公开(公告)号：US11866055B1

公开(公告)日：2024-01-09

申请号：US17662622

申请日：2022-05-09

Applicant: Samsara Inc.

Inventor： Sharan Srinivasan ,  Brian Tuan ,  John Bicket ,  Jing Wang ,  Muhammad Ali Akhtar ,  Abner Ayala Acevedo ,  Bruce Kellerman ,  Vincent Shieh

IPC: B60W40/09 ,  G06N3/082 ,  G06V40/20 ,  G06N3/045

CPC classification number: B60W40/09 ,  G06N3/045 ,  G06N3/082 ,  G06V40/20 ,  B60W2400/00

Abstract: A vehicle device may execute one or more neural networks (and/or other artificial intelligence), based on input from one or more of the cameras and/or other sensors, to intelligently detect safety events in real-time. The one or more neural networks may be an ensemble neural network that includes neural networks for detecting a head and hand of a user, neural networks for detecting hand actions of the user, neural networks for detecting the head pose of the user, neural networks for predicting an occurrence of an event, and neural networks for predicting a start time and end time of the event. Further, the neural networks can be segmented into a modular neural network based on metadata. The segmentation of the neural network can define a thin layer of the modular neural network to enable independent tuning of the thin layer of the modular neural network.

公开(公告)号：US11780446B1

公开(公告)日：2023-10-10

申请号：US17661689

申请日：2022-05-02

Applicant: Samsara Inc.

Inventor： Sharan Srinivasan ,  Brian Tuan ,  John Bicket ,  Jing Wang ,  Muhammad Ali Akhtar ,  Abner Ayala Acevedo ,  Bruce Kellerman ,  Vincent Shieh

IPC: B60W40/09 ,  G06V20/59 ,  G06T7/73 ,  G06N3/045

CPC classification number: B60W40/09 ,  G06N3/045 ,  G06T7/73 ,  G06V20/597

Abstract: A vehicle device may execute one or more neural networks (and/or other artificial intelligence), such as based on input from one or more of the cameras and/or other sensors associated with the dash cam, to intelligently detect safety events in real-time. The vehicle device may further pass the input to a backend server for further analysis and the backend server can detect safety events based on the input. The vehicle device may analyze the output of the vehicle device and the output of the backend server to determine whether the output of the vehicle device is correct. If the output of the vehicle device is incorrect, the vehicle device can adjust how the vehicle device identifies safety events.

公开(公告)号：US11756351B1

公开(公告)日：2023-09-12

申请号：US17412194

申请日：2021-08-25

Applicant: Samsara Inc.

Inventor： Muhammad Ali Akhtar ,  Jennifer Julia Zhang ,  Alvin Wu ,  Benjamin Chang ,  Joanne Wang ,  Katherine Yeonjune Lee

IPC: G07C5/08 ,  G07C5/12 ,  G08G1/127 ,  G07C5/02 ,  G07C5/00 ,  G08G1/00 ,  G06F18/243 ,  B60W40/09 ,  G08G1/01

CPC classification number: G07C5/0816 ,  G06F18/24323 ,  G07C5/008 ,  G07C5/02 ,  G07C5/0841 ,  G07C5/12 ,  G08G1/127 ,  G08G1/20 ,  B60W40/09 ,  G08G1/0112

Abstract: A system receives vehicle metric data from a gateway device connected to a vehicle. The vehicle gateway device gathers data related to operation of the vehicle and/or location data. The system receives data from multiple vehicles and multiple fleets. The system uses machine learning to identify cohorts for fleets. The system calculates metrics for fleets and benchmarks for the cohorts. The system presents the metrics and benchmarks in a graphical user interface.

公开(公告)号：US11386325B1

公开(公告)日：2022-07-12

申请号：US17454799

申请日：2021-11-12

Applicant: Samsara Inc.

Inventor： Sharan Srinivasan ,  Brian Tuan ,  John Bicket ,  Jing Wang ,  Muhammad Ali Akhtar ,  Abner Ayala Acevedo ,  Bruce Kellerman ,  Vincent Shieh

IPC: G06N3/08 ,  G06N7/00 ,  B60W40/09 ,  B60W50/14 ,  G06N20/20

Abstract: A vehicle device may execute one or more neural networks (and/or other artificial intelligence), based on input from one or more of the cameras and/or other sensors, to intelligently detect safety events in real-time. The one or more neural networks may be an ensemble neural network that includes neural networks for detecting a head and hand of a user, neural networks for detecting hand actions of the user, neural networks for detecting the head pose of the user, neural networks for predicting an occurrence of an event, and neural networks for predicting a start time and end time of the event. Further, the neural networks can be segmented into a modular neural network based on metadata. The segmentation of the neural network can define a thin layer of the modular neural network to enable independent tuning of the thin layer of the modular neural network.

公开(公告)号：US20250002033A1

公开(公告)日：2025-01-02

申请号：US18883478

申请日：2024-09-12

Applicant: Samsara Inc.

Inventor： Mathew Chasan Calmer ,  Justin Delegard ,  Justin Pan ,  Sabrina Shemet ,  Meelap Shah ,  Kavya Joshi ,  Brian Tuan ,  Sharan Srinivasan ,  Muhammad Ali Akhtar ,  John Charles Bicket ,  Margaret Finch ,  Vincent Shieh ,  Bruce Kellerman ,  Mitch Lin ,  Marvin Arroz ,  Siddhartha Datta Roy ,  Jason Symons ,  Tina Quach ,  Cassandra Lee Rommel ,  Saumya Jain

IPC: B60W50/14 ,  B60W40/08 ,  G06F3/01 ,  G06N3/02 ,  G06T7/70 ,  G06V10/44 ,  G06V10/74 ,  G06V20/40 ,  G06V20/56 ,  G06V20/59 ,  G07C5/00 ,  G07C5/08 ,  H04N19/132 ,  H04N23/51

Abstract: A vehicle dash cam may be configured to execute one or more neural networks (and/or other artificial intelligence), such as based on input from one or more of the cameras and/or other sensors associated with the dash cam, to intelligently detect safety events in real-time. Detection of a safety event may trigger an in-cab alert to make the driver aware of the safety risk. The dash cam may include logic for determining which asset data to transmit to a backend server in response to detection of a safety event, as well as which asset data to transmit to the backend server in response to analysis of sensor data that did not trigger a safety event. The asset data transmitted to the backend server may be further analyzed to determine if further alerts should be provided to the driver and/or to a safety manager.

公开(公告)号：US12172653B1

公开(公告)日：2024-12-24

申请号：US18357713

申请日：2023-07-24

Applicant: Samsara Inc.

Inventor： Muhammad Ali Akhtar ,  Jennifer Julia Zhang ,  Alvin Wu ,  Benjamin Chang ,  Joanne Wang ,  Katherine Yeonjune Lee

IPC: B60W40/09 ,  G06F18/243 ,  G07C5/02 ,  G07C5/08 ,  G07C5/12 ,  G08G1/00 ,  G08G1/01 ,  G08G1/127

Abstract: A system receives vehicle metric data from a gateway device connected to a vehicle. The vehicle gateway device gathers data related to operation of the vehicle and/or location data. The system receives data from multiple vehicles and multiple fleets. The system uses machine learning to identify cohorts for fleets. The system calculates metrics for fleets and benchmarks for the cohorts. The system presents the metrics and benchmarks in a graphical user interface.

公开(公告)号：US12140445B1

公开(公告)日：2024-11-12

申请号：US17807361

申请日：2022-06-16

Applicant: Samsara Inc.

Inventor： Muhammad Ali Akhtar ,  Jennifer Julia Zhang ,  Alvin Wu ,  Benjamin Chang ,  Joanne Wang ,  Katherine Yeonjune Lee

IPC: G01C21/36 ,  G01C21/00 ,  G01C21/34

Abstract: A system receives vehicle metric data from a gateway device connected to a vehicle. The vehicle gateway device gathers data related to operation of the vehicle and/or location data. The system receives data from multiple vehicles. The vehicle gateway device gathers vehicle metric data and correlates the metric data with location data. The system presents the correlated data in an interactive map graphical user interface.

公开(公告)号：US12118831B1

公开(公告)日：2024-10-15

申请号：US18346516

申请日：2023-07-03

Applicant: Samsara Inc.

Inventor： Alvin Wu ,  Muhammad Ali Akhtar ,  Nishant Raman ,  Jevon Yeoh ,  Saranyu Phusit ,  Joanne Wang ,  Benjamin Chang ,  Katherine Lee ,  Jennifer Julia Zhang

IPC: G07C5/00 ,  G06F16/9038 ,  G07C5/08

CPC classification number: G07C5/008 ,  G06F16/9038 ,  G07C5/0816 ,  G07C5/085

Abstract: An analytics reporting system to perform operations that include: aggregating sensor data collected from a plurality of sensor devices within a database, the sensor data comprising a set of values that correspond with a metric; generating a threshold value based on the set of values that correspond with the metric; accessing a portion of the sensor data based on an identifier associated with the portion of the sensor data; determining the portion of the sensor data transgresses the threshold value; and generating a report that comprises a display of the portion of the sensor data based on the determining that the portion of the sensor data transgresses the threshold value.

公开(公告)号：US20230219592A1

公开(公告)日：2023-07-13

申请号：US18188173

申请日：2023-03-22

Applicant: Samsara Inc.

Inventor： Mathew Chasan Calmer ,  Justin Delegard ,  Justin Pan ,  Sabrina Shemet ,  Meelap Shah ,  Kavya Joshi ,  Brian Tuan ,  Sharan Srinivasan ,  Muhammad Ali Akhtar ,  John Charles Bicket ,  Margaret Finch ,  Vincent Shieh ,  Bruce Kellerman ,  Mitch Lin ,  Marvin Arroz ,  Siddhartha Datta Roy ,  Jason Symons ,  Tina Quach ,  Cassandra Lee Rommel ,  Saumya Jain

IPC: G06V20/56 ,  G06V20/40 ,  G06V20/59 ,  G06T7/70 ,  G06V10/44 ,  G06V10/74

CPC classification number: G06V20/56 ,  G06V20/44 ,  G06V20/597 ,  G06T7/70 ,  G06V10/44 ,  G06V10/761 ,  G06V2201/07

Abstract: A vehicle dash cam may be configured to execute one or more neural networks (and/or other artificial intelligence), such as based on input from one or more of the cameras and/or other sensors associated with the dash cam, to intelligently detect safety events in real-time. Detection of a safety event may trigger an in-cab alert to make the driver aware of the safety risk. The dash cam may include logic for determining which asset data to transmit to a backend server in response to detection of a safety event, as well as which asset data to transmit to the backend server in response to analysis of sensor data that did not trigger a safety event. The asset data transmitted to the backend server may be further analyzed to determine if further alerts should be provided to the driver and/or to a safety manager.

公开(公告)号：US11669714B1

公开(公告)日：2023-06-06

申请号：US17410295

申请日：2021-08-24

Applicant: Samsara Inc.

Inventor： Muhammad Ali Akhtar ,  Abhishyant Khare ,  Brian Tuan ,  John Charles Bicket

IPC: G06N3/02 ,  G06F16/29 ,  G06N7/01

CPC classification number: G06N3/02 ,  G06F16/29 ,  G06N7/01

Abstract: An improved system and method of determining presence of stop signs at intersection based on multiple types of data including ground truth data, telemetry data, and/or trip stills gathered from vehicle devices. The data may be analyzed and aggregated by one or more models and/or neural networks to develop a prediction regarding presence of stop signs at individual intersections.