Introduces fundamental theory, basic and advanced algorithms, and system design issues. Essential reading for experienced researchers and developers, or for those who are just entering the field.

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.

Artificial Intelligence and Machine Learning for Predictive and Analytical Rendering in Edge Computing focuses on the role of AI and machine learning as it impacts and works alongside Edge Computing. Sections cover the growing number of devices and applications in diversified domains of industry, including gaming, speech recognition, medical diagnostics, robotics and computer vision and how they are being driven by Big Data, Artificial Intelligence, Machine Learning and distributed computing, may it be Cloud Computing or the evolving Fog and Edge Computing paradigms. Challenges covered include remote storage and computing, bandwidth overload due to transportation of data from End nodes to Cloud leading in latency issues, security issues in transporting sensitive medical and financial information across larger gaps in points of data generation and computing, as well as design features of Edge nodes to store and run AI/ML algorithms for effective rendering. - Provides a reference handbook on the evolution of distributed systems, including Cloud, Fog and Edge Computing - Integrates the various Artificial Intelligence and Machine Learning techniques for effective predictions at Edge rather than Cloud or remote Data Centers - Provides insight into the features and constraints in Edge Computing and storage, including hardware constraints and the technological/architectural developments that shall overcome those constraints

This book constitutes the proceedings of the 8th International Conference on Big Data Analytics, BDA 2021, which took place during December 2021. Due to COVID-19 pandemic the conference was held virtually. The 16 full and 3 short papers included in this volume were carefully reviewed and selected from 41 submissions. The contributions were organized in topical sections named as follows: medical and health applications; machine/deep learning; IoTs, sensors, and networks; fundamentation; pattern mining and data analytics.

This book gathers high-quality papers presented at the Sixth International Conference on Smart Trends in Computing and Communications (SmartCom 2022), organized by Global Knowledge Research Foundation (GR Foundation) in partnership with IFIP InterYIT during January 11–12, 2022. It covers the state of the art and emerging topics in information, computer communications, and effective strategies for their use in engineering and managerial applications. It also explores and discusses the latest technological advances in, and future directions for, information and knowledge computing and its applications.