This invention describes a system that acts as a central hub for industrial data. It gathers information from factory machines that can label their own data, then adds more context and labels to define how different data points relate to specific business goals, such as minimizing machine downtime or optimizing energy use. This enriched data is then streamed to other systems, like analytics tools, that are interested in particular topics for further analysis.
Why it matters: Filed before significant advancements in AI and machine learning, particularly in automated data contextualization and real-time industrial analytics. These developments since 2019 could make the system's core function of defining correlations and analytic topics far more efficient and powerful.
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