Transforming Petrochemical Safety Using a Multimodal AI Visual Analyzer

The petrochemical industry faces significant safety challenges, necessitating stringent protocols and advanced monitoring systems. Traditional methods rely on manual inspections and fixed sensors, often reacting to hazards only after they occur. Multimodal AI, integrating visual, sensor, and textual data, offers a transformative solution for real-time, proactive safety management. This paper evaluates AI models—Gemini 1.5 Pro, OPENAI GPT-4, and Copilot—in detecting workplace hazards, ensuring compliance with Process Safety Management (PSM) and DuPont safety frameworks. The study highlights the models’ potential in improving safety outcomes, reducing human error, and supporting continuous, data-driven risk management in petrochemical plants. This paper is the first of its kind to use the latest multimodal tech to identify the safety hazard; a similar model could be deployed in other manufacturing industries, especially the oil and gas (both upstream and downstream) industry, fertilizer industries, and production facilities.