operations analytics

Entrance and exit analytics for every door that matters

In short

Entrance and exit analytics reports directional volumes at each doorway of a building or site. Ayonix people counting already counts entry and exit traffic and compares peak periods; applied across every entrance, it shows which doors carry the load, when, and how that changes through the week.

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Conceptual illustration of entrance and exit counting in a corporate lobby. AI-generated conceptual image, not a customer deployment.

In context

Entrance and exit analytics across different settings

The same directional counting, applied at different kinds of doorway. The figures shown are illustrative, not measured Ayonix results.

Workers in high-visibility vests passing through factory entrance turnstiles, with directional in and out counts and an on-site tally overlaid on the doorway — Conceptual illustration of directional entrance and exit counting at a manufacturing site. AI-generated conceptual image, not a customer deployment.

Office workers passing through corporate lobby speed gates, with entries, exits and occupancy counts overlaid on the entrance — Conceptual illustration of entrance and exit counting in a corporate lobby. AI-generated conceptual image, not a customer deployment.

Staff, visitors and a patient in a wheelchair moving through a hospital main entrance, with entries, exits and occupancy counts overlaid on the doorway — Conceptual illustration of entrance and exit counting at a hospital main entrance. AI-generated conceptual image, not a customer deployment.

Shoppers carrying bags entering and leaving a shopping mall entrance, with directional counts and a live occupancy figure overlaid — Conceptual illustration of entrance and exit counting at a retail mall entrance. AI-generated conceptual image, not a customer deployment.

Commuters passing through railway station ticket gates beneath platform signage, with entries, exits and occupancy counts overlaid — Conceptual illustration of entrance and exit counting at a transit station. AI-generated conceptual image, not a customer deployment.

Scope

What this analytic does, and what it does not

What it detects

Entry and exit counts per doorway per interval
Peak arrival and departure periods per entrance
Entrance share of total building traffic
Imbalance between entries and exits over a period

What it does not guarantee

A building occupancy figure without every bounding door being counted
Distinction between staff, visitors and contractors
Accurate counts through very wide doorways where people pass abreast
Any individual identification or access record

The problem

What customers are actually dealing with

These are the situations that lead teams to look at this analytic in the first place.

Reception is staffed for a peak that no longer happens, because arrival patterns changed and nobody measured it.
Cleaning and security rounds are scheduled against assumptions about when doors are busy.
A building has six entrances and no data showing which are genuinely used.
Access-control badge data covers only badge-controlled doors and misses visitor and public entrances entirely.

How it works

Detection workflow

Every event carries the rule that produced it, so an operator can see why they were alerted.

1

Ingest

Every bounding doorway camera is read and monitored for availability.
2

Count directionally

Each doorway produces entry and exit counts from directional line crossing.
3

Aggregate

Counts are accumulated per interval per doorway and rolled up per building.
4

Compare

Intervals are compared across days and weeks to establish arrival and departure patterns.
5

Publish

Per-door and per-building series are written to the dashboard and made available for export.

Entrance and exit analytics workflow diagram

Configuration options

Counting line per doorway with consistent entry and exit direction labelling
Grouping of doorways into buildings, zones or the whole site
Reporting intervals and the working-hours schedule
Exclusion of service and goods doors from headline figures where appropriate
Handling of revolving doors, airlocks and double-leaf entrances
Whether out-of-hours movement is reported as a separate series

Alert quality

How irrelevant and duplicate alerts are reduced

No video analytic eliminates false alerts. These are the mechanisms that reduce them, and the residual rate is measured on your own cameras.

Consistent direction labelling across every door is what makes building-level rollup meaningful.
Track-based counting ensures one person produces one count per crossing.
Separating service doors prevents deliveries from distorting the occupancy-relevant figures.
Reporting availability alongside counts makes gaps visible rather than silently lowering totals.
Group entry through wide doors remains the dominant error source and is quantified during the pilot.

Prerequisites

Camera requirements and environmental limits

Camera suitability decides more of the outcome than any software setting. These are assessed per camera before commitment.

Camera requirements

A counting-suitable view at every doorway included in the analysis
Overhead or steeply angled placement at each threshold
A field of view spanning the full door width, including both leaves of a double door
Consistent lighting at the threshold, including strong daylight through glazed entrances
Frame rate of 12–15 fps or higher at each counted door

Environmental limitations

Revolving doors and airlocks need careful line placement and specific acceptance testing.
A doorway that is not counted leaves a gap in every building-level figure derived from the set.
Wide entrances where groups pass abreast are the main source of under-counting.
Counts do not distinguish between people entering to work and people entering to visit.

Delivery

Alerts, evidence and where they land

Event and evidence fields

Doorway and building identifier
Interval start and end with timezone
Entries and exits in the interval
Net flow and cumulative net for the day
Camera availability percentage
Out-of-hours flag

VMS integration

Entrance analytics is a reporting series. Where a door also needs an out-of-hours crossing alert, the line crossing configuration provides that event to the VMS while the same line continues to produce counts.

See compatibility states →

Deployment options

Edge processing per building so only aggregate counts traverse the network
On-premise processing where all doorway cameras already aggregate to a site server
Multi-site deployment for consistent measurement across a property portfolio

Compare architectures →

Measurement

Dashboard metrics and pilot acceptance criteria

Acceptance thresholds are agreed with you before the pilot starts. This site publishes no benchmark figures, because they do not transfer between sites.

Dashboard metrics

Entries and exits per doorway per interval
Building totals and entrance share
Arrival and departure peak times per building
Weekday versus weekend pattern
Out-of-hours movement per door
Counting availability per doorway

Measurable pilot criteria

Counting error per doorway against a manual count at peak and off-peak
Direction accuracy per doorway, measured separately
Specific acceptance test for any revolving door or airlock in scope
Interval completeness across a full working week
Consistency of building rollup against the sum of its doors

Governance

Privacy and governance

Output is aggregate counts per doorway. No identity, badge record or face template is involved.
Where counts cover staff entrances, employee monitoring obligations and consultation duties may apply.
Aggregate series can be retained without retaining any imagery.

Frequently asked questions

Is this the same as people counting?

It uses the same directional counting mechanism, applied across every doorway of a building and rolled up. The distinction is one of scope and reporting: people counting typically answers a footfall question at one entrance, while entrance and exit analytics describes the whole building.

Can we use badge data instead?

Badge data covers badge-controlled doors and badge-holders. It misses visitors, public entrances and tailgating. The two are complementary — badge data is authoritative for access, camera counting is more complete for movement.

What about revolving doors?

They are workable but need careful line placement and their own acceptance test, because the geometry and the way people enter differ from a standard doorway. They are always tested individually rather than assumed to behave like other doors.

Keep reading

A controlled pilot establishes what this analytic actually does in your environment, against acceptance criteria we agree before it starts. Send a sample video first if you would rather see an assessment before committing to a pilot.