Table of Contents
- Introduction
- What Is a People Counting Solution?
- Typical Use Cases
- Main People Counting Technologies
- Comparison Table: People Counting Technologies
- Reference System Architecture
- Accuracy Considerations
- Privacy and Compliance
- Deployment Checklist
- Integration and Reporting
- Choosing the Right People Counting Solution
- FAQ
- Conclusion
- Sources
A people counting system tracks how many people enter, leave, or stay in a space over time. It uses sensors, software, and reports to turn physical movement into clear data that helps with management and planning.
People counting is commonly used in retail, commercial buildings, transportation centers, public venues, and smart city initiatives. When applied properly, it helps organizations shift from assumptions to evidence-driven planning. Different technologies yield varied results, and accuracy, privacy, and deployment quality are just as important as the sensor itself.
This article offers a neutral, engineering-focused overview of people counting solutions, covering technology options, system architecture, accuracy considerations, privacy practices, and deployment guidance. We can do everything on the Rockchip platform anyway, including people counting smart devices. Keep reading!
Additionally, you can learn more about Rockchips products and solutions:
What Is a People Counting Solution?
At its core, a people counting solution answers one or more of the following questions:
- How many people entered or exited a defined point?
- How many people are currently in a space (occupancy)?
- How does foot traffic vary by time, location, or direction?
- How long do people typically stay in a zone or area?
The output is usually aggregated data rather than information about individuals. In professional deployments, raw sensor signals are converted into events (for example, “3 people entered between 10:00 and 10:01”) and then summarized into reports or dashboards.
A well-designed solution also includes monitoring, calibration, and validation mechanisms. Without these, even high-quality sensors can produce misleading data over time.
Typical Use Cases
People counting solutions are applied across many industries:
- Retail and shopping centers – Footfall trends, peak hours, staff allocation, and store layout optimization.
- Commercial buildings and workplaces – Occupancy monitoring, meeting room utilization, energy optimization, and safety compliance.
- Transportation systems – Passenger flow analysis in stations, terminals, and vehicles.
- Public venues and events – Real-time capacity monitoring, crowd management, and safety thresholds.
- Smart city infrastructure – Pedestrian flow analysis for urban planning and public space management.
In all cases, the value comes not just from counting people, but from understanding patterns over time.
Main People Counting Technologies
There is no single best technology. Each approach has strengths and limitations depending on the environment.
Infrared Beam (Break-Beam) Counters
Infrared beam counters place one or more beams across an entrance and register a count when the beam is interrupted.
Strengths
- Low cost
- Simple installation
- Minimal processing requirements
Limitations
- Poor performance at wide entrances
- Difficulty handling groups walking side by side
- Sensitive to carts, strollers, or unusual movement
These systems are best suited for narrow, controlled doorways where approximate counts are acceptable.
Thermal Sensors
Thermal people counting sensors detect heat signatures rather than visible imagery.
Strengths
- Works in low or variable lighting
- Reduced visual detail compared to cameras
Limitations
- Limited resolution
- Reduced accuracy in dense crowds
- Environmental temperature can affect performance
Thermal sensors are often chosen when visual privacy is a concern but moderate accuracy is sufficient.
2D Video Analytics
Standard cameras combined with analytics software can detect and track people in defined areas.
Strengths
- Flexible analytics
- Supports multiple zones and complex layouts
- Can be updated through software improvements
Limitations
- Sensitive to lighting changes and occlusion
- Requires careful camera placement
- Higher privacy and compliance requirements if video is stored
2D video solutions are powerful but require disciplined system design.
3D Depth and Time-of-Flight Sensors
Depth-based systems use stereo vision or time-of-flight technology to measure distance and shape from above.
Strengths
- Strong separation of individuals
- Reliable entry and exit counting
- Reduced occlusion issues with top-down views
Limitations
- Installation height constraints
- Performance can vary depending on surface reflectivity
These systems are widely used for accurate counting of doorways and corridors.
LiDAR-Based People Counting
LiDAR uses laser distance measurements to detect movement and trajectories.
Strengths
- Robust in challenging lighting
- Scales to large spaces
- Supports advanced flow and density analytics
Limitations
- Higher device cost
- Requires careful calibration and placement
LiDAR is often used in transportation hubs, large venues, and advanced smart city deployments.
Wi-Fi and Bluetooth Sensing (Estimation)
Wireless-based systems detect signals from mobile devices and infer presence.
Strengths
- Non-visual
- Can provide trend-level insights
Limitations
- Counts devices, not people
- Affected by device ownership and OS privacy features
- Unsuitable for precise occupancy or compliance use
These systems are best treated as supplementary indicators rather than primary counting tools.
Access Control and Turnstiles
Where access control systems exist, entry events can be logged directly.
Strengths
- High confidence in controlled environments
- Direct integration with existing systems
Limitations
- Does not capture uncontrolled movement
- Tailgating can distort counts
Access control data is useful but rarely sufficient on its own.
Comparison Table: People Counting Technologies
Reference System Architecture
A modern people counting solution typically consists of:
- Sensor layer – counting devices at entrances or zones
- Edge processing – local computation that converts signals into count events
- Communication layer – secure data transport with buffering and time synchronization
- Data layer – storage, aggregation, and retention management
- Application layer – dashboards, alerts, and integrations
Separating raw sensor data from business metrics improves reliability and long-term maintainability.
Accuracy Considerations
Accuracy is influenced by more than the sensor specification.
Key factors include:
- Sensor placement and angle
- Doorway width and traffic behavior
- Bidirectional movement and lingering
- Environmental changes over time
- Calibration and maintenance practices
Professional deployments regularly validate counts against short manual observations to detect drift.
Privacy and Compliance
People counting systems must be designed with privacy in mind, especially in public or workplace environments.
Best practices include:
- Data minimization
- Edge processing with aggregated outputs
- Limited data retention
- Clear transparency and signage
- Secure access controls and audit logs
A solution that outputs only anonymous counts is generally easier to govern than one that stores raw imagery or identifiers.
Deployment Checklist
Before deployment, ensure the following:
- Site survey completed
- Technology matched to environment
- Mounting height and angle documented
- Network and power planned
- Acceptance testing defined
- Monitoring and alerting configured
- Operational ownership assigned
Most counting errors originate from installation shortcuts rather than technology limitations.
Integration and Reporting
People counting data becomes more valuable when integrated with other systems:
- Building management systems
- Point-of-sale platforms
- Workforce scheduling tools
- Business intelligence platforms
Event-based data exports are generally preferred for engineering validation and long-term analytics.
Choosing the Right People Counting Solution
Start with the decision the data must support. Ask:
- What actions will this data drive?
- What level of accuracy is required?
- What privacy constraints apply?
- Who will operate and maintain the system?
In many cases, a hybrid approach delivers the best results.
Our company can provide this solution end-to-end, including hardware selection, edge software, system integration, and deployment support.
FAQ
What accuracy should a people counting solution achieve?
Accuracy requirements depend on the application. Trend analysis tolerates small errors, whereas safety and compliance use cases require consistently high accuracy and a well-defined approach to handling unknown states.
Can people counting be privacy-friendly?
Yes. Edge processing, anonymized outputs, and strict data governance significantly reduce privacy risk.
Why is Wi-Fi or Bluetooth counting considered an estimate?
Because it measures devices, not people, and device behavior varies widely.
Where should sensors be installed?
Top-down placement at entrances is generally preferred for reliable counting. Zone sensors should match real operational areas.
What systems are commonly integrated?
Building management, retail systems, workforce planning, and BI platforms are common integrations.
Conclusion
A people counting solution is not just a sensor—it is an engineered system. Success depends on matching the technology to the environment, validating accuracy, respecting privacy, and maintaining operational discipline.
When designed and deployed correctly, people counting provides reliable insights that support staffing, safety, and space optimization decisions over the long term.
Sources
- European Data Protection Board – Guidelines on video-based data processing
https://www.edpb.europa.eu/sites/default/files/files/file1/edpb_guidelines_201903_video_devices_en_0.pdf - OpenCV Documentation – Background subtraction methods
https://docs.opencv.org/4.x/d8/d38/tutorial_bgsegm_bg_subtraction.html - Martin et al. – MAC address randomization in mobile devices
https://petsymposium.org/popets/2017/popets-2017-0054.pdf - Bravenec et al. – Privacy aspects of Wi-Fi probe requests
https://arxiv.org/pdf/2206.10927 - LiDAR-based people counting evolution
https://insights.outsight.ai/the-3rd-generation-of-people-counting-technology/
