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Detail
Journal Article
항공안전데이터 및 분석 동향
- Issue Date
- 2021-12
- Citation
- 전자통신동향분석, v.36, no.6, pp.55-66
- ISSN
- 1225-6455
- Publisher
- 한국전자통신연구원
- Language
- Korean
- Type
- Journal Article
- Abstract
- 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.
- KSP Keywords
- Air traffic management, Artificial intelligence technology, Aviation accidents, Big-data, Flight safety, Freight transportation, Learning-based, Low-cost, Risk Factors, Safety hazards, Statistical Analysis
This work is distributed under the term of Korea Open Government License (KOGL)
(Type 4: : Type 1 + Commercial Use Prohibition+Change Prohibition)
(Type 4: : Type 1 + Commercial Use Prohibition+Change Prohibition)
