US 11,756,056 B2
Collection of consumer feedback on dispensed product samples to generate machine learning inferences
Nihal Advani, Chicago, IL (US)
Assigned to Georama, Inc., Chicago, IL (US)
Filed by Georama, Inc., Chicago, IL (US)
Filed on Aug. 14, 2020, as Appl. No. 16/993,891.
Claims priority of provisional application 62/959,864, filed on Jan. 10, 2020.
Prior Publication US 2021/0217032 A1, Jul. 15, 2021
Int. Cl. G06Q 30/0201 (2023.01); G06Q 30/0203 (2023.01); G06N 20/00 (2019.01); G07F 17/00 (2006.01); G07F 9/00 (2006.01); G06V 20/10 (2022.01); G06V 10/764 (2022.01); G06V 20/40 (2022.01); G06V 40/16 (2022.01)
CPC G06Q 30/0201 (2013.01) [G06N 20/00 (2019.01); G06Q 30/0203 (2013.01); G06V 10/764 (2022.01); G06V 20/10 (2022.01); G06V 20/46 (2022.01); G06V 40/175 (2022.01); G07F 9/002 (2020.05); G07F 17/0064 (2013.01)] 18 Claims
OG exemplary drawing
 
1. A system comprising:
a sampling subsystem to distribute one or more samples of a food or drink product to a consumer, wherein the sampling subsystem comprises:
one or more food or drink product holding receptacles to hold the one or more samples of the food or drink product, and
a movable component to retrieve the one or more samples of the food or drink product from the one or more food or drink product holding receptacles;
an interactive imaging device communicatively coupled to the sampling subsystem to acquire images of the consumer while the consumer consumes the one or more samples of the food or drink product, wherein the acquired images comprise images of one or more facial expressions of the consumer while the consumer consumes the one or more samples of the food or drink product; and
a cloud computing server remotely coupled to the interactive imaging device by way of a communication network to deploy one or more machine learning models trained on a plurality of facial expressions of one or more of the consumer or other individuals, wherein
the deployment of the one or more trained machine learning models comprises providing the acquired images as input to the one or more trained machine learning models to generate real-time machine-learning inferences specific to the one or more samples of the food or drink product and the one or more facial expressions of the consumer, and
wherein the cloud computing server is configured to generate customized data associated with the one or more samples of the food or drink product based on the real-time machine-learning inferences.