Sachin Kumar Gupta – författare

The book presents theoretical and experimental approaches, quantitative and qualitative analyses, and simulations in wireless ad-hoc and sensor networks. It further explains the power and routing optimization in underwater sensor networks, advanced cross-layer framework, challenges and security issues in underwater sensor networks, and the use of machine learning and deep learning techniques for security implementations in wireless ad-hoc and sensor networks.This book:Discusses mobile ad-hoc network routing issues and challenges with node mobility and resource limitationsCovers the internet of vehicles, autonomous vehicle architecture, and design of heterogeneous wireless sensor networksPresents various technologies of ad-hoc networks, use of machine learning, and deep learning techniques in wireless sensor networksIllustrates recent advancements in security mechanisms for information dissemination in mobile ad-hoc networks, vehicular ad-hoc networks, flying ad-hoc networks, and autonomous vehiclesHighlights mathematical modeling and analysis of routing protocols for ad-hoc networks and underwater sensor networksIt is primarily written for undergraduate and graduate students, researchers, and academicians in the fields of computer science and engineering, information technology, electrical engineering, and electronics and communications engineering.

Computational methods are necessary for the proper execution of the applications for the benefit of society and technological development. Technological development makes life easier by constructing powerful systems with the help of computational methods. The nature of computational methods changes from time to time and retains only efficient applicable theories. Researchers take the idea of existing computational systems and advance them as per possible future needs. Efficient computational methods solve complex problems and also help to make the system more intelligent. Automation process requires decision-making computational systems. A more intelligent system contains an efficient computational method, which is described by powerful algorithm development. The aim of this book is to identify the technological development for future computational systems, which ultimately reflects the more intelligent system. Automation has become the need of the hour in today’s world, and hence, the computational systems need to be upgraded to that level to perform the required tasks. The most efficient computational algorithm acts like a human being and offers a full sense of intelligent automation.This book:Presents the latest research trends for the upcoming computational intelligent systems in a comprehensive mannerFocuses on the integration of multi-purpose and multi-dimension natural language into intelligent systemsElaborates on nature-inspired and intelligent behaviour-based computational methods to deal with the observation of natureIllustrates applications of quantum cellular energy-efficient computing methods for automation and applications of genetic algorithms in multidisciplinary fieldsDiscusses aspects of intelligent automation like technology-based, architecture-based, logic implementation-based, and the different algorithms-based conceptsIt is primarily written for senior undergraduates, graduate students, and academic researchers in the fields of electrical engineering, electronics and communications engineering, computer science and engineering, and information technology.

Intelligent computation is the need of the current society. This field attracts significant attention due to its application‑oriented systems. It is essential for implementing various society‑related solutions. Automation methods help improve the quality of life and support the development of efficient systems. The available theories and concepts are implemented for the benefit of society, drastically changing the world. The advancement of the existing ideas is simulated in the scenario of future intelligent automation systems. The complicated problems can be easily solved using the mentioned approaches. The decisive nature of the algorithms builds the system more intelligent. This book targets current trends in the relevant field and outlines a path for the development of future automated systems. The intelligence behaviour of the systems is the prime requirement for the age development. The gaps in the current development scenarios need to be identified and bridged by incorporating highly efficient algorithms, ideas, and working prototypes.This book:Presents a comprehensive survey, performance analysis, and time complexity comparison of machine learning techniques in network securityDiscusses energy‑efficient hybrid algorithms for reconfiguration in radial distribution systemsCovers a detailed examination of automation approaches for the study and detection of disparate leaf diseases using computational intelligent systemsIllustrates applications of quantum cellular energy‑efficient computing methods for automationExplain cybersecurity strategies for advanced computational intelligence and customer segmentation through machine learning techniquesThe book is primarily written for senior undergraduates, graduate students, and academic researchers in the fields of electrical engineering, electronics and communications engineering, computer science and engineering, and information technology.

IMPACT OF ARTIFICIAL INTELLIGENCE ON ORGANIZATIONAL TRANSFORMATION Discusses the impact of AI on organizational transformation which is a mix of computational techniques and management practices, with in-depth analysis about the role of automation & data management, and strategic management in relation to human capital, procurement & production, finance, and marketing. The impact of AI in restructuring organizational processes is a combination of management practices and computational technology. This book covers the areas like artificial intelligence & its impact on professions, as well as machine learning algorithms and technologies. The context of applications of AI in business process innovation primarily includes new business models, AI readiness and maturity at the organizational, technological, financial, and cultural levels. The book has extensive details on machine learning and the applications such as robotics, blockchain, Internet of Things. Also discussed are the influence of AI on financial strategies and policies, human skills & values, procurement innovation, production innovation, AI in marketing & sales platforms. Audience Readers include those working in artificial intelligence, business management studies, technology engineers, senior executives, and human resource managers in all types of business.

This book is an essential resource for anyone looking to understand the cutting-edge applications and evolving technologies of Unmanned Aerial Systems, showcasing how they enhance safety and efficiency in monitoring, emergency response, and smart city development. With the evolution of Unmanned Aircraft Systems (UAS), its applications can be observed in the fields of monitoring for fire detection, sustainable computing, emergencies, and law enforcement. They can be useful for monitoring or screening applications, as well as the deployment of smart cities, security monitoring, and communication establishments at rare locations or unapproachable locations. Thus, the wireless ad-hoc networks of Unmanned Aerial Vehicles (UAVs) and infrastructure-based UAVs can be utilized in this proposal. Unmanned aircraft systems (UAS) extend human potential and allow us to execute dangerous or difficult tasks safely and efficiently, saving time, money, and, most importantly, lives. UAS can help police, fire, and other public workers save lives in emergencies like natural disasters, locate missing animals and children, or help fight fighters. Unmanned Aircraft Systems contains novel contributions and emerging trends in the area of Unmanned Aerial Vehicles (UAV), drones, and aircraft without a human pilot aboard. It has three segments incorporating technological advancements and future trends in UAS, the policies and security aspects of UAVs, and their applications as an intelligent system. Along with these state-of-the-art techniques, this book also incorporates advances in AI and machine learning, deep learning, IoT technology, cybersecurity and Blockchain, UAV regulation policies in the United States and Europe, SOTA in ITS, and many more technological advancements, which makes this book the pioneer and benchmarking reference in these areas.

This comprehensive volume delves deep into the diverse applications and implications of generative AI across accounting, finance, economics, business, and management, providing readers with a holistic understanding of this rapidly evolving landscape. Generative Artificial Intelligence in Finance: Large Language Models, Interfaces, and Industry Use Cases to Transform Accounting and Finance Processes provides a comprehensive guide to ethically harnessing generative AI systems to reshape financial management. Generative AI is a key theme across the accounting and finance sectors to drive significant optimizations leading to sustainability. Across 22 chapters, leading researchers supply innovative applications of large language models across the economic realm. Through detailed frameworks, real-world case studies, and governance recommendations, this book highlights applied research for generative AI in finance functions. Several chapters demonstrate how data-driven insights from AI systems can optimize complex financial processes to reduce resource usage, lower costs, and drive positive environmental impact over the long term. In addition, chapters on AI-enabled risk assessment, fraud analytics, and regulatory technology highlight applied research for generative AI in finance. The book also explores emerging applications like leveraging blockchain and metaverse interfaces to create generative AI models that can revolutionize areas from carbon credit trading to virtual audits. Overall, with in-depth applied research at the nexus of sustainability and optimization enabled by data science and generative AI, the book offers a compilation of best practices in leveraging AI for optimal, ethical, and future-oriented financial management. Audience The audience for this book is quite diverse, ranging from financial and accounting experts across banking, insurance, consultancies, regulatory agencies, and corporations seeking to enhance productivity and efficiency; business leaders want to implement ethical and compliant AI practices; researchers exploring the domain of AI and finance.

This book highlights the literature and the practical aspects to understand cybersecurity and privacy in various networks and communication devices. This book presents state-of-the-art advances in the field of cryptography and network security, cybersecurity and privacy, providing a good reference for professionals and researchers.

This book highlights the literature and the practical aspects to understand cybersecurity and privacy in various networks and communication devices. This book presents state-of-the-art advances in the field of cryptography and network security, cybersecurity and privacy, providing a good reference for professionals and researchers.