Google Cloud and solution for industrial automation systems
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This master’s thesis introduces a possible architecture with the Google cloud platform for
storing industrial time-series data from automation programmable logic controller (PLC),
and how different messages from PLC are categorized. Master’s thesis introduces three
cases of how stored data can be used to gain information from the system. The solution
presents a way to divide software responsibilities between local and cloud entity. In the
architecture, few cases as to how data is handled locally and writing messages to the cloud
are explained with more detail and code examples.
The solution was developed concurrently with a new underlying system and because there
was no easy to use and flexible solution that offered needed requirements. The solution
includes interfaces and generalization that it is not dependent on the underlying system,
and architecture is usable with different systems. The architecture was decided to be de-
veloped in a cloud platform that would enable global distribution with additional hosted
tools.