Intelligent Technologies and Robotics

This book addresses the key problems that computational intelligence aims to solve, including (i) the involved computational process might be too complex for mathematical reasoning; (ii) it might contain some uncertainties during the process, or (iii) by nature, the computational process is a randomly determined one (heuristic). The contributors make use of methods that are close to the human's way of reasoning, that is, available information might be inexact or incomplete, yet it would be able to produce controlled actions in an adaptive way. Approaches presented in the book include swarm intelligence, artificial immune systems, image processing, data mining, natural language processing, text mining, and other solutions involving artificial intelligence methodologies.  

This book presents select papers from the 2nd EAI International Conference on Computational Intelligence and Communications (CICom 2021). The papers reveal recent advances in the broader domains of Computational Intelligence including (1) automation, control, and intelligent transportation system; (2) big data, Internet of Things, and smart cities; (3) wireless communication systems and cyber security and; (4) human/brain-computer interfaces, and image and pattern recognition. The book demonstrates complex real-world problems in which mathematical or traditional modelling are not the preferred solution and posits alternative solutions. This collection of applications demonstrates the important advances in computational intelligence. The chapters present various ideas that will benefit researchers, graduate students and engineers in this domain.

This book presents the most recent innovations, trends, and challenges in several aspects of Industry 4.0, including the key technologies and business impacts. The book is relevant to a variety of stakeholders due to Industry 4.0’s broad impact in many fields.  Topics include digital workplace solutions for employee engagement, entrepreneurship and innovation, and Blockchain for business security. The authors cover Industry 4.0 both from a theoretical and applicable standpoint.

Artificial Intelligence (AI) technologies hold immense promise for developing countries by offering innovative solutions to longstanding challenges. By leveraging AI in health care, education, economic development, infrastructure, and resource management, these countries can potentially leapfrog traditional development stages and improve the quality of life for their populations. However, it's essential to approach AI deployment with ethical considerations to ensure that the technology serves the best interests of these communities and thus to maximize the expected benefits.

The I2COMSAPP'24 "International Conference on Artificial Intelligence and its Applications in the Age of Digital Transformation" aims to provide an excellent opportunity to gather experts, researchers, practitioners, and innovators from various fields to explore the latest advancements, challenges, and practical implementations of artificial intelligence and machine learning (ML) technologies. Moreover, it aims to foster knowledge sharing, collaboration, and networking among professionals who are driving responsible and innovative use of AI and leveraging real-world applications for the betterment of society and industries.

Artificial Intelligence (AI) technologies hold immense promise for developing countries by offering innovative solutions to longstanding challenges. By leveraging AI in health care, education, economic development, infrastructure, and resource management, these countries can potentially leapfrog traditional development stages and improve the quality of life for their populations. However, it's essential to approach AI deployment with ethical considerations to ensure that the technology serves the best interests of these communities and thus to maximize the expected benefits.

The I2COMSAPP'24 "International Conference on Artificial Intelligence and its Applications in the Age of Digital Transformation" aims to provide an excellent opportunity to gather experts, researchers, practitioners, and innovators from various fields to explore the latest advancements, challenges, and practical implementations of artificial intelligence and machine learning (ML) technologies. Moreover, it aims to foster knowledge sharing, collaboration, and networking among professionals who are driving responsible and innovative use of AI and leveraging real-world applications for the betterment of society and industries.

This book provides a unique formal foundation for the development of statistical tools useful in the exploration of observational and experimental data related to embodied cognition. The asymptotic limit theorems of information and control theories can be used to construct statistical tools analogous to -- but different from -- regression models for the study of the often highly punctuated cognitive phenomena embedded in and hence influenced by a surrounding ecosystem of which the phenomena are themselves part. The book builds probability models based on those theorems that incorporate embodiment at a number of scales and levels of organization, ranging from the effects of stress on the immune system within a higher organism, through institutional (and machine) cognition under challenge from adversaries, to the failure of public health institutions under pathogen challenge. In distinct contrast to the existing literature, many detailed, worked-out examples provide templates for sophisticated readers to build their own model/tool constructs.

This book provides a comprehensive exploration of the transformative impact of AI technologies across diverse fields. From revolutionizing healthcare diagnostics and advancing natural language processing for low-resource languages to enhancing software development and promoting environmental sustainability, this book explores the cutting-edge advancements and practical applications of generative AI and large language models (LLMs). With a focus on both opportunities and challenges, the book examines the architectural challenges of transformer-based models, the ethical implications of AI, and the importance of language-specific adaptations, particularly for low-resource languages like Arabic. It also highlights the role of AI in code development, multimodal applications, and its integration with intellectual property frameworks. This book is an essential resource for researchers, practitioners, and policymakers seeking to understand and harness the potential of AI to drive innovation and global progress.

The third edition of "Model Predictive Control" provides a thorough introduction to theoretical and practical aspects of the most commonly used MPC strategies. It bridges the gap between the powerful but often abstract techniques of control researchers and the more empirical approach of practitioners. Its chapter structure has been completely overhauled to make the different "flavours" of MPC more easily findable and accessible.  All of the material is thoroughly updated for the third edition with stochastic and distributed MPC making their debuts. New exercises, examples and case-studies have also been added throughout and MATLAB® programs simulating examples and assisting with design can be downloaded. This book gives the student access to a widely-used form of control which is required by many industrial careers.

This book presents a diverse collection of cutting-edge research from the 6th Mediterranean Conference on Pattern Recognition and Artificial Intelligence (MedPRAI24). Covering a wide range of topics, it explores the latest advancements in AI-driven applications, including machine learning for healthcare, cybersecurity, historical document analysis, and digital media. Readers will find studies on AI in social sciences, literature, and governance, alongside technical innovations in image processing, speech analysis, and deep learning. With interdisciplinary contributions spanning engineering, humanities, and political sciences, this volume provides valuable insights into the evolving role of artificial intelligence across multiple domains.

This book provides a practical and rewarding path for early to mid-career professionals of all disciplines (STEM and non-STEM) to develop the intentional mental practice of Systems Thinking together with Rigorous Methods that improve the way we view, contemplate, approach and deal with complex challenges. It teaches a concise and easy to follow set of practice–derived generic Systems Principles that offer a superior alternative to the linear compartmentalized thinking that unfortunately dominates our industry, education, language, and culture today. The book has 3 main parts: Part I introduces systems thinking and covers why thinking of  problems as systems is essential. Part II teaches the Systems Thinking Philosophy and how to use the Systems Principles to guide the way we see, understand, behave, act, and utilize Rigorous Methods to augment dealing with individual and organizational challenges. Part III exposes a range practical applications of Rigorous Methods that apply the Systems Principles particularly the Model-Based Systems Thinking method that integrates System Dynamics, Architectural, Agent-Based, Stochastic, Machine Learning and Artificial Intelligence modeling methods.  The reader will be able to classify good and bad systems thinking culture, understand major systemic successes and failures.   The main theme of this book is Systems Thinking Philosophy based on System Principles and reliable Methods that are likely to stay in demand over time.

This book captures the dynamic spirit of technological advancement and interdisciplinary collaboration showcased at the sixth edition of the conference. This second volume of the proceedings from the VI International Conference on Computer Science, Electronics and Industrial Engineering (CSEI 2024) presents a wide-ranging collection of innovative research under the theme “Emerging Technologies in Communication, Manufacturing, and Renewable Energy Systems.” 

The contributions span several key areas where digital transformation is reshaping traditional practices. Educational informatics features prominently, demonstrating how virtual reality, augmented reality, and artificial intelligence are creating more inclusive and personalized learning environments. These developments are particularly impactful in areas such as chemistry education, traffic safety training, and the support of learners with special educational needs.

Further chapters explore the integration of cyber-physical systems and Internet of Things technologies in applications ranging from smart manufacturing to precision agriculture. Healthcare innovation also finds its place, with research on early detection of neurodegenerative diseases and advanced physiological signal processing, reflecting the convergence of digital intelligence and human wellbeing.

The book also delves into transformative approaches in production and industrial engineering. From sustainable agro-industrial processes to occupational safety under the Industry 5.0 paradigm, authors explore how human-centered and environmentally conscious design is becoming a cornerstone of technological development. Software innovations and digital tools highlight the importance of usability and efficiency, with contributions such as gamified rehabilitation systems and agricultural management platforms.

Finally, advances in automated manufacturing and control systems reveal how robotics and real-time monitoring are driving efficiency and resilience across sectors—from agricultural automation to aerospace training systems.

This book applies the powerful asymptotic limit theorems of information and control theories to understanding the dynamics of dysfunction in cognitive cultural artifacts encompassing individual minds, small social groupings, institutions, machine systems, and their many critical composites. A particular focus is on attempts to build ‘intelligent machines’ that would supposedly rival or surpass human minds. All such efforts are blindsided by the reality that all such machines are cultural artifacts of those who build them, closely reflecting cultural priorities and blindness, and that intelligent entities lacking the feedback of high-speed embodiment must endure exaggerated levels of failure by fabulation and hallucination. A principal feature is the detailed working-out of many probability models that can serve as the foundation of statistical tools for the analysis of real-time, real-world data on cognitive failure across a broad range of modes, scales, and levels of organization.

This book introduces a novel integration of Federated Learning with the vision of Healthcare 5.0 to enable secure, adaptive, and intelligent health systems. It presents cutting-edge frameworks that support decentralized model training across medical institutions while preserving patient privacy and ensuring compliance with data regulations.

Focusing on real-world use cases, such as predictive diagnostics, edge-based patient monitoring, personalized medicine, and surgical robotics, it bridges theoretical advances with practical implementations. This book provides deep insights into the design of scalable, privacy-preserving artificial intelligence infrastructures suited for cross-institutional collaboration.

The First International Conference on Generative AI: Current Research, Industry Trends, and Innovations (FICAI2025) proceedings will provide a comprehensive collection of the latest research and developments in the field of artificial intelligence, with a particular focus on AI & Generative AI. The proceedings will encompass a wide range of topics, including machine learning, ethical AI, and practical applications in sectors such as healthcare, engineering, and cybersecurity.This collection aims to document the significant contributions of academic and industry researchers who are driving the advancement of AI technologies. Each paper presents new methodologies, theoretical frameworks, or practical implementations of AI systems designed to solve real-world problems.With a global lineup of authors and contributors, the FICAI2025 proceedings will also highlight case studies and the latest trends from across industries, offering valuable insights for both AI researchers and professionals in the field.

This book showcases an endeavor to delve into the fusion of artificial intelligence (AI) and the Internet of Things (IoT) within the healthcare domain.

The healthcare sector is currently experiencing a shift fueled by technological advancements and a heightened focus on providing tailored, efficient and impactful care to individuals. AI and IoT have emerged as facilitators of this evolution presenting opportunities to elevate patient results streamline operations and enhance decision-making within healthcare environments.

This publication unites an array of viewpoints from experts in healthcare, technology and research domains. Through an array of enlightening chapters readers will embark on a journey exploring the applications, hurdles and consequences of merging AI with IoT in healthcare contexts. From analytics and remote monitoring to treatment suggestions and operational enhancements the potentials offered by AI and IoT is both captivating and revolutionary.

As editors overseeing this volume’s creation we take pride in presenting an assemblage of contributions that mirror the research findings, innovations and optimal practices in healthcare technology.

Our aim is to encourage readers to engage in thinking, creativity and teamwork when considering the impact of integrating AI with IoT on enhancing patient care and healthcare services.

The authors explore various aspects of information processing for the design of service systems, efficient management, secure storage, and transmission. In addition, the subline provides knowledge and practice in decentralized ICT technologies, including those based on blockchain. The aim of this book is to analyze and develop methods of building decentralized private databases without the presence of a trusted party, methods of data processing in encrypted form to ensure the confidentiality of information, and accessibility of the corresponding fragment of the original or transformed data. In this book it is also relevant to research methods and protocols routing in infocommunication networks, which provides load balancing in the network, and analysis of intrusion detection methods based on analysis of signatures and anomalies in network behavior (state changes) based on machine learning and fractal analysis methods.

This book is a unique collection of advanced research on natural, human-made, and coupled human–natural systems. The contributors analyze the current state of knowledge, address methodological challenges, and explore engaging cases. The chapters demonstrate the balanced disciplinary strength and discuss interdisciplinary perspectives. The authors undertake a holistic and spatially integrative analysis to understand the sustainability of environmental, economic, and social systems, emphasizing the coupled nature of such systems.

The book has seven sections: (1) Advances in Natural and Coupled Human–Natural Systems Research; (2) Economic Systems in the Age of Digital Changes and Unstable Environments; (3) Sustainable Social Systems, Migration Flows, and Social Cohesion; (4) Taking Action for Greater Security and Effective Partnerships for Sustainable Development; (5) Systemic Challenges and Changes in Education Systems in Russia and Around the Globe; (6) Advances in Cultural Traditions and Innovation, Development Barriers, and Social Stability; (7) Human Health and Well-being: Taking Action for Sustainable Development.

Written by scholars and practitioners from multiple fields of knowledge, the book is designed for a broader audience interested in the following research areas: systems research and thinking, sustainability research and thinking, system dynamics, management of complexity, decision analysis, organization theory, governance, natural resources, environmental studies, economic development, social policies, cleaner production, innovation, cultural studies, and sustainable practices.

This book is dedicated to all those interested in the application of computational intelligence techniques for decision-making in uncertain environments. The book is organized into four parts. The first part groups together four works related to conversational systems and decision-making using generative artificial intelligence. The second part includes four articles associated with decision-making in project-oriented environments. The third part includes three works related to decision-making in human health environments and decision-making in sports training. The fourth part of the book contains three articles associated with business decision-making.

This book combines different artificial intelligence techniques for solving decision-making problems, among which the following stand out: generative artificial intelligence, linguistic data summarization techniques, neutrosophic theory, computing with words, among other techniques. The techniques proposed in the book aim to simulate human tolerance in decision-making processes in environments with uncertainty and imprecision.

The authors of the book stand out for their extensive experience in the development of basic and applied applications of computational intelligence. The authors Pedro Y. Piñero Pérez, Iliana Pérez Pupo, Janusz Kacprzyk, and Rafael E. Bello Pérez have published several books associated with artificial intelligence and applied computational intelligence. They continue to work on fundamental and applied research on different artificial intelligence techniques to assist decision-making in different areas of knowledge.

The authors thank all the engineers, professors, and researchers without whose efforts this book could not have been written.