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Picture a world where autonomous systems operate continuously and intelligently, utilizing real-time data to make informed decisions. Such systems have the potential to revolutionize agriculture, urban infrastructure, and industrial automation. This transformation, often termed the Internet of Self-Sustaining Systems (IoSS), is a pivotal topic that demands academic attention and exploration. Addressing this critical issue head-on is The Convergence of Self-Sustaining Systems With AI and IoT, which offers an in-depth examination of this transformative convergence. It serves as a guiding light for academic scholars seeking to unravel the vast potential of self-sustaining systems coupled with AI and IoT. Inside its pages, readers will delve into AI-driven autonomous agriculture, eco-friendly transportation solutions, and intelligent energy management. Moreover, the book explores emerging technologies, security concerns, ethical considerations, and governance frameworks. Join us on this intellectual journey and position yourself at the forefront of the AI and IoT revolution that promises a sustainable, autonomous future.
Through a combination of rapid technological advancement and the ongoing digital revolution, the role of Human Resources (HR) in shaping organizational trajectories has seen unprecedented growth. The amalgamation of digital HR technologies and the advent of Industry 5.0 pose both exceptional opportunities and formidable challenges, especially for developing economies grappling with resource constraints and skill gaps. These nations stand at a crossroads, where leveraging digital HR technologies becomes imperative for bolstering their competitive edge in the global arena. The book Convergence of Human Resources Technologies and Industry 5.0 undertakes a comprehensive exploration of the impacts, implementation, and repercussions of digital HR technologies within the framework of Industry 5.0 in developing economies. Bridging the gap between theory and practice, it employs a comprehensive approach encompassing theoretical frameworks, empirical investigations, and practical insights from both academia and industry. By offering tangible takeaways, and approaches, it equips readers to adeptly harness the power of digital HR technologies, enabling organizations to thrive in the era of Industry 5.0. Designed for HR professionals, executives, managers, researchers, policymakers, and students, this book delves into critical topics such as understanding the notion of Industry 5.0 in developing economies, exploring the transformative potential of digital HR technologies, and addressing challenges associated with their implementation.
In today's rapidly evolving educational landscape, traditional teaching methods often fail to equip students with the skills necessary for success in the 21st century. The siloed approach to education, where subjects are taught in isolation, must reflect the interconnected nature of modern challenges. This disconnect between traditional educational models and the needs of the future workforce is a serious concern among educators. They face the challenge of preparing students for professions that still need to be created using tools and technologies that are still emerging. Revolutionizing Curricula Through Computational Thinking, Logic, and Problem Solving offers a transformative solution to this challenge. By advocating for computational thinking as a fundamental skill set applicable across all academic disciplines, the book provides educators with the tools to bridge this gap. It introduces computational thinking not just as a technical skill but as a way of problem-solving and logical reasoning that enhances critical thinking across subjects. Through practical lesson plans, case studies, and strategies, educators can seamlessly integrate computational thinking into their classrooms, preparing students for the complexities of the modern world.
In an increasingly data-centric world, scholars and practitioners grapple with the complexities of harnessing data analytics effectively across various industries. The challenge lies in navigating the rapid evolution of methodologies, identifying emerging trends, and understanding the nuanced applications of data analytics in real-world scenarios. This gap between theory and practice inhibits academic progress. It hampers industry innovation, leaving stakeholders needing help to leverage data to its full potential. Recent Trends and Future Direction for Data Analytics presents a compelling solution. By delving into real-world case studies spanning supply chain management, marketing, healthcare, and finance, this book bridges the gap between theory and practice, offering invaluable insights into the practical applications of data analytics. A systematic exploration of fundamental concepts, advanced techniques, and specialized topics equips scholars, researchers, and industry professionals with the knowledge and tools needed to navigate the complexities of data analytics with confidence.
Convergence Strategies for Green Computing and Sustainable Development presents a comprehensive exploration of the potential of emerging technologies, such as the Internet of Things (IoT), Artificial Intelligence (AI), fog computing, and cloud computing, to aid in fostering a sustainable future. It examines how these technologies can reduce the impact of unsustainability in societies, the environment, and natural resources, offering invaluable insights into harnessing their power for positive change. Convergence Strategies for Green Computing and Sustainable Development serves as a comprehensive strategy that holistically understands, transforms, and develops technological systems in society. This book caters to a diverse range of readers, including graduate students, researchers, working professionals seeking knowledge, and industry experts seeking information about new trends. With its recommended topics and comprehensive table of contents, readers can gain in-depth knowledge about sustainable cloud computing, artificial intelligence and machine learning for sustainable development, sustainable wireless systems and networks, and the crucial role of green IoT and Edge-AI in driving a sustainable digital transition.
This book covers how Internet of Things (IoT) has a role in shaping the future of our communities. The author shows how the research and education ecosystem promoting impactful solutions-oriented science can help citizenry, government, industry, and other stakeholders to work collaboratively in order to make informed, socially-responsible, science-based decisions. Accordingly, he shows how communities can address complex, interconnected socio-environmental challenges. This book addresses the key inter-related challenges in areas such as the environment, climate change, mining, energy, agro-economic, water, and forestry that are limiting the development of a sustainable and resilient society -- each of these challenges are tied back to IoT based solutions. Presents research into sustainable IoT with respect to wireless communications, sensing, and systems Provides coverage of IoT technologies in sustainability, health, agriculture, climate change, mining, energy, water management, and forestry Relevant for academics, researchers, policy makers, city planners and managers, technicians, and industry professionals in IoT and sustainability
Convergence of Blockchain, AI, and IoT: Concepts and Challenges discusses the convergence of three powerful technologies that play into the digital revolution and blur the lines between biological, digital, and physical objects. This book covers novel algorithms, solutions for addressing issues in applications, security, authentication, and privacy. The book provides an overview of the clinical scientific research enabling smart diagnosis equipment through AI. It presents the role these technologies play in augmented reality and blockchain, covers digital currency managed with bitcoin, and discusses deep learning and how it can enhance human thoughts and behaviors. Targeted audiences range from those interested in the technical revolution of blockchain, big data and the Internet of Things, to research scholars and the professional market.
MACHINE LEARNING APPROACHES FOR CONVERGENCE OF IOT AND BLOCKCHAIN The unique aspect of this book is that its focus is the convergence of machine learning, IoT, and blockchain in a single publication. Blockchain technology and the Internet of Things (IoT) are two of the most impactful trends to have emerged in the field of machine learning. Although there are a number of books available solely on the subjects of machine learning, IoT and blockchain technology, no such book has been available which focuses on machine learning techniques for IoT and blockchain convergence until now. Thus, this book is unique in terms of the topics it covers. Designed as an essential guide for all academicians, researchers, and those in industry who are working in related fields, this book will provide insights into the convergence of blockchain technology and the IoT with machine learning. Highlights of the book include: Examines many industries such as agriculture, manufacturing, food production, healthcare, the military, and IT Security of the Internet of Things using blockchain and AI Developing smart cities and transportation systems using machine learning and IoT Audience The target audience of this book is professionals and researchers (artificial intelligence specialists, systems engineers, information technologists) in the fields of machine learning, IoT, and blockchain technology.
Traditional patient care and treatment approaches often lack the personalized and interactive elements necessary for effective healthcare delivery. This means that the healthcare industry must find innovative solutions to improve patient outcomes, enhance rehabilitation processes, and optimize resource utilization. There is a gap between the traditional approach and the need for innovation that highlights the importance of a comprehensive understanding of emerging technologies, including Kinect Sensor technology, and the potential to transform healthcare practices with this tech. Revolutionizing Healthcare Treatment With Sensor Technology addresses this critical need by thoroughly exploring how Kinect Sensor technology can revolutionize patient care and treatment methodologies. By repurposing and customizing Kinect Sensor for healthcare applications, this book showcases how depth-sensing cameras, infrared sensors, and advanced motion tracking can capture and interpret real-time patient movements and interactions. This book is ideal for healthcare professionals, hospital administrators, researchers, patients, caregivers, and healthcare technology developers seeking to leverage Kinect Sensor technology for enhanced healthcare delivery. Through detailed case studies and practical examples, experts can learn how to integrate Kinect Sensor into various medical settings to gain valuable insights into patients' physical capabilities, monitor their progress, and create personalized treatment plans.
Technological Advancements in Data Processing for Next Generation Intelligent Systems presents an in-depth exploration of cutting-edge data processing technologies that drive the development of next-generation intelligent systems in the context of the digital transformation era. This comprehensive book delves into the role data plays as a critical asset for organizations across diverse industries, and how recent technological breakthroughs have unlocked unprecedented potential for handling vast data volumes and real-time analysis. The book begins by providing a thorough overview of novel technologies such as artificial intelligence (AI) or machine learning (ML), edge computing, federated learning, quantum computing, and more. These revolutionary technologies, when integrated with big data frameworks, in-memory computing, and AI/ML algorithms, have transformed data processing capabilities, enabling the creation of intelligent systems that fuel innovation, optimize operations, and deliver personalized experiences. The ultimate aim of this integration is to empower devices with the ability to make autonomous intelligent decisions, maximizing computing power. This book serves as a valuable resource for research scholars, academicians, and industry professionals working towards the future advancement of optimized intelligent systems and intelligent data processing approaches. The chapters encompass a wide range of topics, including architecture and frameworks for intelligent systems, applications in diverse domains, cloud-based solutions, quantum processing, federated learning, in-memory data processing, real-time stream processing, trustworthy AI for Internet of Things (IoT) sensory data, and more.