Vania Vieira Estrela – författare

Artificial Intelligence (A) is transforming transportation by enabling intelligent, adaptive, and data-driven mobility systems capable of addressing growing urbanization and sustainability challenges. By leveraging machine learning, computer vision, natural language processing, and advanced data analytics, AI enhances traffic prediction, autonomous navigation, safety monitoring, and infrastructure management. These technologies allow transportation networks to respond in real time to changing conditions, reduce congestion and emissions, improve road safety, and optimize resource utilization. AI also plays a central role in integrating vehicles, users, and infrastructure into cohesive smart mobility ecosystems. As transportation systems evolve toward automation, connectivity, and sustainability, AI emerges as a foundational enabler for resilient, efficient, and future-ready transportation networks worldwide.

The book offers a comprehensive and forward-looking examination of AI’s expanding role in modern transportation. The book spans foundational principles and advanced innovations, beginning with intelligent transportation systems and progressing to specialized areas such as AI-driven driving analytics, smart traffic control, and augmented-reality-based safety navigation. It further explores emerging frontiers including autonomous vehicle intelligence, edge-AI frameworks, 6G-enabled mobility, quantum computing, generative AI for infrastructure design, and robust vehicle-to-vehicle communication systems. By integrating theory, applications, and future trends, the book presents a holistic vision of how AI can build safer, smarter, and more sustainable transportation ecosystems while supporting the broader evolution of smart cities.

This book is designed for researchers, engineers, industry professionals, urban planners, policymakers, and advanced students engaged in transportation, artificial intelligence, and smart city development. It serves as both a practical reference and a visionary guide for those seeking to understand, design, and deploy AI-enabled transportation solutions, while supporting informed decision-making and innovation in global mobility systems.

Artificial Intelligence (A) is transforming transportation by enabling intelligent, adaptive, and data-driven mobility systems capable of addressing growing urbanization and sustainability challenges. By leveraging machine learning, computer vision, natural language processing, and advanced data analytics, AI enhances traffic prediction, autonomous navigation, safety monitoring, and infrastructure management. These technologies allow transportation networks to respond in real time to changing conditions, reduce congestion and emissions, improve road safety, and optimize resource utilization. AI also plays a central role in integrating vehicles, users, and infrastructure into cohesive smart mobility ecosystems. As transportation systems evolve toward automation, connectivity, and sustainability, AI emerges as a foundational enabler for resilient, efficient, and future-ready transportation networks worldwide.

The book offers a comprehensive and forward-looking examination of AI’s expanding role in modern transportation. The book spans foundational principles and advanced innovations, beginning with intelligent transportation systems and progressing to specialized areas such as AI-driven driving analytics, smart traffic control, and augmented-reality-based safety navigation. It further explores emerging frontiers including autonomous vehicle intelligence, edge-AI frameworks, 6G-enabled mobility, quantum computing, generative AI for infrastructure design, and robust vehicle-to-vehicle communication systems. By integrating theory, applications, and future trends, the book presents a holistic vision of how AI can build safer, smarter, and more sustainable transportation ecosystems while supporting the broader evolution of smart cities.

This book is designed for researchers, engineers, industry professionals, urban planners, policymakers, and advanced students engaged in transportation, artificial intelligence, and smart city development. It serves as both a practical reference and a visionary guide for those seeking to understand, design, and deploy AI-enabled transportation solutions, while supporting informed decision-making and innovation in global mobility systems.

Comprehensive resource providing strategic defense mechanisms for malware, handling cybercrime, and identifying loopholes using artificial intelligence (AI) and machine learning (ML)

Applying Artificial Intelligence in Cybersecurity Analytics and Cyber Threat Detection is a comprehensive look at state-of-the-art theory and practical guidelines pertaining to the subject, showcasing recent innovations, emerging trends, and concerns as well as applied challenges encountered, and solutions adopted in the fields of cybersecurity using analytics and machine learning. The text clearly explains theoretical aspects, framework, system architecture, analysis and design, implementation, validation, and tools and techniques of data science and machine learning to detect and prevent cyber threats.

Using AI and ML approaches, the book offers strategic defense mechanisms for addressing malware, cybercrime, and system vulnerabilities. It also provides tools and techniques that can be applied by professional analysts to safely analyze, debug, and disassemble any malicious software they encounter.

With contributions from qualified authors with significant experience in the field, Applying Artificial Intelligence in Cybersecurity Analytics and Cyber Threat Detection explores topics such as:

Providing detailed coverage of a rapidly expanding field, Applying Artificial Intelligence in Cybersecurity Analytics and Cyber Threat Detection is an essential resource for a wide variety of researchers, scientists, and professionals involved in fields that intersect with cybersecurity, artificial intelligence, and machine learning.

Comprehensive resource providing strategic defense mechanisms for malware, handling cybercrime, and identifying loopholes using artificial intelligence (AI) and machine learning (ML)

Applying Artificial Intelligence in Cybersecurity Analytics and Cyber Threat Detection is a comprehensive look at state-of-the-art theory and practical guidelines pertaining to the subject, showcasing recent innovations, emerging trends, and concerns as well as applied challenges encountered, and solutions adopted in the fields of cybersecurity using analytics and machine learning. The text clearly explains theoretical aspects, framework, system architecture, analysis and design, implementation, validation, and tools and techniques of data science and machine learning to detect and prevent cyber threats.

Using AI and ML approaches, the book offers strategic defense mechanisms for addressing malware, cybercrime, and system vulnerabilities. It also provides tools and techniques that can be applied by professional analysts to safely analyze, debug, and disassemble any malicious software they encounter.

With contributions from qualified authors with significant experience in the field, Applying Artificial Intelligence in Cybersecurity Analytics and Cyber Threat Detection explores topics such as:

Providing detailed coverage of a rapidly expanding field, Applying Artificial Intelligence in Cybersecurity Analytics and Cyber Threat Detection is an essential resource for a wide variety of researchers, scientists, and professionals involved in fields that intersect with cybersecurity, artificial intelligence, and machine learning.

This book presents the proceedings of the 3rd Brazilian Technology Symposium (BTSym), which is a multi/trans/interdisciplinary event offering an excellent forum for presentations and discussions of the latest scientific and technological developments in various areas of research, with an emphasis on smart design and future technologies.