• Proceedings of the Korean Society of Disaster Information Conference
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• 2023.11a
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• pp.45-46
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• 2023

본 논문은 국제민간항공기구(ICAO)의 안전 정의를 기반으로, 항공안전을 유지하기 위해 체계적인 안전관리시스템(Safety Management System, SMS)이 필요함을 강조한다. 특히, COVID-19 이후의 항공 환경 변화에 빠르게 대응할 수 있는 안전관리체계의 필요성을 제기하였으며, 또한, 기존의 하인리히의 법칙을 확장한 Bird의 신도미노 이론을 활용하여 '안전하지 않은 행위'를 세부적으로 분석하고 데이터를 기반으로 이를 탐지하고 관리할 수 있는 방안을 제시한다. 이를 통해 사고나 사건 발생 이전에 이상 경향을 파악하는 중요성을 강조하며, 이를 위해 항공안전데이터를 수집하고 전처리하여 분석의 기반을 마련하고자 한다. 본 논문은 데이터 분석 기술을 활용하여 항공안전을 향상시키는 방법을 탐구하고, 이를 통해 예방적 안전관리의 기반을 제공할 수 있을 것으로 기대하며, 더불어, 데이터 분석 기술의 중요성을 강조하며, 이를 적극적으로 도입하여 안전성을 높이는데 핵심 역할을 할 것을 희망한다.

• Journal of the Korean Society for Aviation and Aeronautics
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• v.30 no.4
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• pp.145-158
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• 2022

To manage State Safety Program (SSP) in a more integrative and proactive manner, an aviation safety authority of the state shall detect and assess the risk of emerging or hidden safety hazards before they provoke accidents or incidents(ICAO, 2018). In case of South Korea, safety risk assessment is conducted by calculating the likelihood and severity of the hazard following ICAO's safety management manual. It is reasonable to extract the safety risk likelihood by calculating the number of occurrence caused by the hazard. However, it is ambiguous to assess the safety risk severity defined as the extent of harm that might be expected to occur as a consequence of the identified hazard. In this paper, a safety risk assessment method which quantitatively calculates the risk of hazard using aviation safety data(i.e. aviation safety mandatory report, etc.) is proposed. By utilizing the proposed method, the existing process that safety risk is being subjectively assessed by safety inspectors can be supplemented. So that essential aviation safety policy decision making can be accomplished by the accurate result of safety risk assessment.

• Journal of Advanced Navigation Technology
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• v.26 no.6
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• pp.528-535
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• 2022

Although the domestic aviation industry has made rapid progress with the development of aircraft manufacturing and transportation technologies, aviation safety accidents continue to occur. The supervisory agency classifies hazards and risks based on risk-based aviation safety data, identifies safety trends for each air transportation operator, and conducts pre-inspections to prevent event and accidents. However, the human classification of data described in natural language format results in different results depending on knowledge, experience, and propensity, and it takes a considerable amount of time to understand and classify the meaning of the content. Therefore, in this journal, the fine-tuned KoBERT model was machine-learned over 5,000 data to predict the classification value of new data, showing 79.2% accuracy. In addition, some of the same result prediction and failed data for similar events were errors caused by human.

• The Journal of Bigdata
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• v.8 no.2
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• pp.1-13
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• 2023

Current analysis of air passengers mainly relies on statistical methods, but there are limitations in analyzing detailed aspects such as travel routes, number of regional passengers and airport access times. However, with the advancement of big data technology and revised three data acts, big data-based transportation analysis has become more active. Mobile communication data, which can precisely track the location of mobile phone terminals, can serve as valuable analytical data for transportation analysis. In this paper, we propose a air passenger Origin/Destination (O/D) extraction algorithm based on mobile communication data that overcomes the limitations of existing air transportation user analysis methods. The algorithm involves setting airport signal detection zones at each airport and extracting air passenger based on their base station connection history within these zones. By analyzing the base station connection data along the passenger's origin-destination paths, we estimate the entire travel route. For this paper, we extracted O/D information for both domestic and international air passengers at all domestic airports from January 2019 to December 2020. To compensate for errors caused by mobile communication service provider market shares, we applied a adjustment to correct the travel volume at a nationwide citizen level. Furthermore correlation analysis was performed on O/D data and aviation statistics data for air traffic users based on mobile communication data to verify the extracted data. Through this, there is a difference in the total amount (4.1 for domestic and 4.6 for international), but the correlation is high at 0.99, which is judged to be useful. The proposed algorithm in this paper enables a comprehensive and detailed analysis of air transportation users' travel behavior, regional/age group ratios, and can be utilized in various fields such as formulating airport-related policies and conducting regional market analysis.

• Proceedings of the Korean Society of Computer Information Conference
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• 2021.01a
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• pp.281-282
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• 2021

본 논문에서는 항공 수요예측을 위한 빅데이터 기반 플랫폼의 설계 및 실증 결과를 제시한다. 항공 수요예측 통합 플랫폼은 항공산업 관련 데이터를 Open API, RSS Feed, 웹크롤러(Web Crawler) 등을 이용하여 수집 및 분석하여 자체 개발한 항공 수요예측 알고리즘을 기반으로 결과를 시각화하여 보여주도록 구현되어 있다. 또한, 제안하는 플랫폼의 사용자 인터페이스를 통해 변수 설정을 하여 단위별(Global, National 등), 기간별(단기, 중장기 등), 유형별(여객, 화물 등) 예측 통계 자료를 도출할 수 있다. 플랫폼의 성능 검증을 위해 정형화된 데이터를 비롯하여 소셜네트워크서비스(SNS), 검색엔진 등에서 수집한 비정형 데이터까지 활용하여 특정 키워드의 빈도와 특정 노선에 대한 항공 수요간 상관관계를 분석하였다. 개발한 통합 플랫폼의 지능형 항공 수요예측 알고리즘을 통해 전반적인 공항 운영 및 공항 운영 정책 수립에 기여할 것으로 예상한다.

• Proceedings of the Korean Society of Computer Information Conference
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• 2024.01a
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• pp.169-170
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• 2024

본 논문은 2017년부터 2022년까지의 항공정보통계포털 데이터를 기반으로 코로나19가 항공 산업에 미치는 영향을 깊이 분석한 것이다. 인천국제공항, 김포공항, 제주국제공항의 데이터를 중점으로 사용했다. 국내선과 국제선의 항공수요 추이를 월별로 시각화하여, 코로나19의 직접적인 영향 뿐 아니라 사회경제적인 다양한 요인과의 상호작용을 강조했다. 특히, 국내 여행비용 상승이 해외 여행의 매력도를 높일 수 있는 요인으로 논의되었다. 논문은 코로나19의 영향이 계속되며 항공 산업에 지속적인 변화를 초래하고 있다는 결론을 내리고, 항공 산업의 미래 전략 수립 시 다양한 변수를 고려하는 중요성을 강조했다. 또한, 코로나19 이후의 항공 여행 패러다임을 예측하는 데 중요한 기초 자료로서의 역할을 강조한다.

• Proceedings of the Safety Management and Science Conference
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• 2010.04a
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• pp.161-166
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• 2010

항공물류 분야의 개선을 위해 공항에서 연구와 투자를 통하여 공항 선진화를 이루고 있고, 우리나라도 지속적으로 증가하는 항공물류 분야의 개선이 필요하다고 인식하고 개선을 위한 방안을 연구하고 있지만, 항공물류 전반에 걸쳐 통합적인 개선이 이루어지지 않고 개별적이거나 부분적인 시스템 개선으로 중복 투자와 비효율성의 문제가 발생하고 있다. 본 논문에서는 이러한 문제점들을 해결하기 위해 현행 항공물류 프로세스를 수 출입으로 구분하여 분석하였고, 시스템 통합 사례들을 검토하여 프로세스 상에서 발생하는 문서들을 분석하였다. 이중 인터페이스 대상 문서를 선정하고 문서의 데이터 내용과 형식을 정의하였다. 정의한 데이터의 형식을 대상 문서에 코드로 적용시키고 시뮬레이션을 통하여 데이터 저장량을 비교 분석하였다. 이를 통해 항공물류 이해관계자간의 정보 교환이 용이해지고 동일한 정보를 재생성하거나 재가공하는 비효율성을 감소시킬 것으로 기대된다.

• Electronics and Telecommunications Trends
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• v.36 no.6
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• pp.55-66
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• 2021

The air traffic industry, one of Korea's major industries, has recently experienced increased demand from overseas air passengers, launched a low-cost airline, and increased special freight transportation capacity. These initiatives have had a positive impact on air traffic (for example, profitability); however, air traffic management has become more complex, which has increased the incidence of aviation accidents and created safety hazards. There is an increasing need to collect and analyze aviation data that can proactively respond to aviation accidents. Concatenation of collected aviation data as big data and the development of artificial intelligence technology are gradually expanding aviation safety event analysis from conventional statistical analysis to machine learning-based analysis. This paper surveys the trends of flight safety event analysis to derive aviation safety risk factors by looking at the types and characteristics of aviation data that can be used to predict accidents related to safety in aviation operations.

• Journal of Advanced Navigation Technology
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• v.26 no.2
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• pp.54-62
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• 2022

ICAO has recommended data-based aviation safety management and decision-making systems through Annex 19(Safety Management) and Doc 9859(Safety Management Manual), stressing that safety can be greatly improved by sharing aviation safety information throughout the industry. Accordingly, advanced aviation countries have built infrastructure to collect and analyze various aviation safety data in an integrated manner, and also tried to spread identified major safety issues across the industry. On the other hand, in Korea, each stakeholder collects, manages and analyzes safety data individually, so there is a limit to use them in integrative manner. In addition, the scope of using and sharing aviation safety information such as analysis result is also focused on safety management at the national government level, which is insufficient to be shared throughout the industry. Accordingly, the purpose of this study is to present a plan to share and utilize the domestic aviation safety information. To do this, we compare the current situation between FAA and domestic industry and suggest the improvement plans.

• Journal of the Korean Society for Aviation and Aeronautics
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• v.28 no.4
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• pp.89-101
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• 2020

In order to enhance the safety of the international aviation industry, the International Civil Aviation Organization has recommended establishing an operational foundation for systematic and integrated collection, storage, analysis and sharing of aviation safety data. Accordingly, the Korea aviation industry also needs to comprehensively manage the safety data which generated and collected by various stakeholders related to aviation safety, and through this, it is necessary to previously identify and remove hazards that may cause accident. For more effective data management and utilization, a standard structure should be established to enable integrated management and sharing of safety data. Therefore, this study aims to propose the framework about how to manage and integrate the aviation safety data for big data-based aviation safety management and shared platform.