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InnOvative ArtiFicial IntelligencE methodologIes for monitoRing and maintaining large scale complex infrastrUctures and obtaining greener, more Resilient and smart societies

Objective

Over the past 2 decades, the use of artificial intelligence (AI) has exponentially increased toward complete automation of structural inspection and assessment tasks. This trend will continue to rise in image processing as unmanned aerial systems (UAS) and the internet of things (IoT) markets are expected to expand at a compound annual growth rate of 57.5% and 26%, respectively, from 2021 to 2028. It is generally accepted that AI will drive the next revolution in autonomous inspection and health monitoring of civil infrastructure. The possibility of complete automation of the inspection process resulted in a lot of attention from the scientific community leading to a plethora of research in this area. FOURIER intends to establish a network of individual research projects working towards breaking through and innovative system state monitoring (stm) techniques – via the use of AI for large-scale autonomous systemic monitoring, inspection and proactive testing including respective explicit identification of information gaps and uncertainties (information quality) of Complex Engineering Systems to improve their resilience against failures, accidents, sabotage, disruptions and disasters. The objective of FOURIER is to offer innovative research training as well as knowledge exchange opportunities for Doctoral Candidates (DCs) through cross-border and cross-sector mobility for future growth in Europe. FOURIER is an inter/multi-disciplinary and intersectoral programme as it includes seven academic partners, three research centers and seven private companies and two end users from seven different European countries.

Coordinator

POLITECNICO DI TORINO
Net EU contribution
€ 518 875,20
Address
CORSO DUCA DEGLI ABRUZZI 24
10129 Torino
Italy

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Region
Nord-Ovest Piemonte Torino
Activity type
Higher or Secondary Education Establishments
Links
Total cost
No data

Participants (8)

Partners (10)