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Record Nr. |
UNISA996550554203316 |
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Titolo |
Data analytics for internet of things infrastructure / / Rohit Sharma, Gwanggil Jeon, Yan Zhang, editors |
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Pubbl/distr/stampa |
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Cham : , : Springer, , 2023 |
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©2023 |
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ISBN |
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Edizione |
[1st ed.] |
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Descrizione fisica |
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1 online resource (xv, 326 pages) : illustrations |
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Collana |
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Internet of Things Series |
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Altri autori (Persone) |
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SharmaRohit (Rohit Y.) |
JeonGwanggil |
ZhangYan |
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Disciplina |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Nota di contenuto |
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Intro -- Preface -- Key Features -- Contents -- About the Editors -- Big Data in Cloud Today: A Comprehensive Survey -- 1 Introduction -- 2 Characteristics of Big Data -- 3 Classification of Big Data -- 4 Importance of Big Data -- 5 Examples for Big Data -- 6 Tools and Techniques -- 7 Big Data Analytics and Its Benefits -- 8 Cloud Computing -- 9 Working of Cloud Computing -- 10 Conclusion -- References -- Cloud of Things Platform for a Water Meter Network -- 1 Introduction -- 2 Related Work and Problem Motivation -- 2.1 Related Work -- 2.2 IoT Paradigm -- 2.3 Problem Motivation -- 3 Proposed IoT Architecture -- 3.1 System Model -- 3.2 Methodology -- 3.3 Development of Active Switch -- 3.4 Development of an Active Sensor -- 3.5 Integration -- 4 Simulation and Result -- 4.1 Setup Process -- 4.2 Analysis -- 5 Conclusion -- References -- Online Newspaper Development within the Internet of Things Environment: The Role of Computer-Mediated Communication -- 1 Computer-Mediated Communication -- 2 Scholarly Information Related to CMC -- 3 CMC and Development of Online Newspapers -- 3.1 Advantages of Online Newspapers -- 3.2 Delivery of Online News and Information -- 3.3 CMC Journalism Is a Better Option -- 4 Interactivity with News Through CMC and Issues Within IoT Environment -- 4.1 CMC as a Tool for Organizations and Governments to Spread Information and News -- 4.2 |
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The Use of Social Media and Its Social Outcomes Concerning CMC -- 4.3 Emerging Issues Related to the Use of CMC -- 4.4 Reconfiguration of Territorially and Interest-Based Associations -- 4.5 Introduction of New Artifacts and Their Social Outcomes -- 4.6 The Mutual Shaping of Consumers and Technologies -- 5 Conclusion -- References -- FATS (Fuzzy Authentication to Provide Trust-Based Security) in VANET to Mitigate Black Hole Attack -- 1 Introduction -- 2 VANET Architecture. |
3 Attacks and Threats Generated in VANET -- 3.1 Selfish Node Attack -- 3.2 Jellyfish Attack -- 3.3 Data Flooding Attack -- 3.4 Black Hole Attack -- 4 Prominent Issues Caused by a Black Hole Node -- 5 Fuzzy Logic and Its Role in the Proposed Approach -- 5.1 Introduction About Fuzzy Logic -- 5.2 Mamdani Fuzzy Inference System -- 5.2.1 Max-Min Inference Method -- 5.2.2 Max-product inference method -- 6 Fuzzy Logic Trust-Based Authentication Schemes in VANET -- 7 Proposed Algorithm FATS (Fuzzy Authentication to Provide Trust-Based Security) for Black Hole Attack Detection -- 7.1 Pseudocode for Providing a Communication Link to the New Node -- 7.2 Formation of Fuzzy Rules Using Mamdani Inference System in MATLAB -- 8 Implementation of FATS -- 9 Conclusion -- References -- AI-Based Chatbot Agents as Drivers of Purchase Intentions: An Interdisciplinary Study -- 1 Introduction -- 2 Conceptual Background and Development of Hypothesis -- 3 Informational Support of Chatbots and Predicting Purchase Intentions -- 4 Trust, Emotional Credibility, and Predicting Purchase Intentions -- 5 Research Gap -- 6 Objectives -- 7 Methods -- 7.1 Sampling Framework and Questionnaire Design -- 7.2 Measures -- 8 Research Tools and Techniques -- 9 Measurement Model -- 10 Analysis of Structural Model -- 11 Conclusion and Future Research Works -- 12 Limitations -- References -- An Intelligent Model for Identifying Fluctuations in the Stock Market and Predicting Investment Policies with Guaranteed Returns -- 1 Introduction -- 2 Literature Survey -- 3 Impact of Big Data in Stock Market -- 3.1 Big Data -- 3.1.1 Big Data Architecture -- 3.2 Structure of Big Data -- 3.2.1 Structured Data -- 3.2.2 Unstructured Data -- 3.2.3 Semistructured Data -- 3.3 Big Data in the Stock Market -- 3.4 Nature of Dynamic Data in the Stock Market -- 4 Proposed Model (Fig. 2) -- 4.1 Objectives. |
4.2 Mathematical Implementation -- 4.2.1 Statistical Analysis -- 4.2.2 Fuzzy Inferences -- 5 Implementation -- 5.1 Data Preparation -- 5.2 Data Cleaning and Data Preprocessing -- 5.2.1 Data Normalisation -- 5.3 Fuzzy Inference -- 5.3.1 Axis Bank -- 5.3.2 Tata Steel -- 5.3.3 Titan -- 5.3.4 Threshold Value -- 5.3.5 Parameters -- 5.3.6 Fuzzy Rules -- 6 Results and Discussion -- 6.1 Performance Analysis -- 7 Conclusion -- References -- Sandwiched Metasurface Antenna for Small Spacecrafts in IoT Infrastructure -- 1 Introduction -- 2 Antenna Design and Geometrical Analysis -- 3 Results, Data Analysis, and Discussions -- 4 Conclusions and Future Works -- References -- Development of Laser-Beam Cutting-Edge Technology and IOT-Based Race Car Lapse Time Computational System -- 1 Introduction -- 2 Literature Review -- 3 Proposed Method -- 3.1 Block Diagram -- 3.2 Simulation of Proposed System -- 4 Results and Discussion -- 5 Conclusion -- References -- A Study of Cloud-Based Solution for Data Analytics -- 1 Introduction -- 2 Methodology -- 2.1 Amazon Web Services (AWS) Cloud Platform for Data Analytics -- 2.1.1 Architecture Study of a Data Analytics System Using AWS -- 2.1.2 Data Ingestion and Processing -- 2.1.3 Data Preparation -- 2.1.4 AI/ML Workbench -- 2.2 Google Cloud Platform (GCP) for Data Analytics -- 2.2.1 Architecture Study of a Data Analytics System Using GCP -- 2.2.2 Data Ingestion and Processing -- 2.2.3 Data Preparation -- 3 Comparative Analysis of Services Required from AWS and GCP -- 4 Challenges -- 5 |
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Conclusion -- References -- An Intelligent Model for Optimizing Sparsity Problem Toward Movie Recommendation Paradigm Using Machine Learning -- 1 Introduction -- 2 Similar Works Done -- 3 Fundamentals of Big Data -- 3.1 Properties of Big Data -- 3.2 Big Data in Entertainment Industry -- 3.2.1 Uses of Big Data in Media and Entertainment. |
4 Proposed Model -- 4.1 Mathematical Background -- 4.2 Ant Colony Optimization (ACO) -- 4.2.1 Theoretical Considerations on ACO -- 4.3 Data Preparation -- 5 Results and Discussion -- 5.1 Performance Analysis -- 5.1.1 Evaluation Metrics -- 6 Conclusion -- References -- Techniques to Identify Image Objects Under Adverse Environmental Conditions: A Systematic Literature Review -- 1 Introduction -- 1.1 Morphological Operations on Image -- 1.2 Impact of the Environment on Objects -- 2 Methodology and Research Description -- 3 Findings and Results -- 4 Conclusion -- References -- Technology-Enhanced Teaching and Learning During the COVID-19 Pandemic -- 1 Introduction -- 2 Current Perspectives on Technology-Enhanced Language Teaching and Learning -- 3 Computer-Mediated Communication and Interaction Approach -- 4 Research on Remote Teaching in Crisis Situations -- 5 Technology Acceptance Model -- 6 Responsive Online Teaching in Crises -- 7 Bloom's Digital Taxonomy -- 8 Recommendations -- 9 Conclusion -- References -- The Symbiotic Relation of IoT and AI for Applications in Various Domains: Trends and Future Directions -- 1 Introduction -- 2 Recent Works on IoT and AI in Various Domains -- 2.1 Healthcare -- 2.2 Sustainability -- 2.3 Information Security -- 2.4 Education -- 2.5 Pollution Monitoring (Table 5) -- 2.6 Robotics (Table 6) -- 2.7 Other Related Works -- 3 Conclusion and Future Directions -- References -- Text Summarization for Big Data Analytics: A Comprehensive Review of GPT 2 and BERT Approaches -- 1 Introduction -- 2 Related Works -- 2.1 Text Summarization Using Deep Learning -- 2.2 Need for Text Summarization in Big Data Analytics -- 3 BERT -- 3.1 BERT Architecture -- 3.2 Phases in Generating the Summary -- 3.2.1 Input Document -- 3.2.2 Interval Segment Embedding -- 3.2.3 Embedding -- 3.2.4 Segment Embeddings -- 3.2.5 Position Embeddings. |
3.2.6 Summarization -- 3.2.7 Inter Sentence Transformer -- 4 GPT-2 -- 5 Experiment Setup -- 5.1 About the Dataset -- 5.2 Training the Models -- 5.3 Evaluation Metrics -- 5.4 Summary Snippets -- 6 Comparison of Results -- 7 Conclusion -- References -- Leveraging Secured E-Voting Using Decentralized Blockchain Technology -- 1 Introduction -- 2 Blockchain -- 2.1 What Is Blockchain? -- 2.2 Working of a Blockchain -- 2.2.1 Elliptic Curve Digital Signature Technique (ECDSA) -- 2.3 Features of Blockchain Technology -- 2.3.1 Immutability -- 2.3.2 Auditability -- 2.3.3 Persistency -- 2.3.4 Decentralization -- 2.3.5 Anonymity -- 3 Types, Consensus Protocols, and Unfilled Gaps -- 3.1 Types of Blockchain -- 3.1.1 Public Blockchain -- 3.1.2 Private Blockchain -- 3.1.3 Consortium Blockchain -- 3.1.4 Hybrid Blockchain -- 3.2 Consensus Protocols -- 3.2.1 Proof of Work -- 3.2.2 Proof of Burn -- 3.2.3 Proof of Stake -- 3.2.4 Delegated Proof of Stake -- 3.2.5 Proof of Elapsed Time -- 3.2.6 Proof of Participation -- 3.2.7 Proof of Authority -- 3.2.8 Proof of Importance -- 3.2.9 Proof of Capacity -- 3.2.10 Proof of History -- 3.3 Challenges Faced by Existing Systems -- 3.3.1 Paper and Ballot Systems -- 3.3.2 Digital E-Voting Systems -- 4 Recent Advances -- 5 Conclusion -- References -- Multilayer Security and Privacy Provision in Internet of Things Networks: Challenges and Future Trends -- 1 The Internet of Things -- 2 Architecture and Technologies of IoT -- 3 Security Requirements in Distributed IoT Applications -- 4 Existing Challenges and Issues in IoT |
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-- 4.1 Security Issues in the Network Layer -- 4.2 Security Issues at Physical Layer -- 5 Countermeasures for Security in IoT -- 5.1 Attacks on and Threats to IoT -- 5.2 Defenses Against IoT Attacks on Each Layer -- 6 Privacy Issues in IoT -- 6.1 Existing Security Models for IoT Networks -- 7 The Future of IoT -- 7.1 Top-Ten IoT Developments. |
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Sommario/riassunto |
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This book provides techniques for the deployment of semantic technologies in data analysis along with the latest applications across the field such as Internet of Things (IoT). The authors focus on the use of the IoT and big data in business intelligence, data management, Hadoop, machine learning, cloud, smart cities, etc. They discuss how the generation of big data by IoT has ruptured the existing data processing capacity of IoT and recommends the adoption of data analytics to strengthen solutions. The book addresses the challenges in designing the web based IoT system, provides a comparative analysis of different advanced approaches in industries, and contains an analysis of databases to provide expert systems. The book aims to bring together leading academic scientists, researchers, and research scholars to exchange and share their experiences and research results on all aspects of IoT and big data analytics. Provides deployment of semantic technologies in data analysis along with the latest applications in Internet of Things; Familiarizes readers with the data analysis environment so they can apply it in Internet of Things; Addresses the challenges in designing web based IoT systems. |
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