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Blockchain and Deep Learning for Smart Healthcare / / edited by Akansha Singh, Anuradha Dhull, and Krishna Kant Singh
Blockchain and Deep Learning for Smart Healthcare / / edited by Akansha Singh, Anuradha Dhull, and Krishna Kant Singh
Edizione [First edition.]
Pubbl/distr/stampa Hoboken, NJ : , : John Wiley & Sons, Inc., , [2024]
Descrizione fisica 1 online resource (470 pages)
Disciplina 004.67/82
Soggetto topico Cloud computing - Security measures
Artificial intelligence
ISBN 1-119-79240-1
1-119-79239-8
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Cover -- Title Page -- Copyright Page -- Contents -- Preface -- Part 1: Blockchain Fundamentals and Applications -- Chapter 1 Blockchain Technology: Concepts and Applications -- 1.1 Introduction -- 1.2 Blockchain Types -- 1.3 Consensus -- 1.4 How Does Blockchain Work? -- 1.5 Need of Blockchain -- 1.6 Uses of Blockchain -- 1.7 Evolution of Blockchain -- 1.8 Blockchain in Ethereum -- 1.9 Advantages of Smart Contracts -- 1.10 Use Cases of Smart Contracts -- 1.11 Real-Life Example of Smart Contracts -- 1.12 Blockchain in Decentralized Applications -- 1.12.1 Advantages of DApps -- 1.12.2 Role of Blockchain in Metaverse -- 1.12.3 Uses of Blockchain in Metaverse Applications -- 1.12.4 Some Popular Examples of Metaverse Applications -- 1.13 Decentraland -- 1.14 Challenges Faced by Blockchain -- 1.15 Weaknesses of Blockchain -- 1.16 Future of Blockchain -- 1.17 Conclusion -- References -- Chapter 2 Blockchain with Federated Learning for Secure Healthcare Applications -- 2.1 Introduction -- 2.2 Federated Learning -- 2.3 Motivation -- 2.4 Federated Machine Learning -- 2.5 Federated Learning Frameworks -- 2.6 FL Perspective for Blockchain and IoT -- 2.7 Federated Learning Applications -- 2.8 Limitations -- References -- Chapter 3 Futuristic Challenges in Blockchain Technologies -- 3.1 Introduction -- 3.2 Blockchain -- 3.2.1 Background of Blockchain -- 3.2.2 Introduction to Cryptocurrencies: Bitcoin -- 3.2.3 Different Cryptocurrencies -- 3.2.4 Proof of Work (POW) -- 3.3 Issues and Challenges with Blockchain -- 3.4 Internet of Things (IoT) -- 3.5 Background of IoT -- 3.5.1 Issues and Challenges Faced by IoT -- 3.6 Conclusion -- References -- Chapter 4 AIML-Based Blockchain Solutions for IoMT -- 4.1 Introduction -- 4.2 Objective and Contribution -- 4.3 Security Challenges in Different Domains -- 4.4 Healthcare -- 4.5 Agriculture -- 4.6 Transportation.
4.7 Smart Grid -- 4.8 Smart City -- 4.9 Smart Home -- 4.10 Communication -- 4.11 Security Attacks in IoT -- 4.12 Solutions for Addressing Security Using Machine Learning -- 4.13 Solutions for Addressing Security Using Artificial Intelligence -- 4.14 Solutions for Addressing Security Using Blockchain -- 4.15 Summary -- 4.16 Critical Analysis -- 4.17 Conclusion -- References -- Chapter 5 A Blockchain-Based Solution for Enhancing Security and Privacy in the Internet of Medical Things (IoMT) Used in e-Healthcare -- 5.1 Introduction: E-Health and Medical Services -- 5.1.1 What is Blockchain? -- 5.1.2 What are the Advantages and Challenges of Blockchain in Healthcare? -- 5.2 Literature Review -- 5.3 Architecture of Blockchain-Enabled IoMT -- 5.3.1 Opportunities of Blockchain-Enabled IoMT -- 5.3.2 Security Improvement of IoMT -- 5.3.3 Privacy Preservation of IoMT Data -- 5.3.4 Traceability of IoMT Data -- 5.4 Proposed Methodology -- 5.4.1 Overview of the Proposed Architecture -- 5.4.2 Blockchain-Enabled IoMT Architecture -- 5.5 Conclusion and Future Work -- References -- Chapter 6 A Review on the Role of Blockchain Technology in the Healthcare Domain -- 6.1 Introduction -- 6.2 Systematic Literature Methodology -- 6.2.1 Data Sources -- 6.2.2 Selection of Studies -- 6.2.3 Data Extraction and Mapping Process -- 6.2.4 Results -- 6.3 Applications of Blockchain in the Healthcare Domain -- 6.3.1 Blockchains in Electronic Health Records (EHRs) -- 6.3.2 Blockchains in Clinical Research -- 6.3.3 Blockchains in Medical Fraud Detection -- 6.3.4 Blockchains in Neuroscience -- 6.3.5 Blockchains in Pharmaceutical Industry and Research -- 6.3.6 Electronic Medical Records Management -- 6.3.7 Remote Patient Monitoring -- 6.3.8 Drug Traceability -- 6.3.9 Securing IoT Medical Devices -- 6.3.10 Tracking Infectious Disease -- 6.4 Blockchain Challenges.
6.4.1 Resource Limitations and Bandwidth -- 6.4.2 Scalability -- 6.4.3 Lack of Standardization -- 6.4.4 Privacy Leakage -- 6.4.5 Interoperability -- 6.4.6 Security and Privacy of Data -- 6.4.7 Managing Storage Capacity -- 6.4.8 Standardization Challenges -- 6.4.9 Social Challenges -- 6.5 Future Research Directions and Perspectives -- 6.6 Implications and Conclusion -- References -- Chapter 7 Blockchain in Healthcare: Use Cases -- 7.1 Introduction -- 7.1.1 Features of Blockchains -- 7.2 Challenges Faced in the Healthcare Sector -- 7.3 Use Cases of Blockchains in the Healthcare Sector -- 7.3.1 Blockchains for Maintaining Electronic Health Records -- 7.3.2 Electronic Health Record Applications -- 7.3.3 Blockchains in Clinical Trials -- 7.3.4 Blockchains in Improving Patient-Doctor Interactions -- 7.4 What is Medicalchain? -- 7.4.1 Features of Medicalchain -- 7.4.2 Flow of the Processes in Medicalchain -- 7.4.3 The Medicalchain Currency -- 7.5 Implementing Blockchain in SCM -- 7.5.1 Working of this Technique -- 7.6 Why Use Blockchain in SCM -- References -- Part 2: Smart Healthcare -- Chapter 8 Potential of Blockchain Technology in Healthcare, Finance, and IoT: Past, Present, and Future -- 8.1 Introduction -- 8.2 Types of Blockchain -- 8.3 Literature Review -- 8.3.1 Challenges of Blockchain -- 8.3.2 Working of Blockchain -- 8.4 Methodology and Data Sources -- 8.4.1 Eligibility Criteria -- 8.4.2 Search Strategy -- 8.4.3 Study Selection Process -- 8.5 The Application of Blockchain Technology Across Various Industries -- 8.5.1 Finance -- 8.5.2 Healthcare -- 8.5.3 Internet of Things (IoT) -- 8.6 Conclusion -- References -- Chapter 9 AI-Enabled Techniques for Intelligent Transportation System for Smarter Use of the Transport Network for Healthcare Services -- 9.1 Introduction -- 9.2 Artificial Intelligence.
9.3 Artificial Intelligence: Transport System and Healthcare -- 9.4 Artificial Intelligence Algorithms -- 9.5 AI Workflow -- 9.6 AI for ITS and e-Healthcare Tasks -- 9.7 Intelligent Transportation, Healthcare, and IoT -- 9.8 AI Techniques Used in ITS and e-Healthcare -- 9.9 Challenges of AI and ML in ITS and e-Healthcare -- 9.10 Conclusions -- References -- Chapter 10 Classification of Dementia Using Statistical First-Order and Second-Order Features -- 10.1 Introduction -- 10.2 Materials and Methods -- 10.2.1 Dataset -- 10.2.2 Image Pre-Processing -- 10.3 Proposed Framework -- 10.3.1 Discrete Wavelet Transform -- 10.3.1.1 Statistical Features -- 10.3.2 Classification -- 10.3.2.1 K-Nearest Neighbor -- 10.3.2.2 Linear Discriminant Analysis -- 10.3.2.3 Support Vector Machine -- 10.3.3 Performance Measure -- 10.4 Experimental Results and Discussion -- 10.5 Conclusion -- References -- Chapter 11 Pulmonary Embolism Detection Using Machine and Deep Learning Techniques -- 11.1 Introduction -- 11.2 The State-of-the-Art of PE Detection Models -- 11.3 Literature Survey -- 11.4 Publications Analysis -- 11.5 Conclusion -- References -- Chapter 12 Computer Vision Techniques for Smart Healthcare Infrastructure -- 12.1 Introduction -- 12.2 Literature Survey -- 12.2.1 Computer Vision -- 12.2.1.1 Computer Vision Techniques for Safety and Driver Assistance -- 12.2.1.2 Types of Optical Character Recognition Systems -- 12.2.1.3 Phases of Optical Character Recognition -- 12.2.1.4 Threshold Segmentation -- 12.2.1.5 Edge Detection Operator -- 12.2.1.6 Use Cases of OCR -- 12.2.1.7 List of Research Papers -- 12.2.2 How is IoT Changing the Face of Information Science? -- 12.3 Proposed Idea -- 12.3.1 Phases of OCR Processing -- 12.3.1.1 Pre-Processing -- 12.3.1.2 Segmentation -- 12.4 Results -- 12.5 Conclusion -- References.
Chapter 13 Energy-Efficient Fog-Assisted System for Monitoring Diabetic Patients with Cardiovascular Disease -- 13.1 Introduction -- 13.2 Literature Review -- 13.3 Architectural Design of the Proposed Framework -- 13.4 Fog Services -- 13.4.1 Information Processing -- 13.4.2 Algorithm for Extracting Heart Rate and QT Interval -- 13.4.3 Activity Status Categorization and Fall Detection Algorithm -- 13.4.4 Interoperability -- 13.4.5 Security -- 13.4.6 Implementation of the Framework and Testbed Scenario -- 13.4.7 Sensor Layer Implementation -- 13.5 Smart Gateway and Fog Services Implementation -- 13.6 Cloud Servers -- 13.7 Experimental Results -- 13.8 Future Directions -- 13.9 Conclusion -- References -- Chapter 14 Medical Appliances Energy Consumption Prediction Using Various Machine Learning Algorithms -- 14.1 Introduction -- 14.2 Literature Review -- 14.3 Methodology -- 14.3.1 Dataset -- 14.3.2 Data Analysis and Pre-Processing -- 14.3.3 Descriptive Statistics -- 14.3.4 Correlation Matrix -- 14.3.5 Feature Selection -- 14.3.6 Data Scaling -- 14.4 Machine Learning Algorithms Used -- 14.4.1 Multiple Linear Regressor -- 14.4.2 Kernel Ridge Regression -- 14.4.3 Stochastic Gradient Descent (SGD) -- 14.4.4 Support Vector Machine (Support Vector Regression) -- 14.4.5 K-Nearest Neighbor Regressor (KNN) -- 14.4.6 Random Forest Regressor -- 14.4.7 Extremely Randomized Trees Regressor (Extra Trees Regressor) -- 14.4.8 Gradient Boosting Machine/Regressor (GBM) -- 14.4.9 Light GBM (LGBM) -- 14.4.10 Multilayer Perceptron Regressor (MLP) -- 14.4.11 Implementation -- 14.5 Results and Analysis -- 14.6 Model Analysis -- 14.7 Conclusion and Future Work -- References -- Part 3: Future of Blockchain and Deep Learning -- Chapter 15 Deep Learning-Based Smart e-Healthcare for Critical Babies in Hospitals -- 15.1 Introduction -- 15.2 Literature Survey -- 15.2.1 Methodology.
15.2.2 Data Collection.
Record Nr. UNINA-9910830708103321
Hoboken, NJ : , : John Wiley & Sons, Inc., , [2024]
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Communication and computing systems : proceedings of the International Conference on Communication and Computing Systems (ICCCS-2016), Dronacharya College of Engineering, Guragaon, India, 9-11 September, 2016 / / editors, B.M.K. Prasad, Krishna Kant Singh, Neelam Rubil, Karan Singh, Richard O'Kennedy
Communication and computing systems : proceedings of the International Conference on Communication and Computing Systems (ICCCS-2016), Dronacharya College of Engineering, Guragaon, India, 9-11 September, 2016 / / editors, B.M.K. Prasad, Krishna Kant Singh, Neelam Rubil, Karan Singh, Richard O'Kennedy
Pubbl/distr/stampa [Stuttgart, Germany] : , : CRC Press, , [2017]
Descrizione fisica 1 online resource (1,130 pages) : illustrations
Disciplina 005.8
Soggetto topico Computer networks - Access control
ISBN 1-315-31891-1
1-315-36409-3
1-315-31944-6
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Signal and image processing -- Communication and computer networks -- Software computing, intelligent system, machine vision and artificial neural network -- VLSI and embedded system -- Software engineering and emerging technologies.
Record Nr. UNINA-9910165039303321
[Stuttgart, Germany] : , : CRC Press, , [2017]
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Machine learning and cognitive computing for mobile communications and wireless networks / / edited by Krishna Kant [and three others]
Machine learning and cognitive computing for mobile communications and wireless networks / / edited by Krishna Kant [and three others]
Autore Singh Krishna
Edizione [1st edition]
Pubbl/distr/stampa West Sussex, England : , : John Wiley & Sons, Incorporated, , 2020
Descrizione fisica 1 online resource (270 pages) : illustrations
Disciplina 006.31
Soggetto topico Machine learning
ISBN 1-119-64057-1
1-119-64055-5
1-119-64054-7
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Record Nr. UNINA-9910555029703321
Singh Krishna  
West Sussex, England : , : John Wiley & Sons, Incorporated, , 2020
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Machine learning and cognitive computing for mobile communications and wireless networks / / edited by Krishna Kant [and three others]
Machine learning and cognitive computing for mobile communications and wireless networks / / edited by Krishna Kant [and three others]
Autore Singh Krishna
Edizione [1st edition]
Pubbl/distr/stampa West Sussex, England : , : John Wiley & Sons, Incorporated, , 2020
Descrizione fisica 1 online resource (270 pages) : illustrations
Disciplina 006.31
Soggetto topico Machine learning
ISBN 1-119-64057-1
1-119-64055-5
1-119-64054-7
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Record Nr. UNINA-9910824792503321
Singh Krishna  
West Sussex, England : , : John Wiley & Sons, Incorporated, , 2020
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Machine learning approaches for convergence of IoT and blockchain / / edited by Krishna Kant Singh, Akansha Singh, Sanjay K. Sharma
Machine learning approaches for convergence of IoT and blockchain / / edited by Krishna Kant Singh, Akansha Singh, Sanjay K. Sharma
Pubbl/distr/stampa Hoboken, New Jersey : , : Wiley-Scrivener, , [2021]
Descrizione fisica 1 online resource (256 pages)
Disciplina 006.31
Soggetto topico Machine learning
Internet of things
Blockchains (Databases)
ISBN 1-119-76187-5
1-119-76188-3
1-119-76180-8
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Cover -- Half-Title Page -- Series Page -- Title Page -- Copyright Page -- Contents -- Preface -- 1 Blockchain and Internet of Things Across Industries -- 1.1 Introduction -- 1.2 Insight About Industry -- 1.2.1 Agriculture Industry -- 1.2.2 Manufacturing Industry -- 1.2.3 Food Production Industry -- 1.2.4 Healthcare Industry -- 1.2.5 Military -- 1.2.6 IT Industry -- 1.3 What is Blockchain? -- 1.4 What is IoT? -- 1.5 Combining IoT and Blockchain -- 1.5.1 Agriculture Industry -- 1.5.2 Manufacturing Industry -- 1.5.3 Food Processing Industry -- 1.5.4 Healthcare Industry -- 1.5.5 Military -- 1.5.6 Information Technology Industry -- 1.6 Observing Economic Growth and Technology's Impact -- 1.7 Applications of IoT and Blockchain Beyond Industries -- 1.8 Conclusion -- References -- 2 Layered Safety Model for IoT Services Through Blockchain -- 2.1 Introduction -- 2.1.1 IoT Factors Impacting Security -- 2.2 IoT Applications -- 2.3 IoT Model With Communication Parameters -- 2.3.1 RFID (Radio Frequency Identification) -- 2.3.2 WSH (Wireless Sensor Network) -- 2.3.3 Middleware (Software and Hardware) -- 2.3.4 Computing Service (Cloud) -- 2.3.5 IoT Software -- 2.4 Security and Privacy in IoT Services -- 2.5 Blockchain Usages in IoT -- 2.6 Blockchain Model With Cryptography -- 2.6.1 Variations of Blockchain -- 2.7 Solution to IoT Through Blockchain -- 2.8 Conclusion -- References -- 3 Internet of Things Security Using AI and Blockchain -- 3.1 Introduction -- 3.2 IoT and Its Application -- 3.3 Most Popular IoT and Their Uses -- 3.4 Use of IoT in Security -- 3.5 What is AI? -- 3.6 Applications of AI -- 3.7 AI and Security -- 3.8 Advantages of AI -- 3.9 Timeline of Blockchain -- 3.10 Types of Blockchain -- 3.11 Working of Blockchain -- 3.12 Advantages of Blockchain Technology -- 3.13 Using Blockchain Technology With IoT -- 3.14 IoT Security Using AI and Blockchain.
3.15 AI Integrated IoT Home Monitoring System -- 3.16 Smart Homes With the Concept of Blockchain and AI -- 3.17 Smart Sensors -- 3.18 Authentication Using Blockchain -- 3.19 Banking Transactions Using Blockchain -- 3.20 Security Camera -- 3.21 Other Ways to Fight Cyber Attacks -- 3.22 Statistics on Cyber Attacks -- 3.23 Conclusion -- References -- 4 Amalgamation of IoT, ML, and Blockchain in the Healthcare Regime -- 4.1 Introduction -- 4.2 What is Internet of Things? -- 4.2.1 Internet of Medical Things -- 4.2.2 Challenges of the IoMT -- 4.2.3 Use of IoT in Alzheimer Disease -- 4.3 Machine Learning -- 4.3.1 Case 1: Multilayer Perceptron Network -- 4.3.2 Case 2: Vector Support Machine -- 4.3.3 Applications of the Deep Learning in the Healthcare Sector -- 4.4 Role of the Blockchain in the Healthcare Field -- 4.4.1 What is Blockchain Technology? -- 4.4.2 Paradigm Shift in the Security of Healthcare Data Through Blockchain -- 4.5 Conclusion -- References -- 5 Application of Machine Learning and IoT for Smart Cities -- 5.1 Functionality of Image Analytics -- 5.2 Issues Related to Security and Privacy in IoT -- 5.3 Machine Learning Algorithms and Blockchain Methodologies -- 5.3.1 Intrusion Detection System -- 5.3.2 Deep Learning and Machine Learning Models -- 5.3.3 Artificial Neural Networks -- 5.3.4 Hybrid Approaches -- 5.3.5 Review and Taxonomy of Machine Learning -- 5.4 Machine Learning Open Source Tools for Big Data -- 5.5 Approaches and Challenges of Machine Learning Algorithms in Big Data -- 5.6 Conclusion -- References -- 6 Machine Learning Applications for IoT Healthcare -- 6.1 Introduction -- 6.2 Machine Learning -- 6.2.1 Types of Machine Learning Techniques -- 6.2.2 Applications of Machine Learning -- 6.3 IoT in Healthcare -- 6.3.1 IoT Architecture for Healthcare System -- 6.4 Machine Learning and IoT.
6.4.1 Application of ML and IoT in Healthcare -- 6.5 Conclusion -- References -- 7 Blockchain for Vehicular Ad Hoc Network and Intelligent Transportation System: A Comprehensive Study -- 7.1 Introduction -- 7.2 Related Work -- 7.3 Connected Vehicles and Intelligent Transportation System -- 7.3.1 VANET -- 7.3.2 Blockchain Technology and VANET -- 7.4 An ITS-Oriented Blockchain Model -- 7.5 Need of Blockchain -- 7.5.1 Food Track and Trace -- 7.5.2 Electric Vehicle Recharging -- 7.5.3 Smart City and Smart Vehicles -- 7.6 Implementation of Blockchain Supported Intelligent Vehicles -- 7.7 Conclusion -- 7.8 Future Scope -- References -- 8 Applications of Image Processing in Teleradiology for the Medical Data Analysis and Transfer Based on IOT -- 8.1 Introduction -- 8.2 Pre-Processing -- 8.2.1 Principle of Diffusion Filtering -- 8.3 Improved FCM Based on Crow Search Optimization -- 8.4 Prediction-Based Lossless Compression Model -- 8.5 Results and Discussion -- 8.6 Conclusion -- Acknowledgment -- References -- 9 Innovative Ideas to Build Smart Cities with the Help of Machine and Deep Learning and IoT -- 9.1 Introduction -- 9.2 Related Work -- 9.3 What Makes Smart Cities Smart? -- 9.3.1 Intense Traffic Management -- 9.3.2 Smart Parking -- 9.3.3 Smart Waste Administration -- 9.3.4 Smart Policing -- 9.3.5 Shrewd Lighting -- 9.3.6 Smart Power -- 9.4 In Healthcare System -- 9.5 In Homes -- 9.6 In Aviation -- 9.7 In Solving Social Problems -- 9.8 Uses of AI-People -- 9.8.1 Google Maps -- 9.8.2 Ridesharing -- 9.8.3 Voice-to-Text -- 9.8.4 Individual Assistant -- 9.9 Difficulties and Profit -- 9.10 Innovations in Smart Cities -- 9.11 Beyond Humans Focus -- 9.12 Illustrative Arrangement -- 9.13 Smart Cities with No Differentiation -- 9.14 Smart City and AI -- 9.15 Further Associated Technologies -- 9.15.1 Model Identification -- 9.15.2 Picture Recognition.
9.15.3 IoT -- 9.15.4 Big Data -- 9.15.5 Deep Learning -- 9.16 Challenges and Issues -- 9.16.1 Profound Learning Models -- 9.16.2 Deep Learning Paradigms -- 9.16.3 Confidentiality -- 9.16.4 Information Synthesis -- 9.16.5 Distributed Intelligence -- 9.16.6 Restrictions of Deep Learning -- 9.17 Conclusion and Future Scope -- References -- Index -- EULA.
Record Nr. UNINA-9910554844003321
Hoboken, New Jersey : , : Wiley-Scrivener, , [2021]
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Machine learning approaches for convergence of IoT and blockchain / / edited by Krishna Kant Singh, Akansha Singh, Sanjay K. Sharma
Machine learning approaches for convergence of IoT and blockchain / / edited by Krishna Kant Singh, Akansha Singh, Sanjay K. Sharma
Pubbl/distr/stampa Hoboken, New Jersey : , : Wiley-Scrivener, , [2021]
Descrizione fisica 1 online resource (256 pages)
Disciplina 006.31
Soggetto topico Machine learning
Internet of things
Blockchains (Databases)
ISBN 1-119-76187-5
1-119-76188-3
1-119-76180-8
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Cover -- Half-Title Page -- Series Page -- Title Page -- Copyright Page -- Contents -- Preface -- 1 Blockchain and Internet of Things Across Industries -- 1.1 Introduction -- 1.2 Insight About Industry -- 1.2.1 Agriculture Industry -- 1.2.2 Manufacturing Industry -- 1.2.3 Food Production Industry -- 1.2.4 Healthcare Industry -- 1.2.5 Military -- 1.2.6 IT Industry -- 1.3 What is Blockchain? -- 1.4 What is IoT? -- 1.5 Combining IoT and Blockchain -- 1.5.1 Agriculture Industry -- 1.5.2 Manufacturing Industry -- 1.5.3 Food Processing Industry -- 1.5.4 Healthcare Industry -- 1.5.5 Military -- 1.5.6 Information Technology Industry -- 1.6 Observing Economic Growth and Technology's Impact -- 1.7 Applications of IoT and Blockchain Beyond Industries -- 1.8 Conclusion -- References -- 2 Layered Safety Model for IoT Services Through Blockchain -- 2.1 Introduction -- 2.1.1 IoT Factors Impacting Security -- 2.2 IoT Applications -- 2.3 IoT Model With Communication Parameters -- 2.3.1 RFID (Radio Frequency Identification) -- 2.3.2 WSH (Wireless Sensor Network) -- 2.3.3 Middleware (Software and Hardware) -- 2.3.4 Computing Service (Cloud) -- 2.3.5 IoT Software -- 2.4 Security and Privacy in IoT Services -- 2.5 Blockchain Usages in IoT -- 2.6 Blockchain Model With Cryptography -- 2.6.1 Variations of Blockchain -- 2.7 Solution to IoT Through Blockchain -- 2.8 Conclusion -- References -- 3 Internet of Things Security Using AI and Blockchain -- 3.1 Introduction -- 3.2 IoT and Its Application -- 3.3 Most Popular IoT and Their Uses -- 3.4 Use of IoT in Security -- 3.5 What is AI? -- 3.6 Applications of AI -- 3.7 AI and Security -- 3.8 Advantages of AI -- 3.9 Timeline of Blockchain -- 3.10 Types of Blockchain -- 3.11 Working of Blockchain -- 3.12 Advantages of Blockchain Technology -- 3.13 Using Blockchain Technology With IoT -- 3.14 IoT Security Using AI and Blockchain.
3.15 AI Integrated IoT Home Monitoring System -- 3.16 Smart Homes With the Concept of Blockchain and AI -- 3.17 Smart Sensors -- 3.18 Authentication Using Blockchain -- 3.19 Banking Transactions Using Blockchain -- 3.20 Security Camera -- 3.21 Other Ways to Fight Cyber Attacks -- 3.22 Statistics on Cyber Attacks -- 3.23 Conclusion -- References -- 4 Amalgamation of IoT, ML, and Blockchain in the Healthcare Regime -- 4.1 Introduction -- 4.2 What is Internet of Things? -- 4.2.1 Internet of Medical Things -- 4.2.2 Challenges of the IoMT -- 4.2.3 Use of IoT in Alzheimer Disease -- 4.3 Machine Learning -- 4.3.1 Case 1: Multilayer Perceptron Network -- 4.3.2 Case 2: Vector Support Machine -- 4.3.3 Applications of the Deep Learning in the Healthcare Sector -- 4.4 Role of the Blockchain in the Healthcare Field -- 4.4.1 What is Blockchain Technology? -- 4.4.2 Paradigm Shift in the Security of Healthcare Data Through Blockchain -- 4.5 Conclusion -- References -- 5 Application of Machine Learning and IoT for Smart Cities -- 5.1 Functionality of Image Analytics -- 5.2 Issues Related to Security and Privacy in IoT -- 5.3 Machine Learning Algorithms and Blockchain Methodologies -- 5.3.1 Intrusion Detection System -- 5.3.2 Deep Learning and Machine Learning Models -- 5.3.3 Artificial Neural Networks -- 5.3.4 Hybrid Approaches -- 5.3.5 Review and Taxonomy of Machine Learning -- 5.4 Machine Learning Open Source Tools for Big Data -- 5.5 Approaches and Challenges of Machine Learning Algorithms in Big Data -- 5.6 Conclusion -- References -- 6 Machine Learning Applications for IoT Healthcare -- 6.1 Introduction -- 6.2 Machine Learning -- 6.2.1 Types of Machine Learning Techniques -- 6.2.2 Applications of Machine Learning -- 6.3 IoT in Healthcare -- 6.3.1 IoT Architecture for Healthcare System -- 6.4 Machine Learning and IoT.
6.4.1 Application of ML and IoT in Healthcare -- 6.5 Conclusion -- References -- 7 Blockchain for Vehicular Ad Hoc Network and Intelligent Transportation System: A Comprehensive Study -- 7.1 Introduction -- 7.2 Related Work -- 7.3 Connected Vehicles and Intelligent Transportation System -- 7.3.1 VANET -- 7.3.2 Blockchain Technology and VANET -- 7.4 An ITS-Oriented Blockchain Model -- 7.5 Need of Blockchain -- 7.5.1 Food Track and Trace -- 7.5.2 Electric Vehicle Recharging -- 7.5.3 Smart City and Smart Vehicles -- 7.6 Implementation of Blockchain Supported Intelligent Vehicles -- 7.7 Conclusion -- 7.8 Future Scope -- References -- 8 Applications of Image Processing in Teleradiology for the Medical Data Analysis and Transfer Based on IOT -- 8.1 Introduction -- 8.2 Pre-Processing -- 8.2.1 Principle of Diffusion Filtering -- 8.3 Improved FCM Based on Crow Search Optimization -- 8.4 Prediction-Based Lossless Compression Model -- 8.5 Results and Discussion -- 8.6 Conclusion -- Acknowledgment -- References -- 9 Innovative Ideas to Build Smart Cities with the Help of Machine and Deep Learning and IoT -- 9.1 Introduction -- 9.2 Related Work -- 9.3 What Makes Smart Cities Smart? -- 9.3.1 Intense Traffic Management -- 9.3.2 Smart Parking -- 9.3.3 Smart Waste Administration -- 9.3.4 Smart Policing -- 9.3.5 Shrewd Lighting -- 9.3.6 Smart Power -- 9.4 In Healthcare System -- 9.5 In Homes -- 9.6 In Aviation -- 9.7 In Solving Social Problems -- 9.8 Uses of AI-People -- 9.8.1 Google Maps -- 9.8.2 Ridesharing -- 9.8.3 Voice-to-Text -- 9.8.4 Individual Assistant -- 9.9 Difficulties and Profit -- 9.10 Innovations in Smart Cities -- 9.11 Beyond Humans Focus -- 9.12 Illustrative Arrangement -- 9.13 Smart Cities with No Differentiation -- 9.14 Smart City and AI -- 9.15 Further Associated Technologies -- 9.15.1 Model Identification -- 9.15.2 Picture Recognition.
9.15.3 IoT -- 9.15.4 Big Data -- 9.15.5 Deep Learning -- 9.16 Challenges and Issues -- 9.16.1 Profound Learning Models -- 9.16.2 Deep Learning Paradigms -- 9.16.3 Confidentiality -- 9.16.4 Information Synthesis -- 9.16.5 Distributed Intelligence -- 9.16.6 Restrictions of Deep Learning -- 9.17 Conclusion and Future Scope -- References -- Index -- EULA.
Record Nr. UNINA-9910830668203321
Hoboken, New Jersey : , : Wiley-Scrivener, , [2021]
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui