An AI-Based Support System for Left-Behind Children Detection in Vehicles

In general, accidents involving school buses and parents leaving their infants in the car due to a lack of attention are increasing. Also, in-vehicle inspections are being neglected. In this paper, we focus on this problem and propose an AI-based support system for detecting left-behind children in vehicles. In the proposed system, we use YOLO which optimizes the hyperparameters when performing object detection. The proposed system can detect left-behind children by considering adults and dolls in a vehicle. Based on the evaluation results, we found that in Case #1, the accuracy was higher when the number of generations was 300. While, in Case #2, misidentification of adults was resolved by increasing the number of generations. Finally, in Case #3, some scenes were identified as dolls when were shown some body parts of the child.