Towards the Integration of IoT, Cloud and Big Data : Services, Applications and Standards

• Record Nr.: UNINA9910754092203321
• Autore: Rishiwal Vinay
• Pubbl/distr/stampa: Singapore : , : Springer, , 2023; ©2023
• ISBN: 981-9960-34-7
• Edizione: [1st ed.]
• Descrizione fisica: 1 online resource (164 pages)
• Collana: Studies in Big Data Series ; ; v.137
• Altri autori (Persone): KumarPramod; TomarAnuradha; Malarvizhi KumarPriyan
• Soggetti: Internet of things; Cloud computing
• Lingua di pubblicazione: Inglese
• Formato: Materiale a stampa
• Livello bibliografico: Monografia
• Nota di contenuto: Intro -- Preface -- Contents -- Editors and Contributors -- Introduction to Big Data Analytics -- 1 Introduction to Big Data -- 2 The Distinction Between Small and Big Data -- 3 Classification of Big Data -- 4 Characteristics of Big Data -- 5 Who's Generating Big Data? -- 6 Why Is Big Data Important? -- 7 Challenges in Big-Data -- 8 Big Data Applications -- 9 How Big Data Analysis Differs from Business Intelligence Analysis? -- 9.1 Business Intelligence -- 9.2 Big Data -- 9.3 Differences Between Business Intelligence (BI) and Big Data -- 10 The Analytical Lifestyle of Big Data -- 10.1 Phase 1: Discovery -- 10.2 Phase 2: Data Preparation -- 10.3 Phase 3: Model Planning -- 10.4 Phase 4: Model Building -- 10.5 Phase 5: Communicate Results -- 10.6 Phase 6: Operationalize -- 11 Big Data Analysis Necessitates a Set of Skills -- 12 Big Data Domain -- 13 Introduction to Big Data Analytics -- 14 Overview of the Hadoop Ecosystem -- 14.1 HDFS -- 14.2 YARN -- 14.3 MapReduce -- 14.4 Spark -- 15 Overview of Big Data Analysis and Its Need -- 16 Use Cases of Big Data Analytics -- 17 Challenges in Analyzing Big Data -- 18 Big Data Quality Dimensions -- 19 Conclusion -- References -- DCD_PREDICT: Using Big Data on Prediction for Chest Diseases by Applying Machine Learning ; Algorithms -- 1 Introduction -- 1.1 Introduction -- 1.2 Background -- 1.3 Objective -- 2 Literature Survey -- 2.1 Summary -- 3 System Design -- 3.1 Existing System -- 3.2 Identification of Common Risks -- 3.3 Types of Heart Diseases -- 3.4 Problem Statement -- 3.5 Scope -- 3.6 Proposed System -- 4 Methodology -- 4.1 Supervised Learning -- 4.2 Symptom-Based Questionnaire -- 4.3 Dataset Training and Testing -- 5 Process and Analysis -- 5.1 General Process -- 5.2 Use Case Diagram -- 5.3 Data Flow Diagram -- 5.4 System Flow -- 6 Implementation and Results -- 6.1 Details of Algorithms.; 6.2 Data Set and Its Parameters -- 6.3 Dataset Attributes -- 6.4 Execution and Screenshots -- 7 Conclusion and Future Scope -- 7.1 Conclusion -- 7.2 Future Scope -- References -- Design of Energy Efficient IoMT Electrocardiogram (ECG) Machine on 28 nm FPGA -- 1 Introduction -- 2 Background -- 3 Environmental Settings for Energy Efficient IoMT ECG Machine -- 4 Power Analysis of IoMT ECG Machine -- 5 Conclusion -- References -- Automatic Smart Irrigation Method for Agriculture Data -- 1 Introduction -- 2 Motivation -- 3 Contribution of the Chapter -- 4 Organization and Roadmap of the Article -- 5 Related Works -- 6 About the Dataset and Features -- 7 Methodology and Applied Algorithms -- 7.1 Data Processing -- 7.2 Machine Learning -- 8 Result and Analysis -- 9 Challenges in Proposed Work -- 10 Conclusion and Future Work -- References -- Artificial Intelligence Based Plant Disease Detection -- 1 Introduction -- 2 Motivation -- 3 Contribution of the Chapter -- 4 Organization of the Chapter -- 5 Literature Survey -- 6 Issues and Challenges -- 7 Methodology -- 7.1 Advantages of Using Convolution Neural Network (CNN) -- 7.2 Flow of the Models -- 7.3 Image Preprocessing -- 8 Performance Metrics -- 9 Result Analysis -- 10 Conclusion and Future Scope -- References -- IoT Equipped Intelligent Distributed Framework for Smart Healthcare Systems -- 1 Introduction -- 1.1 Internet of Things (IoT) -- 1.2 Smart Healthcare -- 1.3 DDBMS -- 1.4 Artificial Intelligence (AI) -- 1.5 Blockchain Technology -- 2 Security Issues in Smart Healthcare Systems -- 2.1 Communication Media -- 2.2 Topology Issues -- 2.3 Scalability -- 2.4 Mobility and Energy Constraints -- 2.5 Memory Constraints -- 2.6 Multi-protocol Network -- 2.7 Tamper Devices -- 3 Existing Healthcare Systems -- 4 Proposed Model -- 5 Results and Discussion -- 6 Conclusions -- References.; Adaptive Particle Swarm Optimization for Energy Minimization in Cloud: A Success History Based Approach -- 1 Introduction -- 2 Background and Related Work -- 3 Proposed Approach -- 4 Results and Discussions -- 5 Conclusion and Future Work -- Appendix -- References -- Field Monitoring and Automation in Agriculture Using Internet of Things (IoT) -- 1 Introduction -- 2 Related Works -- 3 IoT Technologies for Field Monitoring in Agriculture -- 3.1 Drones in Agriculture -- 3.2 Remote Sensing in Agriculture -- 3.3 Computer Imaging in Agriculture -- 4 Proposed Automated System Model for Agricuture -- 4.1 Proposed System Block Diagram -- 5 Work Flow of System Model -- 5.1 Field Quality Analysis -- 5.2 Irrigation System -- 5.3 System Design -- 5.4 Irrigation System -- 6 Hardware Setup for Proposed System Model -- 7 Android Mobile Application for Monitoring the Work Flow -- 8 Getting Alerts for Motor On/Off via Mobile Application -- 9 Conclusion -- References.
• Sommario/riassunto: This book explores the integration of the Internet of Things (IoT), Cloud Computing, and Big Data technologies, focusing on the development of innovative services, applications, and standards. It addresses the challenges of managing massive data generated by IoT devices and the need for scalable protocols to enable seamless integration with cloud-based systems. The book covers various topics, including Big Data ; analytics, machine learning methods for disease prediction, energy-efficient IoT devices, smart agriculture technologies, and the use of Blockchain for securing medical records. It is intended for researchers, engineers, and professionals in the fields of computer science, engineering, and data science.