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Nabrio

Anonymous visitor demographics and sentiment

Nara estimates the age, gender and facial expression of visitors as anonymous statistics by zone and time. Mall operators, retailers and event organisers use them to plan tenant mix, campaigns and events, with all processing on-site.

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The same camera view before detection
camera · raw
Two people in an office with their faces detected by Nara. Move the lens to compare the raw camera view with what Nara detects.

[ 01 ]The problem

Operators know how many people visit, but not who they are, which makes tenant, marketing and event planning guesswork.

  1. 01inputCameras at entrances and key zones
  2. 02processAnonymous age and gender estimates and facial expression
  3. 03actionVisitor profiles and mood trends by zone and time, on dashboards

How it works

Nara detects faces and estimates age and gender, and classifies facial expression (happy, sad, angry, surprised and so on). The results are kept as anonymous statistics per zone and time, shown on dashboards and shared with other systems over MQTT.

Works with Nara’s built-in models. You set up the zones, rules and outputs.

What you need

  • Cameras with a view of visitors’ faces at entrances or zones
  • A PC, server or NVIDIA Jetson running Nara

Nara building blocks

What it improves

  • Tenant mix decisions
  • Campaign and event planning
  • Audience profiles for sponsors

FAQ

Questions, answered.

Are visitors identified?

No. Age, gender and expression are anonymous estimates used as statistics, and all processing happens on-site. Face recognition is used only for watch-lists that the operator defines.

Talk to us about visitor demographics.

Tell us about your site, cameras and machines, and we’ll show you how it runs on your own hardware, or download Nara and try it yourself.