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Artificial intelligence for a sustainable industry 4.0 / / Shashank Awasthi [and three others], editors
| Artificial intelligence for a sustainable industry 4.0 / / Shashank Awasthi [and three others], editors |
| Pubbl/distr/stampa | Cham, Switzerland : , : Springer, , [2021] |
| Descrizione fisica | 1 online resource (311 pages) |
| Disciplina | 628 |
| Soggetto topico |
Sustainable engineering - Data processing
Artificial intelligence |
| ISBN | 3-030-77070-2 |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Intro -- Preface -- Acknowledgement -- Contents -- About the Authors -- Possibilities of Industrial Trends and Business Benefits with Industry 4.0 Technology: A Survey -- 1 Introduction -- 2 How the Concept of Supply and Demand Applies to the Overall Economy? -- 3 Technology Road Map for Industry 4.0 -- 3.1 Smart Factory -- 3.2 Cargo Loading and Unloading -- 3.2.1 Formal integration platform -- 3.2.2 Technological Challenges and Accompanying Ranging of Data -- 3.2.3 Vertical Incorporation of Intelligent Development -- 3.3 A New Wave of Corporate Supply Chains -- 3.4 All the Way Through the Supply Chain -- 4 Aspects for IT Management to Consider -- 5 Concepts of Creativity -- 6 The Effective Administration of Creativity -- 7 Encompasses Every Facet of Our Lives from Social Media to E-Commerce -- 7.1 Collecting Data -- 7.2 Looking out Opportunities -- 7.3 Consistency -- 8 Conclusion -- References -- Impact of Internet of Things on Logistics Management: A Framework for Logistics Information System -- 1 Introduction -- 2 IoT Emergence and the Internet -- 3 Interaction of IoT and Human -- 4 Information Sharing in Logistics and Supply Chain -- 5 IoT for Logistics Information System -- 6 Benefits of IoT for Logistics -- 7 Innovation of Logistics in IoT Context -- 8 IoT Framework for Logistics Information System -- 9 IoT for Logistics Information System in Future -- 10 Conclusion -- References -- Green Internet of Things (G-IoT): An Exposition for Sustainable Technological Development -- 1 Overview -- 2 Internet of Things -- 2.1 The Technology Stack of IoT -- 2.2 IoT Stack: Connectivity Options -- 2.3 Empowering Technology for IoT -- 2.4 IoT Features -- 2.5 Architecture of IoT -- 2.6 Ecosystem of IoT -- 3 Green IoT -- 3.1 Key Technologies of Green IoT -- 3.2 Application of Green IoT -- 4 IoT Big 7: IoT-Challenges and Problems -- 4.1 IoT Scalability.
4.2 Interoperability of IoT -- 4.3 IoT Reliability -- 4.4 IoT Efficiency -- 4.5 IoT Availability -- 4.6 IoT Software -- 4.7 IoT Security -- 5 Incorporating IoT and Cloud Computing for Addressing Intrinsic Challenges of IoT -- 5.1 Scalability Via Cloud Computing -- 5.2 Interoperability Through Cloud Computing -- 5.3 Functionality Via Cloud Infrastructure -- 5.4 Efficiency Through Cloud Computing -- 5.5 Availability -- 6 Summary and Conclusions -- References -- Quantitative Analysis of Industrial IoT System -- 1 Introduction -- 2 A Calculus for Probabilistic Wireless Network (PBL) -- 3 A Stochastic Routing Calculus -- 4 Syntax -- 5 Structural Equivalence -- 6 Reduction Semantics -- 7 Well-Formed Configurations -- 8 Equivalence of GR with Its Specification -- 9 Conclusion -- References -- Formal Verification of Industrial IoT System: A Behavioural Equivalence -- 1 Introduction -- 2 A Stochastic Routing Calculus -- 3 GR: A Behavioural Equivalence -- 4 Probabilistic Reduction Barbed Pre-congruence -- 5 A Labeled Transition System -- 6 Probabilistic Efficiency Pre-Bisimulation -- 7 An Observational Lts -- 8 Justifying Asynchronous Probabilistic Efficiency Pre-bisimulation Contextually -- 9 Conclusions -- References -- Steganography: Camouflaging Sensitive and Vulnerable Data -- 1 Introduction -- 1.1 Beginning of the Era of Steganography: The Prisoners Problem -- 1.2 A Generalized Framework of Steganography -- 1.3 Categorization in Steganography -- 1.4 Criteria for a Good Steganographic Approach -- 2 Case Studies in Literature -- 2.1 Spatial Domain Techniques -- 2.2 Transform Domain Techniques -- 3 Conclusion -- References -- Technologies for the Rehabilitation of People Affected with CVM: A State-of-the-Art Report -- 1 Introduction -- 2 Rehabilitation for People Affected by CVM -- 3 Available Technological Resources -- 3.1 Rehabilitative Technologies. 3.2 Assistive Technologies -- 4 Conclusions -- References -- Machine Learning Application: Sarcasm Detection Model -- 1 Introduction -- 2 Research Methodology -- 2.1 Parsing Dataset into DataFrames -- 2.2 Checking Null Values -- 2.3 Data Cleaning -- 2.4 Feature and Label Extraction -- 2.5 Stemming -- 2.6 TF-IDF Vectorization -- 2.7 Training and Testing of Data -- 2.8 Training and Testing of the Model -- 2.9 Setting up GUI Application Using Tkinter -- 3 Results and Discussion -- 4 Conclusion -- References -- Modern Technology on Building Marketing 4.0: Impact on Customer Engagement -- 1 Introduction -- 1.1 About Digital and Social Media Emergence -- 1.2 Emergence of Marketing 4.0 -- 2 About the Topic -- 3 The Conceptual Model: Design, Direct, Develop, Interventions, Innovation, and Capabilities (D3I2C) -- 4 Objectives -- 5 Literature Review -- 6 Research Methodology -- 7 Findings -- 7.1 Introduction to Questionnaire -- 7.2 Millennials' Attitude Toward Social Media -- 7.3 Awareness Toward Digital Marketing -- 7.4 Technology on Building Marketing 4.0 -- 8 Interpretation -- 9 Conclusion -- References -- Smart and Intelligent Chatbot Assistance for Future Industry 4.0 -- 1 Introduction -- 2 Related Work -- 2.1 Product Perspective -- 2.1.1 System Interfaces -- 2.1.2 Interfaces -- 2.1.3 Communication Interfaces -- 2.1.4 Site Adaptation Requirements -- 2.2 Product Functions -- 2.3 Assumptions and Dependencies -- 3 Architectural Design -- 3.1 Class Diagrams -- 3.2 Pizza Ordering Agent (Class Diagram) -- 3.3 Hotel Booking Agent (Class Diagram) -- 3.4 Data Flow Diagram -- 4 Implementation and Results -- 4.1 Results -- 5 Conclusion -- References -- Analyzing Subspace Clustering Approaches for High Dimensional Data -- 1 Introduction -- 2 Challenges in Subspace Clustering -- 3 Classification of Subspace Clustering Approaches. 4 Evaluation Measures for Subspace Clustering Algorithms -- 5 Literature -- 6 Empirical Assessment -- 7 Applications and Future Prospects -- 8 Conclusion -- References -- Ant Colony Optimization Technique in Soft Computational Data Research for NP-Hard Problems -- 1 Introduction -- 2 Soft Computing -- 3 Applications of Soft Computing -- 4 Ant Colony Optimization Technique (ACO) -- 4.1 Mathematical Model of ACO -- 5 Variations in ACO -- 6 Some Common Computational Problems Solved Using ACO -- 6.1 Travelling Salesman Problem -- 6.2 Job-Shop Scheduling Problem (JSP) -- 6.3 Quadratic Assignment Problem -- 7 Conclusion -- References -- Use of Kalman Filter and Its Variants in State Estimation: A Review -- 1 Introduction -- 2 Background -- 3 Mathematical Foundation of Kalman Filter -- 3.1 Extended Kalman Filter -- 3.2 Unscented Kalman Filter -- 3.3 Ensemble Kalman Filter -- 3.4 Particle Kalman Filter -- 3.5 Cubature Kalman Filter -- 3.6 Further Types of Kalman Filter -- 4 Discussion -- 5 Conclusion -- References -- Precoder and Combiner Optimization in mmWave Hybrid Beamforming Systems -- 1 Introduction -- 1.1 Multi-user MIMO Downlink System Model -- 1.2 mmWave MIMO Channel Model -- 1.3 Problem Formulation -- 2 Extended Orthogonal Matching Pursuit Method -- 3 Results and Discussions -- 4 Conclusion -- References -- Biometric Identification System: Security and Privacy Concern -- 1 Introduction -- 2 Biometric Modalities -- 2.1 Fingerprint Scan -- 2.2 Human Face -- 2.3 Hand Measurement -- 2.4 Palm Scan -- 2.5 IRIS Scan -- 2.6 Voice -- 3 Use of Software for Biometric Security -- 4 Various Issues in Biometric System -- 4.1 The Algorithm (Encryption) Used in Biometrics Is Weak -- 4.2 Size of Biometric Database Increases with Time -- 4.3 Size of Storage and Key Size -- 4.4 Cyber/Criminal Attacks -- 4.5 Factors Related with Environment -- 4.6 Foreign Particles. 4.7 Attack on Comparator -- 4.8 Template Got Attack by Virus -- 4.9 Medium of Communication -- 4.10 Decision May Be Altered -- 5 Methods of Dealing with Issues in Biometric System -- 5.1 Multimodal Biometrics -- 5.2 Touchless Fingerprint -- 5.3 Using Special Algorithm Having Enhanced Security Specification -- 5.4 Using Second Storage -- 5.5 Security of Database -- 5.6 Biometrics with a Password/OTP/Card Access/Pin -- 6 How Addition of Biometrics Enhance the Security -- 6.1 Fast and Reliable Verification System -- 6.2 Accountability of the Individual -- 6.3 High Efficiency -- 6.4 Convenient -- 6.5 Adoptability of Future Growth of the Organization -- 7 Middleware and Software's Used in Biometrics -- 7.1 FSI -- 7.2 Healthcare -- 7.3 Manufacturing Industry -- 7.4 Service Industry -- 7.5 Government Authorities -- 8 Future Biometric Technologies -- 8.1 On-Spot DNA Test -- 8.2 Brain Wave Scanning -- 9 Advantages of Biometric -- 9.1 Safety and Security -- 9.2 Accuracy -- 9.3 ROI -- 9.4 Scalability -- 9.5 Screening -- 10 Disadvantages of Biometric -- 10.1 Recognition of Physical Traits -- 10.2 Rate of Error -- 10.3 Cost -- 10.4 Delay -- 10.5 Complexity -- 11 Conclusion -- References -- Enabling Technologies: A Transforming Action on Healthcare with IoT a Possible Revolutionizing -- 1 Introduction -- 1.1 The IoT Is Growing Everywhere -- 1.2 Smart Home Dares to Make Sense -- 1.3 Improving IoT in Healthcare -- 1.4 Why Would the Industry Benefit from Using IoT? -- 1.5 Applied Internet of Things in Healthcare -- 2 The Advantages of IoT in Healthcare -- 2.1 Cancer Therapy -- 2.2 Diabetes Management -- 3 Challenges for IoT in Healthcare -- 4 Conclusion -- References -- Automated and Curated Sack Count Leveraging Video Analysis on Moving Objects -- 1 Introduction -- 2 Problem Statement -- 2.1 Related Work -- 3 Proposed Approach -- 3.1 Model Development. 3.1.1 Step 1: Problem Definition. |
| Record Nr. | UNINA-9910506384903321 |
| Cham, Switzerland : , : Springer, , [2021] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Artificial intelligence for a sustainable industry 4.0 / / Shashank Awasthi [and three others], editors
| Artificial intelligence for a sustainable industry 4.0 / / Shashank Awasthi [and three others], editors |
| Pubbl/distr/stampa | Cham, Switzerland : , : Springer, , [2021] |
| Descrizione fisica | 1 online resource (311 pages) |
| Disciplina | 628 |
| Soggetto topico |
Sustainable engineering - Data processing
Artificial intelligence |
| ISBN | 3-030-77070-2 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Intro -- Preface -- Acknowledgement -- Contents -- About the Authors -- Possibilities of Industrial Trends and Business Benefits with Industry 4.0 Technology: A Survey -- 1 Introduction -- 2 How the Concept of Supply and Demand Applies to the Overall Economy? -- 3 Technology Road Map for Industry 4.0 -- 3.1 Smart Factory -- 3.2 Cargo Loading and Unloading -- 3.2.1 Formal integration platform -- 3.2.2 Technological Challenges and Accompanying Ranging of Data -- 3.2.3 Vertical Incorporation of Intelligent Development -- 3.3 A New Wave of Corporate Supply Chains -- 3.4 All the Way Through the Supply Chain -- 4 Aspects for IT Management to Consider -- 5 Concepts of Creativity -- 6 The Effective Administration of Creativity -- 7 Encompasses Every Facet of Our Lives from Social Media to E-Commerce -- 7.1 Collecting Data -- 7.2 Looking out Opportunities -- 7.3 Consistency -- 8 Conclusion -- References -- Impact of Internet of Things on Logistics Management: A Framework for Logistics Information System -- 1 Introduction -- 2 IoT Emergence and the Internet -- 3 Interaction of IoT and Human -- 4 Information Sharing in Logistics and Supply Chain -- 5 IoT for Logistics Information System -- 6 Benefits of IoT for Logistics -- 7 Innovation of Logistics in IoT Context -- 8 IoT Framework for Logistics Information System -- 9 IoT for Logistics Information System in Future -- 10 Conclusion -- References -- Green Internet of Things (G-IoT): An Exposition for Sustainable Technological Development -- 1 Overview -- 2 Internet of Things -- 2.1 The Technology Stack of IoT -- 2.2 IoT Stack: Connectivity Options -- 2.3 Empowering Technology for IoT -- 2.4 IoT Features -- 2.5 Architecture of IoT -- 2.6 Ecosystem of IoT -- 3 Green IoT -- 3.1 Key Technologies of Green IoT -- 3.2 Application of Green IoT -- 4 IoT Big 7: IoT-Challenges and Problems -- 4.1 IoT Scalability.
4.2 Interoperability of IoT -- 4.3 IoT Reliability -- 4.4 IoT Efficiency -- 4.5 IoT Availability -- 4.6 IoT Software -- 4.7 IoT Security -- 5 Incorporating IoT and Cloud Computing for Addressing Intrinsic Challenges of IoT -- 5.1 Scalability Via Cloud Computing -- 5.2 Interoperability Through Cloud Computing -- 5.3 Functionality Via Cloud Infrastructure -- 5.4 Efficiency Through Cloud Computing -- 5.5 Availability -- 6 Summary and Conclusions -- References -- Quantitative Analysis of Industrial IoT System -- 1 Introduction -- 2 A Calculus for Probabilistic Wireless Network (PBL) -- 3 A Stochastic Routing Calculus -- 4 Syntax -- 5 Structural Equivalence -- 6 Reduction Semantics -- 7 Well-Formed Configurations -- 8 Equivalence of GR with Its Specification -- 9 Conclusion -- References -- Formal Verification of Industrial IoT System: A Behavioural Equivalence -- 1 Introduction -- 2 A Stochastic Routing Calculus -- 3 GR: A Behavioural Equivalence -- 4 Probabilistic Reduction Barbed Pre-congruence -- 5 A Labeled Transition System -- 6 Probabilistic Efficiency Pre-Bisimulation -- 7 An Observational Lts -- 8 Justifying Asynchronous Probabilistic Efficiency Pre-bisimulation Contextually -- 9 Conclusions -- References -- Steganography: Camouflaging Sensitive and Vulnerable Data -- 1 Introduction -- 1.1 Beginning of the Era of Steganography: The Prisoners Problem -- 1.2 A Generalized Framework of Steganography -- 1.3 Categorization in Steganography -- 1.4 Criteria for a Good Steganographic Approach -- 2 Case Studies in Literature -- 2.1 Spatial Domain Techniques -- 2.2 Transform Domain Techniques -- 3 Conclusion -- References -- Technologies for the Rehabilitation of People Affected with CVM: A State-of-the-Art Report -- 1 Introduction -- 2 Rehabilitation for People Affected by CVM -- 3 Available Technological Resources -- 3.1 Rehabilitative Technologies. 3.2 Assistive Technologies -- 4 Conclusions -- References -- Machine Learning Application: Sarcasm Detection Model -- 1 Introduction -- 2 Research Methodology -- 2.1 Parsing Dataset into DataFrames -- 2.2 Checking Null Values -- 2.3 Data Cleaning -- 2.4 Feature and Label Extraction -- 2.5 Stemming -- 2.6 TF-IDF Vectorization -- 2.7 Training and Testing of Data -- 2.8 Training and Testing of the Model -- 2.9 Setting up GUI Application Using Tkinter -- 3 Results and Discussion -- 4 Conclusion -- References -- Modern Technology on Building Marketing 4.0: Impact on Customer Engagement -- 1 Introduction -- 1.1 About Digital and Social Media Emergence -- 1.2 Emergence of Marketing 4.0 -- 2 About the Topic -- 3 The Conceptual Model: Design, Direct, Develop, Interventions, Innovation, and Capabilities (D3I2C) -- 4 Objectives -- 5 Literature Review -- 6 Research Methodology -- 7 Findings -- 7.1 Introduction to Questionnaire -- 7.2 Millennials' Attitude Toward Social Media -- 7.3 Awareness Toward Digital Marketing -- 7.4 Technology on Building Marketing 4.0 -- 8 Interpretation -- 9 Conclusion -- References -- Smart and Intelligent Chatbot Assistance for Future Industry 4.0 -- 1 Introduction -- 2 Related Work -- 2.1 Product Perspective -- 2.1.1 System Interfaces -- 2.1.2 Interfaces -- 2.1.3 Communication Interfaces -- 2.1.4 Site Adaptation Requirements -- 2.2 Product Functions -- 2.3 Assumptions and Dependencies -- 3 Architectural Design -- 3.1 Class Diagrams -- 3.2 Pizza Ordering Agent (Class Diagram) -- 3.3 Hotel Booking Agent (Class Diagram) -- 3.4 Data Flow Diagram -- 4 Implementation and Results -- 4.1 Results -- 5 Conclusion -- References -- Analyzing Subspace Clustering Approaches for High Dimensional Data -- 1 Introduction -- 2 Challenges in Subspace Clustering -- 3 Classification of Subspace Clustering Approaches. 4 Evaluation Measures for Subspace Clustering Algorithms -- 5 Literature -- 6 Empirical Assessment -- 7 Applications and Future Prospects -- 8 Conclusion -- References -- Ant Colony Optimization Technique in Soft Computational Data Research for NP-Hard Problems -- 1 Introduction -- 2 Soft Computing -- 3 Applications of Soft Computing -- 4 Ant Colony Optimization Technique (ACO) -- 4.1 Mathematical Model of ACO -- 5 Variations in ACO -- 6 Some Common Computational Problems Solved Using ACO -- 6.1 Travelling Salesman Problem -- 6.2 Job-Shop Scheduling Problem (JSP) -- 6.3 Quadratic Assignment Problem -- 7 Conclusion -- References -- Use of Kalman Filter and Its Variants in State Estimation: A Review -- 1 Introduction -- 2 Background -- 3 Mathematical Foundation of Kalman Filter -- 3.1 Extended Kalman Filter -- 3.2 Unscented Kalman Filter -- 3.3 Ensemble Kalman Filter -- 3.4 Particle Kalman Filter -- 3.5 Cubature Kalman Filter -- 3.6 Further Types of Kalman Filter -- 4 Discussion -- 5 Conclusion -- References -- Precoder and Combiner Optimization in mmWave Hybrid Beamforming Systems -- 1 Introduction -- 1.1 Multi-user MIMO Downlink System Model -- 1.2 mmWave MIMO Channel Model -- 1.3 Problem Formulation -- 2 Extended Orthogonal Matching Pursuit Method -- 3 Results and Discussions -- 4 Conclusion -- References -- Biometric Identification System: Security and Privacy Concern -- 1 Introduction -- 2 Biometric Modalities -- 2.1 Fingerprint Scan -- 2.2 Human Face -- 2.3 Hand Measurement -- 2.4 Palm Scan -- 2.5 IRIS Scan -- 2.6 Voice -- 3 Use of Software for Biometric Security -- 4 Various Issues in Biometric System -- 4.1 The Algorithm (Encryption) Used in Biometrics Is Weak -- 4.2 Size of Biometric Database Increases with Time -- 4.3 Size of Storage and Key Size -- 4.4 Cyber/Criminal Attacks -- 4.5 Factors Related with Environment -- 4.6 Foreign Particles. 4.7 Attack on Comparator -- 4.8 Template Got Attack by Virus -- 4.9 Medium of Communication -- 4.10 Decision May Be Altered -- 5 Methods of Dealing with Issues in Biometric System -- 5.1 Multimodal Biometrics -- 5.2 Touchless Fingerprint -- 5.3 Using Special Algorithm Having Enhanced Security Specification -- 5.4 Using Second Storage -- 5.5 Security of Database -- 5.6 Biometrics with a Password/OTP/Card Access/Pin -- 6 How Addition of Biometrics Enhance the Security -- 6.1 Fast and Reliable Verification System -- 6.2 Accountability of the Individual -- 6.3 High Efficiency -- 6.4 Convenient -- 6.5 Adoptability of Future Growth of the Organization -- 7 Middleware and Software's Used in Biometrics -- 7.1 FSI -- 7.2 Healthcare -- 7.3 Manufacturing Industry -- 7.4 Service Industry -- 7.5 Government Authorities -- 8 Future Biometric Technologies -- 8.1 On-Spot DNA Test -- 8.2 Brain Wave Scanning -- 9 Advantages of Biometric -- 9.1 Safety and Security -- 9.2 Accuracy -- 9.3 ROI -- 9.4 Scalability -- 9.5 Screening -- 10 Disadvantages of Biometric -- 10.1 Recognition of Physical Traits -- 10.2 Rate of Error -- 10.3 Cost -- 10.4 Delay -- 10.5 Complexity -- 11 Conclusion -- References -- Enabling Technologies: A Transforming Action on Healthcare with IoT a Possible Revolutionizing -- 1 Introduction -- 1.1 The IoT Is Growing Everywhere -- 1.2 Smart Home Dares to Make Sense -- 1.3 Improving IoT in Healthcare -- 1.4 Why Would the Industry Benefit from Using IoT? -- 1.5 Applied Internet of Things in Healthcare -- 2 The Advantages of IoT in Healthcare -- 2.1 Cancer Therapy -- 2.2 Diabetes Management -- 3 Challenges for IoT in Healthcare -- 4 Conclusion -- References -- Automated and Curated Sack Count Leveraging Video Analysis on Moving Objects -- 1 Introduction -- 2 Problem Statement -- 2.1 Related Work -- 3 Proposed Approach -- 3.1 Model Development. 3.1.1 Step 1: Problem Definition. |
| Record Nr. | UNISA-996464424503316 |
| Cham, Switzerland : , : Springer, , [2021] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
| ||
Emerging Threats and Countermeasures in Cybersecurity
| Emerging Threats and Countermeasures in Cybersecurity |
| Autore | Shrivastava Gulshan |
| Edizione | [1st ed.] |
| Pubbl/distr/stampa | Newark : , : John Wiley & Sons, Incorporated, , 2024 |
| Descrizione fisica | 1 online resource (533 pages) |
| Disciplina | 005.8 |
| Altri autori (Persone) |
OjhaRudra Pratap
AwasthiShashank SharmaKavita BansalHimani |
| Collana | Advances in Antenna, Microwave, and Communication Engineering Series |
| Soggetto topico | Computer security |
| ISBN |
9781394230587
1394230583 9781394230600 1394230605 9781394230594 1394230591 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Cover -- Series Page -- Title Page -- Copyright Page -- Contents -- Preface -- Chapter 1 Emerging Threats and Trends in Digital Forensics and Cybersecurity -- 1.1 Introduction -- 1.2 Threats Faced by Digital Forensics -- 1.2.1 Technical Challenges -- 1.2.2 Operational Challenges -- 1.2.3 Personnel-Related Challenges -- 1.3 Cybersecurity Threats in 2023 -- 1.3.1 Social Engineering -- 1.3.2 Third-Party Exposure -- 1.3.3 Configuration Mistakes -- 1.3.4 Poor Cyber Hygiene -- 1.3.5 Cloud Vulnerabilities -- 1.3.6 Mobile Device Vulnerabilities -- 1.3.7 Internet of Things (IoT) -- 1.3.8 Ransomware -- 1.3.9 Poor Data Management -- 1.3.10 Inadequate Post-Attack Procedures -- 1.4 New Era of Technology and Their Risks -- 1.4.1 Autonomous Vehicles -- 1.4.2 Artificial Intelligence -- 1.4.3 Robotics and Robotics Process Automation -- 1.4.4 Internet of Things (IoT) -- 1.4.5 5G -- 1.5 Challenges for Digital Forensics -- 1.5.1 High Speed and Volumes -- 1.5.2 Explosion Complexity -- 1.5.3 Development of Standards -- 1.5.4 Privacy-Preserving Investigations -- 1.5.5 Legitimacy -- 1.5.6 Rise of Anti-Forensic Techniques -- 1.6 Impact of Mobile Gadgets on Cybersecurity -- 1.7 The Vulnerabilities in Wireless Mobile Data Exchange -- 1.7.1 Interception of Data -- 1.7.2 Malware Attacks -- 1.7.3 Rogue Access Points -- 1.7.4 Denial of Service Attacks -- 1.7.5 Weak Encryption -- 1.8 Network Segmentation and its Applications -- 1.8.1 Applications -- 1.8.2 Benefits of Network Segmentation -- 1.9 Relationship Between Privacy and Security -- 1.9.1 Security -- 1.9.2 Privacy -- 1.10 Recent Trends in Digital Forensics -- 1.10.1 Cloud Forensics -- 1.10.2 Social Media Forensics -- 1.10.3 IoT Forensics -- 1.11 Opportunities in this Field -- 1.11.1 USB Forensics -- 1.11.2 Intrusion Detection -- 1.11.3 Artificial Intelligence (AI) -- 1.12 Future Enhancements in Digital Forensics.
1.13 Cybersecurity and Cyber Forensics in Smart Cities -- 1.13.1 Smart Cities are Entitled to Cyber-Physical Systems -- 1.13.1.1 Administrative -- 1.13.1.2 Complex CPS in a Glimpse -- 1.13.1.3 IoT Technologies in Smart Cities of the Future -- 1.14 Network Security and Forensics -- 1.15 Software and Social Engineering Attacks on RSA -- 1.16 Cyber Threats and Cybersecurity -- 1.17 Conclusion -- Bibliography -- Chapter 2 Toward Reliable Image Forensics: Deep Learning-Based Forgery Detection -- 2.1 Introduction -- 2.2 Fundamentals of Image Forensics -- 2.2.1 History -- 2.2.2 Image Forgery Types -- 2.2.3 Classical Image Forensics Techniques -- 2.3 Deep Learning in Image Forensics -- 2.3.1 Convolutional Neural Networks (CNNs) -- 2.3.2 Generative Adversarial Networks (GANs) -- 2.4 Datasets of Image Forgery Detection -- 2.5 Feature Extraction and Representation -- 2.6 Model Training and Evaluation -- 2.6.1 Model Training -- 2.6.2 Loss Functions -- 2.6.3 Evaluation Metrics -- 2.7 Challenges and Future Scope -- 2.8 Conclusion -- References -- Chapter 3 Understanding and Mitigating Advanced Persistent Threats in a Dynamic Cyber Landscape -- 3.1 Introduction -- 3.1.1 Advanced -- 3.1.2 Persistent -- 3.1.3 Threat -- 3.1.3.1 Vulnerability -- 3.1.3.2 Risk -- 3.2 APT Lifecycle -- 3.3 Characteristics and Methods of APTs -- 3.4 APT Detection -- 3.5 Mitigation Techniques -- 3.5.1 Application Control/Dynamic Whitelisting -- 3.5.2 Vulnerability Assessment -- 3.5.3 Patch Management -- 3.5.4 Automated Exploit Prevention -- 3.6 Case Study: CozyDuke APT -- Conclusion -- References -- Chapter 4 Class-Imbalanced Problems in Malware Analysis and Detection in Classification Algorithms -- 4.1 Introduction -- 4.2 Background -- 4.2.1 Malware Analysis and Types -- 4.2.2 Class-Imbalanced Problem -- 4.2.3 Imbalanced Techniques -- 4.3 Related Work. 4.4 Detailed Overview of the Methodology -- 4.4.1 Dataset Information -- 4.4.2 Different Evaluation Metrics Used for Class-Imbalanced Study -- 4.4.3 Machine Learning Classifiers -- 4.4.4 Exiting Methods Used for Handling the Class Imbalanced -- 4.5 Discussion and Challenges -- 4.5.1 Research Question -- 4.5.2 Challenges -- 4.6 Conclusion -- References -- Chapter 5 Malware Analysis and Detection: New Approaches and Techniques -- 5.1 Introduction -- 5.2 Malware -- 5.2.1 History of Malware -- 5.2.2 Different Forms of Malware -- 5.2.3 Purpose of Malware Analysis -- 5.3 Case Studies -- 5.4 Future Aspects -- 5.5 Conclusion -- References -- Chapter 6 State-of-the-Art in Ransomware Analysis and Detection -- 6.1 Introduction -- Evolution -- Lifecycle -- Infection Method -- Targets of Ransomware Attacks -- Payment Process and Method -- Ransomware Analysis -- Ransomware Detection -- Ransomware Prevention -- Recovery -- Characteristics -- Difficulties -- Impact of Ransomware Attacks -- Statistics -- Conclusion -- References -- Chapter 7 Cyber-Physical System Security: Challenges and Countermeasures -- 7.1 Introduction -- 7.1.1 Definition and Characteristics of CPS -- 7.1.2 Importance and Applications of CPS -- 7.1.3 Overview of CPS Security Concerns -- 7.2 Challenges in CPS Security -- 7.2.1 Threat Landscape in CPS -- 7.2.2 Vulnerabilities in CPS -- 7.2.2.1 Interconnected System Vulnerabilities -- 7.2.2.2 Lack of Standardized Security Frameworks -- 7.2.2.3 Legacy System Compatibility Issues -- 7.2.2.4 Human Factors and Social Engineering -- 7.3 Security Risks and Consequences -- 7.3.1 Financial Losses and Economic Impact -- 7.3.2 Public Safety and Critical Infrastructure Risks -- 7.3.3 Privacy and Data Breaches -- 7.4 Key Considerations for CPS Security -- 7.4.1 Secure Design and Architecture Principles -- 7.4.1.1 Defense-in-Depth Strategy. 7.4.1.2 Secure Communication Protocols -- 7.4.1.3 Access Control and Authentication Mechanisms -- 7.4.2 Threat Modeling and Risk Assessment -- 7.4.3 Intrusion Detection and Prevention Systems (IDPS) -- 7.4.4 Secure Software Development Practices -- 7.4.4.1 Secure Coding Guidelines -- 7.4.4.2 Code Reviews and Vulnerability Testing -- 7.5 Countermeasures for CPS Security -- 7.5.1 Network Security Measures -- 7.5.1.1 Firewalls and Network Segmentation -- 7.5.1.2 IDPS -- 7.5.2 Physical Security Controls -- 7.5.2.1 Access Controls and Physical Barriers -- 7.5.2.2 Surveillance and Monitoring Systems -- 7.5.3 Incident Response and Recovery Plans -- 7.5.3.1 Incident Handling Procedures -- 7.5.3.2 Backup and Disaster Recovery Strategies -- 7.5.4 Security Awareness and Training Programs -- 7.6 Case Studies and Examples -- 7.6.1 Case Study 1: Industrial Control System (ICS) Security -- 7.6.1.1 Countermeasures -- 7.6.2 Case Study 2: Smart Cities and Infrastructure Protection -- 7.6.2.1 Countermeasures -- 7.6.3 Case Study 3: Autonomous Vehicles and Transportation Systems -- 7.6.3.1 Countermeasures -- 7.7 Future Directions and Emerging Technologies -- 7.7.1 Impact of Emerging Technologies on CPS Security -- 7.7.2 Challenges and Opportunities in Securing CPS in the Future -- 7.8 Conclusion -- References -- Chapter 8 Unraveling the Ethical Conundrum: Privacy Challenges in the Realm of Digital Forensics -- 8.1 Introduction -- 8.2 Fundamental Concepts in Digital Forensics -- 8.3 Privacy Concerns in AI Technology: Security Systems and Cyber Forensics -- 8.4 Maintaining Integrity of Evidence in Forensic Investigations -- 8.5 Ethical Obligations of Forensic Investigators -- 8.6 Conclusion -- References -- Chapter 9 IoT and Smart Device Security: Emerging Threats and Countermeasures -- 9.1 Introduction -- 9.2 The Growth of IoT and Smart Devices. 9.3 Emerging Threat Landscape -- 9.4 Device Vulnerabilities and Exploits -- 9.5 Data Privacy and Leakage -- 9.5.1 Data Privacy Concerns in IoT -- 9.5.2 Data Leakage Concerns in IoT -- 9.6 Network Attacks and Amplification -- 9.6.1 Network Attacks in IoT -- 9.6.2 Amplification Attacks in IoT -- 9.6.3 Preventive Measures and Mitigation -- 9.7 Physical Attacks on Smart Devices -- 9.8 Supply Chain Risks in IoT Ecosystem -- 9.9 Lack of Standardization in IoT Security -- 9.10 Countermeasures and Best Practices -- 9.11 Conclusion and Future Directions -- 9.11.1 Future Directions and Countermeasures -- References -- Chapter 10 Advanced Security for IoT and Smart Devices: Addressing Modern Threats and Solutions -- 10.1 Introduction -- 10.1.1 Overview of IoT and Smart Devices -- 10.1.2 Importance of Security in IoT and Smart Devices -- 10.1.3 Scope of the Chapter -- 10.2 IoT and Smart Device Landscape -- 10.2.1 Growth and Adoption of IoT and Smart Devices -- 10.2.2 Types and Examples of IoT and Smart Devices -- 10.2.3 Challenges in Securing IoT and Smart Devices -- 10.3 Emerging Threats in IoT and Smart Device Security -- 10.3.1 Malware and Ransomware Attacks -- 10.3.2 Device Exploitation and Hijacking -- 10.3.3 Data Breaches and Privacy Concerns -- 10.3.4 Distributed Denial of Service (DDoS) Attacks -- 10.3.5 Supply Chain Attacks -- 10.3.6 Insider Threats -- 10.3.7 Physical Security Risks -- 10.4 Vulnerabilities in IoT and Smart Devices -- 10.4.1 Insecure Communication Protocols -- 10.4.2 Weak Authentication and Authorization -- 10.4.3 Lack of Security Updates and Patch Management -- 10.4.4 Default or Hardcoded Credentials -- 10.4.5 Lack of Device Integrity Verification -- 10.4.6 Insufficient Encryption -- 10.4.7 Inadequate Access Controls -- 10.5 Countermeasures and Best Practices -- 10.5.1 Secure Device Design and Development. 10.5.2 Robust Authentication and Access Controls. |
| Record Nr. | UNINA-9911019501303321 |
Shrivastava Gulshan
|
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| Newark : , : John Wiley & Sons, Incorporated, , 2024 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Sustainable Computing : Transforming Industry 4. 0 to Society 5. 0 / / Shashank Awasthi [and five others], editors
| Sustainable Computing : Transforming Industry 4. 0 to Society 5. 0 / / Shashank Awasthi [and five others], editors |
| Pubbl/distr/stampa | Cham, Switzerland : , : Springer, , [2023] |
| Descrizione fisica | 1 online resource (352 pages) |
| Disciplina | 658.4038028563 |
| Soggetto topico |
Computers - Environmental aspects
Industry 4.0 Society 5.0 |
| ISBN | 3-031-13577-6 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Intro -- Preface -- Acknowledgement -- Contents -- About the Editors -- A Review on Renewable Energy Sources, Potential and Policy in India -- Abbreviations -- 1 Introduction -- 2 Available Conventional Energy in India: Overview -- 2.1 Generation From Traditional Sources in India -- 2.1.1 Coal/Lignite -- 2.1.2 Hydro -- 2.1.3 Nuclear -- 2.1.4 Gas -- 3 Energy Scenario During 12th Five-Year Plan (2012-2017) [1] -- 4 Added Capacity Attained for the Duration of 12th Plan (Not Involved in the Targeted Capacity of 88,537 MW) [1, 3] -- 4.1 A Cooperative Analysis of 12th Plan with Earlier Five-Year Plans -- 4.2 Slipped Projects and Causes of Slippage from 12th Plan Capacity Addition Target [1] -- 5 Peak Demand and Energy Requisite Prediction -- 6 Renewable Energy Sources: Potential in India -- 6.1 Solar Energy -- 6.2 Wind Energy -- 6.3 Biomass Energy -- 6.4 Small Hydro Power (SHP) -- 6.5 Ocean Surface Waves and Tidal Power -- 6.6 Installed RES Potential in India -- 7 Capacity Addition from RES in 12th Plan -- 8 RES Policy of India -- 9 Recent Renewable Energy Initiatives -- 9.1 Solar Parks -- 9.2 Solar Cities -- 9.3 Solar Pump -- 10 Other Programs/Policies/Schemes -- 11 Future Potential of Renewable Energy in India -- 11.1 Renewable Energy Target by 2022 -- 12 Projection of Renewable Energy Generation -- 12.1 Perspective Plan 2022 -- 12.2 Perspective Plan for Grid-Interactive Renewable Power -- 12.3 Perspective Plan for Renewable Power for Urban, Industrial, and Commercial Applications -- 12.4 Medium Term (2032) Deployment Goals -- 13 Conclusion -- 14 Future Work -- References -- Analysis of Brain Signals to Forecast Motor Intentions Using Artificial Intelligence -- 1 Introduction -- 1.1 State of the Art -- 1.2 Our Proposal -- 2 Material and Methods -- 2.1 Database -- 2.2 Pre-processing -- 2.3 Feature Extraction -- 2.4 Classifiers -- 2.4.1 Decision Trees.
2.4.2 Linear Discriminant Analysis -- 2.4.3 Logistic Analysis -- 2.4.4 Support Vector Machine -- 2.4.5 K-Nearest Neighbors -- 2.4.6 Ensemble Methods -- 2.4.7 Neural Networks -- 3 Methodology -- 3.1 Feature Extraction Algorithm -- 4 Results and Discussion -- 4.1 Results -- 4.2 Discussion -- 5 Conclusions -- References -- Automated Detection of Covid-19 Waves with Computerized Tomography Scan Using Deep Learning -- 1 Introduction -- 2 Related Studies -- 2.1 Molecular RT-PCR Test -- 2.2 RAT Tests -- 2.3 Serological Tests -- 3 ML Algorithm Focused on Diagnosis Using CT Scan Images -- 3.1 Multiple Instance Learning (MIL) -- 3.2 Why Deep Learning over Machine Learning -- 4 DL Algorithm Focused on Diagnosis Using CT Scan Images -- 4.1 Deep Neural Network (DNN) -- 4.2 Convolutional Neural Network -- 4.3 Deep Convolutional Neural Network (DCNN) -- 4.4 Transfer Learning Techniques in Deep Learning -- 5 Conclusion -- References -- Internet of Things (IoT) in the Agriculture Sector: Challenges and Solutions -- 1 What Is Advance Agriculture? -- 2 Why Is It Necessary to Adapt to the Advancement of Agriculture? -- 3 Benefits of Using IoT in Agriculture -- 4 Infusion of Internet of Things in Agriculture -- 5 Challenges Encountered in Infusion of IoT in Agriculture -- References -- Implementation of Women's Self-Security System Using IoT-Based Device -- 1 Introduction -- 2 Existing System -- 3 Proposed System -- 4 Methodology -- 5 Result and Discussion -- 6 Conclusion -- References -- Evolution of Hadoop and Big Data Trends in Smart World -- 1 Introduction to Big Data -- 2 The Three V's -- 3 Challenges with Big Data -- 4 Hadoop Architecture: HDFS and Map-Reduce -- 5 HDFS -- 5.1 Features of HDFS -- 5.2 Storage in HDFS -- 6 MapReduce -- 7 Hadoop Ecosystem and Components -- 7.1 YARN (Yet Another Resource Negotiator) -- 7.2 Pig -- 7.3 Hive -- 7.4 HBase -- 7.5 Cassandra. 7.6 Sqoop and Flume -- 7.7 Apache Spark -- 8 Hadoop 3.0 Upgradation -- 9 Applications and Future -- 9.1 Predictive Policing -- 9.2 Unique Identity Project: From Cradle to Grave -- 9.3 Intelligent Transportation System -- 9.4 Smart Meters -- References -- Experimental Investigation of Eco-enzyme and Its Application for Removal of Foul Odour and Organic Impurities -- 1 Introduction -- 2 Materials and Methods -- 3 Results -- 3.1 Laboratory Results -- 3.1.1 Sample Collection -- 3.2 Field Results -- 3.2.1 Barapullah Drain, Delhi (16 February to 9 March 2016) -- 3.2.2 Drains at Pune -- 3.2.3 Sanjay Park, East Delhi -- 3.2.4 Ponds in Chennai -- 3.2.5 STP at Chandigarh -- 3.2.6 Drains of Azamgarh City -- 3.2.7 Garbage Dump Yard at Ghaziabad, UP -- 3.2.8 Two Garbage Dump Yards at Dehradun (Uttarakhand) -- 3.2.9 Garbage Dump Yard at Akola (Maharashtra) -- 4 Conclusions -- References -- Sign Language Recognition Using AI -- 1 Introduction -- 2 Literature Survey -- 3 Proposed Methodology -- 3.1 Implementation Model -- 4 Results -- 5 Conclusion, Limitations, and Future Scope -- 5.1 Conclusion -- 5.2 Limitations -- 5.3 Future Scope -- References -- Data Leakage Detection and Prevention Using Cloud Computing -- 1 Introduction -- 1.1 Motivation -- 2 Data Loss Prevention -- 2.1 Limitations of Cloud DLP -- 3 Related Work -- 3.1 Watermarking Technique -- 3.2 Fake Objects Method -- 3.3 Adversary Model -- 4 Secure Hashing Algorithm (SHA) -- 5 Proposed Model -- 5.1 Data Allocation -- 5.2 Fake Object Module -- 5.3 Optimization Module -- 5.4 Data Distribution Module -- 6 Conclusion -- References -- To Brace Society 5.0: Enhanced Reliability with a Cost-Effective Protocol for Underwater Wireless Sensor Network -- 1 Introduction -- 2 Literature Review -- 3 System Model -- 3.1 Transmission-Power and SNR -- 3.2 Signal-to-Noise Ratio and PDR -- 4 Proposed Model. 4.1 Initial Phase -- 4.2 Graph Building -- 4.3 Transmission Phase -- 5 Results -- 5.1 Evaluation of SNR -- 5.2 Evaluation of BER -- 5.3 Evaluation of PDR -- 6 Conclusion -- References -- A Novel Algorithm for Reconfigurable Architecture for Software-Defined Radio Receiver on Baseband Processor for Demodulation -- 1 Introduction -- 2 Background -- 2.1 Baseband Demodulation -- 2.2 OFDM -- 2.3 Channel Equalization -- 2.4 Phase Offset Correction -- 2.5 QAM (Quadrature Amplitude Modulation) Demapping -- 3 Algorithm Analysis -- 3.1 Dataflow for Channel Selection/FFT -- 3.2 Signal Flow Graph for FIR/FFT -- 4 Architecture Design Approach -- 4.1 Reconfigurability -- 4.2 Data Path -- 4.3 The Communication Interface -- 4.4 The Processing Part -- 4.5 The Storage Part -- 4.6 The Configuration Part -- 4.7 Control Section -- 4.8 Configuration Unit -- 5 Algorithm Mapping -- 5.1 Mapping of Matched FIR Filter -- 5.2 Mapping of FFT -- 6 Synthesis and Evaluation -- 6.1 Synthesis Results for the SDR Receiver -- 6.2 Comparison of Proposed Design with Montium TP -- 6.3 Comparison of Different Implementations -- 7 Conclusions -- 8 Future Work -- References -- Methods and Application of 3D Printing in Implantable MedicalDevices -- 1 Introduction -- 2 3D Printing Manufacturing Process -- 2.1 Stereolithography -- 2.2 Laminated Object Manufacturing -- 2.3 Selective Laser Sintering (SLS) -- 2.4 Fused Deposition Modeling -- 2.5 3D Printing -- 2.6 Photopolymer Jetting -- 2.7 Powder Binder Printer -- 3 Importance of 3D Printing (Medical Field) -- 3.1 3D Printing Materials (Implantable Medical Device) -- 3.1.1 Polymer Materials -- 3.1.2 Metal Materials -- 3.1.3 Ceramic Materials -- 3.1.4 Composite Materials -- 3.1.5 Derived Materials -- 3.2 Medical Devices Printed in 3D -- 3.2.1 Vascular Stents -- 3.2.2 Prosthetic Valve -- 3.2.3 Artificial Joint Prostheses. 3.2.4 Engineering of Hard and Soft Tissues -- 3.2.5 Peripheral Hip Diseases -- 4 Conclusion -- References -- Fuzzy-Based Hierarchical Routing Protocol for Wireless Sensor Networks -- 1 Introduction -- 2 Existing Systems -- 3 Proposed Model -- 4 System Model -- 5 Implementation and Results -- 6 Conclusion -- References -- A Review of AI-Based Diagnosis of Multiple Thoracic Diseases in Chest Radiography -- 1 Introduction -- 2 Important Design Factors -- 2.1 Learning Forms -- 2.2 Network Architecture -- 2.3 Training Types -- 3 Multiple Disease Classification -- 3.1 Evaluation Metrics Used -- 3.2 Popular Dataset -- 3.3 State-of-the-Art Models -- 4 Discussion and Future Trends -- 5 Conclusion -- References -- Introduction to Deep Learning -- 1 Introduction -- 2 Machine Learning Versus Deep Learning -- 3 The Architecture of Deep Learning -- 3.1 Supervised Learning -- 3.2 Convolutional Neural Network -- 3.3 Recurrent Neural Networks -- 3.4 LSTM Networks -- 3.5 GRU Networks -- 3.6 Unsupervised Deep Learning -- 3.7 Self-Organized Map -- 3.8 Autoencoder -- 3.9 Restricted Boltzmann Machine -- 3.10 Deep Belief Network (DBN) -- 3.11 Deep Stacking Network (DSN) -- 4 Applications -- References -- Methodological Assessment of Various Algorithm Types for Load Balancing in Cloud Computing -- 1 Introduction -- 2 Load Balancing -- 3 Data Source -- 3.1 Search Criteria -- 3.2 Evaluation of the Level of Quality -- 4 Methods for Having to Balance Workloads -- 4.1 There Are Two Varieties of It Based on the Current State of the System -- 4.2 Load Balancing Metrics [18] -- 5 Comparative Study (Fig. 8) -- 6 Conclusion -- References -- Extraction Techniques and Evaluation Measures for Extractive Text Summarisation -- 1 Introduction -- 2 Related Work on Extractive Text Summarisation -- 3 Extractive vs Abstractive Summarisation Method. 3.1 Steps Followed by Extractive-Based Summarisation Methods. |
| Record Nr. | UNISA-996547972803316 |
| Cham, Switzerland : , : Springer, , [2023] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
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Sustainable Computing : Transforming Industry 4.0 to Society 5.0 / / edited by Shashank Awasthi, Goutam Sanyal, Carlos M. Travieso-Gonzalez, Pramod Kumar Srivastava, Dinesh Kumar Singh, Rama Kant
| Sustainable Computing : Transforming Industry 4.0 to Society 5.0 / / edited by Shashank Awasthi, Goutam Sanyal, Carlos M. Travieso-Gonzalez, Pramod Kumar Srivastava, Dinesh Kumar Singh, Rama Kant |
| Edizione | [1st ed. 2023.] |
| Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2023 |
| Descrizione fisica | 1 online resource (352 pages) |
| Disciplina |
658.4038028563
004 |
| Soggetto topico |
Telecommunication
Cooperating objects (Computer systems) Computational intelligence Artificial intelligence Communications Engineering, Networks Cyber-Physical Systems Computational Intelligence Artificial Intelligence |
| ISBN |
9783031135774
3031135776 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Introduction -- Sustainable computing in Healthcare -- IoT for Contemporary Life -- Artificial Intelligence in Multimedia Technology -- Artificial Intelligence in Security and Surveillance -- Artificial Intelligence in Big Data Analytics -- Engineering design for sustainable development using IOT/AI -- Intelligent and Smart Grid Systems -- Sustainable computing in Energy conservation -- Sustainable computing in Society 5.0 -- Artificial Intelligence in Geo-Politics -- Cyber Physical System for Social Problems -- Artificial Intelligence and Machine Learning in Healthcare -- Open Challenges in Society 5.0 -- Economic empowerment using AI/ML/IoT -- Machine Learning and Computing for Sustainable Development Goals -- Deep Learning for Society 5.0 -- Intelligent and Smart Farming for Society 5.0 -- Technological Innovation in Industry 4.0 -- Artificial Intelligence in E-Governance -- Deep Learning in E-Governance -- Conclusion. |
| Record Nr. | UNINA-9910637707503321 |
| Cham : , : Springer International Publishing : , : Imprint : Springer, , 2023 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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