AI-Powered Approaches to Environmental Challenges: Trends, Benefits, and Limitations

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Year : August 20, 2024 at 1:42 pm | [if 1553 equals=””] Volume :14 [else] Volume :14[/if 1553] | [if 424 equals=”Regular Issue”]Issue[/if 424][if 424 equals=”Special Issue”]Special Issue[/if 424] [if 424 equals=”Conference”][/if 424] : 02 | Page : 1-8

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T. P. Sulakshna, T. P. Sulakshna,

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  1. Former Assistant Professor (Ad hoc), Department of Civil Engineering,, Former Professor, Department of Mechanical Engineering, NSS college of Engineering,, NSS college of Engineering, Palakkad,, Palakkad, India, India

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Abstract

nDynamic and unpredictable characteristics of environmental processes create challenges in their management and regulation. Artificial intelligence (AI) offers a powerful solution for addressing these complexities.AI tools have become more and more popular across a range of fields and research domains due to their efficient development and rapid growth. We analyse key trends in AI applications, including predictive analytics for climate modelling, automated monitoring of biodiversity, and smart resource management. The benefits of these technologies, such as enhanced efficiency, real-time data analysis, and improved decision-making, are discussed in detail. However, the study also identifies significant limitations, including data quality issues, algorithmic bias, and the need for interdisciplinary collaboration. By providing a comprehensive overview of the current landscape, this article aims to highlight both the potential and the challenges of leveraging AI to create sustainable solutions for a healthier planet. Over the past few years, there has been an exponential increase in interest in using AI in the environmental discipline. This paper aims to review the most recent uses of artificial intelligence (AI) techniques in the environmental field, the prospects they offer, and their benefits and drawbacks.

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Keywords: Environment, Artificial Intelligence, Subject classification codes, Environment, Artificial Intelligence

n[if 424 equals=”Regular Issue”][This article belongs to Journal of Energy, Environment & Carbon Credits(joeecc)]

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[/if 424][if 424 equals=”Special Issue”][This article belongs to Special Issue under section in Journal of Energy, Environment & Carbon Credits(joeecc)][/if 424][if 424 equals=”Conference”]This article belongs to Conference [/if 424]

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How to cite this article: T. P. Sulakshna, T. P. Sulakshna. AI-Powered Approaches to Environmental Challenges: Trends, Benefits, and Limitations. Journal of Energy, Environment & Carbon Credits. August 20, 2024; 14(02):1-8.

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How to cite this URL: T. P. Sulakshna, T. P. Sulakshna. AI-Powered Approaches to Environmental Challenges: Trends, Benefits, and Limitations. Journal of Energy, Environment & Carbon Credits. August 20, 2024; 14(02):1-8. Available from: https://journals.stmjournals.com/joeecc/article=August 20, 2024/view=0

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[if 424 not_equal=””]Regular Issue[else]Published[/if 424] Subscription Review Article

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Volume 14
[if 424 equals=”Regular Issue”]Issue[/if 424][if 424 equals=”Special Issue”]Special Issue[/if 424] [if 424 equals=”Conference”][/if 424] 02
Received July 11, 2024
Accepted July 18, 2024
Published August 20, 2024

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