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Open Access Journal Article

AI-Driven Precision Agriculture Solutions

by David Smith 1,*
1
David Smith
*
Author to whom correspondence should be addressed.
ISTI  2020, 7; 2(1), 7; https://doi.org/10.69610/j.isti.20200322
Received: 24 January 2020 / Accepted: 14 February 2020 / Published Online: 22 March 2020
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Abstract

The rapid advancement of artificial intelligence (AI) has opened up new horizons in various fields, and agriculture is no exception. This abstract focuses on the integration of AI technologies in precision agriculture, a practice that aims to optimize crop production by tailoring farming techniques to specific environmental and soil conditions. The paper explores the potential benefits of AI-driven precision agriculture solutions, including improved crop yields, reduced environmental impact, and enhanced economic efficiency. It examines how AI algorithms can analyze vast amounts of data, such as satellite imagery, soil sensors, and weather forecasts, to make informed decisions on irrigation, fertilization, and pest control. Additionally, the abstract discusses the challenges associated with implementing AI in precision agriculture, such as data privacy concerns, high initial investment costs, and the need for skilled labor. The study concludes that while AI-driven precision agriculture offers significant advantages, it requires careful planning, policy support, and continuous technological innovation to achieve its full potential.

Keywords: Artificial Intelligence, Precision Agriculture, Crop Yields, Data Analysis, Environmental Efficiency.;
Copyright: © 2020 by Smith. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY) (Creative Commons Attribution 4.0 International License). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

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ACS Style
Smith, D. AI-Driven Precision Agriculture Solutions. Information Sciences and Technological Innovations, 2020, 2, 7. https://doi.org/10.69610/j.isti.20200322
AMA Style
Smith D. AI-Driven Precision Agriculture Solutions. Information Sciences and Technological Innovations; 2020, 2(1):7. https://doi.org/10.69610/j.isti.20200322
Chicago/Turabian Style
Smith, David 2020. "AI-Driven Precision Agriculture Solutions" Information Sciences and Technological Innovations 2, no.1:7. https://doi.org/10.69610/j.isti.20200322
APA style
Smith, D. (2020). AI-Driven Precision Agriculture Solutions. Information Sciences and Technological Innovations, 2(1), 7. https://doi.org/10.69610/j.isti.20200322

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References

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