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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. Alavi

Artificial 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 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 Amir H. Alavi

Artificial 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 Vision-Based Structural Health Monitoring (Synthesis Lectures on Mechanical Engineering)

by Khalid M. Mosalam Yuqing Gao

This 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

by Kwang-Cheng Chen

Robots, 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 Robotics

by Kwang-Cheng Chen

Robots, 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, Internet of Things (Smart Engineering Systems)

by Mohan Lal Kolhe Kailash J. Karande Sampat G. Deshmukh

This reference text offers the reader a comprehensive insight into recent research breakthroughs in blockchain, the Internet of Things (IoT), artificial intelligence and material structure and hybrid technologies in their integrated platform, while also emphasizing their sustainability aspects. The text begins by discussing recent advances in energy materials and energy conversion materials using machine learning, as well as recent advances in optoelectronic materials for solar energy applications. It covers important topics including advancements in electrolyte materials for solid oxide fuel cells, advancements in composite materials for Li-ion batteries, progression of materials for supercapacitor applications, and materials progression for thermochemical storage of low-temperature solar thermal energy systems. This book: Discusses advances in blockchain, the Internet of Things, artificial intelligence, material structure and hybrid technologies Covers intelligent techniques in materials progression for sensor development and energy material characterization using signal processing Examines the integration of phase change materials in construction for thermal energy regulation in new buildings Explores the current happenings in technology in conjunction with basic laws and mathematical models Connecting advances in engineering materials with the use of smart techniques including artificial intelligence, machine learning and Internet of Things (IoT) in a single volume, this text will be especially useful for graduate students, academic researchers and professionals in the fields of electrical engineering, electronics engineering, materials science, mechanical engineering and computer science.

Artificial Intelligence, Internet of Things (Smart Engineering Systems)

by Lal Kolhe Mohan

This reference text offers the reader a comprehensive insight into recent research breakthroughs in blockchain, the Internet of Things (IoT), artificial intelligence and material structure and hybrid technologies in their integrated platform, while also emphasizing their sustainability aspects. The text begins by discussing recent advances in energy materials and energy conversion materials using machine learning, as well as recent advances in optoelectronic materials for solar energy applications. It covers important topics including advancements in electrolyte materials for solid oxide fuel cells, advancements in composite materials for Li-ion batteries, progression of materials for supercapacitor applications, and materials progression for thermochemical storage of low-temperature solar thermal energy systems. This book: Discusses advances in blockchain, the Internet of Things, artificial intelligence, material structure and hybrid technologies Covers intelligent techniques in materials progression for sensor development and energy material characterization using signal processing Examines the integration of phase change materials in construction for thermal energy regulation in new buildings Explores the current happenings in technology in conjunction with basic laws and mathematical models Connecting advances in engineering materials with the use of smart techniques including artificial intelligence, machine learning and Internet of Things (IoT) in a single volume, this text will be especially useful for graduate students, academic researchers and professionals in the fields of electrical engineering, electronics engineering, materials science, mechanical engineering and computer science.

Artificial Intelligence, Internet of Things, and Society 5.0 (Studies in Computational Intelligence #1113)

by Azzam Hannoon Abdullah Mahmood

This book unlike any other previous book provides a platform for scholars and researchers to present the latest insights and findings on the application of artificial intelligence and other sustainable technologies for a human-centric society. It brings together technology with society with special attention given to AI and IoT-related intricacies for a digital economy. It covers a variety of research topics including block ciphers, network marketing for sustainability entrepreneurship and AI, AI and stock trading decisions, digital transformation, knowledge management, chatbot engineering, cybersecurity, and smart metering system. The book is a comprehensive reference work for scholars, academics, policymakers, students, and professionals presenting an overall understanding of AI, its present and future trends, and presents a discourse on important policies and strategies on inclusivity, diversity, bias, accountability, security, metaverse applications of AI, and other technologies such as IoT.

Artificial Intelligence, Machine Learning and Blockchain in Quantum Satellite, Drone and Network

by Thiruselvan Subramanian Archana Dhyani Adarsh Kumar Sukhpal Singh Gill

Quantum computing is a field in which advanced technologies like quantum communication, artificial intelligence and machine learning can be used to secure and speed up connectivity using quantum computers, quantum drones or quantum satellites. This book serve as a foundation for researchers and scientists in this field. Future technologies, such as quantum drone delivery systems, quicker internet and climate change mitigation, will need quantum information processing and quantum computation. This book deeply explores the importance of quantum computing in real-time applications. It may be used as a reference book for students in higher education, including undergraduate and graduate students, as well as researchers. Key features: Provides a clear insight into the Internet of Drones for academicians, postdoc fellows, research scholars, graduate and postgraduate students, industry fellows and software engineers Useful to professionals who seek information about the Internet of Drones, including experts in quantum computing and physics and post-quantum cryptography, as well as data scientists and data analysts Covers quantum computing and security for Unmanned Aerial Vehicles (UAV) or drones which are widely useful for applications such as military, government, and non-government systems Explores futuristic aspects of the Intenet of Drones to improve everyday living for ordinary people

Artificial Intelligence, Machine Learning and Blockchain in Quantum Satellite, Drone and Network

by Thiruselvan Subramanian Archana Dhyani Adarsh Kumar Sukhpal Singh Gill

Quantum computing is a field in which advanced technologies like quantum communication, artificial intelligence and machine learning can be used to secure and speed up connectivity using quantum computers, quantum drones or quantum satellites. This book serve as a foundation for researchers and scientists in this field. Future technologies, such as quantum drone delivery systems, quicker internet and climate change mitigation, will need quantum information processing and quantum computation. This book deeply explores the importance of quantum computing in real-time applications. It may be used as a reference book for students in higher education, including undergraduate and graduate students, as well as researchers. Key features: Provides a clear insight into the Internet of Drones for academicians, postdoc fellows, research scholars, graduate and postgraduate students, industry fellows and software engineers Useful to professionals who seek information about the Internet of Drones, including experts in quantum computing and physics and post-quantum cryptography, as well as data scientists and data analysts Covers quantum computing and security for Unmanned Aerial Vehicles (UAV) or drones which are widely useful for applications such as military, government, and non-government systems Explores futuristic aspects of the Intenet of Drones to improve everyday living for ordinary people

Artificial Intelligence, Machine Learning, and Data Science Technologies: Future Impact and Well-Being for Society 5.0 (Demystifying Technologies for Computational Excellence)

by Neeraj Mohan

This book provides a comprehensive, conceptual, and detailed overview of the wide range of applications of Artificial Intelligence, Machine Learning, and Data Science and how these technologies have an impact on various domains such as healthcare, business, industry, security, and how all countries around the world are feeling this impact. The book aims at low-cost solutions which could be implemented even in developing countries. It highlights the significant impact these technologies have on various industries and on us as humans. It provides a virtual picture of forthcoming better human life shadowed by the new technologies and their applications and discusses the impact Data Science has on business applications. The book will also include an overview of the different AI applications and their correlation between each other. The audience is graduate and postgraduate students, researchers, academicians, institutions, and professionals who are interested in exploring key technologies like Artificial Intelligence, Machine Learning, and Data Science.

Artificial Intelligence, Machine Learning, and Data Science Technologies: Future Impact and Well-Being for Society 5.0 (Demystifying Technologies for Computational Excellence)

by Neeraj Mohan Ruchi Singla Priyanka Kaushal Seifedine Kadry

This book provides a comprehensive, conceptual, and detailed overview of the wide range of applications of Artificial Intelligence, Machine Learning, and Data Science and how these technologies have an impact on various domains such as healthcare, business, industry, security, and how all countries around the world are feeling this impact. The book aims at low-cost solutions which could be implemented even in developing countries. It highlights the significant impact these technologies have on various industries and on us as humans. It provides a virtual picture of forthcoming better human life shadowed by the new technologies and their applications and discusses the impact Data Science has on business applications. The book will also include an overview of the different AI applications and their correlation between each other. The audience is graduate and postgraduate students, researchers, academicians, institutions, and professionals who are interested in exploring key technologies like Artificial Intelligence, Machine Learning, and Data Science.

Artificial Intelligence, Management and Trust (Routledge Studies in Trust Research)

by Mariusz So 322 Tysik Magda Gaw 322 Owska Bartlomiej Sniezynski Artur Gunia

The main challenge related to the development of artificial intelligence (AI) is to establish harmonious human-AI relations, necessary for the proper use of its potential. AI will eventually transform many businesses and industries; its pace of development is influenced by the lack of trust on the part of society. AI autonomous decision-making is still in its infancy, but use cases are evolving at an ever-faster pace. Over time, AI will be responsible for making more decisions, and those decisions will be of greater importance. The monograph aims to comprehensively describe AI technology in three aspects: organizational, psychological, and technological in the context of the increasingly bold use of this technology in management. Recognizing the differences between trust in people and AI agents and identifying the key psychological factors that determine the development of trust in AI is crucial for the development of modern Industry 4.0 organizations. So far, little is known about trust in human-AI relationships and almost nothing about the psychological mechanisms involved. The monograph will contribute to a better understanding of how trust is built between people and AI agents, what makes AI agents trustworthy, and how their morality is assessed. It will therefore be of interest to researchers, academics, practitioners, and advanced students with an interest in trust research, management of technology and innovation, and organizational management.

Artificial Intelligence, Management and Trust (Routledge Studies in Trust Research)

by Mariusz Sołtysik Magda Gawłowska Bartlomiej Sniezynski Artur Gunia

The main challenge related to the development of artificial intelligence (AI) is to establish harmonious human-AI relations, necessary for the proper use of its potential. AI will eventually transform many businesses and industries; its pace of development is influenced by the lack of trust on the part of society. AI autonomous decision-making is still in its infancy, but use cases are evolving at an ever-faster pace. Over time, AI will be responsible for making more decisions, and those decisions will be of greater importance. The monograph aims to comprehensively describe AI technology in three aspects: organizational, psychological, and technological in the context of the increasingly bold use of this technology in management. Recognizing the differences between trust in people and AI agents and identifying the key psychological factors that determine the development of trust in AI is crucial for the development of modern Industry 4.0 organizations. So far, little is known about trust in human-AI relationships and almost nothing about the psychological mechanisms involved. The monograph will contribute to a better understanding of how trust is built between people and AI agents, what makes AI agents trustworthy, and how their morality is assessed. It will therefore be of interest to researchers, academics, practitioners, and advanced students with an interest in trust research, management of technology and innovation, and organizational management.

Artificial Intelligence of Things (AIoT): New Standards, Technologies and Communication Systems

by Kashif Naseer Qureshi Thomas Newe

This book is devoted to the new standards, technologies, and communication systems for Artificial Intelligence of Things (AIoT) networks. Smart and intelligent communication networks have gained significant attention due to the combination of AI and IoT networks to improve human and machine interfaces and enhance data processing and services. AIoT networks involve the collection of data from several devices and sensor nodes in the environment. AI can enhance these networks to make them faster, greener, smarter, and safer. Computer vision, language processing, and speech recognition are some examples of AIoT networks.Due to a large number of devices in today’s world, efficient and intelligent data processing is essential for problem-solving and decision-making. AI multiplies the value of these networks and promotes intelligence and learning capabilities, especially in homes, offices, and cities. However, several challenges have been observed in deploying AIoT networks, such as scalability, complexity, accuracy, and robustness. In addition, these networks are integrated with cloud, 5G networks, and blockchain methods for service provision. Many different solutions have been proposed to address issues related to machine and deep learning methods, ontology-based approaches, genetic algorithms, and fuzzy-based systems.This book aims to contribute to the state of the art and present current standards, technologies, and approaches for AIoT networks. This book focuses on existing solutions in AIoT network technologies, applications, services, standards, architectures, and security provisions. This book also introduces some new architectures and models for AIoT networks.

Artificial Intelligence of Things (AIoT): New Standards, Technologies and Communication Systems


This book is devoted to the new standards, technologies, and communication systems for Artificial Intelligence of Things (AIoT) networks. Smart and intelligent communication networks have gained significant attention due to the combination of AI and IoT networks to improve human and machine interfaces and enhance data processing and services. AIoT networks involve the collection of data from several devices and sensor nodes in the environment. AI can enhance these networks to make them faster, greener, smarter, and safer. Computer vision, language processing, and speech recognition are some examples of AIoT networks.Due to a large number of devices in today’s world, efficient and intelligent data processing is essential for problem-solving and decision-making. AI multiplies the value of these networks and promotes intelligence and learning capabilities, especially in homes, offices, and cities. However, several challenges have been observed in deploying AIoT networks, such as scalability, complexity, accuracy, and robustness. In addition, these networks are integrated with cloud, 5G networks, and blockchain methods for service provision. Many different solutions have been proposed to address issues related to machine and deep learning methods, ontology-based approaches, genetic algorithms, and fuzzy-based systems.This book aims to contribute to the state of the art and present current standards, technologies, and approaches for AIoT networks. This book focuses on existing solutions in AIoT network technologies, applications, services, standards, architectures, and security provisions. This book also introduces some new architectures and models for AIoT networks.

Artificial Intelligence of Things for Achieving Sustainable Development Goals (Lecture Notes on Data Engineering and Communications Technologies #192)

by Sanjay Misra Kerstin Siakas Georgios Lampropoulos

This book covers various topics and trends regarding Artificial Intelligence (AI), Internet of Things (IoT), and their applications in society, industry, and environment for achieving Sustainable Development Goals (SDGs) suggested by the United Nations. Additionally, it discusses their advancements and fusion as well as the realization of Artificial Intelligence of Things (AIoT). The book aims to provide an overview and recent research into the fusion, integration, advancements, and impact of these technologies in the context of SDGs achievement. The topics include the applications of AI, IoT, big data, AI-based and IoT-based cloud computing, machine learning and deep learning techniques, and blockchain among others for achieving SDGs. It also presents findings and discussions on potential application domains, addresses open issues and challenges, offers solutions, and provides suggestions for future research for achieving SDGs. The chapters are clustered, according to particular SDGsor areas of focus, into: i) the realization of AIoT for SDGs, ii) the role of AIoT in achieving society and wellbeing-related SDGs, iii) the fulfillment of industrial sectors, infrastructure, and economy-related SDGs through AIoT, and iv) the use of AIoT to aid natural resources and environment-related SDGs. The book assists researchers, practitioners, professionals, and academicians of various scientific fields in exploring and better understanding these state-of-the-art technologies, their advancements, impact, future potentials and benefits, and their role in successfully achieving SDGs.The book:· Offers an in-depth overview of AIoT for achieving SDGs.· Presents the fusion of AI and IoT for bringing a significant change in everyday life and fulfilling SDGs.· Highlights innovative solutions and results of AIoT integration in several domains for achieving SDGs.· Showcases the influence of AIoT on promoting and improving sustainability in the context of SDGs.· Discusses the issues, benefits, solutions, and impact of AIoT in society, industry, and environment for achieving SDGs.

Artificial Intelligence of Things for Smart Green Energy Management (Studies in Systems, Decision and Control #446)

by Sarah El Himer Mariyam Ouaissa Abdulrahman A. A. Emhemed Mariya Ouaissa Zakaria Boulouard

This book is intended to assist in the development of smart and efficient green energy solutions. It introduces energy systems, power generation, and power demands which able to minimise generation costs, power loss or environmental effects. It proposes cutting-edge solutions and approaches based on recent technologies such as intelligent renewable energy systems (wind and solar). These solutions, applied to different sectors, can provide a solid basis for meeting the needs of both developed and developing countries. The book provides a collection of contributions including new techniques, methods, algorithms, practical solutions and models based on applying artificial intelligence and the Internet of things into green energy management systems. It provides a comprehensive reference for researchers, scholars and industry in the field of green energy and computational intelligence.

Artificial Intelligence on Medical Data: Proceedings of International Symposium, ISCMM 2021 (Lecture Notes in Computational Vision and Biomechanics #37)

by Mousumi Gupta Sujata Ghatak Amlan Gupta Abir Lal Mukherjee

This book includes high-quality papers presented at the Second International Symposium on Computer Vision and Machine Intelligence in Medical Image Analysis (ISCMM 2021), organized by Computer Applications Department, SMIT in collaboration with Department of Pathology, SMIMS, Sikkim, India, and funded by Indian Council of Medical Research, during 11 – 12 November 2021. It discusses common research problems and challenges in medical image analysis, such as deep learning methods. It also discusses how these theories can be applied to a broad range of application areas, including lung and chest x-ray, breast CAD, microscopy and pathology. The studies included mainly focus on the detection of events from biomedical signals.

Artificial Intelligence over Infrared Images for Medical Applications: Second MICCAI Workshop, AIIIMA 2023, Held in Conjunction with MICCAI 2023, Vancouver, BC, Canada, October 2, 2023, Proceedings (Lecture Notes in Computer Science #14298)

by Siva Teja Kakileti Geetha Manjunath Robert G. Schwartz Alejandro F. Frangi

This book constitutes the refereed proceedings of the ​Second Workshop on Artificial Intelligence over Infrared Images for Medical Applications, AIIIMA 2023 held in conjunction with MICCAI 2023, held in Vancouver, BC, Canada, on October 2, 2023. The 10 full papers presented in this book were carefully peer reviewed and selected from 15 submissions. The second workshop on AIIIMA, similarily to the first, aimes to create a forum to discuss the specific sub-topic of AI over Infrared Images for Medical Applications at MICCAI and promote this novel area of research, that has the potential to hugely impact our society, among the research community.

Artificial Intelligence over Infrared Images for Medical Applications and Medical Image Assisted Biomarker Discovery: First MICCAI Workshop, AIIIMA 2022, and First MICCAI Workshop, MIABID 2022, Held in Conjunction with MICCAI 2022, Singapore, September 18 and 22, 2022, Proceedings (Lecture Notes in Computer Science #13602)

by Alejandro F. Frangi Robert G. Schwartz Geetha Manjunath Michal Rosen-Zvi Maria Gabrani Christopher Weight Siva Teja Kakileti Nathaniel Braman Pau-Choo Chung Vekataraman Jagadish

This book constitutes the refereed proceedings of the ​First Workshop on Artificial Intelligence over Infrared Images for Medical Applications, AIIIMA 2022, and the First Workshop on Medical Image Assisted Biomarker Discovery, MIABID 2022, both held in conjunction with MICCAI 2022, Singapore, during September 18 and 22, 2022.For MIABID 2022, 7 papers from 10 submissions were accepted for publication. This workshop created a forum to discuss this specific sub-topic at MICCAI and promote this novel area of research among the research community that has the potential to hugely impact our society.For AIIIMA 2022, 10 papers from 15 submissions were accepted for publication. The first workshop on AIIIMA aimed to create a forum to discuss this specific sub-topic of AI over Infrared Images for Medical Applications at MICCAI and promote this novel area of research that has the potential to hugely impact our society, among the research community.

Artificial Intelligence Perspective for Smart Cities

by Vahap Tecim Sezer Bozkus Kahyaoglu

The concept of a "smart city" is used widely in general; however, it is hard to explain because of the complexity and multidimensionality of this notion. However, the essential qualification for being a smart city is to achieve "sustainable social, environmental, and economic development" and boost the living standards of society based on Information and Communication Technology (ICT) and Artificial intelligence (AI). AI in smart cities has become an important aspect for cities that face great challenges to make smart decisions for social well-being, particularly cybersecurity and corporate sustainability. In this context, we aim to contribute literature with a value-added approach where various AI applications of smart cities are discussed from a different perspective. First, we start by discussing the conceptual design, modeling, and determination of components for the sustainability of a smart city structure. Since smart cities operate on spatial-based data, it is important to design, operate, and manage smart city elements using Geographical Information Systems (GIS) technologies. Second, we define the structure, type, unit, and functionality of the layers to be placed on the GIS to achieve best practices based on Industry 4.0 components. Transportation is one of the key indicators of smart cities, so it is critical to make transportation in smart cities accessible for different disabled groups by using AI technologies. Third, we demonstrate what kinds of technologies should be used for which disabled groups in different transportation vehicles with specific examples. Finally, we create a discussion platform for processes and sub-processes such as waste management, emergency management, risk management, and data management for establishing smart cities including the financial and ethical aspects.

Artificial Intelligence Perspective for Smart Cities

by Vahap Tecim Sezer Bozkus Kahyaoglu

The concept of a "smart city" is used widely in general; however, it is hard to explain because of the complexity and multidimensionality of this notion. However, the essential qualification for being a smart city is to achieve "sustainable social, environmental, and economic development" and boost the living standards of society based on Information and Communication Technology (ICT) and Artificial intelligence (AI). AI in smart cities has become an important aspect for cities that face great challenges to make smart decisions for social well-being, particularly cybersecurity and corporate sustainability. In this context, we aim to contribute literature with a value-added approach where various AI applications of smart cities are discussed from a different perspective. First, we start by discussing the conceptual design, modeling, and determination of components for the sustainability of a smart city structure. Since smart cities operate on spatial-based data, it is important to design, operate, and manage smart city elements using Geographical Information Systems (GIS) technologies. Second, we define the structure, type, unit, and functionality of the layers to be placed on the GIS to achieve best practices based on Industry 4.0 components. Transportation is one of the key indicators of smart cities, so it is critical to make transportation in smart cities accessible for different disabled groups by using AI technologies. Third, we demonstrate what kinds of technologies should be used for which disabled groups in different transportation vehicles with specific examples. Finally, we create a discussion platform for processes and sub-processes such as waste management, emergency management, risk management, and data management for establishing smart cities including the financial and ethical aspects.

Artificial Intelligence: A Real Opportunity in the Food Industry (Studies in Computational Intelligence #1000)

by Aboul Ella Hassanien Mona Soliman

This book emphasizes the latest developments and achievements in AI and related technologies with a special focus on food quality. The book describes the applications, and conceptualization of ideas, and critical surveys covering most aspects of AI for food quality.

Artificial Intelligence Research: First Southern African Conference for AI Research, SACAIR 2020, Muldersdrift, South Africa, February 22-26, 2021, Proceedings (Communications in Computer and Information Science #1342)

by Aurona Gerber

This book constitutes the refereed proceedings of the First Southern African Conference on Artificial Intelligence Research, SACAIR 2020, held in Muldersdrift, South Africa, in February 2021. Due to the COVID-19 pandemic the SACAIR 2020 has been postponed to February 2021. The 19 papers presented were thoroughly reviewed and selected from 53 submissions. They are organized on the topical sections on ​AI for ethics and society; AI in information systems, AI for development and social good; applications of AI; knowledge representation and reasoning; machine learning theory.

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