A Study of the Standard Structure for the Social Disaster and Safety Incidents Data

doi:10.15683/kosdi.2021.12.31.817

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2021 Vol.17, Issue 4 Preview Page Next Page

Original Article

A Study of the Standard Structure for the Social Disaster and Safety Incidents Data 사회재난 및 안전사고 데이터 분석을 위한 표준 구조 연구: 이창열¹*ㆍ김태환²
Chang Yeol Lee¹*, Taehwan Kim²; ¹Professor, Department of Computer Engineering, Dongeui University, Busan, Republic of Korea
²Professor, Department of Security Service, Yongin University, Yongin, Republic of Korea

31 December 2021. pp. 817-828

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Abstract

Purpose: In this paper, we propose a common dataset structure which includes the incidents investigation information and features data for machine learning. Most of the data is from the incidents reports of the governmental part and restricts on the social disaster and safety areas. Method: Firstly, we extract basic incidents data from the several incident investigation reports. The data includes the cause, damage, date, classification of the incidents and additionally considers the feature data for the machine learning. All data is represented by XML standard notation. Result: We defined the standard XML schema and the example for the incidents investigation information. Conclusion: We defined the common incidents dataset structure for the machine learning. It may play roles of the common infrastructure for the disaster and safety applications areas

Keywords

Social Disaster

Incident Investigation

Machine Learning

Risk Prediction

Incident Data

연구목적: 본 논문은 사회재난 및 안전사고 발생에 따른 재난 유형별 조사 분석 정보에 대한 공통 데이터 도출과 머신 러닝 기반 사고 예측을 지원하는 특성화 데이터를 통합한 사회재난 및 안전사고 데이터셋 구조를 도출하는 연구에 초점을 맞추었다. 연구방법: 기존 조사 분석 보고서의 사고 분류, 원인, 피해 등을 표시할 수 있는 데이터를 중심으로 머신 러닝에 활용할 수 있는 특성화 데이터 도출과 이에 대한 XML 기반의 표준 체계를 도출한다. 연구결과: XML 기반의 표준 스키마 도출과 사례 제시를 하였다. 결론: 본 논문에서 도출된 표준안을 사회재난 및 안전사고 데이터셋 구축에 활용하고, 이를 기반으로 여러 분야에서 재난 사고 및 안전의 위험을 예측할 수 있는 응용 기술을 개발할 수 있게 지원한다.

키워드

사회재난

사고 분석

머신 러닝

위험 예측

사고 데이터

References

Friend, Z. (2013). Predictive Policing : Using Technology to Reduce Crime, FBI Law Enforcement Bulletin, April 9, 2013
Jung, W.-S., Oh, S.-H., Lee, Y.-T. (2019). "A study on the system implementation of mega complex disaster damage evaluation and estimation using diaster bigdata." The Journal of Korean Institute of Communications and Information Sciences, Vol. 44, No. 7, pp. 1433-1438. 10.7840/kics.2019.44.7.1433
Lee, C.Y. (2018). "A development of the integrated model for the disaster field response and situation information management." Journal of Korea society of disaster information, Vol. 14, No. 1.
Lee, C.Y., Kim. T.H. (2011). "A study of the disaster sign data analysis technologies based on ontology." Journal of the Korean Society of Disaster Information, Vol. 7, No. 3, pp. 220-228.
Lee, H.J., Yun, H.S., Han, H. (2021). "A Study on the selection of types of social disaster by region." KOSDI, Vol. 17, No. 2, pp. 206-217.
MiraeIt Ltd. (2016). A development of the disaster operation management system, Ministry of the Interior and Safety.
MOIS (2018) A development of the social disaster risk index.
MOIS (2020) A development of the risk analysis model in social disaster and applying to local government. MOIS, Korea.
NDMI. (2014) A development of the risk prediction technologies from the real-time disaster risk analysis.
Park, S.Y., Sanggi, H.H., Lee, K.B. (2020). "Trends in disaster prediction technology development and service delivery, electronic and telecommunications trends." Vol. 35, No. 1 pp. 80-88.

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 : 17
No :4
Pages :817-828
DOI :https://doi.org/10.15683/kosdi.2021.12.31.817

[1] Friend, Z. (2013). Predictive Policing : Using Technology to Reduce Crime, FBI Law Enforcement Bulletin, April 9, 2013

[2] Jung, W.-S., Oh, S.-H., Lee, Y.-T. (2019). "A study on the system implementation of mega complex disaster damage evaluation and estimation using diaster bigdata." The Journal of Korean Institute of Communications and Information Sciences, Vol. 44, No. 7, pp. 1433-1438. 10.7840/kics.2019.44.7.1433

[3] Lee, C.Y. (2018). "A development of the integrated model for the disaster field response and situation information management." Journal of Korea society of disaster information, Vol. 14, No. 1.

[4] Lee, C.Y., Kim. T.H. (2011). "A study of the disaster sign data analysis technologies based on ontology." Journal of the Korean Society of Disaster Information, Vol. 7, No. 3, pp. 220-228.

[5] Lee, H.J., Yun, H.S., Han, H. (2021). "A Study on the selection of types of social disaster by region." KOSDI, Vol. 17, No. 2, pp. 206-217.

[6] MiraeIt Ltd. (2016). A development of the disaster operation management system, Ministry of the Interior and Safety.

[7] MOIS (2018) A development of the social disaster risk index.

[8] MOIS (2020) A development of the risk analysis model in social disaster and applying to local government. MOIS, Korea.

[9] NDMI. (2014) A development of the risk prediction technologies from the real-time disaster risk analysis.

[10] Park, S.Y., Sanggi, H.H., Lee, K.B. (2020). "Trends in disaster prediction technology development and service delivery, electronic and telecommunications trends." Vol. 35, No. 1 pp. 80-88.

Journal of the Society of Disaster InformationISSN:1976-2208(Print) 2671-5287(Online)한국재난정보학회

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