How A.I can Solve Overfishing

The Point Is…

Despite what you may have heard, there are not plenty of fish in the sea. If the U.N. Food and Agriculture Organization is correct, we have 19 years left of seafood. With over 2.2 billion people currently relying on fish for protein and many populations relying on the resource for survival, 2048 won’t look good for us. This application of artificial intelligence on small fishing boats is one simple and cost-effective measure to help slow the rate of overfishing. Allowing governments to track and minimize illegal fishing activity is not going to solve this crisis, but it’s an excellent place to start. Ecosystems, food security, and economies all depend on an end to this overfishing before 2048.

How I got interested in solutions for overfishing.

Last year I went scuba diving in the Dominican Republic. It was fun and mind-blowing, and I jumped every time I came within 20-meters of a fish bigger than my thumb. I got to see an ecosystem that is vastly underexplored and grossly underappreciated by most of society. It was sick!

During my second dive, the divemaster started doing a signal that I didn’t recognize. In fairness, the only signals that I knew at the time were “help, I have no oxygen” and “I’m cold.” His signal looked something like this:

Any somewhat intelligent individual should have been able to piece together that the signal meant “shark.” I, on the other hand, decided to ignore the gesture. When I turned around, there was an ~8.5 foot-long blue shark swimming towards me. 

I may have set the record for the loudest noise ever made through a scuba regulator. I was fully prepared to get eaten as a midday snack. To my surprise, the shark couldn’t care less that we were there. It swam directly over my head, and it didn’t glance at us once. It was one of the most beautiful, majestic and heart-stopping things I have ever witnessed.

Expectation vs. Reality

After the dive, I heard some upsetting news. The divemaster told me that he rarely sees blue sharks anymore because they are critically endangered. Blue sharks are the most heavily fished shark species. It’s not because they’re deliberately hunted (although many sharks are). The reason they are becoming endangered is that they are caught accidentally in large commercial fishing nets. When I came home from the trip, I got really interested in the overfishing crisis and started researching… What I found was well, Jeez Louise! It’s a huge problem!

What is overfishing, and why is it a crisis?

The earth’s oceans are one of the largest food sources in the world. Fish are the primary source of protein for 2.2 billion people; however, more and more fishers are returning to shore with empty nets.

Some scientists say that over the last 50 years, fish populations have decreased by 90%. According to the U.N. Food and Agriculture Organization, there won’t be any seafood left to catch by 2048. Why? Overfishing.

Overfishing happens because more fish are caught than are replenished through natural reproduction. The term overfishing makes it sound as if we are catching too many fish because demand is super high.

This is not the issue; we aren’t catching and eating too many fish.

Overfishing is a result of inefficient and unsustainable fishing methods and industry management that increases costs for fishers and destroys marine environments.

A quick refresher on why we care about the survival of our oceans:

  1. Oceans (phytoplankton, in particular) provide 50% of the oxygen we breathe. If we kill too many fish, the food chain collapses and, poof, no more phytoplankton.
  2. Oceans act as a carbon sink for our pollutants. The oceans absorb 28% of the carbon dioxide in the atmosphere, acting as an essential regulator for climate change. Phytoplankton absorb CO2 and produce oxygen.
  3. As previously mentioned, the ocean is a massive source of food. I’m not just talking about sushi bars and fish markets; I’m talking about the millions of people living in extreme poverty who survive off this food source. Millions of people rely on fish as an affordable food source, and ten percent of the world’s population depends on fisheries for their livelihoods. Long story short, we need marine ecosystems to survive.

I asked myself how is it possible that inefficiencies in the fishing process drain an ecosystem as vast as the earth’s oceans? Is it that inefficient? 

The Industry

The most common method used for commercial fishing is trawling. Trawling means dragging a massive net the size of four football fields behind the boat, to catch everything in its way. Moreover, I mean everything40–96% of fish are unintentionally caught and thrown overboard dead or dying. This 40–96% waste is called bycatch, and it is putting a lot of marine species at risk, including the blue shark.

Trawling for fish.

The overexploitation of these populations is creating major issues in marine food chains. This exploitation is pushing the total collapse of the ecosystem forwards. Trawling is currently the cheapest method of fishing. However, sorting the catch from the bycatch is time and labour intensive. Most importantly, it is going to come back to bite society in the butt once we realize that we overexploited our oceans.

Both small and large commercial fishing boats use this unsustainable fishing method. While large vessels catch a lot of fish per outing, small vessels are incredibly abundant, with an estimated 1.2 million boats fishing past the legal limits every day.

Certain countries started putting a government supervisor on every ship to prevent overfishing and stop illegal operations. These supervisors count fish and record the numbers on a paper form.

Manually classifying a fish

Thanks, governments! I appreciate the effort! However, this system makes no sense! Government supervisors are expensive, and, worst of all, they rarely use the data.

A Solution

The task of these supervisors is relatively simple: Count fish, record data. Good news! A.I. can handle that.

This A.I. image classifier can count, identify the species and determine the size of the fish. Camera images of the catch coupled with the A.I. image classifier could readily replace the work of the supervisor.

This data would not only be valuable to make sure that fishers stay within legal fishing limits, but is also useful to track fish populations. Also, it would undoubtedly cost less than a supervisor per boat.

More good news…the technology is available and relatively simple. I made an image classifier that can do this job.

To build this, I used a convolutional neural network (CNN) to build this you only look once (YOLO) image classifier. CNN are the most common type of neural network for computer vision.

A CNN detects patterns in an image by scanning it in many steps. The neural network can then recognize the objects in the picture. The specific model shown above was trained to identify marine species and classifies the animals in real-time. As you can see, a CNN can make identification errors. Over time, the model learns and improves. 

To understand how CNNs work, check out this article on my LinkedIn.

The information collected by the model would feed into government databases, and fishing vessels undergoing illegal activity would be shut down. This would stop millions of small fishing boats that continuing to overfish which would save endangered species.

Regulations could require fishers to equip their vessels with cameras and computer vision technology. The data gathered could be used to track fish populations and fishing activity.

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Author: TKS

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