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Fleet operators generate massive volumes of GPS traces, shipment records, and sensor data every day. With Wherobots, you can snap GPS traces to road networks, model drive-time service areas, and detect roads and sidewalks from imagery.

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Examples

GPS Map Matching

Snap raw GPS points to road network segments to reconstruct the paths vehicles traveled.

Drive-Time Service Areas

Generate drive-time isochrones around hubs and delivery zones to see which locations each one can reach.

Fleet-Scale Map Matching

Aggregate vehicle GPS points into trips and map-match them across a fleet history.

Infrastructure Detection

Detect sidewalks and crosswalks from aerial imagery using RasterFlow computer vision models.

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Key Capabilities

Use map matching to snap GPS trajectories to road networks. Process entire fleet histories in batch or schedule recurring jobs.

Map matching on road networks

Snap trajectories to road segments.

Matching vehicle GPS data at scale

Run map matching across an entire fleet history.
Generate isochrones from distribution centers, hubs, or customer locations to model service areas, optimize delivery windows, and plan network coverage.

Making drive time isochrones

Model service areas by travel time rather than radius.
Apply RasterFlow models to detect roads and sidewalks from aerial imagery to find underserved areas or infrastructure gaps.

Detecting roads with RasterFlow

Find roads in areas where basemaps are thin.

Detecting sidewalks with RasterFlow

Map pedestrian infrastructure from aerial imagery.
Identify anomalous GPS points, unusual route deviations, or fleet behavior outliers using Local Outlier Factor analysis on geospatial data.

Local Outlier Factor

Surface spatial outliers that summary statistics hide.

Get started with Wherobots

Try Wherobots with your own geospatial data in minutes.