Healthcare Paradigms in the Internet of Things Ecosystem

HEALTHCARE PARADIGMS IN THE INTERNET OF THINGS ECOSYSTEM
Copyright
Contributors
Preface
About the editors
About the book
1. The fundamentals of Internet of Things: architectures, enabling technologies, and applications
	1. Introduction
	2. Internet of Things
	3. Architecture of IoT
	4. Enabling technologies of IoT
		4.1 Radio frequency identification
		4.2 Electronic product code
		4.3 Wireless sensor network
		4.4 Near field communication
		4.5 Actuator
		4.6 ZigBee
		4.7 Z-Wave
		4.8 Bluetooth LE
	5. Applications of IoT
		5.1 National
		5.2 Transportation
		5.3 Healthcare
		5.4 Home and personal use
		5.5 Community and social utilities
		5.6 Smart environment
		5.7 Industrial
		5.8 Agriculture
		5.9 Futuristic
	6. Research challenges and issues in IoT
		6.1 Massive scaling or addressing
		6.2 Creating knowledge, Big Data, and data mining
		6.3 Interoperability
		6.4 Cloud computing
		6.5 Fog computing
		6.6 Security
		6.7 Privacy
		6.8 Standardization
	7. Summary
	References
2. IoT for healthcare industries: a tale of revolution
	1. Introduction
	2. Component and mechanism of IoT
		2.1 Sensor
		2.2 Sensor classification
		2.3 Uses of sensors in internet of things
		2.4 Gateway
		2.5 How does an IoT gateway device work?
		2.6 Need for gateway devices in IoT
			2.6.1 Reducing the crack between operational technology and information technology
			2.6.2 Additional security level
			2.6.3 Real-time updates in the field
		2.7 Communication network
			2.7.1 Satellite
			2.7.2 Satellite communication—advantages and disadvantages
			2.7.3 Wi-Fi
			2.7.4 Advantages and disadvantages
			2.7.5 Radio frequency
			2.7.6 Advantages and disadvantages
			2.7.7 Radio frequency identification
			2.7.8 Advantages and disadvantages
			2.7.9 Bluetooth
				2.7.10 Near-field communication
				2.7.11 Modes of NFC
				2.7.12 Advantages and disadvantages
		2.8 Data analytics
			2.8.1 Data analytics and IoT combined—business impact
	3. IoT in healthcare
		3.1 IoT—the new resident doctor
		3.2 History of IoT in healthcare
		3.3 Challenges in current healthcare system
		3.4 IoT healthcare services and applications
		3.5 IoMT industrial market
		3.6 IoT healthcare market—target audience
	4. Reducing healthcare costs with IoT
	5. Challenges of using IoT in the healthcare segment
	6. Conclusion
	References
3. Big data based hybrid machine learning model for improving performance of medical Internet of Things data in healthcare systems
	1. Introduction to Big Data and IoT
		1.1 Types of Big Data
		1.2 Advantages of Big Data processing
		1.3 Architecture of IoT
		1.4 Standards of IoT applications
	2. Relationship between Internet of Things and Big Data
	3. Role of Big Data and IoT in Healthcare Systems
	4. Architecture of Apache Flume and Spark
		4.1 Components of Apache Flume
		4.2 Components of Apache Spark
	5. Data analytics for IoT using Big Data analytics
	6. Big Data pipeline for IoT data storage and processing
		6.1 Proposed Big Data pipeline for processing IoT medical data
		6.2 Hybrid prediction model for diabetes detection
			6.2.1 Step procedure of DBSCAN algorithm
	7. Conclusion and future directions
	References
	Further reading
4. The role of Internet of Things for adaptive traffic prioritization in wireless body area networks
	1. Introduction to wireless body area network
	2. Hardware architecture of biomedical sensor
		2.1 Methods for deployment of biomedical sensors
		2.2 Data dissemination of sensory information
		2.3 Requirements of BMSs in WBAN
	3. Applications of medical sensors
	4. Data dissemination protocols in WBAN
		4.1 Routing protocols
		4.2 Medium access control protocols
	5. Introduction to Internet of Things
		5.1 Applications of IoT
		5.2 Data dissemination architecture using healthcare-IoT
	6. Open issues of WBAN
	7. Open issues of IoT
	8. Conclusion
	References
	Further reading
5. Spatiotemporal pattern and hotspot detection of malaria using spatial analysis and GIS in West Bengal: an approach to medic ...
	1. Introduction
	2. Data and methods
		2.1 Study area
		2.2 Spatial data collection, integration, and management
		2.3 Measures of disease about its occurrences
		2.4 Spatial filtering and smoothing
		2.5 Inverse difference weighted method
		2.6 Hotspot detection and analysis
	3. Results and analysis
		3.1 Spatial analysis
		3.2 Spatial distribution of malaria diseases
		3.3 High-low clustering of malaria distribution
		3.4 Hotspot analysis of malaria distribution
	4. Discussion
		4.1 Challenges to controlling the malaria of West Bengal
	5. Recommendations
	6. Conclusions
	References
	Further reading
6. Integration of Cloud and IoT for smart e-healthcare
	1. Introduction
	2. Related work and application areas
	3. Background terms
		3.1 Internet of Things driven healthcare
			3.1.1 Hierarchical architecture
		3.2 Cloud computing for healthcare
	4. Cloud IoT integration for healthcare systems
	5. Cloud IoT complimentary aspects and drivers for integration
	6. Architecture framework for healthcare system
		6.1 Data acquisition/sensing layer
		6.2 Data transmission/sending layer
		6.3 Cloud processing/storing layer
	7. A Conceptual Healthcare Scenario
	8. Design considerations for healthcare architecture
	9. Cloud IoT security threats and issues
		9.1 Security features and goals
		9.2 Security vulnerabilities
			9.2.1 IoT issues and limitations
				9.2.1.1 Issues in perception layer
				9.2.1.2 Issues at network layer
				9.2.1.3 Issues at application layer
			9.2.2 Cloud service issues
		9.3 Potential defense strategies
	10. Platforms and services
		10.1 Platforms
			10.1.1 Available platforms
			10.1.2 Available services
	11. Challenges and open issues
		11.1 Security and privacy
		11.2 Protocol support and need for standards
		11.3 Efficient power usage
		11.4 Delay and limited bandwidth
		11.5 Quality of service
	12. Discussion and conclusion
	References
	Further reading
7. IoT-based location-aware smart healthcare framework with user mobility support in normal and emergency scenario: a comprehe ...
	1. Introduction to smart and remote healthcare system
	2. Introduction of location-aware healthcare system with mobility support
		2.1 Functional framework
		2.2 Application in healthcare
		2.3 Location-aware protocols
	3. Learning techniques for healthcare system
		3.1 IoT-based healthcare applications
		3.2 Learning techniques used for IoT-based healthcare applications
			3.2.1 Supervised learning
				3.2.1.1 Instance-based learning
				3.2.1.2 Decision tree (J48)
				3.2.1.3 Multilayer Perceptron
				3.2.1.4 Ensemble learners
			3.2.2 Unsupervised learning
				3.2.2.1 k-means clustering
				3.2.2.2 Density-based spatial clustering of applications with noise
			3.2.3 Deep learning techniques
				3.2.3.1 Convolutional neural network
				3.2.3.2 Recurrent neural network
				3.2.3.3 Open research issues
	References
	Further reading
8. Remote health monitoring protocols for IoT-enabled healthcare infrastructure
	1. Introduction
	2. System architecture for IoT-based healthcare
		2.1 Wearable sensing devices
		2.2 Wireless body area network
	3. Potential applications
		3.1 Activity monitoring
		3.2 Healthcare monitoring
		3.3 User-centric applications
	4. Research challenges
		4.1 Energy efficiency
		4.2 User mobility
		4.3 High degree of diversity
	5. Overview of protocol standards
		5.1 IEEE 802.15.4 standard
		5.2 IEEE 802.15.6 standard
		5.3 IEEE 802.11 standard
		5.4 Bluetooth technology
	6. Energy-aware protocols for IoT-based healthcare applications
		6.1 MAC and routing protocols for Tier-1 architecture
		6.2 Routing protocols for tier-2 architecture
	7. Overview of protocols for proactive health monitoring systems
	8. Open research issues
	9. Conclusions
	References
9. Wearable sensor networks for patient health monitoring: challenges, applications, future directions, and acoustic sensor ch ...
	1. Introduction
	2. Key enabling technique of a wearable body network: sensing
		2.1 Sensing technology
	3. Human activity monitoring and e-health sensors
		3.1 E-health sensors
	4. Computable indications in healthcare monitoring
		4.1 Vital signs
		4.2 Body motions
		4.3 Metabolism sensors
	5. Transportable devices
		5.1 Wrist devices
		5.2 Head-mounted devices
		5.3 E-textiles
	6. Attachable devices
		6.1 Wearable skin patches
		6.2 Contact lens
		6.3 Implantable devices
		6.4 Ingestible pills
	7. Textile-based wearable devices and appliances
		7.1 Textile-based electronic devices and systems
		7.2 Textile-based energy devices
	8. Measurement mechanism
		8.1 Response time and physical phenomenon
		8.2 Robustness
		8.3 Sensitivity and linearity
		8.4 Wireless communication
		8.5 Self-power
		8.6 Multifunctional sensing
		8.7 Intellectualization
	9. Wearable sensor applications
		9.1 Safety monitoring
		9.2 Assessment of treatment efficacy
		9.3 Early detection of disorders
		9.4 Home rehabilitation
	10. Underwater wireless sensor network
		10.1 Underwater sensor network architecture
		10.2 Routing protocols and challenges
		10.3 Underwater sensor network applications
		10.4 Challenges and requirements
	11. Short note on next-generation sensor networks
	12. Conclusions and future work
	References
	Further reading
10. RFID technology in health-IoT
	1. History
	2. Introduction
	3. IoT and RFID technology
		3.1 Internet of Things
		3.2 Common challenges of IoT
		3.3 RFID technology
		3.4 RFID tags
		3.5 RFID reader
	4. Functions of RFID technology
	5. Applications of RFID technology
	6. Challenges of RFID technology
	7. IoT healthcare networks
		7.1 The IoThNet topology
		7.2 The IoThNet architecture
		7.3 The IoThNet platform
			7.3.1 IoT healthcare challenges and open issues
	8. IoT healthcare services
		8.1 The internet of m-health things
		8.2 Ambient assisted living
		8.3 Community healthcare
		8.4 Adverse drug reaction
		8.5 Children health information
		8.6 Semantic medical access
		8.7 Wearable device access
		8.8 Indirect emergency healthcare
		8.9 Embedded context prediction
		8.10 Embedded gateway configuration
	9. IoT healthcare applications
		9.1 Electroccardiogram monitoring
		9.2 Glucose level sensing
		9.3 Body temperature monitoring
		9.4 Blood pressure monitoring
		9.5 Rehabilitation system
		9.6 Oxygen saturation monitoring
		9.7 Imminent healthcare solutions
		9.8 Medication management
		9.9 Wheelchair management
		9.10 Healthcare solutions using smartphones
	10. IoT healthcare industry developments and status
	11. IoT system for in-home healthcare
		11.1 Health-IoT
		11.2 The Food-IoT
	12. Conclusion
	References
	Further reading
11. Principles and paradigms in IoT-based healthcare using RFID
	1. Introduction
	2. IoT-based healthcare architecture
	3. Why need IoT
	4. Challenges in IoT healthcare
		4.1 Security and privacy issue
		4.2 Data accuracy
		4.3 Connectivity
		4.4 Compatibility
		4.5 Privacy
	5. IoT-driven system in IoT healthcare
		5.1 IoT-based infant check system
		5.2 A Medical-IoT-based framework
		5.3 Heterogeneous Internet of Medical Things platforms
	6. RFID technology and its working
		6.1 Tag
		6.2 Antenna
		6.3 Management system
	7. Current RFID technology
		7.1 Energy source
		7.2 Passive tag
		7.3 Advantages of passive tag
		7.4 Disadvantages of passive tag
		7.5 Active tag
		7.6 Advantages of active tag
		7.7 Disadvantages of active tag
		7.8 Semi-passive tag
	8. RFID in healthcare
		8.1 Patient monitoring
		8.2 Patient tracking
		8.3 Monitoring section
		8.4 Tracking section
		8.5 Hospital equipment monitoring
		8.6 Drug management system
		8.7 Hospital supply chain management system
		8.8 Human implantation
		8.9 Blood management system using RFID
	9. RFID technology for IoT-based personal healthcare
	10. RFID security concern
		10.1 Security issue of tag data
		10.2 Eavesdropping
		10.3 Spoofing
		10.4 Daniel service attack
		10.5 Traffic analysis
		10.6 RFID reader issues
			10.6.1 How to make RFID tag protected
			10.6.2 Protection of RFID reader
	11. Recommendation
	12. Conclusion
	References
	Further reading
12. Low-cost system in the analysis of the recovery of mobility through inertial navigation techniques and virtual reality
	1. Introduction
	2. Materials and methods
		2.1 Proposal
		2.2 Gait analysis
		2.3 Hardware component
		2.4 Inertial navigation unit
		2.5 Data acquisition unit
		2.6 Wireless transmission unit
		2.7 Virtual reality unit
		2.8 Video game unit
		2.9 Physical support unit
		2.10 Registration unit
		2.11 How the proposal works
	3. Results
	4. Conclusions
	Bibliography
13. Control and remote monitoring of muscle activity and stimulation in the rehabilitation process for muscle recovery
	1. Introduction
	2. Materials and methods
		2.1 Control unit
		2.2 Evaluation unit
		2.3 Stimulation unit
		2.4 Computer application unit
		2.5 How the proposal works
	3. Results
	4. Conclusions
	Bibliography
14. Healthcare technology trade-offs for IoT ecosystems from a developing country perspective: case of Egypt
	1. Introduction
	2. Current state of the art
	3. Architecture and components
	4. Architecture and components
		4.1 Requirements and limitations
		4.2 Feasibility and effectiveness
		4.3 Security and privacy
	5. Emerging applications
	6. Opportunities and challenges for the future
	7. Conclusions
	References
15. Study of asian diabetic subjects based on gender, age, and insulin parameters: healthcare application with IoT and Big Data
	1. Introduction and background
		1.1 History of IoT
		1.2 IoT as medical healthcare
		1.3 Future perspective of IoT
	2. Big Data characteristics
		2.1 Applications of Big Data: healthcare
		2.2 Role of Big Data in IoT
		2.3 Big Data tools
		2.4 Big Data security
	3. Tension-type headache
		3.1 Right time to seek medical emergency?
		3.2 Preventions
		3.3 Tension-type headache, stress, and its causes
		3.4 Types of stress
		3.5 Stress symptoms
			3.5.1 Emotional stress
			3.5.2 Physical symptoms of stress
			3.5.3 Cognitive symptoms of stress
			3.5.4 Behavioral symptoms of stress
			3.5.5 Long-term stress effect
		3.6 Handling of stress
	4. Migraine versus TTH
		4.1 Chronic headache
		4.2 Hypertension
	5. Mental health
	6. Diabetes mellitus and its symptoms
		6.1 Type-1 diabetes
		6.2 Type-2 diabetes
		6.3 CVD, CAN, and CAD
		6.4 Insulin
		6.5 Hypoglycemia
		6.6 Depression
		6.7 Obesity
		6.8 Diets for diagnosing the Type-2 diabetes
	7. Literature survey
	8. Results, interpretation, and discussion
	9. About the study and analysis
		9.1 Gender distribution
		9.2 Age group distribution
		9.3 Age group and gender distribution
		9.4 Analysis: TTH distribution in the sample
		9.5 Diabetes type distribution in the sample
		9.6 Diabetes and insulin consumption
		9.7 Diabetes type and gender distribution
	10. Novelties in our work
	11. Future scope, limitations, and possible applications
	12. Tableau S/W, applications with benefits
	13. Recommendations and future considerations
	14. Conclusion
	Acknowledgments
	References
	Further reading
16. Design and development of IoT-based decision support system for dengue analysis and prediction: case study on Sri Lankan co ...
	1. Introduction
	2. Internet of things, cloud computing, and fog computing
		2.1 Internet of things
		2.2 Internet of medical things
		2.3 Cloud computing
		2.4 Fog computing
	3. IoT-based decision support system for dengue analysis and prediction
		3.1 Fuzzy Rule Neural Classification method for disease prediction and diagnosis for dengue severity
	4. Proposed architecture for dengue analysis and prediction decision support system
		4.1 Proposed system functionalities
		4.2 Data sources
		4.3 Patient health data
		4.4 Medicinal data
		4.5 Cloud layer
		4.6 Fog computing layer
		4.7 IoT security layer
		4.8 Drug and food recommendation system
		4.9 Dengue analysis and prediction flowchart diagram
		4.10 Use case diagram
	5. Conclusion and future works
	References
Index
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