Corporate & university campuses
Quiet safety across every building.
For campus environments, GaitAI can layer CampusShield movement-event monitoring, AccessMotion entry-consistency signals at sensitive doors, and SuspiciousMotion anomaly detection across shared spaces.
The operational problem
Campuses need quiet, privacy-aware safety monitoring across many sites.
Why current workflows fall short
Campuses span many buildings and after-hours situations that security staff cannot continuously supervise, and identity-first monitoring is unacceptable in work and study spaces.
Recommended GaitAI product mix
Quiet, intelligent safety for the spaces people work and learn.
Surfaces movement-safety events across office parks, universities, hospitals and corporate campuses for operator review.
A passive second factor — your walk.
Contributes a passive gait-consistency signal alongside card, face or mobile authentication in high-security spaces. It supports an existing credential rather than replacing it.
Anomalies surfaced — without identity matching as a prerequisite.
Surfaces candidate movement events — loitering, running, restricted-zone entry, tailgating-like patterns and perimeter events — for operator review, without requiring identity recognition.
Example workflow
- 01Buildings, zones and schedules configured
- 02Movement events surface on the campus timeline
- 03After-hours and fall events alert the security desk
- 04Controlled doors add consistency signals
- 05Incidents escalate through campus procedures
Expected operational outputs
Workplace/campus safety, after-hours movement alerts, tailgating indicators and access consistency.
Privacy & responsible use
Designed to support consent-based capture, encrypted transfer, configurable retention and role-based access, with activity logging and skeleton-only processing modes. Deployment requirements depend on the applicable environment, organization and jurisdiction. Privacy-aware architecture does not automatically mean anonymity: pose, gait and trajectories may still carry identifying information. Movement analytics are designed to run without identifying individuals unless a deployment lawfully and explicitly requires it, and identity-related capabilities are intended only for lawful, authorized deployments with appropriate governance, access control and auditability. Outputs are decision support for trained operators — not autonomous enforcement. Children and school workflows require guardian and institutional consent as applicable, limited retention, no automatic identity matching unless specifically authorized, and no automated educational decisions. Qualified people must review movement observations in context.