Sensor-Driven Preventive Preservation in Remote Built Heritage: A Threat-to-Sensor Approach

Sensor-Driven Preventive Preservation in Remote Built Heritage: A Threat-to-Sensor Approach George Pavlidis∗, Vasileios Sevetlidis∗, Vasileios Arampatzakis∗, Sof´ ıa Aparicio†, Fernando Ramonet†, Laura Puigpinos Blazquez‡, Marcel Janer‡, Richard Ahorsu‡, Angela Lluch§, Ignasi Garcia Mila§ ∗Athena Research Center, Xanthi, Greece {gpavlid, vasiseve, vasilis.arampatzakis}@athenarc.gr †Spanish National Research Council (CSIC), Madrid, Spain {sofia.aparicio, fernando.ramonet}@csic.es ‡EURECAT, Barcelona, Spain {laura.puigpinos, marcel.janer, richard.ahorsu}@eurecat.org §Worldsensing, Barcelona, Spain {alluch, igarciamila}@worldsensing.com Abstract—Remote built heritage sites face increasingly complex threats from climate, environment, and human activity, challenging traditional preservation methods. The ARGUS EU project introduces a novel, sensor-driven strategy for preventive preservation, tailored to remote and infrastructure-poor heritage contexts. This paper presents the threat-to-sensor mapping framework developed in ARGUS, aligning sensor types with sitespecific preservation risks. By combining heterogeneous sensing modalities, low-power communication protocols, and riskinformed design, the system supports actionable early warnings and long-term monitoring. Deployments across five pilot sites address key preservation threats: structural deformation, freeze–thaw cycles, environmental degradation, and biological growth. We describe the sensor selection rationale, installation strategies, and early operational insights across varied heritage contexts. Index Terms—Cultural Heritage, Preventive Preservation, Environmental Monitoring, Wireless Sensor Networks, Ontology, Built Heritage I. INTRODUCTION Preventive preservation is increasingly recognized as a cost-effective and ethically aligned approach to preserving cultural heritage assets, particularly in the face of mounting environmental pressures and climatic instabilities. Rather than intervening after damage occurs, preventive preservation aims to mitigate risks in advance through monitoring, environmental control, and informed decision-making. This paradigm becomes particularly crucial for built heritage in remote or infrastructurally fragile locations, where both the accessibility and responsiveness of traditional preservation measures are limited. Recent advances in sensor technologies and wireless communication protocols have enabled new opportunities for deploying smart monitoring systems in cultural heritage contexts. Several notable initiatives have demonstrated the feasibility of using wireless sensor networks (WSNs) for condition monitoring and structural health assessment in historical buildings and archaeological sites. For instance, the permanent WSN deployment described by Zonta et al. [1] and the MEMSCON project detailed by Torfs et al. [2] explored embedded MEMSbased sensors and low-power wireless communication for continuous structural monitoring. Other efforts, such as the San Gimignano case study by Mecocci et al. [3], integrated WSNs for environmental data collection to support heritage conservation. The HERACLES project further emphasized semantic frameworks and interdisciplinary integration to improve decision-making for cultural heritage resilience [4]. Nonetheless, a gap remains in extending these approaches to remote sites—often off-grid, exposed to multiple interacting threats, and lacking baseline digital infrastructure. Current literature lacks robust examples where sensor selection is not generic but tailored to preservation priorities, such as freeze–thaw degradation, air pollution-induced corrosion, biological colonization, or slow geostructural movements. Additionally, few deployments address long-term energy autonomy and communication latency under real-world heritage constraints. The ARGUS project addresses this gap through a multi-site, cross-disciplinary implementation of risk-informed monitoring strategies, underpinned by realistic environmental constraints. ARGUS focuses on identifying critical degradation drivers for each pilot site and deploying sensors adapted not only to the threats but also to the site’s specific architectural, logistical, and regulatory parameters. This builds upon prior work in remote condition monitoring, such as the modular environmental kits used in the EU STORM project [5], and complements newer initiatives like the ARCH project [6], which also target resilience through data fusion but lack the deep site-specific sensor tailoring of ARGUS. This paper presents the threat-informed methodology and deployment framework developed in ARGUS, covering five European heritage sites: Delos (GR), Ranverso (IT), Baltan´ as (ES), Lucreteli (IT), and Schenkenberg (CH). Section II introduces the threat-to-sensor mapping methodology that underpins all sensor design decisions. Section III presents the preservation rationale and site-specific sensor selection strategy. Section IV describes the deployment architectures and cross-site configurations. Section V discusses technical challenges and early operational insights. Section VI concludes with lessons learned and future directions for real-world preventive preservation systems. II. THREAT-TO-SENSOR MAPPING METHODOLOGY The cornerstone of the ARGUS monitoring strategy is a threat-to-sensor mapping methodology: each preservationrelevant threat is matched with one or more sensing modalities that can detect, characterize, or anticipate its material impact. This risk-first approach distinguishes ARGUS from generic environmental monitoring frameworks, many of which focus on collecting broad environmental datasets without aligning with specific preservation threats [7], [8]. The methodology follows four core stages: 1) Threat Identification: Site-specific degradation threats—such as freeze–thaw stress, salt efflorescence, structural movement, or biological colonization—are identified through expert consultation, historical records, and heritage diagnostics. Similar risk-mapping strategies have been employed in the HERACLES [9] and STORM [10] projects, which emphasized the need to translate preservation scenarios into technical monitoring needs. 2) Risk Prioritization: Not all threats are equally urgent. ARGUS uses contextual indicators (e.g., microclimate variability, degree of isolation, presence of vulnerable materials) to prioritize threats based on likely impact and monitoring feasibility. The value of this step is echoed in frameworks such as the CHRESP approach [11], which highlight the role of risk weighting in designing resilience interventions. 3) Sensor-Parameter Matching: For each prioritized threat, relevant physical proxies are identified and mapped to sensor types. This includes temperature and RH for condensation, UV for pigment fading, acoustic emission and FBG (Fiber Bragg Grating) for microcracking, and multispectral imaging for assessing vegetation growth and biological agent infestation [12], [13]. Prior studies have recommended this parameter-level translation to enhance actionable monitoring [14], [15]. 4) Deployment Modeling: ARGUS further considers installation constraints and data pathways, using 3D models or LoRaWAN propagation maps where necessary. This phase ensures that sensors are placed with respect to both monitoring needs and built heritage integrity [16]. To implement preservation-aware sensing, ARGUS adopts a risk-informed design paradigm inspired by frameworks such as CHRESP and HERACLES. For each site, threat identification is followed by risk prioritization based on both impact likelihood and site fragility. Parameters such as climatic variability, material sensitivity, and heritage value weighting influence this prioritization. For instance, Schenkenberg’s freeze–thaw cycles were prioritized due to frequent environmental transitions and known impact on masonry joints. Sensor selection and placement were then optimized using this threat prioritization combined with practical feasibility (e.g., power, connectivity, invasiveness). III. PREVENTIVE PRESERVATION RATIONALE AND SENSOR SELECTION CRITERIA Building on the threat-to-sensor mapping methodology introduced in the previous Section, this section outlines how sitespecific preservation needs guided sensor selection and deployment design. ARGUS adopts a threat-oriented approach to preventive preservation, in which sensor deployments are directly informed by degradation drivers identified at each heritage site. Rather than applying a generic sensor suite, ARGUS focuses on aligning sensing capabilities with site-specific risks such as structural instability, hydrometeorological stress, biological colonization, or pollutant exposure. This alignment ensures that sensor data directly supports preservation decisions. A. Preservation-Driven Monitoring Priorities Each pilot site underwent a heritage risk assessment, identifying the most urgent threats to material integrity. For instance: •Delos (GR): UV radiation and salt-laden humidity contribute to surface erosion and pigment fading. •Ranverso (IT): Capillary rising damp and freeze–thaw cycles degrade frescoes and cause salt efflorescence. •Baltan´ as (ES): Soil moisture variations affect underground structures and accelerate microbial growth. •Lucreteli (IT): Land movement and root pressure threaten wall stability and buried elements. •Schenkenberg (CH): Structural cracks due to mechanical stress and micro-seismic activity are of concern. B. Sensor Selection Criteria Sensors were selected based on the following criteria: •Threat relevance: Only sensors capable of monitoring parameters directly or indirectly tied to known preservation threats were included (e.g., crackmeters for displacement, thermohygrometers for condensation control or wind speed that might translate into erosion and/or movement of built elements). •Material compatibility: All sensors in contact with heritage surfaces are non-invasive or reversible, and installations comply with conservation ethics. •Energy autonomy: Many sites lack permanent power. Battery-powered, solar-fed, or ultra-low-power sensors were prioritized. •Connectivity constraints: LoRaWAN and hybrid communication architectures were favored for long-range, low-bandwidth data collection, which allow simple and scalable network deployments with a low communication latency. •Ease of deployment and maintenance: Sensors were evaluated based on their mechanical footprint, installation complexity, suitable specifications (output signal, power demand, range), and data reliability in non-laboratory settings. Maintenance considerations included the need for recalibration in situ and long-term drift, as highlighted in heritage IoT deployments such as [7]. C. Sensor Typology and Threat Mapping A detailed plan for the deployment of environmental and structural sensors is currently being finalized, organized as follows: •Environmental Sensors: Temperature, relative humidity, air pollutants (NO2, SO2, CO2, VOCs), wind speed, air flow, rainfall, pyranometers, UV/lux sensors, water level sensors. Used for identifying conditions able to trigger or promote soil/structural instability, material decay or biological growth. •Material-Embedded or Wall-mounted Sensors: Crackmeters, moisture probes, freeze–thaw thermistors, tiltmeters, GNSS sensors. Targeted toward detecting early signs of structural failure or infiltration. •Acoustic and Vibration Sensors: Used for tracking stress accumulation, micro-cracking, and potentially biological activity (e.g., woodworms). These sensors will be combined to capture acoustic events and correlate them with physical phenomena, enabling a more comprehensive understanding of degradation processes [17]. •Imaging Devices: A multimodal imaging device was developed that integrates multispectral and thermal cameras, allowing data to be captured for the determination of the Normalized Difference Vegetation Index (NDVI) and Canopy Temperature Depression (CTD) in a single system for assessing plant health. •Presence/Occupancy Sensors: PIR sensor or other type of sensor (yet to be determined) that enables the monitoring of visitors entering sensitive archaeological sites that could lead to their accelerated degradation. The selected sensor configurations reflect a trade-off between precision, energy budget, and preservation goals, ensuring ARGUS offers a realistic pathway toward scalable preventive heritage monitoring. A schematic representation of this mapping logic is presented in Fig. 1, illustrating how threats are translated into physical parameters and aligned with specific sensing technologies. IV. SITE DEPLOYMENT OVERVIEW Sensor deployments across the five ARGUS pilot sites are being configured in collaboration with local heritage authorities, and technical partners. Each deployment balances three factors: (a) threat coverage, (b) physical installation constraints, and (c) energy and data transmission feasibility. The result is a heterogeneous but interoperable system of monitoring units tailored to preservation-critical areas. A. Pilot Sites and Deployment Strategies 1) Delos Island (GR): A remote, power-constrained archaeological site where sensors are deployed for maximum energy autonomy using batteries, solar kits, and LoRaWAN communication. The sensor suite includes UV/lux sensors, temperature and humidity sensors, PIR-based human presence detectors, air quality modules, and anemometers, in line with the deployment matrix. These support monitoring of UV exposure, temperature fluctuations, wind, and visitor presence, all of which are critical to surface erosion, pigment fading, and overall site stability. Multispectral imaging supports biological growth detection. All sensors have been selected to minimize invasiveness and maximize coverage of preservation-relevant threats. Speculative content about undecided tiltmeters and analog data loggers has been omitted to reflect the finalized matrix. 2) Sant’Antonio di Ranverso Abbey (IT): A semi-monastic complex with wall paintings and wooden artworks exposed to rising damp, UV radiation, and temperature instability. The sensor deployment includes thermohygrometers, air flow sensors, acoustic emission probes (for cracking and woodworm activity), UV/lux sensors, a pyranometer, moisture probes, tiltmeters, water level sensors, and a raingauge, all installed with minimal intervention. Air quality sensors are also included as per the matrix. Multispectral imaging and vibration sensors further support monitoring of biological growth and structural response. The sensor selection covers both environmental and structural threats, as well as hydrometeorological risks. 3) Cellar Town of Baltan´ as (ES): Underground wine cellars where humidity and air stagnation lead to microbial colonization. The sensor deployment features FBG sensors on walls, air quality modules (CO, NO2, SO2), vibration sensors, tiltmeters, internal temperature/humidity sensors, air flow sensors, and a human presence sensor. A water level sensor is included where operational. Multispectral imaging is deployed to monitor biological growth and microbial colonization. The configuration ensures that structural, environmental, and occupancy-related threats are covered, with a mixed LoRaWAN and WiFi setup for robust data transmission in the challenging underground geometry. 4) Monti Lucreteli Upland Landscape (IT): A rural heritage ensemble exposed to land shifts and overgrowth. The sensor deployment includes UV/lux sensors, air quality modules, human presence sensors, multispectral imaging for plant stress, air flow sensors, tiltmeters, GNSS sensors, and, conditionally, FBG and vibration sensors as their suitability is finalized. Environmental and structural monitoring is prioritized, with GNSS confirmed and data loggers to be determined. The configuration is designed to maximize coverage of both surface and subsurface threats with minimal speculation. 5) Schenkenberg Castle (CH): A hilltop ruin where freeze–thaw stress and structural cracks dominate. The deployment emphasizes crackmeters, thermistors, and tiltmeters to monitor structural response to environmental threats. Anemometers are included to assess wind-driven risks. Freeze–thaw cycles are mapped via in-wall and surface temperature logging. Vibration and FBG sensors are not part of the current configuration, in alignment with the deployment matrix. Preservation Threats (e.g., freeze–thaw, cracks, bio-growth) Physical Proxies (e.g., temp, RH, airflow, displacement) Sensor Types (e.g., thermistors, RH sensors, crackmeters) Fig. 1. Simplified mapping logic in ARGUS: preservation threats are translated into measurable physical proxies, which are then matched to appropriate sensor types. Fig. 2. 3D digital model of Baltan´ as underground cellar 88, used to inform sensor placement and signal propagation planning. Figure extracted from [18] Fig. 3. Ground plan of a monitored cellar in Baltan´ as with installed sensor locations and identified degradation zones. Architectural plan extracted from [19] B. Cross-Site Sensor Matrix As illustrated in Fig. 2, sensor nodes were deployed to cover zones affected by dampness, poor air circulation, and possible microbial colonization, following a threat-prioritized layout informed by the cellar geometry and risk maps. The resulting matrix illustrates the ARGUS strategy of tailoring deployments to risk maps at each site, following best practices from similar cross-site frameworks such as HeritageCARE [20] and SensMat [21], but extending them to power-constrained, intermittently connected environments. Table I summarizes the distribution of key sensor types across sites. C. Energy and Communication Architectures Power availability and connectivity varied substantially across sites: •Delos and Lucreteli: Fully off-grid. Systems rely on internal long-duration batteries, solar panels and LoRaWAN communication to minimize power draw. •Ranverso and Baltan´ as: Mixed infrastructure; both direct and battery power available. Data transfer via WiFi or local LoRaWAN gateways. •Schenkenberg: Partial coverage; some devices equipped with autonomous power kits pending full deployment. These configurations reflect a scalable, modular strategy enabling deployment in sites of varying complexity and remoteness while preserving heritage integrity. V. OPERATIONAL CHALLENGES AND PRELIMINARY OBSERVATIONS The deployment of environmental and structural sensors in heritage contexts is inherently complex due to site-specific constraints and preservation imperatives. In ARGUS, early implementation across the pilot sites has revealed valuable insights, both technical and procedural. A. Installation Constraints and Heritage Compliance Several sites presented logistical challenges stemming from regulatory protections and fragile surfaces. For example, the installation of moisture sensors at Ranverso required heritage authority clearance due to potential wall perforation. In Delos, sensor mounts had to be entirely non-invasive due to the archaeological character of the site. Custom brackets and adhesive-free anchoring methods were developed in collaboration with preservation experts. B. Energy and Environmental Exposure Power supply remains one of the most significant bottlenecks. While solar-powered kits performed reliably in Mediterranean climates (e.g., Delos, Lucreteli), shaded or enclosed sites (e.g., Baltan´ as cellars) required both direct power and, due to the complexity of the layout, it was necessary to install a second LoRaWAN gateway to ensure sufficient radio coverage, which would otherwise be inadequate. Data loggers and sensors provided by the ARGUS partners (titlmeters/GNSS) work on lithium batteries with long baterylife Sensors exposed to rain, salt, or dust must be suitable to cope with such environmental conditions. For FBG sensors and Raspberry Pibased acoustic emission devices, a stable and clean power source was essential, limiting their deployment zones. TABLE I SENSOR DEPLOYMENT MATRIX ACROSS ARGUS SITES Sensor Type Delos Ranverso Baltan´ as Lucreteli Schenkenberg TH Sensors ✓ ✓ ✓ ✓ ✓ UV / Lux ✓ ✓ ✓ Air Quality (NO2, CO, etc.) ✓ ✓ ✓ ✓ ✓ Moisture / Capillarity ✓ ✓ ✓ ✓ Crackmeters ✓ ✓ ✓ Acoustic Emission ✓ ✓ (✓) Multispectral Imaging ✓ ✓ ✓ ✓ Tiltmeters / GNSS ✓ ✓ ✓ ✓ Vibration Sensors ✓ ✓ (✓) Fiber Bragg Grating ✓ ✓ (✓) Pyranometers ✓ ✓ Anemometers ✓ ✓ ✓ Raingauge ✓ Water level sensor ✓ Air flow sensors ✓ ✓ ✓ Human presence ✓ ✓ ✓ C. Connectivity and Data Transmission LoRaWAN architectures provide robust long-range communication, but data rate and package size limitations constrain the use of high-frequency sensors (e.g., vibration or audio). This challenge has also been noted in heritage-focused deployments such as [22], where hybrid networks are proposed to support layered sensing modalities. To overcome these challenges, the vibration meters process and compute the vibration in its firmware, reducing the size of the data packages to be transmitted. Similarly, GNSS sensors apply the position correction using satellite’s data input before transmitting the readings, avoiding the need of post-processing. D. Sensor Calibration and Ground Truthing Air quality and environmental sensors will require calibration over time, particularly in locations with variable humidity or temperature extremes. Custom-built Arduino-based devices, while cost-effective, showed sensitivity to drift, necessitating validation against commercial-grade units during field trials. Structural sensors (crack-meters, tilt-meters, vibration meters and GNSS) show promising stability but require a baseline and interpretation support from experts to distinguish between seasonal movement and pathological change, especially if there are no available models to expect specific patterns. E. Cross-Team Coordination Effective deployment demanded close coordination among sensor manufacturers (e.g., Worldsensing), data integration teams, and preservation scientists. In Baltan´ as and Ranverso, interdisciplinary on-site meetings proved critical for resolving positioning conflicts and confirming threat relevance. Ongoing feedback loops between sensor data and heritage evaluation protocols are helping refine monitoring plans dynamically. F. Preliminary Observations a) Concrete Early Warnings: Initial deployments have already yielded preservation-relevant insights. For example, in Ranverso, UV/lux sensors revealed excessive afternoon exposure on a fresco-bearing wall, prompting the installation of temporary shading to reduce pigment degradation risk. In Baltan´ as, coupled indoor/outdoor humidity sensors detected persistent lagging peaks in internal RH after rainfall events, which aligned with observed microbial spots, guiding airflow intervention planning. In Schenkenberg, thermistors identified temperature oscillations triggering crackmeter micromovements, suggesting predictive potential for frost-induced stress events. These insights affirm the utility of threat-aligned, contextsensitive sensing systems as enablers for long-term preventive preservation strategies in cultural heritage. b) Synthesis of Deployment Challenges: Across the sites, recurring challenges included: •Heritage Compliance: Constraints on sensor mounting required adhesive-free solutions and authority approvals. •Energy Autonomy: Shaded or subterranean locations (e.g., Baltan´ as) challenged solar reliance, requiring hybrid strategies. •Calibration Drift: Low-cost environmental sensors needed in-field calibration against reference-grade units. •Connectivity Limits: Thick walls and terrain attenuation necessitated careful LoRa gateway positioning. •Team Coordination: Preservation experts, sensor engineers, and system integrators required iterative on-site alignment. These informed refinements to ARGUS’s modular and replicable deployment methodology. VI. CONCLUSION AND FUTURE WORK This paper presented the preventive preservation strategy developed within the ARGUS project, with a focus on the sensor selection and deployment activities. By aligning sensor configurations with specific preservation threats across diverse heritage sites, ARGUS moves beyond generic monitoring schemes toward a purpose-driven and scalable framework for remote built heritage preservation. The experience gathered from the five pilot sites demonstrates both the feasibility and the complexity of such undertakings. Heritage-sensitive installations, energy-autonomous sensor networks, and interdisciplinary coordination have emerged as key enablers for effective monitoring in infrastructurally constrained contexts. Early operational feedback confirms the value of low-power environmental sensing, structural integrity tracking, and threat-informed deployment design. In the next phases of the project, ARGUS will focus on: •Integrating sensor data with heritage interpretation models and decision-support systems. •Validating long-term stability and data quality across seasonal cycles. •Exploring anomaly detection techniques for proactive preservation alerts. •Refining deployment workflows into a replicable protocol for other sites and regions. Ultimately, ARGUS contributes a replicable methodology and field-tested infrastructure that can serve as a foundation for broader preventive preservation strategies in cultural heritage—particularly where remoteness, fragility, and threat multiplicity converge. ACKNOWLEDGMENT This work has been supported by the ARGUS EU project (Grant Agreement No. 101132308), funded by the European Union. Views and opinions expressed are however those of the author(s) only and do not necessarily reflect those of the European Union or of the European Research Executive Agency (REA). 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