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
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Data Storytelling and Big Data value chain in Natural Disaster Management
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
Deep Learning for Post-Earthquake Safety Evaluation of Masonry Buildings
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
Maestro: Forecasting and Risk Management in Forest Fires via IoT Technologies
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
Forest Fire Monitoring and Measuring with Multiple Cooperating Drones
Real-time forest fire perception, monitoring and measuring is a very complex problem of that requires the fusion of different types of sensors and cameras. Using several cooperating aerial robots (drones) is an ideal approach to gather high quality images and measurements at different vantage points suitable for fire status estimation and to process them in… Continue reading Forest Fire Monitoring and Measuring with Multiple Cooperating Drones
Drone imaging for NDMs
Lecture by Nikolaos Militsis. Link to video