Patent Issued for Processing system having a machine learning engine for providing a customized driving assistance output (USPTO 11961397): Allstate Insurance Company

2024 MAY 03 (NewsRx) -- By a News Reporter-Staff News Editor at Insurance Daily News -- From Alexandria, Virginia, NewsRx journalists report that a patent by the inventors Chintakindi, Sunil (Menlo Park, CA, US), Hayes, Howard (Glencoe, IL, US), filed on March 26, 2021, was published online on April 16, 2024.

The patent’s assignee for patent number 11961397 is Allstate Insurance Company (Northbrook, Illinois, United States).

News editors obtained the following quote from the background information supplied by the inventors: “Mobile devices comprise a plurality of sensors. Each interaction with a mobile device yields sensor data, associated with characteristics of a user and the user’s surroundings. Users may not be aware of how best to protect themselves while driving. Accordingly, it would be advantageous to control the plurality of sensors with regard to timing of data collection, an amount of data collected, a type of data collected, and the like, and to aggregate the sensor data to generate customized driving assistance outputs. This may increase driver safety.”

As a supplement to the background information on this patent, NewsRx correspondents also obtained the inventors’ summary information for this patent: “In light of the foregoing background, the following presents a simplified summary of the present disclosure in order to provide a basic understanding of some aspects of the disclosure. This summary is not an extensive overview of the disclosure. It is not intended to identify key or critical elements of the disclosure or to delineate the scope of the disclosure. The following summary merely presents some concepts of the disclosure in a simplified form as a prelude to the more detailed description provided below.

“Methods, systems, and non-transitory computer-readable media are described herein. In some embodiments, a sensor data analysis and device control system including a processor may transmit, to a mobile device, an instruction to position the mobile device within a first vehicle. Further, the sensor data analysis and device control system may receive, from the mobile device, initial sensor data comprising sensor data around and within the first vehicle collected during or after the positioning. Next, the sensor data analysis and device control system may analyze, in real-time, the initial sensor data to identify a potential hazard. Additionally, the sensor data analysis and device control system may receive, after identifying the potential hazard and from the mobile device, additional sensor data associated with the potential hazard. Subsequently, the sensor data analysis and device control system may determine, based on the initial sensor data and the additional sensor data, a customized driving assistance output associated with the potential hazard. Further, the sensor data analysis and device control system may generate, based on the customized driving assistance output, a notification output comprising an indication of the potential hazard. Next, the sensor data analysis and device control system may generate, after generating the notification output, an instruction output comprising an instruction to modify a position or operation of the first vehicle responsive to the potential hazard. In addition, the sensor data analysis and device control system may transmit the notification output and the instruction output to the mobile device.

“In some examples, the instruction to position the mobile device within the first vehicle may comprise an instruction to initiate rotation of the mobile device within the first vehicle.

“In some instances, the initial sensor data may comprise at least one of: video sensor data, audio sensor data, vibration sensor data, and proximity sensor data.

“In some examples, the sensor data analysis and device control system may receive data related to at least one of: a known route of the first vehicle, a risk map for the known route, weather information, and insurance information. Further, the sensor data analysis and device control system may analyze the data to identify an orientation for the mobile device. In addition, the sensor data analysis and device control system may transmit, to the mobile device, an instruction to modify a position of the mobile device to the identified orientation.”

The claims supplied by the inventors are:

“1. A method comprising: receiving, by a sensor data analysis and device control system including a processor and memory, initial sensor data collected by a sensor at least one of around or within a first vehicle; selecting, by the sensor data analysis and device control system, one or more machine learning datasets based on one or more driving conditions associated with the first vehicle; analyzing, in real-time and by the sensor data analysis and device control system, the initial sensor data based on the selected machine learning datasets to identify a potential hazard; generating, by the sensor data analysis and device control system a notification based on the selected machine learning datasets, wherein the notification includes customized driving assistance output comprising an instruction to modify at least one of a position or operation of the first vehicle responsive to the identified potential hazard; and transmitting, from the sensor data analysis and device control system to an operating system of the first vehicle, the notification including a command for the first vehicle to perform the instruction of the customized driving assistance output.

“2. The method of claim 1, wherein the initial sensor data comprises at least one of: video sensor data, audio sensor data, vibration sensor data, or proximity sensor data.

“3. The method of claim 1, further comprising: receiving, by the sensor data analysis and device control system, data related to at least one of: a known route of the first vehicle, a risk map for the known route, weather information, or insurance information; analyzing, by the sensor data analysis and device control system, the data to identify an orientation for a mobile device associated with the first vehicle; and transmitting, by the sensor data analysis and device control system and to the mobile device, an instruction to modify a position of the mobile device to the identified orientation.

“4. The method of claim 1, wherein a recipient device associated with the first vehicle includes a mobile device within the first vehicle, and wherein the mobile device displays the customized driving assistance output.

“5. The method of claim 1, wherein identifying the potential hazard is further based on a comparison to a predetermined threshold value.

“6. The method of claim 1, wherein the first vehicle is an autonomous vehicle, and wherein a recipient device associated with the first vehicle is an autonomous vehicle operating system that executes the instruction of the customizing driving assistance output to modify the position or operation of the first vehicle.

“7. The method of claim 1, wherein a recipient device is an audio output device of the first vehicle, and wherein the audio output device plays audio output of the instruction of the customized driving assistance output.

“8. The method of claim 1, further comprising: receiving, by the sensor data analysis and device control system, data following transmission of the instruction of the customized driving assistance output; and determining, by the sensor data analysis and device control system and responsive to receiving a reaction, whether the instruction has been complied with.

“9. The method of claim 1, further comprising: performing, by the sensor data analysis and device control system, facial recognition on a driver of the first vehicle; and distinguishing, by the sensor data analysis and device control system, a driver from one or more other drivers based on the facial recognition.

“10. An apparatus comprising: a memory; and a processor of a sensor data analysis and device control system, the processor coupled to the memory and programmed with computer-executable instructions for performing steps comprising: receiving, by the sensor data analysis and device control system, initial sensor data collected by a sensor at least one of around or within a first vehicle; selecting, by the sensor data analysis and device control system, one or more machine learning datasets based on one or more driving conditions associated with the first vehicle; analyzing, in real-time and by the sensor data analysis and device control system, the initial sensor data based on the selected machine learning datasets to identify a potential hazard; generating, by the sensor data analysis and device control system, a notification based on the selected machine learning datasets, wherein the notification includes customized driving assistance output comprising an instruction to modify at least one of a position or operation of the first vehicle responsive to the identified potential hazard; and transmitting, from the sensor data analysis and device control system to an operating system of the first vehicle, the notification including a command for the first vehicle to perform the instruction of the customized driving assistance.

“11. The apparatus of claim 10, wherein the instruction is executable to display the customized driving assistance on one or more windows of the first vehicle.

“12. The apparatus of claim 10, wherein the instruction is executable to display an instruction for a driver of the first vehicle to modify the position or operation of the first vehicle in accordance with the customizing driving assistance output.

“13. The apparatus of claim 10, wherein the instruction is executable by an autonomous vehicle operating system to cause the first vehicle to change lanes.

“14. The apparatus of claim 10, wherein a mobile device is mounted in a cradle within the first vehicle and the instruction is further executable to initiate rotation of the cradle.

“15. The apparatus of claim 10, wherein the customized driving assistance output further includes a risk map that indicates a location of the potential hazard.

“16. The apparatus of claim 10, wherein the initial sensor data is received from a mobile device that comprises the sensor data analysis and device control system.

“17. One or more non-transitory computer-readable media storing computer-executable instructions, which when executed by a processor, cause a computing device to perform steps comprising: receiving, by a sensor data analysis and device control system, initial sensor data collected by a sensor at least one of around or within a first vehicle; selecting, by the sensor data analysis and device control system one or more machine learning datasets based on one or more driving conditions associated with the first vehicle; analyzing, in real-time and by the sensor data analysis and device control system, the initial sensor data based on the selected machine learning datasets to identify a potential hazard; generating, by the sensor data analysis and device control system, a notification based on the selected machine learning datasets, wherein the notification includes customized driving assistance output comprising an instruction to modify at least one of a position or operation of the first vehicle responsive to the potential hazard; and transmitting, from the sensor data analysis and device control system to an operating system of the first vehicle, the notification including a command for the first vehicle to perform the instruction of the customized driving assistance output.

“18. The one or more non-transitory computer-readable media of claim 17, further including instructions that, when executed, cause the computing device to: compare the customized driving assistance output to a predetermined driving assistance threshold; and determine, and based on the comparison, whether to generate a second notification.

“19. The one or more non-transitory computer-readable media of claim 17, further including instructions that, when executed, cause the computing device to select different machine learning datasets for a second vehicle and to generate a different notification for a second recipient device associated with the second vehicle responsive to the same identified potential hazard.

“20. The one or more non-transitory computer-readable media of claim 17, wherein the notification further includes a risk map indicating a location of the potential hazard.”

For additional information on this patent, see: Chintakindi, Sunil. Processing system having a machine learning engine for providing a customized driving assistance output. U.S. Patent Number 11961397, filed March 26, 2021, and published online on April 16, 2024. Patent URL (for desktop use only): https://ppubs.uspto.gov/pubwebapp/external.html?q=(11961397)&db=USPAT&type=ids

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