This book focuses primarily on both technical and business aspects needed to select, design, develop and deploy control application (or product) successfully for multiple components in building systems. Designing and deploying a control application require multiple steps such as sensing, system dynamics modelling, algorithms, and testing. This may involve choosing an appropriate methodology and technique at multiple stages during the development process. Understanding the pros and cons of such techniques, most importantly being aware of practically possible approaches in the entire ecosystem, is critical in choosing the best framework and system application for different parts of building systems. Providing a wide overview of the state-of art in controls and building systems, providing guidance on developing an end-to-end system in relation to business fundamentals (distribution channels, stakeholders, marketing, supply-chain and financial management), the book is ideal for fourth-year control/mechanical/electrical engineering undergraduates, graduate students, and practitioners including business leaders concerned with smart building technology.

This book focuses primarily on both technical and business aspects needed to select, design, develop and deploy control application (or product) successfully for multiple components in building systems. Designing and deploying a control application require multiple steps such as sensing, system dynamics modelling, algorithms, and testing. This may involve choosing an appropriate methodology and technique at multiple stages during the development process. Understanding the pros and cons of such techniques, most importantly being aware of practically possible approaches in the entire ecosystem, is critical in choosing the best framework and system application for different parts of building systems. Providing a wide overview of the state-of art in controls and building systems, providing guidance on developing an end-to-end system in relation to business fundamentals (distribution channels, stakeholders, marketing, supply-chain and financial management), the book is ideal for fourth-year control/mechanical/electrical engineering undergraduates, graduate students, and practitioners including business leaders concerned with smart building technology.

This book provides an authoritative resource on the topic of intelligent robots, artificial intelligence and the ethical implications of these revolutionary innovations. It examines the moral and ethical problems that arise in relation to the development, design and use of intelligent robots, which are capable of autonomous or semi-autonomous decision-making. These problems might relate, for example, to medical robots, driverless cars, intelligent military drones, pedagogical robots, police robots, legal robots and many others. The main question addressed in this book is how we can understand, explain and apply the concept of ethics in relation to intelligent robots and artificial intelligence. In each chapter, the author examines a different aspect of this question. The author also questions how we can ensure that intelligent robots are of service to humans and under what conditions intelligent robots could become more ethical than humans. The book employs an original approach to examining this cutting-edge research question, combining different research areas, and offers a wealth of practical relevance and real-world examples, illustrated through vivid case studies. With its jargon free approach and a dedicated chapter on relevant concepts at the end, this book is also accessible to readers without prior knowledge on intelligent robots and the Fourth Industrial Revolution. By providing a general account of this debate, and of the consequences of the innovations resulting from these trends, the book serves as an important contribution to the discussion and will find a natural readership among scholars and students of the innovation economy and those concerned with the ethical considerations arising in the wake of the Fourth Industrial Revolution

This book aims to bring together leading academic scientists, researchers, and research scholars to exchange and share their experiences and research results on all aspects of Artificial Intelligence. The book provides a premier interdisciplinary platform to present practical challenges and adopted solutions. The book addresses the complete functional framework workflow in Artificial Intelligence technology. It explores the basic and high-level concepts and can serve as a manual for the industry for beginners and the more advanced. It covers intelligent and automated systems and its implications to the real-world, and offers data acquisition and case studies related to data-intensive technologies in AI-based applications. The book will be of interest to researchers, professionals, scientists, professors, students of computer science engineering, electronics and communications, as well as information technology.

This book offers an in-depth academic discourse on the convergence of AI, digital platforms, and popular culture, in order to understand the ways in which the platform and cultural industries have reshaped and developed AI-driven algorithmic cultural production and consumption. At a time of fundamental change for the media and cultural industries, driven by the emergence of big data, algorithms, and AI, the book examines how media ecology and popular culture are evolving to serve the needs of both media and cultural industries and consumers. The analysis documents global governments' rapid development of AI-relevant policies and identifies key policy issues; examines the ways in which cultural industries firms utilize AI and algorithms to advance the new forms of cultural production and distribution; investigates change in cultural consumption by analyzing the ways in which AI, algorithms, and digital platforms reshape people's consumption habits; and examines whether governments and corporations have advanced reliable public and corporate policies and ethical codes to secure socio-economic equality. Offering a unique perspective on this timely and vital issue, this book will be of interest to scholars and students in media studies, communication studies, anthropology, globalization studies, sociology, cultural studies, Asian studies, and science and technology studies (STS).

The Home in the Digital Age is a set of multidisciplinary studies exploring the impact of digital technologies in the home, with a shift of emphasis from technology to the people living and using this in their homes. The book covers a wide variety of topics on the design, introduction and use of digital technologies in the home, combining the technological dimension with the cognitive, emotional, cultural and symbolic dimensions of the objects that incorporate digital technologies and project them onto people's lives. It offers a coherent approach, that of the home, which gives unity to the discussion. Scholars of the home, the house and the family will find here the connection with the problems derived from the use of domestic robots and connected devices. Students of artificial intelligence, machine learning, robotics, big data and other branches of digital technologies will find ideas and arguments to apply their disciplines to the home and participate fruitfully in forums where digital technologies are built and negotiated in the home. Experts from various disciplines psychologists and sociologists; philosophers, epistemologists and ethicists; economists; engineers, architects, urban planners and designers and so on and also those interested in developing policies for the home and family will find this book contains well-founded and useful ideas to focus their work.

Blockchain technology is poised to revolutionize more than just payment and crypto-currency. Many vertical industries will be reshaped by the new trusted data models enabled and inspired by the blockchain - healthcare is no exception. In fact, healthcare may hold the greatest opportunities for meaningful use of the technology. Early pioneers have explored some of the first use cases for medical payments, electronic health records, HIPAA/data privacy, drug counterfeiting, and credentialing of healthcare professionals. We have only begun to scratch the surface in how to automate the complexities of today's healthcare systems and design new systems which focus on trust, transparency and the alignment of incentives. Metcalf, Bass, Dhillon, and Hooper have curated a collection of examples based on the fundamentals of blockchain that build upon the early successes and examples that point to the future. After a brief introduction to bitcoin, blockchain and the protocols available, a getting-started guide is presented specific to health and healthcare. The authors discuss the complexities and possibilities of smart contracts and some of the early consortia that are exploring the possibilities. Examples and use cases are found throughout the book, with specific sections that cover the more sophisticated and far-reaching examples which have the potential to scale at the industry-level. In addition, a discussion of integrating blockchain technology into other advanced healthcare trends and IT systems - such as telemedicine, artificial intelligence, machine learning, the Internet of Things, value-based payments , patient engagement solutions, big data solutions, medical tourism, and precision medicine/genetic therapies among many others are presented. The final section provides a glimpse into the future using blockchain technology and examples of research projects that are still in labs across the globe. The appendices may prove particularly useful for additional details on how to get started, including resources and organizations specifically focusing on blockchain and distributed ledger solutions.

In this short introduction, David J. Gunkel examines the shifting world of artificial intelligence, mapping it onto everyday twenty-first century life and probing the consequences of this ever-growing industry and movement. The book investigates the significance and consequences of the robot invasion in an effort to map the increasingly complicated social terrain of the twenty-first century. Whether we recognize it as such or not, we are in the midst of a robot invasion. What matters most in the face of this machine incursion is not resistance, but how we decide to make sense of and respond to the social opportunities and challenges that autonomous machines make available. How to Survive a Robot Invasion is a fascinating and accessible volume for students and researchers of new media, philosophy of technology, and their many related fields. It aims both to assist readers' efforts to understand a changing world and to provide readers with the critical insight necessary for grappling with our science fiction-like future.

This book covers three main types of agricultural systems: the use of robotics, drones (unmanned aerial vehicles), and satellite-guided precision farming methods. Some of these are well refined and are currently in use, while others are in need of refinement and are yet to become popular. The book provides a valuable source of information on this developing field for those involved with agriculture and farming and agricultural engineering. The book is also applicable as a textbook for students and a reference for faculty.

Handbook of Artificial Intelligence in Biomedical Engineering focuses on recent AI technologies and applications that provide some very promising solutions and enhanced technology in the biomedical field. Recent advancements in computational techniques, such as machine learning, Internet of Things (IoT), and big data, accelerate the deployment of biomedical devices in various healthcare applications. This volume explores how artificial intelligence (AI) can be applied to these expert systems by mimicking the human expert's knowledge in order to predict and monitor the health status in real time. The accuracy of the AI systems is drastically increasing by using machine learning, digitized medical data acquisition, wireless medical data communication, and computing infrastructure AI approaches, helping to solve complex issues in the biomedical industry and playing a vital role in future healthcare applications. The volume takes a multidisciplinary perspective of employing these new applications in biomedical engineering, exploring the combination of engineering principles with biological knowledge that contributes to the development of revolutionary and life-saving concepts.

Originally published in 1992, this title reviews seven major subareas in artificial intelligence at that time: knowledge acquisition; logic programming and representation; machine learning; natural language; vision; the design of an AI programming environment; and medicine, a major application area of AI. This volume was an attempt primarily to inform fellow AI workers of recent European work in AI. It was hoped that researchers in 'sister' disciplines, such as computer science and linguistics would gain a deeper understanding of the assumptions, techniques and tools of contemporary AI.

What is AI? A dominant view describes it as the quest "to solve intelligence" - a solution supposedly to be found in the secret logic of the mind or in the deep physiology of the brain, such as in its complex neural networks. The Eye of the Master argues, to the contrary, that the inner code of AI is shaped not by the imitation of biological intelligence, but the intelligence of labour and social relations, as it is found in Babbage's "calculating engines" of the industrial age as well as in the recent algorithms for image recognition and surveillance. The idea that AI may one day become autonomous (or "sentient", as someone thought of Google's LaMDA) is pure fantasy. Computer algorithms have always imitated the form of social relations and the organisation of labour in their own inner structure and their purpose remains blind automation. The Eye of the Master urges a new literacy on AI for scientists, journalists and new generations of activists, who should recognise that the "mystery" of AI is just the automation of labour at the highest degree, not intelligence per se.

Land use and water resources are two major environmental issues which necessitate conservation, management, and maintenance practices through the use of various engineering techniques. Water scientists and environmental engineers must address the various aspects of flood control, soil conservation, rainfall-runoff processes, and groundwater hydrology. Watershed Management and Applications of AI provides the necessary principles of hydrology to provide practical strategies useful for the planning, design, and management of watersheds. The book also synthesizes novel new approaches, such as hydrological applications of machine learning using neural networks to predict runoff and using artificial intelligence for the prediction of groundwater fluctuations. Features: Presents hydrologic analysis and design along with soil conservation practices through proper watershed management techniques Provides analysis of land erosion and sediment transport in watersheds from small to large scale Includes estimations for runoff using different methodologies with systematic approaches for each Discusses water harvesting and development of water yield catchments This book will be a valuable resource for students in hydrology courses, environmental consultants, water resource engineers, and researchers in related water science and engineering fields.

This book covers techniques that can be used to analyze data from IoT sensors and addresses questions regarding the performance of an IoT system. It strikes a balance between practice and theory so one can learn how to apply these tools in practice with a good understanding of their inner workings. This is an introductory book for readers who have no familiarity with these techniques. The techniques presented in An Introduction to IoT Analytics come from the areas of machine learning, statistics, and operations research. Machine learning techniques are described that can be used to analyze IoT data generated from sensors for clustering, classification, and regression. The statistical techniques described can be used to carry out regression and forecasting of IoT sensor data and dimensionality reduction of data sets. Operations research is concerned with the performance of an IoT system by constructing a model of the system under study and then carrying out a what-if analysis. The book also describes simulation techniques. Key Features IoT analytics is not just machine learning but also involves other tools, such as forecasting and simulation techniques. Many diagrams and examples are given throughout the book to fully explain the material presented. Each chapter concludes with a project designed to help readers better understand the techniques described. The material in this book has been class tested over several semesters. Practice exercises are included with solutions provided online at www.routledge.com/9780367686314 Harry G. Perros is a Professor of Computer Science at North Carolina State University, an Alumni Distinguished Graduate Professor, and an IEEE Fellow. He has published extensively in the area of performance modeling of computer and communication systems.

The human brain has some capabilities that the brains of other animals lack. It is to these distinctive capabilities that our species owes its dominant position. Other animals have stronger muscles or sharper claws, but we have cleverer brains. If machine brains one day come to surpass human brains in general intelligence, then this new superintelligence could become very powerful. As the fate of the gorillas now depends more on us humans than on the gorillas themselves, so the fate of our species then would come to depend on the actions of the machine superintelligence. But we have one advantage: we get to make the first move. Will it be possible to construct a seed AI or otherwise to engineer initial conditions so as to make an intelligence explosion survivable? How could one achieve a controlled detonation? To get closer to an answer to this question, we must make our way through a fascinating landscape of topics and considerations. Read the book and learn about oracles, genies, singletons; about boxing methods, tripwires, and mind crime; about humanity's cosmic endowment and differential technological development; indirect normativity, instrumental convergence, whole brain emulation and technology couplings; Malthusian economics and dystopian evolution; artificial intelligence, and biological cognitive enhancement, and collective intelligence. This profoundly ambitious and original book picks its way carefully through a vast tract of forbiddingly difficult intellectual terrain. Yet the writing is so lucid that it somehow makes it all seem easy. After an utterly engrossing journey that takes us to the frontiers of thinking about the human condition and the future of intelligent life, we find in Nick Bostrom's work nothing less than a reconceptualization of the essential task of our time.

This book covers techniques that can be used to analyze data from IoT sensors and addresses questions regarding the performance of an IoT system. It strikes a balance between practice and theory so one can learn how to apply these tools in practice with a good understanding of their inner workings. This is an introductory book for readers who have no familiarity with these techniques. The techniques presented in An Introduction to IoT Analytics come from the areas of machine learning, statistics, and operations research. Machine learning techniques are described that can be used to analyze IoT data generated from sensors for clustering, classification, and regression. The statistical techniques described can be used to carry out regression and forecasting of IoT sensor data and dimensionality reduction of data sets. Operations research is concerned with the performance of an IoT system by constructing a model of the system under study and then carrying out a what-if analysis. The book also describes simulation techniques. Key Features IoT analytics is not just machine learning but also involves other tools, such as forecasting and simulation techniques. Many diagrams and examples are given throughout the book to fully explain the material presented. Each chapter concludes with a project designed to help readers better understand the techniques described. The material in this book has been class tested over several semesters. Practice exercises are included with solutions provided online at www.routledge.com/9780367686314 Harry G. Perros is a Professor of Computer Science at North Carolina State University, an Alumni Distinguished Graduate Professor, and an IEEE Fellow. He has published extensively in the area of performance modeling of computer and communication systems.

The COVID-19 pandemic has hit the global at a colossal scale. With worldwide reported cases of 5.34 million it has led to severe impact on humanity. Being a highly contagious disease, it has given global health services their most severe challenge. Various countries are fighting to minimize the losses due to the outbreak, however a common trait is enforcing lockdown, which has become the main defence mechanism. Researchers are working around the clock to find a breakthrough in the diagnostics and treatment of the pandemic. AI technology is useful for fast drug development and treatment. In the starting phase of COVID-19 pandemic, the medical fraternity in China diagnosed the virus using computed tomography (CT) and X-ray images due to the limitation of testing kits. Deep learning neural network model have also been used for COVID-19 diagnosis. AI assisted intelligent humanoid robots can be used to reduce the human contact and spread of COVID-19. In Italy robots have been used for measuring blood pressure, oxygen saturation and temperature of patients. Robots have also found applications in disinfecting and sterilizing of public places, COVID-19 testing, food and medicine delivery as well as entertaining patients in hospitals and quarantine centers, thereby reducing the workload of doctors and nurses. Prediction of the spread of virus and providing the guidelines or prevention measures is another AI application in COVID-19. Kaggle and GitHub are the two websites where the real-time data of COVID-19 is aggregated. This includes confirmed cases, active cases, cured cases and deaths in each country. This data set can be used for predicting the active cases across different regions of the world so that appropriate amount of health infrastructure can be made available to these places.

'A fascinating hybrid. Part freewheeling history of the rise of the modern autonomous vehicle, part intimate memoir from an insider who was on the front lines for much of that history, Autonomy will more than bring readers up to speed on one of today's most closely watched technologies' Brian Merchant, author of The One Device From the ultimate insider - a former General Motors executive and current advisor to the Google Self-Driving Car project - comes the definitive story of the race between Google, Tesla and Uber to create the driverless car. We stand on the brink of a technological revolution. In the near future, most of us will not own automobiles, but will travel instead in driverless electric vehicles summoned at the touch of an app. We will be liberated from driving, so that the time we spend in cars can be put to more productive use. We will prevent more than 90 percent of car crashes, provide freedom of mobility to the elderly and disabled and decrease our dependence on fossil fuels. Autonomy tells the story of the maverick engineers and computer experts who triggered the revolution. Lawrence Burns - long-time adviser to the Google self-driving car project (now Waymo) and former corporate vice president of research, development and planning at General Motors - provides the perfectly timed history of how we arrived at this point, in a character-driven and vivid account of the unlikely thinkers who accomplished what billion-dollar automakers never dared. Beginning at a 2004 off-road robot race across the Mojave Desert with a million-dollar purse and continuing up to the current stampede to develop driverless technology, Autonomy is a page-turning chronicle of the past, a diagnosis of the present and a prediction of the future - the ultimate guide to understanding the driverless car and to navigating the revolution it has sparked.

Provides for the first time a comprehensive, state-of-the-art overview of the different types of healthcare robots and the advances that AI brings them. Provides, in an easy and accessible way, essential basic information about the autonomy levels of surgery robots, which is novel. As such, could be very valuable to a broad community that ranges from legal scholars, ethicists, developers, policymakers, students, or non-specialists curious about the topic.

Considering the overall situation of the current pandemic and pertinent recommendations, this book focuses on the use of augmented reality (AR) applications for preventing COVID-19 outbreaks along with techniques, tools, and platforms to achieve social distancing.and sanitization. COVID-19 Public Health Measures: An Augmented Reality Perspective contains theoretical and practical knowledge of AR and remedies on how to cope with the pandemic, including multiple use cases along with a set of recommendations. This book illustrates application building using open-source software with an interactive interface to aid impaired users. The initial part of this book emphasizes the basic knowledge of AR, technology, devices, and rest of the relevant theories. This book is aimed at researchers, students of AR, technical healthcare professionals, and practitioners. Key Features: * Consists of an extensive introduction to the terminologies and components of AR * Provides in-depth knowledge of various tools and techniques used in AR * Introduces various platforms and software development kits (SDKs) such as Unity Engine, Unreal Engine, and Vuforia * Gives a step-by-step guide for the development of an AR app * Describes how AR can be used specifically by impaired users not only in the situation of current pandemic but also in normal situations thus simplifying day-to-day activities

The bioscience of immunology has given us a better understanding of human health and disease. Artificial intelligence (AI) has elevated that understanding and its applications in immunology to new levels. Together, AI for immunology is an advancing horizon in health care, disease diagnosis, and prevention. From the simple cold to the most advanced autoimmune disorders and now pandemics, AI for immunology is unlocking the causes and cures. Key features: A highly accessible and wide-ranging short introduction to AI for immunology Includes a chapter on COVID-19 and pandemics Includes scientific and clinical considerations, as well as immune and autoimmune diseases

This volume focuses on natural language processing, artificial intelligence, and allied areas. Natural language processing enables communication between people and computers and automatic translation to facilitate easy interaction with others around the world. This book discusses theoretical work and advanced applications, approaches, and techniques for computational models of information and how it is presented by language (artificial, human, or natural) in other ways. It looks at intelligent natural language processing and related models of thought, mental states, reasoning, and other cognitive processes. It explores the difficult problems and challenges related to partiality, underspecification, and context-dependency, which are signature features of information in nature and natural languages. Key features: Addresses the functional frameworks and workflow that are trending in NLP and AI Looks at the latest technologies and the major challenges, issues, and advances in NLP and AI Explores an intelligent field monitoring and automated system through AI with NLP and its implications for the real world Discusses data acquisition and presents a real-time case study with illustrations related to data-intensive technologies in AI and NLP.

This multi-contributed handbook focuses on the latest workings of IoT (internet of Things) and Big Data. As the resources are limited, it's the endeavor of the authors to support and bring the information into one resource. The book is divided into 4 sections that covers IoT and technologies, the future of Big Data, algorithms, and case studies showing IoT and Big Data in various fields such as health care, manufacturing and automation. Features Focuses on the latest workings of IoT and Big Data Discusses the emerging role of technologies and the fast-growing market of Big Data Covers the movement toward automation with hardware, software, and sensors, and trying to save on energy resources Offers the latest technology on IoT Presents the future horizons on Big Data

This book aims to provide the latest research developments and results in the domain of AI techniques for smart cyber ecosystems. It presents a holistic insight into AI-enabled theoretic approaches and methodology in IoT networking, security analytics using AI tools and network automation, which ultimately enable intelligent cyber space. This book will be a valuable resource for students, researchers, engineers and policy makers working in various areas related to cybersecurity and privacy for Smart Cities. This book includes chapters titled "An Overview of the Artificial Intelligence Evolution and Its Fundamental Concepts, and Their Relationship with IoT Security", "Smart City: Evolution and Fundamental Concepts", "Advances in AI-Based Security for Internet of Things in Wireless Virtualization Environment", "A Conceptual Model for Optimal Resource Sharing of Networked Microgrids Focusing Uncertainty: Paving Path to Eco-friendly Smart Cities", "A Novel Framework for a Cyber Secure Smart City", "Contemplating Security Challenges and Threats for Smart Cities", "Self-Monitoring Obfuscated IoT Network", "Introduction to Side Channel Attacks and Investigation of Power Analysis and Fault Injection Attack Techniques", "Collaborative Digital Forensic Investigations Model for Law Enforcement: Oman as a Case Study", "Understanding Security Requirements and Challenges in the Industrial Internet of Things: A Review", "5G Security and the Internet of Things", "The Problem of Deepfake Videos and How to Counteract Them in Smart Cities", "The Rise of Ransomware Aided by Vulnerable IoT Devices", "Security Issues in Self-Driving Cars within Smart Cities", and "Trust-Aware Crowd Associated Network-Based Approach for Optimal Waste Management in Smart Cities". This book provides state-of-the-art research results and discusses current issues, challenges, solutions and recent trends related to security and organization within IoT and Smart Cities. We expect this book to be of significant importance not only to researchers and practitioners in academia, government agencies and industries, but also for policy makers and system managers. We anticipate this book to be a valuable resource for all those working in this new and exciting area, and a "must have" for all university libraries.

The Future of Digital Data, Heritage and Curation critiques digital cultural heritage concepts and their application to data, developing new theories, curatorial practices and a more-than-human museology for a contemporary and future world. Presenting a diverse range of case examples from around the globe, Cameron offers a critical and philosophical reflection on the ways in which digital cultural heritage is currently framed as societal data worth passing on to future generations in two distinct forms: digitally born and digitizations. Demonstrating that most perceptions of digital cultural heritage are distinctly western in nature, the book also examines the complicity of such heritage in climate change, and environmental destruction and injustice. Going further still, the book theorizes the future of digital data, heritage, curation and the notion of the human in the context of the profusion of new types of societal data and production processes driven by the intensification of data economies and through the emergence of new technologies. In so doing, the book makes a case for the development of new types of heritage that comprise AI, automated systems, biological entities, infrastructures, minerals and chemicals - all of which have their own forms of agency, intelligence and cognition. The Future of Digital Data, Heritage and Curation is essential reading for academics and students engaged in the study of museums, archives, libraries, galleries, archaeology, cultural heritage management, information management, curatorial studies and digital humanities.