Assessment of the handcart pushing and pulling safety by using deep learning 3D pose estimation and IoT force sensors
作者：
Highlights：
• Manual safety management of pushing and pulling (P&P) tasks is inefficient.
• IoT force sensors were used to assess P&P forces.
• Safety of P&P acts was assessed from 3D poses obtained with the VIBE algorithm.
• Besides increased forces, unsafe P&P acts are correlated with the P&P momentum.
• Future studies should account for turn-points and loading/unloading of cargo.
摘要
•Manual safety management of pushing and pulling (P&P) tasks is inefficient.•IoT force sensors were used to assess P&P forces.•Safety of P&P acts was assessed from 3D poses obtained with the VIBE algorithm.•Besides increased forces, unsafe P&P acts are correlated with the P&P momentum.•Future studies should account for turn-points and loading/unloading of cargo.
论文关键词：Deep learning,Ergonomics,Pushing and pulling,Handcart,Unsafe acts
论文评审过程：Received 15 July 2020, Revised 1 May 2021, Accepted 5 June 2021, Available online 12 June 2021, Version of Record 21 June 2021.
论文官网地址：https://doi.org/10.1016/j.eswa.2021.115371
