dc.contributor.author | Tyagi, Amit Kumar | |
dc.contributor.author | Abraham, Ajith | |
dc.contributor.author | Hussain, Farookh Khadeer | |
dc.contributor.author | Kaklauskas, Artūras | |
dc.contributor.author | Kannan, R. Jagadeesh | |
dc.date.accessioned | 2023-09-18T16:25:52Z | |
dc.date.available | 2023-09-18T16:25:52Z | |
dc.date.issued | 2022 | |
dc.identifier.isbn | 9781839533396 | |
dc.identifier.isbn | 9781839533402 | |
dc.identifier.uri | https://etalpykla.vilniustech.lt/handle/123456789/113866 | |
dc.description.abstract | Internet of Things (IoTs) are now being integrated at a large scale in fast-developing applications such as healthcare, transportation, education, finance, insurance and retail. The next generation of automated applications will command machines to do tasks better and more efficiently. Both industry and academic researchers are looking at transforming applications using machine learning and deep learning to build better models and by taking advantage of the decentralized nature of Blockchain. But the advent of these new technologies also brings very high expectations to industries, organisations and users. The decrease of computing costs, the improvement of data integrity in Blockchain, and the verification of transactions using Machine Learning are becoming essential goals. 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. The book is aimed at a broad audience of ICTs, data science, machine learning and cybersecurity researchers interested in the integration of these disruptive technologies and their applications for IoTs. | eng |
dc.format | PDF | |
dc.format.extent | 679 p. | |
dc.format.medium | tekstas / txt | |
dc.language.iso | eng | |
dc.source.uri | https://digital-library.theiet.org/content/books/sc/pbse016e | |
dc.title | Machine learning, blockchain technologies and big data analytics for Iots: Methods, technologies and applications | |
dc.type | Sudaryti mokslo darbai / Compiled research papers | |
dcterms.references | 0 | |
dc.type.pubtype | K5 - Sudarytas mokslo darbas / Compiled scientific paper | |
dc.contributor.institution | Vellore Institute of Technology (VIT) | |
dc.contributor.institution | Machine Intelligence Research Labs (MIR Labs) | |
dc.contributor.institution | University of Technology Sydney | |
dc.contributor.institution | Vilniaus Gedimino technikos universitetas | |
dc.contributor.institution | Vellore Institute of Technology | |
dc.contributor.faculty | Statybos fakultetas / Faculty of Civil Engineering | |
dc.subject.researchfield | T 002 - Statybos inžinerija / Construction and engineering | |
dc.subject.researchfield | T 007 - Informatikos inžinerija / Informatics engineering | |
dc.subject.researchfield | S 003 - Vadyba / Management | |
dc.subject.vgtuprioritizedfields | IK0303 - Dirbtinio intelekto ir sprendimų priėmimo sistemos / Artificial intelligence and decision support systems | |
dc.subject.ltspecializations | L104 - Nauji gamybos procesai, medžiagos ir technologijos / New production processes, materials and technologies | |
dc.subject.en | Internet of Things (IoTs) | |
dc.subject.en | machine learning | |
dc.subject.en | Blockchain | |
dc.subject.en | Big Data analytics | |
dc.publisher.name | Institution of Engineering & Technology (IET) | |
dc.publisher.city | Stevenage | |
dc.identifier.doi | 10.1049/PBSE016E | |
dc.identifier.elaba | 149625537 | |