Innovations in machine learning and IoT for water management:
Water, our planet's life force, faces multiple challenges in the 21st century, including surging global demand, shifting climate patterns, and the urgent need for sustainable management. Guidance, knowledge, and hope is sharply needed in academia and technology industries, and Innovations in Ma...
Gespeichert in:
| Weitere Verfasser: | , , , , |
|---|---|
| Format: | Elektronisch E-Book |
| Sprache: | English |
| Veröffentlicht: |
Hershey, Pennsylvania
IGI Global
[2024]
|
| Schlagworte: | |
| Online-Zugang: | DE-91 DE-898 Volltext |
| Zusammenfassung: | Water, our planet's life force, faces multiple challenges in the 21st century, including surging global demand, shifting climate patterns, and the urgent need for sustainable management. Guidance, knowledge, and hope is sharply needed in academia and technology industries, and Innovations in Machine Learning and IoT for Water Management is a formidable resource to provide these necessities. This book delves into the dynamic synergy of Artificial Intelligence (AI), Machine Learning (ML), and the Internet of Things (IoT), ushering in a new era of water resource stewardship.This book embarks on a journey through the frontiers of AI and IoT, unveiling their transformative impact on water management. From the vantage point of satellite imagery analysis, it scrutinizes the Earth's vital signs, unlocking crucial insights into water resources. It chronicles the rise of AI-powered predictive analytics, a revolutionary force propelling precision water usage and conservation. This book explains how IoT can be an effective tool to increase intelligence of our water systems. The book meticulously navigates through domains as diverse as aquifer monitoring, hydropower generation optimization, and predictive analytics for water consumption. This book caters to a diverse audience, from water management experts and environmental scientists to data science aficionados and IoT enthusiasts. Engineers seeking to reimagine the future of water systems, technology enthusiasts eager to delve into AI's potential, and individuals impassioned by preserving water will all find a well-needed resource in these pages. |
| Beschreibung: | 1 Online-Ressource (312 Seiten) |
| ISBN: | 9798369311950 |
| DOI: | 10.4018/979-8-3693-1194-3 |
Internformat
MARC
| LEADER | 00000nmm a2200000zc 4500 | ||
|---|---|---|---|
| 001 | BV049458564 | ||
| 003 | DE-604 | ||
| 007 | cr|uuu---uuuuu | ||
| 008 | 231208s2024 |||| o||u| ||||||eng d | ||
| 020 | |a 9798369311950 |9 979-83-69311-95-0 | ||
| 024 | 7 | |a 10.4018/979-8-3693-1194-3 |2 doi | |
| 035 | |a (ZDB-98-IGB)00326935 | ||
| 035 | |a (OCoLC)1414554405 | ||
| 035 | |a (DE-599)BVBBV049458564 | ||
| 040 | |a DE-604 |b ger |e rda | ||
| 041 | 0 | |a eng | |
| 049 | |a DE-91 |a DE-898 | ||
| 082 | 0 | |a 333.9100285/631 | |
| 084 | |a WIR 523 |2 stub | ||
| 084 | |a DAT 000 |2 stub | ||
| 245 | 1 | 0 | |a Innovations in machine learning and IoT for water management |c Abhishek Kumar, Arun Lal Srivastav, Ashutosh Kumar Dubey, Vishal Dutt, Narayan Vyas, editor |
| 246 | 1 | 3 | |a Innovations in machine learning and Internet of things for water management |
| 264 | 1 | |a Hershey, Pennsylvania |b IGI Global |c [2024] | |
| 300 | |a 1 Online-Ressource (312 Seiten) | ||
| 336 | |b txt |2 rdacontent | ||
| 337 | |b c |2 rdamedia | ||
| 338 | |b cr |2 rdacarrier | ||
| 520 | |a Water, our planet's life force, faces multiple challenges in the 21st century, including surging global demand, shifting climate patterns, and the urgent need for sustainable management. Guidance, knowledge, and hope is sharply needed in academia and technology industries, and Innovations in Machine Learning and IoT for Water Management is a formidable resource to provide these necessities. This book delves into the dynamic synergy of Artificial Intelligence (AI), Machine Learning (ML), and the Internet of Things (IoT), ushering in a new era of water resource stewardship.This book embarks on a journey through the frontiers of AI and IoT, unveiling their transformative impact on water management. From the vantage point of satellite imagery analysis, it scrutinizes the Earth's vital signs, unlocking crucial insights into water resources. It chronicles the rise of AI-powered predictive analytics, a revolutionary force propelling precision water usage and conservation. This book explains how IoT can be an effective tool to increase intelligence of our water systems. The book meticulously navigates through domains as diverse as aquifer monitoring, hydropower generation optimization, and predictive analytics for water consumption. This book caters to a diverse audience, from water management experts and environmental scientists to data science aficionados and IoT enthusiasts. Engineers seeking to reimagine the future of water systems, technology enthusiasts eager to delve into AI's potential, and individuals impassioned by preserving water will all find a well-needed resource in these pages. | ||
| 650 | 4 | |a Water-supply |x Management |x Data processing | |
| 650 | 4 | |a Water quality management |x Data processing | |
| 650 | 4 | |a Internet of things | |
| 650 | 4 | |a Machine learning | |
| 700 | 1 | |a Vyas, Narayan |d 1998- |4 edt | |
| 700 | 1 | |a Dutt, Vishal |4 edt | |
| 700 | 1 | |a Dubey, Ashutosh Kumar |4 edt | |
| 700 | 1 | |a Srivastav, Arun Lal |d 1984- |4 edt | |
| 700 | 1 | |a Kumar, Abhishek |d 1989- |4 edt | |
| 776 | 0 | 8 | |i Erscheint auch als |n Druck-Ausgabe |z 9798369311943 |
| 856 | 4 | 0 | |u https://doi.org/10.4018/979-8-3693-1194-3 |x Verlag |z URL des Erstveröffentlichers |3 Volltext |
| 912 | |a ZDB-98-IGB | ||
| 943 | 1 | |a oai:aleph.bib-bvb.de:BVB01-034804329 | |
| 966 | e | |u https://doi.org/10.4018/979-8-3693-1194-3 |l DE-91 |p ZDB-98-IGB |q TUM_Paketkauf_2023 |x Verlag |3 Volltext | |
| 966 | e | |u https://doi.org/10.4018/979-8-3693-1194-3 |l DE-898 |p ZDB-98-IGB |q FHR_PDA_IGB |x Verlag |3 Volltext | |
Datensatz im Suchindex
| _version_ | 1808229068953354240 |
|---|---|
| adam_text | |
| adam_txt | |
| any_adam_object | |
| any_adam_object_boolean | |
| author2 | Vyas, Narayan 1998- Dutt, Vishal Dubey, Ashutosh Kumar Srivastav, Arun Lal 1984- Kumar, Abhishek 1989- |
| author2_role | edt edt edt edt edt |
| author2_variant | n v nv v d vd a k d ak akd a l s al als a k ak |
| author_facet | Vyas, Narayan 1998- Dutt, Vishal Dubey, Ashutosh Kumar Srivastav, Arun Lal 1984- Kumar, Abhishek 1989- |
| building | Verbundindex |
| bvnumber | BV049458564 |
| classification_tum | WIR 523 DAT 000 |
| collection | ZDB-98-IGB |
| ctrlnum | (ZDB-98-IGB)00326935 (OCoLC)1414554405 (DE-599)BVBBV049458564 |
| dewey-full | 333.9100285/631 |
| dewey-hundreds | 300 - Social sciences |
| dewey-ones | 333 - Economics of land and energy |
| dewey-raw | 333.9100285/631 |
| dewey-search | 333.9100285/631 |
| dewey-sort | 3333.9100285 3631 |
| dewey-tens | 330 - Economics |
| discipline | Informatik Wirtschaftswissenschaften |
| discipline_str_mv | Informatik Wirtschaftswissenschaften |
| doi_str_mv | 10.4018/979-8-3693-1194-3 |
| format | Electronic eBook |
| fullrecord | <?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>00000nmm a2200000zc 4500</leader><controlfield tag="001">BV049458564</controlfield><controlfield tag="003">DE-604</controlfield><controlfield tag="007">cr|uuu---uuuuu</controlfield><controlfield tag="008">231208s2024 |||| o||u| ||||||eng d</controlfield><datafield tag="020" ind1=" " ind2=" "><subfield code="a">9798369311950</subfield><subfield code="9">979-83-69311-95-0</subfield></datafield><datafield tag="024" ind1="7" ind2=" "><subfield code="a">10.4018/979-8-3693-1194-3</subfield><subfield code="2">doi</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(ZDB-98-IGB)00326935</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(OCoLC)1414554405</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-599)BVBBV049458564</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-898</subfield></datafield><datafield tag="082" ind1="0" ind2=" "><subfield code="a">333.9100285/631</subfield></datafield><datafield tag="084" ind1=" " ind2=" "><subfield code="a">WIR 523</subfield><subfield code="2">stub</subfield></datafield><datafield tag="084" ind1=" " ind2=" "><subfield code="a">DAT 000</subfield><subfield code="2">stub</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">Innovations in machine learning and IoT for water management</subfield><subfield code="c">Abhishek Kumar, Arun Lal Srivastav, Ashutosh Kumar Dubey, Vishal Dutt, Narayan Vyas, editor</subfield></datafield><datafield tag="246" ind1="1" ind2="3"><subfield code="a">Innovations in machine learning and Internet of things for water management</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="a">Hershey, Pennsylvania</subfield><subfield code="b">IGI Global</subfield><subfield code="c">[2024]</subfield></datafield><datafield tag="300" ind1=" " ind2=" "><subfield code="a">1 Online-Ressource (312 Seiten)</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="520" ind1=" " ind2=" "><subfield code="a">Water, our planet's life force, faces multiple challenges in the 21st century, including surging global demand, shifting climate patterns, and the urgent need for sustainable management. Guidance, knowledge, and hope is sharply needed in academia and technology industries, and Innovations in Machine Learning and IoT for Water Management is a formidable resource to provide these necessities. This book delves into the dynamic synergy of Artificial Intelligence (AI), Machine Learning (ML), and the Internet of Things (IoT), ushering in a new era of water resource stewardship.This book embarks on a journey through the frontiers of AI and IoT, unveiling their transformative impact on water management. From the vantage point of satellite imagery analysis, it scrutinizes the Earth's vital signs, unlocking crucial insights into water resources. It chronicles the rise of AI-powered predictive analytics, a revolutionary force propelling precision water usage and conservation. This book explains how IoT can be an effective tool to increase intelligence of our water systems. The book meticulously navigates through domains as diverse as aquifer monitoring, hydropower generation optimization, and predictive analytics for water consumption. This book caters to a diverse audience, from water management experts and environmental scientists to data science aficionados and IoT enthusiasts. Engineers seeking to reimagine the future of water systems, technology enthusiasts eager to delve into AI's potential, and individuals impassioned by preserving water will all find a well-needed resource in these pages.</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Water-supply</subfield><subfield code="x">Management</subfield><subfield code="x">Data processing</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Water quality management</subfield><subfield code="x">Data processing</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">Vyas, Narayan</subfield><subfield code="d">1998-</subfield><subfield code="4">edt</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Dutt, Vishal</subfield><subfield code="4">edt</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Dubey, Ashutosh Kumar</subfield><subfield code="4">edt</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Srivastav, Arun Lal</subfield><subfield code="d">1984-</subfield><subfield code="4">edt</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Kumar, Abhishek</subfield><subfield code="d">1989-</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">9798369311943</subfield></datafield><datafield tag="856" ind1="4" ind2="0"><subfield code="u">https://doi.org/10.4018/979-8-3693-1194-3</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-98-IGB</subfield></datafield><datafield tag="943" ind1="1" ind2=" "><subfield code="a">oai:aleph.bib-bvb.de:BVB01-034804329</subfield></datafield><datafield tag="966" ind1="e" ind2=" "><subfield code="u">https://doi.org/10.4018/979-8-3693-1194-3</subfield><subfield code="l">DE-91</subfield><subfield code="p">ZDB-98-IGB</subfield><subfield code="q">TUM_Paketkauf_2023</subfield><subfield code="x">Verlag</subfield><subfield code="3">Volltext</subfield></datafield><datafield tag="966" ind1="e" ind2=" "><subfield code="u">https://doi.org/10.4018/979-8-3693-1194-3</subfield><subfield code="l">DE-898</subfield><subfield code="p">ZDB-98-IGB</subfield><subfield code="q">FHR_PDA_IGB</subfield><subfield code="x">Verlag</subfield><subfield code="3">Volltext</subfield></datafield></record></collection> |
| id | DE-604.BV049458564 |
| illustrated | Not Illustrated |
| index_date | 2024-07-03T23:14:18Z |
| indexdate | 2024-08-24T01:07:01Z |
| institution | BVB |
| isbn | 9798369311950 |
| language | English |
| oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-034804329 |
| oclc_num | 1414554405 |
| open_access_boolean | |
| owner | DE-91 DE-BY-TUM DE-898 DE-BY-UBR |
| owner_facet | DE-91 DE-BY-TUM DE-898 DE-BY-UBR |
| physical | 1 Online-Ressource (312 Seiten) |
| psigel | ZDB-98-IGB ZDB-98-IGB TUM_Paketkauf_2023 ZDB-98-IGB FHR_PDA_IGB |
| publishDate | 2024 |
| publishDateSearch | 2024 |
| publishDateSort | 2024 |
| publisher | IGI Global |
| record_format | marc |
| spelling | Innovations in machine learning and IoT for water management Abhishek Kumar, Arun Lal Srivastav, Ashutosh Kumar Dubey, Vishal Dutt, Narayan Vyas, editor Innovations in machine learning and Internet of things for water management Hershey, Pennsylvania IGI Global [2024] 1 Online-Ressource (312 Seiten) txt rdacontent c rdamedia cr rdacarrier Water, our planet's life force, faces multiple challenges in the 21st century, including surging global demand, shifting climate patterns, and the urgent need for sustainable management. Guidance, knowledge, and hope is sharply needed in academia and technology industries, and Innovations in Machine Learning and IoT for Water Management is a formidable resource to provide these necessities. This book delves into the dynamic synergy of Artificial Intelligence (AI), Machine Learning (ML), and the Internet of Things (IoT), ushering in a new era of water resource stewardship.This book embarks on a journey through the frontiers of AI and IoT, unveiling their transformative impact on water management. From the vantage point of satellite imagery analysis, it scrutinizes the Earth's vital signs, unlocking crucial insights into water resources. It chronicles the rise of AI-powered predictive analytics, a revolutionary force propelling precision water usage and conservation. This book explains how IoT can be an effective tool to increase intelligence of our water systems. The book meticulously navigates through domains as diverse as aquifer monitoring, hydropower generation optimization, and predictive analytics for water consumption. This book caters to a diverse audience, from water management experts and environmental scientists to data science aficionados and IoT enthusiasts. Engineers seeking to reimagine the future of water systems, technology enthusiasts eager to delve into AI's potential, and individuals impassioned by preserving water will all find a well-needed resource in these pages. Water-supply Management Data processing Water quality management Data processing Internet of things Machine learning Vyas, Narayan 1998- edt Dutt, Vishal edt Dubey, Ashutosh Kumar edt Srivastav, Arun Lal 1984- edt Kumar, Abhishek 1989- edt Erscheint auch als Druck-Ausgabe 9798369311943 https://doi.org/10.4018/979-8-3693-1194-3 Verlag URL des Erstveröffentlichers Volltext |
| spellingShingle | Innovations in machine learning and IoT for water management Water-supply Management Data processing Water quality management Data processing Internet of things Machine learning |
| title | Innovations in machine learning and IoT for water management |
| title_alt | Innovations in machine learning and Internet of things for water management |
| title_auth | Innovations in machine learning and IoT for water management |
| title_exact_search | Innovations in machine learning and IoT for water management |
| title_exact_search_txtP | Innovations in machine learning and IoT for water management |
| title_full | Innovations in machine learning and IoT for water management Abhishek Kumar, Arun Lal Srivastav, Ashutosh Kumar Dubey, Vishal Dutt, Narayan Vyas, editor |
| title_fullStr | Innovations in machine learning and IoT for water management Abhishek Kumar, Arun Lal Srivastav, Ashutosh Kumar Dubey, Vishal Dutt, Narayan Vyas, editor |
| title_full_unstemmed | Innovations in machine learning and IoT for water management Abhishek Kumar, Arun Lal Srivastav, Ashutosh Kumar Dubey, Vishal Dutt, Narayan Vyas, editor |
| title_short | Innovations in machine learning and IoT for water management |
| title_sort | innovations in machine learning and iot for water management |
| topic | Water-supply Management Data processing Water quality management Data processing Internet of things Machine learning |
| topic_facet | Water-supply Management Data processing Water quality management Data processing Internet of things Machine learning |
| url | https://doi.org/10.4018/979-8-3693-1194-3 |
| work_keys_str_mv | AT vyasnarayan innovationsinmachinelearningandiotforwatermanagement AT duttvishal innovationsinmachinelearningandiotforwatermanagement AT dubeyashutoshkumar innovationsinmachinelearningandiotforwatermanagement AT srivastavarunlal innovationsinmachinelearningandiotforwatermanagement AT kumarabhishek innovationsinmachinelearningandiotforwatermanagement AT vyasnarayan innovationsinmachinelearningandinternetofthingsforwatermanagement AT duttvishal innovationsinmachinelearningandinternetofthingsforwatermanagement AT dubeyashutoshkumar innovationsinmachinelearningandinternetofthingsforwatermanagement AT srivastavarunlal innovationsinmachinelearningandinternetofthingsforwatermanagement AT kumarabhishek innovationsinmachinelearningandinternetofthingsforwatermanagement |