	US 12,001,963 B2
	Facilitating ML algorithm contribution to use cases where data is prohibitive
Gopi Subramanian, Boca Raton, FL (US); and Michael C. Stewart, Deerfield Beach, FL (US)
Assigned to Sensormatic Electronics, LLC, Boca Raton, FL (US)
Filed by Sensormatic Electronics, LLC, Boca Raton, FL (US)
Filed on Mar. 19, 2021, as Appl. No. 17/207,340.
Claims priority of provisional application 63/018,190, filed on Apr. 30, 2020.
Prior Publication US 2021/0343129 A1, Nov. 4, 2021
Int. Cl. G06N 3/126 (2023.01); G06F 18/214 (2023.01); G06N 20/00 (2019.01); G08B 13/24 (2006.01)

CPC G06N 3/126 (2013.01) [G06F 18/214 (2023.01); G06N 20/00 (2019.01); G08B 13/2474 (2013.01)]

20 Claims

1. A method, comprising:

determining training information including a plurality of stray training reads and a plurality of valid training reads;

determining modified training information based at least in part on modifying the plurality of valid training reads;

generating a model for distinguishing a valid read from a stray read based on the modified training information and an evolutionary algorithm;

detecting, by a monitoring device, a plurality of tag reads in response to a plurality of interactions between a tag and the monitoring device; and

determining, by the monitoring device, a plurality of valid tag reads based on the model and plurality of tag reads.