GaitAI CampusShield
Quiet, intelligent safety for the spaces people work and learn.
CampusShield combines movement-event monitoring across campus spaces — visitor movement timelines, after-hours alerts, fall detection, restricted-zone monitoring and tailgating indicators.
Problem
Large campuses contain many buildings, movement zones and after-hours situations that cannot be continuously supervised manually.
What GaitAI does
A campus-wide movement-event layer: zone rules per building, after-hours profiles, fall detection in low-traffic areas and entry-pairing indicators at controlled doors.
Who uses it
- Universities
- Corporate campuses
- Hospitals
- Research campuses
- IT parks
What they receive
Example report values — illustrative, not measured performance claims.
Events are review prompts for campus security. A quiet timeline is the normal state; deviations — an after-hours movement, a fall-like event — are what the team actually needs to see.
Why it matters
Campus security teams get a quiet, privacy-aware safety layer across dozens of buildings — surfacing the handful of events that need attention instead of walls of screens.
Example workflow
- 01Campus cameras feed the movement pipeline
- 02Zone and schedule profiles define normal movement
- 03Events (after-hours, falls, zone entries) are flagged
- 04Security reviews the campus timeline
- 05Incidents escalate through existing procedures
Deployment
- Building- and zone-level configuration
- After-hours schedule profiles
- Campus-wide operator timeline
- AccessMotion adds entry-consistency signals at controlled doors
Research basis
Published work is the research foundation for the capabilities this product is built on. That record covers the movement-analysis methods themselves — it is not a validation of this product's outputs, and there is no clinical validation study, accuracy benchmark or trial result behind them.
- Privacy-aware analytics
- Privacy-preserving gait data
Evidence status
GaitAI Evidence Index
2 categories documented
What is documented for this module, and what is not. Research foundation is not product validation — the two are listed separately on purpose.
- Research foundationAvailable
- 1 published record directly addresses a capability this module is built on (Privacy-preserving gait data).
View evidence for Research foundation
Claim / capability: 1 published record directly addresses a capability this module is built on (Privacy-preserving gait data).
Status: Available
Applicability: The cited work is specifically about a method or movement signal this module draws on.
Limitation: Research relevance is not evidence that this product's outputs have been validated.
Inventory reviewed .
- Architectural research relationshipNot yet published
- No further shared-platform research relationship is recorded beyond the research foundation above.
View evidence for Architectural research relationship
Claim / capability: No further shared-platform research relationship is recorded beyond the research foundation above.
Status: Not yet published
Applicability: Shared capabilities such as pose estimation or temporal modelling are used by many modules.
Limitation: A shared-platform relationship is the weakest research link and must not be read as validating this module.
No supporting source is published for this status.
Inventory reviewed .
- Product specificationAvailable
- The module has a documented specification: inputs, pipeline, outputs and stated limitations.
View evidence for Product specification
Claim / capability: The module has a documented specification: inputs, pipeline, outputs and stated limitations.
Status: Available
Applicability: Documented inputs, intended workflow and output design.
Limitation: Documentation does not establish a released implementation or deployment readiness.
- specificationProduct documentation
Inventory reviewed .
- Product implementation evidenceNot yet published
- No module-specific release or deployment record is published here.
View evidence for Product implementation evidence
Claim / capability: No module-specific release or deployment record is published here.
Status: Not yet published
Applicability: Production implementation is distinct from this website's interactive prototypes.
Limitation: The browser pose explorer is not the full clinical or operational product pipeline.
- Context · not validation evidenceProduct and deployment context
Inventory reviewed .
- Interactive demoNot yet published
- No sample output has been built for this module yet.
View evidence for Interactive demo
Claim / capability: No sample output has been built for this module yet.
Status: Not yet published
Applicability: An interactive explanation of the intended output and workflow.
Limitation: Sample outputs contain illustrative values and are not measurements of a visitor or product performance.
No supporting source is published for this status.
Inventory reviewed .
- Benchmark validationNot yet published
- Validation pending publication. No product benchmark numbers are supplied.
View evidence for Benchmark validation
Claim / capability: Validation pending publication. No product benchmark numbers are supplied.
Status: Not yet published
Applicability: A benchmark needs a defined dataset, sample count, environment, hardware and evaluation method.
Limitation: Accuracy, sensitivity, specificity, latency and FPS cannot be inferred from a demonstration.
- Context · not validation evidenceResearch evidence inventory
Inventory reviewed .
- Product-specific validationNot yet published
- No study in the published record evaluates this module's output for a particular intended use.
View evidence for Product-specific validation
Claim / capability: No study in the published record evaluates this module's output for a particular intended use.
Status: Not yet published
Applicability: Validation must match the module, population and intended decision.
Limitation: A product description or related research paper does not establish validated performance.
- Context · not validation evidencePublished evidence inventory
Inventory reviewed .
- Pilot & deployment evidenceNot yet published
- No named pilot, deployment result or customer outcome is documented.
View evidence for Pilot & deployment evidence
Claim / capability: No named pilot, deployment result or customer outcome is documented.
Status: Not yet published
Applicability: Pilot and deployment evidence is assessed separately from research.
Limitation: Use-case journeys describe intended workflows, not customer results.
- Context · not validation evidenceTrust Center
Inventory reviewed .
- Product-specific clinical validationNot yet published
- No product-specific clinical validation study is published in this library.
View evidence for Product-specific clinical validation
Claim / capability: No product-specific clinical validation study is published in this library.
Status: Not yet published
Applicability: Clinical applicability depends on the intended use; safety modules are not presented as clinical tools.
Limitation: No output replaces clinician judgement or establishes a diagnosis.
- Context · not validation evidenceResponsible use and intended context
Inventory reviewed .
- Regulatory clearanceNot claimed
- No medical-device clearance, regulatory approval or compliance status is claimed.
View evidence for Regulatory clearance
Claim / capability: No medical-device clearance, regulatory approval or compliance status is claimed.
Status: Not claimed
Applicability: Regulatory applicability depends on the intended use and deployment jurisdiction.
Limitation: Research publications, patents and prototypes are not regulatory clearances.
- Context · not validation evidenceWhat GaitAI does not claim
Inventory reviewed .
Inventory reviewed How GaitAI states evidence →
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.
Context & limitations
- Monitors movement events, not identity or intent
- Coverage limited to camera-visible areas
- Escalation follows the campus's own procedures
Related SecureVision products
All products
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.
Movement intelligence — with task-relevant movement representations.
The architectural privacy layer for GaitAI: designed to support skeleton-only analytics, face blur, role-based access, configurable retention and audit logs in privacy-sensitive environments.