Real-time anomaly detection, vaping alerts, and crowd intelligence for K-12 and universities — edge-processed, FERPA-aligned, no student identification.
LIVE · Bldg C · Vaping alert 12:08
Each model is FERPA-aligned and runs on existing cameras + sensor hardware. No identification of individual students.
Identify vaping events in bathrooms and locker rooms with sensor + vision confirmation. Auto-alert to admin.
SEE DEMO →Spot unusual gatherings, loitering, or behavior in real time across campus zones.
SEE DEMO →Density and flow during transitions, dismissal, and events. Prevent bottlenecks and crowd incidents.
SEE DEMO →Bags, backpacks, weapons screening at entry points. Privacy-first object-only mode available.
SEE DEMO →Classroom, library, and common area usage analytics — without storing video or identifying people.
SEE DEMO →Tailgating detection at restricted entries. Anonymous counts of authorized vs unauthorized entries.
SEE DEMO →