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InnoGuard: Hybrid and Generative Intelligence for Trustworthy Autonomous Cyber-Physical Systems

Project description

Autonomous cyber-physical system safety and trustworthiness

The increasing use of Autonomous Cyber-Physical Systems (ACPS), such as self-driving cars, which rely on AI, holds great promise for future AI developments. However, concerns arise due to the lack of robust quality assurance and dependability in current ACPS solutions. Supported by the Marie Skłodowska-Curie Actions programme, the InnoGuard project aims to develop novel methods for ACPS quality assurance by creating tailored training programmes for early-stage researchers. The project seeks to automate ACPS quality assessment and evolve system behaviour. Additionally, it will enhance environmental sustainability, energy efficiency, and the trustworthiness of AI methods for ACPS, while improving overall reliability and legal compliance.

Objective

InnoGuard addresses novel challenges imposed by quality assurance of Autonomous Cyber-Physical Systems (ACPS), which have integrated Artificial Intelligence (AI) components. Their use in our daily lives is increasing, such as in public transport systems, highlighting the need for novel, robust development methodologies to ensure their dependability, whose compromise could have severe consequences, as exemplified by various incidents (e.g. accidents caused by Tesla's autopilot system). To ensure ACP dependability, InnoGuard targets developing novel methods for ACPS quality assurance by creating a tailored training program for Early-Stage Researchers (ESRs), with scientific objectives including methods to automate ACPS quality assessment and behavior evolution using AI techniques and enhancing ACPS dependability through real-time security, privacy, and uncertainty handling solutions. Additionally, InnoGuard seeks to improve the trustworthiness of AI methods, enhance environmental sustainability by increasing the energy efficiency of ACPSs with the usage of AI methods, including Large Language Models (LLMs), and validate such techniques in open-source contexts such as Robot Operating Systems (ROS)-based systems. Ultimately, InnoGuard will deliver novel techniques and methodological principles for ACPS quality assurance, ensuring high trustworthiness, reliability, and legal compliance. The project's holistic approach encompasses technical advancements and training initiatives, with a broad plan to disseminate results to industry stakeholders, associations, and the wider public. Through these efforts, InnoGuard strives to elevate the status of ESRs as future experts in ACPS engineering.

Keywords

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Programme(s)

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Topic(s)

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Funding Scheme

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HORIZON-TMA-MSCA-DN - HORIZON TMA MSCA Doctoral Networks

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Call for proposal

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(opens in new window) HORIZON-MSCA-2023-DN-01

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Coordinator

MONDRAGON GOI ESKOLA POLITEKNIKOA JOSE MARIA ARIZMENDIARRIETA S COOP
Net EU contribution

Net EU financial contribution. The sum of money that the participant receives, deducted by the EU contribution to its linked third party. It considers the distribution of the EU financial contribution between direct beneficiaries of the project and other types of participants, like third-party participants.

€ 755 913,60
Address
LORAMENDI 4
20500 ARRASATE
Spain

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Region
Noreste País Vasco Gipuzkoa
Activity type
Higher or Secondary Education Establishments
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Total cost

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Participants (5)

Partners (2)

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