Turn Existing Cameras into Actionable Retail and Workforce Intelligence

• Discover compatible ONVIF cameras automatically on the local network.
• Add newly discovered cameras without creating duplicate records during repeated scans.
• Register RTSP, HTTP, local USB camera, and recorded-video sources.
• Edit camera names, stream URLs, credentials, operational roles, and enabled status.
• Assign cameras as General Tracking, Entrance, Exit, Counter, or Protected Area.
• Protect camera passwords using Windows machine-level encryption.
• Preview live video, test connectivity, display configured zone overlays, and save manual snapshots.
• Use common vendor RTSP paths automatically when an ONVIF-discovered stream path is incomplete.
• Monitor camera state, uptime, frames per second, reconnects, dropped frames, inference latency, and last detection.

• Detect and track people anonymously.
• Count entry and exit line crossings.
• Calculate current, average, and peak occupancy.
• Measure hourly and daily visitor traffic.
• Identify peak operating periods.
• Compare traffic with the preceding equivalent period.
• Monitor site-capacity limits and occupancy breaches.
• Prevent overlapping cameras or zones from inflating site-wide occupancy totals.
• Analyse activity by camera, zone, hour, day, or branch.

• Draw analytics zones directly over a camera view.
• Configure Occupancy, Queue, Dwell, Line Crossing, Protected, Counter, Drawer, Pantry, Employee Dwell, Customer Waiting, and Service zones.
• Use normalized zone coordinates that remain valid when camera resolution changes.
• Monitor queue length, peak queue size, threshold breaches, and queue-service performance.
• Measure average and maximum dwell time.
• Track zone utilization and transitions between operational areas.
• Group overlapping zones and assign ownership priority for accurate counting.
• Reload zone definitions without restarting the analytics service.

• Build activity heatmaps from real zone occupancy and dwell events.
• Visualize movement journeys from actual zone-transition data.
• Identify busy, underused, and high-dwell areas.
• Understand how visitors move between entrances, displays, counters, service areas, and exits.
• Use historical movement patterns to support layout, staffing, and service decisions.

• Register employees with code, name, department, phone, and email.
• Capture guided face images from front, left, right, up, and down angles.
• Use a built-in webcam, secondary USB camera, compatible phone webcam, IP camera, or existing image files.
• Store enrolment media locally under customer-controlled retention rules.
• Recognize enrolled employees across configured cameras when the required OpenVINO face models are installed.
• Search sightings by employee and view the last-seen camera, zone, time, snapshot, and event clip.
• Keep tracking-only cameras separate from official entrance and exit attendance cameras.

• Create attendance events from designated Entrance and Exit cameras.
• Reduce duplicate punches and door-bounce events.
• Pair IN and OUT records into draft work sessions.
• Apply default or employee-specific shifts, grace periods, and break allowances.
• Identify late arrivals, early departures, missing punches, duplicate events, and excessive breaks.
• Measure pantry and employee-zone break sessions.
• Allow managers to approve, reject, or adjust timesheet rows.
• Require a reason for adjustments and retain a complete audit record.
• Keep raw AI observations separate from payroll-approved records.

• Measure employee time spent in operational zones.
• Monitor counter coverage and unattended service areas.
• Measure customer waiting and employee response times.
• Classify customer-service outcomes as Served, SLA Breached, or Abandoned.
• Configure response thresholds based on each site’s service policy.
• Report employee-zone duration and customer-service performance.
• Support staffing and coaching decisions with time-based operational evidence.

• Monitor Protected, Counter, and Cash Drawer zones.
• Detect configured off-hours, unexpected dwell, motion, and protected-zone conditions.
• Correlate camera activity with POS events such as refunds, voids, drawer openings, no-sales, and transaction activity.
• Create risk-scored incidents from multiple contributing signals.
• Capture pre-event and post-event evidence clips when recording is enabled.
• Show the signals, camera, zone, employee or track reference, snapshot, and clip associated with an incident.
• Allow reviewers to mark incidents as New, Reviewed, Dismissed, or Escalated.
• Preserve review notes, reviewer identity, and review time.

Ixpert AI produces review candidates—it does not automatically accuse an employee or customer of wrongdoing. Final decisions remain with authorized human reviewers.

• Record enabled camera streams in configurable video segments.
• Retain pre-event and post-event footage for supported incidents.
• Save snapshots and clips with structured local storage.
• Configure independent retention periods for video, images, events, attendance, employee media, telemetry, logs, and audit records.
• Review storage usage by category.
• Run cleanup immediately or allow the Edge Service to apply retention automatically.

• Enable optional age-band and gender-estimate analytics for anonymous retail observations.
• Filter demographic reports by date, camera, and zone.
• View distribution summaries or detailed anonymous observations.
• Download detailed CSV reports and management-summary PDFs.
• Schedule demographic reports through Report Automation.
• Exclude names, face images, and biometric templates from demographic exports.

Age and gender outputs are estimates, not verified personal attributes. The OpenVINO age-gender-recognition-retail-0013 model is intended for approximately ages 18–75 and publishes an average age error of 6.99 years. Results should be used for aggregated planning, not individual decisions.