The patent badge is an abbreviated version of the USPTO patent document. The patent badge does contain a link to the full patent document.

The patent badge is an abbreviated version of the USPTO patent document. The patent badge covers the following: Patent number, Date patent was issued, Date patent was filed, Title of the patent, Applicant, Inventor, Assignee, Attorney firm, Primary examiner, Assistant examiner, CPCs, and Abstract. The patent badge does contain a link to the full patent document (in Adobe Acrobat format, aka pdf). To download or print any patent click here.

Date of Patent:
Mar. 04, 2025

Filed:

Jan. 24, 2023
Applicant:

Dell Products L.p., Round Rock, TX (US);

Inventors:

Paulo Abelha Ferreira, Rio de Janeiro, BR;

Vinicius Michel Gottin, Rio de Janeiro, BR;

Pablo Nascimento da Silva, Niterói, BR;

Assignee:

Dell Products L.P., Round Rock, TX (US);

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G06N 20/00 (2019.01); G06F 11/3668 (2025.01); G06F 30/27 (2020.01); G06N 3/08 (2023.01);
U.S. Cl.
CPC ...
G06F 11/3688 (2013.01); G06F 11/3692 (2013.01); G06F 30/27 (2020.01); G06N 3/08 (2013.01);
Abstract

One example method includes determining a system aggregate drift metric score based on aggregate drift metric scores received from near-edge nodes associated with a central node. The system aggregate drift metric score indicates a level of model drift across a logistics system. The system aggregate drift metric score is compared with a system drift threshold. Current datasets are received from the near-edge nodes when a system aggregate drift metric score is greater than the system drift threshold. A first dataset is generated comprising a joining of the current datasets received from the plurality of near-edge nodes. A second dataset is received from each the near-edge nodes. The first and second datasets are used to select a machine-learning (ML) model to deploy at each of the near-edge nodes.


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