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    • Level of detail (LoD) geometric analysis of relief mapping employing 3D modeling via UAV images in cultural heritage studies
    Authors: Ergun, Bahadir; Sahin, Cumhur; Bilucan, Furkan;  Advisor: -;  Co-Author: - (2023)

    Unmanned Aerial Vehicles (UAVs) are often preferred for modeling cultural heritage buildings due to their costs and time savings. The need for data collection, analysis, processing, and visual presentation in the context of cultural heritage buildings has become prominent, underscoring the significance of the concept of Level of Detail (LoD). The utilization of CityGML LoD standards enhances the performance of visual presentations, decreases the geometric complexity of objects, and enables users to view the model at the desired level of detail within a computerized environment. Within the scope of this study, it is aimed to determine the accuracy analysis of the 3D model for a cultura...
    • Wildfire detection in large-scale environments using force-based control for swarms of UAVs
    Authors: Georgios, Tzoumas; Lenka, Pitonakova; Lucio, Salinas;  Advisor: -;  Co-Author: - (2023)

    Wildfires affect countries worldwide as global warming increases the probability of their appearance. Monitoring vast areas of forests can be challenging due to the lack of resources and information. Additionally, early detection of wildfires can be beneficial for their mitigation. To this end, we explore in simulation the use of swarms of uncrewed aerial vehicles (UAVs) with long autonomy that can cover large areas the size of California to detect early stage wildfires. Four decentralised control algorithms are tested: (1) random walking, (2) dispersion, (3) pheromone avoidance and (4) dynamic space partition.