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AI detection · Occupancy & peak hour trends

Occupancy & peak hour trends

Know when it's busiest, plan around it. Occupancy and peak hour trends identifies the busiest hours and zones automatically from live camera counts, so staffing and planning decisions aren't guesswork.

  • Live occupancy counts per camera, zone, or site
  • Historical peak-hour and peak-day trends over time
  • Zone-by-zone comparison across a single site
Dashboard chart showing occupancy counts across a day with a highlighted peak-hour window
Occupancy & peak hour trends

This capability tracks:

  • • Live occupancy counts per camera, zone, or site
  • • Historical peak-hour and peak-day trends over time
  • • Zone-by-zone comparison across a single site
  • • Trend data exportable for staffing and space-planning decisions
  • • Portfolio-level comparison across a multi-site account

Why occupancy and peak hour trends matter

Staffing, cleaning schedules, and restocking windows are usually set based on rough assumptions, "lunch is busy," "weekends are slower", rather than actual measured data. Those assumptions drift over time as customer behavior changes, and nobody notices until a location is visibly understaffed during a rush or overstaffed during a lull.

Dedicated people-counting sensors can answer this, but they mean new hardware, new installation, and another system to maintain, often not worth it just to answer a scheduling question.

Occupancy and peak hour trends answers it using cameras that are already in place, turning live subject counts into a continuous, accurate picture of when and where a site is actually busiest.

Diagram showing live subject counts from multiple cameras aggregating into a site-wide occupancy trend
Occupancy aggregation

How it works

Aggregating live counts

Confirmed subject counts from multi-object tracking are aggregated continuously per camera or defined zone, building a live occupancy figure that updates in real time.

Building the trend line

Live counts accumulate into a historical trend broken down by hour of day and day of week, surfacing peak windows automatically rather than requiring a manual count or a separate people-counting sensor.

Where the data feeds

Occupancy data feeds the platform's analytics and reporting module alongside heatmap anomalies for a fuller picture of site activity.

Configuration

Zones are marked on the camera view or site map for per-area occupancy tracking. Each account supports:

  • • Zone boundaries for per-area occupancy tracking
  • • Reporting windows and comparison periods
  • • Notification window per camera: notifications only in the hours you set
  • • Per-camera instance licensing
Configuration panel showing occupancy tracking zones marked across a site floor plan
Occupancy zone setup
Dashboard comparing occupancy trends across multiple zones and sites over a week
Peak hour comparison

Common scenarios

  • • A retail store scheduling staff around measured lunch and weekend peaks
  • • A restaurant identifying its true busiest hours ahead of adding evening shifts
  • • A bank branch planning teller coverage around actual foot traffic patterns
  • • A campus facility comparing occupancy across buildings for space planning
  • • A property manager tracking common-area usage trends across a portfolio

In a patrol round

Occupancy tracking runs as continuous background analytics rather than a per-camera checklist item during a virtual patrol round, but occupancy trends for a patrolled site are visible alongside that site's patrol reports.

FAQ

Frequently asked questions

Confirmed subject counts from multi-object tracking are aggregated per camera or zone continuously, giving a live occupancy figure and a historical trend rather than a one-time manual count.

Peak hour trends inform staffing schedules, cleaning and restocking windows, and space planning decisions, knowing exactly when a location is busiest removes the guesswork from those decisions.

No. It runs on the same connected cameras used for other detection features, with no dedicated people-counting sensors or turnstile hardware required.

The count is built from confirmed subject tracks, which holds up well in moderately busy areas. In very dense crowds, individual tracks can be harder to separate, so figures are best read as a reliable trend indicator rather than an exact headcount at extreme density.

Yes. Occupancy is tracked per camera or defined zone, so trends can be compared zone-by-zone within a site, or rolled up across a multi-site account for portfolio-level staffing and planning decisions.

Historical trends build up continuously from the point tracking is enabled, with retention configurable per account, enough history to establish reliable day-of-week and hour-of-day patterns for staffing and planning decisions.

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