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An IoT-based Occupational Safety Management System in Cold Storage Facilities

机译:冷藏设施中基于物联网职业安全管理系统

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In the contemporary strategy of cold chain logistics, cold storage plays an important role to keep the inventory under the extreme environmental conditions. As the demand of cold storage services is growing rapidly nowadays, attention paid on occupational safety of warehouse workers is increasing under extreme working environment. Traditionally, the safety of workers are assessed by their experience and personal judgement. Without automatic data capturing tools, it is hard to monitor the actual health status of workers who may be dangerous when working too long in the cold storage facilities. In addition, there is a lack of prompt signal to managers and first-aid teams for instant treatment when the workers get cold injuries or illnesses. Therefore, the real-time health monitoring and positioning of the workers are in need. Nowadays, Internet of Things (IoT) is a mean of real-time interconnection system in which target objects are equipped with the identifying and sensing technologies. This paper presents an IoT-based occupational safety management system (IoT-OSMS) by using the identifying and sensing techniques to locate workers' positions and to guarantee the occupational safety. Bluetooth Low Energy (BLE), a kind of Radio Frequency Identification (RFID) solutions, is used to locate and collect the information of the workers inside the cold storage facilities. The workers' locations are calculated by using Trilateration with Taylor's series adjustment and Kalman filter. On the other hand, fuzzy logic technique is used to examine and generate the customized cold stress and monitoring review cycle. By integrating the positioning and Fuzzy logic approaches seamlessly, it is found that the occupational safety of warehouse workers can be guaranteed and monitored in the real-time situation.
机译:在当代冷链物流策略中,冷库在极端环境条件下保持了库存的重要作用。随着冷库服务的需求日趋迅速发展,对仓库工人职业安全的关注在极端工作环境下正在增加。传统上,工人的安全得到了他们的经验和个人判断。没有自动数据捕获工具,很难监控在冷藏设施中工作过长时可能危险的工人的实际健康状况。此外,当工人获得冷伤或疾病时,对管理人员和急救队缺乏迅速的信号。因此,工人的实时健康监测和定位需要。如今,事物互联网(物联网)是实时互连系统的平均值,其中目标对象配备了识别和感测技术。本文通过使用识别和传感技术来定位工人职位并保证职业安全性,提出了基于物联网职业安全管理系统(IOT-OSMS)。蓝牙低能量(BLE),一种射频识别(RFID)解决方案,用于定位和收集冷藏设施内的工人的信息。工人的位置是通过使用Taylor系列调整和卡尔曼滤波器的三边计算来计算的。另一方面,模糊逻辑技术用于检查和生成定制的冷应力和监测审查周期。通过无缝地整合定位和模糊逻辑方法,发现可以在实时情况下保证仓库工作人员的职业安全性。

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