# US 2021/0243566 A1 · Multi-Computer Processing System for Dynamically Executing Response Actions Based on Movement Data

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- Number: US 2021/0243566 A1
- Document ID: US20210243566A1
- Status: Published application
- Kind: A1
- Application number: 17/238,714
- Filed: 2021-04-23
- Published: 2021-08-05
- Earliest claimed: 2019-07-26
- Assignees: Allstate Insurance Company
- Applicants: Allstate Insurance Company
- Inventors: Surender Kumar; Sunil Chintakindi; Howard Hayes; Tim Gibson; Soton Ayodele Rosanwo
- Web page: https://patentgrep.com/patent/US20210243566A1

## CPC

- H04W 4/027: {using movement velocity, acceleration information}
- G06F 18/22: Matching criteria, e.g. proximity measures
- G06Q 10/0639: Performance analysis of employees; Performance analysis of enterprise or organisation operations
- G06Q 30/0201: Market modelling; Market analysis; Collecting market data
- G06Q 30/0224: {based on user history}
- G06Q 30/0236: {Incentive or reward received by requiring registration or ID from user}
- G06Q 40/08: Insurance
- G06Q 50/40: Business processes related to the transportation industry (shipping G06Q10/083)
- G06V 20/593: {Recognising seat occupancy}
- H04L 67/12: specially adapted for proprietary or special-purpose networking environments, e.g. medical networks, sensor networks, networks in vehicles or remote metering networks
- H04L 67/1396: specially adapted for monitoring users' activity
- H04L 67/535: {Tracking the activity of the user (network monitoring arrangements H04L43/00; recording of computer activity G06F11/34)}
- H04W 4/029: Location-based management or tracking services
- H04W 4/02: Services making use of location information
- H04W 4/024: Guidance services
- H04W 4/40: for vehicles, e.g. vehicle-to-pedestrians [V2P]
- H04W 4/44: for communication between vehicles and infrastructures, e.g. vehicle-to-cloud [V2C] or vehicle-to-home [V2H]
- H04W 4/80: Services using short range communication, e.g. near-field communication [NFC], radio-frequency identification [RFID] or low energy communication
- H04W: WIRELESS COMMUNICATION NETWORKS (broadcast communication H04H; communication systems using wireless links for non-selective communication, e.g. wireless extensions H04M1/72)
- G06F: ELECTRIC DIGITAL DATA PROCESSING (computer systems based on specific computational models G06N)
- G06Q: INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06V: IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- H04L: TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION (arrangements common to telegraphic and telephonic communication H04M)

## Abstract

Methods, computer-readable media, systems, and/or apparatuses for evaluating movement data to identify a user as a driver or non-driver passenger are provided. In some examples, movement data may be received from a mobile device of a user. The movement data may include sensor data including location data, such as global positioning system (GPS) data, accelerometer and/or gyroscope data, and the like. Additional data may be retrieved from one or more other sources. For instance, additional data such as usage of applications on the mobile device, public transportation schedules and routes, image data, vehicle operation data, and the like, may be received and analyzed with the movement data to determine whether the user of the mobile device was a driver or non-driver passenger of the vehicle. Based on the determination, the data may be deleted in some examples or may be further processed to generate one or more outputs.

## Claims

### Claim 1

A computing platform, comprising:
a processing unit comprising a processor; and
a memory unit storing computer-executable instructions, which when executed by the processing unit, cause the computing platform to:
receive, from at least an accelerometer associated with a mobile device, sensor data associated with movement of the mobile device during a first time period;
identify a number of other devices available to be paired with the mobile device;
analyze the received sensor data and the identified number of other devices available to be paired with the mobile device to determine whether the movement of the mobile device corresponds to a user of the mobile device being a driver of a vehicle during the first time period or the user of the mobile device being a non-driver passenger of the vehicle during the first time period;
responsive to determining that the movement of the mobile device corresponds to the user being a driver of the vehicle during the first time period, analyze the received sensor data to evaluate driving behaviors of the user associated with operation of the vehicle and generate a first output, including a first offer for a product or service, associated with the driving behaviors of the user; and
responsive to determining that the movement of the mobile device corresponds to the user being a non-driver passenger of the vehicle during the first time period, generate a second output including a second offer for a product or service, different from the first output.

### Claim 2 (depends on 1)

The computing platform of claim 1, wherein analyzing the identified number of other devices available to be paired with the mobile device includes comparing the number of other devices to a threshold and, responsive to determining that the number of other devices is greater than the threshold, determining that the user is traveling on public transportation.

### Claim 3 (depends on 1)

The computing platform of claim 1, further including instructions that, when executed, cause the computing platform to:
receive, from the mobile device, image data including an image of the user,
wherein analyzing the received sensor data further includes analyzing the image data including comparing the received image data to pre-stored image data to determine a position of the user within the vehicle.

### Claim 4 (depends on 1)

The computing platform of claim 1, further including instructions that, when executed, cause the computing platform to:
receive, from one or more external computing systems, public transportation schedules and routes,
wherein analyzing the received sensor data and the identified number of other devices available to be paired with the mobile device further includes analyzing the public transportation schedules and routes including comparing stoppage points within received sensor data to public transportation stops identified from the public transportation schedules and routes.

### Claim 5 (depends on 1)

The computing platform of claim 1, further including instructions that, when executed, cause the computing platform to:
receive, from an on-board vehicle computing device, data indicating an identity of a user performing at least one of: unlocking the vehicle and starting the vehicle,
wherein analyzing the received sensor data and the identified number of other devices available to be paired with the mobile device further includes analyzing the data indicating the identity of the user performing at least one of: unlocking the vehicle and starting the vehicle including comparing the identity of the user performing one of: unlocking the vehicle and starting the vehicle to the user of the mobile device.

### Claim 6 (depends on 1)

The computing platform of claim 1, further including instructions that, when executed, cause the computing platform to:
receive, from an on-board vehicle computing device, data indicating an operating mode of the vehicle,
wherein analyzing the received sensor data and the identified number of other devices available to be paired with the mobile device further includes analyzing the data indicating the operating mode of the vehicle including determining whether the operating mode is an autonomous operating mode.

### Claim 7 (depends on 1)

The computing platform of claim 1, further including instructions that, when executed, cause the computing platform to:
receive additional data from a plurality of sources,
wherein analyzing the received sensor data and the identified number of other devices available to be paired with the mobile device further includes analyzing the additional data from the plurality of sources including applying a weighting factor to different types of data in the additional data from the plurality of sources.

### Claim 8

One or more non-transitory computer-readable media storing computer-executable instructions that, when executed by a computing device, cause the computing device to:
receive, from at least an accelerometer associated with a mobile device, sensor data associated with movement of the mobile device during a first time period;
identify a number of other devices available to be paired with the mobile device;
analyze the received sensor data and the identified number of other devices available to be paired with the mobile device to determine whether the movement of the mobile device corresponds to a user of the mobile device being a driver of a vehicle during the first time period or the user of the mobile device being a non-driver passenger of the vehicle during the first time period;
responsive to determining that the movement of the mobile device corresponds to the user being a driver of the vehicle during the first time period, analyze the received sensor data to evaluate driving behaviors of the user associated with operation of the vehicle and generate a first output, including a first offer for a product or service, associated with the driving behaviors of the user; and
responsive to determining that the movement of the mobile device corresponds to the user being a non-driver passenger of the vehicle during the first time period, generate a second output, including a second offer for a product or service, different from the first output.

### Claim 9 (depends on 8)

The one or more non-transitory computer-readable media of claim 8, wherein analyzing the identified number of other devices available to be paired with the mobile device includes comparing the number of other devices to a threshold and, responsive to determining that the number of other devices is greater than the threshold, determining that the user is traveling on public transportation.

### Claim 10 (depends on 8)

The one or more non-transitory computer-readable media of claim 8, further including instructions that, when executed, cause the computing device to:
receive, from the mobile device, image data including an image of the user,
wherein analyzing the received sensor data further includes analyzing the image data including comparing the received image data to pre-stored image data to determine a position of the user within the vehicle.

### Claim 11 (depends on 8)

The one or more non-transitory computer-readable media of claim 8, further including instructions that, when executed, cause the computing device to:
receive, from one or more external computing systems, public transportation schedules and routes,
wherein analyzing the received sensor data and the identified number of other devices available to be paired with the mobile device further includes analyzing the public transportation schedules and routes including comparing stoppage points within the received sensor data to public transportation stops identified from the public transportation schedules and routes.

### Claim 12 (depends on 8)

The one or more non-transitory computer-readable media of claim 8, further including instructions that, when executed, cause the computing device to:
receive, from an on-board vehicle computing device, data indicating an identity of a user performing at least one of: unlocking the vehicle and starting the vehicle, and wherein analyzing the received sensor data and the identified number of other devices available to be paired with the mobile device further includes analyzing the data indicating the identity of the user performing at least one of: unlocking the vehicle and starting the vehicle including comparing the identity of the user performing one of: unlocking the vehicle and starting the vehicle to the user of the mobile device.

### Claim 13 (depends on 8)

The one or more non-transitory computer-readable media of claim 8, further including instructions that, when executed, cause the computing device to:
receive, from an on-board vehicle computing device, data indicating an operating mode of the vehicle, and wherein analyzing the received sensor data and the identified number of other devices available to be paired with the mobile device further includes analyzing the data indicating the operating mode of the vehicle including determining whether the operating mode is an autonomous operating mode.

### Claim 14 (depends on 8)

The one or more non-transitory computer-readable media of claim 8, further including instructions that, when executed, cause the computing device to:
receive additional data including data from a plurality of sources, and wherein analyzing the received sensor data and the identified number of other devices available to be paired with the mobile device further includes analyzing the additional data including applying a weighting factor to different types of data in the data from the plurality of sources.

### Claim 15

A method, comprising:
by a computing device having at least one processor, a communication interface and a memory storing instructions that, when executed by the at least one processor, cause the processor to:
receiving, from at least an accelerometer associated with a mobile device, by the at least one processor and via the communication interface, sensor data associated with movement of the mobile device during a first time period;
identifying, by the at least one processor, a number of other devices available to be paired with the mobile device;
analyzing, by the at least one processor, the received sensor data and the identified number of other devices available to be paired with the mobile device to determine whether the movement of the mobile device corresponds to a user of the mobile device being a driver of a vehicle during the first time period or the user of the mobile device being a non-driver passenger of the vehicle during the first time period;
if it is determined that the movement of the mobile device corresponds to the user being a driver of the vehicle during the first time period, analyzing, by the at least one processor, the received sensor data to evaluate driving behaviors of the user associated with operation of the vehicle and generating a first output, including a first offer for a product or service, associated with the driving behaviors of the user; and
if it is determined that the movement of the mobile device corresponds to the user being a non-driver passenger of the vehicle during the first time period, generating a second output, including a second offer for a product or service, different from the first output.

### Claim 16 (depends on 15)

The method of claim 15, wherein analyzing the identified number of other devices available to be paired with the mobile device includes comparing the number of other devices to a threshold and, responsive to determining that the number of other devices is greater than the threshold, determining that the user is traveling on public transportation.

### Claim 17 (depends on 15)

The method of claim 15, further including:
receiving, by the at least one processor and from the mobile device, image data including an image of the user,
wherein analyzing the received sensor data further includes analyzing the image data including comparing the received image data to pre-stored image data to determine a position of the user within the vehicle.

### Claim 18 (depends on 15)

The method of claim 15, further including:
receiving, by the at least one processor and from one or more external computing systems, public transportation schedules and routes,
wherein analyzing the received sensor data and the identified number of other devices available to be paired with the mobile device further includes analyzing the public transportation schedules and routes including comparing stoppage points within the received sensor data to public transportation stops identified from the public transportation schedules and routes.

### Claim 19 (depends on 15)

The method of claim 15, further including:
receiving, by the at least one processor and from an on-board vehicle computing device, data indicating an identity of a user performing at least one of: unlocking the vehicle and starting the vehicle, and wherein analyzing the received sensor data and the identified number of other devices available to be paired with the mobile device further includes analyzing the identity of the user performing at least one of: unlocking the vehicle and starting the vehicle including comparing the identity of the user performing one of: unlocking the vehicle and starting the vehicle to the user of the mobile device.

### Claim 20 (depends on 15)

The method of claim 15, further including:
receiving, by the at least one processor and from an on-board vehicle computing device, data indicating an operating mode of the vehicle,
wherein analyzing the received sensor data and the identified number of other devices available to be paired with the mobile device further includes analyzing the data indicating an operating mode of the vehicle including determining whether the operating mode is an autonomous operating mode.