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Smart Buildings / Retail / Occupancy Sensing

mmWave People-Counting Sensor: Privacy-Preserving Radar Occupancy Detection with Edge Processing

For a Dubai smart-building and retail client we built a camera-free mmWave radar sensor that counts people and detects presence, with edge AI filtering. Completed by early 2025; >95% counting accuracy is the design target.

What we did: We integrated mmWave radar sensing, developed on-device (edge) AI filtering that separates people from static objects and moving clutter, designed the low-power, always-on RTOS system, added BLE, Wi-Fi, LTE or LoRa connectivity, and built a real-time occupancy dashboard with integrations for building-automation platforms.

Smart-building and retail client, Dubai, UAE4 monthsTeam of 4

Published Last reviewed:

>95%
People-counting accuracy
Design target
No camera
Privacy-preserving radar sensing
Edge
Detection runs on the device
4 months
Project duration
Illustrative photo: a ceiling-mounted radar sensor above a store entranceIllustrative image

The Challenge

Common people-counting and presence sensors fall short: passive infrared (PIR) and ultrasonic sensors struggle in crowds and with people who stand still, and cameras raise privacy concerns and depend on light. The client wanted an accurate, real-time, privacy-preserving sensor using mmWave radar that detects presence, counts people and works in low visibility.

Accuracy in crowds

PIR and ultrasonic sensors miscount when several people move together or someone stays still.

Impact: Accurate counting

Privacy

Cameras in shops and offices capture identifiable images, which many sites want to avoid.

Impact: No camera images

Light and obstructions

Optical sensors depend on lighting and are confused by shadows and obstructions.

Impact: Works in low visibility

False triggers

Pets, HVAC airflow and moving objects can trigger simple motion sensors.

Impact: Clutter filtering

Our Solution

mmWave radar sends out millimetre-wave radio signals and measures the reflections, so it senses people's movement and position without forming an image and without needing light. We added AI-based filtering on the device to tell people apart from static objects and moving clutter, and ran all detection at the edge in a low-power, always-on design, so no cloud processing is needed. Occupancy data goes out over BLE, Wi-Fi, LTE or LoRa to a real-time dashboard and to building-automation platforms.

System Architecture

Radar sensing and edge AI on the device; occupancy data to the building.

Sensing

  • mmWave radar sensor
  • High-resolution, non-intrusive people detection
  • Works in darkness and low visibility

Edge processing

  • AI-based filtering: people vs static objects and moving clutter
  • Filtering designed to reject pets, HVAC airflow and objects
  • Low-power, always-on RTOS firmware

Connectivity and analytics

  • BLE, Wi-Fi, LTE or LoRa connectivity
  • Real-time occupancy dashboard
  • Integration with smart-building and home-automation platforms

Key Design Points

SensormmWave radar
ProcessingOn-device (edge), no cloud needed
FilteringAI-based clutter rejection
ConnectivityBLE / Wi-Fi / LTE / LoRa
PrivacyNo camera, no images
Counting accuracy>95% (design target)

What We Delivered

  • mmWave radar integration
  • Edge AI filtering for people vs clutter
  • Low-power, always-on presence detection
  • Multi-radio connectivity: BLE, Wi-Fi, LTE, LoRa
  • Real-time occupancy dashboard
  • Building-automation integration for occupancy-based lighting and HVAC control

Outcome

We delivered a low-power, always-on radar sensor that counts people and detects presence in real time without cameras, with filtering designed to reject pets, HVAC airflow and moving objects. The >95% counting accuracy is a design target. Occupancy data can drive occupancy-based lighting and HVAC control; we do not publish energy-saving figures.

How to read the labels: Design target = an engineering target, not a field measurement.

People-counting accuracy

Design target

>95%

Including dynamic environments

Privacy

No camera

Radar sensing only; no images captured

Building integration

Lighting + HVAC

Occupancy data for smart-building and home-automation platforms

Design duration

4 months

Team of 4

Technologies Used

mmWave radarEdge AIRTOSBLEWi-FiLTELoRaOccupancy analyticsBuilding automation

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