Context-Aware Simulation with Machine Vision for Industrial Safety

This paper introduces a framework for enhancing industrial safety through context-aware simulation. The system is built around a modular pipeline that captures real-time data, uses object detection (YOLOv8) and image captioning (BLIP) to interpret scenes, and communicates insights through middleware to a simulation awareness layer. This layer can inject hazards and coordinate responses. By providing richer contextual understanding, the system enables earlier and more effective safety interventions, leading to increased operator confidence compared to traditional threshold-based triggers. The approach demonstrates how advanced perception and language technologies can be integrated into simulation environments to support safer and more efficient industrial operations, while also revealing new behaviors that emerge from this deeper level of situational awareness.