Condition monitoring is the data-collection foundation that predictive maintenance builds on. Instead of inspecting a machine during a scheduled visit, sensors stay attached and report at a set interval. A wireless accelerometer on a motor housing, logging vibration spectra every few minutes, is the classic example; rising energy in specific frequency bands points to bearing damage long before it is audible.
The approach itself does not require machine learning; threshold alarms on well-understood metrics catch many problems. What IoT changes is the economics: battery-powered sensors and low-power radios make it affordable to instrument hundreds of ordinary assets, not just the few critical ones. The resulting time-series data also feeds OEE and energy analyses. Our Industrial IoT guide places it in the wider factory stack.
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