文献类型：期刊文献

英文题名：Real-time safety distance detection and warning for elevator inspection based on adaptive monocular depth estimation

作者：Yao, Bing[1];Liu, Ji[1];Luo, Hui[1]

机构：[1]East China Univ Sci & Technol, Sch Informat Sci & Engn, Key Lab Smart Mfg Energy Chem Proc, Minist Educ, Shanghai 200237, Peoples R China

年份：2024

卷号：235

外文期刊名：MEASUREMENT

收录：;EI(收录号：20242316189581);WOS:【SCI-EXPANDED(收录号:WOS:001248731500001)】；

基金：This work was supported by the National Natural Science Foundation of China under Grant 62231010.

语种：英文

外文关键词：Elevator inspection; YOLOv8; Monocular depth estimation; Safety distance detection; Construction safety

摘要：During elevator inspection, workers are prone to collisions with hazards in narrow elevator machine rooms. Because of the numerous elevator machine rooms with diverse scenes in cities, it is difficult to effectively monitor the distance between workers and hazards. We propose a real-time safety distance detection and warning system consisting of four parts: object detection, depth estimation, safety distance detection, and safety warning. By introducing two adaptive error correction terms, the proposed adaptive monocular depth estimation algorithm effectively reduces the distortion of object pixel size with changes in depth and shooting angle. Then the calculation formula has been improved to accurately measure the distance between objects. The system has been successfully applied to safety supervision at the elevator inspection site in Nanchang City, Jiangxi Province, China. The results, with an average relative error of 3.34% and 84 frames detected per second, show the system exhibits excellent accuracy and real-time performance.