Airport Congestion Analysis with Big Data Analysis - The Case of Gimpo Airport -

빅데이터 분석을 활용한 공항 혼잡도 분석 - 김포공항 사례를 중심으로 -

  • 김진아 (한국공항공사 항로시설본부 인천항공교통시설단 시스템정보부) ;
  • 김진기 (한국항공대학교 경영학부)
  • Received : 2020.03.22
  • Accepted : 2020.06.21
  • Published : 2020.06.30


This study is designed to help customers use more comfortable airports by predicting congestion and congestion times by identifying the traffic routes of passengers in the airport building by day of the week and time by using Wi-Fi sensor collectors, one of the IoT technologies. Analysis of passenger traffic analysis data showed that the most congested time zones were from noon. to 2p.m. for all facilities, which could be used to improve major facilities. Regression analysis of factors affecting congestion found that self-check-in reduces congestion and check-in counters increases congestion. These findings will provide important implications for operations, including congestion management at airports.



  1. Schwab, Klaus, "The Fourth Industrial Revolution," Currency, 2017.
  2. Park, C.-K., "A study on the passenger circulation system of the airport passenger terminal", Korean Institute of Interior Design Journal. 19(3), 2010, pp. 260-268.
  3. Bae, Y., "A study on the improvement of sizeestimation airport passenger terminal using cause and effect diagram. department of construction management", Graduate School of Engineering of Hanyang University, 2018.
  4. Kang, Y. J., "A study for enhancing performance measure of a passenger terminal simulation model", Master Thesis, Graduate School of Korea Aerospace University, 2017.
  5. Seo, H. J., "A study on the customer behavioral analysis using big data of distribution industry", Department of Applied Statistics, Graduate School of Gachon University, 2017.
  6. An, H., "A study on the sentiment analysis in fashion design using big data - Focused on text mining and semantic network analysis", Department of Clothing & Textiles, The Graduate School, Ewha Womans University, 2017.
  7. Turban, E., Pollard, C., Wood, G., "Information Technology for Management", 11th edition, Wiley Custom. ISBN: 978-1-119-92381-7, 2018.
  8. Kim, J.-S., "Big data analysis technologies and practical examples", The Journal of the Korea Contents Association, 12(1), 2014, pp. 14-20.
  9. Park, R. U., "A plan for activation of local tourism through big data with focus on the Jeollabuk-do", Department of Integrated Bio-Resource Science, Graduate School of Jeonju University, 2017.
  10. Kim, J. S., "A big data based spatio-temporal sensor data processing system", Doctoral Thesis, Graduate School of Konkuk University, 2017.
  11. Lee, Y. J., "A study on airport parking lot scale for international airports - Focused on Incheon international airport", Department of Business Administration, Graduate School of Aviation & Management of Korea Aerospace University, 2013.
  12. Moon, D. H., "An establishment of big data at a corporation and a study on the application", Graduate School of Business of Gyeong Sang National University, 2016.
  13. Choi, M. K., "A study on the indoor evacuation path model using space big data of IoT sensor", Department of Geography, Graduate School of Kyung Hee University, 2018.
  14. Kim, J. S., "Subway congestion prediction and recommendation system using big data analysis", Journal of Digital Convergence, 14(11), 2016. pp. 289-295.
  15. Lee, J. G., "A study on improvement of local traffic information providing using big data", Department of Software Engineering, Graduate School of Information Science, Soongsil University, 2017.
  16. Kim, H., "Development of a congestion index for expressway service areas using floating population big data", Graduate School of Transport & Intelligent Transport Systems of Ajou University, 2017.
  17. Han, Y. H., "Development of spatiotemporal congestion recognition index based on big traffic data", Doctoral Thesis, Graduate School of City University of Seoul, 2018.
  18. Min, Y. S., "A study on the efficiency of the national suicide prevention project using big data analysis", Department of Forensic Science of Sungkyunkwan University, 2019.
  19. Yoon, J. H., "A study on applying big data analytics in the electric power industry", Graduate School of Information Science, Yonsei University, 2017.
  20. Lee, S.-J., "The determinants of the implementation of the big data in traffic fields: perspectives of data quality management", Department of Management Information System, Graduate School, Keimyung University, 2018.
  21. Ministry of Construction and Transport, "The Second Airport Development Long-term Master Plan", 1999.
  22. Ministry of Land, Infrastructure and Transport, "The Third Airport Development Long-term Master Plan. Chapter 6. Design and Capacity Estimate of Airport Facility", 2005.
  23. Nepal, R., Al Irsyad, M. I., Nepal, S. K., "Tourist arrivals, energy consumption and pollutant emissions in a developing economyimplications for sustainable tourism", Tourism Management, 72, 2019, pp. 145-154.