MobiCugat

Urban mobility study for the Local Council of Sant Cugat

Sep 2025 – Dec 2026

Code: C-13469

MobiCugat is a city-scale urban mobility study commissioned by the Sant Cugat City Council. The project performs traffic assessment using data from low-emission zone cameras, integrating it with the SUMO traffic simulator via the RUTGe framework for comprehensive transportation analysis.


Partners:

Universitat Politècnica de Catalunya (UPC) HoundLine Ajuntament de Sant Cugat

DISCOVERY

DIstributed Smart Communications with Verifiable EneRgy-optimal Yields

Sep 2024 – Aug 2027

Code: PID2023-148716OB-C32

DISCOVERY is a coordinated national research project focusing on distributed communication systems that integrate privacy, security, and energy efficiency. The UPC subproject addresses communication network protocols and data privacy, contributing to the development of more efficient, secure, and sustainable distributed digital infrastructures for data-driven services powered by machine learning.


Partners:

Universitat Politècnica de Catalunya (UPC) Universidade de Vigo (UVigo) Universidad Carlos III de Madrid (UC3M)

MOBILYTICS

Anonymization Technology for AI-based Analytics of Mobility Data

Nov 2022 – May 2025

Code: TED2021-129782B-I00

MOBILYTICS addresses the challenge of enabling AI-based mobility analytics while preserving user privacy. The project develops anonymization techniques — including non-perturbative masking, perturbative masking, and synthetic data generation — for mobility datasets collected by private companies and public entities. A core goal is promoting sustainable urban mobility through privacy-preserving data sharing. Funded by MICIU/AEI and the European Union NextGenerationEU/PRTR.


Partners:

Universitat Politècnica de Catalunya (UPC)

COMPROMISE

Enhancing Communication Protocols with Machine Learning while Protecting Sensitive Data

Sep 2021 – Feb 2025

Code: PID2020-113795RB-C31

COMPROMISE is a coordinated national project combining knowledge in security, privacy, communication protocols, quality of service, and machine learning. It addresses privacy improvements in network protocols and aims to prevent privacy attacks, protecting communications with mechanisms that balance the trade-off between utility and privacy. Funded by MICIU/AEI.


Partners:

Universitat Politècnica de Catalunya (UPC) Universidade de Vigo (UVigo) Universidad Carlos III de Madrid (UC3M)