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Artificial Intelligence in Performance-Driven Design: Theories, Methods, and Tools
by Narjes Abbasabadi Mehdi AshayeriARTIFICIAL 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.
Artificial Intelligence in PET/CT Oncologic Imaging
by John A. Andreou Paris A. Kosmidis Athanasios D. GouliamosThis book presents artificial intelligence applications that may help in detecting disease, defining tissue characterization (benign vs malignant), staging and correlation with molecular biomarkers. Originally positioned as a means for noninvasive molecular phenotyping and quantification in the 1970s, PET's technological improvements in the 2000s generated renewed interest in quantification, which has grown over the last five years. This progress is parallel with the development of Artificial intelligence (AI) systems for Oncology which aim at providing the best possible treatment to patients suffering from lung, breast, brain, prostate, liver and other types of cancer. The chapters provide an overview of the use of AI in PET/CT imaging for various types of cancer, and it will be an invaluable tool especially for nuclear medicine physicians and oncologists.
Artificial intelligence in Pharmaceutical Sciences
by Mullaicharam Bhupathyraaj Reeta Vijaya Rani, K. Musthafa Mohamed EssaThis cutting-edge reference book discusses the intervention of artificial intelligence in the fields of drug development, modified drug delivery systems, pharmaceutical technology, and medical devices development. This comprehensive book includes an overview of artificial intelligence in pharmaceutical sciences and applications in the drug discovery and development process. It discusses the role of machine learning in the automated detection and sorting of pharmaceutical formulations. It covers nanosafety and the role of artificial intelligence in predicting potential adverse biological effects. FEATURES Includes lucid, step-by-step instructions to apply artificial intelligence and machine learning in pharmaceutical sciences Explores the application of artificial intelligence in nanosafety and prediction of potential hazards Covers application of artificial intelligence in drug discovery and drug development Reviews the role of artificial intelligence in assessment of pharmaceutical formulations Provides artificial intelligence solutions for experts in the pharmaceutical and medical devices industries This book is meant for academicians, students, and industry experts in pharmaceutical sciences, medicine, and pharmacology.
Artificial Intelligence in Practice: How 50 Successful Companies Used AI and Machine Learning to Solve Problems
by Bernard MarrCyber-solutions to real-world business problems Artificial Intelligence in Practice is a fascinating look into how companies use AI and machine learning to solve problems. Presenting 50 case studies of actual situations, this book demonstrates practical applications to issues faced by businesses around the globe. The rapidly evolving field of artificial intelligence has expanded beyond research labs and computer science departments and made its way into the mainstream business environment. Artificial intelligence and machine learning are cited as the most important modern business trends to drive success. It is used in areas ranging from banking and finance to social media and marketing. This technology continues to provide innovative solutions to businesses of all sizes, sectors and industries. This engaging and topical book explores a wide range of cases illustrating how businesses use AI to boost performance, drive efficiency, analyse market preferences and many others. Best-selling author and renowned AI expert Bernard Marr reveals how machine learning technology is transforming the way companies conduct business. This detailed examination provides an overview of each company, describes the specific problem and explains how AI facilitates resolution. Each case study provides a comprehensive overview, including some technical details as well as key learning summaries: Understand how specific business problems are addressed by innovative machine learning methods Explore how current artificial intelligence applications improve performance and increase efficiency in various situations Expand your knowledge of recent AI advancements in technology Gain insight on the future of AI and its increasing role in business and industry Artificial Intelligence in Practice: How 50 Successful Companies Used Artificial Intelligence to Solve Problems is an insightful and informative exploration of the transformative power of technology in 21st century commerce.
Artificial Intelligence in Prescriptive Analytics: Innovations in Decision Analysis, Intelligent Optimization, and Data-Driven Decisions (Intelligent Systems Reference Library #260)
by Witold Pedrycz Gilberto Rivera Eduardo Fernández Gustavo Javier MeschinoConsidering the advances of the different approaches and applications in the last years, and even in the last months, this is a particular moment in history to transform every data-driven decision-making process with the power of Artificial Intelligence (AI). This book reveals, through concrete case studies and original application ideas, how cutting-edge AI techniques are revolutionizing industries such as finance, health care, and manufacturing. It invites us to discover how machine learning, decision analysis, and intelligent optimization are changing, directly or indirectly, almost all aspects of our daily lives. This comprehensive book offers practical insights and real-world applications for professionals, researchers, and students alike. It helps to learn how to apply AI for smarter, data-driven decisions in areas like supply chain management, risk assessment, and even personalized medicine. Be inspired by the chapters of this book and unlock the full potential of AI in your field!
Artificial Intelligence in Process Fault Diagnosis: Methods for Plant Surveillance
by Richard J. FickelschererArtificial Intelligence in Process Fault Diagnosis A comprehensive guide to the future of process fault diagnosis Automation has revolutionized every aspect of industrial production, from the accumulation of raw materials to quality control inspections. Even process analysis itself has become subject to automated efficiencies, in the form of process fault analyzers, i.e., computer programs capable of analyzing process plant operations to identify faults, improve safety, and enhance productivity. Prohibitive cost and challenges of application have prevented widespread industry adoption of this technology, but recent advances in artificial intelligence promise to place these programs at the center of manufacturing process analysis. Artificial Intelligence in Process Fault Diagnosis brings together insights from data science and machine learning to deliver an effective introduction to these advances and their potential applications. Balancing theory and practice, it walks readers through the process of choosing an ideal diagnostic methodology and the creation of intelligent computer programs. The result promises to place readers at the forefront of this revolution in manufacturing. Artificial Intelligence in Process Fault Diagnosis readers will also find: Coverage of various AI-based diagnostic methodologies elaborated by leading expertsGuidance for creating programs that can prevent catastrophic operating disasters, reduce downtime after emergency process shutdowns, and moreComprehensive overview of optimized best practices Artificial Intelligence in Process Fault Diagnosis is ideal for process control engineers, operating engineers working with processing industrial plants, and plant managers and operators throughout the various process industries.
Artificial Intelligence in Project Management and Making Decisions (Studies in Computational Intelligence #1035)
by Pedro Y. Piñero Pérez Rafael E. Bello Pérez Janusz KacprzykThis book presents new developments and advances in the theory, applications, and design methods of computational intelligence, integrated in various areas of project management and BIM environments. The chapters of the book span different soft computing techniques, such as: linguistic data summarization, fuzzy systems, evolutionary algorithms, estimation distribution algorithms, computing with words, augmented reality, and hybrid intelligence systems. In addition, different applications of the neutrosophic theory are presented for the treatment of uncertainty and indeterminacy in decision-making processes. Several chapters of the book constitute systematic reviews, useful for future investigations in the following topics: linguistic summarization of data, augmented reality, and the development of BIM technologies. It is a particularly interesting book for engineers, researchers, specialists, teachers, and students related to project management and the development of BIM technologies.
Artificial Intelligence in Radiation Oncology and Biomedical Physics (Imaging in Medical Diagnosis and Therapy)
by Gilmer Valdes Lei XingThis pioneering book explores how machine learning and other AI techniques impact millions of cancer patients who benefit from ionizing radiation. It features contributions from global researchers and clinicians, focusing on the clinical applications of machine learning for medical physics. AI and machine learning have attracted much recent attention and are being increasingly adopted in medicine, with many clinical components and commercial software including aspects of machine learning integration. General principles and important techniques in machine learning are introduced, followed by discussion of clinical applications, particularly in radiomics, outcome prediction, registration and segmentation, treatment planning, quality assurance, image processing, and clinical decision-making. Finally, a futuristic look at the role of AI in radiation oncology is provided. This book brings medical physicists and radiation oncologists up to date with the most novel applications of machine learning to medical physics. Practitioners will appreciate the insightful discussions and detailed descriptions in each chapter. Its emphasis on clinical applications reaches a wide audience within the medical physics profession.
Artificial Intelligence in Radiation Therapy: First International Workshop, AIRT 2019, Held in Conjunction with MICCAI 2019, Shenzhen, China, October 17, 2019, Proceedings (Lecture Notes in Computer Science #11850)
by Dan Nguyen Lei Xing Steve JiangThis book constitutes the refereed proceedings of the First International Workshop on Connectomics in Artificial Intelligence in Radiation Therapy, AIRT 2019, held in conjunction with MICCAI 2019 in Shenzhen, China, in October 2019.The 20 full papers presented were carefully reviewed and selected from 24 submissions. The papers discuss the state of radiation therapy, the state of AI and related technologies, and hope to find a pathway to revolutionizing the field to ultimately improve cancer patient outcome and quality of life.
Artificial Intelligence in Renewable Energetic Systems: Smart Sustainable Energy Systems (Lecture Notes In Networks And Systems #35)
by Mustapha HattiThis book includes the latest research presented at the International Conference on Artificial Intelligence in Renewable Energetic Systems held in Tipaza, Algeria on October 22–24, 2017. The development of renewable energy at low cost must necessarily involve the intelligent optimization of energy flows and the intelligent balancing of production, consumption and energy storage. Intelligence is distributed at all levels and allows information to be processed to optimize energy flows according to constraints. This thematic is shaping the outlines of future economies of and offers the possibility of transforming society. Taking advantage of the growing power of the microprocessor makes the complexity of renewable energy systems accessible, especially since the algorithms of artificial intelligence make it possible to take relevant decisions or even reveal unsuspected trends in the management and optimization of renewable energy flows. The book enables those working on energy systems and those dealing with models of artificial intelligence to combine their knowledge and their intellectual potential for the benefit of the scientific community and humanity.
Artificial Intelligence in Schools: A Guide for Teachers, Administrators, and Technology Leaders
by Varun AroraArtificial Intelligence in Schools is the first book to explore the use of Artificial Intelligence (AI) as a tool to enhance K–12 instruction and administration. Every industry and sector will be drastically affected by the presence of artificial intelligence, and schooling is no exception! Written for the in-service community—leaders, administrators, coaches, and teachers alike—this is your one-stop opportunity to make sure you don’t fall behind the fast pace and promising innovations of today’s most advanced learning technology. Author Varun Arora presents AI as a problem-solving tool for teaching and learning, exploring its potential and application in real-world school contexts and in the language of educators. Covering curriculum development, feedback and scoring, student empowerment, behavioral and classroom management, college readiness, and more, the book is full of novel insights and concrete, strategic takeaways.
Artificial Intelligence in Shipping: The State of Digital Innovation (Routledge Studies in Transport Analysis)
by Maria LambrouThe book addresses strategic and innovation management matters that emerge with AI technology deployment in shipping. It illustrates the making of an AI-powered shipping operation as a process; advances in AI technology as well as trustworthy design and development principles and practices can frame, inspire, and guide the contextualized AI-instigated shipping digitalization.The volume elaborates on foreseen value aggregation models stemming from the AI and human symbiosis possibilities, and the consequences these developments imply for shipping business organizations and markets. Preemptive value creation models are exemplified, including endeavours for deep shipping knowledge creation, shipping business process augmentation for both low-discretion and high-criticality tasks, and autonomous vessel and maritime infrastructures establishment, as well as new AI-supply side oriented business models. The author posits that AI-driven renewal strategies do not imply a disinvestment in ‘legacy’ functions (aka ship ownership and management) paired with aggressive investment in AI development and platformization; AI management directs a new mix of conceivable physical and digital assets, resources, and capabilities for the chosen nuance of a firm’s business model innovation. The central argument of the book elaborates how shipping companies in the loop can be nothing but the negotiated outcome of a new AI-powered institutional entrepreneurial regime; embedded, distributed agency mechanisms enact the wealth-creating, progressive, and responsible digitalization of shipping.This volume will be of value to students and researchers interested in shipping markets, digital technology, and innovation management.
Artificial Intelligence in Society: Social, Political and Cultural Implications of a Technological Innovation
by Michael Heinlein Norbert HuchlerArtificial Intelligence (AI) represents a key technology for social change in the 21st century. Numerous technological applications are now in use that are based on machine learning and the associated possibilities for data collection, use and exploitation. By making large amounts of data manageable and hidden patterns and connections visible, AI makes many things faster, easier and more efficient - be it in everyday life, at work or in organizations. However, the question remains open as to what profound and sometimes latent consequences for humans as social beings and social coexistence are associated with the use and development of AI. How is the relationship between people and technology changing through AI and how should this change be assessed? What opportunities and risks do the use and development of AI open up for people and society? What are the limits of change and what design options are available? And last but not least: What and who determines the development paths that AI takes - with what consequences and for whom? Some of the articles in this volume have been automatically translated into English by Springer (machine translation by the service DeepL.com). The contributions were then thoroughly revised, corrected and supplemented by the authors. The authors are therefore responsible not only for the content, but also for the linguistic form of the articles. Nevertheless, the text of the book may differ stylistically from a conventional translation.
Artificial Intelligence in Sport Performance Analysis
by Duarte Araújo Micael S Couceiro Ludovic Seifert Hugo Sarmento Keith DavidsTo understand the dynamic patterns of behaviours and interactions between athletes that characterize successful performance in different sports is an important challenge for all sport practitioners. This book guides the reader in understanding how an ecological dynamics framework for use of artificial intelligence (AI) can be implemented to interpret sport performance and the design of practice contexts. By examining how AI methodologies are utilized in team games, such as football, as well as in individual sports, such as golf and climbing, this book provides a better understanding of the kinematic and physiological indicators that might better capture athletic performance by looking at the current state-of-the-art AI approaches. Artificial Intelligence in Sport Performance Analysis provides an all-encompassing perspective in an innovative approach that signals practical applications for both academics and practitioners in the fields of coaching, sports analysis, and sport science, as well as related subjects such as engineering, computer and data science, and statistics.
Artificial Intelligence in Sports, Movement, and Health
by Carlo Dindorf Eva Bartaguiz Freya Gassmann Michael FröhlichThis comprehensive work explores Artificial Intelligence´s profound impact on revolutionizing how we approach sports, movement, and health. It presents a rich collection of insights, practical applications, and perspectives poised to transform these domains. Therefore, leading experts in the fields were brought together, offering diverse perspectives and applications across various disciplines. Through the examination of real-world use cases and future possibilities, this book empowers readers with knowledge, enhancing the understanding of the transformative potential of AI in sports, movement, and health.
Artificial Intelligence in STEM Education: The Paradigmatic Shifts in Research, Education, and Technology (Chapman & Hall/CRC Artificial Intelligence and Robotics Series)
by Fan Ouyang, Pengcheng Jiao, Bruce M. McLaren and Amir H. AlaviArtificial intelligence (AI) opens new opportunities for STEM education in K-12, higher education, and professional education contexts. This book summarizes AI in education (AIED) with a particular focus on the research, practice, and technological paradigmatic shifts of AIED in recent years. The 23 chapters in this edited collection track the paradigmatic shifts of AIED in STEM education, discussing how and why the paradigms have shifted, explaining how and in what ways AI techniques have ensured the shifts, and envisioning what directions next-generation AIED is heading in the new era. As a whole, the book illuminates the main paradigms of AI in STEM education, summarizes the AI-enhanced techniques and applications used to enable the paradigms, and discusses AI-enhanced teaching, learning, and design in STEM education. It provides an adapted educational policy so that practitioners can better facilitate the application of AI in STEM education. This book is a must-read for researchers, educators, students, designers, and engineers who are interested in the opportunities and challenges of AI in STEM education.
Artificial Intelligence in Telemedicine: Processing of Biosignals and Medical images (Innovations in Multimedia, Virtual Reality and Augmentation)
by S. N. Kumar Sherin Zafar Eduard Babulak M. Afshar Alam Farheen SiddiquiThis book explores the role of artificial Intelligence in Telemedicine. It explains the concepts through the detailed study and processing of biosignals, physiological parameters, and medical images. The book focuses on computational algorithms in telemedicine for the processing of biosignals, physiological parameters, and medical Images. The book is presented in two section. The first section presents the role of computational algorithms in the processing of biosignal and medical images for disease diagnosis and treatment planning. Noise removal in ECG signal using an improved adaptive learning approach, classification of ECG signals using CNN for cardiac arrhythmia detection, EEG signal analysis for stroke detection, and EMG signal analysis for gesture classification were discussed in this section. Application of CNN in pertussis Diagnosis by temperature monitoring, physician handwriting recognition using deep learning model, melanoma detection using ABCD parameters, and transfer learning enabled heuristic approach for pneumonia detection was also discussed in this section The second section focus on the role of IoT and artificial intelligence in the healthcare sector. IoT in smart health care and applications of artificial intelligence in disease diagnosis and prediction was discussed in this section. The importance of 5G/6G in the pandemic scenario for telemedicine applications, wireless capsule endoscopy image compression, leukemia detection from the microscopic cell images, and genomic signal processing using numerical mapping techniques was also discussed in this section. This book can be used by a wide range of users including students, research scholars, faculty, and practitioners in the field of engineering for applications in biomedical signal, image analysis, and diagnosis.
Artificial Intelligence in the Capitalist University: Academic Labour, Commodification, and Value (Routledge Studies in Education, Neoliberalism, and Marxism)
by John PrestonUsing Marxist critique, this book explores manifestations of Artificial Intelligence (AI) in Higher Education and demonstrates how it contributes to the functioning and existence of the capitalist university. Challenging the idea that AI is a break from previous capitalist technologies, the book offers nuanced examination of the impacts of AI on the control and regulation of academic work and labour, on digital learning and remote teaching, and on the value of learning and knowledge. Applying a Marxist perspective, Preston argues that commodity fetishism, surveillance, and increasing productivity ushered in by the growth of AI, further alienates and exploits academic labour and commodifies learning and research. The text puts forward a solid theoretical framework and methodology for thinking about AI to inform critical and revolutionary pedagogies. Offering an impactful and timely analysis, this book provides a critical engagement and application of key Marxist concepts in the study of AI’s role in Higher Education. It will be of interest to those working or researching in Higher Education.
Artificial Intelligence in the Food Industry: Enhancing Quality and Safety
by Insha Zahoor Sajad Ahmad Wani Tariq Ahmad GanaieIn this changing world of food processing and handling, efficiency and safety are paramount. Artificial Intelligence in the Food Industry: Enhancing Quality and Safety offers a groundbreaking exploration of how artificial intelligence (AI) technologies can address these critical needs. This book explores the transformative potential of AI, machine learning (ML), and deep learning (DL) algorithms in revolutionizing the food industry. By overcoming the limitations of human involvement, AI ensures a more reliable demand-supply chain and enhances food safety.As the global population grows and food consumption reaches unprecedented levels, the demand for innovative solutions is urgent. This book demonstrates how intelligent systems can accurately assess food quality, implement control mechanisms, categorize foods, and conduct predictive analyses. Such advancements are reshaping sectors, including dairy, bakery, beverages, and fruits and vegetables, making this an indispensable guide for food production and safety professionals.It explores several cutting-edge topics such as the role of ML and computer vision in the agri-food industry, the potential of 3D printing, and the integration of AI with sensory technologies like electronic noses, electronic tongues, and near-infrared spectroscopy. These insights highlight how AI can significantly enhance food quality and productivity, benefiting both consumers and industry players.Artificial Intelligence in the Food Industry not only showcases current advancements but also emphasizes the need for ongoing research and innovation. By inviting readers to explore AI’s transformative potential in food production and service, this book ensures a safer, more efficient, and sustainable future for the food industry.A vital resource for researchers, scientists, and professionals in the food industry, this book presents comprehensive information on ML techniques to improve food quality, AI applications in pesticide management, food inspection, grading using image processing, and the use of robots for food safety and warehouse management.
Artificial Intelligence in the Gulf
by Elie Azar Anthony N. HaddadThis book presents the first broad reflection on the challenges, opportunities, and implications of Artificial Intelligence (AI) in the Gulf Cooperation Council (GCC). Unique results and insights are derived through case studies from diverse disciplines, including engineering, economics, data science, policy-making, governance, and humanscience. Particularly related to these ‘softer’ disciplines, we make some unexplored yet topical contributions to the literature, with a focus on the GCC (but by no means limited to it), including AI and implications for women, Islamic schools of thought on AI, and the power of AI to help deliver wellbeing and happiness in cities and urban spaces. Finally, the readers are provided with a synthesis of ideas, lessons learned, and a path forward based on the diverse content of the chapters. The book caters to the educated non specialist with interest in AI, targeting a wide audience including professionals, academics, government officials, policymakers, entrepreneurs, and non-governmental organizations.
Artificial Intelligence in the Operation and Control of Digitalized Power Systems (Power Systems)
by Sasan Azad Morteza Nazari-HerisThis book covers the practical application of AI-based methods in modern power systems. The complexity of current power system operations has dramatically increased due to the higher penetration of renewable energy sources and power electronic components. Therefore, providing efficient techniques is essential for secure and clean power system operation. This book focuses on the data-driven operation of the digitalized power system using machine language (ML). First, the basics of power system operation and control are presented, covering various areas of system control and operation. Next, significant advances in modern power systems and their corresponding challenges are discussed, and artificial intelligence (AI)-powered techniques, specifically machine learning, are introduced to address these issues. The book also explores AI-powered applications in the operation of power systems. These applications include various aspects of the data-driven process in both situational awareness and control areas. They are presented as practical examples indicating the implementation of an ML-based method to solve operational problems. Artificial Intelligence in the Operation and Control of Digitalized Power Systems is a valuable guide for students, researchers, and practicing engineers to AI-based techniques and real-world applications in power systems.
Artificial Intelligence in Value Creation: Improving Competitive Advantage
by Andrzej WodeckiThis book analyses various models of value creation in projects and businesses by applying different forms of Artificial Intelligence in their products and services. First presenting the main concepts and ideas behind AI, Wodecki assesses different models of technology-based value creation based upon the analysis of over 400 case studies. This framework shows how AI may influence both value creation and competitive advantage (efficiency, creativity and flexibility) within a modern organization. Finally, a conceptual model is formulated to evaluate AI-supported in-company projects and new ventures and identify the key managerial and technical competencies required.
Artificial Intelligence in Vision-Based Structural Health Monitoring (Synthesis Lectures on Mechanical Engineering)
by Khalid M. Mosalam Yuqing GaoThis book provides a comprehensive coverage of the state-of-the-art artificial intelligence (AI) technologies in vision-based structural health monitoring (SHM). In this data explosion epoch, AI-aided SHM and rapid damage assessment after natural hazards have become of great interest in civil and structural engineering, where using machine and deep learning in vision-based SHM brings new research direction. As researchers begin to apply these concepts to the structural engineering domain, especially in SHM, several critical scientific questions need to be addressed: (1) What can AI solve for the SHM problems? (2) What are the relevant AI technologies? (3) What is the effectiveness of the AI approaches in vision-based SHM? (4) How to improve the adaptability of the AI approaches for practical projects? (5) How to build a resilient AI-aided disaster prevention system making use of the vision-based SHM? This book introduces and implements the state-of-the-art machine learning and deep learning technologies for vision-based SHM applications. Specifically, corresponding to the above-mentioned scientific questions, it consists of: (1) motivation, background & progress of AI-aided vision-based SHM, (2) fundamentals of machine learning & deep learning approaches, (3) basic AI applications in vision-based SHM, (4) advanced topics & approaches, and (5) resilient AI-aided applications. In the introduction, a brief coverage about the development progress of AI technologies in the vision-based area is presented. It gives the readers the motivations and background of the relevant research. In Part I, basic knowledges of machine and deep learning are introduced, which provide the foundation for the readers irrespective of their background. In Part II, to verify the effectiveness of the AI methods, the key procedure of the typical AI-aided SHM applications (classification, localization, and segmentation) is explored, including vision data collection, data pre-processing,transfer learning-based training mechanism, evaluation, and analysis. In Part III, advanced AI topics, e.g., generative adversarial network, semi-supervised learning, and active learning, are discussed. They aim to address several critical issues in practical projects, e.g., the lack of well-labeled data and imbalanced labels, to improve the adaptability of the AI models. In Part IV, the new concept of “resilient AI” is introduced to establish an intelligent disaster prevention system, multi-modality learning, multi-task learning, and interpretable AI technologies. These advances are aimed towards increasing the robustness and explainability of the AI-enabled SHM system, and ultimately leading to improved resiliency.The scope covered in this book is not only beneficial for education purposes but also is essential for modern industrial applications. The target audience is broad and includes students, engineers, and researchers in civil engineering, statistics, and computer science. Unique Book Features:• Provide a comprehensive review of the rapidly expanding field of vision-based structural health monitoring (SHM) using artificial intelligence approaches. • Re-organize fundamental knowledge specific to the machine and deep learning in vision tasks.• Include comprehensive details about the procedure of conducting AI approaches for vision-based SHM along with examples and exercises.• Cover a vast array of special topics and advanced AI-enabled vision-based SHM applications.• List a few potential extensions for inspiring the readers for future investigation.
Artificial Intelligence in Wireless Robotics (River Publishers Series In Information Science And Technology Ser.)
by Kwang-Cheng ChenRobots, autonomous vehicles, unmanned aerial vehicles, and smart factory, will significantly change human living style in digital society. Artificial Intelligence in Wireless Robotics introduces how wireless communications and networking technology enhances facilitation of artificial intelligence in robotics, which bridges basic multi-disciplinary knowledge among artificial intelligence, wireless communications, computing, and control in robotics. A unique aspect of the book is to introduce applying communication and signal processing techniques to enhance traditional artificial intelligence in robotics and multi-agent systems.The technical contents of this book include fundamental knowledge in robotics, cyber-physical systems, artificial intelligence, statistical decision and Markov decision process, reinforcement learning, state estimation, localization, computer vision and multi-modal data fusion, robot planning, multi-agent systems, networked multi-agent systems, security and robustness of networked robots, and ultra-reliable and low-latency machine-to-machine networking. Examples and exercises are provided for easy and effective comprehension.Engineers wishing to extend knowledge in the robotics, AI, and wireless communications, would be benefited from this book. In the meantime, the book is ready as a textbook for senior undergraduate students or first-year graduate students in electrical engineering, computer engineering, computer science, and general engineering students. The readers of this book shall have basic knowledge in undergraduate probability and linear algebra, and basic programming capability, in order to enjoy deep reading.
Artificial Intelligence in Wireless Sensors and Instruments: Networks and Applications
by Halit ErenThis book heralds a new era in instrumentation and measurements. It combines artificial intelligence (AI) and wireless communications technologies with instrumentation and measurement systems to function as a single unit. AI has advanced considerably due to deep learning utilizing artificial neural networks, availability of large and curated datasets, implementation of a new generation of fast processors having millions of transistors in chips, advanced algorithms, competitive commercial interests, and interests of governments to gain advantages. At the same time, new and highly advanced wireless technologies open new frontiers in communication systems, both technologically and in terms of applications aspects. Advanced technologies such as 5G and 6G networks enable easy use of communication systems by billions of people as well as by billions of machine-to-machine systems.In this book, the communication principles are explained and the implementation of AI on wireless networks is discussed. Many examples are provided. The author discusses instruments and instrumentation networks, modern sensors, and transducers in detail.AI is the technology humans have created where the machines do not only assist us but also think for us creatively in some cases, excelling humans thinking and reasoning. This book includes a chapter explaining how this is done, backed up with more than 50 figures. The security issues, fairness, efficiency, and social impact and acceptance of AI are highlighted. As explained in this book, AI and wireless communications are changing our lives in many ways, including entertainment, games, social interactions, medicine and healthcare, R&D, automated living, intelligent transport systems, finance and economy, and the Internet of Things.