We use a combination of Machine Learning, AI, and advanced algorithms to identify the number one item that our customers say is their biggest contamination issue “plastic bags”. The dreaded plastic bag can create all kinds of problems when it ends up in the cardboard recycling stream from jamming recycling sorting equipment, blocking optical sorters, and generally just being a pain for those folks sorting cardboard and paper from everything else.

Contamination identification has two parts – figuring out if a container has contamination (in this case is plastic bag present in the picture) and then providing a level of confidence in the analysis. Essentially the system outputs an analysis of each image with the decision made and how confident the system is. One of the goals of the Pello team is to provide a high confidence analysis that can be actioned by users. So instead of providing a lot of alerts of which many are not high confidence we want to provide only alerts that we have high confidence of being correct.

How can the Contamination Alert system be used to improve your operations?

• Reduce contamination events and associated contamination fees charged by vendors by proactively removing contamination items before containers are collected.
• Identify containers that have high levels of contamination and take action to reduce the contamination by improving signage, training employees and tenants and securing containers to reduce illegal use.
• Automate your contamination fee billing by using the feature automatically generate and assign contamination events by client or account.

Here are some examples of the system at work: