12CU is a software solution that uses existing WiFi infrastructure to measure and analyze the buildings occupancy. Its goal is to provide accurate insights into how spaces are used, helping organizations optimize buildings, schedules, and resources.

Data collection via Wi-Fi

12CU relies on devices that connect to the organization’s Wi-Fi network:

• Devices such as smartphones, tablets, and laptops set up to connect to Wi-Fi
• Users authenticate using their personal login (e.g., eduroam)
• The network detects and maintains these connections
• Each connected device acts as a signal that a person is present
• Multiple devices of the same person can be deduplicated 

Even when devices are not actively used, they typically remain connected or reconnect frequently, allowing continuous detection.

Note: If a person has multiple devices, there's a good chance we can deduplicate them and measure a single person.

Location detection

The Wi-Fi infrastructure determines where devices are located:

• Identifies building, floor, and approximate position
• Uses signal strength and triangulation between access points
• Can achieve location accuracy with ~90% of measurements within 10 meters

This allows 12CU to map where people are across the campus.

Data processing and anonymization

Once data is collected:

• Network infrastructure shares connection and location data with 12CU
• 12CU processes and analyzes the data automatically
• Personal identifiers are removed and replaced with anonymous IDs
• Users are categorized into groups (e.g., student, employee, visitor)

This ensures privacy while still enabling meaningful insights.

Note: The use of groups is optional, the product works with or without groups depending on the clients needs.

Counting methodology

12CU continuously counts people on campus:

• A new count is generated every 10 minutes
• A device must be detected at least once within that interval
• Most devices reconnect frequently, ensuring reliable detection
• Results are stored for both real-time and historical analysis

Counting accuracy can reach approximately 95% at building level.

What is included in the count

• People carrying at least one device set up to connect to WiFi
• Devices logged into the organizations networks

What is not included

• Devices switched off
• Devices with WiFi explicitly disabled
• Devices fully isolated (e.g., inside shielded lockers)

Insights and output

The processed data is made available through:

• Dashboards with occupancy insights and statistics
• Historical trend analysis (e.g., every 10 minutes, year-round)
• Data export to tools like Excel or Power BI

What this enables

With these insights, organizations can:

• Compare planned vs. actual occupancy
• Optimize space usage
• Improve scheduling and space planning
• Monitor real-time space/building utilization