Communication/upload devices (e.g., Smartbox) can behave differently based on specific conditions. This article explains what to expect from your communication device.
| Data mode | Low | High | Engineering Scan | Airchitect Scan |
| Main purpose | Machine maintenance management | Machine monitoring | (internal) Remote troubleshooting | (internal) Remote audit for Airchitect |
| Data transmitted* |
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| Sampling Period | 1 week | 5 minutes | 5 seconds | 5 seconds |
| Upload Frequency | N/A | 10 minutes | 10 minutes | 10 minutes |
| Events (alarms) | Machine event + snapshot | Machine event + snapshot + Floating window | Behavior is license dependent | Behavior is license dependent |
| Duration | Always (default) | License dependent | 7 days | 8 days |
Concepts explained
Data transmitted
The measurement points that are captured and uploaded depend on the data mode and the firmware version of the Smartbox. There is a list available with the respective measurement points (MPs). Only if an MP is on the list, we will upload it.
Data Sampling Period
This is the frequency at which data is collected over a specific period of time. A higher sampling rate allows for more frequent data collection, capturing finer details, but it also increases data volume. On the other hand, a lower sampling rate may miss rapid changes in the signal.
Upload Frequency
This refers to how often the collected data from the machine is sent or uploaded to our cloud server for storage, analysis, and processing. It represents the rate at which the data is transmitted from the Smartbox, Clamp, or Central Controller to our cloud.
Machine Event
Events are interpretations of machine behavior by the machine's controller. For example, if the machine suddenly stops, this is interpreted as a Shutdown event. Such events are sent to our cloud via the upload device once they are triggered.
Snapshot
A snapshot refers to a momentary capture of critical machine data and parameters at the moment of a machine event. It includes information such as operating conditions, performance metrics, sensor readings, and any anomalies observed.
Floating Window
This is a time-based data aggregation that collects and analyzes 36 consecutive snapshots. This approach provides a dynamic view of the machine's performance over a specific period (right before a machine-event), enabling trend analysis and anomaly detection.