Leveraging AI and Semantic Web Technologies for Enhanced Image Processing in Robotic Systems - Li, Hao; Chen, Yedong; Xie, Ziming; Ye, Bo; Bansal, Shavi (International journal on semantic web and information systems, 2025)
Fall detection is an important task in the robotic system, and it is related to the well-being of the human subject. However, it is a challenging task to complete due to the presence of false positives and a lack of contextual awareness. In this context, this paper presents a fall detection model that integrates You Only Look Once11—for real-time object detection—with semantic web technologies for intelligent decision-making. The semantic knowledge graph is used to establish a relation between the You Only Look Once11 results and the fall events. Experimental evaluation of the proposed model presents an mAP@0.5 of 0.806, validating the effectiveness of artificial intelligence-driven visual processing combined with semantic knowledge representation for enhanced fall detection in robotic systems.