Skip to main content
Logo GMV

Main navigation

  • Sectors
    • Icono espacio
      Space
    • Icono Aeronáutica
      Aeronautics
    • Icono Defensa y Seguridad
      Defense and Security
    • Icono Sistemas Inteligentes de Transporte
      Intelligent Transportation Systems
    • Icono Automoción
      Automotive
    • Icono Ciberseguridad
      Cybersecurity
    • Icono Servicios públicos Digitales
      Digital Public Services
    • Icono Sanidad
      Healthcare
    • Icono Industria
      Industry
    • Icono Financiero
      Financial
    • Icono Industria
      Services
    • All Sectors

    Highlight

    European Conference on Space Debris
    Our present and future: A tour through the European Conference on Space Debris
  • Talent
  • About GMV
    • Get to Know the Company
    • History
    • Management Team
    • Certifications
    • Corporate Social Responsibility
  • Communication
    • News
    • Events
    • Blog
    • Magazine GMV News
    • Press Room
    • Media library
    • Latest from GMV

Secondary navigation

  • Products A-Z
  • GMV Global
    • Global (en)
    • Spain and LATAM (es - ca - en)
    • Germany (de - en)
    • Portugal (pt - en)
    • Poland (pl - en)
    • All branches and all GMV sites
  • Home
  • Communication
  • News
Back
New search
Date
  • Digital Public Services

BIDS21, how to share confidential and private data from space-related projects

24/05/2021
  • Print
Share
utile_pet

Artificial Intelligence is increasingly relevant in space-related projects. In these projects, the solution is as important as the quality of the data. The current potential of the automatic learning solutions make it possible to use it to complement or even replace in some cases the classic techniques for resolving tasks such as processing signals or detecting anomalies. In addition, the more data is available, the better the performance, so it makes sense that different entities collaborate on a common solution. However, this can cause a problem in terms of privacy and it is not always possible to share the data among the different parties.

To tackle this problem, GMV Data Scientist Juan Miguel Auñón presented uTile PET at the “Big Data from Space 2021 (BIDS21)” event, a solution for the collaborative development of Artificial Intelligence algorithms without having to compromise the privacy of each of the parties. During his presentation, he also offered the example of secure k-means, a clustering algorithm used by organizations to collaborate for a common goods, safeguarding privacy at all times.

uTile PET is a solution developed by GMV that leverages confidential and private data to improve the automatic learning algorithms and analytical models, always in compliance with the requirements of the organization, guaranteeing data privacy and the applicable legislation. With this technology, it is not necessary to choose between data privacy and usability, as it uses advanced cryptographic methods that keep the data encrypted while all the necessary calculations are completed. Thus, uTile PET makes it possible to keep the organization’s sensitive data from being exposed or transferred between departments, organizations or different countries.

  • Print
Share

Related

MyT Summit 2025
  • Digital Public Services
MyT Summit 2025
29 May

8:30 AM - 12:30 PM

5G FORUM 2025
  • Digital Public Services
5G Forum 2025
12 May - 16 May
Paradores
  • Digital Public Services
Discover Paradores heritage like never before

Contact

Contact menu

  • Contact
  • GMV around the world

Blog

  • Blog

Sectors

Sectors menu

  • Space
  • Aeronautics
  • Defense and Security
  • Intelligent Transportation Systems
  • Automotive
  • Cybersecurity
  • Digital Public Services
  • Healthcare
  • Industry
  • Financial
  • Services
  • Talent
  • About GMV
  • Shortcut to
    • Press Room
    • News
    • Events
    • Blog
    • Products A-Z
© 2025, GMV Innovating Solutions S.L.

Footer menu

  • Contact
  • Legal Notice
  • Privacy Policy
  • Cookie Policy

Footer Info

  • Commitment to the Environment
  • Financial Information