Reshaping environmental science through machine learning and IoT:
In the face of escalating environmental challenges such as climate change, air and water pollution, and natural disasters, traditional approaches to understanding and addressing these issues have yet to be proven sufficient. Academic scholars are compelled to seek innovative solutions that marry dig...
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| Weitere Verfasser: | , , , |
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| Format: | Elektronisch E-Book |
| Sprache: | English |
| Veröffentlicht: |
Hershey, Pennsylvania
IGI Global
2024
|
| Schlagworte: | |
| Online-Zugang: | DE-91 DE-898 DE-1050 Volltext |
| Zusammenfassung: | In the face of escalating environmental challenges such as climate change, air and water pollution, and natural disasters, traditional approaches to understanding and addressing these issues have yet to be proven sufficient. Academic scholars are compelled to seek innovative solutions that marry digital intelligence and natural ecosystems. Reshaping Environmental Science Through Machine Learning and IoT serves as a comprehensive exploration into the transformative potential of Machine Learning (ML) and the Internet of Things (IoT) to address critical environmental challenges.The book establishes a robust foundation in ML and IoT, explaining their relevance to environmental science. As the narrative unfolds, it delves into diverse applications, providing theoretical insights alongside practical knowledge. From interpreting weather patterns to predicting air and water quality, the book navigates through the intricate web of environmental complexities. Notably, it unveils approaches to disaster management, waste sorting, and climate change monitoring, showcasing the symbiotic relationship between digital intelligence and natural ecosystems. This book is ideal for audiences from students and researchers to data scientists and disaster management professionals with a nuanced understanding of IoT, ML, and Artificial Intelligence (AI). |
| Beschreibung: | 1 Online-Ressource (438 Seiten) |
| ISBN: | 9798369323526 |
| DOI: | 10.4018/979-8-3693-2351-9 |
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| 520 | |a In the face of escalating environmental challenges such as climate change, air and water pollution, and natural disasters, traditional approaches to understanding and addressing these issues have yet to be proven sufficient. Academic scholars are compelled to seek innovative solutions that marry digital intelligence and natural ecosystems. Reshaping Environmental Science Through Machine Learning and IoT serves as a comprehensive exploration into the transformative potential of Machine Learning (ML) and the Internet of Things (IoT) to address critical environmental challenges.The book establishes a robust foundation in ML and IoT, explaining their relevance to environmental science. As the narrative unfolds, it delves into diverse applications, providing theoretical insights alongside practical knowledge. From interpreting weather patterns to predicting air and water quality, the book navigates through the intricate web of environmental complexities. Notably, it unveils approaches to disaster management, waste sorting, and climate change monitoring, showcasing the symbiotic relationship between digital intelligence and natural ecosystems. This book is ideal for audiences from students and researchers to data scientists and disaster management professionals with a nuanced understanding of IoT, ML, and Artificial Intelligence (AI). | ||
| 650 | 4 | |a Environmental sciences |x Data processing | |
| 650 | 4 | |a Environmental sciences |x Remote sensing | |
| 700 | 1 | |a Gupta, Rajeev Kumar |d 1984- |4 edt | |
| 700 | 1 | |a Jain, Arti |d 1977- |4 edt | |
| 700 | 1 | |a Pateriya, Rajesh Kumar |d 1969- |4 edt | |
| 700 | 1 | |a Wang, John |d 1955- |4 edt | |
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| discipline | Geologie / Paläontologie |
| doi_str_mv | 10.4018/979-8-3693-2351-9 |
| format | Electronic eBook |
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| id | DE-604.BV049735936 |
| illustrated | Not Illustrated |
| indexdate | 2024-12-17T19:01:36Z |
| institution | BVB |
| isbn | 9798369323526 |
| language | English |
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| oclc_num | 1443589656 |
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| owner_facet | DE-91 DE-BY-TUM DE-898 DE-BY-UBR DE-1050 |
| physical | 1 Online-Ressource (438 Seiten) |
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| publishDate | 2024 |
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| publisher | IGI Global |
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| spelling | Reshaping environmental science through machine learning and IoT Rajeev Kumar Gupta, Arti Jain, John Wang, Rajesh Kumar Pateriya, editor Reshaping environmental science through machine learning and Internet of things Hershey, Pennsylvania IGI Global 2024 1 Online-Ressource (438 Seiten) txt rdacontent c rdamedia cr rdacarrier In the face of escalating environmental challenges such as climate change, air and water pollution, and natural disasters, traditional approaches to understanding and addressing these issues have yet to be proven sufficient. Academic scholars are compelled to seek innovative solutions that marry digital intelligence and natural ecosystems. Reshaping Environmental Science Through Machine Learning and IoT serves as a comprehensive exploration into the transformative potential of Machine Learning (ML) and the Internet of Things (IoT) to address critical environmental challenges.The book establishes a robust foundation in ML and IoT, explaining their relevance to environmental science. As the narrative unfolds, it delves into diverse applications, providing theoretical insights alongside practical knowledge. From interpreting weather patterns to predicting air and water quality, the book navigates through the intricate web of environmental complexities. Notably, it unveils approaches to disaster management, waste sorting, and climate change monitoring, showcasing the symbiotic relationship between digital intelligence and natural ecosystems. This book is ideal for audiences from students and researchers to data scientists and disaster management professionals with a nuanced understanding of IoT, ML, and Artificial Intelligence (AI). Environmental sciences Data processing Environmental sciences Remote sensing Gupta, Rajeev Kumar 1984- edt Jain, Arti 1977- edt Pateriya, Rajesh Kumar 1969- edt Wang, John 1955- edt Erscheint auch als Druck-Ausgabe 9798369323519 https://doi.org/10.4018/979-8-3693-2351-9 Verlag URL des Erstveröffentlichers Volltext |
| spellingShingle | Reshaping environmental science through machine learning and IoT Environmental sciences Data processing Environmental sciences Remote sensing |
| title | Reshaping environmental science through machine learning and IoT |
| title_alt | Reshaping environmental science through machine learning and Internet of things |
| title_auth | Reshaping environmental science through machine learning and IoT |
| title_exact_search | Reshaping environmental science through machine learning and IoT |
| title_full | Reshaping environmental science through machine learning and IoT Rajeev Kumar Gupta, Arti Jain, John Wang, Rajesh Kumar Pateriya, editor |
| title_fullStr | Reshaping environmental science through machine learning and IoT Rajeev Kumar Gupta, Arti Jain, John Wang, Rajesh Kumar Pateriya, editor |
| title_full_unstemmed | Reshaping environmental science through machine learning and IoT Rajeev Kumar Gupta, Arti Jain, John Wang, Rajesh Kumar Pateriya, editor |
| title_short | Reshaping environmental science through machine learning and IoT |
| title_sort | reshaping environmental science through machine learning and iot |
| topic | Environmental sciences Data processing Environmental sciences Remote sensing |
| topic_facet | Environmental sciences Data processing Environmental sciences Remote sensing |
| url | https://doi.org/10.4018/979-8-3693-2351-9 |
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