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Completed PROJECT GRANT Swedish Research Council

ECSEL 2020 RIA AIDOaRt

259.99M kr SEK

Funder Vinnova
Recipient Organization Mälardalen University College
Country Sweden
Start Date Apr 01, 2021
End Date Sep 30, 2024
Duration 1,278 days
Number of Grantees 1
Roles Principal Investigator
Data Source Swedish Research Council
Grant ID 2021-01364_Vinnova
Grant Description

Purpose and goal:

To create a framework incorporating methods and tools for continuous software and system engineering and validation leveraging the advantages of AI techniques (notably Machine Learning) in order to provide benefits in significantly improved productivity, quality and predictability of CPSs, CPSoSs and, more generally, large and complex industrial systems.

Expected results and effects:

AIDOaRT aims to impact organizations where continuous deployment and operations management are standard operating procedures. DevOps teams may use the AIDOaRT framework to analyze event streams in real-time and historical data, extract meaningful insights from events for continuous improvement, drive faster deployments and better collaboration, and reduce downtime with proactive detection.

Approach and implementation: The project will be carried out following a continuous integration and continuous delivery (CI/CD) approach inspired by DevOps. The project plan will evolve continuously by considering the overall development and release process and the necessary adjustments to their plan. By following the DevOps practices, the project

will consider an iteration path: 1. Technology plan 2. Technology development 3. Technology integration 4. UC development 5. UC execution and validation 6. Evaluation & feedback

All Grantees

Mälardalen University College

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