Innovative solutions like Lambent Spaces use Wi-Fi to estimate the number of people in physical spaces like buildings, classrooms, offices, and conference areas. This estimation is done by passively detecting devices like laptops, smartphones, tablets, and smartwatches through the signals they emit to stay connected.
In this article, I’ll break down how these Wi-Fi signals lead to occupancy insights in three key steps:
- Getting from Wireless Signals to Device Counts
- Getting from Device Counts to Occupancy Estimates
- Getting from Occupancy Estimates to Actionable Metrics
The widespread adoption and availability of Wi-Fi make it a natural fit to play an increasingly important role in occupancy analytics and space planning.
From Wireless Signals to Device Counts
Most organizations have Wi-Fi infrastructure that can detect these wireless devices, sometimes even if they aren’t actively connected to the network. Lambent Spaces seamlessly integrates with an organization’s Wi-Fi infrastructure through vendor-approved network management APIs. It continuously collects data about devices that are connected or visible to each Wi-Fi access point. This process doesn’t involve accessing the actual network or capturing data packets.
The collected data includes information like when a device was seen, its unique MAC address, and sometimes details like an authenticated username, device type, signal strength, connection properties, and device position, which uses methods like trilateration based on signal properties. When device positions aren’t available in the collected Wi-Fi data, they can be approximated using techniques like proximity.
The accuracy of device positions depends on the capabilities and locations of the Wi-Fi access points and the characteristics of the physical environment. Lambent Spaces uses available data to determine device positions and can identify areas where different technology like sensors may be required to achieve a desired level of accuracy.
To protect individual privacy, especially regarding MAC addresses, Lambent Spaces anonymizes sensitive data at the point of integration using cryptographic hashing and an organization-controlled key. This ensures that the data processed by Lambent Spaces cannot be linked to specific individuals without additional information. Lambent Spaces does not track individuals or record location data, and personal information is never exposed through applications, data exports, or APIs.
The anonymous data represents a spatiotemporal distribution of devices. Sampling methods used during data collection ensure that small variations, like someone walking through an area, don’t significantly affect the overall distribution of device counts. However, the count of devices alone is not a reliable estimate of occupancy in a space.
From Device Counts to Occupancy Estimates
Estimating occupancy based on devices comes with challenges. Not all devices are always connected, some are better indicators of a person’s presence, some people carry multiple devices, and some people carry none.
Lambent Spaces addresses these challenges by using machine learning models and algorithms to estimate occupancy based on device behavior and connectivity patterns. It preferentially considers only those devices most likely associated with a person, such as wearables or mobile phones. Devices like desktop computers and printers, which are typically stationary, are not included in occupancy estimates. Additionally, each deployment is validated, and parameters adjusted to align estimates with observed occupancy, and to accommodate differences in the number of devices people carry and the physical environment.
Individual occupancy estimates are averaged over 5 to 15-minute intervals to smooth out minor fluctuations and better align with external events and activities. This results in a distribution of occupancy estimates for the organization, revealing usage patterns across different spaces and across different times.
From Occupancy Estimates to Actionable Metrics
Effective space planning requires more than just occupancy data; it needs context and correlation with other information. Lambent Spaces integrates data from facilities management systems (such as capacity, cost, size, category, and purpose) and context from operations and scheduling systems (like operating hours, staffing, resource availability, reservations, and events).
This comprehensive data forms the basis for Lambent Spaces spatial analytics, visualizations, KPI dashboards, and targeted reports. These insights help organizations reduce capital costs, improve the experience of employees and students, and work toward a more sustainable future. And it all starts with the foundational power of Wi-Fi.
Lambent Spaces helps corporate customers reshape, resize, and restack buildings by revealing occupancy and utilization trends and patterns. To learn more, book a demo.
