Using machine learning to predict a usage profile and recommendations associated with a computing device

US11449921B2 · kind B2 · utility

Assignee

• Dell Products L.P. · US

Inventors

• Tejas Naren Tennur Narayanan · Austin, US
• Gautam Kaura · Austin, US
• Stephen Young · Cumming, US
• Sathish Kumar Bikumala · Round Rock, US
• Harshit Mehta · Austin, US
• Harshita Dubey · Round Rock, US
• Avanthika Sankararaman · Cedar Park, US

Key dates

• Filing date: Jun 19, 2020
• Grant date: Sep 20, 2022
• Expiry date: Mar 13, 2041

Classification

• Technology area (CPC G): Physics
• CPC primary: G06Q30/012
• WIPO field: IT methods for management
• WIPO sector: Electrical engineering

Abstract

In some examples, a server may receive usage data from a computing device, determine a usage profile of the computing device, and determine that a component of the computing device is predicted to fail and at what time. If the time is within a warranty period of a current warranty, then the server may recommend purchasing an upgraded warranty and provide a cost-benefit analysis of purchasing the upgraded warranty. If the time is outside the warranty period, then the server may recommend purchasing an extended warranty and provide a cost-benefit analysis of purchasing the extended warranty. The server may use the usage data to make a recommendation to upgrade one or more components (e.g., memory, disk drive, network card, or the like) of the computing device. The server may use the usage data to make a recommendation to upgrade from the computing device to a different computing device.