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Artificial Intelligence for Improved Patient Outcomes: Principles for Moving Forward with Rigorous Science
by Daniel W. ByrneArtificial Intelligence for Improved Patient Outcomes provides new, relevant, and practical information on what AI can do in healthcare and how to assess whether AI is improving health outcomes. With clear insights and a balanced approach, this innovative book offers a one-stop guide on how to design and lead pragmatic real-world AI studies that yield rigorous scientific evidence—all in a manner that is safe and ethical. Daniel Byrne, Director of Artificial Intelligence Research at AVAIL (the Advanced Vanderbilt Artificial Intelligence Laboratory) and author of landmark pragmatic studies published in leading medical journals, shares four decades of experience as a biostatistician and AI researcher. Building on his first book, Publishing Your Medical Research, the author gives the reader the competitive advantage in creating reproducible AI research that will be accepted in prestigious high-impact medical journals.
Artificial Intelligence for Industries of the Future: Beyond Facebook, Amazon, Microsoft and Google (Future of Business and Finance)
by Mayank KejriwalThis book provides a brief synthesis of the known implementations, opportunities and challenges at the intersection of artificial intelligence (AI) and modern industry beyond the big-four companies that traditionally consume and produce such advanced technology: Facebook, Amazon, Microsoft and Google. With this information, the author also makes some reasonable claims about the role of AI in future industries. The book draws on a broad range of material, including reports from consulting firms, published surveys, academic papers and books, and expert knowledge available to the author due to numerous collaborations in academia and industry on AI. It is rigorous rather than speculative, drawing on known findings and expert summaries, where available. This provides industry leaders and other interested stakeholders with an accessible review of contemporary perspectives on AI’s forward-looking role in industry as well as a clarifying guide on the major issues that companies are likely to face as they commence on this exciting path.Examines the likely role of AI in industries of the future, both known and unknownPresents use-cases of AI currently being explored across Big Tech, multi-national corporations and start-upsExplores the regulation of AI and its potential impacts on the workforce
Artificial Intelligence for Information Management: A Healthcare Perspective (Studies in Big Data #88)
by K. G. Srinivasa Siddesh G. M. S. R. Mani SekharThis book discusses the advancements in artificial intelligent techniques used in the well-being of human healthcare. It details the techniques used in collection, storage and analysis of data and their usage in different healthcare solutions. It also discusses the techniques of predictive analysis in early diagnosis of critical diseases. The edited book is divided into four parts – part A discusses introduction to artificial intelligence and machine learning in healthcare; part B highlights different analytical techniques used in healthcare; part C provides various security and privacy mechanisms used in healthcare; and finally, part D exemplifies different tools used in visualization and data analytics.
Artificial Intelligence for Innovative Healthcare Informatics
by Shabir Ahmad Parah Mamoon Rashid Vijayakumar VaradarajanThere are several popular books published in Healthcare Computational Informatics like Computational Bioengineering and Bioinformatics (2020), Springer; Health Informatics (2017), Springer; Health Informatics Vision: From Data via Information to Knowledge (2019), IOS Press; Data Analytics in Biomedical Engineering and Healthcare (2020), Elsevier. However, in all these mentioned books, the challenges in Biomedical Imaging are solved in one dimension by use of any specific technology like Image Processing, Machine Learning or Computer Aided Systems. In this book, the book it has been attempted to bring all technologies related to computational analytics together and apply them on Biomedical Imaging.
Artificial Intelligence for Intelligent Systems: Fundamentals, Challenges, and Applications (Intelligent Data-Driven Systems and Artificial Intelligence)
by Mariya Ouaissa Mariyam Ouaissa Inam Ullah Khan Muhammad Fayaz Rehmat UllahThe aim of this book is to highlight the most promising lines of research, using new enabling technologies and methods based on AI/ML techniques to solve issues and challenges related to intelligent and computing systems. Intelligent computing easily collects data using smart technological applications like IoT-based wireless networks, digital healthcare, transportation, blockchain, 5.0 industry and deep learning for better decision making. AI enabled networks will be integrated in smart cities' concept for interconnectivity. Wireless networks will play an important role. The digital era of computational intelligence will change the dynamics and lifestyle of human beings. Future networks will be introduced with the help of AI technology to implement cognition in real-world applications. Cyber threats are dangerous to encode information from network. Therefore, AI-Intrusion detection systems need to be designed for identification of unwanted data traffic.This book: Provides a better understanding of artificial intelligence-based applications for future smart cities Presents a detailed understanding of artificial intelligence tools for intelligent technologies Showcases intelligent computing technologies in obtaining optimal solutions using artificial intelligence Discusses energy-efficient routing protocols using artificial intelligence for Flying ad-hoc networks (FANETs) Covers machine learning-based Intrusion detection system (IDS) for smart grid It is primarily written for senior undergraduate, graduate students, and academic researchers in the fields of electrical engineering, electronics and communication engineering, and computer engineering.
Artificial Intelligence for Internet of Things: AI for IoT and Health Systems (Engineering Cyber-Physical Systems and Critical Infrastructures #8)
by Alireza Souri Salaheddine BendakIoTHIC-2023 is a multidisciplinary, peer-reviewed international conference on Internet of Things (IoT) and healthcare systems with Artificial Intelligence (AI) techniques such as data mining, machine learning, image processing, and meta-heuristic algorithms. The AI-based techniques are applied on many fields of healthcare systems, including predicting and detecting diseases in hospitals, clinics, smart health monitoring systems, surgery, medical services, and etc.
Artificial Intelligence for Internet of Things: Design Principle, Modernization, and Techniques (Smart Engineering Systems)
by N Thillaiarasu Suman Lata Tripathi V DhinakaranThe text comprehensively discusses the essentials of the Internet of Things (IoT), machine learning algorithms, industrial and medical IoT, robotics, data analytics tools, and technologies for smart cities. It further covers fundamental concepts, advanced tools, and techniques, along with the concept of energy-efficient systems. It also highlights software and hardware interfacing into the IoT platforms and systems for better understanding. It will serve as an ideal reference text for senior undergraduate, graduate students, and academic researchers in the fields of electrical engineering, electronics and communication engineering, and computer engineering. Features: Covers cognitive Internet of Things and emerging network, IoT in robotics, smart cities, and health care Discusses major issues in the field of the IoTsuch as scalable and secure issues, energy-efficient, and actuator devices Highlights the importance of industrial and medical IoT Illustrates applications of the IoT in robotics, smart grid, and smart cities Presents real-time examples for better understanding The text comprehensively discusses design principles, modernization techniques, advanced developments in artificial intelligence.This will be helpful for senior undergraduates, graduate students, and academic researchers in diverseengineering fields including electrical, electronics and communication, and computer science.
Artificial Intelligence for Intrusion Detection Systems
by Mayank Swarnkar Shyam Singh RajputThis book is associated with the cybersecurity issues and provides a wide view of the novel cyber attacks and the defense mechanisms, especially AI-based Intrusion Detection Systems (IDS).Features: • A systematic overview of the state-of-the-art IDS• Proper explanation of novel cyber attacks which are much different from classical cyber attacks• Proper and in-depth discussion of AI in the field of cybersecurity• Introduction to design and architecture of novel AI-based IDS with a trans- parent view of real-time implementations• Covers a wide variety of AI-based cyber defense mechanisms, especially in the field of network-based attacks, IoT-based attacks, multimedia attacks, and blockchain attacks. This book serves as a reference book for scientific investigators who need to analyze IDS, as well as researchers developing methodologies in this field. It may also beused as a textbook for a graduate-level course on information security.
Artificial Intelligence for IoT Cookbook: Over 70 recipes for building AI solutions for smart homes, industrial IoT, and smart cities
by Michael RoshakImplement machine learning and deep learning techniques to perform predictive analytics on real-time IoT dataKey FeaturesDiscover quick solutions to common problems that you'll face while building smart IoT applicationsImplement advanced techniques such as computer vision, NLP, and embedded machine learningBuild, maintain, and deploy machine learning systems to extract key insights from IoT dataBook DescriptionArtificial intelligence (AI) is rapidly finding practical applications across a wide variety of industry verticals, and the Internet of Things (IoT) is one of them. Developers are looking for ways to make IoT devices smarter and to make users' lives easier. With this AI cookbook, you'll be able to implement smart analytics using IoT data to gain insights, predict outcomes, and make informed decisions, along with covering advanced AI techniques that facilitate analytics and learning in various IoT applications. Using a recipe-based approach, the book will take you through essential processes such as data collection, data analysis, modeling, statistics and monitoring, and deployment. You'll use real-life datasets from smart homes, industrial IoT, and smart devices to train and evaluate simple to complex models and make predictions using trained models. Later chapters will take you through the key challenges faced while implementing machine learning, deep learning, and other AI techniques, such as natural language processing (NLP), computer vision, and embedded machine learning for building smart IoT systems. In addition to this, you'll learn how to deploy models and improve their performance with ease. By the end of this book, you'll be able to package and deploy end-to-end AI apps and apply best practice solutions to common IoT problems.What you will learnExplore various AI techniques to build smart IoT solutions from scratchUse machine learning and deep learning techniques to build smart voice recognition and facial detection systemsGain insights into IoT data using algorithms and implement them in projectsPerform anomaly detection for time series data and other types of IoT dataImplement embedded systems learning techniques for machine learning on small devicesApply pre-trained machine learning models to an edge deviceDeploy machine learning models to web apps and mobile using TensorFlow.js and JavaWho this book is forIf you're an IoT practitioner looking to incorporate AI techniques to build smart IoT solutions without having to trawl through a lot of AI theory, this AI IoT book is for you. Data scientists and AI developers who want to build IoT-focused AI solutions will also find this book useful. Knowledge of the Python programming language and basic IoT concepts is required to grasp the concepts covered in this artificial intelligence book more effectively.
Artificial Intelligence for Knowledge Management: Third IFIP WG 12.6 International Workshop, AI4KM 2015, Held at IJCAI 2015, Buenos Aires, Argentina, July 25-31, 2015, Revised Selected Papers (IFIP Advances in Information and Communication Technology #497)
by Eunika Mercier-Laurent and Danielle BoulangerThis book features a selection of papers presented at the Third IFIP WG 12.6 International Workshop on Artificial Intelligence for Knowledge Management, AI4KM 2015, held in Buenos Aires, Argentina, in July 2015, in the framework of the International Joint Conference on Artificial Intelligence, IJCAI 2015. The 9 revised and extended papers were carefully reviewed and selected from 15 submissions. They present new research and innovative aspects in the field of knowledge management such as knowledge models, KM and Web, knowledge capturing and learning, and KM and AI intersections.
Artificial Intelligence for Knowledge Management: 6th IFIP WG 12.6 International Workshop, AI4KM 2018, Held at IJCAI 2018, Stockholm, Sweden, July 15, 2018, Revised and Extended Selected Papers (IFIP Advances in Information and Communication Technology #588)
by Eunika Mercier-LaurentThis book features a selection of extended papers presented at the 6th IFIP WG 12.6 International Workshop on Artificial Intelligence for Knowledge Management, AI4KM 2018, held in Stockholm, Sweden, in July 2018, in the framework of the International Joint Conference on Artificial Intelligence, IJCAI 2018.The 11 revised and extended papers were carefully reviewed and selected for inclusion in this volume. They present new research and innovative aspects in the field of knowledge management such as machine learning, knowledge models, KM and Web, knowledge capturing and learning, and KM and AI intersections.
Artificial Intelligence for Knowledge Management: 4th IFIP WG 12.6 International Workshop, AI4KM 2016, Held at IJCAI 2016, New York, NY, USA, July 9, 2016, Revised Selected Papers (IFIP Advances in Information and Communication Technology #518)
by Eunika Mercier-Laurent Danielle BoulangerThis book features a selection of papers presented at the 4th IFIP WG 12.6 International Workshop on Artificial Intelligence for Knowledge Management, AI4KM 2016, held in New York, USA, in July 2016, in the framework of the International Joint Conference on Artificial Intelligence, IJCAI 2016. The 9 revised and extended papers were carefully reviewed and selected from 16 submissions. They present new research and innovative aspects in the field of knowledge management such as machine learning, knowledge models, KM and Web, knowledge capturing and learning, and KM and AI intersections.
Artificial Intelligence for Knowledge Management: 5th IFIP WG 12.6 International Workshop, AI4KM 2017, Held at IJCAI 2017, Melbourne, VIC, Australia, August 20, 2017, Revised Selected Papers (IFIP Advances in Information and Communication Technology #571)
by Eunika Mercier-Laurent Danielle BoulangerThis book features a selection of extended papers presented at the 5th IFIP WG 12.6 International Workshop on Artificial Intelligence for Knowledge Management, AI4KM 2017, held in Melbourne, VIC, Australia, in August 2017, in the framework of the International Joint Conference on Artificial Intelligence, IJCAI 2017. The 11 revised and extended papers were carefully reviewed and selected for inclusion in this volume. They present new research and innovative aspects in the field of knowledge management such as machine learning, knowledge models, KM and Web, knowledge capturing and learning, and KM and AI intersections.
Artificial Intelligence for Knowledge Management: 8th IFIP WG 12.6 International Workshop, AI4KM 2021, Held at IJCAI 2020, Yokohama, Japan, January 7–8, 2021, Revised Selected Papers (IFIP Advances in Information and Communication Technology #614)
by Eunika Mercier-Laurent M. Özgür Kayalica Mieczyslaw Lech OwocThis book features a selection of extended papers presented at the 8th IFIP WG 12.6 International Workshop on Artificial Intelligence for Knowledge Management, AI4KM 2021, held in Yokohama, Japan, in January 2021, in the framework of the International Joint Conference on Artificial Intelligence, IJCAI 2020.*The 14 revised and extended papers presented together with an invited talk were carefully reviewed and selected for inclusion in this volume. They present new research and innovative aspects in the field of knowledge management and discuss methodological, technical and organizational aspects of artificial intelligence used for knowledge management.*The workshop was held virtually.
Artificial Intelligence for Knowledge Management: Second IFIP WG 12.6 International Workshop, AI4KM 2014, Warsaw, Poland, September 7-10, 2014, Revised Selected Papers (IFIP Advances in Information and Communication Technology #469)
by Eunika Mercier-Laurent Mieczysław Lech Owoc Danielle BoulangerThis book features a selection of papers presented at the Second IFIP WG 12. 6 International Workshop on Artificial Intelligence for Knowledge Management, AI4KM 2014, held in Wroclaw, Poland, in September 2014, in the framework of the Federated Conferences on Computer Science and Information Systems, FedCSIS 2014. The 9 revised and extended papers and one invited paper were carefully reviewed and selected for inclusion in this volume. They present new research and innovative aspects in the field of knowledge management and are organized in the following topical sections: tools and methods for knowledge acquisition; models and functioning of knowledge management; techniques of artificial intelligence supporting knowlege management; and components of knowledge flow.
Artificial Intelligence for Knowledge Management: 7th IFIP WG 12.6 International Workshop, AI4KM 2019, Held at IJCAI 2019, Macao, China, August 11, 2019, Revised Selected Papers (IFIP Advances in Information and Communication Technology #599)
by Mieczysław Lech Owoc Maciej PondelThis book features a selection of extended papers presented at the 7th IFIP WG 12.6 International Workshop on Artificial Intelligence for Knowledge Management, AI4KM 2019, held in Macao, China, in August 2019, in the framework of the International Joint Conference on Artificial Intelligence, IJCAI 2019.The 8 revised and extended papers were carefully reviewed and selected for inclusion in this volume. They present new research and innovative aspects in the field of knowledge management such as machine learning, knowledge models, KM and Web, knowledge capturing and learning, and KM and AI intersections.
Artificial Intelligence for Knowledge Management, Energy, and Sustainability: 9th IFIP WG 12.6 and 1st IFIP WG 12.11 International Workshop, AI4KMES 2021, Held at IJCAI 2021, Montreal, QC, Canada, August 19–20, 2021, Revised Selected Papers (IFIP Advances in Information and Communication Technology #637)
by Eunika Mercier-Laurent Gülgün KayakutluThis book features a selection of extended papers presented at the 9th IFIP WG 12.6 International Workshop on Artificial Intelligence for Knowledge Management, AI4KM 2021, and the 1st International Workshop on Energy and Sustainability, AIES 2021, named AI4KMES 2021 and held in conjunction with IJCAI 2021 in August 2021. The conference was planned to take place in Montréal, Canada, but changed to an online event due to the COVID-19 pandemic. The 15 papers included in this book were carefully reviewed and selected from 17 submissions. They deal with knowledge management and sustainability challenges, focusing on methodological, technical and organizational aspects of AI used for facing related complex problems. This year's topic was AI for Knowledge Management, Energy and Sustainable Future.
Artificial Intelligence for Knowledge Management, Energy and Sustainability: 10th IFIP International Workshop on Artificial Intelligence for Knowledge Management, AI4KMES 2023, Krakow, Poland, September 30–October 1, 2023, Revised Selected Papers (IFIP Advances in Information and Communication Technology #693)
by Eunika Mercier-Laurent Abdul Wahid Gülgün Kayakutlu Mieczyslaw Lech Owoc Karl MasonThis volume IFIP AICT 693 constitutes the refereed proceedings of the 10th IFIP International Workshop on Artificial Intelligence for Knowledge Management, AI4KMES 2023, from September 30th – October 1st, 2023, held in Krakow, Poland. The 15 full papers presented together with 2 short papers were carefully reviewed and selected from 49 submissions. The accepted papers covered a large scope of topics related to sustainability in various contexts such as smart cities, agriculture, energy and gas production and distribution, industry, management and biodiversity.
Artificial Intelligence for Learning: How to use AI to Support Employee Development
by Donald ClarkArtificial intelligence is creating huge opportunities for workplace learning and employee development. However, it can be difficult for L&D professionals to assess what difference AI can make in their organization and where it is best implemented. Artificial Intelligence for Learning is the practical guide L&D practitioners need to understand what AI is and how to use it to improve all aspects of learning in the workplace. It includes specific guidance on how AI can provide content curation and personalization to improve learner engagement, how it can be implemented to improve the efficiency of evaluation, assessment and reporting and how chatbots can provide learner support to a global workforce.Artificial Intelligence for Learning debunks the myths and cuts through the hype around AI allowing L&D practitioners to feel confident in their ability to critically assess where artificial intelligence can make a measurable difference and where it is worth investing in. There is also critical discussion of how AI is an aid to learning and development, not a replacement as well as how it can be used to boost the effectiveness of workplace learning, reduce drop off rates in online learning and improve ROI. With real-world examples from companies who have effectively implemented AI and seen the benefits as well as case studies from organizations including Netflix, British Airways and the NHS, this book is essential reading for all L&D practitioners needing to understand AI and what it means in practice.
Artificial Intelligence for Learning: Using AI and Generative AI to Support Learner Development
by Donald ClarkWith Artificial Intelligence (AI) creating huge opportunities for learning and employee development, how can learning professionals best implement the use of AI into their environment?Artificial Intelligence for Learning is the essential guide for learning professionals who want to understand how to use AI to improve all aspects of learning in organizations. This new edition debunks the myths and misconceptions around AI, discusses the learning theory behind generative AI and gives strategic and practical advice on how AI can be used.This book also includes specific guidance on how AI can provide learning support, chatbot functionality and content, as well as ideas on ethics and personalization. This book is necessary reading for all learning practitioners needing to understand AI and what it means in practice.
Artificial Intelligence for Marketing: Practical Applications
by Jim SterneA straightforward, non-technical guide to the next major marketing tool Artificial Intelligence for Marketing presents a tightly-focused introduction to machine learning, written specifically for marketing professionals. This book will not teach you to be a data scientist—but it does explain how Artificial Intelligence and Machine Learning will revolutionize your company's marketing strategy, and teach you how to use it most effectively. <p><p> Data and analytics have become table stakes in modern marketing, but the field is ever-evolving with data scientists continually developing new algorithms—where does that leave you? How can marketers use the latest data science developments to their advantage? This book walks you through the "need-to-know" aspects of Artificial Intelligence, including natural language processing, speech recognition, and the power of Machine Learning to show you how to make the most of this technology in a practical, tactical way. Simple illustrations clarify complex concepts, and case studies show how real-world companies are taking the next leap forward. <p> Marketing and data science are two fast-moving, turbulent spheres that often intersect; that intersection is where marketing professionals pick up the tools and methods to move their company forward. Artificial Intelligence and Machine Learning provide a data-driven basis for more robust and intensely-targeted marketing strategies—and companies that effectively utilize these latest tools will reap the benefit in the marketplace. Artificial Intelligence for Marketing provides a nontechnical crash course to help you stay ahead of the curve.
Artificial Intelligence for Marketing Management (Routledge Studies in Marketing)
by Park Thaichon Sara QuachArtificial intelligence (AI) has driven businesses to adopt new business practices rapidly, enhance product development and services, has helped to power AI-based market intelligence and customer insights, and improve customer relationship management. This timely book addresses the use of AI in marketing. This book also explores the dark side of AI in marketing management and discusses ethics and transparency of automated decision-making in AI applications, data privacy, cyber security issues, and biases in various facets of marketing. Emerging applications of AI such as DeepFakes which use deep learning technology could increase risks of manipulation and deception. Hence, apart from leveraging AI capabilities and advantages, the book cautions the need for prevention strategies to deal with potential issues that could arise from the adoption of AI in marketing management. This book will provide practical insights into the role of AI in marketing management. It will be a useful reference for those researching marketing and marketing professionals.
Artificial Intelligence for Materials Science (Springer Series in Materials Science #312)
by Yuan Cheng Tian Wang Gang ZhangMachine learning methods have lowered the cost of exploring new structures of unknown compounds, and can be used to predict reasonable expectations and subsequently validated by experimental results. As new insights and several elaborative tools have been developed for materials science and engineering in recent years, it is an appropriate time to present a book covering recent progress in this field.Searchable and interactive databases can promote research on emerging materials. Recently, databases containing a large number of high-quality materials properties for new advanced materials discovery have been developed. These approaches are set to make a significant impact on human life and, with numerous commercial developments emerging, will become a major academic topic in the coming years. This authoritative and comprehensive book will be of interest to both existing researchers in this field as well as others in the materials science community who wish to take advantage of these powerful techniques. The book offers a global spread of authors, from USA, Canada, UK, Japan, France, Russia, China and Singapore, who are all world recognized experts in their separate areas. With content relevant to both academic and commercial points of view, and offering an accessible overview of recent progress and potential future directions, the book will interest graduate students, postgraduate researchers, and consultants and industrial engineers.
Artificial Intelligence for Military Applications with Blockchain
by Gururaj H L Gowtham M Ajay A V Pramod H BIn an era where advanced technology plays a critical role in maintaining national security, Artificial Intelligence for Military Applications with Blockchain investigates how combining AI and blockchain could transform military operations. This comprehensive guide offers creative answers for contemporary military problems while addressing the most important defense-related concerns, from data security to decision-making.It explores constrained networking middleware for defense applications, guaranteeing smooth communication under critical circumstances. This book starts with an in-depth examination of blockchain’s potential to improve document management across defense departments, then moves to a detailed discussion of security and privacy in military applications. The integration of AI and blockchain in military context is then the main topic of discussion, along with its advantages, disadvantages, and real-time applications.The potential of blockchain and AI to protect data and streamline operations is also explored, providing readers with insights into the military and healthcare sectors. This book offers a thorough examination of the military’s current and future use of AI, as well as a breakdown of cybersecurity issues and how blockchain technology is being used to improve military cybersecurity. A dedicated chapter examines the ways in which blockchain technology is being used by computational intelligence to transform the defense environment.Key features: Examines privacy and security issues in military blockchain applications Investigates military operations using constrained networking middleware Discusses integrating AI and blockchain technology for military applications Includes case studies of blockchain and AI uses in the military and healthcare Thoroughly examines cybersecurity issues and how blockchain technology can help This book is essential for military personnel, defense academics, and cybersecurity specialists interested in the use of AI and blockchain for defense. It presents real-world examples and case studies together with an outlook on how these technologies will influence future military operations.
Artificial Intelligence for Multimedia Information Processing: Tools and Applications
by Xavier Savarimuthu Sivakannan Subramani Alex Noel Joseph RajAdvances in artificial intelligence (AI), widespread mobile devices, internet technologies, multimedia data sources, and information processing have led to the emergence of multimedia processing. Multimedia processing is the application of signal processing tools to multimedia data—text, audio, images, and video—to allow the interpretation of these data, particularly in urban and smart city environments. This book discusses the new standards of multimedia and information processing from several technological perspectives, including analytics empowered by AI, streaming on the intelligent edge, multimedia edge caching and AI, services for edge AI, and hardware and devices for multimedia on edge intelligence.FEATURES Covers a wide spectrum of enabling technologies for AI and machine learning for multimedia and information processing Includes many applications using AI, from robotics and driverless cars to environmental, human health, and remote sensing Presents an overview of the fundamentals of AI and multimedia processing: imaging, signal, and speech Explains new models and architectures for multimedia streaming, services, and caching for AI Discusses the emerging paradigms of the deployment of hardware and devices for multimedia on edge intelligence Gives recommendations for future research in multimedia and AI This book is written for engineers and graduate students in image and signal processing, information processing, environmental engineering, medical and public health, etc., who are interested in machine learning, deep learning, and multimedia processing.