Advances and Hurdles in Using AI to Protect Our Water and Environment

Greg Howard
3rd February, 2024

Image Source: Natural Science News, 2024

Rapid economic growth has taken a significant toll on our natural environment, especially on the quality of our water. The careful management of water resources is critical for both the economy and the stability of society now and in the future. Maintaining economic development while preserving ecological balance is a complex challenge that requires the growth of both sectors to be interdependent. Deep learning (DL), a type of advanced artificial intelligence, has made waves in different fields such as self-driving cars, medical diagnostics, and speech recognition due to its ability to provide sophisticated data interpretations. Given its successful track record, deep learning is now being eyed for its potential in water resource management, environmental protection, and the study of water ecology. A comprehensive review has been conducted to explore deep learning applications dedicated to these water-related fields. To understand how DL can make a difference, the review first takes a step-by-step look at the concept and modeling process of deep learning. This includes preparatory stages like organizing data, selecting the right algorithms, and evaluating the performance of the models. The characteristics and performances of various deep learning algorithms are then scrutinized. The review considers the strengths and weaknesses of these algorithms by examining how they are structured and how they function. Based on this analysis, recommendations are made for selecting appropriate deep learning algorithms in different water science research scenarios. Moreover, the review ponders the future of deep learning as it applies to water science. It aims to guide researchers in tackling a broader array of water-related problems by providing references and contributing fresh perspectives on the smart evolution of water science. The findings of this review from the Ecological Environment Management and Assessment Center at Central South University of Forestry and Technology, are anticipated to serve as an informative resource for those seeking to address complex water issues using intelligent technology.

Environment Biotech Ecology

References

Main Study

1) Deep learning in water protection of resources, environment, and ecology: achievement and challenges.

Published 2nd February, 2024

https://doi.org/10.1007/s11356-024-31963-5

References

Main Study

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