AI is changing the waste industry, here’s five ways that is happening
The world is on the cusp of an extraordinary new era driven by advances in Artificial Intelligence (AI). Business, governments and individuals see the evolution of AI capabilities as a once-in-a-generation opportunity to revolutionise the way we work and how we make decisions, to deliver lasting positive change.
For environmental services, mitigating climate change and supporting the movement towards a circular economy is of crucial importance. AI could be a catalyst to accelerate collaboration and knowledge-sharing, as well as making processes smarter, more efficient, and scalable.
This is also true of recent advancements in the application of AI in the management of resources and waste. AI provides a new avenue for the industry to accelerate efforts aimed at tackling the climate crisis, before we reach an irreversible tipping point.
AI adoption and impact
Waste management is changing. The sector is moving rapidly towards greater automation, digitalisation and circularity. While this in part is naturally being driven by an ongoing ambition to improve efficiencies and reduce costs, there is another significant force. This is the growing demand across the value chain to move towards regenerative business models that will help protect the earth’s valuable resources and sustain the planet into the future.
New regulatory tools, such as the Plastic Packaging Tax, Simpler Recycling, packaging Extended Producer Responsibility (pEPR), and in the future, a UK-wide Deposit Return Scheme will work together to support this transition, improving the overall recovery rate of valuable recyclable materials.
With a push towards enabling the circular economy, growing regulation and the rising costs of operations, AI advancements offer a wealth of opportunity across the waste management sector.
Five ways AI is changing the waste industry:
1. Composition analysis, contamination identification, and waste tracking
AI vision systems are being developed for utilisation with cameras on vehicles, on bins, or even within mobile phones, to assess the composition of the waste collected.
In some instances, this could help identify contaminants, including dangerous items such as vapes and batteries. If we can remove key contaminants effectively at source, not only are we more likely to get a better quality recyclate at the end of the treatment process, but we can also protect our assets from fire hazards or mechanical damage.
Going one step further, we can also use this process to help monitor where contamination levels are high, identifying hotspots where education campaigns could be effectively used to improve behaviours related to what goes in bins and why.
2. Route planning and optimisation
Logistics and route planning are critical in waste management because the sector relies on transporting high volumes of materials, frequently, and from a wide variety of sites across the UK. Our objective is to transport as much volume in as little distance as possible, lowering carbon emissions. 91¶¶Òùimproved collection route efficiencies by 9% since 2019 across I&C alone.
There are a number of emerging solutions aimed at improving the sector’s ability to monitor and manage collections routes, and combine traditionally disparate sets of data to support more efficient route planning.
This application of AI has the potential to help the industry not only reduce unnecessary trips, or even avoid difficult times to travel, such as periods of high congestion, but also to better manage the emissions associated with collections as routes are optimised.
One can envision a future where we have smart cities with numerous connected devices across sectors, enabling a more coordinated approach to providing optimised environmental services.
3. Identification, sortation and recovery of materials
Waste management recovery facilities use manual picking in combination with screens, optical sorters and near infrared sorters. However, while these technologies can identify materials by a range of colours, sizes, and shapes, or by chemical composition, they still have limitations.
AI vision systems are capable of utilising more nuanced visual indicators on materials in the facility for enhanced identification of different materials, no matter the format. They are placed above belts within Material and Plastic Recovery Facilities (MRFs / PRFs), where they learn and improve beyond the foundation they were trained on. Essentially, they get smarter over time.
Biffa’s engineering teams across MRFs, PRFs and Polymers Facilities have been working closely with a variety of start-ups to help train the algorithms to be fit for purpose in the real-world waste environment.
These vision systems are being developed and refined further, to more effectively identify an even greater range of visual cues, material and product types. Eventually, we hope this can support the recovery of more high value material, for reintroduction back into the economy.
4. Waste material flows visibility
Regulations such as pEPR increase the responsibility of producers for the materials they place on the market. Alongside these regulations are growing reporting requirements, and an interest from producers in understanding how their materials are being handled at end of life. NGOs are equally interested in the ability to monitor the efficacy of recycling and behavioural change campaigns.
91¶¶Òùis exploring the use of AI systems to improve the visibility of material flows across our operations. With greater visibility and transparency, targeted actions can be taken more readily to improve the management of waste and resources in collaboration with our partners and customers. Our compliance and engineering teams are leading the way, working with the Environment Agency alongside partners to explore how AI can be used to more easily and efficiently meet the sampling requirements for the MRF Code of Practice.
5. Health & Safety in waste management
We’re an asset heavy sector with a great deal of interaction between people, vehicles and equipment. It is of vital importance to manage any potential risks to health and safety as proactively as possible. Biffa’s municipal experts are leading the way by exploring the use of AI vision systems to prevent and reduce the risks of accidents and injuries.
Let's work together
Small & medium enterprises
Larger organisations
Local authorities
91¶¶Òùand AI innovation
91¶¶Òùis working with some of the leading AI technology providers and start-ups, to help refine their solutions for application in a real-world, industrial environment.
Challenges with the application of the technology in an industrial setting remain. The waste management environment can be very complicated and unpredictable, with the potential for heavy contamination, and an enormous variety of materials that can arrive in a multitude of formats. The efficiency of AI technologies compared to existing sortation infrastructure still needs time, and the sector will need to focus on scalability across the UK given the costs and space requirements involved.
As we continue on this journey, ethical considerations with the application of AI in new environments will also continue to be of critical importance to ensure AI is used carefully and responsibly, with the right protective measures in place.
While these solutions still have some way to go to reach widespread scalability, 91¶¶Òùis committed to working closely with our partners and supporting the upskilling of the workforce as the industry moves towards a more digitised future. We are excited to see how these solutions develop going forward.