PAER: A new web platform for acquisition, storage, processing, and visualization of natural risks

One of the main obstacles to natural risk reduction is the effective communication of risks to stakeholders and the public. Although numerous instruments, models, and platforms can be integrated, the lack of common protocols and standards often requires ad hoc adjustments. This contribution presents PAER (Piattaforma Acquisizione ed Elaborazione Rischi - Risk Acquisition and Processing Platform), a newly developed web platform within the Tech4You project - Technologies for climate change adaptation and quality of life improvement, funded under the Next Gen EU framework. PAER is characterized by an extremely flexible structure that can collect data from multiple sources, including variable-time-series data, rasters, and images.

The PAER framework is a service dedicated to risk acquisition and processing, designed to store and manage heterogeneous types of data, both temporal and spatial. The platform can integrate information from ground-based monitoring networks and outputs generated by complex computational models. The service is essential for visualizing and storing environmental variables and for monitoring critical areas, thereby supporting advanced analyses and timely decision-making.

PAER targets a wide range of stakeholders, both public and private. Owing to its ease of use and flexibility in customizing data-entry methods, the service is accessible to a range of users, each with different needs and levels of expertise. Users can configure a comprehensive data-validation workflow, including automated alerts, to ensure that all collected information is accurate and reliable. The optimized database structure enables fast and efficient queries, even when managing large datasets, ensuring smooth performance. Additionally, the system supports automatic data acquisition through APIs, simplifying integration with external sources and streamlining data flow management.

The experimental validation involved multiple pilot projects across different domains. PAER successfully integrated datasets from hydrological monitoring and flood-risk assessment, including cosmic-ray neutron sensors for soil moisture estimation, pedestrian flood instability maps, and intelligent camera data from urban areas. The platform also managed in situ observations from piezometers, soil moisture probes, and meteorological stations, combined with weather forecasts produced by numerical models at regional and seasonal scales. Furthermore, PAER integrated wildfire-monitoring data, including intelligent camera imagery, regional risk maps, and automatically collected CO2 sensor measurements from forest mountainous areas. Additionally, the platform incorporates a Decision Support System (DSS) for agriculture based on the AquaCrop model, which automatically leverages other information already present in the platform and can be highly customized by users to meet specific agricultural management needs.

The experimental results confirm that PAER provides a robust, unified environment for integrating, storing, and analyzing different environmental datasets, demonstrating its suitability for multi-domain, multi-scale environmental risk monitoring applications. The platform's flexibility and scalability make it an ideal candidate for broader adoption in environmental risk management worldwide. Future developments will focus on expanding the range of integrated data sources and applying PAER to additional natural-hazard scenarios across diverse geographical contexts, thereby fostering international collaboration and knowledge sharing in risk assessment and mitigation.