In manufacturing plants, a review of the labor environment is as important as the efficiency of the manufacturing process. In the food industry, a high level of labor motivation is as important as preventing contamination with foreign matters and with drugs by malicious persons. In such circumstances recognizing individual persons is very difficult because the uniforms, caps, masks are worn.
This system is able to identify individual persons by ID number given by the system to all the laborers at their entry to the plant. OpenPose, which works on edge devices, like IP cameras and an AI Box set up near production lines, detects a worker’s skeleton and posture in a factory. Through skeleton data, OpenPose captures and TensorFlow judges if a posture is normal or abnormal at the primary level. Data captured by edge devices is sent to MQTT broker in an edge server, then MQTT data is registered in Elasticsearch. Unusual skeleton data detected through unsupervised machine learning is sent to VANTIQ, using Webhook. All data gathered to VANTIQ Edge are checked again to determine if they’re normal or not. If the system detects an abnormality in monitored labor notification is sent to an appropriate factory manager according to predefined rules. Data are recorded along with captured images in VANTIQ Cloud and used for anomaly detection’s administration and notification. A dashboard is provided as well, on which recorded data can be seen.