Effective Ai Blockchain And E Governance Applications For Knowledge Discovery And Management

Emerging technologies have become both crucibles and showrooms for the practical application of artificial intelligence, the internet of things, and cloud computing, and for integrating big data into everyday life. Is the digital world optimized and sustainable using intelligence systems, machine learning, and cyber security methods? This complex concoction of challenges requires new thinking of the synergistic utilization of intelligence systems, machine learning, deep learning and blockchain methods, data-driven decision-making with automation infrastructure, autonomous transportation, and connected buildings. Effective AI, Blockchain, and E-Governance Applications for Knowledge Discovery and Management provides a global perspective on current and future trends concerning the integration of intelligent systems with cybersecurity applications, including recent advances and challenges related to the concerns of security and privacy issues in deep learning with an emphasis on the current state-of-the-art methods, methodologies and implementation, attacks, and countermeasures. The book also discusses the challenges that need to be addressed for implementing DL-based security mechanisms that should have the capability of collecting or distributing data across several applications. Topics covered include skill development and tools for intelligence systems, deep learning, machine learning, blockchain, IoT, cloud computing, data ethics, and infrastructure. It is ideal for independent researchers, research scholars, scientists, libraries, industry experts, academic students, business associations, communication and marketing agencies, entrepreneurs, and all potential audiences with a specific interest in these topics.

In the age of immediate technical expansion, our world faces a multifaceted challenge: ensuring the sustainability of our digital transformation. Governments and organizations have wholeheartedly embraced innovative technologies such as artificial intelligence, blockchain, and e-governance, but in doing so, they have encountered a complex web of issues. These range from cybersecurity concerns in an increasingly digitalized world to the need for intelligent systems capable of managing automation infrastructure and interconnected environments. Sustainable Development in AI, Blockchain, and E-Governance Applications offers a forward-thinking approach that harnesses the synergy between intelligent systems, machine learning, deep learning, and blockchain methods. It explores data-driven decision-making, automation infrastructure, autonomous transportation, and the creation of connected buildings, all aimed at crafting a sustainable digital future. By delving into topics like machine learning for smart parking, disease classification through neural networks, and the Internet of Things (IoT) for smarter cities, this book equips academic scholars with the tools they need to navigate the complex terrain of technology and governance. Academic scholars and researchers in technology, governance, and sustainability will find this book to be an indispensable resource. It caters to those seeking a comprehensive understanding of current and future trends in the integration of intelligent systems with cybersecurity applications.

Organizations face a pressing challenge in today's rapidly evolving economies: navigating the ethical complexities of adopting Artificial Intelligence (AI) and related technologies. As AI becomes increasingly integral to operations, transparency, fairness, accountability, and privacy concerns are more critical than ever. Organizations need practical guidance to develop and implement AI ethics strategies effectively. Cases on AI Ethics in Business offers a comprehensive solution by examining AI Ethics through theoretical lenses and innovative practices. It provides a roadmap for organizations to address ethical challenges in AI adoption, offering insights from leaders in the field. With a focus on theory-to-practice, the book equips readers with actionable strategies and frameworks to navigate the ethical implications of AI, ensuring responsible and sustainable AI deployment.

Integrating electric vehicles (EVs) into power distribution systems presents significant challenges, particularly concerning power source dependability and grid stability. The distribution system, a critical element of the power system, is susceptible to failures and power outages exacerbated by the extensive adoption of EVs. Additionally, managing the administration, monitoring, and control of power systems in the context of EV integration is a complex and daunting task for energy experts. A Sustainable Future with E-Mobility: Concepts, Challenges, and Implementations offers a comprehensive solution to these challenges. It explores infrastructure frameworks, planning strategies, control strategies, and software applications for integrating EVs with power distribution systems, focusing on innovative grid developments. By providing insights into architectural reconfiguration, restoration strategies, power quality control, and regulatory aspects, the book equips students, researchers, academicians, policymakers, and industry experts with the knowledge needed to achieve a secure, resilient, and efficient integration of EVs into distribution networks.

In the face of escalating environmental challenges such as climate change, air and water pollution, and natural disasters, traditional approaches to understanding and addressing these issues have yet to be proven sufficient. Academic scholars are compelled to seek innovative solutions that marry digital intelligence and natural ecosystems. Reshaping Environmental Science Through Machine Learning and IoT serves as a comprehensive exploration into the transformative potential of Machine Learning (ML) and the Internet of Things (IoT) to address critical environmental challenges. The book establishes a robust foundation in ML and IoT, explaining their relevance to environmental science. As the narrative unfolds, it delves into diverse applications, providing theoretical insights alongside practical knowledge. From interpreting weather patterns to predicting air and water quality, the book navigates through the intricate web of environmental complexities. Notably, it unveils approaches to disaster management, waste sorting, and climate change monitoring, showcasing the symbiotic relationship between digital intelligence and natural ecosystems. This book is ideal for audiences from students and researchers to data scientists and disaster management professionals with a nuanced understanding of IoT, ML, and Artificial Intelligence (AI).

Academic scholars find themselves confronted with a formidable challenge: staying abreast of the ever-evolving landscape of Artificial Intelligence(AI). The intricate interplay between AI and its profound impact on various facets of society, including customer engagement, remains an enigma for many. This knowledge gap not only hampers their ability to contribute meaningfully to their fields but also leaves them trailing behind the dynamic developments taking place in industries worldwide. As AI continues to reshape the business environment, it becomes imperative for academia to bridge this chasm between theory and practice. Leveraging ChatGPT and Artificial Intelligence for Effective Customer Engagement is an effective solution to the pressing problem at hand. With meticulous clarity, it unravels the complexities of ChatGPT, an innovative AI technology, and its revolutionary potential in the realm of customer engagement. It offers a lifeline to academic scholars seeking to navigate the uncharted territory of AI, providing them with an in-depth understanding of how ChatGPT can reshape customer interactions.

The confluence of Artificial Intelligence of Things (AIoT) and Semantic Web technologies is nothing short of revolutionary. The profound impact of this synergy extends far beyond the realms of industry, research, and society; it shapes the very fabric of our future. Semantic Web Technologies and Applications in Artificial Intelligence of Things is a meticulously crafted reference that not only acknowledges this significance but also serves as a guide for those navigating the complexities of Industry 4.0 and AIoT. This curated compendium of cutting-edge technologies acts as a veritable knowledge base for future developments. As academics, scholars, and industry professionals, the ideal audience of this book, will find meticulously curated content that caters to their diverse interests and expertise, covering topics ranging from smart agriculture, manufacturing, industry, health sciences, and government. Seasoned academics, students, and visionary industry leaders, will find this book to be an indispensable guide that paves the way for innovation and progress.

As society transitions into the digital age, the demand for advanced robotics and autonomous systems has remained unchanged. However, the field faces significant challenges bridging the gap between current capabilities and the potential for brilliant, autonomous machines. While exact and efficient, current robotic systems need more sophistication and adaptability of human intelligence. This limitation restricts their application in complex and dynamic environments, hindering their ability to realize their potential fully. Multidisciplinary Applications of AI Robotics and Autonomous Systems addresses these challenges by presenting cutting-edge research and innovative robotics and autonomous systems solutions. By exploring topics such as digital transformation, IoT, AI, and cloud-native computing paradigms, readers will understand the latest advancements in the field. The book delves into theoretical frameworks, computational models, and experimental approaches, offering insights to help researchers and practitioners develop more intelligent and autonomous machines.