Non-destructive, scalable, smart monitoring of remote cultural treasures

• Unité de recherche: SEFRI
• Numéro de projet: 23.00550

Résumé des résultats (Abstract) (Anglais)

ARGUS draws on the current challenges in monitoring remote built heritage assets and the current research focus on preventive preservation, and envisions the development of: (a) a novel built heritage digital twin model to support multi-scale/modal data; (b) an advanced digitisation strategy to support the digital twin model; (c) a portable measurements system for non-descructive physical and chemical monitoring based on miniaturised sensors, and sensor composites integration, comprising of ground and aereal components; (d) AI-enabled methods for the modeling and identification (reverse engineer) of threat factors and their impact; (e) AI-powered multimodal data methods for the fusion of (i) remote sensing climate, weather and pollution data with (ii) natural disaster regional statistics, (iii) governmental statistics (ii) on-site acquired measurements; (f) Trustworthy AI decision support methods for the preventive preservation of built heritage. ARGUS’ innovation targets: (a) Researchers/academics: data from the ARGUS monitoring systems, long-term status processed data, the novel multimodal digital twin white paper, multidimensional/modal data visualisations, APIs. (b) Stakeholders/heritage managers/practitioners: real-time monitoring, long-term status analysis, predictive preser¬vation predictions, intervention decision support. (c) Authorities: real-time monitoring, long-term status analysis, predictive preservation strategies. (d) General public: real-time visualisations, crowdsourcing and citizen contribution in preventive preservation, citizens-in-the-loop R&I design with Living Labs and Hackathons.