Udai Shanker – författare

Blockchain-Enabled Innovations in Location-Based Services for Healthcare addresses the growing need for secure, intelligent healthcare solutions integrating location-based services (LBS), Internet of Things (IoT), and blockchain technologies. This reference explores how these technologies transform healthcare delivery improving autonomy and real-time care while safeguarding sensitive data. It responds to the challenges posed by the proliferation of wearable sensors and smart medical devices by proposing decentralized, privacy-preserving frameworks.The book’s comprehensive chapters cover blockchain trust models, adaptive privacy for patient trajectories, wearable computing, deep learning for medical imaging, secure communication in healthcare IoT, and AI-powered diagnostics. Contributions from global experts provide case-driven analyses and technical depth, addressing current challenges in healthcare data security, interoperability, and predictive modeling. The interdisciplinary approach integrates computer science, data privacy, and healthcare informatics, making it a valuable resource for researchers and professionals.Blockchain-Enabled Innovations in Location-Based Services for Healthcare benefits academic researchers, industry practitioners, graduate students, and policymakers by offering cutting-edge knowledge in secure, decentralized healthcare systems. It equips readers with advanced methodologies and practical solutions to design inclusive healthcare technologies, fostering innovation in smart health monitoring, medical image analysis, and data-driven diagnostics within privacy-compliant frameworks.Provides comprehensive coverage of blockchain, AI, and IoT integration in healthcarePresents case-driven methodologies with real-world healthcare implementationsOffers advanced research insights on big data analytics and medical image processingIntegrates privacy-preserving technologies with IoT and big data analytics

This book discusses the application of data systems and data-driven infrastructure in existing industrial systems in order to optimize workflow, utilize hidden potential, and make existing systems free from vulnerabilities. The book discusses application of data in the health sector, public transportation, the financial institutions, and in battling natural disasters, among others. Topics include real-time applications in the current big data perspective; improving security in IoT devices; data backup techniques for systems; artificial intelligence-based outlier prediction; machine learning in OpenFlow Network; and application of deep learning in blockchain enabled applications. This book is intended for a variety of readers from professional industries, organizations, and students.

This book discusses the application of data systems and data-driven infrastructure in existing industrial systems in order to optimize workflow, utilize hidden potential, and make existing systems free from vulnerabilities. The book discusses application of data in the health sector, public transportation, the financial institutions, and in battling natural disasters, among others. Topics include real-time applications in the current big data perspective; improving security in IoT devices; data backup techniques for systems; artificial intelligence-based outlier prediction; machine learning in OpenFlow Network; and application of deep learning in blockchain enabled applications. This book is intended for a variety of readers from professional industries, organizations, and students. 

This book discusses the application of data systems and data-driven infrastructure in existing industrial systems in order to optimize workflow, utilize hidden potential, and make existing systems free from vulnerabilities. The book discusses application of data in the health sector, public transportation, the financial institutions, and in battling natural disasters, among others. Topics include real-time applications in the current big data perspective; improving security in IoT devices; data backup techniques for systems; artificial intelligence-based outlier prediction; machine learning in OpenFlow Network; and application of deep learning in blockchain enabled applications. This book is intended for a variety of readers from professional industries, organizations, and students.

This book includes selected papers presented at International Conference on Data Science and Artificial Intelligence (DSAI 2025), organized by Department of Computer Science and Engineering, Madan Mohan Malaviya University of Technology, Gorakhpur, India, during April 1–2, 2025. The book covers a variety of topics, such as expert applications and artificial intelligence/machine learning; advance web technologies such as IoT, big data, cloud computing in expert applications; information and cyber-security threats and solutions; and multimedia applications in forensics, security, and intelligence.