Buchumschlag

Blockchain for Secure Healthcare Using Internet of Medical Things (IoMT)

Healthcare has become an extremely important and relevant topic in day to day discussions ever since the COVID-19 pandemic has been encountered by the global population. This has led to a renewed focus and attention that researchers from every discipline have put in to realize better strategies for...

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Bibliographische Detailangaben
Hauptverfasser: Gupta, Sunil (VerfasserIn), Sharma, Hitesh Kumar (VerfasserIn), Kapoor, Monit (VerfasserIn)
Körperschaft: SpringerLink (Online service)
Format: Elektronisch E-Book
Sprache:Englisch
Veröffentlicht: Cham : Springer International Publishing : Imprint: Springer, 2023.
Ausgabe:1st ed. 2023.
Schlagworte:
Blockchains (Databases).
Medical informatics.
Internet of things.
Blockchain.
Health Informatics.
Internet of Things.
Online-Zugang:https://doi.org/10.1007/978-3-031-18896-1
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Inhaltsangabe:
  • 1. Chapter
  • 1.1. Introduction
  • 1.2. Smart Healthcare and Telemedical System
  • 1.2.1. Smart Healthcare Technology
  • 1.2.2. Remote monitoring and automated healthcare system
  • 1.2.3. Remote Care and Telehealth
  • 1.2.4. Emergency response solution for connectivity
  • 1.2.5. Smart Hospital Management
  • 1.3. Telemedical Healthcare
  • 1.3.1. Registration Phase
  • 1.3.2. Login Phase and Mutual Authentication
  • 1.3.3. Telemedicine Server
  • 1.4. Intelligent Medical Care using IoT
  • 1.5. Smart Healthcare: Challenges and Threats
  • Conclusion
  • References
  • 2. Chapter
  • 2.1. Introduction
  • 2.2. IoT Related Sub-Components
  • 2.2.1. Embedded programming
  • 2.2.2. Hardware device
  • 2.2.3. Security
  • 2.2.4. Networking and cloud Integration
  • 2.2.5. Data Analytics and prediction
  • 2.2.6. Machine Learning and AI
  • 2.3. Architecture of IoT
  • 2.3.1. Sensors and Actuators
  • 2.3.2. Internet gateway
  • 2.3.3. Edge Computing IT System
  • 2.3.4. Data Centre and Cloud
  • 2.3.5. Application of IoT
  • 2.3.6. Smart Homes
  • 2.3.7. Smart Agriculture
  • 2.3.8. Energy Management
  • 2.3.9. Industrial Internet
  • 2.4. IoT In Healthcare
  • 2.4.1. Remote patient monitoring
  • 2.4.2. Real time Data Tracking
  • 2.4.3. Connected wearables
  • 2.5. Internet of Medical Things (IoMT or IoMedT)
  • 2.6. Challenges for IoMT
  • Conclusion
  • References
  • 3. Chapter
  • 3.1. Introduction
  • 3.2. IoT Components
  • 3.2.1. Devices/Sensors
  • 3.2.2. Connectivity
  • 3.2.3. Data Processing
  • 3.2.4. User Interface
  • 3.3. IoMedT Components
  • 3.3.1. Patient and Payer
  • 3.3.2. Connected Medical Devices
  • 3.3.3. Communication Services (Connectivity)
  • 3.3.4. Analytics Platform (Data Processing
  • 3.3.5. Service Providers
  • 3.4. Integration of Latest Technology with IoMedT
  • 3.5. Benefits and Challenges of IoMedT
  • 3.5.1. Benefits of IoMedT
  • 3.5.2. Challenges in IoMedT
  • Conclusion
  • References
  • 4. Chapter
  • 4.1. Introduction to Smart healthcare and IoMT
  • 4.2. Perception layer - Sensor systems for data collection
  • 4.2.1. Gateway layer
  • 4.2.2. Management service layer/application support layer- data storage
  • 4.2.3. Application/service layer
  • 4.3. IoMT: A boon in healthcare
  • 4.4. Challenges of IoMT
  • 4.5. Benefits of IoMT
  • 4.6. Structural components of IoMT
  • 4.7. Functional components of IoMT
  • 4.8. Structural and Functional Challenges
  • Conclusion
  • References
  • 5. Chapter
  • 5.1. Introduction
  • 5.2. Working of Blockchain
  • 5.2.1. Distributed Database
  • 5.2.2. A network of nodes
  • 5.2.3. Building Trust
  • 5.3. Benefits of Blockchain Technology
  • 5.3.1. Time-saving
  • 5.3.2. Cost-saving
  • 5.3.3. Tighter security
  • 5.4. Application of Blockchain
  • 5.4.1. Asset Management
  • 5.4.2. Cross-Border Payments
  • 5.4.3. Healthcare
  • 5.4.4. Cryptocurrency
  • 5.4.5. Birth and Death Certificates
  • 5.4.6. Online Identity Verification
  • 5.4.7. Internet of Things
  • 5.4.8. Copyright and Royalties
  • 5.5. Application of Blockchain in Smart Healthcare
  • 5.5.1. Research
  • 5.5.2. Seamless switching of patients between providers
  • 5.5.3. Faster, cheaper, better patient care
  • 5.5.4. Interoperable electronic health records
  • 5.5.5. Data security
  • 5.5.6. Mobile health apps and remote monitoring
  • 5.5.7. Tracing and securing medical supplies
  • 5.5.8. Health insurance claims
  • 5.5.9. Tracking diseases and outbreaks
  • 5.5.10. Safeguarding genomics
  • Conclusion
  • References
  • 6. Chapter
  • 6.1. Introduction
  • 6.2. Possible Security Attacks in DMR Internet of Things Networks
  • 6.3. Security Schemes and There Challenges in DMR
  • Conclusion
  • References
  • 7. Chapter
  • 7.1. Introduction
  • 7.2. Benefits of IoMT in Smart Healthcare
  • 7.2.1. Cost Reduction
  • 7.2.2. Improve Treatment
  • 7.2.3. Faster Disease Diagnosis
  • 7.2.4. Drug and Equipment Management
  • 7.2.5. Error Reduction
  • 7.3. Tools and Technique for IoMT in Smart Healthcare
  • 7.3.1. Electronic Health Record (EHR)
  • 7.3.2. Referral Trackers
  • 7.3.3. Patient Portals
  • 7.3.4. Remote Patient Monitoring
  • 7.3.5. Computerized Provider Order Entry
  • 7.4. Use case of IoMT in Healthcare Industry
  • 7.4.1. Internet of things for patients
  • 7.4.2. Internet of things for Hospitals
  • 7.4.3. Internet of things for Physicians
  • 7.4.4. Internet of things for Business
  • 7.4.5. Internet of things for Health Insurance Companies
  • 7.5. Privacy and Security Issue in IoMT
  • 7.5.1. Patients are not in charge of their own information
  • 7.5.2. Present to Your Own Device (BYOD)
  • 7.5.3. Telecommuting presents security chances
  • 7.6. Challenges of IoMT in Smart Healthcare
  • 7.6.1. Underdeveloped Initiatives
  • 7.6.2. Unavailability of Memory
  • 7.6.3. Keeping Updated
  • 7.6.4. Data Security
  • 7.6.5. Global healthcare regulations
  • 7.6.6. Scalable Platforms
  • 7.6.7. Data Overloading
  • 7.7. Impact of IoMT on the future of the healthcare industry
  • Conclusion
  • References
  • 8. Chapter
  • 8.1. Introduction
  • 8.1.1. Big Data relation with Cloud Computing
  • 8.1.2. Relationship between IoMT and Big Data
  • 8.1.3. Big Data and the Internet of Medical Things
  • 8.1.4. IoT and Cloud Computing
  • 8.1.5. Benefits of using big data, IoT and the cloud
  • 8.2. IoMT needs to be integrated with cloud computing
  • 8.3. Integration of IoT and Cloud Computing
  • 8.4. Benefits of integrating IoT and cloud computing
  • Conclusion
  • References
  • 9. Chapter
  • 9.1. Introduction
  • 9.1.1. IoT in Smart Healthcare Systems
  • 9.2. Background/Present state in Data security
  • 9.2.1. Data Security requirements in Smart Healthcare Systems
  • 9.3. Privacy and QoS in smart healthcare
  • 9.4. Data Security and Privacy Issues in Healthcare
  • 9.5. QoS Parameters for Smart Healthcare
  • 9.6. Suggested Security Techniques to Preserve QoS
  • Conclusion
  • References
  • 10. Chapter
  • 10.1. Introduction
  • 10.2. Authentication Schemes for Tele Medical Healthcare System
  • 10.3. Processes of an authentication protocol
  • Conclusion
  • References
  • 11. Chapter
  • 11.1. Introduction
  • 11.1.1. Security
  • 11.1.2. Features
  • 11.2. Types of Blockchain Networks
  • 11.2.1. Public blockchain network
  • 11.2.2. Private blockchain network
  • 11.2.3. Permissioned blockchain network
  • 11.2.4. Consortium Blockchain networks
  • 11.3. Applications of Blockchain
  • 11.3.1. Smart contracts
  • 11.3.2. Involving Blockchain into Internet of Things (IOT)
  • 11.3.3. Preventing Identity Theft
  • 11.4. Application of Blockchain in Smart Healthcare
  • 11.4.1. Keeping transparency in delivering healthcare goods
  • 11.4.2. Storing of medical data of patients
  • 11.4.3. Remote health monitoring using IOT and blockchain
  • 11.5. Electronic Health Record (EHR) and its Storage
  • 11.5.1. Medical Big Data Mining and Processing in e-Healthcar
  • 11.5.2. Smart healthcare systems using big data
  • 11.6. Significance of Blockchain in Security of Electronic Health Record (EHR)
  • Conclusion
  • References
  • 12. Chapter
  • 12.1. Introduction
  • 12.1.1. A Different Healthcare World
  • 12.2. Components of Telemedicine
  • 12.2.1. Teleconsultation
  • 12.2.2. Telementoring
  • 12.2.3. Telemonitoring
  • 12.3. Emerging technologies in telemedicine
  • 12.3.1. Technologies proceeding telemedicine
  • 12.3.2. mRNA Technology
  • 12.3.3. Neurotechnology
  • 12.3.4. Precision Medicine
  • 12.3.5. Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR)
  • 12.3.6. Health Wearables
  • 12.3.7. Technology in Mental Health
  • 12.3.8. Artificial Intelligence
  • 12.3.9. Augmented and virtual reality
  • 12.3.10. Tele-robots
  • 12.3.11. IoT and nanotechnology
  • 12.3.12. 3D Printing
  • 12.3.13. Enhanced Access to Medical Data and Information
  • 12.3.14. Big Data
  • 12.3.15. Improved Lines of Communication
  • 12.3.16. Electronic Health Records
  • 12.3.17. Metaverse
  • Conclusion
  • References
  • 13. Chapter
  • 13.1. Introduction
  • 13.1.1. AI and Machine Learning
  • 13.1.2. Cloud Computing
  • 13.1.3. Cyber security/Cloud Security
  • 13.2. Role of Artificial Intelligence, Cloud Computing, and Internet Security in Smart Healthcare
  • 13.2.1. Artificial Intelligence and Machine Learning (AIML) in Healthcare Systems 182
  • 13.2.2. Early Cancer Diagnosis
  • 13.2.3. Diagnosis of Fatal Blood Diseases
  • 13.2.4. Customer Service Chatbots
  • 13.2.5. Managing the Medical Records
  • 13.2.6. Dosage Errors
  • 13.2.7. Robotic Surgeries
  • 13.3. Cloud Computing in Healthcare Systems
  • 13.4. Security Challenge in Smart Healthcare
  • Conclusion
  • References
  • 14. Chapter
  • 14.1. Introduction
  • 14.1.1. Capturing storage techniques for healthcare data
  • 14.1.2. About Healthcare Data
  • 14.1.3. Data storage
  • 14.1.4. Onsite data storage
  • 14.1.5. Public cloud data storage
  • 14.1.6. Hybrid cloud data storage solution
  • 14.1.7. Benefits of storing data on the cloud from multiple sources
  • 14.2. ML-enabled storage systems
  • 14.3. The current state of technology
  • 14.4. Enhancing existing Enterprise Data Warehouses (EDW)
  • 14.5. Background work
  • 14.6. ML techniques for treatment of healthcare data
  • 14.7. Smart access techniques for storage systems
  • 14.8. Prediction of diseases on healthcare data, both batch, and real-time data streams 197
  • Conclusion
  • References
  • 15. Chapter
  • 15.1. Introduction
  • 15.2. Smart Healthcare Tools and Techniques
  • 15.2.1. Cloud Computing in Smart Healthcare
  • 15.2.2. Medical Records Centralization
  • 15.2.3. Promoting Patient Engagement
  • 15.2.4. Better Scalability
  • 15.2.5. Cost-Effectiveness
  • 15.2.6. Advanced Analytics for Healthcare
  • 15.3. Current and Future application of AI, IoT, Blockchain and Cloud Computing in Smart Healthcare . 210
  • 15.3.1. Applications of Artificial Intelligence in Smart Healthcare
  • 15.3.2. Machine learning neural networks and deep learning
  • 15.3.3. Physical robots 15.3.4. Natural language processing (NLP.

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