ART-RISK Project: Artificial Intelligence Applied to the Preventive Conservation of Heritage Buildings
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The main objective of the ART-RISK project: "Artificial Intelligence Applied to the Preventive Conservation of Heritage Buildings" is to conduct research to create a computerised tool for the preventive conservation of heritage in urban centres, based on artificial intelligence models, and make it available to organisations and companies dedicated to restoration and rehabilitation.
For its development, a new method of analysis for the vulnerability and risk of unique buildings is proposed, which will bring together multidisciplinary teams specialising in the protection and conservation of historic built heritage from the following fields: Chemistry, Architecture, Archaeology, Conservators-Restorers, Art History, Geology, Biology, Mathematics, and Computer Science.
The novelty of this CHALLENGE lies in its approach and its result, a registered open-source software tool to evaluate decision-making in land-use planning policies, urban planning, and historic heritage management. For the first time, a cross-cutting approach will be applied, encompassing the heritage, urban, architectural, and cultural value, along with an analysis of the environmental context and the socio-demographic situation of the site, to enable decision-making based on scientific criteria, thus minimising the risks of heritage loss.
This project will develop a new predictive model based on fuzzy logic (using XFUZZY 3.3), which for the first time includes a multi-scenario study, evaluating environmental risks, climate change, building usage levels, and static structural risks, alongside historical data from the monuments' lifespan, using historical series and assessing the degree of impact through pre-vulnerability matrices (array cluster). The aim is to evaluate this system for at least two types of buildings widely found in Spain (churches, walls, and bastions). To validate the two model types, a blind interlaboratory diagnostic exercise will be carried out to determine if the prediction aligns with the decisions of independent working groups.
The expected outcome is a new Artificial Intelligence programme that will replicate human reasoning and the relationships between vulnerability factors, risk factors, and historical monument parameters using fuzzy set theory. All results will be included in an open-access application and will be available to the general public, heritage management authorities, and companies dedicated to rehabilitation. Additionally, this system will be fed by user contributions to update the historical series, creating a continuous feedback loop for ongoing improvement.
The work plan has its own dissemination and transfer objective, involving international PhD holders and professionals from the heritage management and conservation sector across various countries.
ART-RISK Project awarded the Europa Nostra Prize 2021:
Miembers of the ART-RISK project:
Organisations:
Generalitat Valenciana Cultura Arts IVC+R.
Universidad de Sevilla.
Universidad Pablo de Olavide.
Fundación Universitaria Popayán.
Agenzia nacionale per le nuove tecnologie, l’energia e lo sviluppo económico sostenible ENEA.
Consiglio Nazionale delle Ricerche.
Xiloscopio Conservación y Restauración.
Universidade de Aveiro.
Consejería de Cultura, Junta de Andalucía.
AGH University of Science and Technology.
Universidad Austral de Chile.
Research team members:
Pilar Ortiz Calderón: Principal Investigator of the team. Doctor in Chemistry. Professor at the University Pablo de Olavide.
Rocío Ortiz Calderón: Doctor in Architecture. Professor at the University Pablo de Olavide.
Juan Manuel Macías: Doctor in Architecture. Professor at the University of Seville.
María Auxiliadora Gómez Morón: Doctor in Chemistry. Professor at the University Pablo de Olavide.
Dolores Segura Pachón: Doctor in Biology. Professor at the University Pablo de Olavide.
María de los Ángeles Garrido Vizuete: Doctor in Mathematics. Professor at the University of Seville.
Daniel Cagigas Muñiz: Doctor in Computer Science. Professor at the University of Seville.
Ana Velosa: Doctor in Civil Engineering. Professor at the University of Aveiro (Portugal).
Maurizio Indirli: Doctor in Geology. National Agency for New Technologies, Energy, and Sustainable Economic Development (ENEA), (Italy).
Giuseppina Padeletti: Doctor in Chemistry. National Research Council (CNR), Italy.
Working team members:
José María Martín Ramírez: Geologist. Master's in Lasers and Applications in Chemistry. Professor at the University Pablo de Olavide.
Arturo Pérez Plaza: Archaeologist. Master's in Architecture and Historical Heritage. Technical Advisor for Archaeology, General Directorate of Cultural Assets and Museums, Ministry of Culture, Regional Government of Andalusia.
Gemma Contreras Zamorano: Doctor in Art History. Master's in Conservation Status Diagnosis of Historical Heritage. Director of the Institut Valencià de Conservació, Restauració i Investigación of the Generalitat Valenciana.
Virginia Cisternas: Architect. Specialist in Architectural Restoration. Master's in Conservation Status Diagnosis of Historical Heritage. Xiloscopio Conservation and Restoration (Valparaíso, Chile).
María Isabel Turbay: Doctor in Architecture. Master's in Conservation Status Diagnosis of Historical Heritage. Professor at Fundación Universitaria de Popayán (Popayán, Colombia).
Javier Becerra Luna: Doctor in Restoration-Conservation. Master's in Conservation Status Diagnosis of Historical Heritage. Professor at the University Pablo de Olavide.
Andrés José Prieto Ibáñez: Bachelor's in Building Construction. Master's in Comprehensive Building Management. University of Seville.
Julia Benítez Jiménez: Environmental Scientist. Master's in Conservation Status Diagnosis of Historical Heritage. University Pablo de Olavide.
Ana María Tirado Hernández: Environmental Scientist. Master's in Conservation Status Diagnosis of Historical Heritage. University Pablo de Olavide.
