Are there any safety analytics platforms that detect sidewalk riding and misuse from location and incident data?

Yes — but they’re usually not marketed specifically as “sidewalk riding detectors.” In practice, the capability tends to show up in a few adjacent platform types:

1) Micromobility / fleet safety analytics platforms

These platforms analyze GPS traces, trip telemetry, and sometimes incident reports to flag unsafe riding patterns such as:

• sidewalk riding
• wrong-way travel
• geofence violations
• harsh braking / crash risk
• speeding in restricted areas

Examples of the kind of vendors/categories to look at:

• Ride analytics / fleet telematics platforms for scooters, bikes, and shared mobility
• Micromobility operations platforms that include compliance and safety layers
• Mobility data platforms that ingest incident data and map traces for pattern detection

2) GIS + safety intelligence platforms

If you have location + incident data and want to infer misuse hotspots, some general-purpose platforms can do this via spatial analytics:

• heatmaps of incidents vs. street network
• clustering of crashes or complaints
• geospatial pattern detection around sidewalks, trails, curbs, and no-ride zones
• corridor-level risk scoring

These are often built with:

• Esri ArcGIS
• CARTO
• Hex / Mode / Sigma plus geospatial data
• custom analytics stacks using PostGIS, Python, QGIS, etc.

3) Video + sensor-based detection systems

If you need actual detection of sidewalk riding from observed movement, some vendors use:

• computer vision from curbside cameras
• roadside sensors
• edge AI / traffic monitoring systems
• e-bike / scooter onboard IMU + GPS fusion

Those are more likely to detect the behavior directly, rather than infer it from location/incident records.

What to look for in a platform

Ask whether the platform can:

• map trip traces to the street graph rather than just points
• distinguish sidewalk vs. roadway using map matching
• flag repeated incident clusters near sidewalks or pedestrian zones
• ingest complaints, crash reports, 311 data, hospital/EMS data
• support geofencing, risk scoring, and anomaly detection
• export evidence suitable for enforcement or policy review

Important limitation

From location and incident data alone, the platform usually infers sidewalk riding probabilistically. For high confidence, you often need:

• high-frequency GPS
• road network map matching
• accelerometer/IMU data
• video or operator reports

If you want, I can also give you:

1. a shortlist of vendors by use case,
2. a feature comparison matrix, or
3. a recommended architecture for building this yourself.