VEHICLE BACKUP CAMERA DATA FOR RISK DETECTION AND COLLISION ANALYSIS

    公开(公告)号:US20250111705A1

    公开(公告)日:2025-04-03

    申请号:US18827418

    申请日:2024-09-06

    Inventor: Brian N. Harvey

    Abstract: A vehicle-based system may store and analyze image data captured by backup cameras, rear-facing, and/or side-facing cameras on a vehicle, to detect high-risk driving scenarios and/or for use in post-collision analyses. The rear-facing or side-view image data may be analyzed on-vehicle while driving, and/or may be transmitted from the vehicle to a remote server for analysis. The backup image data may be analyzed individually or in conjunction with other vehicle sensor data, telematics data, environment data, and the like. In some cases, a vehicle-based system may detect an on-board event, such as a collision, high-risk scenario, or other vehicle damage, and may transmit the image data to a remote server in response to detecting the event. Additionally or alternatively, the vehicle-based system may analyze the image data on-board the vehicle to detect high-risk driving scenarios, and to determine vehicle control commands to avoid or mitigate the high-risk scenarios.

    EXHAUST FAN ASSEMBLY SYSTEM AND METHOD FOR EXHAUSTING A GAS

    公开(公告)号:US20240302068A1

    公开(公告)日:2024-09-12

    申请号:US18509049

    申请日:2023-11-14

    Inventor: Brian N. Harvey

    Abstract: A gas mitigation system includes a duct defining a channel extending between an inlet positioned in flow communication with a ground pit positioned at least partially beneath the building, and an outlet positioned above the inlet and outside of the building. The system further includes a fan assembly having a fan coupled in flow communication with the channel and a motor operably coupled to the fan. A sensor is configured to detect an operating parameter of the fan assembly including at least one of the flow of air within the channel and vibrations generated by operation of the fan assembly. A processor is in communication with the sensor and a memory storing instructions thereon, which, when executed by the processor, may cause the processor to receive the operating parameter detected by the sensor and transmit an alert based upon the operating parameter.

    Systems and methods for maintaining a self-driving vehicle

    公开(公告)号:US12008843B2

    公开(公告)日:2024-06-11

    申请号:US18160120

    申请日:2023-01-26

    CPC classification number: G07C5/008 B60R16/0234 G06Q10/20 G06Q40/08 G07C5/0841

    Abstract: A computer-based method for maintaining an autonomous or self-driving vehicle is provided. The method is implemented using a vehicle controlling (“VC”) computer device installed on the vehicle. The method may include determining that a maintenance operation is required for the self-driving vehicle, retrieving an operator schedule for an operator of the self-driving vehicle, retrieving a facility schedule for a facility, determining a time for performing the maintenance operation based upon the operator schedule, the facility schedule, and an amount of time required to (i) complete the maintenance operation, (ii) drive the self-driving vehicle from a first location to the facility to arrive at the determined time, and (iii) drive the self-driving vehicle to a second location, instructing the self-driving vehicle to drive from the first location to the facility to arrive at the determined time; and/or instructing the self-driving vehicle to drive from the facility a second location.

    Systems and Methods for Detecting and Preventing Damage to Pipes

    公开(公告)号:US20240142330A1

    公开(公告)日:2024-05-02

    申请号:US18095675

    申请日:2023-01-11

    CPC classification number: G01M3/007 G01M3/243

    Abstract: Systems and methods are described for detecting a leak based upon home telematics data. The method may include: (1) receiving home telematics data from one or more sensors associated with one or more pipes (or piping systems) in a structure, wherein the home telematics data is indicative of the frequency with which the one or more pipes are being used; (2) determining, using a trained machine learning algorithm, pipe activity associated with the one or more pipes is occurring at an irregular frequency; (3) determining, based upon at least the determination that the pipe activity associated with the one or more pipes is occurring at the irregular frequency, that the one or more pipes are leaking; and (4) transmitting an indication to a user associated with the home that the one or more pipes are leaking.

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