Using AI to Improve the Process of Waste Management

In this article we will be providing an insight into the waste management industry and how technologies such as AI can provide savings of energy and much more, through improved and faster methods of sorting for wasted materials.

Waste Management Sorting

Currently most waste management sorting is carried out through a single-sort system. This can cause the sorting process to become slow as all materials go into the same box. When this reaches the waste management plant this then needs to be separated as materials such as cardboard and plastic need to be treated differently in order to be recycled. This requires plant operators to manually sort each item into a different bin. 

Once each item is separated into each bin it is then transported to a specific plant which deals with that material. For example, all glass sorted will be crushed into forming cullet which is then cleaned of debris and other contaminants. From there it is loaded into trucks and transported to a plant which manufacturers glass products. It is then heated in a furnace and then treated to form a certain shape (e.g. bottles, glassware etc.), in result recycled.

More information can be found here detailing various ‘streams’ of plant materials and how they are recycled and used. 

This article will be focusing on the first part of waste management which is sorting material. This first part of the whole recycling/waste management process can be time consuming and in-accurate at times. Therefore, a possible use of AI would be to help sort through this wasted material.

Using AI to Aid Sorting

Improved and sophisticated AI-powered technologies are on the rise across various industries, from smarter manufacturing, warehouse management, cleaner energy production and much more. AI algorithms can be used in conjunction with smart sensors, so that when material arrives at the plant and is deposited onto the conveyor belts to be sorted, the AI can categorise each material such as glass, metal, cardboard as well as non-recyclable objects and sort them into different bins automatically.

Furthermore, AI can help categorise even further by separating different types of metals using sensors such as inductive proximity sensors. These sensors can detect various compositions of different metals based on magnetism. More information on this can be found here.

Additionally, AI can be programmed with special considerations such as to identify contaminated objects before they are processed. For example, if plastic bottles are brought to the plant in bulk, the AI in conjunction with smart sensors can determine which are contaminated and which are not, sorting them into two different bins. From there, the contaminated bottles can be decontaminated and prepared for recycling, whereas the non-contaminated pile can be prepared and sent to the recycling plant. This can save time and resources that are required in the process of decontamination, since there would be no real need to decontaminate clean material. 

In one such use case, AMP built a dual-robot system, which is able to sort through recyclables at a rate of 160 pieces per minute. This is a 4-5x increase in comparison to a human operator, which sorts through 30-40 pieces of recyclables per minute. Additionally, it can cause mental and physical strain on human operators working long hours and decreasing efficiency over time. On the other hand, AI sophisticated machines can keep a consistent pace throughout the day. This could help direct focus of human operators to tasks which require more attentive measures and critical thinking.

As AI-powered systems will still require maintenance, human operators can direct their focus on tracking its performance and catching mistakes it may make during the sorting process instead. Whilst AI can improve the efficiency of recycling, cut down unnecessary costs and reduce physical strain on human operators, there is still more to be done on encouraging recycling and increasing its awareness to people around the world. 

We hope this article has provided a good overview of the potential applications of AI embedded systems in waste management and how it could be used to cut down on unnecessary costs within this industry. If you are looking for research & development services, or have an idea you would like to discuss, don’t hesitate to contact us.

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