A Systematic Literature Review on Safety Research Related to Chemical Industrial Parks

Development to Emergency Evacuation Decision Making in Hazardous Materials Incidents Using Machine Learning

Chemical accidents are the biggest factor that hinders the development of the chemical industry. Issuing an emergency evacuation order is one of effective ways to reduce human casualties that may occur due to chemical accidents. The present study proposes a machine learning-based decision making model for faster and more accurate decision making for the issuance of an emergency evacuation order in the event of a chemical accident. To implement the decision making model, supervised learning by the 1-Dimension Convolutional Neural Network based model was carried out using the HSEES and NTSIP data of ATSDR in the United States. An action—victim matrix was devised to determine the validity of emergency evacuation orders and the decision making model was made to learn the matrix so that the decision making model could recommend whether to execute the emergency evacuation orders or not. To make the decision making model learn the chemical accident situations, the embedding technique used in text mining was applied, and weighted learning was carried out considering the fact that learning data are asymmetric. The AUROC value for the results of the decision making by the model is 0.82, which is at a reliable level. Establishing such an emergency response decision making model using the method proposed in the present study in the mitigation stage will help the process. Among the chemical accident emergency management stages, constructing a database for the model, and using the model as a tool for quick decision making for an emergency evacuation order, is also thought to be helpful in the establishment and implementation of emergency response plans for chemical accidents.

Trends in Civic Engagement Disaster Safety Education Research: Systematic Literature Review and Keyword Network Analysis

Background: Education plays the most important role in establishing a disaster management system by creating a safety culture in the community and by engaging its members. This study explored the trends in research on disaster safety education based on the community from the perspective of lifelong education. Methods: We undertook a systematic literature review and keyword network analysis. The main search keywords were “community”, “disaster”, “safety”, and “education”. The subjects of education were adults, including disaster-vulnerable people, such as elderly and disabled people. A total of 185 articles and papers were identified and then narrowed down to 56. Results: Research related to disaster safety education has developed in a direction that reflects the characteristics of disasters that occur in the region. Currently, disaster safety education is being studied in various fields, including the humanities, social sciences, and engineering, focusing on disaster prevention. The main research methods in the reviewed literature were qualitative, especially case studies that applied narrative, storytelling, and risk scenario construction. Conclusion: The study provides a framework for the in-depth analysis of disaster risk management and risk level of communities, and lays the academic foundation for it.