Shamik Tiwari – författare

Digital Twins for Sustainable Development covers digital twins for sustainability as a virtual representation of a physical system or environment, such as a building, city, or natural ecosystem and how they are used to support sustainable development and management practices. The book demonstrates how data from a variety of sources, such as sensors, satellite imagery, and other monitoring tools can be used for advanced analytics and modeling techniques to simulate the system's behavior over time. This allows researchers and professionals in computer science to manage complex systems and promote sustainable development and resource management practices.Overviews the use of digital twins and their applications for sustainable developmentHighlights methods and strategies that use digital twins to manage complex systemsContains case studies that illustrate the benefits of using digital twins, including how energy usage patterns can be analyzed and optimized to reduce energy waste and carbon emissions

Digital Twins for Sustainable Development covers digital twins for sustainability as a virtual representation of a physical system or environment, such as a building, city, or natural ecosystem and how they are used to support sustainable development and management practices. The book demonstrates how data from a variety of sources, such as sensors, satellite imagery, and other monitoring tools can be used for advanced analytics and modeling techniques to simulate the system's behavior over time. This allows researchers and professionals in computer science to manage complex systems and promote sustainable development and resource management practices. - Overviews the use of digital twins and their applications for sustainable development- Highlights methods and strategies that use digital twins to manage complex systems- Contains case studies that illustrate the benefits of using digital twins, including how energy usage patterns can be analyzed and optimized to reduce energy waste and carbon emissions

Artificial Intelligence (AI) has emerged as one of the most transformative technologies of the 21st century, revolutionizing fields such as finance, healthcare, security, and human-centered decision systems. As AI continues to evolve, its applications increasingly integrate machine learning, deep learning, cognitive sciences, and data-driven analytics. Artificial Intelligence Frontiers: Innovations, Challenges, and Applications presents a comprehensive compilation of cutting-edge research exploring new AI technologies, their applications, and implementation challenges.The book examines diverse AI applications across multiple domains. It begins with neural networks for financial risk assessment and decision-making, then explores multimodal AI systems that integrate vision, text, and speech to enhance machine cognition. Additional chapters address predictive modeling using Long Short-Term Memory networks and deep learning applications in computer vision, including road lane detection and deepfake detection.Beyond technical innovations, the book investigates AI's role in healthcare and social sciences, covering perinatal depression analysis and neurodevelopmental disorder diagnosis in India. These contributions demonstrate AI's potential for early detection, improved diagnostics, and data-driven healthcare interventions.Recognizing the growing importance of responsible AI, subsequent chapters address critical issues of transparency, explainability, privacy, and ethical governance. Discussions on explainable AI, trustworthy human-centric systems, and regulatory frameworks for data protection emphasize the essential balance between technological innovation and ethical accountability.By consolidating perspectives from researchers, practitioners, and scholars, this book provides readers with comprehensive insights into AI's transformative nature. It serves as an invaluable resource for students, researchers, and professionals seeking to understand the latest advances, current policies, and ethical considerations shaping AI's future.