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Ambient Intelligence and Internet of Things : Convergent Technologies
| Ambient Intelligence and Internet of Things : Convergent Technologies |
| Autore | Mahmood Rashid |
| Pubbl/distr/stampa | Newark : , : John Wiley & Sons, Incorporated, , 2022 |
| Descrizione fisica | 1 online resource (421 pages) |
| Altri autori (Persone) |
RajaRohit
KaurHarpreet KumarSandeep NagwanshiKapil Kumar |
| Soggetto genere / forma | Electronic books. |
| ISBN |
9781119821830
9781119821236 |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Cover -- Title Page -- Copyright Page -- Contents -- Preface -- Chapter 1 Ambient Intelligence and Internet of Things: An Overview -- 1.1 Introduction -- 1.2 Ambient Intelligent System -- 1.3 Characteristics of AmI Systems -- 1.4 Driving Force for Ambient Computing -- 1.5 Ambient Intelligence Contributing Technologies -- 1.6 Architecture Overview -- 1.7 The Internet of Things -- 1.8 IoT as the New Revolution -- 1.9 IoT Challenges -- 1.10 Role of Artificial Intelligence in the Internet of Things (IoT) -- 1.11 IoT in Various Domains -- 1.12 Healthcare -- 1.13 Home Automation -- 1.14 Smart City -- 1.15 Security -- 1.16 Industry -- 1.17 Education -- 1.18 Agriculture -- 1.19 Tourism -- 1.20 Environment Monitoring -- 1.21 Manufacturing and Retail -- 1.22 Logistics -- 1.23 Conclusion -- References -- Chapter 2 An Overview of Internet of Things Related Protocols, Technologies, Challenges and Application -- 2.1 Introduction -- 2.1.1 History of IoT -- 2.1.2 Definition of IoT -- 2.1.3 Characteristics of IoT -- 2.2 Messaging Protocols -- 2.2.1 Constrained Application Protocol -- 2.2.2 Message Queue Telemetry Transport -- 2.2.3 Extensible Messaging and Presence Protocol -- 2.2.4 Advance Message Queuing Protocol (AMQP) -- 2.3 Enabling Technologies -- 2.3.1 Wireless Sensor Network -- 2.3.2 Cloud Computing -- 2.3.3 Big Data Analytics -- 2.3.4 Embedded System -- 2.4 IoT Architecture -- 2.5 Applications Area -- 2.6 Challenges and Security Issues -- 2.7 Conclusion -- References -- Chapter 3 Ambient Intelligence Health Services Using IoT -- 3.1 Introduction -- 3.2 Background of AML -- 3.2.1 What is AML? -- 3.3 AmI Future -- 3.4 Applications of Ambient Intelligence -- 3.4.1 Transforming Hospitals and Enhancing Patient Care With the Help of Ambient Intelligence -- 3.4.2 With Technology, Life After the COVID-19 Pandemic -- 3.5 COVID-19 -- 3.5.1 Prevention.
3.5.2 Symptoms -- 3.6 Coronavirus Worldwide -- 3.7 Proposed Framework for COVID-19 -- 3.8 Hardware and Software -- 3.8.1 Hardware -- 3.8.2 Heartbeat Sensor -- 3.8.3 Principle -- 3.8.4 Working -- 3.8.5 Temperature Sensor -- 3.8.6 Principle -- 3.8.7 Working -- 3.8.8 BP Sensor -- 3.8.9 Principle -- 3.8.10 Working -- 3.9 Mini Breadboard -- 3.10 Node MCU -- 3.11 Advantages -- 3.12 Conclusion -- References -- Chapter 4 Security in Ambient Intelligence and Internet of Things -- 4.1 Introduction -- 4.2 Research Areas -- 4.3 Security Threats and Requirements -- 4.3.1 Ad Hoc Network Security Threats and Requirements -- 4.3.1.1 Availability -- 4.3.1.2 Confidentiality -- 4.3.1.3 Integrity -- 4.3.1.4 Key Management and Authorization -- 4.3.2 Security Threats and Requirements Due to Sensing Capability in the Network -- 4.3.2.1 Availability -- 4.3.2.2 Confidentiality -- 4.3.2.3 Integrity -- 4.3.2.4 Key Distribution and Management -- 4.3.2.5 Resilience to Node Capture -- 4.3.3 Security Threats and Requirements in AmI and IoT Based on Sensor Network -- 4.3.3.1 Availability -- 4.3.3.2 Confidentiality -- 4.3.3.3 Confidentiality of Location -- 4.3.3.4 Integrity -- 4.3.3.5 Nonrepudiation -- 4.3.3.6 Fabrication -- 4.3.3.7 Intrusion Detection -- 4.3.3.8 Confidentiality -- 4.3.3.9 Trust Management -- 4.4 Security Threats in Existing Routing Protocols that are Designed With No Focus on Security in AmI and IoT Based on Sensor Networks -- 4.4.1 Infrastructureless -- 4.4.1.1 Dissemination-Based Routing -- 4.4.1.2 Context-Based Routing -- 4.4.2 Infrastructure-Based -- 4.4.2.1 Network with Fixed Infrastructure -- 4.4.2.2 New Routing Strategy for Wireless Sensor Networks to Ensure Source Location Privacy -- 4.5 Protocols Designed for Security Keeping Focus on Security at Design Time for AmI and IoT Based on Sensor Network -- 4.5.1 Secure Routing Algorithms. 4.5.1.1 Identity-Based Encryption (I.B.E.) Scheme -- 4.5.1.2 Policy-Based Cryptography and Public Encryption with Keyword Search -- 4.5.1.3 Secure Content-Based Routing -- 4.5.1.4 Secure Content-Based Routing Using Local Key Management Scheme -- 4.5.1.5 Trust Framework Using Mobile Traces -- 4.5.1.6 Policy-Based Authority Evaluation Scheme -- 4.5.1.7 Optimized Millionaire's Problem -- 4.5.1.8 Security in Military Operations -- 4.5.1.9 A Security Framework Application Based on Wireless Sensor Networks -- 4.5.1.10 Trust Evaluation Using Multifactor Method -- 4.5.1.11 Prevention of Spoofing Attacks -- 4.5.1.12 QoS Routing Protocol -- 4.5.1.13 Network Security Virtualization -- 4.5.2 Comparison of Routing Algorithms and Impact on Security -- 4.5.3 Inducing Intelligence in IoT Networks Using Artificial Intelligence -- 4.5.3.1 Fuzzy Logic-1 -- 4.5.3.2 Fuzzy Logic-2 -- 4.6 Introducing Hybrid Model in Military Application for Enhanced Security -- 4.6.1 Overall System Architecture -- 4.6.2 Best Candidate Selection -- 4.6.3 Simulation Results in Omnet++ -- 4.6 Conclusion -- References -- Chapter 5 Futuristic AI Convergence of Megatrends: IoT and Cloud Computing -- 5.1 Introduction -- 5.1.1 Our Contribution -- 5.2 Methodology -- 5.2.1 Statistical Information -- 5.3 Artificial Intelligence of Things -- 5.3.1 Application Areas of IoT Technologies -- 5.3.1.1 Energy Management -- 5.3.1.2 5G/Wireless Systems -- 5.3.1.3 Risk Assessment -- 5.3.1.4 Smart City -- 5.3.1.5 Health Sectors -- 5.4 AI Transforming Cloud Computing -- 5.4.1 Application Areas of Cloud Computing -- 5.4.2 Energy/Resource Management -- 5.4.3 Edge Computing -- 5.4.4 Distributed Edge Computing and Edge-of-Things (EoT) -- 5.4.5 Fog Computing in Cloud Computing -- 5.4.6 Soft Computing and Others -- 5.5 Conclusion -- References. Chapter 6 Analysis of Internet of Things Acceptance Dimensions in Hospitals -- 6.1 Introduction -- 6.2 Literature Review -- 6.2.1 Overview of Internet of Things -- 6.2.2 Internet of Things in Healthcare -- 6.2.3 Research Hypothesis -- 6.2.3.1 Technological Context (TC) -- 6.2.3.2 Organizational Context (OC) -- 6.2.3.3 Environmental Concerns (EC) -- 6.3 Research Methodology -- 6.3.1 Demographics of the Respondents -- 6.4 Data Analysis -- 6.4.1 Reliability and Validity -- 6.4.1.1 Cronbach's Alpha -- 6.4.1.2 Composite Reliability -- 6.4.2 Exploratory Factor Analysis (EFA) -- 6.4.3 Confirmatory Factor Analysis Results -- 6.4.3.1 Divergent or Discriminant Validity -- 6.4.4 Structural Equation Modeling -- 6.5 Discussion -- 6.5.1 Technological Context -- 6.5.2 Organizational Context -- 6.5.3 Environmental Context -- 6.6 Conclusion -- References -- Chapter 7 Role of IoT in Sustainable Healthcare Systems -- 7.1 Introduction -- 7.2 Basic Structure of IoT Implementation in the Healthcare Field -- 7.3 Different Technologies of IoT for the Healthcare Systems -- 7.3.1 On the Basis of the Node Identification -- 7.3.2 On the Basis of the Communication Method -- 7.3.3 Depending on the Location of the Object -- 7.4 Applications and Examples of IoT in the Healthcare Systems -- 7.4.1 IoT-Based Healthcare System to Encounter COVID-19 Pandemic Situations -- 7.4.2 Wearable Devices -- 7.4.3 IoT-Enabled Patient Monitoring Devices From Remote Locations -- 7.4.3.1 Pulse Rate Sensor -- 7.4.3.2 Respiratory Rate Sensors -- 7.4.3.3 Body Temperature Sensors -- 7.4.3.4 Blood Pressure Sensing -- 7.4.3.5 Pulse Oximetry Sensors -- 7.5 Companies Associated With IoT and Healthcare Sector Worldwide -- 7.6 Conclusion and Future Enhancement in the Healthcare System With IoT -- References -- Chapter 8 Fog Computing Paradigm for Internet of Things Applications -- 8.1 Introduction. 8.2 Challenges -- 8.3 Fog Computing: The Emerging Era of Computing Paradigm -- 8.3.1 Definition of Fog Computing -- 8.3.2 Fog Computing Characteristic -- 8.3.3 Comparison Between Cloud and Fog Computing Paradigm -- 8.3.4 When to Use Fog Computing -- 8.3.5 Fog Computing Architecture for Internet of Things -- 8.3.6 Fog Assistance to Address the New IoT Challenges -- 8.3.7 Devices Play a Role of Fog Computing Node -- 8.4 Related Work -- 8.5 Fog Computing Challenges -- 8.6 Fog Supported IoT Applications -- 8.7 Summary and Conclusion -- References -- Chapter 9 Application of Internet of Things in Marketing Management -- 9.1 Introduction -- 9.2 Literature Review -- 9.2.1 Customer Relationship Management -- 9.2.2 Product Life Cycle (PLC) -- 9.2.3 Business Process Management (BPM) -- 9.2.4 Ambient Intelligence (AmI) -- 9.2.5 IoT and CRM Integration -- 9.2.6 IoT and BPM Integration -- 9.2.7 IoT and Product Life Cycle -- 9.2.8 IoT in MMgnt -- 9.2.9 Impacts of AmI on Marketing Paradigms -- 9.3 Research Methodology -- 9.4 Discussion -- 9.4.1 Research Proposition 1 -- 9.4.2 Research Proposition 2 -- 9.4.3 Research Proposition 3 -- 9.4.4 Research Proposition 4 -- 9.4.5 Research Proposition 5 -- 9.5 Results -- 9.4 Conclusions -- References -- Chapter 10 Healthcare Internet of Things: A New Revolution -- 10.1 Introduction -- 10.2 Healthcare IoT Architecture (IoT) -- 10.3 Healthcare IoT Technologies -- 10.3.1 Technology for Identification -- 10.3.2 Location Technology -- 10.3.2.1 Mobile-Based IoT -- 10.3.2.2 Wearable Devices -- 10.3.2.3 Ambient-Assisted Living (AAL) -- 10.3.3 Communicative Systems -- 10.3.3.1 Radiofrequency Identification -- 10.3.3.2 Bluetooth -- 10.3.3.3 Zigbee -- 10.3.3.4 Near Field Communication -- 10.3.3.5 Wireless Fidelity (Wi-Fi) -- 10.3.3.6 Satellite Communication -- 10.4 Community-Based Healthcare Services -- 10.5 Cognitive Computation. 10.6 Adverse Drug Reaction. |
| Record Nr. | UNINA-9910646196503321 |
Mahmood Rashid
|
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| Newark : , : John Wiley & Sons, Incorporated, , 2022 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Intelligent IT Solutions for Sustainability in Industry 5. 0 Paradigm : Select Proceedings of ICEIL 2023
| Intelligent IT Solutions for Sustainability in Industry 5. 0 Paradigm : Select Proceedings of ICEIL 2023 |
| Autore | Shukla Balvinder |
| Edizione | [1st ed.] |
| Pubbl/distr/stampa | Singapore : , : Springer Singapore Pte. Limited, , 2024 |
| Descrizione fisica | 1 online resource (517 pages) |
| Altri autori (Persone) |
MurthyB. K
HasteerNitasha KaurHarpreet Van BelleJean-Paul |
| Collana | Lecture Notes in Electrical Engineering Series |
| ISBN |
9789819716821
9789819716814 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Intro -- Preface -- Contents -- About the Editors -- Participation of Cybersecurity Practitioners in a Cybersecurity CoP in Africa -- 1 Introduction -- 2 Literature Review -- 3 Methodology -- 4 Research Findings and Discussion -- 4.1 Low Cybersecurity Talent Pool Affects CoP Participation -- 4.2 Content Development Affects CoP Participation -- 4.3 Overworked and Stressed Cybersecurity Practitioners Have Low CoP Participation -- 4.4 Organisational Support Facilitates CoP Participation -- 4.5 Availability of Cybersecurity Influencers and Active Community Members -- 4.6 Institutional Resource Support Facilitates CoP Participation -- 5 Conclusion -- References -- Parallel Corpus Development Using Machine Translation -- 1 Introduction -- 2 Machine Translation Systems -- 2.1 Statistical Machine Translation -- 2.2 Neural Machine Translation -- 2.3 Neural Machine Translation Using Transformer -- 3 Comparable and Parallel Corpus Development -- 4 Experiments and Results -- 5 Conclusion -- References -- A Study on Indian Digital Banking Online Customer Experience -- 1 Introduction -- 2 Literature Review -- 3 Hypotheses -- 4 Research Methodology -- 5 Findings and Discussion -- 5.1 Measurement Model -- 5.2 Structural Model -- 6 Results -- 7 Theoretical Contribution -- 8 Managerial Implications -- 9 Conclusion and Limitations -- References -- A Comparative Analysis and Statistical Inference of Diabetes Cases -- 1 Introduction -- 2 Related Work -- 3 Methodology -- 4 Results -- 4.1 Comparative Analysis -- 5 Conclusion and Future Work -- References -- Impact of Gamification on Student Learning: An Empirical Evidence -- 1 Introduction -- 2 Module Design -- 3 Methodology -- 4 Results and Discussion -- 5 Lesson Learned -- 6 Conclusion -- References -- Measuring Impact of Generative AI in Software Development and Innovation -- 1 Introduction.
2 Generative AI Tools in Software Development and Innovation -- 3 Generative AI Algorithms Steps in Software Development and Innovation -- 4 Prior Work -- 5 Conclusion -- 6 Future Directions/Scope -- References -- Sustainability in the Digital Era: Case Study of a Security Equipment Manufacturing SME -- 1 Introduction -- 2 Literature Review -- 3 Materials and Methods -- 3.1 Company Description -- 3.2 Methods and Tools -- 4 SWOT Analysis of Enablers of the Case Organization -- 5 Conclusion -- References -- Using Monte Carlo Methods for Retirement Simulations of the 401K and IRA -- 1 Introduction -- 2 Proposed Model -- 3 Model Parameters -- 4 Case Studies -- 5 Conclusion -- Appendix -- References -- A Novel Classification Scheme for Credit Card Fraud Detection Using Data Mining -- 1 Introduction -- 2 Literature Review -- 3 Methodology -- 3.1 Proposed Methodology Framework -- 4 Results -- 4.1 Dataset -- 4.2 Pre-processing Result -- 4.3 Tool Used -- 4.4 Other Approaches -- 5 Discussion of Fraud Detected in Various Countries -- 6 Conclusion -- References -- Analyzing the Impact of UPI on Supply Chain Performance: A Natural Language Processing Approach with Generative Pre-trained Transformers -- 1 Introduction -- 2 Research Gaps -- 3 Literature Review -- 4 Data Collection -- 5 Research Methodology -- 6 Analysis and Discussion -- 7 Conclusion -- References -- Mental Health: Prediction and Analysis of Anxiety, Depression, Stress and Happiness Using Machine Learning -- 1 Introduction -- 2 Literature Review -- 3 Methodology -- 3.1 Data Collection -- 3.2 Classification and Results -- 3.3 Analysis and Discussion -- 4 Conclusion and Future Scope -- Appendix** -- References -- Detecting Diabetes Retinopathy Through Machine Learning -- 1 Introduction -- 2 Related Work -- 3 Proposed Work -- 4 Dataset Used -- 5 Proposed Model Workflow Using Dataset. 6 Results and Calculations -- 7 Limitations -- 8 Conclusion -- References -- Extracting Relevant Features for Software Transplantation -- 1 Introduction -- 1.1 Software Features -- 2 Extracting Features -- 3 Methodology -- 4 Result and Analysis -- 4.1 Example Analysis -- 5 Related Work -- 6 Conclusion and Future Work -- References -- Robust Method for Accessing IoT Devices and Blockchain for Secure Data Management -- 1 Overview -- 2 Background Study -- 2.1 Internet of Things (IoT) -- 2.2 Threats to Security and Safety -- 2.3 Communication Protocols -- 2.4 Fundamental Security -- 2.5 IoT Security Concerns -- 2.6 System Ports -- 3 Proposed Model -- 4 Result and Discussion -- 5 Conclusion -- References -- Comparative Analysis of Financial Datasets Predictive Modeling Using Feature Extraction Methods -- 1 Introduction -- 2 Related Work -- 3 Pre-processing -- 4 Proposed Methodology -- 5 Result Analysis and Discussion -- 6 Conclusion -- References -- Cancer Detection Techniques: An Overview of Traditional and AI-Based Methods and Their Comparative Analysis -- 1 Introduction -- 1.1 Cancer Types -- 1.2 Background -- 1.3 Scope of the Paper -- 2 Cancer Detection Overview -- 2.1 Feature Extraction -- 3 Literature Survey -- 3.1 CNN-Based Cancer Detection Techniques -- 4 Results and Analysis of Cancer Detection via Machine Learning -- 5 Conclusion -- 5.1 Contributions of the Paper -- 5.2 Recommendations for Future Research for Cancer Detection -- References -- The Role of Generative Artificial Intelligence (GAI) in Education: A Detailed Review for Enhanced Learning Experiences -- 1 Introduction -- 2 History of Generative Artificial Intelligence -- 3 Role of Generative Artificial Intelligence in Education Field -- 4 Generative Artificial Intelligence Role in Various Fields -- 5 Literature Review -- 6 Conclusion -- 7 Future Scope of GAI in Education Field. References -- Employing Machine Learning Models in Prediction of Harmful Gases from Agri-Waste -- 1 Introduction -- 2 Related Work -- 3 Proposed Methodology -- 4 Results and Discussion -- 5 Conclusion and Future Scope -- References -- Emerging Trends and Perspectives on Challenges and Opportunities in Cloud Computing: A Systematic Literature Review -- 1 Introduction -- 2 Models for Cloud Computing -- 2.1 Infrastructure as a Service -- 2.2 Platform as a Service -- 2.3 Software as a Service -- 3 Related Work -- 4 Cloud Computing Security-Level Open Challenges and Solutions -- 4.1 Data Security Threats -- 5 Conclusion -- References -- TagTrackr: A Smart Asset Tracking Solution -- 1 Introduction -- 2 Related Study -- 3 Proposed Work -- 3.1 Mobile Application -- 3.2 Website -- 4 Result and Analysis -- 4.1 Using NFC Technology Is Better Than Using RFID or Face Detection for Managing Check-in and Out Records for Several Reasons -- 4.2 Real-Time Location Tracking -- 4.3 Detection of Users Going Out of an Area in a Circle -- 4.4 Usability Test -- 5 Future Scope -- 6 Conclusion -- References -- Assessing the Effectiveness of the ELSA App for English Language Learning of Indian Native Speakers -- 1 Introduction -- 2 Literature Review -- 3 Data Analysis -- 4 Results -- 5 Discussions -- 6 Conclusions -- References -- SafeMeds: Electronic Health Records Using Blockchain -- 1 Introduction -- 2 Literature Review -- 3 Methodology -- 4 Results -- 5 Conclusion and Future Scope -- References -- Key Performance Indicators Affecting the Efficiency of Agri Value Chain Ecosystem -- 1 Introduction -- 2 Background of the Study -- 3 Objectives of the Value Chain Ecosystem -- 4 Research Methodology -- 4.1 Survey Techniques -- 4.2 Environmental Performance Indicators -- 4.3 Supply Chain Cycle time -- 4.4 Healthcare Supply Chain -- 4.5 Testing Hypothesis. 4.6 Green Supply Chain Hypothesis -- 4.7 Establish Evaluation Index Set -- 4.8 Establish the weight coefficient matrix -- 4.9 Scores of Qualitative Indicators -- 5 Result and Discussion -- 6 Conclusion -- References -- Implementation of File Tracking Machine to Assess Employee Performance Using Web Services System -- 1 Introduction -- 2 Review of Literature -- 3 Performance Evaluation -- 4 Research Methodology -- 5 Conclusions -- References -- Intelligent Irrigation Systems in Agriculture Using Fuzzy Logic Techniques -- 1 Introduction -- 1.1 Background and Motivation -- 1.2 Problem Statement and Objectives -- 1.3 Overview of Fuzzy Logic and Its Applications in Agriculture -- 2 Related Work -- 2.1 Review of Existing Intelligent Systems of Irrigation -- 2.2 Applications of Fuzzy Logic in Various Agricultural Domains -- 3 Methodology -- 3.1 Data Collection and Sensor Integration -- 3.2 Methodology for Determining Decisions Using Fuzzy Logic -- 3.3 Weather Forecasting Integration -- 3.4 Crop-Specific Requirements Modeling -- 4 Implementing of Intelligent Irrigation System Design -- 4.1 Architecture and Components -- 4.2 Fuzzy Rule Base Development -- 4.3 Membership Functions for Relevant Variables -- 4.4 Fusion of Sensor Data and Weather Forecasts -- 5 Experimental Setup -- 5.1 Description of the Test Site -- 5.2 Data Collection and Preprocessing -- 5.3 Evaluation Metrics -- 6 Results and Discussion -- 6.1 Performance Comparison with Conventional Irrigation Methods -- 6.2 Sensitivity Analysis of Fuzzy Logic Parameters -- 6.3 Case Studies and Real-World Application Scenarios -- 7 Benefits and Limitations -- 7.1 Advantages of Using Fuzzy Logic in Intelligent Irrigation -- 7.2 Potential Challenges and Constraints -- 8 Conclusion -- 8.1 Summary of Contributions -- 8.2 Future Research Directions -- References. Modified Modeling of RoF for Advanced Wireless Network for Long Haul Communication. |
| Record Nr. | UNINA-9910872181803321 |
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Shukla Balvinder
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| Singapore : , : Springer Singapore Pte. Limited, , 2024 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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