• Title/Summary/Keyword: Aviation Safety Data

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A Study on the Analysis of Aviation Safety Data Structure and Standard Classification (항공안전데이터 구조 분석 및 표준 분류체계에 관한 연구)

  • Kim, Jun Hwan;Lim, Jae Jin;Lee, Jang Ryong
    • 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.

Aviation Safety Mandatory Report Topic Prediction Model using Latent Dirichlet Allocation (LDA) (잠재 디리클레 할당(LDA)을 이용한 항공안전 의무보고 토픽 예측 모형)

  • Jun Hwan Kim;Hyunjin Paek;Sungjin Jeon;Young Jae Choi
    • Journal of the Korean Society for Aviation and Aeronautics
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    • v.31 no.3
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    • pp.42-49
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    • 2023
  • Not only in aviation industry but also in other industries, safety data plays a key role to improve the level of safety performance. By analyzing safety data such as aviation safety report (text data), hazard can be identified and removed before it leads to a tragic accident. However, pre-processing of raw data (or natural language data) collected from each site should be carried out first to utilize proactive or predictive safety management system. As air traffic volume increases, the amount of data accumulated is also on the rise. Accordingly, there are clear limitation in analyzing data directly by manpower. In this paper, a topic prediction model for aviation safety mandatory report is proposed. In addition, the prediction accuracy of the proposed model was also verified using actual aviation safety mandatory report data. This research model is meaningful in that it not only effectively supports the current aviation safety mandatory report analysis work, but also can be applied to various data produced in the aviation safety field in the future.

Requirements for Operation Procedure and Plan for the Korean Aviation Safety Big-Data Platform based on the Case of FAA ASIAS (국내 항공안전 빅데이터 플랫폼 운영관리체계 수립 중점 - FAA ASIAS를 중심으로 -)

  • Kim, Jun Hwan;Lim, Jae Jin;Park, Yu Rim;Lee, Jang Ryong
    • Journal of the Korean Society for Aviation and Aeronautics
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    • v.29 no.4
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    • pp.105-116
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    • 2021
  • The importance of a systematic approach to collect, process, analyze, and share safety data in aviation safety management is continuously increasing. Accordingly, the domestic aviation industry has been making efforts to build a Big-data platform that can utilize multi-field safety data generated and managed by various stakeholders and to develop safety management technology based on them. Big data platforms not only must meet appropriate technical requirements, but also need to establish a management system for effective operation. The purpose of this study is to suggest the requirements of the aviation safety big data platform operation procedure and plan by reviewing the advanced overseas cases (FAA ASIAS). This study can provide overall framework and managerial direction for the operation of the aviation safety big data platform.

A Study on the Sharing and Utilizing the Domestic Aviation Safety Information Based on FAA Case (FAA 사례 기반 국내 항공안전정보 공유·활용 방안 연구)

  • Park, Yu-rim;Kim, Jun-hwan;Choi, Hyun-seon;Chung, Min-joo
    • 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.

Feasibility Study of Aviation Safety Data Analysis for Airworthiness Management System Improvement (항공안전 데이터 분석 기반 항공기 감항관리체계 개선 방안 연구)

  • Jeong, Hyun-Jin;Kim, Seung-Kak;Kim, Yong;Sim, Yeong-Min
    • Journal of the Korean Society for Aviation and Aeronautics
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    • v.25 no.2
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    • pp.25-38
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    • 2017
  • Current limitation of Aviation airworthiness manage system and text based Aviation safety report data, lack of Data Manage system for aviation parts failure and lack of continuing airworthiness related to task linking system for Inspection/Report/Improvement(AD ; Airworthiness Directive) have been apprehended to suggest direction of realizing improved operating system by applying aviation airworthiness manage system by using standardization and safety performance index based managing and safety performance index based data analyzing.

Trends of Aircraft Safety Data and Analysis Methods (항공안전데이터 및 분석 동향)

  • Kim, J.Y.;Park, N.S.
    • 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.

A Study on Auto-Classification of Aviation Safety Data using NLP Algorithm (자연어처리 알고리즘을 이용한 위험기반 항공안전데이터 자동분류 방안 연구)

  • Sung-Hoon Yang;Young Choi;So-young Jung;Joo-hyun Ahn
    • 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.

A Study on the Improvement of Aviation Safety Management System through Analysis of Legal System and Data Status (법제도 및 데이터 현황 분석을 통한 항공안전관리시스템 개선방안 연구)

  • Hae-yoon Byeon;Hyun-Jin Jeong
    • Journal of the Society of Disaster Information
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    • v.19 no.1
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    • pp.105-116
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    • 2023
  • Purpose: The purpose of this study is to present the preemptive prevention and improvement measures for aviation safety management by examining the current status of the aviation industry and the operation system of the aviation safety management system and identifying the shortcomings of the currently operating aviation safety management system. Method: A plan to improve aviation safety management was proposed through an analysis of recent incidents and accidents, current status of domestic laws, and analysis of overseas operating institutions and safety management systems. Result: Through the recent aircraft safety-related incidents, deficiencies of currently operating aviation safety management, and response cases of advanced countries in overseas aviation, improvement points in terms of management systems and laws and preventive aviation safety management plans were derived. Conclusion: The method for improving aviation safety management was presented based on the technique using data, and it should be materialized through additional related research.

A Study on De-Identification Methods to Create a Basis for Safety Report Text Mining Analysis (항공안전 보고 데이터 텍스트 분석 기반 조성을 위한 비식별 처리 기술 적용 연구)

  • Hwang, Do-bin;Kim, Young-gon;Sim, Yeong-min
    • Journal of the Korean Society for Aviation and Aeronautics
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    • v.29 no.4
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    • pp.160-165
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    • 2021
  • In order to identify and analyze potential aviation safety hazards, analysis of aviation safety report data must be preceded. Therefore, in consideration of the provisions of the Aviation Safety Act and the recommendations of ICAO Doc 9859 SMM Edition 4th, personal information in the reporting data and sensitive information of the reporter, etc. It identifies the scope of de-identification targets and suggests a method for applying de-identification processing technology to personal and sensitive information including unstructured text data.

Study of the Introduction on the Aviation Safety Data Protection System (항공안전데이터 보호제도 도입 방안 연구)

  • Kim, Eun-jung
    • The Korean Journal of Air & Space Law and Policy
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    • v.33 no.1
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    • pp.81-120
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    • 2018
  • To promote the aviation safety reporting system that is operated to enhance aviation safety and to utilize related information, it should first be preceded by standards for non-punishment and data protection. It is because the purpose of collection and analysis of aviation safety related data through the aviation safety reporting system is to prevent recurrence of accidents by investigating their causes through collection and analysis of diverse types of information related to aviation safety. Both mandatory and voluntary reporting systems are in operation for aviation safety under the current Aviation Safety Act. It is said that they were introduced to survey causes for accidents and to prevent recurrences. In fact, however, it is hard to expect active implementation of the reporting system for aviation safety unless the reporters are firstly exempted from punishment. Therefore, the system should be improved so that it can satisfy its purpose and the purposes of data collection concerning aviation safety through examination of the purposes of the reporting system. One of the matters that needs to be considered to promote the reporting system should be the scope of aviation safety hindrances presupposed under the current institution. The voluntary aviation safety reporting system differs from the systems of ICAO or the key advanced countries, including the USA and the UK as it limits the target accidents subject to reporting to minor aviation safety hindrances only. That being said, improvements should be made by requiring mandatory reporting of aviation safety hindrances based on their severity while recognizing a greater variety of aviation safety concerns like international standards. Safety actions and sharing of information based on collection and analysis of diverse data related to aviation safety will greatly contribute to enhance aviation safety as the purposes of the reporting system are to explore causes for accidents and to prevent their recurrences. What is most important in this regard is strict data protection and non-punishment principles; compliance with them should be secured. We can hardly expect the successful operation of the system unless the reporter is exempted from punishment and the relevant data is protected as promotion of voluntary reporting is an essential factor for enhancing the safety culture. Otherwise, the current system may induce hiding of relevant facts or data to evade punishment. It is true that the regulation for enhancing safety tends to have limitations or blind spots; nevertheless, it should still be enforced strictly and completely. Technological progresses and mistakes of operators appear in different forms based on individual cases. The consequential damages may amount to a truly severe level. Therefore, we have studied and suggested to the methods of activiation and amendments on the aviation safety reporting system, which is referred for one of the proactive safety management systems. The proposed improvement of the reporting system and introduction of non-punishment for collection of aviation safety data for deploying a preemptive prevention system would serve as the backbone for enhancing aviation safety in Korea.