Mission and Vision of Artificial Intelligence in Agriculture: Addressing Transparency, Scalability, and Security Issues, and Future Directions

Authors

  • A Rajesh kanna Department of Computer Science, Sri S. Ramasamy Naidu Memorial College, Sattur, 626203, Virudhunagar, Tamil Nadu, India
  • Thalari Chandrasekhar Department of Electronics, Government Science college, Hassan, Affiliated to University of Mysore, Hassan-573021, Karnataka, India
  • Thatiparthi Subramanya Prem Rajiv Kumar UG Scholars, Department of CSE, Narayana Engineering College, Nellore, 524004, A.P., India
  • Vavilla Rupesh UG Scholars, Department of CSE, Narayana Engineering College, Nellore, 524004, A.P., India
  • Cheemalamarri Venkata Naga Rugvidh UG Scholars, Department of CSE, Narayana Engineering College, Nellore, 524004, A.P., India
  • S. Chinnem Rama Mohan Department of CSE, Narayana Engineering College, Nellore, 524004, Andhra Pradesh, India

Keywords:

Artificial Intelligence, Precision Agriculture, Autonomous farming, Urban Agriculture, Supply chain optimization, Crop management, Weather Forecasting.

Abstract

AI-induced era is currently progressing. We are seeing phenomenal AI advancements. In front of our eyes, many things are becoming automated, and AI could significantly impact agriculture, the field that feeds and nourishes us every day. We envision various applications such as optimizing supply chains, weather predictions, adapting to climate change, automating physical processes with robotics, making precise decisions, saving resources as side effects of the economy get improved, and more competition in the field.It brings positive changes, yet there are specific challenges regarding scalability, security, the way it is adapted, improper AI training that can lead to disastrous results, educating farmers on this new technology, making more people aware of it, financial challenges, commercialization, etc.There are advantages and disadvantages, like higher computing costs, training time, and a lack of high-quality datasets. Considering all these challenges, adaptation takes time, money, patience, and effort. All these are present possibilities; there can be more possibilities yet to be discovered. We present them as future projections, and the sheer data doesn't make an AI model work; it's the algorithms that make AI predict, think, understand, and produce solutions that are compliant with the norms and ethical rules of conduct.

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Published

2024-09-24

How to Cite

A Rajesh kanna, Thalari Chandrasekhar, Thatiparthi Subramanya Prem Rajiv Kumar, Vavilla Rupesh, Cheemalamarri Venkata Naga Rugvidh, & S. Chinnem Rama Mohan. (2024). Mission and Vision of Artificial Intelligence in Agriculture: Addressing Transparency, Scalability, and Security Issues, and Future Directions. Journal of Computational Analysis and Applications (JoCAAA), 33(06), 85–96. Retrieved from https://eudoxuspress.com/index.php/pub/article/view/709

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