AI-Powered Staff
Exclusion for Accurate
People Counting

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What Is Staff Exclusion in People Counting?

Staff exclusion in people counting removes employees from visitor data, ensuring analytics reflect genuine customer traffic. In retail stores, supermarkets, and showrooms, employees often move through entrances, aisles, checkout areas, and service zones. Without accurate employee exclusion, staff movements can be miscounted as customer traffic, skewing metrics like conversion rates, peak hours, dwell time, and store performance.

Milesight supports staff exclusion for AI-based people counting through multiple methods, including epaulet or chest badge recognition, staff lanyards, and UWB recognition. These options enable precise separation of staff and customer counts for better store performance insights.

Why Staff Exclusion Matters in People Counting?

Improving Customer
Footfall Data Accuracy

Employee movements often inflame visitor counts and skew metrics. Excluding staff activity yields accurate customer traffic data, enabling precise conversion rates, dwell times, and peak hours analysis. Cleaner data informs better merchandising, layout, campaigns, and engagement decisions.

Enhancing Customer Experience with Real-Time Staff Visibility

Real-time staff identification helps managers understand where employees are positioned across the store. When customer traffic rises in entrances, checkout areas, or high-value zones, managers can quickly reassign employees to provide assistance, reduce waiting time, and improve service coverage.

Optimizing Staff Scheduling
and Store ROI

Employee identification provides a more reliable foundation for workforce planning. Managers can align staff shifts with actual visitor traffic, avoid overstaffing or understaffing, and evaluate staff productivity more fairly. This supports better labor cost control and more accurate ROI analysis.

Staff Exclusion Implementation Methods

Milesight offers multiple staff exclusion methods, including badges, lanyards, and UWB, to suit various store
environments, uniforms, and management needs, ensuring optimal accuracy and aesthetics.

UWB-Based Staff Exclusion

UWB-based staff exclusion utilizes Ultra Wide Band technology for precise employee positioning. It comprises anchors, staff tags, and charging bases. Anchors receive signals from staff-worn tags, which transmit location data for accurate identification. UWB provides precise staff identification via wireless signals, ideal for stores require both accuracy and a clutter-free look.

Milesight UWB staff exclusion achieves up to 99% accuracy and enables staff trajectory analysis when used with the Milesight VS series devices.

va05

Compatible Hardware:

Compatible with VS125-LW and VS125 models with the required hardware and firmware versions.

Best-Fit Scenarios:

UWB-based employee exclusion is ideal for high-end retail, combining accuracy with aesthetics. Its compact, lightweight, and discreet design easily integrates into staff routines, allowing employees to carry it unobtrusively without visible badges or lanyards.

For retailers that require more than basic traffic correction, UWB enables advanced operational insight. It supports staff trajectory analysis, real-time employee positioning, and resource optimization, helping managers understand staff distribution and improve workforce management. UWB is ideal for premium stores, flagship locations, and retail chains seeking precise people counting, cleaner conversion analysis, and smarter staffing.

Staff Badge and Epaulet Recognition

Staff badge and epaulet recognition uses a specially designed visual pattern that can be recognized by compatible people counting sensors. When employees wear the badge on the shoulder or chest, the sensor identifies them as staff members and excludes their movements from customer traffic data. The VA04 Multifunctional Staff Badge supports shoulder (epaulet mode) and chest (badge mode) wear, ensuring simple, anonymous, and privacy-friendly staff exclusion.

staff exclusion in people counting va04

Compatible Hardware:

  • Compatible with the VS125 Series people counting sensors
  • Supports staff epaulet and badge scenarios

Key Requirements:

  • People counter firmware: V1.0.4 and later
  • Recommended installation height: 2.2m–4m
  • Optimal installation height for above-chest wearing: 2.2m–3.5m
  • Badge should be worn consistently on the shoulder or chest
  • Badge should remain clearly visible and not be covered by collars, scarves, hair, or other items
  • Staff clothing should avoid patterns similar to the VA04 badge

Best-Fit Scenarios:

Badge and epaulet recognition suits retail stores seeking a simple, cost-effective method to exclude staff from people counting data, especially when uniforms display visible badges or shoulder identifiers.

Staff Lanyard Recognition

When staff members wear a special lanyard around the neck, compatible people counting sensors can identify them as employees and exclude their movements from visitor counts.

Compatible Hardware:

  • VA21 Staff Lanyard for VS125 Series
  • VA31 Staff Lanyard for VS13x Series

*VA31 supports VS133 and VS135 models with compatible firmware

staff exclusion in people counting va21 va31

Key Requirements:

  • VA21 firmware requirement: V1.0.2 and later
  • VA21 recommended installation height: 2.2m–4m
  • VA31 firmware requirement: VS133 V1.0.2 and later; VS135 V1.0.5-r2 and later
  • Lanyard should be worn around the neck and kept clearly visible
  • Lanyard should not be covered by collars, scarves, hair, or other items
  • For VA31, staff uniforms should not contain reflective materials

Best-Fit Scenarios:

Lanyard recognition suits stores where employees wear name badges or ID cards, offering a familiar method that boosts traffic data accuracy with minimal workflow disruption.

Methodsstaff exclusion in people counting vs125

VS125/LW

AI Stereo Vision People Counter

staff exclusion in people counting vs126

VS126

AI Ultra High-Mount
People Counter

staff exclusion in people counting vs125 outdoor

VS125-O

AI Stereo Vision People Counter

staff exclusion in people counting vs133

VS133

AI ToF People
Counting Sensor

staff exclusion in people counting vs135

VS135

AI ToF People
Counting Sensor

staff exclusion in people counting vs121

VS121

AI Workplace Occupancy Sensor

Epaulet
Chest Badge
Lanyard
UWB
= Supported,
= Not Supported,
= Planned or Feasible

*Epaulet and chest badge recognition use the same device; the difference lies in the wearing position, not the hardware itself.

What Makes Milesight Staff
Exclusion Stand Out

High-Accuracy Staff Identification

Milesight staff identification uses AI visual recognition and UWB positioning for accurate employee recognition across retail environments. Visual identification methods utilize standardized markers such as epaulets, badges, and lanyards to facilitate sensor recognition, while UWB tags provide wireless positioning signals to enhance accuracy in distinguishing individual employees. This multi-method approach minimizes errors from occlusion, clothing, lighting, or movement variability.

Anonymous Staff Identification

Milesight identifies employees without collecting personal data. Staff members do not need to register personal IDs, facial information, or other personally identifiable data for employee recognition. It differentiates staff from visitors using dedicated methods, ensuring accurate counting while preserving privacy. It is ideal for retail environments where data privacy, customer trust, and operational simplicity are equally important.

Adaptable to Multiple Retail Scenarios

Milesight supports different detection scenarios, including line-crossing people counting and area-based detection. Whether a retailer needs to exclude staff from entrance traffic, sales area analytics, or zone-based occupancy insights, it ensures accuracy across different store layouts. So it is well-suited for a wide range of retail environments, including retail stores, supermarkets, shopping malls, showrooms, flagship stores, and chain locations.

Flexible Deployment and Seamless Integration

Milesight Staff Exclusion easily integrates with compatible people counting devices, simplifying setups for new and existing installations. Retailers can enable staff identification via accessories or upgrades without replacing sensors. Supporting protocols like MQTT, HTTP, and Modbus, Milesight devices transmit exclusion data to third-party systems, enabling scalable, reliable traffic analytics across single stores and multiple locations.

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FAQs

Q: How to choose the right staff exclusion method for different store scenarios?

  • Choose staff exclusion methods based on accuracy, store image, workflow, and cost.
  • High-end / flagship stores: Use UWB for precision, aesthetics, and advanced insights.
  • Standard stores / supermarkets: Use lanyard or epaulet recognition for a balance of cost, ease of deployment, and stable identification. It works well when uniforms and wearing rules are standardized.
  • Small or cost-sensitive stores: Choose badge or lanyard recognition. They are easy to deploy but depend on proper wear.
  • Staff-only entrances: Use exclusion lines or button-triggered zones as a low-cost option, but they depend on fixed staff routes.
  • Distinctive uniforms: Use uniform recognition or Re-ID to reduce wearables, but it may be less reliable if customers wear similar clothing.

Q: Besides staff exclusion, how does Milesight ensure accurate people counting?

Beyond staff exclusion, Milesight improves AI-based people counting accuracy through multiple layers of technology and deployment design:

  • Advanced sensing technologies: Milesight people counters use technologies such as binocular stereo vision, ToF, AI, and PIR to detect human movement accurately across different environments.
  • Rich people counting functions: Features such as bi-directional people counting, regional people counting, dwell time detection, and heat maps help retailers capture both visitor volume and in-store behavior insights.
  • Visitor demographic insights: Beyond staff identification, Milesight supports people attribute analytics such as adults/children differentiation, gender recognition, and group counting, helping retailers better understand visitor composition while safeguarding privacy.
  • Flexible installation options: Multiple mounting methods and installation heights help sensors adapt to entrances, aisles, checkout areas, and large open spaces, reducing blind spots and coverage errors.
  • Reliable platform integration: Milesight devices support data integration with third-party platforms, enabling retailers to use accurate traffic insights for conversion analysis, staffing, and operational optimization.

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