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Advances in Fuzzy-Based Internet of Medical Things (IoMT)
| Advances in Fuzzy-Based Internet of Medical Things (IoMT) |
| Autore | Prakash Yadav Satya |
| Edizione | [1st ed.] |
| Pubbl/distr/stampa | Newark : , : John Wiley & Sons, Incorporated, , 2024 |
| Descrizione fisica | 1 online resource (309 pages) |
| Altri autori (Persone) |
YadavSudesh
RajPethuru C. de AlbuquerqueVictor Hugo |
| ISBN |
1-394-24225-5
1-394-24224-7 |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910842398203321 |
Prakash Yadav Satya
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| Newark : , : John Wiley & Sons, Incorporated, , 2024 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Automated Workflow Scheduling in Self-Adaptive Clouds : Concepts, Algorithms and Methods / / by G. Kousalya, P. Balakrishnan, C. Pethuru Raj
| Automated Workflow Scheduling in Self-Adaptive Clouds : Concepts, Algorithms and Methods / / by G. Kousalya, P. Balakrishnan, C. Pethuru Raj |
| Autore | Kousalya G |
| Edizione | [1st ed. 2017.] |
| Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2017 |
| Descrizione fisica | 1 online resource (XVII, 225 p. 74 illus.) |
| Disciplina | 004.6782 |
| Collana | Computer Communications and Networks |
| Soggetto topico |
Computer networks
Application software Computer input-output equipment Artificial intelligence Computer Communication Networks Information Systems Applications (incl. Internet) Input/Output and Data Communications Artificial Intelligence |
| ISBN | 3-319-56982-1 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Stepping into the Digital Intelligence Era -- Demystifying the Traits of Software-Defined Cloud Environments (SDCEs) -- Workflow Management Systems -- Workflow Scheduling Algorithms and Approaches -- Workflow Modeling and Simulation Techniques -- Execution of Workflow Scheduling in Cloud Middleware -- Workflow Predictions through Operational Analytics and Machine Learning -- Workflow Integration and Orchestration - Opportunities and the Challenges -- Workload Consolidation through Automated Workload Scheduling -- Automated Optimization Methods for Workflow Execution -- Hybrid IT: Characteristics and Capabilities. |
| Record Nr. | UNINA-9910254821403321 |
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Kousalya G
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| Cham : , : Springer International Publishing : , : Imprint : Springer, , 2017 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Blockchain, artificial intelligence, and the Internet of things : possibilities and opportunities / / Pethuru Raj [and three others] editors
| Blockchain, artificial intelligence, and the Internet of things : possibilities and opportunities / / Pethuru Raj [and three others] editors |
| Pubbl/distr/stampa | Cham, Switzerland : , : Springer, , [2022] |
| Descrizione fisica | 1 online resource (218 pages) |
| Disciplina | 004.678 |
| Collana | EAI/Springer Innovations in Communication and Computing |
| Soggetto topico |
Internet of things
Blockchains (Databases) |
| ISBN | 3-030-77637-9 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910523909503321 |
| Cham, Switzerland : , : Springer, , [2022] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Edge of Intelligence : Exploring the Frontiers of AI at the Edge
| Edge of Intelligence : Exploring the Frontiers of AI at the Edge |
| Autore | Mahajan Shubham |
| Edizione | [1st ed.] |
| Pubbl/distr/stampa | Newark : , : John Wiley & Sons, Incorporated, , 2025 |
| Descrizione fisica | 1 online resource (460 pages) |
| Altri autori (Persone) |
MunirathinamSathyan
RajPethuru |
| ISBN |
9781394314393
1394314396 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910987494603321 |
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Mahajan Shubham
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| Newark : , : John Wiley & Sons, Incorporated, , 2025 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Essentials of Microservices Architecture : Paradigms, Applications, and Techniques
| Essentials of Microservices Architecture : Paradigms, Applications, and Techniques |
| Autore | Surianarayanan Chellammal |
| Edizione | [First edition.] |
| Pubbl/distr/stampa | [Place of publication not identified] : , : Taylor & Francis, , 2019 |
| Descrizione fisica | 1 online resource (xx, 294 pages) |
| Disciplina | 005.3 |
| Altri autori (Persone) |
GanapathyGopinath
RajPethuru |
| Soggetto topico | Application software - Development |
| ISBN |
1-000-61756-4
0-429-32992-X |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Chapter 1. An Introduction to Service Oriented ArchitectureChapter 2. Demystifying Microservices Architecture (MSA)Chapter 3. Communication Models for MicroservicesChapter 4. Designing APIs and Developing Middleware Platform for MicroservicesChapter 5. Service Discovery and API GatewayChapter 6. Service Orchestration and ChoreographyChapter 7. Database Transactions in MSAChapter 8. Patterns for Microservice-Centric ApplicationsChapter 9. MSA Security and MigrationChapter 10. Platform Solutions for MSA |
| Record Nr. | UNINA-9910952279503321 |
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Surianarayanan Chellammal
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| [Place of publication not identified] : , : Taylor & Francis, , 2019 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Generative AI : Disruptive Technologies for Innovative Applications
| Generative AI : Disruptive Technologies for Innovative Applications |
| Autore | Gayathri N |
| Edizione | [1st ed.] |
| Pubbl/distr/stampa | Newark : , : John Wiley & Sons, Incorporated, , 2025 |
| Descrizione fisica | 1 online resource (291 pages) |
| Disciplina | 006.3 |
| Altri autori (Persone) |
KumarS. Rakesh
ChandranRamesh RajPethuru PelusiDanilo |
| Soggetto topico | Artificial intelligence |
| ISBN |
1-394-30291-6
1-394-30293-2 |
| 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 Introduction to Generative AI -- 1.1 What is Generative AI -- 1.2 Difference Between AI, Machine Learning and Generative AI -- 1.3 History of Generative AI -- 1.4 Key Milestones and Continued Progress -- 1.4.1 Generative Adversarial Networks (GANs) -- 1.4.2 Variational Autoencoders (VAEs) -- 1.4.3 Autoregressive Models -- 1.4.4 Transformer Models -- 1.4.5 Recurrent Neural Networks and Long Short-Term Memory Networks -- 1.4.6 Energy-Based Models (EBMs) -- 1.4.7 Flow-Based Models -- 1.4.8 Diffusion Models -- 1.5 Exploring the Inner Workings of Generative AI: Understanding Large Language Models (LLMs) -- 1.6 LLMs vs. Generative AI -- 1.7 The Impact and Future of LLMs -- 1.8 Benefits of Generative AI -- 1.9 Risks of Generative AI -- 1.10 Evaluating Generative AI Models -- 1.11 Technical Challenges and Limitations of Gen AI -- 1.11.1 Continual Reliance on Data -- 1.11.2 Hallucinations -- 1.11.3 Lack of Creativity -- 1.11.4 Ethics and Privacy -- 1.12 Real Life Use Case of Gen AI -- 1.13 Conclusion -- References -- Chapter 2 Generative Adversarial Networks (GANs) -- 2.1 Introduction -- 2.2 Tale of Two Minds: Unveiling the GAN Mechanism -- 2.2.1 Origins -- 2.2.2 Foundational Concepts of Generative Adversarial Network -- 2.2.3 The Discriminator -- 2.2.3.1 Theoretical Understanding -- 2.2.3.2 Objectives and Functionality -- 2.2.3.3 Mathematical Formulation -- 2.2.4 The Generator -- 2.2.4.1 The Generator's Objective and Mathematical Formulation -- 2.2.4.2 Creative Dynamics of the Generator -- 2.2.5 Adversarial Training -- 2.2.5.1 Fundamental Principles of Adversarial Training -- 2.2.5.2 Training Dynamics in Adversarial Training -- 2.2.5.3 Adversarial Training Application -- 2.2.5.4 Difficulties and Restrictions -- 2.2.5.5 Future Paths and Prospects for Research.
2.3 From Brushstrokes to Breakthroughs: Diverse Canvas of GAN Applications -- 2.3.1 Dreaming Up New Worlds: Aesthetic Mastery -- 2.3.1.1 Mastery of Aesthetics Using GANs -- 2.3.1.2 Improving Realism -- 2.3.2 Data Augmentation -- 2.3.2.1 GAN-Based Enrichment of Data -- 2.3.2.2 Cross-Domain Applications -- 2.3.3 Unsupervised Learning -- 2.3.3.1 GANs in Unsupervised Learning -- 2.4 Challenges and Ethical Considerations -- 2.4.1 Mode Collapse -- 2.4.2 Instability During Training -- 2.4.3 Absence of Convergence -- 2.5 A Glimpse into the Future: Where GANs Will Lead Us -- 2.5.1 Customized Content Production -- 2.5.2 Targeted Image Reproduction -- 2.5.3 Improved Data Distortion -- 2.5.4 Conditional Generation -- 2.5.5 Overcoming Obstacles -- 2.6 Conclusion: The Revolutionary Impact of Generative Adversarial Networks (GANs) -- References -- Chapter 3 Reinforcement Learning in Generative AI -- 3.1 Introduction -- 3.2 Current State of the Art in Generative AI with Reinforcement Learning -- 3.3 Different Applications for Generative AI with Reinforcement Learning -- 3.4 Characteristics of Generative AI with Reinforcement Learning -- 3.5 Outstanding Problems in Generative AI with Reinforcement Learning -- 3.6 Limitations of Generative AI with Reinforcement Learning -- 3.7 Conclusion -- References -- Chapter 4 Pix2pix GAN for Image-to-Image Translation: A Comparative Study with Diverse Datasets -- 4.1 Introduction -- 4.1.1 Significance of Generative AI in the Three Use Cases -- 4.2 Related Works -- 4.3 Methodology -- 4.4 Results and Discussions -- 4.4.1 Dataset -- 4.4.2 Experimental Assessment -- 4.5 Conclusion -- References -- Chapter 5 Study of State-of-the-Art Performance Metrics in NLP: Specifically for Text Summarization in the Medical Domain Using the SumPubMed Dataset -- 5.1 Introduction -- 5.2 Literature Review -- 5.3 Research Methodology -- 5.4 Results. 5.5 Conclusions -- 5.6 Future Score of Work -- References -- Chapter 6 The Impact of Generative AI in Gaming: Exploring Immersive Experiences -- 6.1 Introduction -- 6.2 Realistic Textures and Landscapes -- 6.3 Intelligent NPCS and Adaptive Behaviors -- 6.4 Expanding Beyond Traditional Gaming -- 6.5 Conclusion -- References -- Chapter 7 Ethical Dimensions and Societal Effects of Generative AI: The Portrayal of Ethical Issues of ChatGPT, DALL-E, and Other Systems -- Introduction -- Ethical Considerations in AI-Driven Recruitment: Video and Image Interviews -- UNESCO -- Conclusion -- Acknowledgments -- References -- Chapter 8 Generative Artificial Intelligence for Social Good and Sustainable Development -- 8.1 Introduction -- 8.1.1 Motivation of Generative Artificial Intelligence -- 8.1.2 The Contribution of the Chapter -- 8.1.3 The Organization of the Chapter -- 8.2 An Overview of Generative Artificial Intelligence and Its Applications -- 8.2.1 Text Generation -- 8.2.2 Image Generation -- 8.2.3 Audio and Music Generation -- 8.2.4 Data Augmentation -- 8.2.5 Video and Animation Generation -- 8.2.6 Drug Discovery -- 8.2.7 Content Recommendation -- 8.2.8 Language Translation -- 8.2.9 Humanoid Robots and Avatars -- 8.2.10 Design and Creativity -- 8.3 Generative AI for Social Good -- 8.3.1 Personalized Healthcare Interventions -- 8.3.2 Equitable Education Access -- 8.3.3 Disaster Response and Humanitarian Aid -- 8.3.4 Accessible Information for Diverse Audiences -- 8.3.5 Mental Health Support and Therapy -- 8.3.6 Language Translation for Communication and Diplomacy -- 8.3.7 Environmental Conservation and Sustainability -- 8.3.8 Crisis Counseling and Suicide Prevention -- 8.3.9 Promoting Social Equity Through Policy Insights -- 8.3.10 Content Creation for Nonprofits and Humanitarian Organizations. 8.4 Generative Artificial Intelligence for Sustainable Development -- 8.4.1 Renewable Energy Optimization -- 8.4.2 Smart Resource Management -- 8.4.3 Climate Change Mitigation -- 8.4.4 Ecosystem Monitoring and Conservation -- 8.4.5 Circular Economy Promotion -- 8.4.6 Sustainable Agriculture and Food Security -- 8.4.7 Urban Planning and Smart Cities -- 8.4.8 Water Resource Management -- 8.4.9 Global Supply Chain Sustainability -- 8.4.10 Environmental Education and Advocacy -- 8.5 Ethical and Regulatory Considerations -- 8.5.1 Data Privacy and Security -- 8.5.2 Fairness and Bias -- 8.5.3 Explainability and Transparency -- 8.5.4 Accountability -- 8.5.5 Environmental Impact -- 8.5.6 Ethical Use Cases -- 8.5.7 Global Collaboration -- 8.5.8 Ethical Artificial Intelligent Education -- 8.5.9 Public Engagement, Input and Global Governance -- 8.6 Generative Artificial Intelligence Limitations -- 8.6.1 Data Dependence -- 8.6.2 Bias and Fairness -- 8.6.3 Ethical Concerns -- 8.6.4 Lack of Creativity and Common Sense -- 8.6.5 Resource Intensive -- 8.6.6 Interpretability and Transparency -- 8.6.7 Overfitting -- 8.7 Future Research Directions -- 8.8 Lessons Learned and the Conclusion -- 8.8.1 Lessons -- 8.8.2 Conclusion -- References -- Chapter 9 Revolutionizing Implementation: Cutting-Edge Tools and Resources in Generative AI -- 9.1 Introduction -- 9.2 Foundational Theories and Models -- 9.3 State-of-the-Art Tools in Generative AI -- 9.4 Generative AI Tools Strategies -- 9.5 Literature Review Methodology -- 9.6 Challenges and Solutions -- 9.7 Future Directions -- 9.8 Conclusion -- References -- Chapter 10 Applying Fuzzy Data Science in Generative AI for Healthcare -- 10.1 Introduction -- 10.1.1 Overview of Fuzzy Data Science and Generative AI -- 10.1.2 Relevance of These Technologies in Healthcare -- 10.1.3 Objectives and Structure of the Chapter. 10.2 Fundamentals of Fuzzy Data Science -- 10.2.1 Definition and Principles of Fuzzy Logic and Fuzzy Sets -- 10.2.2 Importance of Handling Uncertainty and Imprecision in Healthcare Data -- 10.2.3 Integration of Fuzzy Logic Along with AI Technologies -- 10.3 Generative AI in Healthcare -- 10.3.1 Explanation of Generative Models and Their Applications in Healthcare -- 10.3.2 Benefits of Generative AI for Medical Imaging, Diagnostics, and Treatment Planning -- 10.4 Synergizing Fuzzy Data Science with Generative AI -- 10.4.1 Conceptual Framework for Integrating Fuzzy Logic with Generative AI -- 10.4.2 Techniques and Methodologies for Combining These Technologies -- 10.4.2.1 Fuzzy Generative Adversarial Networks (Fuzzy GANs) -- 10.4.2.2 Fuzzy Variational Autoencoders (Fuzzy VAEs) -- 10.4.2.3 Fuzzy Clustering with Generative Models -- 10.4.3 Sources of Complexity in Healthcare Data and Uses of the Hybrid Approach -- 10.4.3.1 Handling Uncertainty and Imprecision -- 10.5 Case Study 1: Enhancing Diagnostic Accuracy -- 10.6 Case Study 2: Personalized Treatment Planning -- 10.7 Challenges and Limitations -- 10.7.1 Technical Challenges in Integrating Fuzzy Logic and Generative AI -- 10.7.2 Data Quality and Interpretability Issues -- 10.7.3 Ethical and Privacy Considerations in Healthcare Applications -- 10.8 Future Directions -- 10.8.1 Emerging Trends and Innovations in Fuzzy Data Science and Generative AI -- 10.8.2 Potential Future Applications in Healthcare -- 10.8.3 Recommendations for Researchers and Practitioners -- 10.9 Conclusion -- 10.9.1 Summary of Key Findings from the Case Studies -- 10.9.2 Overall Impact of Fuzzy Data Science and Generative AI on Healthcare -- 10.9.3 Final Thoughts on the Future of These Technologies in Medical Science -- References. Chapter 11 Generative AI in Hospital Industry Transforming Medical Imagining for Patient Diagnosis and Health Data Management. |
| Record Nr. | UNINA-9911025992103321 |
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Gayathri N
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| Newark : , : John Wiley & Sons, Incorporated, , 2025 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Intelligent Robots and Drones for Precision Agriculture / / edited by Sundaravadivazhagan Balasubramanian, Gnanasankaran Natarajan, Pethuru Raj Chelliah
| Intelligent Robots and Drones for Precision Agriculture / / edited by Sundaravadivazhagan Balasubramanian, Gnanasankaran Natarajan, Pethuru Raj Chelliah |
| Edizione | [1st ed. 2024.] |
| Pubbl/distr/stampa | Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2024 |
| Descrizione fisica | 1 online resource (479 pages) |
| Disciplina | 338.16 |
| Collana | Signals and Communication Technology |
| Soggetto topico |
Automatic control
Robotics Automation Agriculture Telecommunication Control, Robotics, Automation Communications Engineering, Networks |
| ISBN | 3-031-51195-6 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Introduction -- Intelligent computing with drones and robotics for Precision Agriculture -- Smart Farming and Precision Agriculture and Its Need in Today’s World -- Role of Machine Learning in Smart Farming and Its Applications -- Types of Soil Classification for the Identification of the Right Crop to be Cultivated -- Convergence of IoT, Big Data and Machine Learning for better yield Prediction in Smart Farming -- Soil Classification and Crop Prediction using Machine Learning Techniques -- Artificial Intelligence (AI) – enabled Drone Technology for Smart Farming -- Connected Drones for Smart Farming: The Use Cases and Challenges -- Drones and Robots in Smart Agriculture -- IoT-based Precision Agriculture and Crop Management using Machine Learning Approaches -- Smart Organic Agriculture in Traditional South Indian Based Farming System -- Crop and Fertilizer Recommendation System for Sustainable Agricultural Development -- The Role of Robotics and Drones in Precision Farming using Artificial Intelligence with an Automatic Learning Approach -- Applications of UAV-AD (Unmanned Aerial Vehicle-Agricultural Drones) in Precision Farming -- Machine Learning (ML) Algorithms on IoT and Drone Data for Smart Farming -- Recent improvements and major challenges in Digitized farming: A review -- A Comprehensive Review on the Internet of Things, 5G network, Drone Technologies for Smart Agriculture -- Internet of Things based Smart Agriculture Advisory System -- Conclusion. |
| Record Nr. | UNINA-9910845497003321 |
| Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2024 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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The internet of things and big data analytics : integrated platforms and industry use cases / / edited by Pethuru Raj, T. Poongodi, Balamurugan Balusamy, and Manju Khari
| The internet of things and big data analytics : integrated platforms and industry use cases / / edited by Pethuru Raj, T. Poongodi, Balamurugan Balusamy, and Manju Khari |
| Edizione | [First edition.] |
| Pubbl/distr/stampa | Boca Raton, FL : , : CRC Press, , 2020 |
| Descrizione fisica | 1 online resource (339 pages) |
| Disciplina | 004.67/8 |
| Soggetto topico |
Internet of things
Big data |
| ISBN |
1-00-303673-2
1-000-05739-9 1-003-03673-2 1-000-05735-6 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910794120603321 |
| Boca Raton, FL : , : CRC Press, , 2020 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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The internet of things and big data analytics : integrated platforms and industry use cases / / edited by Pethuru Raj, T. Poongodi, Balamurugan Balusamy, and Manju Khari
| The internet of things and big data analytics : integrated platforms and industry use cases / / edited by Pethuru Raj, T. Poongodi, Balamurugan Balusamy, and Manju Khari |
| Edizione | [First edition.] |
| Pubbl/distr/stampa | Boca Raton, FL : , : CRC Press, , 2020 |
| Descrizione fisica | 1 online resource (339 pages) |
| Disciplina | 004.67/8 |
| Soggetto topico |
Internet of things
Big data |
| ISBN |
1-00-303673-2
1-000-05739-9 1-003-03673-2 1-000-05735-6 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910799941603321 |
| Boca Raton, FL : , : CRC Press, , 2020 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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The internet of things and big data analytics : integrated platforms and industry use cases / / edited by Pethuru Raj, T. Poongodi, Balamurugan Balusamy, and Manju Khari
| The internet of things and big data analytics : integrated platforms and industry use cases / / edited by Pethuru Raj, T. Poongodi, Balamurugan Balusamy, and Manju Khari |
| Edizione | [First edition.] |
| Pubbl/distr/stampa | Boca Raton, FL : , : CRC Press, , 2020 |
| Descrizione fisica | 1 online resource (339 pages) |
| Disciplina | 004.67/8 |
| Soggetto topico |
Internet of things
Big data |
| ISBN |
1-00-303673-2
1-000-05739-9 1-003-03673-2 1-000-05735-6 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910812360003321 |
| Boca Raton, FL : , : CRC Press, , 2020 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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