Machine Learning, Blockchain Technologies and Big Data Analytics for Iots : Methods, Technologies and Applications

• Autore: Tyagi Amit Kumar
• Pubblicazione: Stevenage : , : Institution of Engineering & Technology, , 2022; ©2022
• Edizione: 1st ed.
• Descrizione fisica: 1 online resource (939 pages)
• Disciplina: 006.3
• Soggetto topico: Machine learning
• Altri autori: AbrahamAjith <1968-> HussainFarookh Khadeer KaklauskasArturas Jagadeesh KannanR
• Nota di contenuto: Chapter 1: Introduction to machine learning, blockchain technologies, and Big Data analytics for IoTs: concepts, open issues, and critical challengesChapter 2: Image enhancement on low-light and dark images for object detection using Artificial Intelligence for field practitionersChapter 3: Cache memory architecture for the convergence of machine learning, Internet of Things (IoT), and blockchain technologiesChapter 4: Machine learning algorithms for Big Data analytics including deep learningChapter 5: Machine learning-based blockchain technologies for data storage: challenges, and opportunitiesChapter 6: Clustering crowdsourced healthcare data from drones using Big Data analyticsChapter 7: Authentication and authorization in cloud computing using blockchainChapter 8: Fundamentals of machine learning and blockchain technologies for applications in cybersecurityChapter 9: Real-world applications of generative adversarial networks and their role in blockchain technologyChapter 10: Internet of Things (IoTs)-enabled security using artificial intelligence and blockchain technologiesChapter 11: Blockchain network with artificial intelligence - DeFi affair managementChapter 12: Vulnerabilities of smart contracts and solutionsChapter 13: Data analytics for socio-economic factors affecting crime ratesChapter 14: Deployment of automated teller machinery for e-pollingChapter 15: Machine learning-based blockchain technology for protection and privacy against intrusion attacks in intelligent transportation systemsChapter 16: Blockchain-enabled Internet of Things (IoTs) platforms for vehicle sensing and transportation monitoringChapter 17: Blockchain-enabled Internet of Things (IoTs) platforms for the healthcare sectorChapter 18: An integrated dimensionality reduction model for classifying IoT-enabled smart healthcare genomic dataChapter 19: Blockchain-based learning automated analytics platform in telemedicineChapter 20: A sensor-based architecture for telemedical and environmental air pollution monitoring system using 5G and blockchainChapter 21: Blockchain-enabled Internet of Things (IoT) platforms for financial servicesChapter 22: Blockchain and machine learning: an approach for predicting the commodity pricesChapter 23: Knowledge extraction from abnormal stock returns: evidence from Indian stock marketChapter 24: Impact of influence analysis of social media fake news - a machine learning perspectiveChapter 25: Application of machine learning techniques based on real-time images for site specific insect pest and disease management of cropsChapter 26: A prioritized potential framework for combined computing technologies: IoT, Machine Learning, and blockchainChapter 27: Conclusion to this book.
• Sommario/riassunto: This edited book covers the challenges, opportunities, innovations, new concepts and emerging trends related to the use of machine learning, blockchain and big data analytics for IoTs. It is aimed at a broad audience of ICTs, Data science, machine learning and cybersecurity researchers.
• Titolo autorizzato: Machine Learning, Blockchain Technologies and Big Data Analytics for Iots
• ISBN: 1-83724-509-6; 1-5231-5335-0; 1-83953-340-4
• Formato: Materiale a stampa
• Livello bibliografico: Monografia
• Lingua di pubblicazione: Inglese
• Record Nr.: 9911006504503321
• Lo trovi qui: Univ. Federico II
• Serie: Computing and Networks