Unified data platform
scattered truck data → one governed golden sourceFour sources flow through a Bronze → Silver → Gold medallion into curated entities. Surfaces marked “To confirm” are the open questions we close with you in the workshop.
Sources
Truck & context data feeds (toggle a card to mute its contribution)
Medallion pipeline
Raw → cleaned/time-synced → curated entities
Data quality
Trip-level checks
Data acquisition · CTP
Transmitting vibration over the Connected Truck Platform
Full-fidelity µs vibration streamed to the cloud. Maximum signal — nothing thrown away before analysis.
Trade-off: May exceed CTP payload / bandwidth limits.
Illustrative: 4 vibration channels × 3 axes × 1 kHz × 2 bytes/sample × 24 h.
Time synchronisation
Aligning two streams onto one trip timeline (Silver layer)
Every telematics tick anchors a window of thousands of NVH samples. The real NVH rate is to confirm — it sizes the Bronze volume and the sync strategy.
Sensor placement
Where each candidate signal would physically sit on the Actros — the sprung/unsprung question, made visual
Marker 1 (cab) and marker 3 (axle/wheel) are the two ends of the sprung-vs-unsprung question — see the Sensor inventory footnote below for why that placement choice matters more than any other spec on this page.
Sensor inventory
Candidate road-quality signals on the Actros — spec confirmed in the workshop
| Signal | Sensor / make | Axis | Sampling rate | Mount | Mount type | Range / unit | Status |
|---|---|---|---|---|---|---|---|
| Longitudinal-G (TCM-G) | Torque Control Module · G-sensor | X (long.) | To confirm | Cab | Sprung | ± g · to confirm | To confirm |
| Vibration (NVH) | Tri-axial accelerometer · Siemens | X / Y / Z | µs-level · to confirm | Chassis or axle — location TBC | To confirm | g · to confirm | To confirm |
| Vertical acceleration (Z) — axle candidate | Tri-axial accelerometer (proposed) | Z (vert.) | ≥100 Hz · to confirm | Axle / wheel hub | Unsprung | ± g · to confirm | Proposed |
| Axle displacement | Suspension displacement sensor | Z (vert.) | To confirm | Per axle | Unsprung | mm | To confirm |
| Wheel speed | ABS / ESP wheel-speed sensor | — | ~1 Hz (CTP) | Per wheel | — | km/h | Confirmed |
| Vehicle speed · RPM | Powertrain telematics | — | ~1 Hz (CTP) | ECU | — | km/h · rpm | Confirmed |
| GPS position | Telematics GNSS | lat / lng | ~1 Hz (CTP) | Telematics unit | — | degrees | Confirmed |
| OxTS GNSS/INS (VOLTS) | OxTS unit — AccelX/Y/Z, IsoIsVerticalAcceleration (ISO 8855) | X / Y / Z + vertical (derived) | ~10 Hz · sporadic in catalogue | Vehicle body (test rig) — exact location TBC | Sprung | g · scaling to confirm | To confirm |
Sprung vs. unsprung is the biggest open architecture question here: a sprung-mass sensor (cab/chassis, e.g. today's longitudinal-G TCM-G) only sees vibration after the suspension has filtered it; an unsprung-mass sensor (axle/wheel hub) sees the road directly. Confirm which mount points actually exist on the Actros before committing to a signal.
Ground truth & validation
How we know a grade is correct — the open item this workshop must close
Illustrative — computed once real repeat-pass data exists (see Segment.passCount / rqiStdDev).
No finalised labelled dataset yet. Validation depends on BSCB expert review plus a ground-truth deep-dive — this section is exactly the open item that review is meant to close.
Predict part wear from the vibration you’re already collecting
The same axle vibration that grades the road also stresses the truck. One signal, read twice — how rough the road is, and which parts it’s wearing out.
predicts
Warranty reads the vibration the road doesn’t explain. Residual = measured axle vibration − what RQM's road model predicts for this road & speed. Above its own road-normalised baseline, that residual is a signal about the truck, not the road.
Component breakdown
Each component, the vibration feature that wears it, and its predicted health
Warranty ontology extension
How the warranty domain hangs off RQM's Gold layer — the RQM output is the bridge
What we still need
What warranty needs beyond the RQM sensor data — the open items for this use case
Which part failed, on which VIN, at what mileage — the warranty ground truth. A new data source (Daimler's claims system), not sensor data.
Maps a vibration channel to a specific physical component instance and its install date — asset data not in VOLTS or CTP today.
Bearing-fault frequencies can sit above the rate spec'd for road roughness — same axle mount, possibly a higher rate.
A cumulative per-vehicle wear signal rolled up over the truck's life — a different feature-store pattern to RQM's per-trip view.