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22 abril 2024

How does Artificial Intelligence facilitate recycling?

Urban waste management is a challenge for both the environment and the maintenance of cities could AI be the solution?

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Cubos de colores de reciclaje

In Spain, about 22 million tons of waste were recycled in 2020, according to the Ministry of Ecological Transition and the Demographic Challenge (Miteco). This equates to 110 million 1 cubic metre recycling bins. Far from improving the situation, the World Bank estimates a 70%  growth in waste generation by 2025.

Could artificial intelligence (AI) be the solution? Almost half of the waste generated in 2020 was deposited in landfills, with the corresponding risks for the environment.

Gráfica sobre los volúmenes procesados según su tratamiento

Volumes processed depending on the processing method

  • Years on the horizontal access, from 2004 to 2020.
  • Tons on the vertical axis, with a scale ranging from 0 to 18,000,000.

Data Lines:

  • Incineration:  Represented by a pink line.
  • Recycling of materials:  Represented by a blue line.
  • Landfill:  Represented by a green line.
  • Composting and digestion:  Represented by a light blue line.

Observations:

  • The line representing the "Landfill" (green) shows the highest amount of tons processed and is fairly consistent over the years.
  • The lines representing "Material Recycling" (blue) and "Composting and Digestion" (light blue) show moderate amounts and fluctuations over the years.
  • The line representing "Incineration" (pink) shows the lowest quantities of tons processed and fluctuates slightly over the years.

Source:  Ministry of Ecological Transition and the Demographic Challenge.

If we dig a little deeper, this is what we find: AI offers solutions ranging from collection to processing and recycling. This technology makes it easier to take data-driven decisions, optimise operations and promote more sustainable practices. How? Let's take a look!

 

Artificial Intelligence is Redefining Recycling

Artificial intelligence could change the recycling landscape, and how it does it is evidence of this:

  • Optimising waste collection:  Algorithms can analyse waste generation patterns and optimise collection routes. What is the result? A reduction in the operating costs and the carbon footprint. By adjusting routes and schedules according to actual needs, unnecessary travel is minimised.
  • Automatically sorting waste:  AI can identify and separate different types of waste in recycling plants. This automation improves sorting accuracy and increases the amount of recyclable material recovered.
  • Integrating the Internet of Things (IoT):  IoT devices, such as sensors and cameras installed in wheelie bins, work in tandem with AI systems to monitor fill levels, identifying when and where collection is needed.
  • Prior preventive analysis: Artificial Intelligence can predict waste generation and so help cities and organisations to plan infrastructure needs. These analyses can contribute to the implementation of more effective policies for waste reduction and encourage recycling.
  • RUBSEE  case study:  This technology, which combines AI with computer vision, has been implemented in recycling plants to monitor the amount and type of waste in real time. Operators can then detect problems and optimise processes. Pilot projects, such as the one carried out at the Els Hostalets de Pierola Recycling Plant in Barcelona, demonstrate how AI actually improves efficiency in waste management.

 

Towards a circular economy: The impact of AI

One of the goals of integrating AI for recycling is to promote the transition to a circular economy, where resources are used more efficiently and waste generation is minimised. AI helps maintain the value of products and materials for as long as possible, but how does it contribute to a circular economy?

Recycling is more effective as a result of the accurate analysis of materials, ensuring that they are reused or recycled rather than discarded. By improving this efficiency, sustainability is also promoted, establishing an environmental management perfectly aligned with  the United Nations Sustainable Development Goals.

Persona tirando una cáscara de plátano a la basura

Artificial intelligence is redefining the way we recycle, providing solutions that not only improve operational efficiency, but also support environmental sustainability.

As it can transform data into smart decisions, AI is a crucial pillar in waste management for a greener and more sustainable future, although we still have a long way to go. This has been proven by Mikela Druckman.

Mikela Druckman, founder of GreyParrot, has developed an artificial intelligence system that analyses waste processing and recycling installations. The technology is being applied in 50 European locations, where cameras and AI software study the waste stream in real time.

But there are also challenges to face. Although it may not seem like it, identifying objects that have been transformed, such as a deformed and dirty Coca-Cola bottle, is one of the biggest challenges they face.

It looks like artificial intelligence will transform recycling into a smart ecosystem, putting the icing on the cake in an era of advanced sustainability, proving that the environment and technology can be seamlessly intertwined.

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