Industrial IoT with InfluxDB
The industrial world has a long history of modernizing its process controls in order to keep production running efficiently and safely while minimizing downtime. Yet many are locked in established data historian solutions that are costly and lack the methods needed to provide innovation and interoperability.
Recently, the idea of “Industry 4.0” has come into use. It is a leap forward from computers and automation like the assembly line was a leap forward from the steam engine, which includes autonomous systems being fed raw and trained data. In short, it’s using machine learning and artificial intelligence to improve the efficiency of industrial systems. This development has already occurred in non-industrial settings, and been given the name “IoT”, or the Internet of Things. As such, the implementation of Industry 4.0 is commonly called “IIoT”, for the Industrial Internet of Things.
The goal of IIoT is to create interconnection between devices, sensors, and people; improve information transparency, making data available to operators; provide technical assistance for operators in doing otherwise unpleasant or unsafe tasks; and decentralize decisions so that systems can perform their tasks autonomously.
Yet many are locked in established data historian solutions that are costly and lack the methods needed to provide innovation and interoperability. How can your business go from costly, closed-source, unscalable solutions that are common in the industrial sector to an effective IIoT implementation? In this technical paper, we review a few open source projects you should consider.
