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How Technology Help saving whale population
A trivial solution is imposing a narrow traffic scheme. This method has been proven effective in many regions, including the Gulf of Panama.
The Gulf of Panama is home to thousands of humpback whales. A narrow shipping line scheme reduces the probability that a whale crossing vessel routes. Recent studies show that this technique has diminished whale deaths significantly.
Another straightforward way is to impose a speed limit on vessels. This procedure mitigates the risks of collisions and reduces the damage when they occur.
Yet, both these methods aren’t workable options in the open water. Most sea territories are still unprotected with little or no protocols.
The scientific community also has employed a range of AI-powered techniques. Here are some.
Google AI and National Oceanic and Atmospheric Administration (NOAA) on real-time orca detection.
Google AI created a model for detecting an endangered species of killer whales. It uses dozens of underwater microphones to detect orcas’ presence and alert officials.
Google trained the models with 1,800 hours of underwater audio recordings with 68,000 labels. It also conducts further studies to expand this to other kinds of whales and associate the sound signals with orca’s health conditions.
Project CETI by the government of Dominica and the national geographic society.
CETI is determined to deploy dozens of devices over the next five years. These devices could help us listen, interpret, and communicate back with sperm whales.
According to CETI, this is also the largest interspecies communication project ever.
CNN to recognize Humpback whale songs.
Another Google-NOAA collaborated project aims to recognize humpback whale songs. They used 187,000 hours of acoustic data to train the convolutional neural network. These deep neural networks distinguish between different themes using their frequency and patterns.
Analysis of this study showed drastic reductions of humpback whales in the Hawaiian region.
Canadian government’s right-whale detection.
This project uses computer vision to detect whales from aerial drone imagery. The project is aimed at protecting North Atlantic right whales from ship strikes.
This team has proven that deep learning can be used in the detection and classification of whales. They are also looking forward to scaling it up into more locations.
These efforts clearly show that we can have two-way communications with whales. If we could communicate, we could also drive them to a safe zone. That’s the key that caught my attention towards reinforcement learning.
To me, these individual researches seem like pieces of a giant puzzle. Reinforcement Learning could connect the unique components and may solve the riddle.
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