UK Researchers Trained A Computer Algorithm Using Machine Learning And Ecoacoustic Indices To Identify The Health Of Coral Reef Using The Sound

This Article is written as a summay by Marktechpost Staff based on the research paper 'Enhancing automated analysis of marine soundscapes using ecoacoustic indices and machine learning'. All Credit For This Research Goes To The Researchers of This Project. Check out the paper, blog post.

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Using ecoacoustic indices and machine learning, improve automated analysis of maritime soundscapes. Marine habitat ecological monitoring is critical for understanding these ecosystems and accurately quantifying the benefits of conservation and restoration programs in our oceans.

According to new research, artificial intelligence (AI) can track the health of coral reefs by learning the song of the reef. Professionals definitely must do rigorous analyses to determine reef health based on sound recordings because coral reefs have a complex soundscape.

Scientists from the University of Exeter created a computer system to recognize the difference between healthy and damaged reef recordings.

Source: https://www.sciencedirect.com/science/article/pii/S1470160X22004575

This was used to keep track of the team’s progress on reef restoration projects.

Because coral reefs are under threat from various factors, including climate change, it’s critical to track their health and the performance of conservation efforts; one key challenge is that visual and audio reef surveys are typically labor-intensive. Visual surveys are also hampered by the fact that many reef species hide or are active at night, and the richness of reef sounds makes individual recordings difficult to determine reef health.

Researchers used machine learning to solve that problem, to see if a computer could learn the song of the reef. Their findings suggest that a computer can detect patterns that a human ear cannot. It can inform us how the reef is doing more quickly and correctly.

Other species, such as coral reef fish, make a wide range of noises. Many of these screams have no recognized significance, but the new AI system can distinguish between general sounds of healthy and diseased reefs.

Reef health might be tracked using sound recorders and artificial intelligence worldwide to track reefs’ health and determine whether their efforts to conserve and restore them are practical. 

“In many circumstances, it’s quicker and less expensive to place an underwater hydrophone on a reef and leave it there than to send experienced divers to the reef on a regular basis to survey it – especially in isolated areas.”