Cloud vs Edge PHM: $47K/Year Gap in 100-Sensor Setup

#predictivemaintenanc #edgecomputing #cloudarchitecture #vibrationmonitoring

The $800/Month AWS Bill That Made Me Rethink Everything

Streaming raw vibration data from 100 sensors to AWS at 10kHz each costs about $847/month just in data transfer fees. Add compute, storage, and suddenly your predictive maintenance proof-of-concept is burning through budget faster than the bearings you're trying to save.

I ran the numbers for a real 100-sensor vibration monitoring deployment—cloud-only vs edge preprocessing vs hybrid—and the cost gap was shocking enough to change the entire architecture.

Detailed view of a server rack with a focus on technology and data storage. — Photo by panumas nikhomkhai on Pexels

The Scenario: 100 Accelerometers, 10kHz Each

Industrial vibration monitoring typically uses MEMS accelerometers sampling at 10-25kHz (ISO 10816 recommends at least 3x the highest fault frequency you want to detect). For bearing fault detection, 10kHz is the bare minimum—you need headroom for gear mesh frequencies and harmonics.

Each sensor generates:
$$
\text{Data rate} = 10,000 \text{ samples/sec} \times 4 \text{ bytes (float32)} = 40 \text{ KB/s}
$$

With 100 sensors:
$$

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