Periodic Reporting for period 1 - ARGUS (Non-destructive, scalable, smart monitoring of remote cultural treasures)
Reporting period: 2023-12-01 to 2024-11-30
Remote heritage sites face threats from human activity (e.g. unregulated tourism, looting, pollution), natural disasters (earthquakes, floods, wildfires, invasive species), and climate change (erosion, extreme weather). These factors interact, amplifying risks and requiring interdisciplinary collaboration for mitigation.
ARGUS addresses these challenges by developing:
(a) A digital twin for multi-scale/modal data,
(b) Advanced digitization strategies,
(c) Portable sensor systems for non-destructive monitoring,
(d) AI-driven threat modeling and impact analysis,
(e) AI-powered fusion of climate, disaster, and on-site data,
(f) Trustworthy AI decision support for preventive preservation.
ARGUS collects data from historical records, case studies, literature, and in-project measurements to benefit researchers, heritage managers, authorities, and the public through real-time monitoring, predictive preservation, and citizen engagement.
ARGUS addresses these challenges by developing:
(a) A digital twin for multi-scale/modal data,
(b) Advanced digitization strategies,
(c) Portable sensor systems for non-destructive monitoring,
(d) AI-driven threat modeling and impact analysis,
(e) AI-powered fusion of climate, disaster, and on-site data,
(f) Trustworthy AI decision support for preventive preservation.
ARGUS collects data from historical records, case studies, literature, and in-project measurements to benefit researchers, heritage managers, authorities, and the public through real-time monitoring, predictive preservation, and citizen engagement.
ARGUS has completed its first 12 months, achieving significant progress in defining its foundational methodologies, designing initial system components, and engaging with stakeholders and the public. The project has successfully established its coordination and management structures, ensuring smooth collaboration among the consortium partners. During this period, ARGUS has focused on data collection and analysis, multimodal integration design, system architecture design, and pilot preparation. The first phases of the project concentrated on defining requirements, conducting gap analyses, and aligning technological advancements with end-user needs. This has resulted in the delivery of key milestones, including the Risk Management Plan, the Data Management Plan, the first set of pilot site assessments, and initial work on the digital twin framework. From an administrative perspective, regular technical and management meetings have taken place, ensuring that all work packages (WPs) remain on schedule. Two plenary meetings have been held in Athens and Rome, and a third is scheduled to take place in January 2024, in Madrid, facilitating discussions on project direction, risk mitigation strategies, and technical alignment. Despite minor challenges related to data heterogeneity and pilot site logistics, ARGUS remains well-positioned to meet its long-term objectives, with work now shifting towards technology validation, systems refinement, and stakeholder engagement in the upcoming months. As ARGUS is designed to work on a 6-month milestone model, two milestones have been met during the 12-month reporting period. In particular:
Milestone 1 (MS1) on Month 6 (M6): MS1 marked the successful initiation of the project work, established the project identity and web presence, the definition of the current situation, gap analysis and user requirements, the pilots design, and the complete Data management Plan. MS1 was related to several important deliverables: D1.1. Data management plan (DMP, SEN), D2.1. Current situation, gap analysis, user requirements (R, SEN), D6.1 (Draft). Pilots’ preparation report (R, SEN), D7.1. Project Website and material (DEC, PU). Milestone 2 (MS2) on Month 12 (M12): MS2 marked the completion of the historical data collection framework, and the initial steps in the development of the new digital twin data model and the data model fusion methods, along with a draft layout of the best practices, requirements, KPIs, architecture and IA plan. MS2 also marked the completion of the 1st year of dissemination, exploitation, communication actions. MS2 is related to deliverables: D3.1. Data historicity and migration framework (R, SEN), A progress report on T2.2-6 T5.1-2 and T7.1-3,5.
Milestone 1 (MS1) on Month 6 (M6): MS1 marked the successful initiation of the project work, established the project identity and web presence, the definition of the current situation, gap analysis and user requirements, the pilots design, and the complete Data management Plan. MS1 was related to several important deliverables: D1.1. Data management plan (DMP, SEN), D2.1. Current situation, gap analysis, user requirements (R, SEN), D6.1 (Draft). Pilots’ preparation report (R, SEN), D7.1. Project Website and material (DEC, PU). Milestone 2 (MS2) on Month 12 (M12): MS2 marked the completion of the historical data collection framework, and the initial steps in the development of the new digital twin data model and the data model fusion methods, along with a draft layout of the best practices, requirements, KPIs, architecture and IA plan. MS2 also marked the completion of the 1st year of dissemination, exploitation, communication actions. MS2 is related to deliverables: D3.1. Data historicity and migration framework (R, SEN), A progress report on T2.2-6 T5.1-2 and T7.1-3,5.
There are no results beyond the state of the art at this stage.