Sensor Math & Specifications

A deep technical review of the accelerometer calibration matrices, Butterworth filtering, and dynamic road shock calculations.

Isolating Road Wear from Cabin Noise

How our software isolates vehicle suspension movements from engine noise.

The raw accelerometer reads gravitational forces across three dimensions ($a_x$, $a_y$, $a_z$). To isolate true pavement anomalies, we first remove the baseline Earth gravity vector ($1.0g$) using a continuous low-pass gravity filter:

g_vector(t) = α · g_vector(t-1) + (1 - α) · a_raw(t)
a_isolated(t) = a_raw(t) - g_vector(t)

Where $\alpha = 0.98$ acts as the low-pass smoothing factor. Pothole spikes are identified when the isolated vertical magnitude exceeds a dynamic threshold $T_{puka}$ calculated using running statistics:

T_puka = μ_accel + k · σ_accel

Sensor Cradle Rigid Mounts

Because smartphones vary in vehicle placement, rigid cradle installations are critical. Loose dashboard mounts introduce cabin rattling which mimics high-g pothole shocks.

  • Mounting Preference: Solid glass suction cradle or bolted dashboard brackets.
  • Excluded Setups: Phone placed loosely in cup holders, passenger seats, or coat pockets.
  • Device Calibration: Run an initial 30-second flat drive calibration to determine the vehicle suspension variance vector.
API Note: Calibration matrices are normalized relative to vehicle weight and suspension classes (Sedan vs SUV) before IPFS uploads.