rdf-syntax-grammar
mods:
  schema location: http://www.loc.gov/mods/v3 http://www.loc.gov/standards/mods/v3/mods-3-2.xsd
  title info:
    title: Blockchain and digital twin for smart healthcare
  name:
    name part: Nguyen, Tuan Anh
    role:
      role term: editor.
  name:
    name part: ScienceDirect (Online service)
  type of resource: text
  genre: Electronic books.
  origin info:
    place:
      place term: ne
    date issued: 2025
    issuance: monographic
  language:
    language term: eng
  physical description:
    form: remote
    extent: 1 online resource.
  abstract: The smart hospital framework involves three main layers: data, insight and access. Medical data is collected real-time from devices and systems in a smart hospitals: the internet of medical things. This data is integrated to provide insight from the analytics or machine learning software using digital twins. Security and transparency are brought through a combination of digital twin and blockchain technologies. Blockchain and Digital Twins for Smart Healthcare describes the role of blockchain and digital twins in smart healthcare. It describes the ecosystem of the Internet of Medical Things, how data can be gathered using a sensor network, which is securely stored, updated and managed with blockchain for efficient and private medical data exchange. The end goal is insight that provides faster, smarter decisions with more efficiency to improve care for the patient.
  table of contents: Front Cover -- Blockchain and Digital Twin for Smart Healthcare -- Copyright Page -- Contents -- List of contributors -- About the editor -- Foreword -- 1 Internet of Medical Things: architecture, trends, and challenges -- 1.1 Introduction -- 1.1.1 What is Internet of Medical Things? -- 1.1.2 Internet of Things to Internet of Medical Things evolution -- 1.2 Internet of Medical Things architecture -- 1.2.1 Internet of Medical Things types -- 1.2.2 Internet of Medical Things devices and protocols -- 1.2.3 Sensors for Internet of Medical Things -- 1.2.4 Internet of Medical Things communications -- 1.3 Design challenges -- 1.4 Security attacks on Internt of Medical Things -- 1.5 Security techniques in Internet of Medical Things -- 1.6 Application of Internet of Medical Things -- 1.7 Challenges and future directions in Internet of Medical Things -- 1.8 Future prospects and conclusions -- References -- 2 Internet of Health Things: an introduction -- Nomenclature -- 2.1 Introduction -- 2.2 Major components of Internet of Health Things -- 2.2.1 Internet of Health Things devices -- 2.2.1.1 Wearable devices -- 2.2.1.2 Implantable devices -- 2.2.1.3 Hospital devices -- 2.2.1.4 Home medical devices -- 2.2.2 Architectures -- 2.2.2.1 Perception layer -- 2.2.2.2 Gateway layer -- 2.2.2.3 Cloud layer -- 2.2.2.4 Application layer -- 2.2.3 Communication technologies -- 2.2.3.1 Bluetooth -- 2.2.3.2 Zigbee -- 2.2.3.3 Wi-Fi -- 2.2.3.4 Cellular network -- 2.2.3.5 Satellite -- 2.3 Recent advances in Internet of Health Things for smart healthcare -- 2.3.1 Patient monitoring -- 2.3.1.1 Glucose level monitoring -- 2.3.1.2 Heart rate monitoring -- 2.3.1.3 Blood pressure monitoring -- 2.3.1.4 Body temperature monitoring -- 2.3.1.5 Oxygen saturation monitoring -- 2.3.2 Smart medication -- 2.3.3 Intelligent diagnosis of chronic diseases -- 2.3.4 Ambient assisted living.
  table of contents: 2.4 Current challenges and potential solutions -- 2.4.1 Connectivity and interoperability -- 2.4.2 Network and power supply -- 2.4.3 Wearable devices -- 2.4.4 Standardization -- 2.4.5 Data protection and security -- 2.5 Conclusion -- References -- 3 Smart sensor networks based on edge technologies -- 3.1 Introduction -- 3.2 Research methodology -- 3.3 Classification of smart sensor networks applications in edge-based smart cities -- 3.3.1 Urban monitoring -- 3.3.2 Transportation -- 3.3.3 Data management -- 3.3.4 Resource management -- 3.3.5 Urban heat island -- 3.4 Analysis of results -- 3.5 Open issues -- 3.6 Conclusion -- References -- 4 Blockchain and cyber-physical systems in the smart healthcare -- 4.1 Introduction -- 4.2 Characteristics of medical cyber-physical systems -- 4.2.1 Unit-level medical cyber-physical systems -- 4.2.2 Integration-level medical cyber-physical systems -- 4.2.3 System-level medical cyber-physical systems -- 4.2.4 Acceptance-level medical cyber-physical systems -- 4.2.5 Evolutionary-level medical cyber-physical systems -- 4.3 Blockchain evolving healthcare sector -- 4.3.1 Tracing medical frauds -- 4.3.2 Potential impact of blockchain technology in the healthcare sector -- 4.4 Significant technologies supporting medical cyber-physical systems and blockchain in the healthcare sector -- 4.4.1 Internet of Things -- 4.4.2 Cloud computing -- 4.4.3 Dew computing -- 4.4.4 Big data analytics -- 4.4.5 Robots -- 4.5 Main obstacles to the successful integration of blockchain and medical cyber-physical systems in the healthcare sector -- 4.5.1 Data interoperability and integration -- 4.5.2 Privacy and security concerns -- 4.5.3 Scalability and performance -- 4.5.4 Regulatory and governance challenges -- 4.5.5 Technology acceptance and training -- 4.5.6 Cybersecurity and resilience -- 4.6 Conclusion -- References.
  table of contents: 5 Impact of the Internet of Medical Things (IoMT) on healthcare: perspectives from organizations, professionals, and patien... -- 5.1 Introduction -- 5.2 Healthcare organization perspective-managing data silos and resource allocation -- 5.2.1 Managing data silos -- 5.2.2 Managing resource allocation -- 5.3 Healthcare professional perspective-workloads -- 5.4 Patient perspective-health inequality and digital exclusion -- 5.5 Conclusion -- References -- 6 Smart medical sensor network -- 6.1 Introduction -- 6.2 Research methodology -- 6.3 Classification of approaches related to smart medical sensor networks in smart cities -- 6.3.1 Application class -- 6.3.2 Communication class -- 6.3.3 Security class -- 6.4 Analysis of results -- 6.5 Open issues -- 6.6 Conclusion -- References -- 7 Medical sensor network and machine learning-enabled digital twins for diagnostic and therapeutic purposes -- 7.1 Introduction -- 7.1.1 Background -- 7.1.2 Problem statement -- 7.1.3 Literature review -- 7.1.4 Safety considerations and standards -- 7.2 Technologies and procedures -- 7.2.1 Technology description -- 7.2.2 Method procedure -- 7.2.2.1 Sensor selection and deployment -- 7.2.2.2 Data acquisition and transmission -- 7.2.2.3 Data preprocessing and feature extraction -- 7.2.2.4 Machine learning model development -- 7.2.2.5 Digital twin integration -- 7.2.2.6 Real-time monitoring and feedback -- 7.2.2.7 Model updating and refinement -- 7.2.2.8 Validation and performance evaluation -- 7.2.3 Facilities, resources, and networks -- 7.2.3.1 Sensors and wearable devices -- 7.2.3.2 Signal acquisition and transmission hardware -- 7.2.3.3 Computing resources -- 7.2.3.4 Software tools and frameworks -- 7.2.3.5 Secure communication and when dealing with data -- 7.2.3.6 Clinical and research facilities -- 7.2.3.7 Collaborative resources -- 7.2.3.8 Regulatory and ethical resources.
  table of contents: 7.2.4 Computational modeling framewoks -- 7.2.4.1 Finite element analysis -- 7.2.4.2 Multiphysics simulation -- 7.2.4.3 Agent-based modeling -- 7.2.4.4 Machine learning and deep learning frameworks -- 7.2.4.5 Cloud computing platforms -- 7.2.4.6 High-performance computing resources -- 7.2.5 Optimization and troubleshooting -- 7.2.5.1 Optimization strategies -- 7.2.5.2 Troubleshooting techniques -- 7.2.6 Limitations -- 7.2.6.1 Data privacy and security concerns -- 7.2.6.2 Interoperability and standardization challenges -- 7.2.6.3 Algorithmic bias and fairness -- 7.2.6.4 Scalability and computational complexity -- 7.2.6.5 User adoption and acceptance -- 7.2.6.6 Regulatory and ethical considerations -- 7.2.6.7 Limited generalizability and transferability -- 7.2.6.8 Continuous monitoring and maintenance -- 7.3 Data analysis and validation of results -- 7.3.1 Data analysis -- 7.3.1.1 Statistical analysis -- 7.3.1.2 Time series analysis -- 7.3.1.3 Signal processing and feature extraction -- 7.3.1.4 Pattern recognition and anomaly detection -- 7.3.1.5 Sensitivity analysis and uncertainty quantification -- 7.3.1.6 Visualization and exploratory data analysis -- 7.3.2 Validation, calculation, and expression of results -- 7.3.2.1 Model validation -- 7.3.2.2 System-level validation -- 7.3.2.3 Clinical validation -- 7.3.2.4 Calculation and expression of results -- 7.3.2.5 Uncertainty and sensitivity analysis -- 7.3.2.6 Reproducibility and transparency -- 7.4 Discussion and evaluation -- 7.5 Conclusion -- References -- 8 IoMT-driven smart healthcare -- 8.1 Introduction -- 8.2 Architecture of Internet of Medical Things-driven smart healthcare -- 8.2.1 Things layer -- 8.2.2 Gateway layer -- 8.2.3 Cloud layer -- 8.2.4 Function layer -- 8.3 Emerging technologies in Internet of Medical Things-driven smart healthcare -- 8.3.1 Sensor technology in things layer.
  table of contents: 8.3.2 Communication technology in gateway layer -- 8.3.3 Cloud-blockchain enabled secure distributed computing in cloud layer -- 8.3.4 Artificial intelligence technology in function layer -- 8.4 Smart healthcare: modules and its application -- 8.5 Challenges and open research issues -- 8.5.1 Challenges in technical design -- 8.5.2 Social challenges -- 8.5.3 OpenResearch issues -- References -- 9 Internet of Things for e-health -- 9.1 Introduction -- 9.2 Role of Internet of Things in healthcare -- 9.2.1 Patients -- 9.2.2 Obstacles for healthcare providers -- 9.2.3 Difficulties for healthcare administrators -- 9.2.4 Government officials -- 9.2.5 Payers' challenges (government programs and insurance companies) -- 9.3 Fundamental Internet of Things applications in healthcare -- 9.3.1 Remote patient monitoring -- 9.3.2 Smart medical devices -- 9.3.3 Wearable health technology -- 9.3.4 Internet of Things in hospitals -- 9.4 Benefits of utilizing Internet of Things in healthcare -- 9.4.1 Transformative ways of the healthcare sector with involvement of Internet of Things -- 9.5 Where is Internet of Things in healthcare heading? -- 9.6 Security and privacy concerns -- 9.7 Future scope of Internet of Things in healthcare -- 9.8 Conclusion and outlook -- References -- 10 Blockchain based system for healthcare digital twin -- 10.1 Introduction -- 10.1.1 Background -- 10.1.2 Significance of healthcare digital twins -- 10.1.3 Emerging challenges in data security and patient privacy -- 10.2 Healthcare digital twin programs -- 10.2.1 Definition and overview -- 10.2.2 Transformative potential in patient care -- 10.2.3 Applications and use cases -- 10.3 Blockchain technology in healthcare -- 10.3.1 Introduction to blockchain -- 10.3.2 Decentralization and immutability -- 10.3.3 Relevance to securing healthcare data.
  note: edited by Tuan Anh Nguyen.
  subject:
    topic: Blockchains (Databases)
    topic: Medical applications
  subject:
    topic: Digital twins (Computer simulation)
  classification: R859.7.B56
  classification: 610.28
  identifier: 9780443303005
  identifier: http://proxy.library.tamu.edu/login
  record info:
    record content source: OPELS
    record creation date: 250224
    record change date: 20260327181123.6
    record identifier: in00005774360
    language of cataloging:
      language term: eng