The future of waste: the role of AI in waste management

Tuesday 1st October 2024

Can artificial intelligence improve the way UK businesses dispose of their waste?

Over the past few years, AI has been making headlines for good and bad reasons. From sci-fi level innovation to concerns around how artificial intelligence will impact the arts, it’s no surprise Collins named ‘AI’ it’s 2023 word of the year.

But while AI is very good at grabbing headlines, it can also change the way certain industries are run, including waste management. AI has the potential to create a more sustainable waste management landscape, and we’re already seeing some of these possibilities become a reality.

However, there are factors to consider when introducing AI into any sector. Let’s take a closer look at the role of AI in the future of waste management: the good and the bad.

Automated waste sorting

Traditional methods of waste sorting involve a lot of time and resources, relying on manual sorting processes to separate reusable and recyclable materials from those that need to go to landfill.

Government figures reveal that the UK produces 220 million tonnes of waste every year, and a significant portion of this goes to landfill unnecessarily. Manual waste sorting is prone to human error, while AI systems can sort through a much higher volume of waste with greater accuracy.

AI systems can not only sort through waste, but also flag anything which is potentially problematic or dangerous, giving regulators a better understanding of what materials we should and shouldn’t be using.

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AI scanners and predictive analysis

AI scanners can sort through waste to a much higher level of accuracy than human sorting, even separating electronic devices into their separate reusable parts. AMP Robotics even reports AI systems which can detect which coffee chain disposed coffee cups belong to, allowing blame to be placed directly at the manufacturers creating large amounts of waste.

Through AI, paper, plastics, glass, organic materials, metals, electronics and more can all be sorted correctly without human intervention. By sorting through large amounts of data, AI systems can also predict what future waste patterns will look like, which is particularly useful during peak periods like new product launches or seasonal sales.

Optimised collection, pickup, and home waste

By analysing real-time data, AI can improve efficiency in waste collection by removing the risk of missed pick-ups or half-filled trucks, adjusting pickup routes to suit current circumstances at the drop of a hat.

In a similar way, AI can use real-time data to improve waste management at source. Bin sensors can predict waste accumulation levels, and barcode scanning or image recognition software can provide accurate information about the most sustainable disposal methods.

The challenges of AI for waste management

Despite it’s potential, there are still concerns surrounding the use of AI in waste management. One of the most pressing issues is job displacement, as relying on AI waste sorting and pickup routes could see many workers within the waste industry lose work.

What’s more, AI systems can be expensive and energy intensive. Smaller businesses in particular may struggle to make the initial investment needed to benefit from AI tech, resulting in them falling behind larger corporations.

Similarly, AI systems can be complex, and businesses without the means to hire experts or pay for staff training could miss out on the benefits of AI for waste management.

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