Modeling flash floods in urban areas with complex topography is always challenging. Considering fine-scale hydrodynamic 2D shallow water model to perform simulations requires a lot of manual or semi-automatic data processing before being able to run simulations. This involves the transformation of high-resolution Digital Surface Model (Lidar) into a Digital Elevation Model that conserves the… Continue reading Flash flood modeling and in urban areas using High Resolution hydrodynamic model and machine learning models
Cloud Computing during the time has gained concrete evidence to be a disruptive technology still in its full development. Many drawbacks of the Cloud have brought to improve many their crucial aspects, like performance, security and privacy, etc. Today Edge Computing try to deal with these implications to make them less problematic and much more… Continue reading From Cloud to Edge through Microservices
The challenges that emergency services face when dealing with disasters are becoming increasingly complex. Thus, methods of analysing new digital information for situation assessment and operational planning is of crucial importance. This talk presents an approach for multi-modal analysis of digital data such as geo-social media posts using artificial intelligence (AI), helping to ensure the… Continue reading Multimodal Analysis of Geo-social Media Data for Improved Disaster Management: From Science to Digital Practice
This lecture explores the concepts of Data Storytelling and the Big Data value chain in the context of Natural Disaster Management. It delves into the significance of effectively communicating data to inform decision-making and seeks to uncover the potential of utilizing big data to improve disaster response and mitigation efforts. The lecture discusses the challenges… Continue reading Data Storytelling and Big Data value chain in Natural Disaster Management
Natural disasters present multifaceted challenges that necessitate swift and accurate responses. In the realm of post-earthquake safety assessments, the rapid and precise evaluation of damages is pivotal to ensure the optimal allocation of resources and facilitate effective emergency management. Many earthquake-prone nations employ standardized forms, such as the Italian AeDES, New Zealand Earthquake Rapid Assessment,… Continue reading Deep Learning for Post-Earthquake Safety Evaluation of Masonry Buildings
The Maestro telemetry system predicts forest fire risk based on geolocated weather data collected by sensor nodes. Sensor nodes provide a low-cost solution to reliably monitor the microclimate of forested areas and to correlate the current conditions with possible prolonged drought. In case of fire, nodes fall into emergency mode by transmitting more frequent measurements… Continue reading Maestro: Forecasting and Risk Management in Forest Fires via IoT Technologies