IP Library › Granted Patent US 11,530,925
Granted Patent B1
US 11,530,925 · App. 16/713,777 · Granted Dec 20, 2022

Multi-computer system for dynamically detecting and identifying hazards

Inventors: David Evan Shields (Evanston, IL); David Lambert (La Grange, IL); Kyle Patrick Schmitt (Chicago, IL); Pratheek M. Harish (Ontario, CA)
Assignee: Allstate Insurance Company
G01C21/3415G06N5/04G06N20/00G08G1/0112G08G1/0967
View Patent ↗
Loading inventors, assignments & file history…
Monitor This Case
Get email alerts when status or documents change.
Order Certified Copies
Most orders are placed with the USPTO same day — all within 24 business hours.
Order via The Patent Place →
Pre-filled with this patent's details
Quick Facts
Patent No.
US 11,530,925
App. No.
16/713,777
Granted
Dec 20, 2022
Kind
B1
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.

Claims (47)

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:

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.

2. The computing platform of claim 1 , further including:

receiving data associated with a plurality of users, the received data including driving behavior data for each user of the plurality of users; and

grouping users of the plurality of users into identifiable groups of users based on the received data.

3. The computing platform of claim 1 , wherein the at least one irregularity includes at least one of: a pot hole and an obstruction in the road.

4. The computing platform of claim 1 , wherein the driving behaviors of the driver include at least one of: swerving, hard braking, lane deviations or sudden speed changes.

5. The computing platform of claim 1 , wherein the at least one irregularity in the road is identified by analyzing the received data using machine learning.

6. The computing platform of claim 1 , wherein the generated notification is personalized for the identified at least one group of users.

7. The computing platform of claim 1 , wherein the common vehicle type relates to a profession associated with users in the one or more groups of users.

8. The computing platform of claim 1 , wherein the generated notification is personalized for the at least one group of users by including a notification of an upcoming traffic stoppage.

9. 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.

10. The computing platform of claim 9 , wherein the plurality of sources includes a plurality of other vehicles at or near a location of the vehicle.

11. The computing platform of claim 9 , wherein the driving behaviors of the driver include at least one of: swerving, hard braking, lane deviations or sudden speed changes.

12. The computing platform of claim 11 , wherein the data related to the driving behaviors of the driver includes data captured by one or more sensors configured to detect movement of the vehicle.

13. The computing platform of claim 12 , wherein the one or more sensors are arranged in a mobile device of the driver and wherein the one or more sensors detect movement of the mobile device and translate the movement to identified irregularities.

14. The computing platform of claim 9 , wherein the generated notification is personalized for the identified at least one group of users.

15. The computing platform of claim 9 , wherein the alternate route is customized for the at least one group of users.

16. 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.

17. The method of claim 16 , further including transmitting the generated notification from the vehicle to the plurality of vehicles.

18. The method of claim 16 , wherein the generated notification is personalized for the identified at least one group of users.

19. The method of claim 16 , wherein the plurality of sensors is arranged in a mobile device of the driver.

20. The method of claim 16 , wherein the common vehicle type includes at least one of a first responder vehicle, a bus, or a fleet vehicle.

Assignments (1)
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Nov 7, 2022
From: SHIELDS, DAVID EVAN; LAMBERT, DAVID; SCHMITT, KYLE PATRICK; HARISH, PRATHEEK M.
To: ALLSTATE INSURANCE COMPANY
Reel/Frame 061675/0980 →
Continuity (1)
Provisional Application 62783485 · Dec 21, 2018
Cited By (3)
US 12,505,734 US 12,669,630 US 12,680,817