Beyond the sorting application, our A.I. based vision technology can monitor in real time the waste flow processed by waste treatment plants, to foster their operation so that better economic, environmental and regulatory performance can be achieved.

This was the seed of our RUBSEE project: the development of a waste stream monitoring system based on AI for which Sadako have had the financial support of the European Union under an SME Phase 2 – Horizon2020 program.

Project started on February 2017 and has successfully ended on September 2019, with two main outcomes: relevant advances in Sadako’s AI technology for waste detection (commercialized via licensing to Max-AI©) and 3 pilot systems installed and running in 3 different European waste treatment plants.

The following video summarizes Sadako trajectory and the RUBSEE work and results:


RUBSEE monitoring system

In a typical industry, the input raw materials are totally controlled, and all undergoing products are fully oversight in their way to become finished goods.

However, the input of an urban Waste Treatment Plant or Material Recovery Facility is a highly variable and uncontrolled waste flow. Nowadays plants work without real time automatic information of the mix of materials they are processing or obtaining along the relevant points of their layout.

Although there’s a lot of value in the data collection, NIR conventional sensors or other available technologies are too expensive for that.

To address this unmet need and opportunity, we have developed RUBSEE, a disruptive real-time monitoring system that uses advanced Artificial Intelligence and Computer Vision to determine in every moment the composition (kind/quantity) of material present in a number of locations in the plant. It aggregates and presents the information so that in can be easily analyzed and activated and generates automatic alerts that can help managers and technical team to detect and resolve undesirable events.

With the information created by RUBSEE:

  • Operators can adjust the parameters of their current equipment on real time and in some cases even readapt the layout design
  • In the same way, unexpected technical failures or equipment yield drops can be immediately detected for quick solving
  • Historic information and comparative analysis can shed light to plant operation and allow data-driven decisions

The system can identify what’s moving across the lines, providing to waste operators the same type of actionable information that manufacturing, and energy companies already employ.


The project development has faced great technological challenges, mainly related to the complexity of the waste flux.

RUBSEE targets the whole plant layout, and so it needs to be able to detect and measure in a big diversity of waste streams, more or less crowded and with a very different mix of objects depending on the location inside the plant. Some of the positions addressed have supposed a great defiance in terms of Artificial Intelligence based visual recognition.



We would like to specially thank:



  • The Technological Center Ateknea Solutions, that has developed the Remote Monitoring Platform for data aggregation and management and the ADUS (Automatic Database Update System).
  • The Research Center Centre de Visió per Computadorwhich collaborated in the whole AI Data strategy and supported the Data Base creation.

Below images show some of the monitoring devices installed in the 3 pilot sites as well as examples of the platform interface.


In spite of the challenges faced, Sadako is really encouraged with the project results. The technology generated has been market delivered via licensing to Max-AI© product family, while we keep continuous efforts for enhancing its performance and reach.

RUBSEE is already making relevant contribution to waste treatment plants, making them smarter and more efficient, and we remain working so that the contribution will be greater in the future.