Designing an IoT system for an electromechanical sorting line

From a moving conveyor to a live cloud dashboard.

The thesis explores integrating the Internet of Things with electromechanical systems by monitoring and controlling a box-sorting process. A virtual conveyor line detects boxes and separates them into small, medium and large — while every signal (counts, speeds, arm states, faults) is collected, stored and visualised in real time.

It spans the whole stack: building the 3D scene in Factory I/O, programming the control logic in Ladder on Siemens TIA Portal, bridging the PLC to the cloud over OPC UA with Node-RED, storing time-series data in InfluxDB on AWS, and presenting it through secured Grafana dashboards — plus a custom TIA Portal function block that tracks machine runtime for maintenance.

The data pipeline, end to end.

What it delivers.

Beyond the core pipeline, the system raises automatic fault alerts (missing boxes, sudden speed drops), tracks lost boxes, and includes a custom TIA Portal function block that monitors each conveyor's runtime — turning raw machine signals into maintenance insight.