LEADER 10885nam 22004813 450 001 9910510580503321 005 20211129080318.0 010 $a9783030738853$b(electronic bk.) 010 $z9783030738846 035 $a(MiAaPQ)EBC6812148 035 $a(Au-PeEL)EBL6812148 035 $a(CKB)19919156000041 035 $a(OCoLC)1287137541 035 $a(EXLCZ)9919919156000041 100 $a20211129d2022 uy 0 101 0 $aeng 135 $aurcnu|||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aIoT and Cloud Computing for Societal Good 210 1$aCham :$cSpringer International Publishing AG,$d2022. 210 4$d©2022. 215 $a1 online resource (331 pages) 225 1 $aEAI/Springer Innovations in Communication and Computing Ser. 311 08$aPrint version: Verma, Jitendra Kumar IoT and Cloud Computing for Societal Good Cham : Springer International Publishing AG,c2022 9783030738846 327 $aIntro -- Preface -- Technical Programme Committee -- Editorial Advisory Board -- Contents -- About the Editors -- Part I Tackling Climate Change -- 1 Towards Energy Efficient Cloud Computing: Research Directions and Methodological Approach -- 1.1 Introduction -- 1.2 Background Motivation -- 1.3 Power Consumption and Energy Efficient Dynamic VM Consolidation -- 1.4 Defining Objective and Setting Research Questions -- 1.5 Methodological Approach -- 1.6 Conclusion -- References -- 2 IoT-Based Smart Air Quality Control System: Prevention to COVID-19 -- 2.1 Introduction -- 2.1.1 Motivation -- 2.1.2 Contribution -- 2.1.3 Organization -- 2.2 Related Work -- 2.3 Proposed Model -- 2.4 Results and Discussion -- 2.5 Conclusion and Future Scope -- References -- 3 Forecasting of Air Pollution via a Low-Cost IoT-Based Monitoring System -- 3.1 Introduction -- 3.2 Related Work -- 3.3 Methodology -- 3.3.1 Data -- 3.3.2 Models -- 3.3.3 Model Calibration -- 3.4 Result -- 3.5 Discussion and Future Work -- References -- 4 Internet of Things Based Best Fruit Segregation and Taxonomy System for Smart Agriculture -- 4.1 Introduction -- 4.2 Literature Review -- 4.3 Methodology -- 4.4 Software/Hardware Tool Used -- 4.4.1 Software Part -- 4.4.2 Hardware Part -- 4.5 Design and Implementation -- 4.5.1 Background Separation of Image -- 4.5.2 Calculating the Center of Blob -- 4.5.3 Calculating Black Dots -- 4.5.4 Fourier Transform -- 4.6 Conclusion -- References -- 5 Toward the Creation of a Web-Based Platform "Bike Sharing" in the Local Transport System -- 5.1 General Formulation of the Problem -- 5.2 Analysis of Recent Research and Publications -- 5.3 Selection of Previously Unsolved Parts of the Overall Problem -- 5.4 Statement of Research Tasks -- 5.5 Material and Research Results -- 5.6 Conclusions -- References -- Part II Digital Health, Learning and Industry. 327 $a6 A Survey of Societal Applications of IOT -- 6.1 Introduction -- 6.2 Motivation -- 6.3 IOT -- 6.4 Trends in the Internet of Things -- 6.5 Comparison with the Existing System -- 6.6 Agriculture Applications of IoT -- 6.6.1 Monitoring of Irrigation in Agriculture with IoT -- 6.6.2 Smart Agriculture -- 6.6.3 Intelligent Irrigation -- 6.6.4 Automated Weather Report Causation for Smart Irrigation -- 6.6.5 IoT Based Disease Analysis in Agriculture -- 6.6.6 Flood Prevention Using IoT -- 6.7 Healthcare Applications of IoT -- 6.7.1 IoT in Healthcare -- 6.7.2 Challenges in Health Care with IoT -- 6.7.3 Multidisciplinary Health Care System -- 6.7.4 Survey on Internet of Things Based on Health Care -- 6.7.5 IoT Incorporate Attention Monitoring to Intercept Incursion -- 6.7.6 IoT Based Healthcare with Body Sensor Network (BSN) -- 6.8 IoT in Military -- 6.8.1 Smart Sniper with IoT -- 6.8.2 Military Applications in Smart City with IoT -- 6.8.3 IoT Based Military Federation -- 6.8.4 Fault Tolerant Techniques on the Internet of Military Things -- 6.8.5 IoT Based Military Applications -- 6.9 IoT in Railways -- 6.10 Smart Train Detector Using IoT Approach -- 6.11 IoT in Smart Cities -- 6.12 Smart Home -- 6.12.1 Energy Competent Home Automation Using IoT -- 6.12.2 Home Gadgets Control with IoT -- 6.12.3 Performance Analysis on Wireless Smart Home Automation -- 6.13 Industrial IoT -- 6.13.1 The Internet of Robotic Things -- 6.14 Recognition Proficiency -- 6.15 Fluctuation Proficiency -- 6.16 Conclusion -- References -- 7 Simplify the Difficult: Artificial Intelligence and Cloud Computing in Healthcare -- 7.1 Introduction -- 7.2 Motivation -- 7.3 Cloud Computing -- 7.3.1 Software as a Service (SaaS) -- 7.3.2 Platform as a Service (PaaS) -- 7.3.3 Infrastructure as a Service (IaaS) -- 7.3.4 Internet of Things (IoT) -- 7.4 Artificial Intelligence Tools -- 7.4.1 Neuron. 327 $a7.4.2 Neural Networks -- 7.4.2.1 Deep Neural Network -- 7.4.2.2 Natural Language Processing -- 7.4.2.3 Recurrent Neural Networks (RNN) -- 7.4.2.4 Convolutional Neural Network (CNN) -- 7.5 Application Areas -- 7.5.1 Information Tools -- 7.5.1.1 Applications in Health Care Administration -- 7.5.1.2 Cloud Computing Systems for Healthcare Management -- 7.5.1.3 Health Monitoring with IoT -- 7.5.2 Disease Management -- 7.5.2.1 Diabetes Management Through Artificial Intelligence -- 7.5.2.2 Monitoring Mental Health Through IoT -- 7.5.3 Preemptive Measures -- 7.5.3.1 Early Detection Through Biomarkers -- 7.5.3.2 Diagnosis Through Image Recognition -- 7.5.4 Pathological Diagnosis -- 7.5.4.1 Rheumatoid Arthritis -- 7.5.4.2 Epileptic Seizures -- 7.5.4.3 Alzheimer's Disease -- 7.5.4.4 Diabetic Retinopathy -- 7.5.4.5 Breast Cancer -- 7.5.4.6 Obstructive Lung Disease -- 7.5.4.7 Cardiovascular Diseases (CVDs) -- 7.5.5 Applications in Mental Healthcare -- 7.5.5.1 Mental Health Detection Through Sentimental Analysis on Tweets -- 7.5.5.2 Suicide Prevention -- 7.6 Current Limitations -- 7.7 Conclusions and Future Prospects -- References -- 8 NOS Personal Assistant to Engage Elderly People withSmart Home -- 8.1 Introduction -- 8.2 Background -- 8.2.1 Internet of Things -- 8.2.2 Ambient Assisted Living Market -- 8.2.3 Natural Interfaces Landscape -- 8.3 NOS Technology -- 8.3.1 The Challenges of NOS Personal Assistant -- 8.3.2 The Overall Solution -- 8.3.3 A Bottom-Up Approach -- 8.4 Future Research and Innovation Directions -- 8.5 Conclusion -- References -- 9 Digital Technologies Changing the Landscape of Corporate Learning and Development -- 9.1 Introduction -- 9.1.1 Rise of Digital Learning -- 9.2 Digital Learning Framework -- 9.2.1 Start with the End in Mind -- 9.2.2 Assess the Digital Fluency of Your Target Audience -- 9.2.3 Design the Content. 327 $a9.2.4 Select Appropriate Digital Learning Platforms and Tools -- 9.2.5 Implement the Digital Learning Program -- 9.2.6 Measure the Impact and Foster Continuous Improvement -- 9.3 Creating the Culture of Learning -- 9.4 Upskilling L& -- D Personnel -- 9.5 Conclusion -- References -- 10 An Assessment of the Behavioral Intention of Generation Z Toward the Adoption of Digital Learning Applications -- 10.1 Introduction -- 10.2 Literature Review -- 10.2.1 Digital Learning -- 10.2.2 Internet of Things (IoT) and Cloud Computing -- 10.2.3 Digital Learning App -- 10.2.4 Actual Use (AU) -- 10.2.5 Behavioral Intention to Use (BITU) -- 10.2.6 Attitude Toward Use (ATU) -- 10.2.7 Perceived Usefulness (PU) -- 10.2.8 Perceived Ease of Use (PEOU) -- 10.2.9 Utility, Learning, and Perceived Usefulness -- 10.2.10 Student Engagement and Perceived Usefulness -- 10.2.11 Data Security and Perceived Usefulness -- 10.2.12 Feedback and Rating and Perceived Usefulness -- 10.2.13 Accessibility and Perceived Usefulness -- 10.2.14 User Interface and Perceived Usefulness -- 10.2.15 Entertainment and Perceived Ease of Use -- 10.2.16 Accessibility and Perceived Ease of Use -- 10.2.17 User Interface and Perceived Ease of Use -- 10.2.18 Exiting TAM Models -- 10.3 Research Methodology -- 10.4 Data Analysis and Interpretation -- 10.4.1 Sample Characteristics and Distributions (N == 490) -- 10.4.2 Measurement Model: Reliability and Validity -- 10.4.3 Structural Equation Model -- 10.5 Discussion -- 10.6 Practical Implications -- 10.7 Theoretical Implications -- 10.8 Conclusion -- References -- 11 A Literature Review on Lean Manufacturing in the Industry 4.0: From Integrated Systems to IoT and Smart Factories -- 11.1 Introduction -- 11.2 The Term Industry 4.0 -- 11.3 From Integrated System to IoT -- 11.4 Smart Factory: Future of Automated Production -- 11.5 Industry 4.0 Characteristics. 327 $a11.6 Enabling Technologies of Industry 4.0 -- 11.6.1 Big Data and Analytics -- 11.6.2 Industrial Cloud and Cloud Computing -- 11.6.3 Internet of Things (IoT) -- 11.6.4 Augmented Reality -- 11.6.5 Simulation -- 11.6.6 Autonomous Robot -- 11.6.7 Horizontal and Vertical Integration -- 11.6.8 Additive Manufacturing -- 11.6.9 Cybersecurity -- 11.7 Conclusions -- References -- Part III Improving the Technology -- 12 Multimodal Feature Analysis for Precise Human Hand Gesture Recognition -- 12.1 Introduction and Background -- 12.2 Multimodal Feature Analysis for Gesture Recognition -- 12.2.1 Multi-model Feature Extraction -- 12.2.2 Multi-model Feature Recognition -- 12.3 Results and Discussion -- 12.3.1 Success Ratio -- 12.3.2 Recognition Time -- 12.4 Conclusion -- References -- 13 Calculating the Optimal Frequency of Maintenance for the Improvement of Risk Management: Plausible Models for the Integration of Cloud and IoT -- 13.1 Introduction -- 13.2 Variables Used in the Maintenance Frequency Optimization Process -- 13.2.1 Reliability and Risk -- 13.2.2 Operational Costs -- 13.2.3 Loss of Performance -- 13.2.4 Extension of Equipment Life -- 13.3 Mathematical Models Used for Preventive Replacement -- 13.3.1 Optimal Replacement Model with Use -- 13.3.2 Optimal Interval of Preventive Replacement -- 13.4 Case Study -- 13.5 Conclusions -- References -- 14 Interceptor Pattern-Based Middleware for IoT Protocol Interoperability -- 14.1 Introduction -- 14.2 Related Works -- 14.3 Related Works -- 14.4 Related Works -- 14.5 Specific Use Case -- 14.6 Test Results and Discussion -- 14.7 Conclusions -- References -- 15 Mining Active Influential Nodes for Finding Information Diffusion in Social Networks -- 15.1 Introduction -- 15.2 Literature Review -- 15.2.1 Influential Nodes Identification in Static Network. 327 $a15.2.2 Influential Nodes Identification in Dynamic/Temporal Networks. 410 0$aEAI/Springer Innovations in Communication and Computing Ser. 608 $aElectronic books. 700 $aVerma$b Jitendra Kumar$01068795 701 $aSaxena$b Deepak$01068796 701 $aGonzález-Prida$b Vicente$01068797 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 912 $a9910510580503321 996 $aIoT and Cloud Computing for Societal Good$92553768 997 $aUNINA LEADER 04583nam 22008055 450 001 9910299613003321 005 20250717134844.0 010 $a9789462099418 010 $a9462099413 024 7 $a10.1007/978-94-6209-941-8 035 $a(CKB)3710000000342685 035 $a(EBL)2095743 035 $a(OCoLC)900864477 035 $a(SSID)ssj0001466950 035 $a(PQKBManifestationID)11804455 035 $a(PQKBTitleCode)TC0001466950 035 $a(PQKBWorkID)11504348 035 $a(PQKB)10329590 035 $a(DE-He213)978-94-6209-941-8 035 $a(MiAaPQ)EBC3035030 035 $a(nllekb)BRILL9789462099418 035 $a(MiAaPQ)EBC2095743 035 $a(Au-PeEL)EBL3035030 035 $a(CaPaEBR)ebr11012065 035 $a(CaONFJC)MIL790317 035 $a(Au-PeEL)EBL2095743 035 $a(CaPaEBR)ebr11286919 035 $a(PPN)185487637 035 $a(EXLCZ)993710000000342685 100 $a20150421d2015 u| 0 101 0 $aeng 135 $aur|n|---||||| 181 $ctxt 182 $cc 183 $acr 200 10$aAgainst All Odds $eAn Empirical Study about the Situative Pedagogical Ethos of Vocational Trainers /$fby Sarah Forster-Heinzer 205 $a1st ed. 2015. 210 1$aRotterdam :$cSensePublishers :$cImprint: SensePublishers,$d2015. 215 $a1 online resource (343 p.) 225 1 $aMoral Development and Citizenship Education 300 $aDescription based upon print version of record. 311 08$a9789462099401 311 08$a9462099405 311 08$a9789462099395 311 08$a9462099391 320 $aIncludes bibliographical references. 327 $aPreliminary Material -- Against all odds: An introduction -- The scope of ethos: In search of clarity -- Models of pedagogical ethos -- Ethos: Supererogative commitment in situations of odds -- Methodology -- The trainers? ethos: Results -- Discussion -- The impact of a pedagogical trainer?s ethos experienced by apprentices -- Conclusion -- References. 330 $aIt is nearly impossible to overestimate the significance of a professional ethos in pedagogical situations. Most theories of education understand ethos and ethical acting as belonging to the core of the pedagogical profession. Despite this evidence, remarkably few empirical studies exist on ethos. This book has three main aims: 1) to conceptualize the pedagogical ethos at the theoretical level, 2) to operationalize it systematically, and 3) to study it empirically from the trainers? perspective but also from that of apprentices. Part 1 offers a critical discussion on different theoretical approaches of professional morality. These include theories on moral values or professional codes, virtue ethics, professional sensitivity, moral commitment, and caring. Identified communalities are combined to form a new model of professional ethos. More intensively than other existing theories, the ethos approach presented in this book stresses the content?s situational impact on decision-making and motivation. The main question guiding the instrument development, dealt with in Part 2, asks how we can distinguish professional morality from the general notion that people should be good. In order to answer this question, vocational education but also a trainer?s pedagogical duties and responsibilities are discussed. Part 3 then presents the result of two empirical studies with vocational trainers and apprentices. It offers some interesting findings for further reflection ? input not only relevant for researchers but also educational institutes, professional associations, and practitioners themselves. In short: this book contributes significantly to research on professional morality as well as vocational education. 410 0$aMoral Development and Citizenship Education 606 $aEnergy policy 606 $aEnergy policy 606 $aElectric power production 606 $aEnergy Policy, Economics and Management 606 $aElectrical Power Engineering 606 $aMechanical Power Engineering 615 0$aEnergy policy. 615 0$aEnergy policy. 615 0$aElectric power production. 615 14$aEnergy Policy, Economics and Management. 615 24$aElectrical Power Engineering. 615 24$aMechanical Power Engineering. 676 $a370.113 700 $aForster-Heinzer$b Sarah$0955703 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910299613003321 996 $aAgainst all odds$92162716 997 $aUNINA