing, voice over IP, cloud computing, privacy, smart grid systems, distributed systems, agent-based systems, assistive technology, social networks, and wearable computing.