Method for smartphone-based accident detection

US11375338B2 · US · B2

Patent metadata
FieldValue
Publication numberUS-11375338-B2
Application numberUS-202017071905-A
CountryUS
Kind codeB2
Filing dateOct 15, 2020
Priority dateAug 20, 2015
Publication dateJun 28, 2022
Grant dateJun 28, 2022

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  1. Title

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  2. Abstract

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  4. Key dates

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  5. First independent claim

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Abstract

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A method and system for detecting an accident of a vehicle, the method including: receiving a movement dataset collected at least at one of a location sensor and a motion sensor arranged within the vehicle, during a time period of movement of the vehicle, extracting a set of movement features associated with at least one of a position, a velocity, and an acceleration characterizing the movement of the vehicle during the time period, detecting a vehicular accident event from processing the set of movement features with an accident detection model, and in response to detecting the vehicular accident event, automatically initiating an accident response action.

First claim

Opening claim text (preview).

We claim: 1. A system for determining a vehicular accident associated with first user and a vehicle, the system comprising: a first application executing on a first device associated with the first user, wherein the first application is operable to collect a first movement dataset sampled from at least one of a first motion sensor and a first location sensor of the first device; and wherein the first application is operable to collect a first and second pressure dataset sampled from a first pressure sensor of the first device; and an accident detection processing system operable to: at a first time, determine a pressure threshold condition based on the first pressure dataset; at a second time, extract a pressure level from the second pressure dataset, wherein the second time is different from the first time; retrieve an accident detection model; and in response to the pressure level satisfying the threshold pressure condition at the second time, execute an accident detection routine, the accident detection routine operable to determine a vehicular accident event in substantially real-time with the accident detection model using the first movement dataset. 2. The system of claim 1 , wherein the accident detection processing system is operable to: extract a vehicle motion characteristic from the first movement dataset, wherein the vehicle motion characteristic describes movement of the vehicle; and detect satisfaction of a threshold condition based on the vehicle motion characteristic and the first pressure dataset. 3. The system of claim 2 , wherein retrieval of the accident detection model occurs in response to detection of the satisfaction of the threshold condition. 4. The system of claim 1 , further comprising: a set of supplementary applications executing on a set of supplementary devices associated with a plurality of users and a plurality of vehicles, wherein the set of supplementary applications is operable to collect a set of supplementary pressure datasets sampled at sensors of the set of supplementary devices during driving sessions associated with the plurality of vehicles, wherein the accident detection model comprises an accident detection machine learning model, and wherein the accident detection processing system is operable to: train the accident detection machine learning model based on the set of supplementary pressure datasets; and determine the vehicular accident event with the accident detection machine learning model, the first pressure dataset, and the first movement dataset. 5. The system of claim 1 , wherein the accident detection processing system is operable to, in response to determination of the vehicular accident event, initiate an accident response action associated with the vehicular accident. 6. The system of claim 5 , further comprising: a second application executing on a second device associated with a second user, wherein the accident response action comprises transmission of an accident-related communication to the second device through the second application. 7. The system of claim 6 , wherein the second user is associated with an emergency service, and wherein the accident-related communication comprises location data indicating an accident location of the vehicular accident. 8. The system of claim 1 , wherein the mobile computing device comprises a microphone, wherein the first application is operable to collect an acoustic dataset sampled at the microphone and comprising pressure waves emitted by the vehicle during a time period associated with the first movement dataset, and wherein the accident detection processing system is operable to determine the vehicular accident event with the accident detection model, the acoustic dataset, and the first movement dataset.

Assignees

Inventors

Classifications

  • Probabilistic graphical models, e.g. probabilistic networks · CPC title

  • related to vehicle motion · CPC title

  • Personal emergency signalling and security systems (emergency non-personal manually actuated alarm activators G08B25/12) · CPC title

  • Insurance · CPC title

  • for creating historical data or processing based on historical data · CPC title

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What does patent US11375338B2 cover?
A method and system for detecting an accident of a vehicle, the method including: receiving a movement dataset collected at least at one of a location sensor and a motion sensor arranged within the vehicle, during a time period of movement of the vehicle, extracting a set of movement features associated with at least one of a position, a velocity, and an acceleration characterizing the movement…
Who is the assignee on this patent?
Zendrive Inc
What technology area does this patent fall under?
Primary CPC classification H04W4/027. Mapped technology areas include Electricity.
When was this patent published?
Publication date Tue Jun 28 2022 00:00:00 GMT+0000 (Coordinated Universal Time) (B2). Legal status and post-grant events are not shown on this page.
What related patents are in patentsdb?
We list 12 related publications on this page (citations in our corpus or others sharing the same primary CPC).