TY  - JOUR
T1  - Ontology and CNN-based Inference of the Threat Relationship Between UAVs and Surrounding Objects
AU  - Jeon, MyungJoong 
AU  - Lee, MinHo 
AU  - Park, HyunKyu 
AU  - Park, YoungTack 
AU  - Yoon, Hyung-Sik 
AU  - Kim, Yun-Geun 
JO  - Journal of KIISE, JOK
PY  - 2020
DA  - 2020/1/14
DO  - 10.5626/JOK.2020.47.4.404
KW  - UAVs
KW  - relationship inference
KW  - ontology
KW  - grid map
AB  - The technology that identifies the relationship between surrounding objects and recognizes the situation is considered as an important and necessary technology in various areas. Numerous methodologies are being studied for this purpose. Most of the studies have solved the problem by building the domain knowledge into ontology for reasoning of situation awareness. However, based on the existing approach; it is difficult to deal with new situations in the absence of domain experts due to the dependency of experts on relevant domain knowledge. In addition, it is difficult to build the knowledge to infer situations that experts have not considered. Therefore, this study proposes a model for using ontology and CNN for reasoning of the relationships between UAVs and surrounding objects to solve the existing problems. Based on the assumption that the accuracy of ontology reasoning is insufficient, first, the reasoning was performed using the information from the detected surrounding objects. Later, the results of ontology reasoning are revised by CNN inference. Due to the limitations of actual data acquisition, data generator was built to generate data similar to real data. For evaluation of this study, two models of relationships between two objects were built and evaluated; both the models showed over 90% accuracy.