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How Computer Vision Has Evolved and Its Role in Waste Sorting

Imagine there is no trash. That’s right, no waste paper, plastic or cans, but rather materials simply waiting to be sorted for recycling. Imagine that instead of it being sorted using your fingers, it is sorted by a waste sorting machine that uses artificial intelligence and computer vision.  Well, no need to imagine, as computer vision in industrial processes has progressed massively over the past five years and artificial Intelligence (AI) now plays a huge role in many industries – including waste management.

What Is Computer Vision?

Computer vision technology is a subset of AI and Machine Learning designed to process and analyse visual data like images and videos.  Each image is a collection of unstructured information about the world – computer vision will use patterns (colours, texture etc) and transform them to provide meaningful insights to questions like “What is in this image?” or “What action is happening in this video?”.

Given the ability of computer vision to make sense of our surroundings and images, it is already used in several industries. For example, autonomous vehicles, like self-driving cars, use computer vision technology to identify potential hazards and visualise the road ahead.  Security companies will use it to detect unusual behaviour on a CCTV camera, care homes can automatically detect falls, and shopping malls can estimate their footfall.

How Did Computer Vision Develop?

Computer vision technology might seem like a new development, but it’s actually been around since the 1950s. However, limited computational power, and rudimentary algorithms for processing the images meant that its applications were limited.

It wasn’t until 1974 that optical character recognition (OCR) and intelligent character recognition (ICR) technology were capable of recognising printed typefaces and handwriting respectively, and it took until 2012 before machines could detect the outlines of basic shapes. Still, even with these advances, the algorithms required to sort waste with AI only arrived around 2017 with more advanced object detection frameworks – making everything we do at Recycleye exciting and cutting-edge research.

As AI and machine learning become more applicable, the potential of computer vision is even more clear. Computers have become more powerful;  now, we can supply a machine with millions of images to ‘train’ it into recognising a different material/object types in difficult, crushed, dirty settings.

How Does Computer Vision Work?

If you’re going to use computer vision technology for waste sorting or any other application, the first step is to ensure that the machine can differentiate between various objects.  A trash bot needs to be able to tell the difference between a cardboard and a plastic box, so that each item can be processed appropriately.

To do this, the system needs to receive and analyse vast amounts of related data. If you want to ‘train’ a computer to be able to recognise a drinks can, for example, you need to supply it with a high volume of labelled images of cans. Then, the computer will be able to detect similar cans in new settings/ unseen images. This is the power of machine learning, it learns to work well in irregular environments and new, unseen scenarios.

Using Computer Vision for Waste Sorting

Now that artificial intelligence and computer vision has advanced sufficiently, it can be used to sort and process waste accurately and effectively. In fact, AI-powered computers are already being used at materials recycling facilities (MRFs) to streamline and accelerate the waste sorting process.

For example, Recycleye Vision is deployed across many waste management plants in Europe and uses computer vision to scan and identify co-mingled waste. Each item of waste is identified (where the item is) and then classified (what the item is) This can feed into the plant’s data system to tune every machine in the facility and provide accurate compositional data, or be used to directly control a robot or sorting technology.  However, the impact of AI on waste sorting automation doesn’t stop there.

Can AI Automate Waste Management?

Once waste items are scanned and identified using computer vision, waste sorting robots can be used to pick and sort materials.  Computer vision technology enables devices to accurately identify materials and Recycleye’s AI software automates the picking and sorting process.

By using AI robots in this way, efficiency can be increased, and automation can be used to maximise the number of waste items that are economically and accurately sorted for recycling. As we come under increasing pressure to eliminate waste and protect the environment, the use of computer vision and AI has the potential to deliver meaningful environmental benefits, as well as commercial advantages for MRFs.

What Does the Future of AI Waste Sorting Look Like?

Technology continues to revolutionise entire industries and the waste management sector is no exception. As AI waste sorting is used in an increasing number of MRFs, a larger percentage of waste can be successfully recycled, as opposed to being sent to landfill sites. This reduces the negative environmental impact of waste, encourages reuse and repurposing, and helps us move towards a more sustainable, circular lifestyle.

While waste sorting was once reliant on manual analysis and sorting, computer vision technology and artificial intelligence is transforming MRFs into high-tech hubs that can eradicate waste.

To learn more about waste sorting automation powered by computer vision, just get in touch.


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