Bui Thanh Hung – författare

In a world increasingly driven by technology, this book explores the intersection of artificial intelligence (AI), IoT, and Cloud Computing and women''s safety, highlighting the transformative potential of technology in safeguarding women''s well-being in the physical and the digital world. As the safety and security industry embraces technological advancements, the need for inclusive and gender-centric solutions has become increasingly evident. This reference book delves into this critical area, showcasing the development of AI, IoT, and Cloud applications specifically tailored to address the unique safety challenges faced by women.

• Provides a comprehensive exploration of how AI and related technologies are reshaping the future of women''s safety.

• Emphases the utilisation of AI to tackle the specific challenges women encounter in various contexts.

• Introduces innovative solutions such as wearable technology, AI-powered surveillance systems, and mobile applications designed for emergency responses.

• Discusses ethical implications of deploying technology for personal security and navigates the evolving legal landscape surrounding data privacy.

• Bridges the gap between theoretical discussions and practical implementations, offering a guide to developing technology for the improvement of women''s safety.

It is an invaluable resource for professionals and researchers interested in the transformative role of AI, IoT, and Cloud in shaping the future of women''s safety.

In a world increasingly driven by technology, this book explores the intersection of artificial intelligence (AI), IoT, and Cloud Computing and women''s safety, highlighting the transformative potential of technology in safeguarding women''s well-being in the physical and the digital world. As the safety and security industry embraces technological advancements, the need for inclusive and gender-centric solutions has become increasingly evident. This reference book delves into this critical area, showcasing the development of AI, IoT, and Cloud applications specifically tailored to address the unique safety challenges faced by women.

• Provides a comprehensive exploration of how AI and related technologies are reshaping the future of women''s safety.

• Emphases the utilisation of AI to tackle the specific challenges women encounter in various contexts.

• Introduces innovative solutions such as wearable technology, AI-powered surveillance systems, and mobile applications designed for emergency responses.

• Discusses ethical implications of deploying technology for personal security and navigates the evolving legal landscape surrounding data privacy.

• Bridges the gap between theoretical discussions and practical implementations, offering a guide to developing technology for the improvement of women''s safety.

It is an invaluable resource for professionals and researchers interested in the transformative role of AI, IoT, and Cloud in shaping the future of women''s safety.

COMPUTATIONAL INTELLIGENCE IN SUBSTAINABLE RELIABILITY ENGINEERING

The book is a comprehensive guide on how to apply computational intelligence techniques for the optimization of sustainable materials and reliability engineering.

This book focuses on developing and evolving advanced computational intelligence algorithms for the analysis of data involved in reliability engineering, material design, and manufacturing to ensure sustainability. Computational Intelligence in Sustainable Reliability Engineering unveils applications of different models of evolutionary algorithms in the field of optimization and solves the problems to help the manufacturing industries. Some special features of this book include a comprehensive guide for utilizing computational models for reliability engineering, state-of-the-art swarm intelligence methods for solving manufacturing processes and developing sustainable materials, high-quality and innovative research contributions, and a guide for applying computational optimization on reliability and maintainability theory. The book also includes dedicated case studies of real-life applications related to industrial optimizations.

Audience

Researchers, industry professionals, and post-graduate students in reliability engineering, manufacturing, materials, and design.

COMPUTATIONAL INTELLIGENCE IN SUBSTAINABLE RELIABILITY ENGINEERING

The book is a comprehensive guide on how to apply computational intelligence techniques for the optimization of sustainable materials and reliability engineering.

This book focuses on developing and evolving advanced computational intelligence algorithms for the analysis of data involved in reliability engineering, material design, and manufacturing to ensure sustainability. Computational Intelligence in Sustainable Reliability Engineering unveils applications of different models of evolutionary algorithms in the field of optimization and solves the problems to help the manufacturing industries. Some special features of this book include a comprehensive guide for utilizing computational models for reliability engineering, state-of-the-art swarm intelligence methods for solving manufacturing processes and developing sustainable materials, high-quality and innovative research contributions, and a guide for applying computational optimization on reliability and maintainability theory. The book also includes dedicated case studies of real-life applications related to industrial optimizations.

Audience

Researchers, industry professionals, and post-graduate students in reliability engineering, manufacturing, materials, and design.

This book comprehensively explains how to use various fuzzy-based models to solve real-time industrial challenges.

The book provides information about fundamental aspects of the field and explores the myriad applications of fuzzy logic techniques and methods. It presents basic conceptual considerations and case studies of applications of fuzzy computation. It covers the fundamental concepts and techniques for system modeling, information processing, intelligent system design, decision analysis, statistical analysis, pattern recognition, automated learning, system control, and identification. The book also discusses the combination of fuzzy computation techniques with other computational intelligence approaches such as neural and evolutionary computation.

Audience

Researchers and students in computer science, artificial intelligence, machine learning, big data analytics, and information and communication technology.

This book comprehensively explains how to use various fuzzy-based models to solve real-time industrial challenges.

The book provides information about fundamental aspects of the field and explores the myriad applications of fuzzy logic techniques and methods. It presents basic conceptual considerations and case studies of applications of fuzzy computation. It covers the fundamental concepts and techniques for system modeling, information processing, intelligent system design, decision analysis, statistical analysis, pattern recognition, automated learning, system control, and identification. The book also discusses the combination of fuzzy computation techniques with other computational intelligence approaches such as neural and evolutionary computation.

Audience

Researchers and students in computer science, artificial intelligence, machine learning, big data analytics, and information and communication technology.

The book explores the fundamental principles and transformative advancements in cutting-edge algorithmic technologies, detailing their application and impact on revolutionizing healthcare.

This book provides an in-depth account of how technologies such as artificial intelligence (AI), machine learning (ML), and the Internet of Things (IoT) are reshaping healthcare, transitioning from traditional diagnostic and treatment approaches to data-driven solutions that improve predictive accuracy and patient outcomes. The text also addresses the challenges and considerations associated with adopting these technologies, including ethical implications, data security concerns, and the need for human-centered approaches in algorithmic medicine.

After introducing digital twin technology and its potential to enhance healthcare delivery, the book examines the broader effects of digital technology on the healthcare system. Subsequent chapters explore topics such as innovations in medical imaging, predictive analytics for improved patient outcomes, and deep learning algorithms for brain tumor detection. Other topics include generative adversarial networks (GANs), convolutional neural networks (CNNs), smart wearables for remote patient monitoring, effective IoT solutions, telemedicine advancements, and blockchain security for healthcare systems. The integration of biometric systems driven by AI, securing cyber-physical systems in healthcare, and digitizing wellness through electronic health records (EHRs) and electronic medical records (EMRs) are also discussed. The book concludes with an extensive case study comparing the impacts of various healthcare applications, offering insights and encouraging further research and innovation in this dynamic field.

Audience

This book is suitable for academicians and professionals in health informatics, bioinformatics, biomedical science and engineering, artificial intelligence, as well as clinicians, IT specialists, and policymakers in healthcare.

The book explores the fundamental principles and transformative advancements in cutting-edge algorithmic technologies, detailing their application and impact on revolutionizing healthcare.

This book provides an in-depth account of how technologies such as artificial intelligence (AI), machine learning (ML), and the Internet of Things (IoT) are reshaping healthcare, transitioning from traditional diagnostic and treatment approaches to data-driven solutions that improve predictive accuracy and patient outcomes. The text also addresses the challenges and considerations associated with adopting these technologies, including ethical implications, data security concerns, and the need for human-centered approaches in algorithmic medicine.

After introducing digital twin technology and its potential to enhance healthcare delivery, the book examines the broader effects of digital technology on the healthcare system. Subsequent chapters explore topics such as innovations in medical imaging, predictive analytics for improved patient outcomes, and deep learning algorithms for brain tumor detection. Other topics include generative adversarial networks (GANs), convolutional neural networks (CNNs), smart wearables for remote patient monitoring, effective IoT solutions, telemedicine advancements, and blockchain security for healthcare systems. The integration of biometric systems driven by AI, securing cyber-physical systems in healthcare, and digitizing wellness through electronic health records (EHRs) and electronic medical records (EMRs) are also discussed. The book concludes with an extensive case study comparing the impacts of various healthcare applications, offering insights and encouraging further research and innovation in this dynamic field.

Audience

This book is suitable for academicians and professionals in health informatics, bioinformatics, biomedical science and engineering, artificial intelligence, as well as clinicians, IT specialists, and policymakers in healthcare.

This book constitutes papers from the 1st International Conference on Artificial Intelligence and Digital Twin Technology, IconAIDTT 2023, held in Sivakasi, India, April 26–28, 2023.

The 12 full papers and the 1 short paper included in this volume were carefully reviewed and selected from 41 submissions. The papers cover the following topics: Advanced AI and IoT Solutions for Environmental, Healthcare, and Security Challenges; Deep Learning Techniques for Wireless networks and Data Analysis.

This book gathers selected high-quality research papers presented at the Second International Conference on Intelligent System (ICIS 2023), organized by Industrial University of Ho Chi Minh City, Vietnam during September 29–30, 2023. It discusses high-quality and cutting-edge research in the areas of informatics, intelligent systems, and smart technologies and applications. The book is a collection of the latest research articles in intelligent control, artificial intelligence, neural networks, knowledge discovery, decision support systems, soft computing, data mining, and ontologies, machine learning, intelligent measurement, and other related fields.