There is now a plethora of internet of things (IoT) devices on the market that can connect to the internet and the desired environment to produce sufficient and reliable data that is required by the government administration for a variety of purposes. Additionally, the potential benefits of incorporating artificial intelligence (AI) and machine learning into governance are numerous. Governments can use AI and machine learning to enforce the law, detect fraud, and monitor urban areas by identifying problems before they occur. The government can also use AI to easily automate processes and replace mundane and repetitive tasks. AI, IoT, and Blockchain Breakthroughs in E-Governance defines and emphasizes various AI algorithms as well as new internet of things and blockchain breakthroughs in the field of e-governance. Covering key topics such as machine learning, government, and artificial intelligence, this premier reference source is ideal for government officials, policymakers, researchers, academicians, practitioners, scholars, instructors, and students.

In the ever-changing world of engineering, the confluence of Augmented Reality (AR) and Virtual Reality (VR) promises a revolutionary frontier; one that has the potential to remodel the fundamental fabric of our designed world. As our society approaches the genesis of a new age, the need for the study of this bourgeoning technology becomes clear. If harnessed properly, AR and VR have the capacity to revolutionize basic aspects of engineering methods. The combination of AR and VR can tackle the rising difficulties that engineers encounter in their design processes by providing improved tools for visualization and conceptualization. Navigating the Augmented and Virtual Frontiers in Engineering, is a thorough examination of the transformational impact of AR and VR in the vast field of engineering. This book explores the fundamental concepts, practical applications, and significant consequences of incorporating AR and VR technology into numerous engineering disciplines. It provides a comprehensive knowledge of how these immersive technologies are used in design processes, training simulations, maintenance procedures, and collaborative engineering projects. Covering topics such as asset management, geographic analysis, and sustainability, this book is an excellent resource for engineers, researchers, technological developers, postgraduate students, educators, academicians, and more.

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.

In today's rapidly advancing digital world, governments face the dual challenge of harnessing technology to enhance security systems while safeguarding sensitive data from cyber threats and privacy breaches. Futuristic e-Governance Security With Deep Learning Applications provides a timely and indispensable solution to these pressing concerns. This comprehensive book takes a global perspective, exploring the integration of intelligent systems with cybersecurity applications to protect deep learning models and ensure the secure functioning of e-governance systems. By delving into cutting-edge techniques and methodologies, this book equips scholars, researchers, and industry experts with the knowledge and tools needed to address the complex security challenges of the digital era. The authors shed light on the current state-of-the-art methods while also addressing future trends and challenges. Topics covered range from skill development and intelligence system tools to deep learning, machine learning, blockchain, IoT, and cloud computing. With its interdisciplinary approach and practical insights, this book serves as an invaluable resource for those seeking to navigate the intricate landscape of e-governance security, leveraging the power of deep learning applications to protect data and ensure the smooth operation of government systems.

In our data-rich era, extracting meaningful insights from the vast amount of information has become a crucial challenge, especially in government service delivery where informed decisions are paramount. Traditional approaches struggle with the enormity of data, highlighting the need for a new approach that integrates data science and machine learning. The book, Machine Learning and Data Science Techniques for Effective Government Service Delivery, becomes a vital resource in this transformation, offering a deep understanding of these technologies and their applications. Within the complex landscape of modern governance, this book stands as a solution-oriented guide. Recognizing data's value in the 21st century, it navigates the world of data science and machine learning, enhancing the mechanics of government service. By addressing citizens' evolving needs, these advanced methods counter inefficiencies in traditional systems. Tailored for experts across technology, academia, and government, the book bridges theory and practicality. Covering foundational concepts and innovative applications, it explores the potential of data-driven decision-making for a more efficient and citizen-centric government future.

The industrial landscape is changing rapidly, and so is global society. This change is driven by the growing adoption of the Industrial Internet of Things (IIoT) and artificial intelligence (AI) technologies. IIoT and AI are transforming the way industrial engineering is done, enabling new levels of automation, productivity, and efficiency. However, as IIoT and AI become more pervasive in the industrial world, they also offer new security risks that must be addressed to ensure the reliability and safety of critical systems. Industrial Internet of Things Security: Protecting AI-Enabled Engineering Systems in Cloud and Edge Environments provides a comprehensive guide to IIoT security, covering topics such as network architecture, risk management, data security, and compliance. It addresses the unique security challenges that the cloud and edge environments pose, providing practical guidance for securing IIoT networks in these contexts. It includes numerous real-world case studies and examples, providing readers with practical insights into how IIoT security and AI-enabled industrial engineering are being implemented in various industries. Best practices are emphasized for the readers to ensure the reliability, safety, and security of their systems while also learning the latest developments in IIoT security for AI-enabled industrial engineering systems in this rapidly evolving field. By offering step-by-step guidance for the implantation process along with best practices, this book becomes a valuable resource for practitioners and engineers in the areas of industrial engineering, IT, computer engineering, and anyone looking to secure their IIoT network against cyber threats.