Allstate Insurance Company

Younuskhan Mohamed Iynoolkhan

Surender Kumar

Mark V Slusar

Clint J Marlow

Timothy W Gibson

Chris Wiklund

Nilesh Malpekar

Robert Andrew Nendorf

Patrick O'Reilly

Bich-Thuy Le

Charles Peavie

Event-based and subscription-based connected vehicle control and response systems, methods, and apparatus are disclosed. An example method comprises receiving first data acquired by a first plurality of vehicle operation sensors of a first vehicle from a first computing device associated with a first subscriber, identifying an occurrence of an event involving a second vehicle and a third vehicle based on the first data, receiving second data acquired by a second plurality of vehicle operation sensors of the second vehicle, identifying which vehicle of the second vehicle or the third vehicle is at-fault based on the first data and the second data, determining, for the first subscriber and responsive to determining that the first data was used in determining which of the first vehicle or the second vehicle is at-fault, one or more objects, and transmitting the one or more objects to the first computing device.

Subscription-based and event-based connected vehicle control and response systems

Aspects of the disclosure relate to systems, methods, and computing devices for managing the processing and execution of machine learning classifiers across a variety of platforms. Machine classifiers can be developed to process a variety of input datasets. In several embodiments, a variety of transformations can be performed on raw data to generate the input datasets. The raw data can be obtained from a disparate set of data sources each having its own data format. The generated input datasets can be formatted using a common data format and/or a data format specific for a particular machine learning classifier. A sequence of machine learning classifiers to be executed can be determined and the machine learning classifiers can be executed on one or more computing devices to process the input datasets. The execution of the machine learning classifiers can be monitored and notifications can be transmitted to various computing devices.

Multi-platform machine learning systems

Methods, computer-readable media, software, and apparatuses may receive, at a field vehicle, field data from one or more unmanned autonomous vehicles, where the field data may be indicative of an item for assessment. Edge-computing, based on machine learning techniques, may be performed at the field vehicle to identify one or more characteristics of the assessment, and a projected cost may be determined. An estimate may be sent to a consumer. In some aspects, the projected costs may be based on local data related to a geographical location of the item. In another aspect, underwriting tasks may be performed at the field vehicle, and a quote may be sent to a consumer.

Inspection and assessment based on mobile edge-computing

Growing community of inventors

Rolling Meadows, IL, United States of America

Younuskhan Mohamed Iynoolkhan