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:
Jun. 27, 2023

Filed:

Apr. 07, 2022
Applicant:

Toshiba Tec Kabushiki Kaisha, Shinagawa-ku, JP;

Inventors:

Guillermo Hernandez Gallegos, Jalisco, MX;

David Fuentes, Jalisco, MX;

Kevin Marquez Vaca, Jalisco, MX;

Daniel Garcia Zuñiga, Jalisco, MX;

Carlos Perez Hermosillo, Jalisco, MX;

Assignee:
Attorneys:
Primary Examiner:
Int. Cl.
CPC ...
H04N 1/08 (2006.01); H04N 1/00 (2006.01); H04L 67/12 (2022.01);
U.S. Cl.
CPC ...
H04N 1/00344 (2013.01); H04N 1/00244 (2013.01); H04N 1/00493 (2013.01); H04L 67/12 (2013.01); H04N 2201/0094 (2013.01);
Abstract

A system and method for maintenance and supplying of a fleet of multifunction peripheral devices includes two or more networked devices including a decision engine. Devices discover one another and one device is designated as a server. The server creates a virtual lobby accessible by other devices and its decision engine is enabled. The server invites other devices into its virtual lobby, and these devices join the lobby in response. Devices provide their device state information to the lobby. The enabled decision engine generates recommendations for consumable replenishment, device servicing or device configuration, relaying the recommendations to a system administrator's tablet or smartphone. The administrator may accept, reject, modify or implement received suggestions. Consumable supplies or servicing recommendations can be done automatically if enabled. Administrator actions are fed back to the server for machine learning to improve future suggestions.


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