State Farm Mutual Automobile Insurance Company

Lynn Splittstoesser

Kenneth Jason Sanchez

Aaron Scott Chan

John Adrian Nepomuceno

Mohamed A Wazeer

Jeremy Shawn Fogg

Sanjay Jayaswal

Systems and methods for improving vehicular safety are disclosed. According to embodiments, an electronic device may collect or accumulate various sensor data associated with operation of a vehicle by an individual, including image data, telematics data, and/or data indicative of a condition of the individual. The electronic device may analyze the sensor data to determine whether the individual is distracted and whether the vehicle is approaching a location that may be prone to incidents. The electronic device may accordingly generate and present a notification to the individual to mitigate any posed risks.

Technology for notifying vehicle operators of incident-prone locations

A damage assessment (DA) computing device for determining building damage may be provided. The DA computing device may train a machine learning damage model using historical damage data, identify a plurality of buildings that are susceptible to potential damage from an upcoming weather event, the plurality of buildings including the building, input data associated with a roof of the building to the trained damage model, receive a model output from the trained damage model, the model output including a damage status of the roof representing the predicted extent of damage to the roof, when the predicted extent of damage to the roof exceeds a threshold, automatically generate a claim initiation message including a link that, upon selection thereof, causes initiation an insurance claim for the roof based upon the model output and the parameters associated with the building, and/or transmit the claim initiation message to a user.

Systems and methods for determining building damage

A damage assessment (DA) computing device for determining building damage may be provided. The DA computing device may retrieve historical damage data associated with roof damage from a historical damage database, generate a damage model based upon the retrieved historical damage data, identify an building for a roof damage assessment, retrieve damage data associated with the building, compare the damage data associated with the roof to the damage model, and/or determine a damage status of the roof based upon the comparison.

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Bloomington, IL, United States of America

Lynn Splittstoesser