Machine learning approach for cloud data analytics in IoT:
In this era of IoT, edge devices generate gigantic data during every fraction of a second. The main aim of these networks is to infer some meaningful information from the collected data. For the same, the huge data is transmitted to the cloud which is highly expensive and time-consuming. Hence, it n...
Gespeichert in:
| Weitere beteiligte Personen: | , , , , |
|---|---|
| Format: | Elektronisch E-Book |
| Sprache: | Englisch |
| Veröffentlicht: |
Hoboken, NJ Beverly, MA
John Wiley & Sons, Inc.
2021
Hoboken, NJ Beverly, MA Scrivener Publishing LLC 2021 |
| Ausgabe: | 1st edition. |
| Schlagwörter: | |
| Links: | https://learning.oreilly.com/library/view/-/9781119785804/?ar |
| Zusammenfassung: | In this era of IoT, edge devices generate gigantic data during every fraction of a second. The main aim of these networks is to infer some meaningful information from the collected data. For the same, the huge data is transmitted to the cloud which is highly expensive and time-consuming. Hence, it needs to devise some efficient mechanism to handle this huge data, thus necessitating efficient data handling techniques. Sustainable computing paradigms like cloud and fog are expedient to capably handle the issues of performance, capabilities allied to storage and processing, maintenance, security, efficiency, integration, cost, energy and latency. However, it requires sophisticated analytics tools so as to address the queries in an optimized time. Hence, rigorous research is taking place in the direction of devising effective and efficient framework to garner utmost advantage. Machine learning has gained unmatched popularity for handling massive amounts of data and has applications in a wide variety of disciplines, including social media. Machine Learning Approach for Cloud Data Analytics in IoT details and integrates all aspects of IoT, cloud computing and data analytics from diversified perspectives. It reports on the state-of-the-art research and advanced topics, thereby bringing readers up to date and giving them a means to understand and explore the spectrum of applications of IoT, cloud computing and data analytics. |
| Beschreibung: | Includes bibliographical references and index. - Description based on online resource; title from digital title page (viewed on April 04, 2023) |
| Umfang: | 1 Online-Ressource |
| ISBN: | 9781119785873 1119785871 9781119785866 1119785863 9781119785859 1119785855 9781119785804 |
Internformat
MARC
| LEADER | 00000cam a22000002 4500 | ||
|---|---|---|---|
| 001 | ZDB-30-ORH-067581862 | ||
| 003 | DE-627-1 | ||
| 005 | 20240228121412.0 | ||
| 007 | cr uuu---uuuuu | ||
| 008 | 210811s2021 xx |||||o 00| ||eng c | ||
| 020 | |a 9781119785873 |c electronic book |9 978-1-119-78587-3 | ||
| 020 | |a 1119785871 |c electronic book |9 1-119-78587-1 | ||
| 020 | |a 9781119785866 |c electronic book |9 978-1-119-78586-6 | ||
| 020 | |a 1119785863 |c electronic book |9 1-119-78586-3 | ||
| 020 | |a 9781119785859 |c electronic book |9 978-1-119-78585-9 | ||
| 020 | |a 1119785855 |9 1-119-78585-5 | ||
| 020 | |a 9781119785804 |9 978-1-119-78580-4 | ||
| 035 | |a (DE-627-1)067581862 | ||
| 035 | |a (DE-599)KEP067581862 | ||
| 035 | |a (ORHE)9781119785804 | ||
| 035 | |a (DE-627-1)067581862 | ||
| 040 | |a DE-627 |b ger |c DE-627 |e rda | ||
| 041 | |a eng | ||
| 082 | 0 | |a 006.3/1 |2 23 | |
| 245 | 1 | 0 | |a Machine learning approach for cloud data analytics in IoT |c edited by Sachi Nandan Mohanty, Jyotir Moy Chatterjee, Monika Mangla, Suneeta Satpathy, Sirisha Potluri |
| 250 | |a 1st edition. | ||
| 264 | 1 | |a Hoboken, NJ |a Beverly, MA |b John Wiley & Sons, Inc. |c 2021 | |
| 264 | 1 | |a Hoboken, NJ |a Beverly, MA |b Scrivener Publishing LLC |c 2021 | |
| 300 | |a 1 Online-Ressource | ||
| 336 | |a Text |b txt |2 rdacontent | ||
| 337 | |a Computermedien |b c |2 rdamedia | ||
| 338 | |a Online-Ressource |b cr |2 rdacarrier | ||
| 500 | |a Includes bibliographical references and index. - Description based on online resource; title from digital title page (viewed on April 04, 2023) | ||
| 520 | |a In this era of IoT, edge devices generate gigantic data during every fraction of a second. The main aim of these networks is to infer some meaningful information from the collected data. For the same, the huge data is transmitted to the cloud which is highly expensive and time-consuming. Hence, it needs to devise some efficient mechanism to handle this huge data, thus necessitating efficient data handling techniques. Sustainable computing paradigms like cloud and fog are expedient to capably handle the issues of performance, capabilities allied to storage and processing, maintenance, security, efficiency, integration, cost, energy and latency. However, it requires sophisticated analytics tools so as to address the queries in an optimized time. Hence, rigorous research is taking place in the direction of devising effective and efficient framework to garner utmost advantage. Machine learning has gained unmatched popularity for handling massive amounts of data and has applications in a wide variety of disciplines, including social media. Machine Learning Approach for Cloud Data Analytics in IoT details and integrates all aspects of IoT, cloud computing and data analytics from diversified perspectives. It reports on the state-of-the-art research and advanced topics, thereby bringing readers up to date and giving them a means to understand and explore the spectrum of applications of IoT, cloud computing and data analytics. | ||
| 650 | 0 | |a Machine learning | |
| 650 | 0 | |a Cloud computing | |
| 650 | 0 | |a Internet of things | |
| 650 | 4 | |a Apprentissage automatique | |
| 650 | 4 | |a Infonuagique | |
| 650 | 4 | |a Internet des objets | |
| 650 | 4 | |a Cloud computing | |
| 650 | 4 | |a Internet of things | |
| 650 | 4 | |a Machine learning | |
| 700 | 1 | |a Mohanty, Sachi Nandan |e HerausgeberIn |4 edt | |
| 700 | 1 | |a Chatterjee, Jyotir Moy |e HerausgeberIn |4 edt | |
| 700 | 1 | |a Mangla, Monika |e HerausgeberIn |4 edt | |
| 700 | 1 | |a Satpathy, Suneeta |e HerausgeberIn |4 edt | |
| 700 | 1 | |a Potluri, Sirisha |e HerausgeberIn |4 edt | |
| 776 | 1 | |z 9781119785804 | |
| 776 | 0 | 8 | |i Erscheint auch als |n Druck-Ausgabe |z 9781119785804 |
| 966 | 4 | 0 | |l DE-91 |p ZDB-30-ORH |q TUM_PDA_ORH |u https://learning.oreilly.com/library/view/-/9781119785804/?ar |m X:ORHE |x Aggregator |z lizenzpflichtig |3 Volltext |
| 912 | |a ZDB-30-ORH | ||
| 912 | |a ZDB-30-ORH | ||
| 951 | |a BO | ||
| 912 | |a ZDB-30-ORH | ||
| 049 | |a DE-91 | ||
Datensatz im Suchindex
| DE-BY-TUM_katkey | ZDB-30-ORH-067581862 |
|---|---|
| _version_ | 1821494831747170304 |
| adam_text | |
| any_adam_object | |
| author2 | Mohanty, Sachi Nandan Chatterjee, Jyotir Moy Mangla, Monika Satpathy, Suneeta Potluri, Sirisha |
| author2_role | edt edt edt edt edt |
| author2_variant | s n m sn snm j m c jm jmc m m mm s s ss s p sp |
| author_facet | Mohanty, Sachi Nandan Chatterjee, Jyotir Moy Mangla, Monika Satpathy, Suneeta Potluri, Sirisha |
| building | Verbundindex |
| bvnumber | localTUM |
| collection | ZDB-30-ORH |
| ctrlnum | (DE-627-1)067581862 (DE-599)KEP067581862 (ORHE)9781119785804 |
| dewey-full | 006.3/1 |
| dewey-hundreds | 000 - Computer science, information, general works |
| dewey-ones | 006 - Special computer methods |
| dewey-raw | 006.3/1 |
| dewey-search | 006.3/1 |
| dewey-sort | 16.3 11 |
| dewey-tens | 000 - Computer science, information, general works |
| discipline | Informatik |
| edition | 1st edition. |
| format | Electronic eBook |
| fullrecord | <?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>03821cam a22006132 4500</leader><controlfield tag="001">ZDB-30-ORH-067581862</controlfield><controlfield tag="003">DE-627-1</controlfield><controlfield tag="005">20240228121412.0</controlfield><controlfield tag="007">cr uuu---uuuuu</controlfield><controlfield tag="008">210811s2021 xx |||||o 00| ||eng c</controlfield><datafield tag="020" ind1=" " ind2=" "><subfield code="a">9781119785873</subfield><subfield code="c">electronic book</subfield><subfield code="9">978-1-119-78587-3</subfield></datafield><datafield tag="020" ind1=" " ind2=" "><subfield code="a">1119785871</subfield><subfield code="c">electronic book</subfield><subfield code="9">1-119-78587-1</subfield></datafield><datafield tag="020" ind1=" " ind2=" "><subfield code="a">9781119785866</subfield><subfield code="c">electronic book</subfield><subfield code="9">978-1-119-78586-6</subfield></datafield><datafield tag="020" ind1=" " ind2=" "><subfield code="a">1119785863</subfield><subfield code="c">electronic book</subfield><subfield code="9">1-119-78586-3</subfield></datafield><datafield tag="020" ind1=" " ind2=" "><subfield code="a">9781119785859</subfield><subfield code="c">electronic book</subfield><subfield code="9">978-1-119-78585-9</subfield></datafield><datafield tag="020" ind1=" " ind2=" "><subfield code="a">1119785855</subfield><subfield code="9">1-119-78585-5</subfield></datafield><datafield tag="020" ind1=" " ind2=" "><subfield code="a">9781119785804</subfield><subfield code="9">978-1-119-78580-4</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-627-1)067581862</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-599)KEP067581862</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(ORHE)9781119785804</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-627-1)067581862</subfield></datafield><datafield tag="040" ind1=" " ind2=" "><subfield code="a">DE-627</subfield><subfield code="b">ger</subfield><subfield code="c">DE-627</subfield><subfield code="e">rda</subfield></datafield><datafield tag="041" ind1=" " ind2=" "><subfield code="a">eng</subfield></datafield><datafield tag="082" ind1="0" ind2=" "><subfield code="a">006.3/1</subfield><subfield code="2">23</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">Machine learning approach for cloud data analytics in IoT</subfield><subfield code="c">edited by Sachi Nandan Mohanty, Jyotir Moy Chatterjee, Monika Mangla, Suneeta Satpathy, Sirisha Potluri</subfield></datafield><datafield tag="250" ind1=" " ind2=" "><subfield code="a">1st edition.</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="a">Hoboken, NJ</subfield><subfield code="a">Beverly, MA</subfield><subfield code="b">John Wiley & Sons, Inc.</subfield><subfield code="c">2021</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="a">Hoboken, NJ</subfield><subfield code="a">Beverly, MA</subfield><subfield code="b">Scrivener Publishing LLC</subfield><subfield code="c">2021</subfield></datafield><datafield tag="300" ind1=" " ind2=" "><subfield code="a">1 Online-Ressource</subfield></datafield><datafield tag="336" ind1=" " ind2=" "><subfield code="a">Text</subfield><subfield code="b">txt</subfield><subfield code="2">rdacontent</subfield></datafield><datafield tag="337" ind1=" " ind2=" "><subfield code="a">Computermedien</subfield><subfield code="b">c</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="a">Online-Ressource</subfield><subfield code="b">cr</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="500" ind1=" " ind2=" "><subfield code="a">Includes bibliographical references and index. - Description based on online resource; title from digital title page (viewed on April 04, 2023)</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">In this era of IoT, edge devices generate gigantic data during every fraction of a second. The main aim of these networks is to infer some meaningful information from the collected data. For the same, the huge data is transmitted to the cloud which is highly expensive and time-consuming. Hence, it needs to devise some efficient mechanism to handle this huge data, thus necessitating efficient data handling techniques. Sustainable computing paradigms like cloud and fog are expedient to capably handle the issues of performance, capabilities allied to storage and processing, maintenance, security, efficiency, integration, cost, energy and latency. However, it requires sophisticated analytics tools so as to address the queries in an optimized time. Hence, rigorous research is taking place in the direction of devising effective and efficient framework to garner utmost advantage. Machine learning has gained unmatched popularity for handling massive amounts of data and has applications in a wide variety of disciplines, including social media. Machine Learning Approach for Cloud Data Analytics in IoT details and integrates all aspects of IoT, cloud computing and data analytics from diversified perspectives. It reports on the state-of-the-art research and advanced topics, thereby bringing readers up to date and giving them a means to understand and explore the spectrum of applications of IoT, cloud computing and data analytics.</subfield></datafield><datafield tag="650" ind1=" " ind2="0"><subfield code="a">Machine learning</subfield></datafield><datafield tag="650" ind1=" " ind2="0"><subfield code="a">Cloud computing</subfield></datafield><datafield tag="650" ind1=" " ind2="0"><subfield code="a">Internet of things</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Apprentissage automatique</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Infonuagique</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Internet des objets</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Cloud computing</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Internet of things</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Machine learning</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Mohanty, Sachi Nandan</subfield><subfield code="e">HerausgeberIn</subfield><subfield code="4">edt</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Chatterjee, Jyotir Moy</subfield><subfield code="e">HerausgeberIn</subfield><subfield code="4">edt</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Mangla, Monika</subfield><subfield code="e">HerausgeberIn</subfield><subfield code="4">edt</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Satpathy, Suneeta</subfield><subfield code="e">HerausgeberIn</subfield><subfield code="4">edt</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Potluri, Sirisha</subfield><subfield code="e">HerausgeberIn</subfield><subfield code="4">edt</subfield></datafield><datafield tag="776" ind1="1" ind2=" "><subfield code="z">9781119785804</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">9781119785804</subfield></datafield><datafield tag="966" ind1="4" ind2="0"><subfield code="l">DE-91</subfield><subfield code="p">ZDB-30-ORH</subfield><subfield code="q">TUM_PDA_ORH</subfield><subfield code="u">https://learning.oreilly.com/library/view/-/9781119785804/?ar</subfield><subfield code="m">X:ORHE</subfield><subfield code="x">Aggregator</subfield><subfield code="z">lizenzpflichtig</subfield><subfield code="3">Volltext</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">ZDB-30-ORH</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">ZDB-30-ORH</subfield></datafield><datafield tag="951" ind1=" " ind2=" "><subfield code="a">BO</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">ZDB-30-ORH</subfield></datafield><datafield tag="049" ind1=" " ind2=" "><subfield code="a">DE-91</subfield></datafield></record></collection> |
| id | ZDB-30-ORH-067581862 |
| illustrated | Not Illustrated |
| indexdate | 2025-01-17T11:20:38Z |
| institution | BVB |
| isbn | 9781119785873 1119785871 9781119785866 1119785863 9781119785859 1119785855 9781119785804 |
| language | English |
| open_access_boolean | |
| owner | DE-91 DE-BY-TUM |
| owner_facet | DE-91 DE-BY-TUM |
| physical | 1 Online-Ressource |
| psigel | ZDB-30-ORH TUM_PDA_ORH ZDB-30-ORH |
| publishDate | 2021 |
| publishDateSearch | 2021 |
| publishDateSort | 2021 |
| publisher | John Wiley & Sons, Inc. Scrivener Publishing LLC |
| record_format | marc |
| spelling | Machine learning approach for cloud data analytics in IoT edited by Sachi Nandan Mohanty, Jyotir Moy Chatterjee, Monika Mangla, Suneeta Satpathy, Sirisha Potluri 1st edition. Hoboken, NJ Beverly, MA John Wiley & Sons, Inc. 2021 Hoboken, NJ Beverly, MA Scrivener Publishing LLC 2021 1 Online-Ressource Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Includes bibliographical references and index. - Description based on online resource; title from digital title page (viewed on April 04, 2023) In this era of IoT, edge devices generate gigantic data during every fraction of a second. The main aim of these networks is to infer some meaningful information from the collected data. For the same, the huge data is transmitted to the cloud which is highly expensive and time-consuming. Hence, it needs to devise some efficient mechanism to handle this huge data, thus necessitating efficient data handling techniques. Sustainable computing paradigms like cloud and fog are expedient to capably handle the issues of performance, capabilities allied to storage and processing, maintenance, security, efficiency, integration, cost, energy and latency. However, it requires sophisticated analytics tools so as to address the queries in an optimized time. Hence, rigorous research is taking place in the direction of devising effective and efficient framework to garner utmost advantage. Machine learning has gained unmatched popularity for handling massive amounts of data and has applications in a wide variety of disciplines, including social media. Machine Learning Approach for Cloud Data Analytics in IoT details and integrates all aspects of IoT, cloud computing and data analytics from diversified perspectives. It reports on the state-of-the-art research and advanced topics, thereby bringing readers up to date and giving them a means to understand and explore the spectrum of applications of IoT, cloud computing and data analytics. Machine learning Cloud computing Internet of things Apprentissage automatique Infonuagique Internet des objets Mohanty, Sachi Nandan HerausgeberIn edt Chatterjee, Jyotir Moy HerausgeberIn edt Mangla, Monika HerausgeberIn edt Satpathy, Suneeta HerausgeberIn edt Potluri, Sirisha HerausgeberIn edt 9781119785804 Erscheint auch als Druck-Ausgabe 9781119785804 |
| spellingShingle | Machine learning approach for cloud data analytics in IoT Machine learning Cloud computing Internet of things Apprentissage automatique Infonuagique Internet des objets |
| title | Machine learning approach for cloud data analytics in IoT |
| title_auth | Machine learning approach for cloud data analytics in IoT |
| title_exact_search | Machine learning approach for cloud data analytics in IoT |
| title_full | Machine learning approach for cloud data analytics in IoT edited by Sachi Nandan Mohanty, Jyotir Moy Chatterjee, Monika Mangla, Suneeta Satpathy, Sirisha Potluri |
| title_fullStr | Machine learning approach for cloud data analytics in IoT edited by Sachi Nandan Mohanty, Jyotir Moy Chatterjee, Monika Mangla, Suneeta Satpathy, Sirisha Potluri |
| title_full_unstemmed | Machine learning approach for cloud data analytics in IoT edited by Sachi Nandan Mohanty, Jyotir Moy Chatterjee, Monika Mangla, Suneeta Satpathy, Sirisha Potluri |
| title_short | Machine learning approach for cloud data analytics in IoT |
| title_sort | machine learning approach for cloud data analytics in iot |
| topic | Machine learning Cloud computing Internet of things Apprentissage automatique Infonuagique Internet des objets |
| topic_facet | Machine learning Cloud computing Internet of things Apprentissage automatique Infonuagique Internet des objets |
| work_keys_str_mv | AT mohantysachinandan machinelearningapproachforclouddataanalyticsiniot AT chatterjeejyotirmoy machinelearningapproachforclouddataanalyticsiniot AT manglamonika machinelearningapproachforclouddataanalyticsiniot AT satpathysuneeta machinelearningapproachforclouddataanalyticsiniot AT potlurisirisha machinelearningapproachforclouddataanalyticsiniot |