Execution period

August 2017 March 2018

The project

The agri-food sector is is the largest consumer in the manufacturing industry, consuming between 8% and 15% of the water consumed by the whole of the European industry. An Aragonese meat industry has been chosen as the software development field. The meat industry is the main agribusiness subsector by sales volume.

Until now, industry has prioritized the optimization of other resources of the higher cost than water by making technological investments in other areas, such as energy, transportation, production processes, etc. No However, the management of the water cycle for industrial use in terms of quality control, regulatory compliance, the cost of water at the point of use and environmental responsibility are of concern to industries.

DIGICAT aims to develop an artificial intelligence software appliedto the agri-food industry to improve the integrated management of the water cycle. Endowed of Artificial Intelligence (Big Data Analytics and Predictive Capabilities), DIGICAT will help companies in the agri-food sector to make the right decisions. decisions for the optimization of water flows in time quasi-real and predictive in nature.

To this end, DIGICAT has the following partners:

  • ZINNAE (Coordinator)
  • COGNIT (Technical Coordinator)
Innovative Business Clusters

This The project has received grant assistance under the support program for Innovative Business Groups (AEIs). This program to support the strengthening of innovation clusters se the European strategy to improve the competitiveness of the European Union’s innovation.

The groups that can benefit from the grants of the program are those entities whose innovative potential and mass are The critical acclaim has earned them recognition from the Ministry of Economy, Industry and Competitiveness (MINECO) through its registration in the Registry of Innovative Business Groups.

ZINNAE has been part of the Registry of Innovative Business Groups since 2010.

Project objectives

This project is phase 1 for the development of an artificial intelligence software for the management of (DIGICAT), in a way that will help the manufacturing industry to agri-food industry to manage their water flows. The software will be able to establish patterns and therefore to be able to predict behavior depending on production, and it is possible to anticipate in to possible deviations from the requirements at all times and thus to keep water consumption optimized at all times.

Specific objectives for Phase 1 include the following:

  1. Identify the needs of a replicable agri-food production process, Fribin meat industry.
  2. Visualize the characterization of relevant water streams by applying Business Intelligence.
  3. Data analysis for decision making in stream optimization with the objective of minimizing consumption and discharge
  4. Establish patterns of water flow behavior and productivity.
  5. Identify indicators for prediction and anticipation of needs.
  6. Pre-development of software prediction algorithms
  7. Perform the Value Added Analysis of the software
  8. Conduct Market Proximity and Continuity Analysis of the project
Work Packages

The The project is coordinated by ZINNAE with the technical support of COGNIT. The The project includes the following five work packages:

  • PT1 Project coordination and dissemination of results
  • PT2 Analysis of the Fribin water cycle
  • PT3 Visualization and optimization of water flows
  • PT4 Rapid prototyping of big data analytics solutions applied to streamflow optimization.
  • PT5 Analysis of added value, market proximity and continuity
More information and contact

More information and collaboration opportunities at ZINNAE, through cpresa@zinnae.org.

And in COGNIT, through p.delchicca(@)cognit.es

And in ITAINNOVA, through csaviron(@)itainnova.es

And in CONTAZARA, through jsantacruz(@)contazara.es

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