Machine Learning, Blockchain Technologies and Big Data Analytics for IoTs: methods, technologies and applications
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...
Gespeichert in:
| Weitere Verfasser: | , , , , |
|---|---|
| Format: | Elektronisch E-Book |
| Sprache: | English |
| Veröffentlicht: |
Stevenage
The Institution of Engineering and Technology
2022
|
| Schriftenreihe: | IET security series
16 |
| Online-Zugang: | TUM01 UBY01 Volltext |
| Zusammenfassung: | 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. |
| Beschreibung: | 1 Online-Ressource (xxxviii, 639 Seiten) Illustrationen, Diagramme |
| ISBN: | 9781839533402 |
| DOI: | 10.1049/PBSE016E |
Internformat
MARC
| LEADER | 00000nmm a2200000zcb4500 | ||
|---|---|---|---|
| 001 | BV048530589 | ||
| 003 | DE-604 | ||
| 005 | 20240207 | ||
| 007 | cr|uuu---uuuuu | ||
| 008 | 221025s2022 |||| o||u| ||||||eng d | ||
| 020 | |a 9781839533402 |9 978-1-83953-340-2 | ||
| 024 | 7 | |a 10.1049/PBSE016E |2 doi | |
| 035 | |a (ZDB-100-IET)PBSE016E | ||
| 035 | |a (OCoLC)1349537552 | ||
| 035 | |a (DE-599)BVBBV048530589 | ||
| 040 | |a DE-604 |b ger |e rda | ||
| 041 | 0 | |a eng | |
| 049 | |a DE-91 |a DE-706 | ||
| 084 | |a ST 530 |0 (DE-625)143679: |2 rvk | ||
| 084 | |a ST 300 |0 (DE-625)143650: |2 rvk | ||
| 245 | 1 | 0 | |a Machine Learning, Blockchain Technologies and Big Data Analytics for IoTs |b methods, technologies and applications |c edited by Amit Kumar Tyagi, Ajith Abraham, Farookh Khadeer Hussain, Arturas Kaklauskas and R. Jagadeesh Kannan |
| 264 | 1 | |a Stevenage |b The Institution of Engineering and Technology |c 2022 | |
| 300 | |a 1 Online-Ressource (xxxviii, 639 Seiten) |b Illustrationen, Diagramme | ||
| 336 | |b txt |2 rdacontent | ||
| 337 | |b c |2 rdamedia | ||
| 338 | |b cr |2 rdacarrier | ||
| 490 | 0 | |a IET security series |v 16 | |
| 520 | |a 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. | ||
| 700 | 1 | |a Tyagi, Amit Kumar |d 1988- |0 (DE-588)1231503025 |4 edt | |
| 700 | 1 | |a Abraham, Ajith |d 1968- |0 (DE-588)123881315 |4 edt | |
| 700 | 1 | |a Hussain, Farookh Khadeer |0 (DE-588)1207270997 |4 edt | |
| 700 | 1 | |a Kaklauskas, Arturas |d 1961- |0 (DE-588)172784700 |4 edt | |
| 700 | 1 | |a Kannan, R. Jagadeesh |4 edt | |
| 776 | 0 | 8 | |i Erscheint auch als |n Druck-Ausgabe |z 978-1-83953-339-6 |
| 856 | 4 | 0 | |u https://doi.org/10.1049/PBSE016E |x Verlag |z URL des Erstveröffentlichers |3 Volltext |
| 912 | |a ZDB-100-IET | ||
| 999 | |a oai:aleph.bib-bvb.de:BVB01-033907310 | ||
| 966 | e | |u https://doi.org/10.1049/PBSE016E |l TUM01 |p ZDB-100-IET |q TUM_Paketkauf_2022 |x Verlag |3 Volltext | |
| 966 | e | |u https://doi.org/10.1049/PBSE016E |l UBY01 |p ZDB-100-IET |x Verlag |3 Volltext | |
Datensatz im Suchindex
| _version_ | 1804184523656658944 |
|---|---|
| adam_txt | |
| any_adam_object | |
| any_adam_object_boolean | |
| author2 | Tyagi, Amit Kumar 1988- Abraham, Ajith 1968- Hussain, Farookh Khadeer Kaklauskas, Arturas 1961- Kannan, R. Jagadeesh |
| author2_role | edt edt edt edt edt |
| author2_variant | a k t ak akt a a aa f k h fk fkh a k ak r j k rj rjk |
| author_GND | (DE-588)1231503025 (DE-588)123881315 (DE-588)1207270997 (DE-588)172784700 |
| author_facet | Tyagi, Amit Kumar 1988- Abraham, Ajith 1968- Hussain, Farookh Khadeer Kaklauskas, Arturas 1961- Kannan, R. Jagadeesh |
| building | Verbundindex |
| bvnumber | BV048530589 |
| classification_rvk | ST 530 ST 300 |
| collection | ZDB-100-IET |
| ctrlnum | (ZDB-100-IET)PBSE016E (OCoLC)1349537552 (DE-599)BVBBV048530589 |
| discipline | Informatik |
| discipline_str_mv | Informatik |
| doi_str_mv | 10.1049/PBSE016E |
| format | Electronic eBook |
| fullrecord | <?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>03021nmm a2200433zcb4500</leader><controlfield tag="001">BV048530589</controlfield><controlfield tag="003">DE-604</controlfield><controlfield tag="005">20240207 </controlfield><controlfield tag="007">cr|uuu---uuuuu</controlfield><controlfield tag="008">221025s2022 |||| o||u| ||||||eng d</controlfield><datafield tag="020" ind1=" " ind2=" "><subfield code="a">9781839533402</subfield><subfield code="9">978-1-83953-340-2</subfield></datafield><datafield tag="024" ind1="7" ind2=" "><subfield code="a">10.1049/PBSE016E</subfield><subfield code="2">doi</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(ZDB-100-IET)PBSE016E</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(OCoLC)1349537552</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-599)BVBBV048530589</subfield></datafield><datafield tag="040" ind1=" " ind2=" "><subfield code="a">DE-604</subfield><subfield code="b">ger</subfield><subfield code="e">rda</subfield></datafield><datafield tag="041" ind1="0" ind2=" "><subfield code="a">eng</subfield></datafield><datafield tag="049" ind1=" " ind2=" "><subfield code="a">DE-91</subfield><subfield code="a">DE-706</subfield></datafield><datafield tag="084" ind1=" " ind2=" "><subfield code="a">ST 530</subfield><subfield code="0">(DE-625)143679:</subfield><subfield code="2">rvk</subfield></datafield><datafield tag="084" ind1=" " ind2=" "><subfield code="a">ST 300</subfield><subfield code="0">(DE-625)143650:</subfield><subfield code="2">rvk</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">Machine Learning, Blockchain Technologies and Big Data Analytics for IoTs</subfield><subfield code="b">methods, technologies and applications</subfield><subfield code="c">edited by Amit Kumar Tyagi, Ajith Abraham, Farookh Khadeer Hussain, Arturas Kaklauskas and R. Jagadeesh Kannan</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="a">Stevenage</subfield><subfield code="b">The Institution of Engineering and Technology</subfield><subfield code="c">2022</subfield></datafield><datafield tag="300" ind1=" " ind2=" "><subfield code="a">1 Online-Ressource (xxxviii, 639 Seiten)</subfield><subfield code="b">Illustrationen, Diagramme</subfield></datafield><datafield tag="336" ind1=" " ind2=" "><subfield code="b">txt</subfield><subfield code="2">rdacontent</subfield></datafield><datafield tag="337" ind1=" " ind2=" "><subfield code="b">c</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="b">cr</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="490" ind1="0" ind2=" "><subfield code="a">IET security series</subfield><subfield code="v">16</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">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.</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Tyagi, Amit Kumar</subfield><subfield code="d">1988-</subfield><subfield code="0">(DE-588)1231503025</subfield><subfield code="4">edt</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Abraham, Ajith</subfield><subfield code="d">1968-</subfield><subfield code="0">(DE-588)123881315</subfield><subfield code="4">edt</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Hussain, Farookh Khadeer</subfield><subfield code="0">(DE-588)1207270997</subfield><subfield code="4">edt</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Kaklauskas, Arturas</subfield><subfield code="d">1961-</subfield><subfield code="0">(DE-588)172784700</subfield><subfield code="4">edt</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Kannan, R. Jagadeesh</subfield><subfield code="4">edt</subfield></datafield><datafield tag="776" ind1="0" ind2="8"><subfield code="i">Erscheint auch als</subfield><subfield code="n">Druck-Ausgabe</subfield><subfield code="z">978-1-83953-339-6</subfield></datafield><datafield tag="856" ind1="4" ind2="0"><subfield code="u">https://doi.org/10.1049/PBSE016E</subfield><subfield code="x">Verlag</subfield><subfield code="z">URL des Erstveröffentlichers</subfield><subfield code="3">Volltext</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">ZDB-100-IET</subfield></datafield><datafield tag="999" ind1=" " ind2=" "><subfield code="a">oai:aleph.bib-bvb.de:BVB01-033907310</subfield></datafield><datafield tag="966" ind1="e" ind2=" "><subfield code="u">https://doi.org/10.1049/PBSE016E</subfield><subfield code="l">TUM01</subfield><subfield code="p">ZDB-100-IET</subfield><subfield code="q">TUM_Paketkauf_2022</subfield><subfield code="x">Verlag</subfield><subfield code="3">Volltext</subfield></datafield><datafield tag="966" ind1="e" ind2=" "><subfield code="u">https://doi.org/10.1049/PBSE016E</subfield><subfield code="l">UBY01</subfield><subfield code="p">ZDB-100-IET</subfield><subfield code="x">Verlag</subfield><subfield code="3">Volltext</subfield></datafield></record></collection> |
| id | DE-604.BV048530589 |
| illustrated | Not Illustrated |
| index_date | 2024-07-03T20:52:12Z |
| indexdate | 2024-07-10T09:40:42Z |
| institution | BVB |
| isbn | 9781839533402 |
| language | English |
| oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-033907310 |
| oclc_num | 1349537552 |
| open_access_boolean | |
| owner | DE-91 DE-BY-TUM DE-706 |
| owner_facet | DE-91 DE-BY-TUM DE-706 |
| physical | 1 Online-Ressource (xxxviii, 639 Seiten) Illustrationen, Diagramme |
| psigel | ZDB-100-IET ZDB-100-IET TUM_Paketkauf_2022 |
| publishDate | 2022 |
| publishDateSearch | 2022 |
| publishDateSort | 2022 |
| publisher | The Institution of Engineering and Technology |
| record_format | marc |
| series2 | IET security series |
| spelling | Machine Learning, Blockchain Technologies and Big Data Analytics for IoTs methods, technologies and applications edited by Amit Kumar Tyagi, Ajith Abraham, Farookh Khadeer Hussain, Arturas Kaklauskas and R. Jagadeesh Kannan Stevenage The Institution of Engineering and Technology 2022 1 Online-Ressource (xxxviii, 639 Seiten) Illustrationen, Diagramme txt rdacontent c rdamedia cr rdacarrier IET security series 16 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. Tyagi, Amit Kumar 1988- (DE-588)1231503025 edt Abraham, Ajith 1968- (DE-588)123881315 edt Hussain, Farookh Khadeer (DE-588)1207270997 edt Kaklauskas, Arturas 1961- (DE-588)172784700 edt Kannan, R. Jagadeesh edt Erscheint auch als Druck-Ausgabe 978-1-83953-339-6 https://doi.org/10.1049/PBSE016E Verlag URL des Erstveröffentlichers Volltext |
| spellingShingle | Machine Learning, Blockchain Technologies and Big Data Analytics for IoTs methods, technologies and applications |
| title | Machine Learning, Blockchain Technologies and Big Data Analytics for IoTs methods, technologies and applications |
| title_auth | Machine Learning, Blockchain Technologies and Big Data Analytics for IoTs methods, technologies and applications |
| title_exact_search | Machine Learning, Blockchain Technologies and Big Data Analytics for IoTs methods, technologies and applications |
| title_exact_search_txtP | Machine Learning, Blockchain Technologies and Big Data Analytics for IoTs methods, technologies and applications |
| title_full | Machine Learning, Blockchain Technologies and Big Data Analytics for IoTs methods, technologies and applications edited by Amit Kumar Tyagi, Ajith Abraham, Farookh Khadeer Hussain, Arturas Kaklauskas and R. Jagadeesh Kannan |
| title_fullStr | Machine Learning, Blockchain Technologies and Big Data Analytics for IoTs methods, technologies and applications edited by Amit Kumar Tyagi, Ajith Abraham, Farookh Khadeer Hussain, Arturas Kaklauskas and R. Jagadeesh Kannan |
| title_full_unstemmed | Machine Learning, Blockchain Technologies and Big Data Analytics for IoTs methods, technologies and applications edited by Amit Kumar Tyagi, Ajith Abraham, Farookh Khadeer Hussain, Arturas Kaklauskas and R. Jagadeesh Kannan |
| title_short | Machine Learning, Blockchain Technologies and Big Data Analytics for IoTs |
| title_sort | machine learning blockchain technologies and big data analytics for iots methods technologies and applications |
| title_sub | methods, technologies and applications |
| url | https://doi.org/10.1049/PBSE016E |
| work_keys_str_mv | AT tyagiamitkumar machinelearningblockchaintechnologiesandbigdataanalyticsforiotsmethodstechnologiesandapplications AT abrahamajith machinelearningblockchaintechnologiesandbigdataanalyticsforiotsmethodstechnologiesandapplications AT hussainfarookhkhadeer machinelearningblockchaintechnologiesandbigdataanalyticsforiotsmethodstechnologiesandapplications AT kaklauskasarturas machinelearningblockchaintechnologiesandbigdataanalyticsforiotsmethodstechnologiesandapplications AT kannanrjagadeesh machinelearningblockchaintechnologiesandbigdataanalyticsforiotsmethodstechnologiesandapplications |