ActSen - AI-enabled Real-time IoT-based Ergonomic Risk Assessment System

被引:7
|
作者
Low, Jia Xin [1 ]
Wei, Yongmei [1 ]
Chow, Joshua [1 ]
Ali, Iskandar F. B. [1 ]
机构
[1] Nanyang Polytech, Sch Engn, Singapore, Singapore
关键词
component; Musculoskeletal Disorders; Muscle Fatigue Analysis; Artificial Intelligence; Machine Learning; IoT;
D O I
10.1109/ICIOT.2019.00024
中图分类号
TP31 [计算机软件];
学科分类号
081202 ; 0835 ;
摘要
Musculoskeletal Disorders (MSDs) are injuries and disorders that affect the human body's movement or musculoskeletal system. There are three primary ergonomic MSD risk factors, High task repetition, Forceful exertions and Repetitive awkward postures. Exposure to these workplace risk factors fatigue the worker's body beyond their ability to recover, leading to MSD. A variety of ergonomic risk assessment tools have been developed such as Rodgers Muscle Fatigue Analysis to help to evaluate the risk of MSD so that early intervention can be applied to prevent the development of an MSD. However, ergonomic risk assessment tools are usually carried out using subjective observational methods, which require a field expert performing a time-consuming analysis of the postures on site. Monitoring workers under staged environment and high manpower cost make observational methods impractical and not accurate to conduct ergonomic risk assessment especially for dynamic and non-routine work. In this paper, ActSen, a real-time ergonomic risk assessment system is proposed. ActSen leverages on the recent development of embedded and Artificial Intelligent (AI) technologies. ActSen can continuously (a) acquire workers activities/postures data using various sensors, (b) process, classify and tabulate the workers movements using AI algorithms, (c) conduct real ergonomic risk assessment based on the detected activities/postures, and (d) output to interactive dashboard to facilitate smart scheduling and provide assistance when needed.
引用
收藏
页码:76 / 78
页数:3
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