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US 11,530,925 B1Granted
Multi-computer system for dynamically detecting and identifying hazards
AssigneeAllstate Insurance Company
InventorsDavid Evan Shields, David Lambert, Kyle Patrick Schmitt, Pratheek M. Harish
Life of this patent
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Abstract
Systems, methods, computer-readable media, and apparatuses for providing hazard detection and broadcast functions are provided. In some examples, sensor data may be captured by a mobile device, vehicle, or the like. The data may be used to detect a hazard, identify a type of hazard, and the like. One or more users or groups of users for notification of the hazard may be identified and one or more notifications may be transmitted to users within the group.
Claims20
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:
- identify, based on received data generated by one or more sensors associated with a vehicle and representing driving behaviors of a driver of the vehicle, at least one irregularity in a road on which the vehicle is travelling;
- receive, from a plurality of sources, additional data;
- generate one or more groups of users based on a common vehicle type identified from the additional data;
- identify, based on the at least one irregularity, at least one group of users of the one or more groups of users;
- generate a notification identifying the at least one irregularity;
- and
- transmit, using one or more wireless network connections, the generated notification to the identified at least one group of users.
7 more elements
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:
- identify, based on machine learning analysis of received data related to driving behaviors of a driver of a vehicle, at least one irregularity in a road on which the vehicle is travelling;
- receive, from a plurality of sources, additional data;
- generate one or more groups of users based on a type of vehicle identified from the additional data;
- identify, based on the at least one irregularity and the additional data and using machine learning, at least one group of users of the one or more groups of users having driving behaviors similar to the driving behaviors of the driver of the vehicle;
- generate a notification identifying the at least one irregularity and identifying an alternate route to avoid the identified at least one irregularity;
- and
- transmit, using one or more wireless network connections, the generated notification to the identified at least one group of users.
7 more elements
A method, comprising:
- receiving, by a computing device having a processor and memory, sensor data from a plurality of sensors detecting movement of a vehicle;
- analyzing, by the processor, the received sensor data to identify one or more driving behaviors of a driver of the vehicle;
- identifying, by the processor and based on machine learning analysis of the analyzed sensor data, at least one irregularity in a road on which the vehicle is travelling;
- receiving, by the processor and from a plurality of sources, additional data;
- generating, by the processor, at least one group of users based on a common vehicle type identified from the additional data;
- identifying, by the processor using machine learning and based on the at least one irregularity and the additional data, a plurality of vehicles within a predefined distance of the vehicle;
- identifying, by the processor, users associated with the plurality of vehicles and in the at least one group of users;
- generating, by the processor, a notification identifying the at least one irregularity;
- and
- transmitting, by the processor and using one or more wireless network connections, the generated notification to the plurality of vehicles within the predefined distance of the vehicle and associated with users in the at least one group of users.
7 more elements
Dependencies are inferred from the claim text.