Communication gaps
A scenario for identifying a break in the incoming stream and escalating a longer communication gap.
Automotive · Proof of concept
Machine data.
Dashboards and alerts.
An automotive proof of concept explored telemetry ingestion, dashboards and alert scenarios using a simulated stream of machine data.
Project evidence
Three defined alert scenarios.
- Scenarios: communication, force and speed
- 3
- Communication-gap alert threshold
- 1 minute
- Critical communication-gap threshold
- 5 minutes
These figures describe the PoC scenario definitions in the demonstration deck. They are defined detection thresholds, not measured notification delivery times or production performance results.
The use case
Connect telemetry to an operational view.
Machine data can be spread across equipment interfaces, databases and local files. Monitoring requires a way to collect those signals, put them into context and present useful views to operational teams.
The proof of concept used sample machine data to simulate a stream. Data was collected through Azure IoT Hub, stored in InfluxDB and visualized through Grafana dashboards.
PoC architecture
From a simulated stream to dashboards.
- 01Sample machine data
A simulated stream for the demonstration.
- 02Azure IoT Hub
Collection of the simulated telemetry.
- 03InfluxDB
Storage of time-series readings.
- 04Grafana & alerts
Dashboard views and scenario-based notifications.
Scenarios explored
Define what should trigger attention.
Force patterns
Scenarios for sudden deviations and gradual changes in force readings during test cycles.
Speed patterns
Scenarios for sudden or gradual changes in speed readings, with messaging channels for notification.
Delivery scope
What the proof of concept established.
The PoC connected a simulated machine-data stream to time-series storage and dashboard views. It provided a concrete environment for exploring the three defined monitoring scenarios and messaging alert channels.
The scope described here is a demonstration using simulated data. Production rollout and measured operational improvements require separate validation.
A production engagement starts with actual source connectivity, the signals available, the decisions operators need to make and the tests needed to validate dashboards and alerts.
Connect your operational data.
Discuss your machine interfaces, existing systems and the reporting or alerting workflows your team needs.