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
Archives: Resources
Resource description
Drone imaging for NDMs
Lecture by Nikolaos Militsis. Link to video
Sensors and Big Data Analytics for NDM
Natural Disaster Management (NDM, e.g., for wildfires, floods) can be greatly improved by automating precise semantic 3D mapping and disaster evolution prediction to achieve NDM goals in near-real-time. To this end, many heterogeneous extreme data sources must be analyzed and fused: smart drone sensors (e.g., RGB, RGBD and thermal cameras, Lidars, motion sensors), emergency vehicle… Continue reading Sensors and Big Data Analytics for NDM
Blaze Fire Classification – Segmentation Dataset
The Aristotle University of Thessaloniki (hereinafter, AUTH) created the following dataset, entitled ‘Blaze’, within the context of the project TEMA that was funded by the European Commission-European Union [Grant Agreement number: 101093003; start date: 01/12/2022; end date: 30/11/2026]. General description of the dataset The dataset will be used for wildfire image classification and burnt area segmentation tasks for Unmanned Aerial… Continue reading Blaze Fire Classification – Segmentation Dataset
UAV Infrastructure Inspection
This lecture overviews the use of drones for infrastructure inspection and maintenance. Various types of inspection, e.g., using visual cameras, LIDAR or thermal cameras are reviewed. Primary application area is electric line inspection. Line detection and tracking and drone perching are examined. Human action recognition and co-working assistance are overviewed.
MultiDrone Datasets
This lecture overviews MultiDrone Datasets that has many applications in autonomous drone research and development. It covers the following topics in detail: Datasets developed in the MultiDrone R&D project, notably on visualizing crowd images, shot types, person detection, cyclist races, UAV detection, landing site detection and boating races.