A Study on the Development of a Decision Support Program for Field Commanders Using Generative AI

doi:10.15683/kosdi.2026.3.31.071

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2026 Vol.22, Issue 1 Preview Page Next Page

Original Article

A Study on the Development of a Decision Support Program for Field Commanders Using Generative AI 생성형 AI를 활용한 현장지휘관 의사결정 지원 프로그램 개발 연구: 고영주¹ㆍ구본찬²ㆍ길진혁³*ㆍ박하나⁴ㆍ곽찬희⁵**ㆍ함양훈⁶ㆍ이성민⁷ㆍ신동일⁸
Young-joo Ko¹, Bon-chan Ku², Jin-hyuck Gil³*, Ha-na Park⁴, Chanhee Kwak⁵**, Yang-hoon Ham⁶, Seong-min Lee⁷, Dong-il Shin⁸; ¹Fire Chief, Gyeonggi-Do Ansan Fire Station, Ansan, Republic of Korea
²Fire Chief, Gyeonggi-Do Fire and Disaster Headquarters, Suwon, Republic of Korea
³Fire Captain, Gyeonggi-Do Suwon Southern Fire Station, Suwon, Republic of Korea
⁴Researcher, Gyeonggi-Do Fire Services Academy, Yongin, Republic of Korea
⁵Associate Professor, Department of Artificial Intelligence Convergence Engineering, Kangnam University, Yongin, Republic of Korea
⁶BE Course, Department of Artificial Intelligence Convergence Engineering, Kangnam University, Yongin, Republic of Korea
⁷BE Course, Department of Artificial Intelligence Convergence Engineering, Kangnam University, Yongin, Republic of Korea
⁸Professor, Department of Disaster and Safety, Myongji University, Yongin, Republic of Korea
^**Current Address: Associate Professor, Department of Business Management, Gachon University, Seong-nam, Republic of Korea

31 March 2026. pp. 71-80

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Abstract

Purpose: Using generative AI, we tried to develop a program that summarizes and provides expertise such as manuals and instructions to field commanders. Method: Through in-depth interviews with field commanders, decision-making obstacles and problems were analyzed, and virtual scenario answers were provided through programs that learned related manuals and guidelines to verify the applicability of the field by conducting a survey for firefighters. Result: As a result of virtual scenario analysis, it was confirmed that the AI-based decision support program has the effect of increasing the speed and accuracy of decision-making by providing key information to field commanders quickly and accurately. Conclusion: This study suggested the possibility that the Generative AI can supplement the limitations of the manual-based system, strengthen field command expertise, ensure consistency in decision-making, and contribute to the reduction of human and property damage.

Keywords

Field Commander

Generative AI

Decision-making Support

LLM

Disaster Response

연구목적: 생성형 AI를 활용하여 현장지휘관에게 매뉴얼·지침 등 전문 지식을 요약하여 제공하는 프로그램을 개발하고자 하였다. 연구방법: 현장지휘관 심층 인터뷰를 통해 의사결정 장애요인과 문제점을 분석하고, 관련 매뉴얼·지침을 학습한 프로그램을 통해 가상 시나리오 답변을 제공하여 소방공무원 대상 설문조사를 실시하여 현장 적용 가능성을 검증하였다. 연구결과: 가상 시나리오 분석 결과, AI 기반 의사결정 지원 프로그램은 현장지휘관에게 핵심 정보를 신속·정확하게 제공하여 의사결정 속도와 정확성을 높이는 효과가 있음을 확인하였다. 결론: 본 연구는 생성형 AI가 매뉴얼 기반 현장지휘 체계의 한계를 보완하고, 전문성 강화, 의사결정 일관성 확보, 인명 및 재산 피해 경감에 기여할 수 있는 가능성을 제시하였다.

키워드

현장지휘관

생성형 AI

의사결정 지원

LLM

재난 대응

References

Han, C.-H., Shin, K.-Y., Choi, S.-H., Moon, S.-W., Lee, C.-H., Lee, J.-K. (2020). “A methodology of decision making condition-based data modeling for constructing AI staff.” Journal of the Korean Internet Information Society, Vol. 21, No. 1, pp. 237-246.
Kim, J.-H., Ryu, S.-H., Lee, D.-G. (2023). “A study on the subjectivity of firefighters’ fire response decision-making factors: Focusing on a survey using the Q methodology.” Journal of Knowledge Management, Vol. 24, No. 4, pp. 23-42.
Kim, Y.-W., Lee, B.-Y., Kwon, K.-B. (2023). “Development of Disaster situation specific tailored weather emergency information alert system.” Journal of the Korean Society of Disaster Information, Vol. 19, No. 1, pp. 69-75.
Ko, S.-B. (2025). Safety Management Document Review Adequacy Verification Study Using Generative AI Technology. Master Thesis, Konkuk University.
Ko, Y.-J. (2021). Real-Time Location Identification of Indoor Rescue Requesters at Accident Sites and Location-Based Rescue Response. Ph.D. Dissertation, Myongji University.
Lee, C.-Y., Park, G.-J., Kim, J.-G., Kim, T.-H. (2022). “A design of the social disasters safety platform based on the structured and unstructured data.” Journal of The Korean Society of Disaster Information, Vol. 18, No. 3, pp. 609-621.
Lee, E.-P. (2019). “Time line analysis after fire brigade arrival on Jecheon sports center fire.” Korean Journal of Scientific Criminal Investigation, Vol. 13, No. 1, pp. 50-59. 10.20297/jsci.2019.13.1.50
Lee, K.-J. (2020). A Study on the Problem and Improvement of the Command System in a Large-scale Disaster Scene: Focusing on the Fire Accident Site Command System. Master Thesis, University of Seoul.
Nam, G.-T., Seo, K.-J., Choi, D.-C. (2022). “A study on the development of AI-based fire fighting facility design technology through image recognition.” Journal of The Korean Society of Disaster Information, Vol. 18, No. 4, pp. 883-890.
National Fire Agency (2025). Standard Operating Procedures for Disaster Sites. National Fire Agency, Sejong, Korea.
National Fire Service Academy (2023). Field Command Theory. National Fire Service Academy, Cheonan, Korea.
National Fire Service Academy (2025). Fire Tactics I-1. National Fire Service Academy, Cheonan, Korea.
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Yoon, K.-Y. (2022). “Exploring investigation and analysis techniques - The X Event research method.” Korea Institute of Public Administration, Vol. 40, pp. 65-69.

Information

Publisher :The Korean Society of Disaster Information
Publisher(Ko) :한국재난정보학회
Journal Title :Journal of the Society of Disaster Information
Journal Title(Ko) :한국재난정보학회논문집
Volume : 22
No :1
Pages :71-80
DOI :https://doi.org/10.15683/kosdi.2026.3.31.071

[1] Han, C.-H., Shin, K.-Y., Choi, S.-H., Moon, S.-W., Lee, C.-H., Lee, J.-K. (2020). “A methodology of decision making condition-based data modeling for constructing AI staff.” Journal of the Korean Internet Information Society, Vol. 21, No. 1, pp. 237-246.

[2] Kim, J.-H., Ryu, S.-H., Lee, D.-G. (2023). “A study on the subjectivity of firefighters’ fire response decision-making factors: Focusing on a survey using the Q methodology.” Journal of Knowledge Management, Vol. 24, No. 4, pp. 23-42.

[3] Kim, Y.-W., Lee, B.-Y., Kwon, K.-B. (2023). “Development of Disaster situation specific tailored weather emergency information alert system.” Journal of the Korean Society of Disaster Information, Vol. 19, No. 1, pp. 69-75.

[4] Ko, S.-B. (2025). Safety Management Document Review Adequacy Verification Study Using Generative AI Technology. Master Thesis, Konkuk University.

[5] Ko, Y.-J. (2021). Real-Time Location Identification of Indoor Rescue Requesters at Accident Sites and Location-Based Rescue Response. Ph.D. Dissertation, Myongji University.

[6] Lee, C.-Y., Park, G.-J., Kim, J.-G., Kim, T.-H. (2022). “A design of the social disasters safety platform based on the structured and unstructured data.” Journal of The Korean Society of Disaster Information, Vol. 18, No. 3, pp. 609-621.

[7] Lee, E.-P. (2019). “Time line analysis after fire brigade arrival on Jecheon sports center fire.” Korean Journal of Scientific Criminal Investigation, Vol. 13, No. 1, pp. 50-59. 10.20297/jsci.2019.13.1.50

[8] Lee, K.-J. (2020). A Study on the Problem and Improvement of the Command System in a Large-scale Disaster Scene: Focusing on the Fire Accident Site Command System. Master Thesis, University of Seoul.

[9] Nam, G.-T., Seo, K.-J., Choi, D.-C. (2022). “A study on the development of AI-based fire fighting facility design technology through image recognition.” Journal of The Korean Society of Disaster Information, Vol. 18, No. 4, pp. 883-890.

[10] National Fire Agency (2025). Standard Operating Procedures for Disaster Sites. National Fire Agency, Sejong, Korea.

[11] National Fire Service Academy (2023). Field Command Theory. National Fire Service Academy, Cheonan, Korea.

[12] National Fire Service Academy (2025). Fire Tactics I-1. National Fire Service Academy, Cheonan, Korea.

[13] Yeom, M.-Y. (2016). A Study of Firefighter's Decision-Making in Disaster Scene. Master Thesis, Kangwon National University.

[14] Yoon, K.-Y. (2022). “Exploring investigation and analysis techniques - The X Event research method.” Korea Institute of Public Administration, Vol. 40, pp. 65-69.

Journal of the Society of Disaster Information ISSN:1976-2208(Print) 2671-5287(Online) 한국재난정보학회논문집

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