Priya Batta – författare

Federated Quantum Convolutional Neural Networks in Healthcare: Enhancing Privacy and Efficiency explores the innovative intersection of quantum computing and federated learning in the context of healthcare. As medical data grows exponentially and privacy concerns intensify, this book addresses the urgent need for secure, scalable AI solutions that enable collaborative data analysis without compromising patient confidentiality. It offers a detailed examination of the theoretical foundations of quantum machine learning and federated systems, complemented by practical case studies spanning medical imaging, genomics, and disease diagnosis. The content delves into architecture design, security protocols, and optimization techniques, equipping researchers and practitioners with the tools to develop privacy-preserving AI models tailored for medical applications. The book also discusses regulatory considerations, deployment challenges, and future research directions, positioning itself as a vital resource for advancing healthcare AI. Its comprehensive approach bridges fundamental science and real-world implementation, empowering healthcare professionals, data scientists, and policy makers to harness next-generation quantum federated systems for improved patient outcomes and data security. This resource is essential for those seeking to implement cutting-edge AI technologies in healthcare, ensuring secure, efficient, and collaborative medical data analysis.Explains the integration of quantum computing with federated learning tailored for healthcarePresents case studies on medical imaging, genomics, and disease diagnosisDetails privacy-preserving methods and secure communication protocolsDiscusses scalability, efficiency, and deployment challenges in healthcare environmentsHighlights future directions and potential societal impact of FedQCNNs

Blockchain Technology in Water Management and New Energy Economy explores the transformative role of blockchain in addressing two of the most pressing global challenges: efficient water resource management and the transition to a sustainable energy future. As climate change, population growth, and urbanization exert increasing pressure on natural resources, traditional systems for managing water and energy are proving inadequate. This book presents blockchain as a powerful enabler of transparency, decentralization, and trust in resource governance, offering innovative solutions that can reshape these critical sectors. The book is divided into two major sections. The first focuses on water management, covering how blockchain can enhance monitoring, prevent water theft, support real-time quality assessments, and enable equitable distribution through smart contracts. It examines case studies where decentralized ledger technology has improved water conservation, optimized irrigation systems in agriculture, and facilitated peer-to-peer water trading.The second section delves into the new energy economy, highlighting blockchain’s potential in supporting renewable energy integration, smart grids, decentralized energy markets, and carbon credit tracking. It discusses how blockchain can empower consumers to become "prosumers" — both producing and consuming energy — while maintaining secure and traceable transactions. Additionally, the book explores cross-cutting themes such as data privacy, regulatory challenges, scalability, and the socio-economic impact of blockchain adoption. Through real-world examples, technical insights, and forward-looking perspectives, this book provides a comprehensive guide for researchers, policy makers, engineers, and sustainability advocates seeking to understand and apply blockchain technology for a greener and more resource-efficient future.

Discover how to turn nature’s best problem-solving strategies into powerful computational tools with this comprehensive guide to building resilient, adaptive, and next-generation algorithms for healthcare, finance, and engineering. Nature-inspired intelligence is a rapidly evolving field that draws from biological and physical phenomena, such as evolution, swarm behavior, neural processing, and immune systems, to develop algorithms capable of handling complexity, uncertainty, and scalability. Unlike conventional computational approaches, these techniques adapt dynamically, mimic resilience, and exhibit problem-solving strategies observed in nature. As industries face increasingly complex and data-intensive challenges, nature-inspired intelligence provides robust, efficient, and innovative solutions, positioning it as a cornerstone of future technological and scientific progress. This book presents a comprehensive exploration of how biological, physical, and ecological principles can be transformed into powerful computational tools for solving some of today’s most challenging problems. Drawing inspiration from natural processes, the book highlights a broad spectrum of algorithms that push beyond traditional approaches to optimization and decision-making. Blending theory with application, the book demonstrates how nature-inspired intelligence can address complexity across domains including healthcare, energy, finance, engineering, and emerging technologies. Readers will find the volume: Offers an in-depth exploration of a wide range of nature-inspired computational techniques, including evolutionary algorithms, swarm intelligence, neural models, and physics-inspired methods;Bridges the gap between natural systems and computational problem-solving, appealing to a diverse audience of researchers and practitioners;Features case studies in robotics, healthcare, finance, engineering, and environmental sustainability, and highlights how these algorithms are used to tackle practical challenges across industries;Addresses the latest advancements in combining multiple nature-inspired techniques and explores cutting-edge topics like quantum computing and bio-hybrid systems. ensuring the content remains relevant to current research and innovation.Audience Computer scientists, engineers, applied mathematicians, data scientists, and researchers in optimization and complex systems, as well as professionals in healthcare, energy, finance, and technology seeking innovative problem-solving approaches.

Blockchain and the Water Supply Chain explores the transformative potential of blockchain technology in ensuring sustainable, transparent and efficient water governance. Placing water at the center of smart infrastructure innovation, the book addresses the urgent need for trustworthy and traceable systems in the distribution and management of water resources. This book also delves into how blockchain can revolutionize the water supply chain through decentralized monitoring, smart contracts and immutable data records to reduce losses, enhance accountability and enable real-time decision making. It analyzes key challenges such as interoperability, scalability and regulatory hurdles, while also showcasing innovative use cases and pilot projects across the globe. With contributions from experts in water management, blockchain and environmental policy, this book bridges the gap between digital innovation and sustainable resource management, and is an essential guide for researchers, policymakers and technologists aiming to reshape the future of water systems.

Blockchain and the Water Supply Chain explores the transformative potential of blockchain technology in ensuring sustainable, transparent and efficient water governance. Placing water at the center of smart infrastructure innovation, the book addresses the urgent need for trustworthy and traceable systems in the distribution and management of water resources. This book also delves into how blockchain can revolutionize the water supply chain through decentralized monitoring, smart contracts and immutable data records to reduce losses, enhance accountability and enable real-time decision making. It analyzes key challenges such as interoperability, scalability and regulatory hurdles, while also showcasing innovative use cases and pilot projects across the globe. With contributions from experts in water management, blockchain and environmental policy, this book bridges the gap between digital innovation and sustainable resource management, and is an essential guide for researchers, policymakers and technologists aiming to reshape the future of water systems.

Sustainable Supply Chains and Carbon Footprint Reduction explores how blockchain technology enables greener, more accountable supply chains by improving traceability, reducing inefficiencies and offering real-time visibility into resource use and carbon emissions. This book examines how blockchain creates secure, tamper-proof records of supply chain activities, helping industries track products from origin to consumption while ensuring compliance with environmental standards. Through real-world case studies and practical strategies, it highlights blockchain's role in driving sustainable practices across sectors such as agriculture, manufacturing, logistics and energy. Designed for business leaders, sustainability professionals and policymakers, this book provides actionable insights for leveraging blockchain to meet climate goals and support circular economy initiatives and demonstrates how digital innovation and sustainability can work together to create transparent, resilient and environmentally responsible supply chains.

Sustainable Supply Chains and Carbon Footprint Reduction explores how blockchain technology enables greener, more accountable supply chains by improving traceability, reducing inefficiencies and offering real-time visibility into resource use and carbon emissions. This book examines how blockchain creates secure, tamper-proof records of supply chain activities, helping industries track products from origin to consumption while ensuring compliance with environmental standards. Through real-world case studies and practical strategies, it highlights blockchain's role in driving sustainable practices across sectors such as agriculture, manufacturing, logistics and energy. Designed for business leaders, sustainability professionals and policymakers, this book provides actionable insights for leveraging blockchain to meet climate goals and support circular economy initiatives and demonstrates how digital innovation and sustainability can work together to create transparent, resilient and environmentally responsible supply chains.

AI-driven Innovations in Physiotherapy and Oncology 1 explores the transformative impact of artificial intelligence (AI) on two critical domains of healthcare. As the global demand for personalized, efficient and data-driven medical interventions increases, this book offers a timely examination of how AI technologies are reshaping clinical practices in both physiotherapy and oncology. The book explores how AI supports early cancer detection, personalized treatment planning and monitoring of disease progression, while also playing a pivotal role in physiotherapy by enabling intelligent rehabilitation strategies tailored to oncology patients. From AI-driven motion analysis and virtual physiotherapy assistants to predictive models for treatment response and functional recovery, this book showcases innovations that optimize physical therapy outcomes for cancer patients. It also addresses ethical challenges, data governance and the integration of AI within clinical workflows. Designed for clinicians, researchers and healthcare innovators, this book is a vital resource for understanding how AI bridges the gap between oncology care and rehabilitative physiotherapy.

AI-driven Innovations in Physiotherapy and Oncology 1 explores the transformative impact of artificial intelligence (AI) on two critical domains of healthcare. As the global demand for personalized, efficient and data-driven medical interventions increases, this book offers a timely examination of how AI technologies are reshaping clinical practices in both physiotherapy and oncology. The book explores how AI supports early cancer detection, personalized treatment planning and monitoring of disease progression, while also playing a pivotal role in physiotherapy by enabling intelligent rehabilitation strategies tailored to oncology patients. From AI-driven motion analysis and virtual physiotherapy assistants to predictive models for treatment response and functional recovery, this book showcases innovations that optimize physical therapy outcomes for cancer patients. It also addresses ethical challenges, data governance and the integration of AI within clinical workflows. Designed for clinicians, researchers and healthcare innovators, this book is a vital resource for understanding how AI bridges the gap between oncology care and rehabilitative physiotherapy.

AI-driven Innovations in Physiotherapy and Oncology 2 explores the transformative impact of artificial intelligence (AI) on two critical domains of healthcare. As the global demand for personalized, efficient and data-driven medical interventions increases, this book offers a timely examination of how AI technologies are reshaping clinical practices in both physiotherapy and oncology. The book explores how AI supports early cancer detection, personalized treatment planning and monitoring of disease progression, while also playing a pivotal role in physiotherapy by enabling intelligent rehabilitation strategies tailored to oncology patients. From AI-driven motion analysis and virtual physiotherapy assistants to predictive models for treatment response and functional recovery, this book showcases innovations that optimize physical therapy outcomes for cancer patients. It also addresses ethical challenges, data governance and the integration of AI within clinical workflows. Designed for clinicians, researchers and healthcare innovators, this book is a vital resource for understanding how AI bridges the gap between oncology care and rehabilitative physiotherapy.

AI-driven Innovations in Physiotherapy and Oncology 2 explores the transformative impact of artificial intelligence (AI) on two critical domains of healthcare. As the global demand for personalized, efficient and data-driven medical interventions increases, this book offers a timely examination of how AI technologies are reshaping clinical practices in both physiotherapy and oncology. The book explores how AI supports early cancer detection, personalized treatment planning and monitoring of disease progression, while also playing a pivotal role in physiotherapy by enabling intelligent rehabilitation strategies tailored to oncology patients. From AI-driven motion analysis and virtual physiotherapy assistants to predictive models for treatment response and functional recovery, this book showcases innovations that optimize physical therapy outcomes for cancer patients. It also addresses ethical challenges, data governance and the integration of AI within clinical workflows. Designed for clinicians, researchers and healthcare innovators, this book is a vital resource for understanding how AI bridges the gap between oncology care and rehabilitative physiotherapy.

AI-driven Healthcare Innovations presents a timely and authoritative exploration of how artificial intelligence (AI) is transforming modern clinical practices and medical research. Positioned at the intersection of healthcare, data science and computational intelligence, this book provides a comprehensive context for understanding the growing role of AI in diagnosis, treatment and decision-making within neurology and broader medical domains. The book systematically examines core AI techniques, including machine learning (ML), deep learning (DL) and intelligent optimization, and demonstrates their practical deployment across neurological disorders, medical imaging, predictive analytics and personalized care. Emphasis is placed on real-world clinical workflows, data acquisition and preprocessing, model interpretability and performance evaluation. In addition, we also address ethical considerations, regulatory challenges and data security issues critical to healthcare adoption. By combining theoretical foundations with applied case studies and future research directions, this book serves as a valuable resource for researchers, clinicians, graduate students and industry professionals seeking to leverage AI-driven innovations to improve patient outcomes and advance next-generation healthcare systems.

AI-driven Healthcare Innovations presents a timely and authoritative exploration of how artificial intelligence (AI) is transforming modern clinical practices and medical research. Positioned at the intersection of healthcare, data science and computational intelligence, this book provides a comprehensive context for understanding the growing role of AI in diagnosis, treatment and decision-making within neurology and broader medical domains. The book systematically examines core AI techniques, including machine learning (ML), deep learning (DL) and intelligent optimization, and demonstrates their practical deployment across neurological disorders, medical imaging, predictive analytics and personalized care. Emphasis is placed on real-world clinical workflows, data acquisition and preprocessing, model interpretability and performance evaluation. In addition, we also address ethical considerations, regulatory challenges and data security issues critical to healthcare adoption. By combining theoretical foundations with applied case studies and future research directions, this book serves as a valuable resource for researchers, clinicians, graduate students and industry professionals seeking to leverage AI-driven innovations to improve patient outcomes and advance next-generation healthcare systems.

AI-driven Innovations in Physiotherapy and Oncology 3 is positioned at the intersection of artificial intelligence (AI), clinical rehabilitation and cancer care, addressing the growing need for data-driven, personalized and technology-enabled healthcare solutions. The book contextualizes recent advances in machine learning, deep learning, computer vision and intelligent decision-support systems within modern physiotherapy and oncology practices. This book systematically explores how AI models enhance diagnosis, treatment planning, therapy optimization and outcome prediction across musculoskeletal rehabilitation, neuro-physiotherapy, radiation oncology and precision cancer care. It covers sensor-based motion analysis, AI-assisted imaging, predictive analytics, digital therapeutics and intelligent rehabilitation platforms, supported by real-world case studies and implementation frameworks. The book also discusses ethical considerations, clinical validation, interoperability and regulatory challenges to bridge the gap between research and practice. Designed for researchers, clinicians, graduate students and healthcare technologists, this book provides both theoretical foundations and practical insights for integrating AI into next-generation physiotherapy and oncology workflows

AI in Orthopedic Trauma Care 1 explores how AI technologies are transforming comparative clinical decision-making in orthopedic trauma. Positioned within precision healthcare, this book shows how AI-assisted analytics enhance the evaluation of surgical techniques and treatment strategies. Integrating machine learning, deep learning, medical imaging analytics, wearable sensor data and electronic health records, this book applies data-driven methods to compare fixation approaches, operative techniques, graft choices and pharmacological interventions. Emphasis is placed on outcome analysis, optimized treatment selection, continuous monitoring and complication reduction through structured clinical pathways. By combining orthopedic expertise with advanced computational tools, this book offers practical insights for clinicians, healthcare technologists and researchers advancing patient-centered, AI assisted trauma care.

AI in Orthopedic Trauma Care 2 focuses on predictive modeling and data-driven strategies across the continuum of trauma care. Framed within precision healthcare, it examines how AI-driven systems enhance decision-making, risk assessment and recovery planning. This book integrates machine learning and clinical data analytics to predict fracture union, assess osteoporosis and implant failure risk, evaluate infection probability, and support polytrauma management. It further explores functional recovery modeling and personalized rehabilitation pathways. Emphasizing responsible AI integration, this book addresses ethical governance, data security, transparency and implementation challenges, offering practical guidance for clinicians, healthcare technologists and researchers building intelligent, secure, and patient-centered orthopedic trauma systems.

AI-driven Innovations in Physiotherapy and Oncology 4 explores how artificial intelligence (AI) is transforming patient care, rehabilitation and cancer management. It presents a comprehensive overview of AI applications in physiotherapy and oncology, highlighting data-driven diagnostics, personalized treatment planning and predictive analytics. This book discusses the integration of machine learning, computer vision and wearable technologies to enhance rehabilitation outcomes, monitor patient progress and optimize therapeutic interventions. In oncology, it also examines AI-supported early detection, tumor classification, precision medicine and treatment response prediction. Real-world case studies and emerging research trends are included to demonstrate practical implementation and clinical impact. By bridging technological advancements with healthcare practices, this book provides valuable insights for researchers, clinicians and professionals seeking to understand and leverage AI for improved patient outcomes and next-generation medical innovation.

AI-driven Innovations in Physiotherapy and Oncology 4 explores how artificial intelligence (AI) is transforming patient care, rehabilitation and cancer management. It presents a comprehensive overview of AI applications in physiotherapy and oncology, highlighting data-driven diagnostics, personalized treatment planning and predictive analytics. This book discusses the integration of machine learning, computer vision and wearable technologies to enhance rehabilitation outcomes, monitor patient progress and optimize therapeutic interventions. In oncology, it also examines AI-supported early detection, tumor classification, precision medicine and treatment response prediction. Real-world case studies and emerging research trends are included to demonstrate practical implementation and clinical impact. By bridging technological advancements with healthcare practices, this book provides valuable insights for researchers, clinicians and professionals seeking to understand and leverage AI for improved patient outcomes and next-generation medical innovation.

The rapid evolution of embedded technologies has transformed modern automation, intelligent devices and connected infrastructures. Intelligent Embedded Systems 1 provides a comprehensive introduction to the principles, architectures and real-world applications of intelligent embedded systems across diverse domains. This book explores the integration of artificial intelligence (AI), the Internet of Things (IoT), autonomous navigation, robotics, industrial automation, healthcare and smart manufacturing, highlighting how embedded intelligence enables efficient, reliable and adaptive systems. Through theoretical foundations, practical implementations and application-driven case studies, the book bridges the gap between academic concepts and industrial practice. Designed for undergraduate and postgraduate students, researchers, engineers and professionals, this book offers valuable insights into emerging technologies, while establishing the foundational knowledge required to develop next-generation intelligent embedded solutions.

The rapid evolution of embedded technologies has transformed modern automation, intelligent devices and connected infrastructures. Intelligent Embedded Systems 2 explores advanced architectures, intelligent algorithms and emerging technologies that are shaping the future of embedded computing. This book examines AI-enabled embedded platforms, edge and fog computing, cyber-physical systems, autonomous decision-making, real time embedded intelligence, secure IoT integration, digital twins and next-generation industrial applications. Emphasis is placed on scalable system design, intelligent control, cybersecurity, energy-efficient computing and autonomous operations within Industry 4.0 and smart environments. Featuring contemporary research trends, practical methodologies and application-oriented case studies, this book serves as a valuable resource for researchers, graduate students, industry practitioners and technology developers seeking to design, deploy and optimize intelligent embedded systems for complex real-world challenges.

Blockchain and the Water Supply Chain explores the transformative potential of blockchain technology in ensuring sustainable, transparent and efficient water governance. Placing water at the center of smart infrastructure innovation, the book addresses the urgent need for trustworthy and traceable systems in the distribution and management of water resources.This book also delves into how blockchain can revolutionize the water supply chain through decentralized monitoring, smart contracts and immutable data records to reduce losses, enhance accountability and enable real-time decision making. It analyzes key challenges such as interoperability, scalability and regulatory hurdles, while also showcasing innovative use cases and pilot projects across the globe. With contributions from experts in water management, blockchain and environmental policy, this book bridges the gap between digital innovation and sustainable resource management, and is an essential guide for researchers, policymakers and technologists aiming to reshape the future of water systems.

Sustainable Supply Chains and Carbon Footprint Reduction explores how blockchain technology enables greener, more accountable supply chains by improving traceability, reducing inefficiencies and offering real-time visibility into resource use and carbon emissions.This book examines how blockchain creates secure, tamper-proof records of supply chain activities, helping industries track products from origin to consumption while ensuring compliance with environmental standards. Through real-world case studies and practical strategies, it highlights blockchain's role in driving sustainable practices across sectors such as agriculture, manufacturing, logistics and energy.Designed for business leaders, sustainability professionals and policymakers, this book provides actionable insights for leveraging blockchain to meet climate goals and support circular economy initiatives and demonstrates how digital innovation and sustainability can work together to create transparent, resilient and environmentally responsible supply chains.

AI-driven Innovations in Physiotherapy and Oncology 1 explores the transformative impact of artificial intelligence (AI) on two critical domains of healthcare. As the global demand for personalized, efficient and data-driven medical interventions increases, this book offers a timely examination of how AI technologies are reshaping clinical practices in both physiotherapy and oncology. The book explores how AI supports early cancer detection, personalized treatment planning and monitoring of disease progression, while also playing a pivotal role in physiotherapy by enabling intelligent rehabilitation strategies tailored to oncology patients. From AI-driven motion analysis and virtual physiotherapy assistants to predictive models for treatment response and functional recovery, this book showcases innovations that optimize physical therapy outcomes for cancer patients. It also addresses ethical challenges, data governance and the integration of AI within clinical workflows. Designed for clinicians, researchers and healthcare innovators, this book is a vital resource for understanding how AI bridges the gap between oncology care and rehabilitative physiotherapy.

AI-driven Innovations in Physiotherapy and Oncology 2 explores the transformative impact of artificial intelligence (AI) on two critical domains of healthcare. As the global demand for personalized, efficient and data-driven medical interventions increases, this book offers a timely examination of how AI technologies are reshaping clinical practices in both physiotherapy and oncology.The book explores how AI supports early cancer detection, personalized treatment planning and monitoring of disease progression, while also playing a pivotal role in physiotherapy by enabling intelligent rehabilitation strategies tailored to oncology patients. From AI-driven motion analysis and virtual physiotherapy assistants to predictive models for treatment response and functional recovery, this book showcases innovations that optimize physical therapy outcomes for cancer patients. It also addresses ethical challenges, data governance and the integration of AI within clinical workflows. Designed for clinicians, researchers and healthcare innovators, this book is a vital resource for understanding how AI bridges the gap between oncology care and rehabilitative physiotherapy.

AI-driven Innovations in Physiotherapy and Oncology 3 is positioned at the intersection of artificial intelligence (AI), clinical rehabilitation and cancer care, addressing the growing need for data-driven, personalized and technology-enabled healthcare solutions. The book contextualizes recent advances in machine learning, deep learning, computer vision and intelligent decision-support systems within modern physiotherapy and oncology practices. This book systematically explores how AI models enhance diagnosis, treatment planning, therapy optimization and outcome prediction across musculoskeletal rehabilitation, neuro-physiotherapy, radiation oncology and precision cancer care. It covers sensor-based motion analysis, AI-assisted imaging, predictive analytics, digital therapeutics and intelligent rehabilitation platforms, supported by real-world case studies and implementation frameworks. The book also discusses ethical considerations, clinical validation, interoperability and regulatory challenges to bridge the gap between research and practice. Designed for researchers, clinicians, graduate students and healthcare technologists, this book provides both theoretical foundations and practical insights for integrating AI into next-generation physiotherapy and oncology workflows

AI-driven Healthcare Innovations presents a timely and authoritative exploration of how artificial intelligence (AI) is transforming modern clinical practices and medical research. Positioned at the intersection of healthcare, data science and computational intelligence, this book provides a comprehensive context for understanding the growing role of AI in diagnosis, treatment and decision-making within neurology and broader medical domains. The book systematically examines core AI techniques, including machine learning (ML), deep learning (DL) and intelligent optimization, and demonstrates their practical deployment across neurological disorders, medical imaging, predictive analytics and personalized care. Emphasis is placed on real-world clinical workflows, data acquisition and preprocessing, model interpretability and performance evaluation. In addition, we also address ethical considerations, regulatory challenges and data security issues critical to healthcare adoption. By combining theoretical foundations with applied case studies and future research directions, this book serves as a valuable resource for researchers, clinicians, graduate students and industry professionals seeking to leverage AI-driven innovations to improve patient outcomes and advance next-generation healthcare systems.

AI in Orthopedic Trauma Care 1 explores how AI technologies are transforming comparative clinical decision-making in orthopedic trauma. Positioned within precision healthcare, this book shows how AI-assisted analytics enhance the evaluation of surgical techniques and treatment strategies.Integrating machine learning, deep learning, medical imaging analytics, wearable sensor data and electronic health records, this book applies data-driven methods to compare fixation approaches, operative techniques, graft choices and pharmacological interventions. Emphasis is placed on outcome analysis, optimized treatment selection, continuous monitoring and complication reduction through structured clinical pathways.By combining orthopedic expertise with advanced computational tools, this book offers practical insights for clinicians, healthcare technologists and researchers advancing patient-centered, AI assisted trauma care.

AI-driven Innovations in Physiotherapy and Oncology 4 explores how artificial intelligence (AI) is transforming patient care, rehabilitation and cancer management. It presents a comprehensive overview of AI applications in physiotherapy and oncology, highlighting data-driven diagnostics, personalized treatment planning and predictive analytics.This book discusses the integration of machine learning, computer vision and wearable technologies to enhance rehabilitation outcomes, monitor patient progress and optimize therapeutic interventions. In oncology, it also examines AI-supported early detection, tumor classification, precision medicine and treatment response prediction. Real-world case studies and emerging research trends are included to demonstrate practical implementation and clinical impact.By bridging technological advancements with healthcare practices, this book provides valuable insights for researchers, clinicians and professionals seeking to understand and leverage AI for improved patient outcomes and next-generation medical innovation.