electric-vehicle-detection-analysis

Detect electric motorcycles and e-bikes in restricted areas by analyzing video streams and images for illegal parking and driving events. The skill processes local input files or network URLs to return violation counts, risk levels, warnings, and suggestions.

E-bike violation counting tallies total electric vehicles plus illegal parking and driving events in restricted zones. The analysis assigns a violation risk level and generates actionable management warnings and safety suggestions based on the detected counts.

Yes, you can use this e-bike detection skill for batch compliance monitoring in residential communities and institutional facilities. It supports real-time video streams and static image analysis to monitor no-entry and no-parking zones.

Retrieve historical e-bike detection reports by triggering a cloud-based query workflow. The skill fetches prior detection report records and displays them as a Markdown table with clickable report links for reviewing past violation data.

Yes, you need a mandatory open-id validation and cloud API execution via scripts to run electric vehicle violation detection. The analysis requires local input files or network URLs to process the video streams and images.

The e-bike detection analysis works with both local input files and network URLs. It processes camera video streams and images to identify electric motorcycles and e-bikes in restricted areas for compliance monitoring.