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Artificial Intelligence and Cybersecurity: Advances and Innovations (Green Engineering and Technology)
by Ishaani Priyadarshini and Rohit SharmaArtificial intelligence and cybersecurity are two emerging fields that have made phenomenal contributions toward technological advancement. As cyber-attacks increase, there is a need to identify threats and thwart attacks. This book incorporates recent developments that artificial intelligence brings to the cybersecurity world. Artificial Intelligence and Cybersecurity: Advances and Innovations provides advanced system implementation for Smart Cities using artificial intelligence. It addresses the complete functional framework workflow and explores basic and high-level concepts. The book is based on the latest technologies covering major challenges, issues and advances, and discusses intelligent data management and automated systems. This edited book provides a premier interdisciplinary platform for researchers, practitioners and educators. It presents and discusses the most recent innovations, trends and concerns as well as practical challenges and solutions adopted in the fields of artificial intelligence and cybersecurity.
Artificial Intelligence and Cybersecurity: Advances and Innovations (Green Engineering and Technology)
by Ishaani Priyadarshini Rohit SharmaArtificial intelligence and cybersecurity are two emerging fields that have made phenomenal contributions toward technological advancement. As cyber-attacks increase, there is a need to identify threats and thwart attacks. This book incorporates recent developments that artificial intelligence brings to the cybersecurity world. Artificial Intelligence and Cybersecurity: Advances and Innovations provides advanced system implementation for Smart Cities using artificial intelligence. It addresses the complete functional framework workflow and explores basic and high-level concepts. The book is based on the latest technologies covering major challenges, issues and advances, and discusses intelligent data management and automated systems. This edited book provides a premier interdisciplinary platform for researchers, practitioners and educators. It presents and discusses the most recent innovations, trends and concerns as well as practical challenges and solutions adopted in the fields of artificial intelligence and cybersecurity.
Artificial Intelligence and Data Mining Approaches in Security Frameworks: Advances And Challenges (Advances in Data Engineering and Machine Learning)
by Neeraj Bhargava Ritu Bhargava Pramod Singh Rathore Rashmi AgrawalArtificial intelligence (AI) and data mining is the fastest growing field in computer science. AI and data mining algorithms and techniques are found to be useful in different areas like pattern recognition, automatic threat detection, automatic problem solving, visual recognition, fraud detection, detecting developmental delay in children, and many other applications. However, applying AI and data mining techniques or algorithms successfully in these areas needs a concerted effort, fostering integrative research between experts ranging from diverse disciplines from data science to Artificial Intelligence. Successful application of security frameworks to enable meaningful, cost effective, personalize security service is a primary aim of engineers and researchers today. However realizing this goal requires effective understanding, application and amalgamation of AI and Data Mining and several other computing technologies to deploy such system in an effective manner. This book provides state of the art approaches of artificial intelligence and data mining in these areas. It includes areas of detection, prediction, as well as future framework identification, development, building service systems and analytical aspects. In all these topics, applications of AI and data mining, such as artificial neural networks, fuzzy logic, genetic algorithm and hybrid mechanisms, are explained and explored. This book is aimed at the modeling and performance prediction of efficient security framework systems, bringing to light a new dimension in the theory and practice. This groundbreaking new volume presents these topics and trends, bridging the research gap on AI and data mining to enable wide-scale implementation. Whether for the veteran engineer or the student, this is a must-have for any library.
Artificial Intelligence and Data Mining Approaches in Security Frameworks (Advances in Data Engineering and Machine Learning)
by Neeraj Bhargava Ritu Bhargava Pramod Singh Rathore Rashmi AgrawalArtificial intelligence (AI) and data mining is the fastest growing field in computer science. AI and data mining algorithms and techniques are found to be useful in different areas like pattern recognition, automatic threat detection, automatic problem solving, visual recognition, fraud detection, detecting developmental delay in children, and many other applications. However, applying AI and data mining techniques or algorithms successfully in these areas needs a concerted effort, fostering integrative research between experts ranging from diverse disciplines from data science to Artificial Intelligence. Successful application of security frameworks to enable meaningful, cost effective, personalize security service is a primary aim of engineers and researchers today. However realizing this goal requires effective understanding, application and amalgamation of AI and Data Mining and several other computing technologies to deploy such system in an effective manner. This book provides state of the art approaches of artificial intelligence and data mining in these areas. It includes areas of detection, prediction, as well as future framework identification, development, building service systems and analytical aspects. In all these topics, applications of AI and data mining, such as artificial neural networks, fuzzy logic, genetic algorithm and hybrid mechanisms, are explained and explored. This book is aimed at the modeling and performance prediction of efficient security framework systems, bringing to light a new dimension in the theory and practice. This groundbreaking new volume presents these topics and trends, bridging the research gap on AI and data mining to enable wide-scale implementation. Whether for the veteran engineer or the student, this is a must-have for any library.
Artificial Intelligence and Data Mining in Healthcare
by Malek Masmoudi Bassem Jarboui Patrick SiarryThis book presents recent work on healthcare management and engineering using artificial intelligence and data mining techniques. Specific topics covered in the contributed chapters include predictive mining, decision support, capacity management, patient flow optimization, image compression, data clustering, and feature selection.The content will be valuable for researchers and postgraduate students in computer science, information technology, industrial engineering, and applied mathematics.
Artificial Intelligence and Data Science Based R&D Interventions: Proceedings of NERC 2022
by Ratnajit Bhattacharjee Debanga Raj Neog Konda Reddy Mopuri Santosh Kumar VipparthiThis book title is a composition of multiple research efforts that are based on cutting-edge Artificial Intelligence (AI) techniques. Some of the signal processing problems are addressed with techniques from the broad areas of machine learning and deep learning.
Artificial Intelligence and Deep Learning for Computer Network: Management and Analysis (Chapman & Hall/Distributed Computing and Intelligent Data Analytics)
by Sangita Roy Rajat Subhra Chakraborty Jimson Mathew Arka Prokash Mazumdar Sudeshna ChakrabortyArtificial Intelligence and Deep Learning for Computer Network: Management and Analysis aims to systematically collect quality research spanning AI, ML, and deep learning (DL) applications to diverse sub-topics of computer networks, communications, and security, under a single cover. It also aspires to provide more insights on the applicability of the theoretical similitudes, otherwise a rarity in many such books. Features: A diverse collection of important and cutting-edge topics covered in a single volume. Several chapters on cybersecurity, an extremely active research area. Recent research results from leading researchers and some pointers to future advancements in methodology. Detailed experimental results obtained from standard data sets. This book serves as a valuable reference book for students, researchers, and practitioners who wish to study and get acquainted with the application of cutting-edge AI, ML, and DL techniques to network management and cyber security.
Artificial Intelligence and Deep Learning for Computer Network: Management and Analysis (Chapman & Hall/Distributed Computing and Intelligent Data Analytics)
Artificial Intelligence and Deep Learning for Computer Network: Management and Analysis aims to systematically collect quality research spanning AI, ML, and deep learning (DL) applications to diverse sub-topics of computer networks, communications, and security, under a single cover. It also aspires to provide more insights on the applicability of the theoretical similitudes, otherwise a rarity in many such books. Features: A diverse collection of important and cutting-edge topics covered in a single volume. Several chapters on cybersecurity, an extremely active research area. Recent research results from leading researchers and some pointers to future advancements in methodology. Detailed experimental results obtained from standard data sets. This book serves as a valuable reference book for students, researchers, and practitioners who wish to study and get acquainted with the application of cutting-edge AI, ML, and DL techniques to network management and cyber security.
Artificial Intelligence and Digital Systems Engineering (Analytics and Control)
by Adedeji B. BadiruThe resurgence of artificial intelligence has been fueled by the availability of the present generation of high-performance computational tools and techniques. This book is designed to provide introductory guidance to artificial intelligence, particularly from the perspective of digital systems engineering. Artificial Intelligence and Digital Systems Engineering provides a general introduction to the origin of AI and covers the wide application areas and software and hardware interfaces. It will prove to be instrumental in helping new users expand their knowledge horizon to the growing market of AI tools, as well as showing how AI is applicable to the development of games, simulation, and consumer products, particularly using artificial neural networks. This book is for the general reader, university students, and instructors of industrial, production, civil, mechanical, and manufacturing engineering. It will also be of interest to managers of technology, projects, business, plants, and operations.
Artificial Intelligence and Digital Systems Engineering (Analytics and Control)
by Adedeji B. BadiruThe resurgence of artificial intelligence has been fueled by the availability of the present generation of high-performance computational tools and techniques. This book is designed to provide introductory guidance to artificial intelligence, particularly from the perspective of digital systems engineering. Artificial Intelligence and Digital Systems Engineering provides a general introduction to the origin of AI and covers the wide application areas and software and hardware interfaces. It will prove to be instrumental in helping new users expand their knowledge horizon to the growing market of AI tools, as well as showing how AI is applicable to the development of games, simulation, and consumer products, particularly using artificial neural networks. This book is for the general reader, university students, and instructors of industrial, production, civil, mechanical, and manufacturing engineering. It will also be of interest to managers of technology, projects, business, plants, and operations.
Artificial Intelligence and Economic Sustainability in the Era of Industrial Revolution 5.0 (Studies in Systems, Decision and Control #528)
by Abdalmuttaleb M. A. Musleh Al-Sartawi Abdulnaser Ibrahim NourIndustry 5.0 has been dubbed as the digital revolution with a soul. This book incorporates a wealth of research which integrates artificial intelligence (AI) with economic sustainability and Industry 5.0. It examines the human-centricity of the upcoming digital revolution and the role of sustainable technologies in enhancing the livelihoods of workers, individuals, communities, and eventually societies. It provides insight on important areas related to artificial intelligence, sustainable development, and society 5.0. The chapters present a wide range of topics including block cipher, entrepreneurship and AI, AI and stock trading decisions, digital transformation, knowledge management, chatbot engineering, cybersecurity, and smart metering system. This book is beneficial to scholars and academics who will find in it the knowledge of the support of AI and its contribution to economic sustainability, and solutions to enhance human-centricity and resilience.
Artificial Intelligence and Economics: the Key to the Future (Lecture Notes in Networks and Systems #523)
by Domenico Marino Melchiorre MonacaThis book aims to deal with the main advances in the study of artificial intelligence, the digital and circular economy and innovation from a multidisciplinary perspective. Whoever governs the artificial intelligence will hold the keys to the world and the future. This consideration explains the growing role of artificial intelligence in our lives and the need to understand its mechanisms.This book presents original research articles addressing various aspects of artificial intelligence applied to economics, law, management, and optimization. The topics discussed include, economics, territorial policies, law, resource allocation strategies, information technology, and learning for inclusion.Combining the input of contributing professors and researchers from Italian and other foreign universities, the book is of interest to students, researchers, and practitioners, as well as members of the public in general, interested in the world of the artificial intelligence and economics.
Artificial Intelligence and Edge Computing for Sustainable Ocean Health (The Springer Series in Applied Machine Learning)
by Debashis De Diganta Sengupta Tien Anh TranArtificial Intelligence and Edge Computing for Sustainable Ocean Health explores the transformative role of AI and edge computing in preserving and enhancing ocean health. The growing influence of Artificial Intelligence (AI), along with the Internet of Things (IoT) in generating wide coverage of sensor networks, and Edge Computing (EC) has paved the way for investigation of underwater as well as massive marine data, thereby generating huge potential for credible research opportunities for these domains. This book’s journey begins with a broad overview of Artificial Intelligence for Sustainable Ocean Health, setting the foundation for understanding AI's potential in marine conservation. The subsequent chapter, Role of Artificial Intelligence and Technologies in Improving Ocean Health in Promoting Tourism, illustrates the synergy between technological advancements and sustainable tourism practices, demonstrating how AI can enhance the attractiveness and preservation of marine destinations. The identification, restoration, and monitoring of marine resources along with the utilization of technology continues in Utilization of Underwater Wireless Sensor Network through Supervising a Random Network Environment in the Ocean Environment has been extensively dealt with. The technical challenges of underwater imaging, essential for accurate data collection and analysis has been discussed. The importance of Explainable AI is discussed in chapters like Sustainable Development Goal 14: Explainable AI (XAI) for Ocean Health, Explainable AI (XAI) for Ocean Health: Exploring the Role of Explainable AI in Enhancing Ocean Health, and A Comprehensive Study of AI (XAI) for Ocean Health Monitoring, which emphasize transparency and trust in AI systems. Further, Revolutionizing Internet of Underwater Things with Federated Learning, Underwater Drone, Underwater Imagery with AI/ML and IoT in ROV Technology and Ocean Cleanup has been demonstrated using innovative approaches to addressing underwater challenges. The book also includes a Review on the Optics and Photonics in Environmental Sustainability, focusing on the role of optics in marine conservation. Security issues are tackled in Intelligent Hash Function Based Key-Exchange Scheme for Ocean Underwater Data Transmission, and the overarching potential of AI in marine resource management is discussed in Artificial Intelligence as Key-enabler for Safeguarding the Marine Resources.
Artificial Intelligence and Environmental Sustainability: Challenges and Solutions in the Era of Industry 4.0 (Algorithms for Intelligent Systems)
by Hui Lin Ong Ruey-An Doong Raouf Naguib Chee Peng Lim Atulya K. NagarThe book discusses comprehensive and cutting-edge research and development endeavors, as well as innovative solutions, in implementing AI and related technologies to meet and undertake current and future challenges towards ensuring environmental sustainability. It explores the future research directions in the era of Industry 4.0. In the beginning, an overview of the utilization of Al for environmental sustainability is provided. The remaining chapters of the book cover the technological and application aspects of Al for environmental sustainability with illustrative examples. Finally, challenges with respect to deploying Al to solving environmental problems and the future trends are covered.
Artificial Intelligence and Evolutionary Algorithms in Engineering Systems: Proceedings of ICAEES 2014, Volume 1 (Advances in Intelligent Systems and Computing #324)
by L. Padma Suresh Subhransu Sekhar Dash Bijaya Ketan PanigrahiThe book is a collection of high-quality peer-reviewed research papers presented in Proceedings of International Conference on Artificial Intelligence and Evolutionary Algorithms in Engineering Systems (ICAEES 2014) held at Noorul Islam Centre for Higher Education, Kumaracoil, India. These research papers provide the latest developments in the broad area of use of artificial intelligence and evolutionary algorithms in engineering systems. The book discusses wide variety of industrial, engineering and scientific applications of the emerging techniques. It presents invited papers from the inventors/originators of new applications and advanced technologies.
Artificial Intelligence and Evolutionary Algorithms in Engineering Systems: Proceedings of ICAEES 2014, Volume 2 (Advances in Intelligent Systems and Computing #325)
by L Padma Suresh Subhransu Sekhar Dash Bijaya Ketan PanigrahiThe book is a collection of high-quality peer-reviewed research papers presented in Proceedings of International Conference on Artificial Intelligence and Evolutionary Algorithms in Engineering Systems (ICAEES 2014) held at Noorul Islam Centre for Higher Education, Kumaracoil, India. These research papers provide the latest developments in the broad area of use of artificial intelligence and evolutionary algorithms in engineering systems. The book discusses wide variety of industrial, engineering and scientific applications of the emerging techniques. It presents invited papers from the inventors/originators of new applications and advanced technologies.
Artificial Intelligence and Evolutionary Computations in Engineering Systems: Computational Algorithm for AI Technology, Proceedings of ICAIECES 2020 (Advances in Intelligent Systems and Computing #1361)
by S. Chandramohan Bala Venkatesh Subhransu Sekhar Dash Swagatam Das C. SharmeelaThis book gathers selected papers presented at the 6th International Conference on Artificial Intelligence and Evolutionary Computations in Engineering Systems, held at the Anna University, Chennai, India, from 20 to 22 April 2020. It covers advances and recent developments in various computational intelligence techniques, with an emphasis on the design of communication systems. In addition, it shares valuable insights into advanced computational methodologies such as neural networks, fuzzy systems, evolutionary algorithms, hybrid intelligent systems, uncertain reasoning techniques, and other machine learning methods and their application to decision-making and problem-solving in mobile and wireless communication networks.
Artificial Intelligence and Evolutionary Computations in Engineering Systems: Proceedings Of Icaieces 2015 (Advances in Intelligent Systems and Computing #1056)
by Subhransu Sekhar Dash C. Lakshmi Swagatam Das Bijaya Ketan PanigrahiThis book gathers selected papers presented at the 4th International Conference on Artificial Intelligence and Evolutionary Computations in Engineering Systems, held at the SRM Institute of Science and Technology, Kattankulathur, Chennai, India, from 11 to 13 April 2019. It covers advances and recent developments in various computational intelligence techniques, with an emphasis on the design of communication systems. In addition, it shares valuable insights into advanced computational methodologies such as neural networks, fuzzy systems, evolutionary algorithms, hybrid intelligent systems, uncertain reasoning techniques, and other machine learning methods and their application to decision-making and problem-solving in mobile and wireless communication networks.
Artificial Intelligence and Expert Systems for Engineers (New Directions in Civil Engineering #11)
by C. S. Krishnamoorthy S. RajeevThis book provides a comprehensive presentation of artificial intelligence (AI) methodologies and tools valuable for solving a wide spectrum of engineering problems. What's more, it offers these AI tools on an accompanying disk with easy-to-use software. Artificial Intelligence and Expert Systems for Engineers details the AI-based methodologies known as: Knowledge-Based Expert Systems (KBES); Design Synthesis; Design Critiquing; and Case-Based Reasoning. KBES are the most popular AI-based tools and have been successfully applied to planning, diagnosis, classification, monitoring, and design problems. Case studies are provided with problems in engineering design for better understanding of the problem-solving models using the four methodologies in an integrated software environment.Throughout the book, examples are given so that students and engineers can acquire skills in the use of AI-based methodologies for application to practical problems ranging from diagnosis to planning, design, and construction and manufacturing in various disciplines of engineering.Artificial Intelligence and Expert Systems for Engineers is a must-have reference for students, teachers, research scholars, and professionals working in the area of civil engineering design in particular and engineering design in general.
Artificial Intelligence and Expert Systems for Engineers (New Directions in Civil Engineering #11)
by C. S. Krishnamoorthy S. RajeevThis book provides a comprehensive presentation of artificial intelligence (AI) methodologies and tools valuable for solving a wide spectrum of engineering problems. What's more, it offers these AI tools on an accompanying disk with easy-to-use software. Artificial Intelligence and Expert Systems for Engineers details the AI-based methodologies known as: Knowledge-Based Expert Systems (KBES); Design Synthesis; Design Critiquing; and Case-Based Reasoning. KBES are the most popular AI-based tools and have been successfully applied to planning, diagnosis, classification, monitoring, and design problems. Case studies are provided with problems in engineering design for better understanding of the problem-solving models using the four methodologies in an integrated software environment.Throughout the book, examples are given so that students and engineers can acquire skills in the use of AI-based methodologies for application to practical problems ranging from diagnosis to planning, design, and construction and manufacturing in various disciplines of engineering.Artificial Intelligence and Expert Systems for Engineers is a must-have reference for students, teachers, research scholars, and professionals working in the area of civil engineering design in particular and engineering design in general.
Artificial Intelligence and Green Computing: Proceedings of the International Conference on Artificial Intelligence and Green Computing (Lecture Notes in Networks and Systems #806)
by Najlae Idrissi Abdellatif Hair Mohamed Lazaar Youssef Saadi Mohammed Erritali Said El KafhaliThe main objective of this book is to explore the synergy between cutting-edge AI technologies and environmentally conscious practices through collecting best selected research papers presented at the International Conference on Artificial Intelligence and Green Computing (ICAIGC 2023), which took place from March 15 to 17, 2023, in Beni Mellal, Morocco. Within the pages of this book, readers find a wealth of research findings, survey works, and practical experiences aimed at fostering a comprehensive understanding of the pivotal role AI plays in various fields, including agriculture, health care, IT, and more. It highlights both the opportunities presented by the widespread usage of AI and the challenges associated with its continued advancement. As a result, the book has been divided into three parts: 1)- AI for multimedia processing, 2)- AI for distributed computing, and 3)- AI applications. The book serves as a comprehensive resource that brings together on-going research and practical experiences from the ICAIGC 2023 conference. It strives to deepen the understanding of the essential role AI plays in multiple fields. Whether you are an AI enthusiast, researcher, or practitioner, the insights contained within these pages expand your horizons and inspire further exploration of AI's potential in shaping a greener and more technologically advanced future.
Artificial Intelligence and Hardware Accelerators
by Ashutosh Mishra Jaekwang Cha Hyunbin Park Shiho KimThis book explores new methods, architectures, tools, and algorithms for Artificial Intelligence Hardware Accelerators. The authors have structured the material to simplify readers’ journey toward understanding the aspects of designing hardware accelerators, complex AI algorithms, and their computational requirements, along with the multifaceted applications. Coverage focuses broadly on the hardware aspects of training, inference, mobile devices, and autonomous vehicles (AVs) based AI accelerators
Artificial Intelligence and Heuristics for Enhanced Food Security (International Series in Operations Research & Management Science #331)
by Chandrasekar VuppalapatiThis book introduces readers to advanced data science techniques for signal mining in connection with agriculture. It shows how to apply heuristic modeling to improve farm-level efficiency, and how to use sensors and data intelligence to provide closed-loop feedback, while also providing recommendation techniques that yield actionable insights. The book also proposes certain macroeconomic pricing models, which data-mine macroeconomic signals and the influence of global economic trends on small-farm sustainability to provide actionable insights to farmers, helping them avoid financial disasters due to recurrent economic crises. The book is intended to equip current and future software engineering teams and operations research experts with the skills and tools they need in order to fully utilize advanced data science, artificial intelligence, heuristics, and economic models to develop software capabilities that help to achieve sustained food security for future generations.
Artificial Intelligence and Heuristics for Smart Energy Efficiency in Smart Cities: Case Study: Tipasa, Algeria (Lecture Notes in Networks and Systems #361)
by Mustapha HattiThis book emphasizes the role of micro-grid systems and connected networks for the strategic storage of energy through the use of information and communication techniques, big data, the cloud, and meta-heuristics to support the greed for artificial intelligence techniques in data and the implementation of global strategies to meet the challenges of the city in the broad sense. The intelligent management of renewable energy in the context of the energy transition requires the use of techniques and tools based on artificial intelligence (AI) to overcome the challenges of the intermittence of resources and the cost of energy. The advent of the smart city makes an increased call for the integration of artificial intelligence and heuristics to meet the challenge of the increasing migration of populations to the city, in order to ensure food, energy, and environmental security of the citizen of the city and his well-being. This book is intended for policymakers, academics, practitioners, and students. Several real cases are exposed throughout the book to illustrate the concepts and methods of the networks and systems presented. This book proposes the development of new technological innovations—mainly ICT—the concept of “Smart City” appears as a means of achieving more efficient and sustainable cities. The overall goal of the book is to develop a comprehensive framework to help public and private stakeholders make informed decisions on smart city investment strategies and develop skills for assessment and prioritization, including resolution of difficulties with deployment and reproducibility.
Artificial Intelligence and Inclusive Education: Speculative Futures and Emerging Practices (Perspectives on Rethinking and Reforming Education)
by Jeremy Knox Yuchen Wang Michael GallagherThis book brings together the fields of artificial intelligence (often known as A.I.) and inclusive education in order to speculate on the future of teaching and learning in increasingly diverse social, cultural, emotional, and linguistic educational contexts. This book addresses a pressing need to understand how future educational practices can promote equity and equality, while at the same time adopting A.I. systems that are oriented towards automation, standardisation and efficiency. The contributions in this edited volume appeal to scholars and students with an interest in forming a critical understanding of the development of A.I. for education, as well as an interest in how the processes of inclusive education might be shaped by future technologies. Grounded in theoretical engagement, establishing key challenges for future practice, and outlining the latest research, this book offers a comprehensive overview of the complex issues arising from the convergence of A.I. technologies and the necessity of developing inclusive teaching and learning.To date, there has been little in the way of direct association between research and practice in these domains: A.I. has been a predominantly technical field of research and development, and while intelligent computer systems and ‘smart’ software are being increasingly applied in many areas of industry, economics, social life, and education itself, a specific engagement with the agenda of inclusion appears lacking. Although such technology offers exciting possibilities for education, including software that is designed to ‘personalise’ learning or adapt to learner behaviours, these developments are accompanied by growing concerns about the in-built biases involved in machine learning techniques driven by ‘big data’.