US 12,073,152 B2
Vehicle asset modeling using language processing methods
Elham Khabiri, Briarcliff Manor, NY (US); Anuradha Bhamidipaty, Yorktown Heights, NY (US); Robert Jeffrey Baseman, Brewster, NY (US); Chandrasekhara K. Reddy, Kinnelon, NJ (US); and Srideepika Jayaraman, White Plains, NY (US)
Assigned to INTERNATIONAL BUSINESS MACHINES CORPORATION, Armonk, NY (US)
Filed by INTERNATIONAL BUSINESS MACHINES CORPORATION, Armonk, NY (US)
Filed on Jul. 20, 2020, as Appl. No. 16/933,977.
Prior Publication US 2022/0019708 A1, Jan. 20, 2022
This patent is subject to a terminal disclaimer.
Int. Cl. G06F 30/15 (2020.01); G06F 30/27 (2020.01); G06F 40/40 (2020.01)
CPC G06F 30/15 (2020.01) [G06F 30/27 (2020.01); G06F 40/40 (2020.01)] 20 Claims
OG exemplary drawing
 
1. A computing device comprising:
a processor;
a storage device for content and programming coupled to the processor;
a vehicle asset modeling module stored in the storage device, wherein an execution of the vehicle asset modeling module by the processor configures the computing device to perform acts comprising:
identifying and clustering a plurality of assets based on static properties of a vehicle asset using a first module of the vehicle asset modeling module;
determining a rating of one or more assets of the clustered plurality of assets based on dynamic properties of the vehicle asset, by a second module of the vehicle asset modeling module;
performing an event prediction by converting a numeric data of the clustered plurality of assets to a natural language processing (NLP) domain by a third module of the vehicle asset modeling module;
performing one or more sequence-to-sequence methods to predict a malfunction of a component of the vehicle asset and/or an event based on past patterns, by the third module of the vehicle asset modeling module; and
storing information related to the event prediction and malfunction prediction in the storage device.