Allstate Insurance Company

Arity International Limited

Howard Hayes

Surender Kumar

Sunil Kumar Chintakindi

Timothy W Gibson

Regina Madigan

John Rugel

Mark V Slusar

Veljko Krunic

Daniel Kraft

Jenny Sankovsky

Brian Stricker

Matthew Olenak

Soton Ayodele Rosanwo

John S Parkinson

Jason D Park

Tim Gibson

Avani Patel

Araba Appiagyei-Dankah

Robert H Johnson

Tao Chen

Moises Norena

Aleksandr Likhterman

Santhosh Thammi

Dana Ferguson

Grady Irey

Caleb Johnson

Srinivas Nainala

Philip Peter Ramirez

Matei Stroila

Anuradha Kodali

John Bradley Moats

Jorge Caraballo Falcon

David Border

Ashley Greenwell

Juan Ortiz-Zabala

Methods, computer-readable media, software, and apparatuses may monitor consumer information in order to determine a probability of a data breach associated with a customer based on an online presence of the customer. The probability of a data breach may be used to present metrics to a consumer and/or a service provider. Further, the consumer may be presented with information indicating what factors contribute to the probability of a data breach, as well as information regarding how to reduce those factors.

Cyber-security presence monitoring and assessment

Systems and methods are disclosed for monitoring or affecting movement of a vehicle using a traffic device. An event data source may have a processor and/or a transceiver. The event data source may transmit, via the transceiver and to a vehicle and infrastructure computing device, information indicative of an event affecting a portion of road. The vehicle and infrastructure computing device may comprise a vehicle and infrastructure control computer. The vehicle and infrastructure computing device may receive, from the event data source, the information indicative of the event affecting the portion of road. The computing device may determine one or more traffic devices associated with the portion of road and configured to control traffic for the portion of road. Based on the information indicative of the event affecting the portion of road, the computing device may send, to the one or more traffic devices associated with the portion of road, instructions to change one or more characteristics of the one or more traffic devices.

Electrical data processing system for monitoring or affecting movement of a vehicle using a traffic device

Aspects of the disclosure relate to computing platforms that utilize improved mitigation analysis and policy management techniques to improve onboarding security. A computing platform may initiate an onboarding process with a mobile device. The computing platform may receive one or more onboarding verification inputs indicative of a user identity. The computing platform may send commands directing a mitigation analysis and output generation platform to analyze the onboarding verification inputs. The computing platform may receive a mitigation output indicating a degree of correlation between the one or more received onboarding verification inputs and expected onboarding verification inputs. In response to determining that the mitigation output exceeds a predetermined mitigation threshold, the computing platform may send mitigation interface information and one or more commands directing the mobile device to display an onboarding mitigation interface that prompts for one or more additional onboarding verification inputs indicative of the user identity.

Onboarding platform for performing dynamic mitigation analysis

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.

Multi-computer processing system for dynamically executing response actions based on movement data

Aspects of the present disclosure describe systems, methods, and devices for automated vehicular control based on glare detected by an optical system of a vehicle. In some aspects, automated control includes controlling the operation of the vehicle itself, a vehicle subsystem, or a vehicle component based on a level of glare detected. According to some examples, controlling the operation of a vehicle includes instructing an automatically or manually operated vehicle to traverse a selected route based on levels of glare detected or expected along potentials routes to a destination. According to other examples, controlling operation of a vehicle subsystem or a vehicle component includes triggering automated responses by the subsystem or the component based on a level of glare detected or expected. In some additional aspects, glare data is shared between individual vehicles and with a remote data processing system for further analysis and action.

Glare detection systems and methods for automated vehicular control

Methods, computer-readable media, systems and apparatuses for determining a blind corner navigational score based on real-time or near real-time navigational analysis using sensor data, digital image data, and a map database are discussed. In some arrangements, detection of a blind sensor may be performing using sensor data, digital image data, and navigational data from a map database system. In at least some arrangements, a warning signal or a vehicle control signal may be transmitted to a vehicle in response to a determination that the blind corner navigational score is above a threshold. In at least some arrangements, route correction and/or route modification based on an upcoming blind corner may be performed if a blind corner navigational score is above a threshold.

Automated vehicle control and guidance based on real-time blind corner navigational analysis

A system may be configured to detect an emergency condition at a premises; dispatch one or more autonomous drones to a location associated with the emergency condition; receive from the one or more autonomous drones, sensor data associated with the emergency condition; generate, based on the sensor data, a plan identifying an evacuation route for safely evacuating the premises; and transmit an instruction that causes the one or more autonomous drones to indicate, to one or more persons in a vicinity of the emergency condition, the evacuation route. The system may further detect, based on the sensor data, one or more safe areas in the premises, and the evacuation route may pass through at least one of the one or more safe areas.

Emergency incident detection, response, and mitigation using autonomous drones

A system including a processor and memory may provide for automatically activating or deactivating a feature of a fleet vehicle. For example, one or more fleet vehicles may include one or more of a global-positioning system, a speed governor, electronically-controlled brakes, an electronically-controlled accelerator, a speed limiter, or an on-board computer with a processor and memory. One or more features may be activated by a local or remote computing device or system. For example, a system may determine one or more recommended routes between two or more locations. The system may track a fleet vehicle's progress along a route, and activate a feature of the fleet vehicle based on the fleet vehicle following or not following the recommended route. For example, the system may cause activation of a speed limiter on the fleet vehicle, disable the fleet vehicle, and/or activate or deactivate autonomous features of the fleet vehicle.

Fleet vehicle feature activation

Computing systems for vehicle diagnostics are provided. In accordance with some aspects, a computing system may receive, from a vehicle (e.g., from a computing device installed in and/or at the vehicle), a diagnostic code generated by an on-board diagnostic (OBD) system of the vehicle. The computing system may determine an issue with the vehicle based on the diagnostic code and may determine, based on the issue, a remedial action for addressing the issue and a timeframe for performing the remedial action. The computing system may store data identifying the issue, the remedial action, and the timeframe in a record associated with the vehicle.

Vehicle diagnostics

Systems and apparatuses for receiving data from a plurality of sensors and using the data, as well as other data, to generate a parking recommendation for an autonomous vehicle and instruct the autonomous vehicle to travel to the recommended parking location are provided. Data may be received from a plurality of sensors within a first autonomous vehicle, as well as from other vehicles and/or structures. Historical parking data associated with the first autonomous vehicle may also be extracted. In some examples, an expected future trip of the first autonomous vehicle may be determined. The system may then evaluate the data to generate a parking recommendation for the first autonomous vehicle. The system may generate and transmit instructions for traveling from a current location to the recommended parking location and may cause the first autonomous vehicle to travel to the recommended parking location.

Generating and transmitting parking instructions for autonomous and non- autonomous vehicles

Aspects of the disclosure relate to computing platforms that utilize improved mitigation analysis and policy management techniques to improve onboarding security. A computing platform may determine that a predetermined period of time has elapsed since finalizing an onboarding process. The computing platform may receive spot check verification inputs indicative of a user identity and may direct a mitigation analysis and output generation platform to analyze the spot check verification inputs. The computing platform may receive an indication of a correlation between the spot check verification inputs and expected spot check verification inputs. In response to determining that the correlation exceeds a predetermined threshold, the computing platform may determine that an additional verification test should be conducted, and may direct the mobile device to display an interface that prompts for additional onboarding verification inputs.

Methods, computer-readable media, systems, and/or apparatuses are provided for providing offer and insight generation functions. User input requesting an offer or insight may be received and an image of a photographic identification of a user may be requested. The image of the photographic identification may be captured and stored. A self-captured image of the user may be captured (e.g., via an image capture device of the computing device) and compared to an image of a user from the photographic identification. Responsive to determining that the images match, displaying an instruction to capture a vehicle identification number. The vehicle identification number may be captured. Data, including location data, may be extracted and an archive including the extracted data may be generated and the data may be transmitted to an entity computing system for processing. The entity computing system may evaluate the data and generate one or more insights and/or outputs.

Data processing system with machine learning engine to provide output generation functions

Methods, apparatuses, systems, and computer-readable media for identifying and executing one or more interactive condition evaluation tests and collecting and analyzing user behavior data to generate an output are provided. In some examples, user information may be received and one or more interactive condition evaluation tests may be identified. An instruction may be transmitted to a computing device of a user and executed on the computing device to enable functionality of one or more sensors that may be used in the identified tests. Upon initiating a test, data may be collected from the one or more sensors. The collected sensor data may be transmitted to the system and processed using one or more machine learning datasets. Additionally, user behavior data may be collected and processed using one or more machine learning datasets. The sensor data, the user behavior data, and other data may be used together to generate an output.

Data processing system with machine learning engine to provide output generating functions

Systems, methods, computer-readable media, and apparatuses for identifying and executing one or more interactive condition evaluation tests to generate an output are provided. In some examples, user information may be received by a system and one or more interactive condition evaluation tests may be identified. An instruction may be transmitted to a computing device of a user and executed on the computing device to enable functionality of one or more sensors that may be used in the identified tests. A user interface may be generated including instructions for executing the identified tests. Upon initiating a test, data may be collected from one or more sensors in the computing device. The data collected may be transmitted to the system and may be processed using one or more machine learning datasets to generate an output.

Aspects of the disclosure relate to a system and method for cryptographically transmitting and storing identity tokens and/or activity data among spatially distributed computing devices. The system may comprise a plurality of chains, such as an identity chain and an activity chain. In some aspects, identity data associated with a user may be used to generate an identity token for the user. The identity token may be transmitted to a plurality of computing devices for verification. Based on a verification of the identity token, the identity token may be stored in the identity chain. A request to perform an activity may also be received, and identity data associated with the user may be received in order to authenticate the user. The computing device may generate, based on the received identity data, an identity token for the user.

Growing community of inventors

Glencoe, IL, United States of America

Howard Hayes