Periodic Reporting for period 1 - ERA4CH (Earthquake Risk plAtform For european cities Cultural Heritage protection)
Reporting period: 2023-01-01 to 2024-12-31
Seismic movements significantly impact the structural stability of Cultural Heritage, often characterized by outdated construction methods and materials, despite high population density. Risk information is essential to reduce vulnerability, minimize economic losses, and assist disaster managers and cultural heritage professionals in designing effective mitigation measures to lower restoration costs and casualties.
The ERA4CH project develops tools that integrate Artificial Intelligence with structural stability models, advanced remote sensing, image processing, geotechnics, and cadastral data in a GIS application for assessing damage and monitoring historic centers.
This innovative methodology facilitates effective monitoring and management of historic centers to mitigate the effects of catastrophic events, allowing for preventive interventions in areas likely to experience the most damage. Three representative test cases are: Narni (Italy), a UNESCO candidate site; the historical center of Chania (Greece); and Strovolos (Nicosia, Cyprus).
Objective #1: Development and Integration of Methodologies
AI will enhance the application of structural stability models for entire historical centers. A library of simplified structural stability models will be used to derive fragility curves and resilience parameters. These models will account for local soil conditions affecting seismic responses. An AI software will analyze building façades using image processing and machine learning to automate the classification of resilience-related civil engineering parameters, feeding this data into the stability models. Data can be gathered through crowdsourcing with citizen-captured images and resources like Google Street View or UAV surveys. Copernicus services and ground sensors will be utilized for dynamic monitoring of soil instabilities and building movements, focusing on InSAR mapping and Lidar scanning.
Objective #2: Platform Development and Deployment
The aim is to create the ERA4CH Platform (GIS-based) that integrates AI image processing, remote sensing methods, ground data, and risk models for earthquake risk forecasting in cultural heritage sites. The platform will combine traditional Earth Observation methods with innovative risk modeling and AI tools to create a pre-operational service. It will extend structural stability models to all buildings in the study area, producing earthquake risk maps. This multi-task platform will merge EO and in-situ data, including terrestrial and aerial RS data and crowdsourced information, featuring a shared repository and a GIS interface.
Objective #3: Demonstration and Validation of the Methodology
The objective is to demonstrate and validate the ERA4CH Platform at three case studies: Narni, Chania, and Strovolos. These locations are strategically selected due to their exposure to seismic risk in Southern and Central Europe. Validation will occur in areas with relevant data from past earthquakes. ERA4CH combines expertise from research centers and SMEs across disciplines, including civil and geotechnical engineering, IT, remote sensing, and EO applications, fostering knowledge exchange and the development of novel techniques and tools for cultural heritage.
The ERA4CH project develops tools that integrate Artificial Intelligence with structural stability models, advanced remote sensing, image processing, geotechnics, and cadastral data in a GIS application for assessing damage and monitoring historic centers.
This innovative methodology facilitates effective monitoring and management of historic centers to mitigate the effects of catastrophic events, allowing for preventive interventions in areas likely to experience the most damage. Three representative test cases are: Narni (Italy), a UNESCO candidate site; the historical center of Chania (Greece); and Strovolos (Nicosia, Cyprus).
Objective #1: Development and Integration of Methodologies
AI will enhance the application of structural stability models for entire historical centers. A library of simplified structural stability models will be used to derive fragility curves and resilience parameters. These models will account for local soil conditions affecting seismic responses. An AI software will analyze building façades using image processing and machine learning to automate the classification of resilience-related civil engineering parameters, feeding this data into the stability models. Data can be gathered through crowdsourcing with citizen-captured images and resources like Google Street View or UAV surveys. Copernicus services and ground sensors will be utilized for dynamic monitoring of soil instabilities and building movements, focusing on InSAR mapping and Lidar scanning.
Objective #2: Platform Development and Deployment
The aim is to create the ERA4CH Platform (GIS-based) that integrates AI image processing, remote sensing methods, ground data, and risk models for earthquake risk forecasting in cultural heritage sites. The platform will combine traditional Earth Observation methods with innovative risk modeling and AI tools to create a pre-operational service. It will extend structural stability models to all buildings in the study area, producing earthquake risk maps. This multi-task platform will merge EO and in-situ data, including terrestrial and aerial RS data and crowdsourced information, featuring a shared repository and a GIS interface.
Objective #3: Demonstration and Validation of the Methodology
The objective is to demonstrate and validate the ERA4CH Platform at three case studies: Narni, Chania, and Strovolos. These locations are strategically selected due to their exposure to seismic risk in Southern and Central Europe. Validation will occur in areas with relevant data from past earthquakes. ERA4CH combines expertise from research centers and SMEs across disciplines, including civil and geotechnical engineering, IT, remote sensing, and EO applications, fostering knowledge exchange and the development of novel techniques and tools for cultural heritage.
The ERA4CH project aims to enhance the resilience of cultural heritage against seismic risks by integrating advanced methodologies and tools. Key objectives include defining user requirements, analyzing seismic risk methodologies, and developing an AI-enabled platform for risk assessment and monitoring.
Achievements include identifying high-level user needs from stakeholders, discussing scientific requirements related to structural stability models, and developing AI software for building façade analysis. The project has also focused on crowdsourcing data collection methods and introduced Rapid Visual Screening (RVS) for efficient assessments of heritage buildings while emphasizing the importance of non-destructive evaluation techniques. The ERA4CH mobile application, designed for rapid in-situ building assessment, is currently under development and testing. This tool integrates AI and computer vision models with structural stability forms, ensuring user-friendliness.
Future activities involve the ongoing development of the ERA4CH platform, integrating structural stability and AI models, and field testing a mobile application designed for cultural heritage risk assessment and forecasting.
Achievements include identifying high-level user needs from stakeholders, discussing scientific requirements related to structural stability models, and developing AI software for building façade analysis. The project has also focused on crowdsourcing data collection methods and introduced Rapid Visual Screening (RVS) for efficient assessments of heritage buildings while emphasizing the importance of non-destructive evaluation techniques. The ERA4CH mobile application, designed for rapid in-situ building assessment, is currently under development and testing. This tool integrates AI and computer vision models with structural stability forms, ensuring user-friendliness.
Future activities involve the ongoing development of the ERA4CH platform, integrating structural stability and AI models, and field testing a mobile application designed for cultural heritage risk assessment and forecasting.
The development of the ERA4CH mobile application for rapid visual building assessment represents a significant advancement in the integration of new AI methodologies into the field of seismic risk evaluation of buildings. This innovative tool automates the inspection process, enhancing efficiency and accuracy by leveraging machine learning algorithms to analyze building facades in real time. The mobile application not only streamlines the assessment workflow but also facilitates quick and effective evaluations of structural integrity, which is crucial in mitigating seismic risks.
However, further research is necessary to integrate additional AI techniques and refine structural stability models within the application. This enhancement will improve the application's capabilities and its overall reliability in real-world scenarios. The consortium is actively exploring these avenues to ensure that the mobile application remains at the forefront of technological development in building assessment.
A demonstration of the mobile application is scheduled to take place at a training conference in Spring 2025, providing an opportunity for stakeholders to witness its capabilities firsthand and engage with the technology. This event aims to showcase the application’s effectiveness and gather feedback, which will be invaluable for future improvements.
However, further research is necessary to integrate additional AI techniques and refine structural stability models within the application. This enhancement will improve the application's capabilities and its overall reliability in real-world scenarios. The consortium is actively exploring these avenues to ensure that the mobile application remains at the forefront of technological development in building assessment.
A demonstration of the mobile application is scheduled to take place at a training conference in Spring 2025, providing an opportunity for stakeholders to witness its capabilities firsthand and engage with the technology. This event aims to showcase the application’s effectiveness and gather feedback, which will be invaluable for future improvements.