Monika Sethi – författare

Integrated Smart Technologies for Sustainable Water Systems Using Computer Applications presents a comprehensive exploration of how cutting-edge computational technologies are revolutionizing water resource management. This multidisciplinary guide demonstrates the practical integration of artificial intelligence (AI), Internet of Things (IoT) systems, and emerging digital technologies to address critical challenges in hydrology, hydraulics, water quality, and smart infrastructure development.This book systematically examines the application of advanced technologies including AI, machine learning, IoT, blockchain, cloud and edge computing, and Geographic Information Systems across diverse water management scenarios. Through theoretical models, algorithmic approaches, and real-world case studies from both developed and developing countries, it illustrates key findings in AI-driven water demand and quality predictions, IoT-enabled real-time distribution network monitoring, blockchain applications for transparent water resource transactions, intelligent flood forecasting systems, automated irrigation methods, wastewater treatment automation, and digital twin development for dynamic infrastructure modeling. The work uniquely incorporates emerging concepts such as explainable AI, climate resilience frameworks, and digital twin technologies, positioning it at the forefront of current industry and academic research trends.This essential resource is designed for researchers, industry professionals, software developers, educators, and students specializing in water resource management and sustainable technology applications. The content balances foundational insights with advanced methodologies, making it equally valuable for newcomers seeking a comprehensive understanding and experienced practitioners looking to implement cutting-edge solutions for sustainable water system management.

Integrated Smart Technologies for Sustainable Water Systems Using Computer Applications presents a comprehensive exploration of how cutting-edge computational technologies are revolutionizing water resource management. This multidisciplinary guide demonstrates the practical integration of artificial intelligence (AI), Internet of Things (IoT) systems, and emerging digital technologies to address critical challenges in hydrology, hydraulics, water quality, and smart infrastructure development.This book systematically examines the application of advanced technologies including AI, machine learning, IoT, blockchain, cloud and edge computing, and Geographic Information Systems across diverse water management scenarios. Through theoretical models, algorithmic approaches, and real-world case studies from both developed and developing countries, it illustrates key findings in AI-driven water demand and quality predictions, IoT-enabled real-time distribution network monitoring, blockchain applications for transparent water resource transactions, intelligent flood forecasting systems, automated irrigation methods, wastewater treatment automation, and digital twin development for dynamic infrastructure modeling. The work uniquely incorporates emerging concepts such as explainable AI, climate resilience frameworks, and digital twin technologies, positioning it at the forefront of current industry and academic research trends.This essential resource is designed for researchers, industry professionals, software developers, educators, and students specializing in water resource management and sustainable technology applications. The content balances foundational insights with advanced methodologies, making it equally valuable for newcomers seeking a comprehensive understanding and experienced practitioners looking to implement cutting-edge solutions for sustainable water system management.

Integrated Smart Technologies for Sustainable Water Systems Using Computer Applications presents a comprehensive exploration of how cutting-edge computational technologies are revolutionizing water resource management. This multidisciplinary guide demonstrates the practical integration of artificial intelligence (AI), Internet of Things (IoT) systems, and emerging digital technologies to address critical challenges in hydrology, hydraulics, water quality, and smart infrastructure development.This book systematically examines the application of advanced technologies including AI, machine learning, IoT, blockchain, cloud and edge computing, and Geographic Information Systems across diverse water management scenarios. Through theoretical models, algorithmic approaches, and real-world case studies from both developed and developing countries, it illustrates key findings in AI-driven water demand and quality predictions, IoT-enabled real-time distribution network monitoring, blockchain applications for transparent water resource transactions, intelligent flood forecasting systems, automated irrigation methods, wastewater treatment automation, and digital twin development for dynamic infrastructure modeling. The work uniquely incorporates emerging concepts such as explainable AI, climate resilience frameworks, and digital twin technologies, positioning it at the forefront of current industry and academic research trends.This essential resource is designed for researchers, industry professionals, software developers, educators, and students specializing in water resource management and sustainable technology applications. The content balances foundational insights with advanced methodologies, making it equally valuable for newcomers seeking a comprehensive understanding and experienced practitioners looking to implement cutting-edge solutions for sustainable water system management.

This book offers a comprehensive and interdisciplinary perspective on healthcare intelligent systems, highlighting the growing role of applied mathematics, data-driven methodologies, and artificial intelligence in modern healthcare. The book brings together scholarly contributions that explore how intelligent models, data representations, and computational techniques are applied to healthcare diagnostics, medical imaging, and clinical decision-support systems.The chapters cover a wide range of topics, including medical imaging modalities, data handling and representation, deep learning techniques, explainable and trustworthy artificial intelligence, generative models, three-dimensional reconstruction, performance evaluation metrics, ethical considerations, and emerging trends in healthcare technologies. Through practical insights and real-world case studies, the volume illustrates how intelligent systems support disease detection, diagnosis, and personalized treatment planning.Designed for researchers, graduate students, and professionals in healthcare technology, computer science, and biomedical engineering, this book serves as a valuable reference on intelligent healthcare solutions.

This book offers a comprehensive and interdisciplinary perspective on healthcare intelligent systems, highlighting the growing role of applied mathematics, data-driven methodologies, and artificial intelligence in modern healthcare. The book brings together scholarly contributions that explore how intelligent models, data representations, and computational techniques are applied to healthcare diagnostics, medical imaging, and clinical decision-support systems.The chapters cover a wide range of topics, including medical imaging modalities, data handling and representation, deep learning techniques, explainable and trustworthy artificial intelligence, generative models, three-dimensional reconstruction, performance evaluation metrics, ethical considerations, and emerging trends in healthcare technologies. Through practical insights and real-world case studies, the volume illustrates how intelligent systems support disease detection, diagnosis, and personalized treatment planning.Designed for researchers, graduate students, and professionals in healthcare technology, computer science, and biomedical engineering, this book serves as a valuable reference on intelligent healthcare solutions.