Authors:
James Hawk
Abstract:
Using existing technologies, create a method of identifying the location of the SCS(Self Checkout System) shopper and steering the SCS sounds (prompts, scan beeps, etc.) only to the one shopper. This reduces or eliminates the cross-talk of adjacent SCS systems.
Background:
In busy store environments, SCS systems are in close proximity to other SCS or other POS systems. Sounds from adjacent SCS systems, such as a scan beep, audio prompts for shoppers, etc. can be mistaken by the shopper which reduces SCS satisfaction, SCS throughput, and general usefulness.
Description:
Using existing technologies, such as LiDAR arrays or multiple video cameras, the primary shopper (when there are multiple shoppers present) needs to be identified and tracked. The typical shopper is not stationary as they pick up, scan, then bag items. That tracking data could be used with sound directing devices such as https://www.wired.com/2002/02/point-n-shoot-sound-makes-waves/ to transmit sounds only to one shopper.
This not only enhances the current shopping experience, but it will further allow more customized audio messaging that could be tied to loyalty or other customer attributes.
Claims: This submission would identify the ‘primary shopper’ when there is a plurality of humans present. This process could be improved by the introduction of ML to interpret feedback (body language or audio capture) to then improve the algorithm. Further, the ‘primary shopper’ role could change during a transaction based on their actions (e.g., someone else starts scanning). Tracking a moving person is not novel and is a piece of prior art. However, continuous delivery of audio to that moving (or changing) ‘primary shopper’ is novel.
TGCS Reference 3206
