Powered by OpenAIRE graph
Found an issue? Give us feedback
image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ ZENODOarrow_drop_down
image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
ZENODO
Part of book or chapter of book . 2025
License: CC BY
Data sources: ZENODO
ZENODO
Part of book or chapter of book . 2025
License: CC BY
Data sources: Datacite
ZENODO
Part of book or chapter of book . 2025
License: CC BY
Data sources: Datacite
versions View all 2 versions
addClaim

Exploring the Impact of Artificial Intelligence on Agriculture

Authors: Lalbiakzuali;

Exploring the Impact of Artificial Intelligence on Agriculture

Abstract

Incorporating Artificial Intelligence (AI) into agriculture heralds a profound revolution in agriculture, offering unsurpassed efficiency, sustainability, and productivity. The implementation of AI and Internet of Things (IoT) in agriculture is a ‘Smart farming’. Smart farming addresses many issues related to crop production as it allows monitoring the changes in climate factors, soil characteristics, soil moisture, etc. A certain set of technologies in the agriculture industry are increasingly crucial for the survival of various enterprises. Farmers obtain unprecedented insights into their crops and soil by leveraging advanced technologies like AI-driven precision farming. The real-time analysis of data from drones, various sensors and satellite imagery allows for accurate decision-making in areas like irrigation, fertilization and pest control. This targeted approach maximise yields while reducing resource consumption and environmental impact. Additionally, AI-powered invention and automation revolutionize labour-heavy tasks, such as sowing and harvesting, improving efficiency and decreasing reliance on manual labour. Predictive analytics and decision support systems enable the farmers to foresee potential challenges and make well-informed decisions, strengthening their ability to adapt to changing conditions. While there are hurdles like data privacy issues and technological infrastructure limitations, AI's transformative potential in revolutionizing farming practices and tackling global food security challenges is beyond doubt. With ongoing innovation and thoughtful implementation, AI has great potential to usher in a new era of smart and sustainable agriculture.

  • BIP!
    Impact byBIP!
    selected citations
    These citations are derived from selected sources.
    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    0
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Average
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Average
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Average
Powered by OpenAIRE graph
Found an issue? Give us feedback
selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average