Object Detection Based Aircraft Cargo Safety Assessment Methodology

Presented in the paper is the methodology of safety assessment in an aircraft cargo system. Generally, aviation accidents incur astronomical costs, including expenses for aircraft loss, loss of human lives, accident processing, and more. Particularly, inadequate securing of cargo, despite being preventable in advance, can lead to significant accidents. For this reason, various studies have been conducted to monitor aircraft cargo. However, the cost of implementing those systems is significant, thus necessitating the development of a more cost-effective yet efficient cargo safety assessment system. This paper presents an artificial intelligence model using object detection to determine whether aircraft cargo latches are properly secured. Four experiments were con- ducted, each varying the training environment, testing environment, and label states. The data used in the experiments were obtained by constructing a virtual simulation environment.