Electronic device usage has increased considerably in the past two decades. System configurations are continuously requiring upgrades; existing systems often become obsolete in a matter of 2–3 years. Green computing is the complete effective management of design, manufacture, use, and disposal, involving as little environmental impact as possible. This book intends to explore new and innovative ways of conserving energy, effective e-waste management, and renewable energy sources to harness and nurture a sustainable eco-friendly environment. This book: • Highlights innovative principles and practices using effective e-waste management and disposal • Explores artificial intelligence based sustainable models • Discovers alternative sources and mechanisms for minimizing environmental hazards • Highlights successful case studies in alternative sources of energy • Presents solid illustrations, mathematical equations, as well as practical in-the-field applications • Serves as a one-stop reference guide to stakeholders in the domain of green computing, e-waste management, renewable energy alternatives, green transformational leadership including theory concepts, practice and case studies • Explores cutting-edge technologies like internet of energy and artificial intelligence, especially the role of machine learning and deep learning in renewable energy and creating a sustainable ecosystem • Explores futuristic trends in renewable energy This book aims to address the increasing interest in reducing the environmental impact of energy as well as its further development and will act as a useful reference for engineers, architects, and technicians interested in and working with energy systems; scientists and engineers in developing countries; industries, manufacturers, inventors, universities, researchers, and interested consultants to explain the foundation to advanced concepts and research trends in the domain of renewable energy and sustainable computing. The content coverage of the book is organized in the form of 11 clear and thorough chapters providing a comprehensive view of the global renewable energy scenario, as well as how science and technology can play a vital role in renewable energy.

This book provides basic knowledge of the programming and interfacing of devices with IoT modem and programming. The aim is to explain the basic steps to understand the IoT and its application in agriculture field. It will serve be a reference book for postgraduate and undergraduate Engineering students. Students from Electronics, Electrical, Mechatronics, Robotics, Mechanical, Computer science can use the book for their projects and research. This book is based entirely on the practical experience of the authors while undergoing projects with the students and industries. This book is co-published with NIPA. Taylor and Francis does not sell or distribute its print and electronic editions in India, Pakistan, Nepal, Bhutan, Bangladesh and Sri Lanka.

Unique selling point: * Brings together insights on various fields, and how IoT and AI combined can help bring about sustainable living Core audience: * Researchers and academics - worldwide applicability Place in the market: * Gives a more comprehensive overview of the potential applications of IoT and AI for sustainability than other books on the market

An Economist Best Book of 2021 Artificial Intelligence is going to war. Intelligent military systems are already reshaping conflict-from the chaos of battle, with pilotless drones and robot tanks, to the headquarters far from the action, where generals and politicians use technology to weigh up what to do. AI changes how we fight, and even how likely it is that we will. Warbots will be faster, more agile and more deadly than today's crewed weapons. New tactics are already emerging, but much deeper thinking is needed. When will an intelligent machine escalate, and how might you deter it? Can robots predict the future? And what happens to the 'art of war' as machines become creative? An international campaign against 'killer robots' hopes to ban AI from conflict. But the genie is out-autonomous weapons are too useful for states to outlaw. Still, crafting sensible rules for our warbots is possible. This fascinating book shows how it might be done.

This carefully designed, multi-authored textbook covers a broad range of theoretical issues in cognitive science, psychology, and neuroscience. With accessible language, a uniform structure, and many pedagogical features, Mind, Cognition, and Neuroscience: A Philosophical Introdution is the best high-level overview of this area for an interdisciplinary readership of students. Written specifically for this volume by experts in their fields who are also experienced teachers, the book's thirty chapters are organized into the following parts: I. Background Knowledge II. Classical Debates III. Consciousness IV. Crossing Boundaries Each chapter starts with relevant key words and definitions and a chapter overview, then presents historical coverage of the topic, explains and analyzes contemporary debates, and ends with a sketch of cutting edge research. A list of suggested readings and helpful discussion topics conclude each chapter. This uniform, student-friendly design makes it possible to teach a cohort of both philosophy and interdisciplinary students without assuming prior understanding of philosophical concepts, cognitive science, or neuroscience. Key Features: Synthesizes the now decades-long explosion of scientifically informed philosophical research in the study of mind. Expands on the offerings of other textbooks by including chapters on language, concepts and non-conceptual content, and animal cognition. Offers the same structure in each chapter, moving the reader through an overview, historical coverage, contemporary debates, and finally cutting-edge research. Packed with pedagogical features, like defined Key Terms, Suggested Readings, and Discussion Questions for each chapter, as well as a General Glossary. Provides readers with clear, chapter-long introductions to Cognitive Neuroscience, Molecular and Cellular Cognition, Experimental Methods in Cognitive Neuroscience, Philosophy of Mind, Philosophy of Science, Metaphysical Issues, and Epistemic Issues.

Co-location pattern mining detects sets of features frequently located in close proximity to each other. This book focuses on data mining for co-location pattern, a valid method for identifying patterns from all types of data and applying them in business intelligence and analytics. It explains the fundamentals of co-location pattern mining, co-location decision tree, and maximal instance co-location pattern mining along with an in-depth overview of data mining, machine learning, and statistics. This arrangement of chapters helps readers understand the methods of co-location pattern mining step-by-step and their applications in pavement management, image classification, geospatial buffer analysis, etc.

This book is a unique and note-worthy enquiry into the implications of algorithmic knowledge for human subjectivity Eran Fisher provides timely insight on a relevant field of research, i.e., how algorithms impact our society This book will make a timely contribution to the social study of algorithms and will prove especially valuable for scholars working at the intersections of media and communication studies, internet studies, information studies, the sociology of technology, the philosophy of technology, and science and technology studies

Inspired by Roland Barthes's practice of "semioclasm" in Mythologies, this book offers a "technoclasm"; a cultural critique of US narratives, discourses, images, and objects that have transformed the politics of automation into statements of fact about the "rise of the robots". Treating automation as an ensemble of technologies and science fictions, this book foregrounds automation's ideologies, exaggerations, failures, and mystifications of the social value of human labor in order to question accepted and prolific automation mythologies. Jesse Ramirez offers a study of automation that recognizes automation as a technosocial project, that uses the tools of cultural studies and history to investigate the narratives and ideologies that often implicitly frame the automation debate, and that concretely and soberly assesses the technologies that have made the headlines. The case studies featured include some of the most widely cited and celebrated automatic technologies, such as the Baxter industrial robot, the self-driving car, and the Watson AI system. An ideal resource for anyone interested in or studying emerging technology and society, automation, Marxist cultural theory, cultural studies, science fiction studies, and the cultural history of technology.

Discusses the requirements and establishment of a layered protocol architecture. Highlights the importance of cable media in getting a high-speed network. Covers the fundamental concepts and advanced topics such as metro ethernet, and ethernet first mile in the field of networking. Presents important topics such as multiprotocol label switching, cloud computing in networking, and the internet of things. Explores the necessity of software-defined networking and network functions virtualization.

Artificial Intelligence and Learning Futures: Critical Narratives of Technology and Imagination in Higher Education explores the implications of artificial intelligence's adoption in higher education and the challenges to building sustainable instead of dystopic schooling. As AI becomes integral to both pedagogy and profitability in today's colleges and universities, a critical discourse on these systems and algorithms is urgently needed to push back against their potential to enable surveillance, control, and oppression. This book examines the development, risks, and opportunities inherent to AI in education and curriculum design, the problematic ideological assumptions of intelligence and technology, and the evidence base and ethical imagination required to responsibly implement these learning technologies in a way that ensures quality and sustainability. Leaders, administrators, and faculty as well as technologists and designers will find these provocative and accessible ideas profoundly applicable to their research, decision-making, and concerns.

Data Ethics of Power takes a reflective and fresh look at the ethical implications of transforming everyday life and the world through the effortless, costless, and seamless accumulation of extra layers of data. By shedding light on the constant tensions that exist between ethical principles and the interests invested in this socio-technical transformation, the book bridges the theory and practice divide in the study of the power dynamics that underpin these processes of the digitalization of the world. Gry Hasselbalch expertly draws on nearly two decades of experience in the field, and key literature, to advance a better understanding of the challenges faced by big data and AI developers. She provides an innovative ethical framework for studying and governing Big-Data and Artificial Intelligence. Offering both a historical account and a theoretical analysis of power dynamics and their ethical implications, as well as incisive ideas to guide future research and governance practices, the book makes a significant contribution to the establishment of an emerging data and AI ethics discipline. This timely book is a must-read for scholars studying AI, data, and technology ethics. Policymakers in the regulatory, governance, public administration, and management sectors will find the practical proposals for a human-centric approach to big data and AI to be a valuable resource for revising and developing future policies.

'If you think you understand AI and all of the related issues, you don't. By the time you finish this exceptionally lucid and riveting book you will breathe more easily and wisely' - Michael Gazzaniga A leading computer scientist brings human sense to the AI bubble No recent scientific enterprise has been so alluring, terrifying and filled with extravagant promise and frustrating setbacks as artificial intelligence. Writing with clarity and passion, leading AI researcher Melanie Mitchell offers a captivating account of modern-day artificial intelligence. Flavoured with personal stories and a twist of humour, Artificial Intelligence illuminates the workings of machines that mimic human learning, perception, language, creativity and common sense. Weaving together advances in AI with cognitive science and philosophy, Mitchell probes the extent to which today's 'smart' machines can actually think or understand, and whether AI even requires such elusive human qualities at all. Artificial Intelligence: A Guide for Thinking Humans provides readers with an accessible and clear-eyed view of the AI landscape, what the field has actually accomplished, how much further it has to go and what it means for all of our futures.

* The first real AI in project management book on the market published by a respected press * Provides behind-the-scenes insights on what technology providers are planning for project managers * Explores how AI will reinvent project, programme, and portfolio management, allowing project managers to get back to focusing on people

a short and accessible introduction to AI and computational creativity written by a leading expert

Digital forensics plays a crucial role in identifying, analysing, and presenting cyber threats as evidence in a court of law. Artificial intelligence, particularly machine learning and deep learning, enables automation of the digital investigation process. This book provides an in-depth look at the fundamental and advanced methods in digital forensics. It also discusses how machine learning and deep learning algorithms can be used to detect and investigate cybercrimes. This book demonstrates digital forensics and cyber-investigating techniques with real-world applications. It examines hard disk analytics and style architectures, including Master Boot Record and GUID Partition Table as part of the investigative process. It also covers cyberattack analysis in Windows, Linux, and network systems using virtual machines in real-world scenarios. Digital Forensics in the Era of Artificial Intelligence will be helpful for those interested in digital forensics and using machine learning techniques in the investigation of cyberattacks and the detection of evidence in cybercrimes.

i. This book will contain AI, ML, DL, big data and security never before considered ii. Innovative artificial intelligence techniques and algorithms iii. Only emerging from recent research and development, e.g. AI for big data from security perspective, which are not covered in any existing texts iv. Artificial Intelligence for big data and security Applications with advanced features v. Key new finding of machine learning and deep learning for Security Applications

1. Covers latest concepts in intelligent analytics for industry 4.0. 2. Presents the applications of intelligent analytics for various industry 4.0 domains. 3. Covers latest research topics in the field. 4. Written in a comprehensive and simple manner. 5. The text is accompanied by tables and illustrative figures for better understanding of the topic.

a short and accessible introduction on AI and Art written by leading experts

Modern Computational Techniques for Engineering Applications presents recent computational techniques used in the advancement of modern grids with the integration of non-conventional energy sources like wind and solar energy. It covers data analytics tools for smart cities, smart towns, and smart computing for sustainable development. This book- Discusses the importance of renewable energy source applications wind turbines and solar panels for electrical grids. Presents optimization-based computing techniques like fuzzy logic, neural networks, and genetic algorithms that enhance the computational speed. Showcases cloud computing tools and methodologies such as cybersecurity testbeds and data security for better accuracy of data. Covers novel concepts on artificial neural networks, fuzzy systems, machine learning, and artificial intelligence techniques. Highlights application-based case studies including cloud computing, optimization methods, and the Industrial Internet of Things. The book comprehensively introduces modern computational techniques, starting from basic tools to highly advanced procedures, and their applications. It further highlights artificial neural networks, fuzzy systems, machine learning, and artificial intelligence techniques and how they form the basis for algorithms. It presents application-based case studies on cloud computing, optimization methods, blockchain technology, fog and edge computing, and the Industrial Internet of Things. It will be a valuable resource for senior undergraduates, graduate students, and academic researchers in diverse fields, including electrical engineering, electronics and communications engineering, and computer engineering.

'This is the most important conversation of our time, and Tegmark's thought-provoking book will help you join it' Stephen Hawking THE INTERNATIONAL BESTSELLER. DAILY TELEGRAPH AND THE TIMES BOOKS OF THE YEAR SELECTED AS ONE OF BARACK OBAMA'S FAVOURITE BOOKS OF 2018 AI is the future - but what will that future look like? Will superhuman intelligence be our slave, or become our god? Taking us to the heart of the latest thinking about AI, Max Tegmark, the MIT professor whose work has helped mainstream research on how to keep AI beneficial, separates myths from reality, utopias from dystopias, to explore the next phase of our existence. How can we grow our prosperity through automation, without leaving people lacking income or purpose? How can we ensure that future AI systems do what we want without crashing, malfunctioning or getting hacked? Should we fear an arms race in lethal autonomous weapons? Will AI help life flourish as never before, or will machines eventually outsmart us at all tasks, and even, perhaps, replace us altogether? 'This is a rich and visionary book and everyone should read it' The Times

- Curating Social Data - Summarizing Social Data - Analyzing Social Data - Social Data Analytics Applications: Trust, Recommender Systems, Cognitive Analytics

The Science of Deep Learning emerged from courses taught by the author that have provided thousands of students with training and experience for their academic studies, and prepared them for careers in deep learning, machine learning, and artificial intelligence in top companies in industry and academia. The book begins by covering the foundations of deep learning, followed by key deep learning architectures. Subsequent parts on generative models and reinforcement learning may be used as part of a deep learning course or as part of a course on each topic. The book includes state-of-the-art topics such as Transformers, graph neural networks, variational autoencoders, and deep reinforcement learning, with a broad range of applications. The appendices provide equations for computing gradients in backpropagation and optimization, and best practices in scientific writing and reviewing. The text presents an up-to-date guide to the field built upon clear visualizations using a unified notation and equations, lowering the barrier to entry for the reader. The accompanying website provides complementary code and hundreds of exercises with solutions.

The first of its kind, this anthology in the burgeoning field of technology ethics offers students and other interested readers 32 chapters, each written in an accessible and lively manner specifically for this volume. The chapters are conveniently organized into five parts: I. Perspectives on Technology and its Value II. Technology and the Good Life III. Computer and Information Technology IV. Technology and Business V. Biotechnologies and the Ethics of Enhancement A hallmark of the volume is multidisciplinary contributions both (1) in "analytic" and "continental" philosophies and (2) across several hot-button topics of interest to students, including the ethics of autonomous vehicles, psychotherapeutic phone apps, and bio-enhancement of cognition and in sports. The volume editors, both teachers of technology ethics, have compiled a set of original and timely chapters that will advance scholarly debate and stimulate fascinating and lively classroom discussion. Downloadable eResources (available from www.routledge.com/9781032038704) provide a glossary of all relevant terms, sample classroom activities/discussion questions relevant for chapters, and links to Stanford Encyclopedia of Philosophy entries and other relevant online materials. Key Features: Examines the most pivotal ethical questions around our use of technology, equipping readers to better understand technology's promises and perils. Explores throughout a central tension raised by technological progress: maintaining social stability vs. pursuing dynamic social improvements. Provides ample coverage of the pressing issues of free speech and productive online discourse.

The Ethics of Artificial Intelligence in Education identifies and confronts key ethical issues generated over years of AI research, development, and deployment in learning contexts. Adaptive, automated, and data-driven education systems are increasingly being implemented in universities, schools, and corporate training worldwide, but the ethical consequences of engaging with these technologies remain unexplored. Featuring expert perspectives from inside and outside the AIED scholarly community, this book provides AI researchers, learning scientists, educational technologists, and others with questions, frameworks, guidelines, policies, and regulations to ensure the positive impact of artificial intelligence in learning.

The text focuses on the theory, design, and implementation of the Internet of Things (IoT), in a modern communication system. It will be useful to senior undergraduate, graduate students, and researchers in diverse fields domains including electrical engineering, electronics and communications engineering, computer engineering, and information technology. Features: Presents all the necessary information on the Internet of Things in modern computing Examines antenna integration challenges and constraints in the Internet of Things devices Discusses advanced Internet of Things networks and advanced controllers required for modern architecture Explores security and privacy challenges for the Internet of Things-based health care system Covers implementation of Internet of Things security protocols such as MQTT, Advanced Message Queuing Protocol, XMPP, and DSS The text addresses the issues and challenges in implementing communication and security protocols for IoT in modern computing. It further highlights the applications of IoT in diverse areas including remote health monitoring, remote monitoring of vehicle data and environmental characteristics, industry 4.0, 5G communications, and Next-gen IoT networks. The text presents case studies on IoT in modern digital computing. It will serve as an ideal reference text for senior undergraduate, graduate students, and academic researchers in diverse fields domains including electrical engineering, electronics and communications engineering, computer engineering, and information technology.