11365nam 2200613 450 991058448360332120231110223117.0981-19-1408-7(MiAaPQ)EBC7046604(Au-PeEL)EBL7046604(CKB)24267611600041(EXLCZ)992426761160004120230104d2022 uy 0engurcnu||||||||txtrdacontentcrdamediacrrdacarrierInternet of things based smart healthcare intelligent and secure solutions applying machine learning techniques /Suparna Biswas [and three others] editorsSingapore :Springer,[2022]©20221 online resource (394 pages)Smart computing and intelligencePrint version: Biswas, Suparna Internet of Things Based Smart Healthcare Singapore : Springer,c2022 9789811914072 Includes bibliographical references.Intro -- Contents -- IoT Based Smart Healthcare -- Wearable Sensors and Machine Intelligence for Smart Healthcare -- 1 Introduction -- 2 Presents Healthcare Issues and Challenges for Remote Patients -- 3 The Possibilities of IoT as an Alternate to Conventional Healthcare System -- 4 IoT-Enabled Healthcare System -- 4.1 General Architecture -- 4.2 Proposed Architecture for the Healthcare System -- 4.3 Proposed Model -- 4.4 Component Description -- 4.5 Working Procedure of Healthcare Model -- 5 The Need and Importance of Machine Learning in Smart Healthcare -- 6 Conclusion -- References -- Architecture for Smart Healthcare: Cloud Versus Edge -- 1 Introduction -- 2 Role of Cloud Computing in Smart Healthcare Architecture -- 2.1 Properties of Cloud Computing -- 2.2 Utilities of Cloud Computing -- 2.3 Deployment Models of Cloud Computing -- 2.4 Different Architectures of Cloud Computing Used in Smart Healthcare -- 3 Role of Edge Computing in Smart Healthcare Architecture -- 3.1 Utilities of Edge Computing -- 3.2 Different Proposed Architectures of Edge Computing Used in Smart Healthcare -- 3.3 Limitation of Edge Computing -- 4 Difference Between Cloud of Edge on Smart Healthcare Perspective -- 5 Conclusion -- References -- The Medical Internet of Things: A Review of Intelligent Machine Learning and Deep Learning Applications for Leveraging Healthcare -- 1 Introduction -- 2 The Architecture of MIoT -- 2.1 The Perception Layer -- 2.2 The Network Layer -- 2.3 The Application Layer -- 3 IoT in Healthcare -- 3.1 IoT Services and Applications -- 3.2 IoT Healthcare Applications -- 3.3 Benefits of IoT in HealthCare -- 4 Machine Learning and Deep Learning Applications for MIoT -- 4.1 Machine Learning and Deep Learning Applications -- 5 Related Work and Discussion -- 5.1 Summary -- 6 Challenges -- 7 Future Directions -- 8 Conclusion -- References.Main Challenges and Concerns of IoT Healthcare -- 1 Introduction -- 2 Applications of IoT in Healthcare -- 3 Benefits of IoT in Healthcare -- 4 Role of Cloud and Edge Computing in IoT Healthcare Services -- 4.1 Role of Cloud Computing in IoT Healthcare Services -- 4.2 Role of Edge Computing in IoT Healthcare -- 5 Challenges and Concerns of Healthcare IoT Ecosystem -- 5.1 Security and Privacy -- 5.2 Device Vulnerability -- 5.3 Interoperability -- 5.4 Connectivity -- 5.5 Volume of Data and Its Analytics -- 5.6 Energy Efficiency -- 5.7 Trust Issues and Government Policies -- 5.8 Other Challenges -- 6 Open Issues -- 7 Conclusion -- References -- Challenges of Handling Data in IoT-Enabled Healthcare -- 1 Introduction -- 2 IoT Healthcare Services and Applications -- 2.1 Services -- 2.2 IoT Applications -- 3 Challenges of Health Data -- 3.1 Inter-Domain Authentication and Interoperability -- 3.2 Security and Privacy -- 3.3 Device Communication -- 3.4 Management of Data -- 4 Uncertainties in Data -- 4.1 Types of Uncertainty in Healthcare -- 4.2 Sources of Uncertainty in IoT System -- 5 Statistical Methods -- 6 Case Studies -- 6.1 Accuracy-Related Error Prediction -- 6.2 Results for Precision Error Reduction -- 7 Virtual Sensor-Based Infrastructure -- 8 Conclusion -- References -- Context and Body Vitals Monitoring Systems -- Human Activity Recognition Systems Based on Sensor Data Using Machine Learning -- 1 Introduction -- 1.1 Classification of HAR According to Sensor Deployment -- 1.2 General Components of HAR System -- 1.3 Few Challenges of HAR in IoHT with Their Solution -- 2 Activity Recognition Method: A Machine Learning (ML) Approach -- 2.1 Why ML is to Be Used in HAR -- 2.2 Data Preprocessing: -- 2.3 Learning and Inference -- 2.4 Why to Prefer Modern ML Techniques and Deep Learning -- 3 Different State-Of-The-Art ML/DL Techniques.4 Future Direction of Research -- References -- Human Activity Recognition Systems Based on Audio-Video Data Using Machine Learning and Deep Learning -- 1 Introduction -- 2 HAR -- 3 Sensory Data, Audio and Video Data for HAR -- 3.1 Sensory Data -- 3.2 Audio Data -- 3.3 Video Data -- 4 ML and DL in HAR -- 4.1 ML in HAR -- 4.2 Challenges of ML in HAR -- 4.3 DL in HAR -- 4.4 Challenges of DL in HAR -- 5 Implementation of HAR -- 5.1 Experimental Environment -- 6 Evaluation of HAR Systems -- 6.1 Evaluation Methodologies -- 6.2 Evaluation Metrics -- 7 Case Studies -- 8 Conclusion -- References -- On Body Vitals Monitoring for Disease Prediction: A Systematic Survey -- 1 Introduction to the Need for Generalized IOT Healthcare Paradigm -- 2 Role of Body Vital Monitoring System for Disease Prediction in IOT Healthcare -- 3 Valuable Vital Signs and Their Need to Be Monitored -- 3.1 Electrocardiogram (ECG) -- 3.2 Heart Rate (HR) -- 3.3 Blood Pressure (BP) -- 3.4 Respiration Rate -- 3.5 Blood Oxygen Saturation (SpO2) -- 3.6 Body Temperature -- 4 Review on the Recent Technological Advances in the Remote Healthcare Monitoring System -- 5 Summary -- References -- Review of Body Vitals Monitoring Systems for Disease Prediction -- 1 Introduction -- 2 Relevant Works -- 2.1 Data Collection -- 2.2 Analysis Techniques -- 3 Open Research Issues -- 4 Applications of Smart Devices -- 4.1 Personal ECG Monitor -- 4.2 Portable Smart Watch -- 4.3 Smart Glucometer -- 4.4 Brain Sensing Headband -- 4.5 Smart Temporal Thermometer -- 4.6 Fertility Tracking Bracelet -- 4.7 Pain Relief Device -- 4.8 Bio Scarf -- 5 Data Security -- 6 Technical Analysis -- 6.1 Data Preprocessing -- 6.2 Feature Extraction -- 6.3 Learning Approaches -- 6.4 Performance Measure -- 7 Conclusion -- References -- Quantitative Assessment of Smartphone Usage in College Students-A Digital Phenotyping Approach.1 Introduction -- 2 Experiment and Study Design -- 2.1 Study Procedure -- 2.2 Incentives and Privacy Considerations -- 2.3 Data Collection -- 3 Smartphone Technology -- 3.1 Working of an Accelerometer -- 4 Activity Detection -- 5 Sleep Detection -- 6 Sociability -- 7 Location and Mobility Patterns -- 7.1 Mobility Patterns -- 8 Discussions -- 8.1 Smartphone Addiction: Mobile Usage Hours -- 8.2 Sleep Quality Impact -- 9 Conclusions -- References -- Home Automation System Combining Internet-of-Things with Brain-Computer Interfacing -- 1 Introduction -- 1.1 The Application of Smart Health Care -- 1.2 Home Automation Related to Health Care -- 1.3 Human Brain -- 1.4 Electrode Placement in Human Brain -- 1.5 Brain-Computer Interface -- 1.6 Electroencephalogram Using Machine Learning -- 1.7 Internet-of-Things Devices and Technologies -- 2 Literature Survey -- 3 Proposed Work -- 3.1 Electrode Placement and Data Acquisition -- 3.2 Preprocessing -- 3.3 Signal Processing -- 3.4 Application Device Control System -- 4 Results -- 4.1 Experimental Setup -- 4.2 EEG Recording and Data Collection -- 5 Conclusion and Future Direction -- References -- Social Sensing Applications for Public Health -- ``Montaj'': A Gaming System for Assessing Cognitive Skills in a Mobile Computing Platform -- 1 Introduction -- 2 Design and Development -- 2.1 Device Compatibility and System Installation -- 2.2 Life Cycle of a Study -- 2.3 Use Cases Diagram -- 2.4 Data Flow Diagram (DFD) -- 2.5 Entity Relationship (ER) Diagram -- 2.6 Games in `Montaj': Registration and Removal-Flexibility of the System -- 2.7 Games Made Available with the System -- 2.8 Built in Search Facilities of `Montaj' -- 2.9 Provision for Importing New Games -- 3 Testing and Validation -- 4 Novelty of System Implemented in the System -- 4.1 Capability of Accommodating Externally Implemented Games.4.2 Novelty of the Games Implemented in the System -- 5 Usability Analysis -- 6 Conclusion -- References -- Social Data Analysis Techniques and Applications -- 1 Introduction -- 2 Social Sensing Application in Public Health -- 3 Social Data in Public Health -- 4 Social Data Analysis Techniques in Public health -- 4.1 Natural Language Processing -- 4.2 News Analytic -- 4.3 Opinion Mining -- 4.4 Scraping -- 4.5 Sentiment Analysis -- 4.6 Text Analytics -- 4.7 Social Network Analysis -- 5 State of Art Social Data Applications -- 6 SNA Techniques and Applications in Public Health -- 7 Conclusion -- References -- Challenges and Limitations of Social Data Analysis Approaches -- 1 Introduction -- 2 General Challenges -- 2.1 Technical Limitations -- 2.2 Actionability Concern -- 2.3 Ethical Considerations -- 3 Other Issues for Social Data Analysis -- 3.1 Issues of Social Data Collection -- 3.2 Issues for Processing Data -- 3.3 Issues Analysing Data -- 4 Social Data in Real-World Applications -- 5 Conclusion -- References -- Reliability, Security and Privacy of Health Data -- IoT-Based Secure Health Care: Challenges, Requirements and Case Study -- 1 Introduction -- 2 Traditional Versus Modern Architecture -- 3 Security Threats -- 4 Importance of Privacy and Security -- 4.1 Mutual-Authentication -- 4.2 Confidentiality -- 4.3 Anonymity -- 4.4 Data Freshness -- 4.5 Data Integrity -- 4.6 Data Availability -- 5 Taxonomy of Privacy and Security in Health Care -- 5.1 Access Control Schemes -- 5.2 Authentication Schemes -- 5.3 Encryption Schemes -- 6 Case Study on Intrusion Detection System for Health Care -- 6.1 Models -- 6.2 Desired Features of Healthcare IDS and IPS -- 6.3 Commercial IDS and IPS -- 6.4 Open Research Issues -- 7 Conclusion -- References.Applications of IoT and Blockchain Technologies in Healthcare: Detection of Cervical Cancer Using Machine Learning Approaches.Smart Computing and Intelligence Internet of thingsMedical innovationsMedicineData processingInternet de les cosesthubProcessament de dadesthubMedicinathubLlibres electrònicsthubInternet of things.Medical innovations.MedicineData processing.Internet de les cosesProcessament de dadesMedicina004.678Biswas SuparnaMiAaPQMiAaPQMiAaPQBOOK9910584483603321Internet of things based smart healthcare3000654UNINA