Edge computing system with low power wide area network connectivity and autonomous or semi-autonomous machine learning

US12290339B2 · kind B2 · utility

Assignee

• CareBand, Inc. · US

Inventors

• Adam G. Russek-Sobol · Chicago, US
• Joseph T. Kreidler · Arlington Heights, US
• Brian A. Donlin · Chicago, US
• Jon G. Ledwith · Palatine, US
• Patrick J. McVey · Wheeling, US
• Ross D. Moore · Winnetka, US
• Peter Nanni · Algonquin, US
• Dwayne D. Forsyth · Deer Park, US
• Paul Sheldon · Mequon, US
• Todd Sobol · Dayton, US
• John D. Reed · Arlington, US

Key dates

• Filing date: Sep 6, 2024
• Grant date: May 6, 2025
• Expiry date: Sep 6, 2044

Classification

• Technology area (CPC G): Physics
• CPC primary: G08C17/02
• WIPO field: Medical technology
• WIPO sector: Instruments

Abstract

A mobile edge computing system, a communication network and a method of using a mobile edge computing device. The mobile edge computing system includes a communication module that establishes signal communication over numerous wireless communication protocols at least one of which uses a low power wide area network protocol. A logic device is made up of a distributed set of processing units including both a central processing unit and one or more processors configured for performing machine learning operations the latter of which include one or more of a graphical processor unit and a tensor processing unit. When the system receives event data that has been acquired by one or more of the communication module and a sensor, the system executes a trained machine learning model and conveys, using the low power wide area network protocol, an output that has been produced by the trained machine learning model.