스마트 기술을 활용한 승강기 위험 상황 자동 예측판단 기법 개발

Abstract

In Korea, the first elevator was introduced in 1910. Thereafter, Korea has been ranked 3rd in installation and 7th in maintenance worldwide. During the last five years, an average of 35000 elevators per year have been installed, and the total number of installed elevator increases every year. In Korea, 92.1% of the elevator malfunctions are to be stuck in an elevator. When passengers are stuck in an elevator, elevator maintenance personnel or firefighters usually rescue them; however, the number of firefighter rescues has been increasing compared to the number of new elevators installed. Along with the increase in being stuck in an elevator and the increase in the number of firefighter rescues, anxiety of elevator passengers and social costs are also increasing. Hence, there is a need to find a method to reduce these incidences. Therefore, it is essential to develop an intelligent rescue system using video, video, vibration, noise and elevator’s malfunction signal for various hazard pattern recognition. In this study, we propose a new technology that can prevent incidents such as being stuck in an elevator, violence or collapse, and minimize the gap in field management through a fast and accurate hazard prediction and response method based on machine learning.