The Internet of Things (IoT) represents new opportunities for manufacturers to capitalize on the value of data for their business. One of those opportunities is through leveraging an approach called machine learning, which is a branch of artificial intelligence that enables machines (or virtual representations of machines in the cloud) to learn new behaviors based on their external environments, internal health, and changing inputs. However, in order for machine learning to work, humans must be able to grok the context of how the machine data is collected, aggregated, and consumed…
Analytics enable humans to give machines a voice – the ability for the machines to provide or derive insights based on data. Making machines more human with a voice in this way doesn’t happen overnight, but the road that leads there starts with basic connectivity and data collection. Once data is collected, further levels of analytics maturity may be achieved, including the ability to remotely describe a problem, diagnose the root cause of a problem, and predict a problem that may happen in the future.
Source: Mark Benson, Exosite
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