Industrial AI Safety | Jay Polrahttps://jaypolra.github.io/tags/industrial-ai-safety/Industrial AI SafetyHugo Blox Builder (https://hugoblox.com)en-usFri, 01 May 2026 00:00:00 +0000https://jaypolra.github.io/media/icon_hu_3943bc2ea2cd9fa1.pngIndustrial AI Safetyhttps://jaypolra.github.io/tags/industrial-ai-safety/Development of Trailing Image Detection for a Melt Shop Safety Toolhttps://jaypolra.github.io/publication/aistch-2026/Fri, 01 May 2026 00:00:00 +0000https://jaypolra.github.io/publication/aistch-2026/A Dual-Model Approach to Industrial Safety: Computer Vision for PPE Compliance and Hazard Zone Monitoring in Steel Productionhttps://jaypolra.github.io/publication/tms-2025/Wed, 01 Jan 2025 00:00:00 +0000https://jaypolra.github.io/publication/tms-2025/VLM-Based Hazard Reasoninghttps://jaypolra.github.io/project/vlm-hazard-reasoning/Wed, 01 Jan 2025 00:00:00 +0000https://jaypolra.github.io/project/vlm-hazard-reasoning/<p>YOLO can flag a red zone but cannot explain why the scene is dangerous. This project tests whether general-purpose VLMs can fill that explainability gap using structured domain-aware prompting.</p> <p>Prompts give models physical context about melt shop environments: what pot haulers are, what molten metal implies, what worker corridors mean for safety. Two-stage reasoning pipeline: first describe the scene neutrally, then evaluate against safety conditions.</p> <p>Output covers scene description, detected entities, spatial relationships, hazard assessment, risk level, and recommended action.</p>