Introducing Greyparrot AI Waste Recognition System

Through AI-powered computer vision software, we provide in-depth data insights to stakeholders in the resources and waste sector - giving them vital information they have previously not been able to access.

Greyparrot Dashboard view-centre

How does it work?

Greyparrot offers a complete waste composition analysis solution that automates the manual process of sampling and auditing material through intelligent monitoring and analysis.

Monitor 100% of waste 24/7

Greyparrot solution provides real-time composition information at product, material and brand level.

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100% of waste is monitored providing instant live data

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We can currently differentiate more than 49+ categories of waste

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We do this with an accuracy of 95%

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Product

AI Monitoring Unit

Our AI monitoring unit can be retrofitted across different conveyor belt environments without changing existing infrastructure. The integrated AI model recognises the composition of large waste flows  in real time at a granular product, brand and material level.

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Waste Analytics Dashboard

The waste analytics dashboard is completely configurable and customisable and displays instant live  data analytics reports and insights to inform your decision-making.

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Waste Composition Integration

Our waste composition integration can link actionable insights with third party systems through an open API. This provides cognitive AI intelligence to existing software frameworks and automated sorting machinery.

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Our use cases for MRF, PRF and other reprocessors

Click on each number to find out more:

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Unit 1
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Measure all input materials (before or on the high-speed conveyor belt)

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Unit 2
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Measure recovered material before QC with optional API link to sorting robot or valve bar

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Unit 3
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Measure unrecovered materials on residue line

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Unit 4
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Measure material purity and QC performance with Unit 2

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Unit 5
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API link to baler for digital purity stamp

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Unit 6
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Measure input/output material samples to replace manual audits

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Greyparrot AI

Greyparrot detects differences almost imperceptible to the human eye.

1 Product recognition

Successful recognition of packaging vs. non-packaging and food vs. non-food grade objects, even with small and overlapping items.

2 Material recognition

We can recognise 49+ categories of waste with +95% accuracy, even with crumpled, crushed or deformed items.

3 Brand recognition

We also differentiate SKU (stock keeping units) and size of products (e.g. small diet coke vs large coke)

Successful recognition of packaging vs. non-packaging and food vs. non-food grade objects, even with small and overlapping items.

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We can recognise 49+ categories of waste with +95% accuracy, even with crumpled, crushed or deformed items.

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We also differentiate SKU (stock keeping units) and size of products (e.g. small diet coke vs large coke)

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Get in touch today

Book a demo to see our dashboard running in real-time at a sorting facility

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