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Mr. Prasantha Kumar sahoo, M. Sai Venkata Ramana, S. Vasisht Iyenger , B. Eshanth
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Page No: 1 - 13
Abstract : The project aims to address the critical need for a robust explosion risk assessment tool in the oil and gas industry, particularly in oil and gas refinery environments where safety is paramount. Traditional methods of threat assessment are often manual, subjective, and limited in their capacity to provide real-time insights, which poses significant challenges for industry professionals in managing potential hazards. Our project leverages real-time weather data and machine learning algorithms to develop an advanced web application designed to identify and assess threat zones within oil and gas refineries. By utilizing refinery-specific datasets, real-time weather parameters, and machine learning models, the application enables users to upload or access refinery data, select industry-specific details, and receive accurate risk predictions along with stability class assessments. The application integrates the OpenWeatherMap API to provide up-to-date weather information, while a Random Forest classifier used for gas classification and some other parameters are calculated and trained on relevant features such as wind speed, cloud cover, and insolation levels to predict explosion risks. Designed with an intuitive, user-friendly interface, this tool will be invaluable for safety engineers, refinery managers, and environmental professionals, facilitating proactive risk management and informed decision-making. By addressing limitations in current risk assessment methods—such as limited access to real-time environmental data, variable risk levels, and lack of predictive analytics—our project aims to provide a comprehensive, data-driven solution for managing safety and mitigating risks in high-stakes industrial environments.
Keyword Gas Classification, OpenWeatherMap API, Insolation Calculation, Predictive Analytics, Explosion Efficiency, Risk Prediction.
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Arora, P., & Bhardwaj, S. (2021). Methods for Threat and Risk Assessment and Mitigation to Improve Security in the Automotive Sector. Methods, 8(2).