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What to consider when deploying Internet of Things (IoT) solutions, and when to try a more dynamic approach.
With large capital expenses invested in their production assets, manufacturers need those assets working at capacity. Every hour of downtime is expensive—unplanned downtime is even more so.
One of the tenets of an effective Industry 4.0 strategy is to keep production running by analyzing real-time data at scale to predict and prevent issues that otherwise lead to downtime. This near-continuous production relies on machine-machine communication through the Internet of Things (IoT). As part of an IoT ecosystem, sensors throughout a manufacturing facility capture and communicate necessary information for analysis. At the backend of the IoT ecosystem are machine learning models trained to recognize normal (or abnormal) machine behavior and deliver actionable insights accordingly.
IoT deployment, a key part of digital transformation, is not for manufacturing alone. Any industry which works with machines, equipment, or other assets can use IoT to realize efficiencies; as a result, this technology is on a meteoric growth curve. By 2025, there will be an impressive 27 billion IoT installations around the world, according to IoT Analytics.
So what’s really under the hood when we talk about IoT? And why does it matter if an IoT deployment uses fixed or dynamic sensors?
In this whitepaper, you will learn:
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