Community Research and Development Information Service - CORDIS

H2020

RUBSEE Report Summary

Project ID: 756841

Periodic Reporting for period 1 - RUBSEE (Extending artificial intelligence revolution in the waste field beyond sorting)

Reporting period: 2017-02-01 to 2018-01-31

Summary of the context and overall objectives of the project

RUBSEE is a real-time monitoring system based on Artificial Intelligence and Computer Vision techniques. This system is able to determine the composition of material in Waste Treatment Plants. This monitoring platform will allow the facilities reducing the amount of recyclable material that is currently being landfilled or incinerated. They will be able to recover more material, so they will increase their benefits.

Work performed from the beginning of the project to the end of the period covered by the report and main results achieved so far

From the beginning of the project to the end of the period covered, the following work and main results has been achieved:
• A dataset with around 500.000 objects has been created from machine learning, this objects are separated in 12 categories (due to customer requirements)
• The recordings have been done in one of the three pilots plants involved in this project and are stored in Sadako’s servers.
• We have created a Neural Network able to detect different kind of material (the initial Neural Network was able only to detect PET bottles) with the most advanced techniques of deep learning.
• The current NN has a Recall way over the targeted in the proposal. We are working to improve the purity, but the current value is high. We are progressing according to the objectives defined.
• The current NN is able to detect 12 different kind of materials instead of 10 as originally considered in the proposal.
• We have developed different software modules needed to use the RUBSEE system as a single unit:
o Acquisition module
o Detection module
o Communication module
• We have started developing the RUBSEE monitoring platform and we already have implemented some user screens.
• We have advanced towards defining our business model / commercial strategy.

Progress beyond the state of the art and expected potential impact (including the socio-economic impact and the wider societal implications of the project so far)

Sadako’s technology is able to detect and measure a big diversity of objects existing in crowded waste streams, this is a big challenge in terms of visual recognition.
Our disruptive low cost technology will let to increase the recovery rates, so decrease the quantity of material sent to landfills or incinerated. RUBSEE will be a key tool for the waste treatment and recycling plants, promoting the circular economy.

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