Agricultural informatics : automation using the IoT and machine learning / edited by Amitava Choudhury, Arindam Biswas, Manish Prateek, Amlan Chakrabarti

"The emergence of automation in agriculture has become an important issue for every country. The world population is increasing at a very fast rate, and along with this increase in population the need for food is also increasing at a brisk pace. Traditional methods used by farmers are no longer sufficient to serve this increasing demand, resulting in the intensified use of harmful pesticides. This in turn has had a profound effect on agricultural practices, which in the end can render the land barren. This book discusses the different automation practices, including the internet of things (IoT), wireless communications, machine learning, artificial intelligence, and deep learning, currently being employed to address this problem. There are some areas of concern in the field of agriculture, such as crop disease, lack of storage, weed and water management, pesticide control, and lack of irrigation, all of which can be solved using the different techniques mentioned above".

Medienart:

E-Book

Erscheinungsjahr:

2021

Erschienen:

Hoboken, NJ: Wiley ; 2021

Beverly, MA: Scrivener Publishing ; 2021

Weitere Ausgaben:

Erscheint auch als Druck-Ausgabe: Agricultural informatics

Reihe:

Advances in learning analytics for intelligent cloud-IoT systems

Sprache:

Englisch

Beteiligte Personen:

Choudhury, Amitava [HerausgeberIn]
Biswas, Arindam, 1984- [HerausgeberIn]
Prattek, Manish [HerausgeberIn]
Chakrabarti, Amlan [HerausgeberIn]

Links:

onlinelibrary.wiley.com [lizenzpflichtig]
doi.org

ISBN:

978-1-119-76923-1

Themen:

Agrarinformatik
Agricultural informatics
Agriculture
Automation
Internet der Dinge
Internet of things
Landwirtschaft
Machine learning
Maschinelles Lernen

Anmerkungen:

Includes bibliographical references and index

Umfang:

1 Online-Ressource (xviii, 275 Seiten) ; Illustrationen, Diagramme

doi:

10.1002/9781119769231

funding:

Förderinstitution / Projekttitel:

PPN (Katalog-ID):

1760376388