An OPC UA client/gateway-based architecture for SCADA systems with automatic mental fatigue detection application

With the emergence of Industry 4.0 concepts, including digital twins, traditional Supervisory Control and Data Acquisition (SCADA) systems impose significant restrictions on the interoperable communication between machines that use various Industrial Internet-of-Things (IIoT) devices. Also, recent Internet-of-Things (IoT) advancements led to the development of the analogous Operator 4.0 concept, which focuses on augmenting workers with technology (e.g., using wearable IoT devices that can monitor workers' health conditions) and constructing "human" digital twins. This thesis presents a new smart factory concept that consists of integrated and interoperable manufacturing machine and human (i.e., worker) digital twin units. First, a new data exchange architecture based on Open Platform Communication protocol Unified Architecture (OPC UA) was developed and tested to create a digital twin of an IIoT device and monitor real-time sensor data. Second, the architecture further incorporated a newly developed and tested mental fatigue detection technique based on wearable photoplethysmography (PPG) sensor readings to create a human's digital twin unit that monitors a worker's mental fatigue to mitigate potential safety risks. Such an integration facilitates real-time monitoring of both machines' processing parameters and factory workers' physiological parameters simultaneously. Experimental results demonstrate the proof-of-concept of the new data exchange architecture in creating interoperable and non-restricted machine and human digital twin units for smart factories.