Abstract
(Englisch)
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The doctoral network (DN) Decentralized Infrastructure Asset MOnitoring and coNDition assessment (DIAMOND) will train a new generation of Early Stage Researchers (ESRs), who will be central to the digital transformation in EU for safety, economic competitiveness and resilience of critical infrastructure assets (civil/mechanial/social) by assimilating sensors, data analytics and sectoral needs of monitoring and assessment for timely decision making. DIAMOND addresses this timely challenge by aligning advanced computational capabilities to self-aware engineered environments (infrastructure/energy, automotive, industrial and art assets). A key enabler here is via advances in Artificial intelligence (AI), allowing for intelligent sensing nodes (AI on a chip), while concurrently establishing sustainability of such monitoring via bespoke power harvesting modalities and material choice. Our lab-ona- chip approach is a potent enabler for large-scale, cost-effective and automated implementation of responsible AI, as is necessary for monitoring applications at infrastructural scale. Our DN will explore key enablers of this decentralized approach in a cross-cutting manner, delivering deep expertise in sensor technology, data communication hardware/software, instrumentation & measurement strategies, structural health monitoring, system identification and data analytics promoting bespoke and timely interdisciplinary dialogue while promoting ethics, responsibility and environmental & societal good. DIAMOND will be an exemplar in intersectoral training for leading impactful sectors including transportation, automobile, renewable energy and art curation, while being adaptable for further sectors in an asset-agnostic
way. It will establish at-location monitoring and subsequent evidence-based sustainable lifetime decisions at the core of EU processes and sectors.
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