Artificial intelligent-based water and soil management

Elbeltagi, A; Kushwaha, NL; Srivastava, A; Zoof, AT

Artificial intelligent-based water and soil management

Elbeltagi, A Kushwaha, NL Srivastava, A

Zoof, AT

Permalink

Publisher:: Elsevier
Publication Type:: Chapter
Citation:: Deep Learning for Sustainable Agriculture, 2022, pp. 129-142
Issue Date:: 2022-01-01

Closed Access

	Filename	Description	Size
	20511034_10283345220005671.pdf	Published version	348.37 kB	Adobe PDF	View/Open

Copyright Clearance Process

Recently Added
In Progress
Closed Access

This item is closed access and not available.

Full metadata record

Field	Value	Language
dc.contributor.author	Elbeltagi, A
dc.contributor.author	Kushwaha, NL
dc.contributor.author	Srivastava, A https://orcid.org/0000-0002-3963-265X
dc.contributor.author	Zoof, AT
dc.date.accessioned	2023-03-27T21:45:03Z
dc.date.available	2023-03-27T21:45:03Z
dc.date.issued	2022-01-01
dc.identifier.citation	Deep Learning for Sustainable Agriculture, 2022, pp. 129-142
dc.identifier.isbn	9780323903622
dc.identifier.uri	http://hdl.handle.net/10453/168619
dc.description.abstract	Artificial intelligence (AI) has revolutionized information technology and shaped the way we live. AI is a computational model that allows computers to learn from data and approximate solutions for complex functions. Due to their flexibility and robustness, AI has been widely applied in large scale fields ranging from robotics to airplane flight control. This chapter discusses the advances in all aspect of AI applied in several issues, such as hydrology, agronomy, meteorology, education, healthcare, action, and more. It focuses specifically on various AI applications related to water and soil management and states that AI achieves high performance, accuracy, and correlation with low statistical errors as a rapid decision tool under changing climate conditions. Brief introductions of AI with their adaptability to agricultural water and soil management are also interpreted. Furthermore, this chapter illustrates how the AI tool will help agricultural decision makers and water and soil managers achieve agricultural sustainability.
dc.language	en
dc.publisher	Elsevier
dc.relation.ispartof	Deep Learning for Sustainable Agriculture
dc.relation.isbasedon	10.1016/B978-0-323-85214-2.00008-2
dc.rights	info:eu-repo/semantics/closedAccess
dc.title	Artificial intelligent-based water and soil management
dc.type	Chapter
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Science
pubs.organisational-group	/University of Technology Sydney/Faculty of Science/School of Life Sciences
utslib.copyright.status	closed_access	*
dc.date.updated	2023-03-27T21:45:01Z
pubs.publication-status	Published

Abstract:

Artificial intelligence (AI) has revolutionized information technology and shaped the way we live. AI is a computational model that allows computers to learn from data and approximate solutions for complex functions. Due to their flexibility and robustness, AI has been widely applied in large scale fields ranging from robotics to airplane flight control. This chapter discusses the advances in all aspect of AI applied in several issues, such as hydrology, agronomy, meteorology, education, healthcare, action, and more. It focuses specifically on various AI applications related to water and soil management and states that AI achieves high performance, accuracy, and correlation with low statistical errors as a rapid decision tool under changing climate conditions. Brief introductions of AI with their adaptability to agricultural water and soil management are also interpreted. Furthermore, this chapter illustrates how the AI tool will help agricultural decision makers and water and soil managers achieve agricultural sustainability.

Please use this identifier to cite or link to this item:

http://hdl.handle.net/10453/168619