Abstract:
Industrial environments need reliable and fast data monitoring to maintain
operational efficiency and safety. This project takes on the task of constructing a secure
Industrial Internet of Things (IIoT) pipeline to create an end-to-end data collecting and
visualization system. My work is centered on the system's basic integration and data
processing elements. The approach entailed establishing Node-RED to communicate
directly with a Programmable Logic Controller (PLC) and collect vital process data. This
data was then published to a MQTT broker, and the communication channel was
encrypted with TLS certificates created by Step-CA to assure data integrity and secrecy.
As a result, I created a service to listen to MQTT topics, parse the incoming data, and
store it in a TimescaleDB database for efficient time-series analysis.
For data presentation, I built a Flask-based web application with two primary
functions: it embeds a Grafana dashboard that queries TimescaleDB for historical data
visualization, and it also uses a WebSocket connection to display live data directly from
the MQTT stream, providing an immediate, real-time view of the industrial process. The
final product is a safe and fully functional monitoring tool that later can send the user
both live and historical data. This shows that industrial automation hardware can be
successfully combined with modern open-source IoT technology.
