Intelligent emergency assisted decision-making method based on standard digitalization: Hazardous chemical accidents in industrial parks
Contemporary society is confronted with multifaceted challenges, and the intricate interplay of interconnected factors significantly complicates emergency response efforts. Current practices rely on quick decisions by domain experts; however, the limitations of individual expertise and the urgency o...
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| Format: | Article |
| Language: | English |
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KeAi Communications Co., Ltd.
2025-03-01
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| Series: | Journal of Safety Science and Resilience |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2666449624000513 |
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| author | Zhenxiang Tao Xiaohan Liu Ying Li Peifeng Hu Weitong Tang Ning Luo Jiansong Wu Rui Yang |
| author_facet | Zhenxiang Tao Xiaohan Liu Ying Li Peifeng Hu Weitong Tang Ning Luo Jiansong Wu Rui Yang |
| author_sort | Zhenxiang Tao |
| collection | DOAJ |
| description | Contemporary society is confronted with multifaceted challenges, and the intricate interplay of interconnected factors significantly complicates emergency response efforts. Current practices rely on quick decisions by domain experts; however, the limitations of individual expertise and the urgency of crises hinder both precision and standardization. To address these issues, we propose a novel approach: an intelligent method for emergency decision-making grounded in a standardized digital knowledge graph. First, our study examined the underlying theory of standardized digital transformation and event-chain evolution. This led to the construction of a knowledge graph encompassing standard emergency knowledge, as well as supplementary derivative data pertinent to event response. Second, through the application of semantic analysis and intention recognition of the decision target, coherent and interpretable query sentences for the decision system were crafted. These query sentences then served as a conduit for retrieving standard emergency knowledge relevant to the current emergency situation, as well as potential secondary disasters. The overarching goal is to provide emergency decision makers with effective support mechanisms that are both well informed and tailored to the specific demands of each situation. |
| format | Article |
| id | doaj-art-cdc7b6c262ae4cc380f98f9ca4bbe61b |
| institution | Kabale University |
| issn | 2666-4496 |
| language | English |
| publishDate | 2025-03-01 |
| publisher | KeAi Communications Co., Ltd. |
| record_format | Article |
| series | Journal of Safety Science and Resilience |
| spelling | doaj-art-cdc7b6c262ae4cc380f98f9ca4bbe61b2025-01-28T04:14:56ZengKeAi Communications Co., Ltd.Journal of Safety Science and Resilience2666-44962025-03-01617992Intelligent emergency assisted decision-making method based on standard digitalization: Hazardous chemical accidents in industrial parksZhenxiang Tao0Xiaohan Liu1Ying Li2Peifeng Hu3Weitong Tang4Ning Luo5Jiansong Wu6Rui Yang7School of Emergency Management and Safety Engineering, China University of Mining and Technology-Beijing, Beijing 100083, China; Corresponding author.School of Emergency Management and Safety Engineering, China University of Mining and Technology-Beijing, Beijing 100083, ChinaSchool of Emergency Management and Safety Engineering, China University of Mining and Technology-Beijing, Beijing 100083, ChinaSchool of Emergency Management and Safety Engineering, China University of Mining and Technology-Beijing, Beijing 100083, ChinaSchool of Safety Science, Tsinghua University, Beijing 100084, ChinaState Grid Zhongxing Beijing Zhongxing Property Management Co., Ltd, Beijing 100053, ChinaSchool of Emergency Management and Safety Engineering, China University of Mining and Technology-Beijing, Beijing 100083, ChinaSchool of Safety Science, Tsinghua University, Beijing 100084, ChinaContemporary society is confronted with multifaceted challenges, and the intricate interplay of interconnected factors significantly complicates emergency response efforts. Current practices rely on quick decisions by domain experts; however, the limitations of individual expertise and the urgency of crises hinder both precision and standardization. To address these issues, we propose a novel approach: an intelligent method for emergency decision-making grounded in a standardized digital knowledge graph. First, our study examined the underlying theory of standardized digital transformation and event-chain evolution. This led to the construction of a knowledge graph encompassing standard emergency knowledge, as well as supplementary derivative data pertinent to event response. Second, through the application of semantic analysis and intention recognition of the decision target, coherent and interpretable query sentences for the decision system were crafted. These query sentences then served as a conduit for retrieving standard emergency knowledge relevant to the current emergency situation, as well as potential secondary disasters. The overarching goal is to provide emergency decision makers with effective support mechanisms that are both well informed and tailored to the specific demands of each situation.http://www.sciencedirect.com/science/article/pii/S2666449624000513Public safetyEmergency responseAssisted decisionKnowledge graphStandard digitization |
| spellingShingle | Zhenxiang Tao Xiaohan Liu Ying Li Peifeng Hu Weitong Tang Ning Luo Jiansong Wu Rui Yang Intelligent emergency assisted decision-making method based on standard digitalization: Hazardous chemical accidents in industrial parks Journal of Safety Science and Resilience Public safety Emergency response Assisted decision Knowledge graph Standard digitization |
| title | Intelligent emergency assisted decision-making method based on standard digitalization: Hazardous chemical accidents in industrial parks |
| title_full | Intelligent emergency assisted decision-making method based on standard digitalization: Hazardous chemical accidents in industrial parks |
| title_fullStr | Intelligent emergency assisted decision-making method based on standard digitalization: Hazardous chemical accidents in industrial parks |
| title_full_unstemmed | Intelligent emergency assisted decision-making method based on standard digitalization: Hazardous chemical accidents in industrial parks |
| title_short | Intelligent emergency assisted decision-making method based on standard digitalization: Hazardous chemical accidents in industrial parks |
| title_sort | intelligent emergency assisted decision making method based on standard digitalization hazardous chemical accidents in industrial parks |
| topic | Public safety Emergency response Assisted decision Knowledge graph Standard digitization |
| url | http://www.sciencedirect.com/science/article/pii/S2666449624000513 |
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