TECHNOLOGY FOR ANALYZING SENSOR DATA TO DETECT CONFIGURATIONS OF VEHICLE OPERATION

    公开(公告)号:US20210334660A1

    公开(公告)日:2021-10-28

    申请号:US17371721

    申请日:2021-07-09

    申请人: BlueOwl, LLC

    IPC分类号: G06N3/08 G07C5/00 G07C5/08

    摘要: Systems and methods for using collecting and analyzing device sensor data to determine whether an individual is an operator or a passenger of a vehicle are disclosed. According to certain aspects, an electronic device associated with the individual may collect or access sensor data that is indicative of or associated with an operation of the vehicle. The electronic device may transmit pertinent portion(s) of the sensor data to a backend server, which may input the portion(s) into a neural network for analysis. The neural network may output a probability metric(s) indicative of whether the individual is a passenger or an operator of the vehicle.

    Technology for analyzing sensor data to detect configurations of vehicle operation

    公开(公告)号:US11087209B1

    公开(公告)日:2021-08-10

    申请号:US15656883

    申请日:2017-07-21

    申请人: BLUEOWL, LLC

    IPC分类号: G06N3/08 G07C5/00 G07C5/08

    摘要: Systems and methods for using collecting and analyzing device sensor data to determine whether an individual is an operator or a passenger of a vehicle are disclosed. According to certain aspects, an electronic device associated with the individual may collect or access sensor data that is indicative of or associated with an operation of the vehicle. The electronic device may transmit pertinent portion(s) of the sensor data to a backend server, which may input the portion(s) into a neural network for analysis. The neural network may output a probability metric(s) indicative of whether the individual is a passenger or an operator of the vehicle.

    Audio assessment for analyzing sleep trends using machine learning techniques

    公开(公告)号:US10542930B1

    公开(公告)日:2020-01-28

    申请号:US15659256

    申请日:2017-07-25

    申请人: BlueOwl, LLC

    摘要: A computer system for assessing sound to analyze a user's sleep includes a processor configured to perform operations including: (i) storing sample sound data associated with a plurality of sample sleep events, the sample sound data including a plurality of sample characteristics each respectively associated with at least one sample sleep event of the plurality of sample sleep events; (ii) receiving, from a client device, subject sound data collected during a sleep interval; (iii) analyzing, using a machine learning algorithm, the subject sound data collected during the sleep interval; (iv) identifying, based upon the analyzing, a subject characteristic associated with the subject sound data; (v) comparing the subject characteristic with the plurality of sample characteristics; and (vi) determining, based upon the comparing, whether the subject characteristic substantially matches at least one sample characteristic to identify one or more subject sleep events occurring during the sleep interval.

    SYSTEMS AND METHODS FOR DETECTING FULL-STOPS TO REDUCE VEHICLE ACCIDENTS

    公开(公告)号:US20220237956A1

    公开(公告)日:2022-07-28

    申请号:US17680667

    申请日:2022-02-25

    申请人: BlueOwl, LLC

    发明人: Vinay Kumar

    摘要: A telematics analysis (TA) computing device including a processor in communication with a memory device for monitoring driving behavior of a driver of a vehicle may be provided. The processor may be configured to: (i) aggregate historical location data and historical telematics data from a plurality of users, (ii) generate mapping data based at least in part upon the historical location data and the historical telematics data, (iii) identify one or more stop locations based at least in part upon the mapping data, (iv) store the one or more stop locations, (v) receive current location data and current telematics data after each trip taken by the driver, (vi) compare the current location data and the current telematics data to the one or more stop locations, (vii) generate stop data associated with the driver for each trip taken by the driver, wherein the stop data includes whether the driver stopped at the one or more stop locations during each trip, and (viii) determine one or more driving behaviors of the driver based at least in part upon the stop data.