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Derivation of Smart Urban Regeneration Service Using Monte Carlo Simulation and Estimation of Importance

몬테카를로 시뮬레이션을 활용한 스마트 도시재생서비스 도출 및 중요도 산정

  • Gang, Su-Yeon (Dept. of Urban & Transportation Engineering, Kongju National University) ;
  • Jung, Yeon-Jun (Dept. of Urban & Transportation Engineering, Kongju National University) ;
  • Lee, Kyung-Hwan (Dept. of Urban Systems Engineering, Kongju National University) ;
  • Ko, Eun-Jeong (Institute of Engineering Research, Seoul National University)
  • 강수연 (공주대 도시.교통공학과) ;
  • 정연준 (공주대 도시.교통공학과) ;
  • 이경환 (공주대 도시융합시스템공학과) ;
  • 고은정 (서울대학교 공학연구원)
  • Received : 2022.01.20
  • Accepted : 2022.05.24
  • Published : 2022.06.30

Abstract

In the current 4th industrial revolution era, there is an increasing interest worldwide in smart cities with smart technology applied to established cities. However, in the process of promoting these smart urban regeneration projects, specific and relevant services must first be introduced; few studies have been conducted on the importance of each. Therefore, this study derives several smart urban regeneration services that can be applied to smart urban regeneration projects while utilizing the Monte Carlo simulation (MCS) to supplement the sample limitations and uncertainty risks of existing decision-making methodologies. Therefore, in this study, four types and thirteen detailed serviceswere derived through existing research and related guidelines. Through an expert survey, the importance of each service was calculated, and risks were considered by defining unavoidable, uncertainty factors in a probability distribution using MCS; the process was repeated 100,000 times. The most important service scored 28.4% for Work·Employment, in the detailed service category 9.4% was for the job information service, 9.3% for safe return home service and 9.2% for fire monitoring. These results suggest that smart urban regeneration services should be applied differently according to the location of the target site and the size of the project. Additionally, when implementing smart urban regeneration projects, it is necessary to actively introduce smart urban regeneration services that can help local residents solve job issues, crime and disaster prevention concerns, and environmental problems. From a methodological point of view, this study is significant in that it proposed and utilized MCS to supplement the risk of uncertainty in the existing expert survey. These results are expected to be useful in the process of further promoting smart urban regeneration.

Keywords

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