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*** This post is part of our Go Beyond People Counting series ***
Employee detection is an emerging trend in people counting sensors. The applications for this functionality are very varied and range from excluding staff in low traffic flow environment for more accurate data, to understanding how staff movements influence customers and even to automating calls for staff when customers are waiting.
How does it work?
But first, it is important to understand how it all works. As detailed in the Introducing Vector 4D post, the Vector 4D uses a Time of Flight sensor to detect invisible infrared light that has been reflected off people passing beneath it. Analysing this information using proprietary algorithms, it can accurately identify when there is a person present.
Staff can be detected by wearing a passive lanyard made from a special material. The infrared light reflected from this material has a special signature that can be identified, ensuring the employee is correctly tracked.
The lanyard is unobtrusive, discreet and works independently of clothing colour or style. Unlike other people counters that can detect staff, the Vector 4D does not require RF tags, beacons, batteries or any complicated set up.
Privacy for the staff member is maintained as the system does not distinguish between individual staff members.
Do I need to detect staff?
If you answer “yes” to one or more of the questions below then it is likely that having a people counter than can accurately detect employees is important.
- Do you have a low traffic flow environment where staff movement distorts the data?
- Do you want to exclude employees from counts?
- Do you want to specifically count employee movements?
- Do you want to understand how staff interact with customers?
- Do you want to automate calls for staff when a customer is waiting?
- Do you have door or security staff working within your store?
Data is only useful if it is accurate. By excluding employees and improving the accuracy of your footfall data you can make better informed decisions.
By detecting staff, new metrics about how staff interact with customers can be reported. This topic will be discussed further in future blog posts, along with applications such as automating calls for staff attendance when a customer is waiting.