Argus project

Outdoor photovoltaic-power generation scene.

A remote monitoring revolution to pioneer the future of cultural heritage preservation

Remote heritage sites are often vulnerable to a variety of environmental and anthropogenic factors that can cause damage or even destroy these important cultural and historical landmarks.

Three key factors affect remote heritage sites and monuments:

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Human activity

Our activities can cause both direct impacts (unregulated tourism, looting, construction and development of infrastructure and other buildings) and indirect impacts (air pollution, density of population, natural resource exploitation, etc).

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Natural disasters

Earthquakes, hurricanes, floods and other natural disasters such as fires can cause significant damage to heritage sites. Invasive species of plants and animals can also cause significant damage to heritage sites

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Climate change

Climate change is crossing the boundaries of anthropogenic and natural factors and is widely recognized as one of the major threats to heritage sites. Changes in temperature and precipitation patterns can cause physical damage to heritage sites, such as erosion, landslides, and flooding

Researchers are now focusing on the effects of those factors that might interact with each other and amplify their impact on the degradation of materials and weakened structures.

Effective preventive, protective and mitigative strategies require communities, governments, and experts across disciplines to work together.

Preserving Cultural Legacies

Asian archaeologist works on a pyramid pharaoh research in Giza, Cairo

With a focus on preventive preservation, ARGUS pioneers an innovative approach to safeguarding our shared history through the power of cutting-edge technology and collective action.

ARGUS envisions the development of:

  • A portable measurements system for non-destructive physical and chemical monitoring based on miniaturised sensors;
  • A digital twin model that aids in handling diverse data across various scales and modes, backed by an advanced digitization approach;
  • AI-driven techniques for modelling and identifying threat factors and their impacts, integrating multimodal data including remote sensing climate, weather, and pollution data with natural disaster statistics and governmental on-site measurements.
  • Trustworthy AI decision support methods for the preventive preservation of built heritage.

Targeting researchers, stakeholders, authorities, and the public, ARGUS promises real-time monitoring, long-term analysis, and innovative strategies to safeguard our cultural heritage.


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At the core of ARGUS there is the multimodal data management system that consists of three main data sources and one secondary source from the citizen’s co-creation involvement. The main sources are:

  • The existing documentation (which may include a variety of data forms) that will be filtered and transformed to the data forms in ARGUS;
  • The multichannel satellite data;
  • The multimodal sensor data for area-/point-wise non-destructive measurements on monuments.

Those data will empower the development of the new ARGUS digital twin for remote built heritage, that will support the creation of complex visualisations and decision support. Citizens will also contribute to the design and validation of the management system with the implementation of Living Labs and Hackathons.

Pilot sites

ARGUS is distinguished by its selection of diverse pilot sites, each with its own unique story and conservation challenges. ARGUS builds and tests on extremely distinct pilot sites targeting to support a wide range of challenges for built heritage preservation.

ARGUS Techniques for Heritage Preservation

Preventive preservation refers to a strategic approach towards more sustainable preservation, taking advantage of regular monitoring with the aim to slow down the process of decay and better retain the cultural significance associated. Application of preventive preservation strategies allows a better preservation and a reduction of costs linked to conservation activities. Preventive protection may be extended by integrating citizen participation, by including citizens in the design loop, and raising awareness in heritage protection and sustainable development. ARGUS proposes a multimodal, multi-dimensional research and innovation in the preventive protection of remote heritage monuments.

ARGUS’ modules to support the multimodal remote monitoring strategy

Renovation of the old church. Architect and engineer taking measurements in the field

Multimodal digital twin ontology and advanced digitisation

Risk scenarios will be designed upon the novel digital twin model through the integration of multi-dimensional spatiotemporal data, time-series data, remote sensing data, sensor measurements, expert knowledge, and supplementary support data. ARGUS proposes a novel remote-built heritage digital twin model beyond the state of the art.

Aerial view of Belvoir Fortress ruins in Israel

Multimodal on-site sensing for built heritage assessment, monitoring and preventive preservation

ARGUS proposes a dynamic ground and airborne monitoring system integrating environmental sensors (for dust, pollution and greenhouse gases) with specific infestation detection methods (for insects, for example) and the monitoring of internal conditions of the structures at selected conditions (of temperature and humidity).

ARGUS proposes a pipeline for the automatic generation of damage augmented Finite Element models (beyond SotA) based on images obtained on-site. To achieve this, ARGUS advances the SotA by i) developing a non-supervised machine learning model for identifying out-of-plane deformation and cracking, ii) correlating cracking with mechanical properties degradation and iii) automating the generation and calibration of Finite Element models considering existing damage. Those three tasks, currently treated separately, are the necessary conditions for using numerical simulation to assess structural damage in its different manifestations (e.g., cracking, crushing, material loss, residual deformations), typically based on computer vision and deep learning.

Current crack evolutions measurements use permanently installed devices, altering the monument aesthetics and with the risk of being disrupted by weather conditions or human/animal activity. ARGUS proposes the monitoring and kinematic characterization of cracks opening through time-based on aerial images to monitor crack propagation through time.

Multispectral thermal imaging is a non-invasive imaging technique that requires the use of camera sensors sensitive to the thermal range beyond the visible spectrum. ARGUS proposes new portable multispectral imaging systems for ground and aerial deployment to target the standardization of data structures and datasets in the domain.

ARGUS will heavily rely on Fibre Bragg Grating technology, a fibre optic sensor, to ensure low/zero noise high-speed sensor connectivity and data transfer built into all portable system models for measurements and adapted to the requirements of remote built heritage. The Bragg fibre can be fixed locally for continuous monitoring as an integrated sensor or be a part of a portable system, and it does not need to be powered by electrical current in the detection area, allowing it to be installed in critical environments.

AE technology is a non-destructive inspection technique that allows both real-time monitoring and prediction of the behaviour of the studied target. The energy dissipation produced by AE events is basically due to phase transformation, crack formation and growth, friction, or moving dislocations, and signals may also be generated by leaks, cavitation, solidification, and liquefaction. ARGUS AE research will focus on monitoring the internal structure state of the measured heritage asset, including the methods for data standardization, analysis, and transmission.

LiDAR (Light Detection and Ranging) is an active sensing technique used to perform high-resolution scanning using visible or infrared light. ARGUS proposes the integration of LiDAR and SfM (Structure from Motion) scanning with the other on-site sensing systems into the portable ground and aerial measuring composite system. SfM will be applied in a ground and aerial mode in ARGUS, where integration with the other sensing systems will be sought.

ARGUS proposes the integration and miniaturization of several different sensors and sensor techniques towards a novel portable sensor composite capable of ground and aerial deployment. The accompanying software will be web-based, secure, and facilitate real-time device and network management. The overall development of the monitoring systems will comply with the “do no significant harm” regulations, by using eco-friendly materials, when possible, and by minimizing the overall power consumption. Sensors will be used to gather data relating to monitoring critical parameters of remote built heritage.

Drone near churc

Remote sensing of heritage sites for assessment, monitoring and preventive preservation

Geophysical techniques by means of measuring the geophysical properties of the ground within and in the vicinity of cultural monuments can play a critical role in the assessment of the ground-based factors of the integrity of the cultural monuments. Thanks to remote sensing, it is possible to acquire information that can be related to the deterioration of architectural features and other archaeological elements. A multi-scalar model of risk assessment can thus be specifically designed for each site or monument.

Copernicus and OpenSkiron will be the main sources of the satellite remote sensing, providing data on meteorological variables, atmospheric composition, and air quality. In addition, ARGUS proposes the novel fusion of photogrammetric multispectral techniques—which create evidence for the existence of pockets of humidity or residues of salinity to map small fractures along the walls or the floor of monuments—with geophysical techniques, mainly electrical resistivity, ground penetrating radar imaging, and soil resistance tomography, to map the 4m subsurface and identify voids, seawater infiltration, foundation breaks, etc. This will be accompanied by the development of fusion algorithms and AI techniques for the automatic detection of features.

ARGUS proposes a coastline change modelling pipeline that will make use of aerial and satellite images of different sources, and it will be implemented as a customized Geographic Information Systems (GIS) tool to be easily used with different datasets and models. Automation will be targeted to be generally applicable general applicability to more coastal sites. The long-term shoreline displacement impact will be examined under the prism of the risk suffered by coastal cultural heritage monuments and sites. Also, grain size analysis will be performed on sand samples, to identify the material equilibrium of the coastline from the sediment transportation. The monitoring and recording of changes in the coastline will also be used in the calibration of the coastline change model.

Urbanization impacts heritage sites directly, typically as a result of population increase, migration, and infrastructure improvements, in a fast and usually uncontrolled development. Multi-temporal satellite databases will be tested for monitoring urban expansion. Future projections can be processed to identify any future urban pressure on cultural heritage sites, based on cellular automata approaches.

Soil erosion is a common issue globally. To anticipate soil erosion, soil erosion models are crucial. Although the process is complex, several models have been put forth to help with improved measurement and forecast of soil loss. ARGUS will implement the Revised Universal Soil Loss Equation (RUSLE) methodology based on remote sensing data and products, supporting stakeholders in cases where no in-situ calibration data exist, or no other geological-meteorological data are available. Satellite-based products can be used instead as proxies in these areas, to estimate the threat to a site.

AE technology is a non-destructive inspection technique that allows both real-time monitoring and prediction of the behaviour of the studied target. The energy dissipation produced by AE events is primarily due to phase transformation, crack formation and growth, friction, or moving dislocations. Signals may also be generated by leaks, cavitation, solidification, and liquefaction. ARGUS AE research will focus on monitoring the internal structure state of the measured heritage asset, including the methods for data standardization, analysis, and transmission.

ARGUS proposes the automatic detection of flooded areas, exploiting the high temporal resolution of the Sentinel-1 (beyond state-of-the-art), attaining a systematic mapping of flooded areas and providing statistical evidence on the ARGUS pilots. For a rapid and straightforward processing workflow, Sentinel-1 data will be processed, followed by scene calibration, and terrain correction for topographic distortions, until converting every dataset into a single-band image.

ARGUS proposes the use of cloud services such as the Hyp-3 platform and the European Ground Motion Service to support the analysis of ground displacement, including the processing of high-resolution radar datasets such as Cosmo Sky towards the successful modelling of ground movements due to earthquakes. High coherence between the image acquisitions is crucial for the interferometric analysis's requirements, a measurement method using the phenomenon of interference of light, sound, or radio waves.

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Multimodal and multidimensional data fusion and visualization

ARGUS will build upon hybrid intermediate data fusion approaches based on deep learning architectures, particularly for heritage asset management and will create a multimodal multi-layered GIS-like visualisation that will greatly aid in providing more intuitive heritage asset visualisations and aligned data representations for Open Science applications through APIs. ARGUS will proceed towards a novel hybrid method to account for the diversity of the data. This will enable the complex visualisation required for the visual representation of the novel remote heritage digital twin model and will be the basis for the decision support.

3D Wireframe Castle Render with Blue Light Beam

Decision support (DSS) in preventive preservation of remote built heritage

The ARGUS DSS is envisioned as a hybrid fusion of multiple models encompassing the best from different approaches, targeting effectiveness and sustainability. ARGUS will build on its multimodal multi-dimensional data fusion, bridging GIS, remote sensing, environmental, climatic, on-site (ground and aerial) sensing, including many physical quantities. The DSS will provide diagnosis of the status and predictions for early warnings with quantified assessments, including recognition of damage and assessment of risks from multiple modalities (e.g., flooding and soil erosion risk, salt-weathering, temperature extremes, intense rainfall, erosion, landslides, tectonic activity, etc.). The vulnerability model will be able to be adjusted to the needs of the specific monuments through parametrisation.

Citizen science

Within ARGUS, citizen science will be crucial to the collection of the extensive monitoring data underlying curative preservation. A specific program of citizen science activities will be carried out, involving the design and implementation of citizen involvement activities. This will include the organization of several Living Labs, targeting the awareness raising in the factors influencing the status of the remote built heritage and integrating co-design approaches in ARGUS’ workflows. Additionally, the organization of Hackathons will rely on the ARGUS open data and APIs to attract cross-disciplinary participation and open lab approaches.

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Millions €

Meet the Partners

Cyprus University of Technology
University of Cyprus
Roma Tre Universitat Degli Studi
Fraunhofer FIT
World Sensing
Ephorate of Antiquities of Cyclades
Centro Conservazione Restauro La Venaria Reale

Project Workpackages

Project Progress

Project and Technical Management

Leader: ATHENA
Month: 1-36


Requirements, Specifications, Architecture

Leader: ATHENA
Month: 1-36


Data collection framework

Month: 1-24


Technology Miniaturisation and Integration

Leader: World Sensing
Month: 1-30


Models and Trustworthy AI Solutions

Leader: Fraunhofer
Month: 1-36


Technology validation pilot demonstrators

Leader: University ROMA 3
Month: 1-36


Dissemination, exploitation, and impact creation

Leader: KNEIA
Month: 1-36