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The COVID-19 pandemic underscored the critical need for robust health monitoring systems in offshore oil platforms, where isolation and operational continuity are paramount. Building on Adeoye’s experience in responding to the pandemic, this paper conceptualizes an AI-powered pandemic response framework designed specifically for offshore oil facilities. The proposed system leverages artificial intelligence to predict, manage, and mitigate health crises, ensuring both safety and business continuity during global pandemics. At the core of the framework is a predictive health monitoring system that utilizes real-time data from multiple sources, including personnel health records, environmental sensors, and global epidemiological reports. Machine learning algorithms process this data to identify patterns and trends, enabling early detection of potential outbreaks. Predictive analytics tools are deployed to forecast infection rates and the likely spread of diseases, allowing for proactive intervention measures such as isolation protocols, targeted testing, and remote medical support. The AI-driven system also incorporates automated resource management to optimize the availability of medical supplies, personal protective equipment (PPE), and personnel deployment. By continuously analyzing supply chain data, the system ensures the timely replenishment of critical resources, mitigating disruptions that could compromise safety and operational efficiency. Furthermore, the framework includes communication protocols that disseminate real-time health information to both onshore and offshore teams, promoting coordinated responses to emerging threats. This AI-based solution is designed to integrate with existing health and safety systems on offshore platforms, enhancing their ability to manage global health crises more effectively. The framework's emphasis on prediction, early intervention, and automated resource management ensures that offshore oil facilities can maintain operational continuity while prioritizing the health and safety of their workforce during pandemics.
Aderamo et al. (Fri,) studied this question.