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ActSen - AI-Enabled Real-Time IoT-Based Ergonomic Risk Assessment System

机译:ACTSEN - 支持AI的实时IOT的人体工程学风险评估系统

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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 nonroutine 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.
机译:肌肉骨骼疾病(MSDS)是影响人体运动或肌肉骨骼系统的伤害和障碍。有三个主要符合人体工程学的MSD风险因素,高任务重复,有力的努力和重复的尴尬姿势。暴露于这些工作场所的风险因素疲劳,超越其恢复能力,导致MSD。已经开发了各种符合人体工程学风险评估工具,例如Rodgers肌肉疲劳分析,以帮助评估MSD的风险,从而可以应用早期干预以防止MSD的发展。然而,符合人体工程学风险评估工具通常使用主观观测方法进行,这需要一个现场专家对现场姿势进行耗时的分析。监测阶段环境下的工人和高人力成本使观测方法不切实际,不准确地开展人体工程学风险评估,特别是对于动态和非参半的工作。本文提出了一个实时互动性风险评估制度。 Actsen利用嵌入式和人工智能(AI)技术的最新发展。 Actsen可以持续使用(a)使用各种传感器获得工人活动/姿势数据,(b)流程,分类和制表工人使用AI算法的运动,(c)根据检测到的活动/姿势进行真正的符合人体工程学风险评估,并(D )输出到交互式仪表板以促进智能调度并在需要时提供帮助。

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