Contemporary Developments In Agricultural Cyber Physical Systems

The cultivation of crops plays a very important role in agriculture. However, proper maintenance and management are required. Lack of such management would lead to crop loss or reduced crop yields. Hence, the ability to detect and identify diseases on infected crops is a problem of increasing concern. Real-time disease detection systems do not exist in the current agricultural landscape. It requires tremendous amounts of work, expertise in plant diseases, and excessive processing time. Using precision agriculture techniques, combined with AI, a great deal of work is reduced. Contemporary Developments in Agricultural Cyber-Physical Systems provides a forum for researchers and practitioners to exchange ideas and achieve progress in cyber-physical systems by highlighting agricultural applications, advances, and research challenges. The book features chapters on all aspects pertaining to this multidisciplinary paradigm, in particular in its application to sustainable agriculture developments. Covering topics such as automation, monitoring systems, and smart agriculture, this premier reference source is an excellent resource for scientists, healthcare professionals, data analysts, computer scientists, students and educators of higher education, researchers, and academicians.

The cultivation of crops plays a very important role in agriculture. However, proper maintenance and management are required. Lack of such management would lead to crop loss or reduced crop yields. Hence, the ability to detect and identify diseases on infected crops is a problem of increasing concern. Real-time disease detection systems do not exist in the current agricultural landscape. It requires tremendous amounts of work, expertise in plant diseases, and excessive processing time. Using precision agriculture techniques, combined with AI, a great deal of work is reduced. Contemporary Developments in Agricultural Cyber-Physical Systems provides a forum for researchers and practitioners to exchange ideas and achieve progress in cyber-physical systems by highlighting agricultural applications, advances, and research challenges. The book features chapters on all aspects pertaining to this multidisciplinary paradigm, in particular in its application to sustainable agriculture developments. Covering topics such as automation, monitoring systems, and smart agriculture, this premier reference source is an excellent resource for scientists, healthcare professionals, data analysts, computer scientists, students and educators of higher education, researchers, and academicians.

The rapid proliferation of connected devices in our daily lives, from smart homes to industrial sensors, has led to an explosion of data that requires processing before it is useful to experts. However, modern devices often have limited resources, making it challenging to decode and utilize this data effectively. Additionally, the need for real-time decision-making further complicates this issue, as traditional data processing methods take far too long to be able to keep up with the required volume and speed. Developments Towards Next Generation Intelligent Systems for Sustainable Development offers a comprehensive solution to these challenges by integrating novel technologies such as AI, edge computing, federated learning, quantum computing, and more. The book shows how intelligent systems can maximize computing power by leveraging these technologies to process large volumes of data efficiently and autonomously and make real-time decisions. The proposed architectures and frameworks focus on real-time analysis, faster decision-making, enhanced privacy, and efficient data processing.

Technological Advancements in Data Processing for Next Generation Intelligent Systems presents an in-depth exploration of cutting-edge data processing technologies that drive the development of next-generation intelligent systems in the context of the digital transformation era. This comprehensive book delves into the role data plays as a critical asset for organizations across diverse industries, and how recent technological breakthroughs have unlocked unprecedented potential for handling vast data volumes and real-time analysis. The book begins by providing a thorough overview of novel technologies such as artificial intelligence (AI) or machine learning (ML), edge computing, federated learning, quantum computing, and more. These revolutionary technologies, when integrated with big data frameworks, in-memory computing, and AI/ML algorithms, have transformed data processing capabilities, enabling the creation of intelligent systems that fuel innovation, optimize operations, and deliver personalized experiences. The ultimate aim of this integration is to empower devices with the ability to make autonomous intelligent decisions, maximizing computing power. This book serves as a valuable resource for research scholars, academicians, and industry professionals working towards the future advancement of optimized intelligent systems and intelligent data processing approaches. The chapters encompass a wide range of topics, including architecture and frameworks for intelligent systems, applications in diverse domains, cloud-based solutions, quantum processing, federated learning, in-memory data processing, real-time stream processing, trustworthy AI for Internet of Things (IoT) sensory data, and more.

The Handbook of Research on AI and ML for Intelligent Machines and Systems offers a comprehensive exploration of the pivotal role played by artificial intelligence (AI) and machine learning (ML) technologies in the development of intelligent machines. As the demand for intelligent machines continues to rise across various sectors, understanding the integration of these advanced technologies becomes paramount. While AI and ML have individually showcased their capabilities in developing robust intelligent machine systems and services, their fusion holds the key to propelling intelligent machines to a new realm of transformation. By compiling recent advancements in intelligent machines that rely on machine learning and deep learning technologies, this book serves as a vital resource for researchers, graduate students, PhD scholars, faculty members, scientists, and software developers. It offers valuable insights into the key concepts of AI and ML, covering essential security aspects, current trends, and often overlooked perspectives that are crucial for achieving comprehensive understanding. It not only explores the theoretical foundations of AI and ML but also provides guidance on applying these techniques to solve real-world problems. Unlike traditional texts, it offers flexibility through its distinctive module-based structure, allowing readers to follow their own learning paths.

In the digital transformation era, integrating business intelligence and data analytics has become critical for the growth and sustainability of industrial organizations. However, with this technological evolution comes the pressing need for robust cybersecurity measures to safeguard valuable business intelligence from security threats. Strengthening Industrial Cybersecurity to Protect Business Intelligence delves into the theoretical foundations and empirical studies surrounding the intersection of business intelligence and cybersecurity within various industrial domains. This book addresses the importance of cybersecurity controls in mitigating financial losses and reputational damage caused by cyber-attacks. The content spans a spectrum of topics, including advances in business intelligence, the role of artificial intelligence in various business applications, and the integration of intelligent systems across industry 5.0. Ideal for academics in information systems, cybersecurity, and organizational science, as well as government officials and organizations, this book serves as a vital resource for understanding the intricate relationship between business intelligence and cybersecurity. It is equally beneficial for students seeking insights into the security implications of digital transformation processes for achieving business continuity.

Cyber-attacks significantly impact all sectors of the economy, reduce public confidence in e-services, and threaten the development of the economy using information and communication technologies. The security of information systems and electronic services is crucial to each citizen's social and economic well-being, health, and life. As cyber threats continue to grow, developing, introducing, and improving defense mechanisms becomes an important issue. Cyber Security Policies and Strategies of the World's Leading States is a comprehensive book that analyzes the impact of cyberwarfare on world politics, political conflicts, and the identification of new types of threats. It establishes a definition of civil cyberwarfare and explores its impact on political processes. This book is essential for government officials, academics, researchers, non-government organization (NGO) representatives, mass-media representatives, business sector representatives, and students interested in cyber warfare, cyber security, information security, defense and security, and world political issues. With its comprehensive coverage of cyber security policies and strategies of the world's leading states, it is a valuable resource for those seeking to understand the evolving landscape of cyber security and its impact on global politics. It provides methods to identify, prevent, reduce, and eliminate existing threats through a comprehensive understanding of cyber security policies and strategies used by leading countries worldwide.

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.