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Elsevier

Quantum Computing for Internet of Things

  • 1 Edición, Volumen 145 - 1 de marzo de 2027
  • Última edición
  • Editor: Suyel Namasudra
  • Idioma: Inglés

Quantum Computing for Internet of Things, published as Volume 147 of the serial Advances in Computers, provides a comprehensive examination of the convergence of quantum compu… Leer más

Descripción

Quantum Computing for Internet of Things, published as Volume 147 of the serial Advances in Computers, provides a comprehensive examination of the convergence of quantum computing and the Internet of Things (IoT). The volume introduces the fundamental principles of quantum computing, including qubits and quantum mechanics, and explores the architectures, enabling technologies, and intelligent applications that underpin modern IoT ecosystems. It highlights how quantum technologies can enhance IoT performance, security, optimisation, and data processing capabilities across diverse application domains.

The volume presents emerging advances in quantum-enabled IoT systems, including distributed quantum computing frameworks, quantum machine learning approaches, quantum simulation tools, and novel optimisation techniques tailored to IoT environments. Case studies and application-focused chapters demonstrate the use of quantum methods in military systems, climate change analysis, and healthcare analytics. The volume concludes by addressing key research challenges, implementation barriers, and future directions, making it a valuable resource for researchers and practitioners working at the intersection of quantum technologies and connected intelligent systems.

Puntos claves

  • Reviews the fundamental concepts and principles of quantum computing relevant to IoT applications
  • Examines IoT architectures, enabling technologies, and intelligent connected systems
  • Explores distributed quantum computing approaches and quantum simulation frameworks for IoT environments
  • Highlights the application of quantum machine learning in climate analysis and healthcare classification problems
  • Presents novel quantum optimisation techniques designed for large-scale IoT ecosystems
  • Discusses current research challenges, technological limitations, and future opportunities for quantum-enabled IoT systems

De interès para

Computer scientists and researchers in quantum computing; Internet of Things (IoT) researchers and practitioners; Artificial intelligence and machine learning specialists; Distributed systems and network computing researchers; Cybersecurity and intelligent systems professionals; Graduate students and advanced scholars in computer science, information technology, and data science; Engineers developing next-generation connected and quantum-enabled technologies

Índice

1. Quantum Computing Fundamentals: From Qubits to Quantum Principles

2. Internet of Things: Architectures, Enabling Technologies, and Intelligent Applications

3. Quantum Computing for Internet of Things: Concepts and Applications

4. Quantum Computing in IoT-based Military Applications

5. Quantum Computers based on Distributed Computing Systems for IoT

6. IoT-Driven Quantum Machine Learning for Climate Change Analysis

7. Quantum Simulation Tools and Software Frameworks

8. A Novel Quantum Computing Optimization Technique for the IoT Environment

9. IoT-based System using Quantum Support Vector Machine for Type-2 Diabetes Classification

10. Quantum-Enabled IoT Systems: Research Challenges and Future Directions

Detalles del producto

  • Edición: 1
  • Última edición
  • Volumen: 145
  • Publicado: 1 de marzo de 2027
  • Idioma: Inglés

Sobre el editor

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Suyel Namasudra

Suyel Namasudra has received Ph.D. degree from the National Institute of Technology Silchar, Assam, India. He was a post-doctorate fellow at the International University of La Rioja (UNIR), Spain. Currently, Dr. Namasudra is working as an assistant professor in the Department of Computer Science and Engineering at the National Institute of Technology Agartala, Tripura, India. Before joining the National Institute of Technology Agartala, Dr. Namasudra was an assistant professor in the Department of Computer Science and Engineering at the National Institute of Technology Patna, Bihar, India. His research interests include blockchain technology, cloud computing, DNA computing, and information security. Dr. Namasudra has edited 7 books, 5 patents, and 85 publications in conference proceedings, book chapters, and refereed journals like IEEE TII, IEEE TCE, IEEE T-ITS, IEEE TSC, IEEE TCSS, IEEE TCBB, ACM TOMM, ACM TOSN, ACM TALLIP, FGCS, CAEE, and many more. He is the Editor-in-Chief of the Cloud Computing and Data Science (ISSN: 2737-4092 (online)) journal. Dr. Namasudra has served as a Lead Guest Editor/Guest Editor in many reputed journals like IEEE TCE (IEEE, IF: 4.3), IEEE TBD (IEEE, IF: 7.2), ACM TOMM (ACM, IF: 3.144), MONET (Springer, IF: 3.426), CAEE (Elsevier, IF: 3.818), CAIS (Springer, IF: 4.927), CMC (Tech Science Press, IF: 3.772), Sensors (MDPI, IF: 3.576), and many more. He has also participated in many international conferences as an organizer and session chair. Dr. Namasudra is a senior member of IEEE, and a member of ACM and IEI. He has been featured in the list of the top 2% scientists in the world in 2021, 2022, and 2023. His h-index is 37.

Afiliaciones y experiencia
Department of Computer Science and Engineering, National Institute of Technology Agartala, Tripura, India