Current studies specifically signify that the so-called “Great Pacific Garbage Patch” is 16 times bigger than what it was before. This swirling collection of trash, mostly consisting of discarded plastic (between Hawaii and California) spans about 1.6 million square kilometers, making it three times larger than France or double that of Texas back in the United States.
However, scientists observe that out of around 13 million metric tons of plastic trash that is dumped into the oceans each year, only a fraction come floating on the ocean surface. The rest washes up on beaches, lingers in mid-ocean or sink to the sea floor. Nevertheless, no one knew precisely, the volume of such trash that ended up on the shoreline, till Morris Enyeart from Barnegat, New Jersey commenced measuring plastic pollution on beaches by conducting drone surveys and machine learning algorithm to help him achieve the result.
Incidentally, machine learning uses programmed algorithms that receive and analyze input data to predict output values within an acceptable range. When relevant data is fed to these algorithms, as in the present case, it separates plastic bottle caps, plastic bags and sundry other plastic throwaways from stones, driftwood and all other flotsam and jetsam that is washed up on the beaches almost on a daily basis.
Meanwhile, UK nonprofit THE PLASTIC TIDE wanted to gather some harder data on all that plastic. Instituted by Peter Kohler (34), the organization is in the course of developing a sure fire method for measuring marine litter which Kohler and his group hope would go a long way towards limiting the litter.
We are Creating the Eyes and The Brain
“We’re creating the eyes and the brain to track plastic pollution,” Kohler said. Drone-mounted cameras serve as the eyes, taking thousands of aerial photos. The brain is a machine learning algorithm, which Kohler and his collaborators are training to recognize plastic fragments.
“Training the algorithm requires a lot of photos of beaches and a lot of human eyes to tag the plastic in those photos,” says Kohler. The Plastic Tide has uploaded all the photos they’ve collected to Zooniverse, a citizen science portal, so anyone can go online and tag plastic. This past March, during British Science Week, the effort got a shot in the arm when students across the United Kingdom identified more than 1.5 million plastic fragments in photos.
Photos Taken by Enyeart
Many of those photos, however, weren’t from UK, but from a New Jersey beach across the Pond and were taken by 72-year old Morris Enyeart, who has contributed more than 7,000 images to THE PLASTIC TIDE. Enyeart could have retired a couple years ago, when he sold his web design company. Instead, he started looking for a new project. “I wanted to do something new, something challenging, something that would benefit other people,” he said.
Enyeart started by getting a commercial drone pilot’s license, with the plan of surveying the litter along THE New Jersey beach. But he soon came to realize that a photo survey had limited utility. “I can fly the drone. I can take pictures. But what benefit is that other than just having pictures?” Enyeart thought. “That’s where machine learning changes the game.”
Morris Enyeart Joins Hand With Peter Kohler
In his endeavor to proceed further, Morris Enyeart visited THE PLASTIC TIDE website and was quick to visualize the utility of adding machine learning to his own project. This resulted in joining hands with Peter Kohler. Since then, Enyeart has conducted more than 100 surveys of Island Beach State Park near his home in Barnegat, New Jersey, and uploaded thousands of photos to help train THE PLASTIC TIDE’s algorithm.
Launching of the Marine Litter DRONET
THE PLASTIC TIDE is thrilled to announce the launch of the global Marine Litter DRONET, said Peter Kohler. “It supports THE PLASTIC TIDE’s mission by bringing together different people, organizations, NGOs and enthusiasts from around the world to design a simple, repeatable and accurate method for surveying marine litter with drone technology,” declared highly elated Kohler and his team.