Abstract
The advanced use and the evolution of technologies regarding autonomous Unmanned Aerial Vehicle (UAV) have increased the availability of information and resources to perceive the environment, allowing its application in various activities, such as inspection and military. However, the intelligence level of these kind of systems needs to be improved in order to fit them in modern tasks. In this sense, this work proposes a high-level processing approach to be embedded in UAV system for understanding human activities in real environment. Additionally, the Case-Based Reasoning (CBR) methodology is also applied to allow the adaptation of the flight plan and the fully autonomous surveillance in limited areas. In order to enhance the solution, the proposed architecture is inspired in the biologic model of the human cognitive system and comprises low, middle and high levels to enable the perception of the environment as well as comprehension of the scene. The experiments have shown technical feasibility and effectiveness of the architecture. Moreover, the use of UAV has reduced the number of cameras and operators, being also capable to reach difficult areas.