Patent Issued for Processing system for dynamic event verification and sensor selection (USPTO 11609558): Allstate Insurance Company

2023 APR 06 (NewsRx) -- By a News Reporter-Staff News Editor at Insurance Daily News -- Allstate Insurance Company (Northbrook, Illinois, United States) has been issued patent number 11609558, according to news reporting originating out of Alexandria, Virginia, by NewsRx editors.

The patent’s inventors are Isaac, Emad S. (Downers Grove, IL, US).

This patent was filed on October 29, 2019 and was published online on March 21, 2023.

From the background information supplied by the inventors, news correspondents obtained the following quote: “Aspects of the disclosure relate to enhanced processing systems for performing dynamic event verification and sensor selection. Many organizations and individuals rely on sensor data to determine whether an event occurred. In many instances, however, data used to determine whether an event occurred, or the determinations themselves may be inaccurate. There remains an ever-present need to develop improved methods of verifying whether an event occurred using sensor data.”

Supplementing the background information on this patent, NewsRx reporters also obtained the inventors’ summary information for this patent: “Aspects of the disclosure provide effective, efficient, scalable, and convenient technical solutions that address and overcome the technical problems associated with event verification and sensor selection. In accordance with one or more arrangements discussed herein, a computing platform having at least one processor, a communication interface, and memory may receive first source data comprising driving data associated with a first vehicle over a first time period. Based on the first source data, the computing platform may determine that the first vehicle experienced an event, resulting in an event output. In response to determining the event output, the computing platform may generate a request for second source data associated with the first vehicle over the first time period. The computing platform may receive, from a sensor device, the second source data. Based on a comparison of the first source data to the second source data, the computing platform may determine an event comparison output. The computing platform may determine that the event comparison output exceeds a predetermined comparison threshold. In response to determining that the event comparison output exceeds the predetermined comparison threshold, the computing platform may send an indication of an event.

“In some arrangements, determining that the vehicle experienced an event may comprise comparing the first source data to one or more machine learning datasets using one or more machine learning algorithms. In some examples, the computing platform may determine that the event comparison output does not exceed the predetermined comparison threshold. In response to determining that the event comparison output does not exceed the predetermined comparison threshold, the computing platform may update the one or more machine learning datasets and the one or more machine learning algorithms.

“In some arrangements, in response to determining that the event comparison output exceeds the predetermined comparison threshold, the computing platform may generate event confirmation interface information and one or more commands directing a mobile device to cause display of an event confirmation interface based on the event confirmation interface information. The computing platform may establish a wireless connection with the mobile device. While the wireless connection is established, the computing platform may send, to the mobile device, the event confirmation interface information and one or more commands directing the mobile device to cause display of the event confirmation interface.

“In some examples, the computing platform may be one of: a first mobile device and a first vehicle sensor. In some examples, the computing platform may be one of: a second mobile device and a second vehicle sensor. In these examples, the computing platform may be located in the first vehicle and the sensor device may be located in a second vehicle.

“In some arrangements, the computing platform may be an event analysis server with wireless connections established with one or more sensor devices including the sensor device, and wherein the computing device is configured to receive the first source data from one of the one or more sensor devices. In some arrangements, the first source data may include a first type of data and the second source data may include a second type of data different than the first type of data.”

The claims supplied by the inventors are:

“1. A computing device comprising: at least one processor; a communication interface communicatively coupled to the at least one processor; and memory storing computer-readable instructions that, when executed by the at least one processor, cause the computing device to: receive, from a first sensor device, first source data comprising driving data associated with a first vehicle over a first time period; determine, based on the first source data, that the first vehicle experienced an event, resulting in an event output; generate, in response to determining the event, a request for a second sensor device to send second source data associated with the first vehicle over the first time period; receive, from the second sensor device, the second source data after generating the request; determine, based on a comparison of the first source data and the second source data, an event comparison output indicating a correlation between the first source data and the second source data; determine that the event comparison output exceeds a comparison threshold; and send, in response to determining that the event comparison output exceeds the comparison threshold, an indication of the event.

“2. The computing device of claim 1, wherein determining that the first vehicle experienced the event comprises comparing the first source data and one or more machine learning datasets using one or more machine learning algorithms.

“3. The computing device of claim 1, wherein the memory stores additional computer-readable instructions that, when executed by the at least one processor, further cause the computing device to: determine that the event comparison output does not exceed the comparison threshold; and update, in response to determining that the event comparison output does not exceed the comparison threshold, one or more machine learning datasets used for event determination.

“4. The computing device of claim 3, wherein the memory stores additional computer-readable instructions that, when executed by the at least one processor, further cause the computing device to: generate, in response to determining that the event comparison output exceeds the comparison threshold, one or more commands directing a mobile device to cause display of an event confirmation; establish a wireless connection with the mobile device; and send, to the mobile device and while the wireless connection is established, the one or more commands to the mobile device.

“5. The computing device of claim 1, wherein the first sensor device is a sensor of a first mobile device or a first vehicle sensor.

“6. The computing device of claim 5, wherein the second sensor device is a sensor of a second mobile device or a second vehicle sensor.

“7. The computing device of claim 1, wherein the first sensor device is located in the first vehicle and the second sensor device is located in a second vehicle.

“8. The computing device of claim 1, wherein the computing device is part of an event analysis server with wireless connections established with the first sensor device and the second sensor device.

“9. The computing device of claim 1, wherein the first source data includes a first type of data, and wherein the second source data includes a second type of data different than the first type of data.

“10. A method comprising: at a computing device comprising at least one processor, a communication interface, and memory: receiving, from a first sensor device, first source data comprising driving data associated with a first vehicle over a first time period; determining, based on the first source data, that the first vehicle experienced an event, resulting in an event output; generating, in response to determining the event, a request for a second sensor device to send second source data associated with the first vehicle over the first time period; receiving, from the second sensor device, the second source data after generating the request; determining, based on a comparison of the first source data to the second source data, an event comparison output indicating a correlation between the first source data and the second source data; determining that the event comparison output exceeds a comparison threshold; and sending, in response to determining that the event comparison output exceeds the comparison threshold, an indication of the event.

“11. The method of claim 10, wherein determining that the first vehicle experienced the event comprises comparing the first source data and one or more machine learning datasets using one or more machine learning algorithms.

“12. The method of claim 10, further comprising: determining that the event comparison output does not exceed the comparison threshold; and updating, in response to determining that the event comparison output does not exceed the comparison threshold, one or more machine learning datasets used for event determination.

“13. The method of claim 12, further comprising: generating, in response to determining that the event comparison output exceeds the comparison threshold, one or more commands directing a mobile device to cause display of an event confirmation; establishing a wireless connection with the mobile device; and sending, to the mobile device and while the wireless connection is established, the one or more commands to the mobile device.

“14. The method of claim 10, wherein the first sensor device is a sensor of a first mobile device or a first vehicle sensor.

“15. The method of claim 14, wherein the second sensor device is a sensor of a second mobile device or a second vehicle sensor.

“16. The method of claim 10, wherein the first sensor device is located in the first vehicle and the second sensor device is located in a second vehicle.

“17. The method of claim 10, wherein the computing device is part of an event analysis server with wireless connections established with the first sensor device and the second sensor device.

“18. The method of claim 10, wherein the first source data includes a first type of data, and wherein the second source data includes a second type of data different than the first type of data.

“19. One or more non-transitory computer-readable media storing instructions that, when executed by a computing device comprising at least one processor, a communication interface, and memory, cause the computing device to: receive, from a first sensor device, first source data comprising driving data associated with a first vehicle over a first time period; determine, based on the first source data, that the first vehicle experienced an event, resulting in an event output; generate, in response to determining the event, a request for a second sensor device to send second source data associated with the first vehicle over the first time period; receive, from the second sensor device, the second source data after generating the request; determine, based on a comparison of the first source data and the second source data, an event comparison output indicating a similarity between the first source data and the second source data; determine that the event comparison output exceeds a comparison threshold; and send, in response to determining that the event comparison output exceeds the comparison threshold, an indication of the event.

“20. The one or more non-transitory computer-readable media of claim 19, wherein determining that the first vehicle experienced the event comprises comparing the first source data and one or more machine learning datasets using one or more machine learning algorithms.”

For the URL and additional information on this patent, see: Isaac, Emad S. Processing system for dynamic event verification and sensor selection. U.S. Patent Number 11609558, filed October 29, 2019, and published online on March 21, 2023. Patent URL (for desktop use only): https://ppubs.uspto.gov/pubwebapp/external.html?q=(11609558)&db=USPAT&type=ids

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