An IoT-based occupational safety management system in cold storage facilities

Abstract

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.