HaMMon: Integrated AI for Enhanced Seasonal Forecasting and Environmental Risk Management

Enhancing environmental risk management thanks to integrated AI
Thematic area: Earth/Climate, Projects
Financing: ICSC Innovation Grants
Enabling Technology: Advanced Modeling and Simulation, Artificial Intelligence, Geographic Information Systems (GIS), High Performance Computing, Image recognition

This project expands the HaMMon initiative by improving its system for seasonal forecasting and hazard assessment of extreme events. It will refine environment classification algorithms initially developed in WP3 and WP4 of Hammon. The project is intended to improve efficiency in the processing and analysis of environmental data, with the goal of achieving more accurate predictions of extreme weather events and a clearer understanding of the vulnerability of the built environment to climate-induced hazards.

Italian Research Center on High Performance Computing Big Data and Quantum Computing (ICSC), project funded by European Union – NextGenerationEU – and National Recovery and Resilience Plan (NRRP) – Mission 4 Component 2. 

The goal

  • Improved mapping of extreme natural event risk for Italy. 
  • Enhancement of monitoring activities in Italy, aimed at quantifying the impacts of extreme events. 
  • Improved knowledge of assets exposed to catastrophic risks.  
  • Development of medium-range high-resolution forecasts of extreme events in Italy. 
  • Development of a technological infrastructure for data processing and distribution. 

The initial challenge

The study and monitoring of natural hazards and their consequences have shown a drastic increase in recent years. In the context of a changing climate, these aspects play a crucial role in assessing the local and regional impact of floods, droughts, storm surges, convective storms and other extreme phenomena. More generally, observed climate change has been shown to enhance the activity of existing slow landslides and to reactivate quiescent ones. In addition to climate-related phenomena, earthquakes represent a huge threat to our country and, in light of the losses suffered in recent decades in Italy, it is necessary to improve the seismic risk mitigation strategy. 

The solution

The HaMMon project aims to address the problem of natural hazards in Italy, exacerbated by climate change, through an innovative approach that integrates different technologies and methodologies. At the heart of the project is the creation of an advanced computing platform for data management and development activities, which focuses on the availability of high-performance data and services. In this context, risk monitoring and post-event analysis play a crucial role, especially in assessing damage caused by natural disasters.  

An important component of the project is the use of advanced mapping technologies, such as photogrammetry techniques, to create high-resolution 3D models of affected areas, useful for damage assessments. It will also explore the use of artificial intelligence and the development of innovative algorithms for information extraction and for the classification and identification of buildings.  

The project also employs climate models to predict extreme events and assess their impact, including generating AI weather models for modelling extreme weather events. Another key aspect is the mapping of the built environment in Italy, which aims to analyse the characteristics of buildings to determine their vulnerability to natural hazards.   

Finally, the project includes the analysis of the vulnerability of structures and infrastructures, especially those affected by slow landslides, and the development of fragility curves related to seismic and flood risks. In essence, HaMMon aims to develop a complex and integrated system for the assessment and management of natural risks in Italy, exploiting the most advanced technologies in the field of monitoring, data analysis and artificial intelligence. 

Benefits

  • Web application for remote inspection of areas damaged by natural disasters  
  • Web service to expose 3D models to third-party applications with tools for automatic (or semi-automatic) extraction of information on buildings and disasters
  • Operational model for risk management based on seasonal forecasts  
  • Weather generation software for risk management applications  
  • Software tools (library, sdk) for extracting building information based on satellite and aerial imagery or street view imagery  
  • Fragility and loss curves for structural, flood and seismic risk for specific building taxonomies.  
  • Identification of risks related to natural disasters  
  • Enhancement and automation of controls on building activity. 

Partners

Participating Spoke

 

For further information, please contact: barbara.vecchi@ifabfoundation.org

Sustainable Development Goals

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