Data from computer vision sensors are more valuable for workplace experience initiatives than data from other types of sensors like infrared, WiFi, Bluetooth, or RFID sensors because it provides a more comprehensive and accurate picture of how employees are using the workspace.
Computer vision sensors use sophisticated algorithms to detect people and objects in the workspace and track their real-time movements. This allows them to provide highly detailed information about how people use different office areas, including which spaces are most popular, how long people spend in each area, and how they move around the space. This level of detail can help companies identify behavior patterns and make data-driven decisions to optimize the workspace.
In contrast, other types of sensors like infrared, wifi, Bluetooth, or RFID have limitations that make them less effective for workplace experience initiatives. For example, infrared sensors are limited to detecting heat signatures and cannot provide detailed information about how people use space. Similarly, wifi, Bluetooth, or RFID sensors rely on people carrying devices or wearing badges, which can be unreliable and not accurately capture all movements.
The differences in data accuracy and granularity between computer vision entry and area sensors and competing technology are quite significant. For example, XY Sense offers industry-leading computer vision sensors that provide superior coverage (95 sqm/1000 square feet/20 desks versus about half that for other technologies), accuracy (<1ft), actionable out-of-the-box analytics, and more sustainable installation capabilities (~80% less cabling required.)
Learn more about the various available occupancy sensor technologies.