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The EU Packaging and Packaging Waste Directive sets minimum recycling targets of 50% by weight of plastic packaging waste by 2025 and 55% by 2030 for all member states since 2018.

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Part 1: Citeo presentation

To respond to ecological emergency and accelerate the transition into a cirCular economy.
Pioneer of sustainable development since the early 1990s in France, Citeo has developed its expertise by creating a new future for household packaging and graphic papers. Citeo has developed eco-design, collection, sorting and recycling services within the framework of Extended Producer Responsibility (EPR), thanks to the joint action of its corporate customers who are at the heart of its development, as well as in partnership with local authorities along with sorting and recycling professionals.

Part 2: Ingedata presentation

Ingedata helps with integration into data enrichment pipelines.

The added value of AI compared to other technologies, such as spectrometry, product identification code, is to also consider them as sources in its decision process. The challenge is to design a data collection and enrichment pipeline that is comprehensive enough to enable effective computer vision.

Recycling of waste starts with the identification of materials

Materials are not visually recognizable, especially since they are often associated with each other. It is therefore the type of waste that leads to the identification of the material. However, there is an infinite quantity of products that require data annotation solutions adapted to very large quantities of object classes.

Case Study : Data annotation issues and quality of recycled materials

Suez : To automate a quality control at the exit of the sorting centers, allowing to obtain the mass quality of the flows from the interpretation of a continuous video image.

Our Top 5 questions for successful waste sorting with AI 

Today, many recycling processes are controlled by computers. Using computer vision and ML for smarter recycling requires that we first integrate the future conditions of how this waste will be handled. Proper consideration of these issues allows Ingedata annotators to deliver exemplary quality.

Part 3: Q&A

Featured Speaker

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Jean

Chief Customer Officier Ingedata

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Robin

Project Manager Citeo

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Karine

Journalist and moderator

About Ingedata

Ingedata is a leading provider of data annotation to train, validate and optimize Computer Vision and Natural Language Processing models. We are expert in the setup of specialized team and the definition of production workflows, for the annotation of image datasets that are used to train computer vision models.

We hire specialized doctors, general practicioners, nurses, cytopathologists and medical students to annotate data with various levels of complexity. Available workflows allow productivity while ensuring tight quality control and data security.

“Data are becoming the new raw material of business.”

Craig Mundie, Senior Advisor to the CEO at Microsoft and its former Chief Research and Strategy Officer

« Ingedata brought great project management skills to our project. I was a bit worried about our tight deadlines, but the quality of the project architecture secured the annotation workflows and ensured swift deployment and delivery. We could use Ingedata's annotations to retrain our AI models and hit our model accuracy targets. »

Marion Rosenstiehl Program & Product Manager @Suez