Ivves

Industrial-grade Verification and Validation of Evolving Systems

The use of AI and complex, evolving systems (ES), i.e. systems that rapidly change, either due to fast iteration cycles in development or due to their capability to self-adapt and learn, will grow significantly in automation, computation and novel digital services.

Targeting the challenges in verification and validation of AI and evolving systems, IVVES will systematically develop Artificial Intelligence approaches for robust and comprehensive, industrial-grade V&V of “embedded AI”, i.e. machine-learning for control of complex, mission-critical evolving systems and services covering the major industrial domains in Europe.

Transport

/ Transportation

Finance

/ Finance

Healthcare

/ Healthcare

Industrial automation

/ Industrial automation

Cyber Security

/ Cybersecurity

Running from October 2019 to December 2022

European Alliance Summit 2019

European Alliance Summit

November 14, 2019
Amsterdam, The Netherlands

IEEE EMBS Benelux 2019

Annual IEEE EMBS Benelux Chapter Symposium

November 28, 2019
Leuven, Belgium

Ivves ITEA3

IVVES Kick Off

November 29, 2019
Best, The Netherlands

Latest Publications

D6.1 IVVES Dissemination plan

This document describes the plan for using and disseminating the knowledge in the context of the IVVES project, through various means including internal and external communication channels, the distribution of dissemination material and participation in dissemination activities.

D5.1 Requirements for the IVVES experimentation framework

By making sure that all the IVVES outcomes come with a well-defined and clear package of training and possibilities to try them out (experiment with them), we hope to give dissemination of the IVVES outcomes a real boost.

D4.1 Data-driven engineering: state of the art & gap analysis

WP4 in IVVES, titled ‘Data-Driven Engineering’, focuses on implementing solutions for identifying data correlations and behavioural patterns throughout the entire product life cycle with respect to component failures, and with the ultimate goal of enabling predictive maintenance and anomaly detection.

Solution Development Partners

F-Secure
VTT Technical Research Centre of Finland Ltd.
NETCheck S.A.
Futurice
ING
SII CONCATEL S.L.
HeadAI ltd.
Marviq B.V.
ABB AB
Philips
Sogeti Nederland B.V.
Bombardier
Solita Oy
Keyland Sistemas de Gestión SL
Ekkono Solutions

Service Provider Partners

Centre de recherche informatique de Montréal
Praegus B.V.
RHEA Technologies Lab Inc.
The Open University of The Netherlands
Techila Technologies
Addiva AB
University of Helsinki
Prover Technology
InnSpire
RISE - Research institutes of Sweden SICS