Patents by Inventor Abner Ayala
Abner Ayala has filed for patents to protect the following inventions. This listing includes patent applications that are pending as well as patents that have already been granted by the United States Patent and Trademark Office (USPTO).
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Patent number: 12266123Abstract: Methods, systems, and computer programs are presented for monitoring tailgating when a vehicle follows another vehicle at an unsafe distance. A method for enhancing a Following Distance (FD) machine learning (ML) model is disclosed. The method includes providing a management user interface (UI) for configuring FD parameters, followed by receiving FD events. A UI for manual FD annotation and another for customer review of filtered FD events are also provided. Annotations and customer review information are collected to improve the training set for the FD ML model. The FD model is then trained with the new data and downloaded to a vehicle. Once installed, the FD model is utilized to detect FD events within the vehicle, thereby enhancing the vehicle's safety and performance in driving scenarios by improving the accuracy and reliability of FD event predictions or detections.Type: GrantFiled: May 23, 2024Date of Patent: April 1, 2025Assignee: Samsara Inc.Inventors: Suryakant Kaushik, Cole Jurden, Marc Clifford, Robert Koenig, Abner Ayala, Kevin Lai, Jose Cazarin, Margaret Irene Finch, Rachel Demerly, Nathan Hurst, Yan Wang, Akshay Raj Dhamija
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Patent number: 12168445Abstract: 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.Type: GrantFiled: August 11, 2023Date of Patent: December 17, 2024Assignee: Samsara Inc.Inventors: Sharan Srinivasan, Brian Tuan, John Bicket, Jing Wang, Muhammad Ali Akhtar, Abner Ayala Acevedo, Bruce Kellerman, Vincent Shieh
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Patent number: 12165393Abstract: Methods, systems, and computer programs are presented for the management of lane-departure (LD) events. One method includes training a classifier for LD events and loading the classifier into a vehicle. LD events are detected based on outward images using the classifier, while the turn signal is monitored to prevent false triggers. If an LD event is detected, rules are checked for alerting the driver and deciding whether to alert the driver or not. Subsequently, additional rules are checked for reporting the event and deciding whether to report the event to a Behavior Monitoring System (BMS) or to discard it. The method also includes a solid line departure model that identifies crossing dashed, solid-white, and solid-yellow lanes, delaying alerts and event generation until a significant portion of the vehicle crosses over the lane. The model also outputs a confidence score reflecting the amount of vehicle deviation from the driving lane.Type: GrantFiled: April 23, 2024Date of Patent: December 10, 2024Assignee: Samsara Inc.Inventors: Akshay Raj Dhamija, Abner Ayala, Rohit Annigeri, Cole Jurden, Douglas Boyle, Jason Liu, Kevin Lai, Jose Cazarin, Pang Wu, Nathan Hurst, Brian Westphal, Lucas Doyle, Saurabh Tripathi, Shirish Nair
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Patent number: 11995546Abstract: 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.Type: GrantFiled: July 8, 2022Date of Patent: May 28, 2024Assignee: Samsara Inc.Inventors: Sharan Srinivasan, Brian Tuan, John Bicket, Jing Wang, Muhammad Ali Akhtar, Abner Ayala Acevedo, Bruce Kellerman, Vincent Shieh
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Patent number: 11866055Abstract: 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.Type: GrantFiled: May 9, 2022Date of Patent: January 9, 2024Assignee: Samsara Inc.Inventors: Sharan Srinivasan, Brian Tuan, John Bicket, Jing Wang, Muhammad Ali Akhtar, Abner Ayala Acevedo, Bruce Kellerman, Vincent Shieh
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Patent number: 11780446Abstract: 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.Type: GrantFiled: May 2, 2022Date of Patent: October 10, 2023Assignee: Samsara Inc.Inventors: Sharan Srinivasan, Brian Tuan, John Bicket, Jing Wang, Muhammad Ali Akhtar, Abner Ayala Acevedo, Bruce Kellerman, Vincent Shieh
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Patent number: 11386325Abstract: 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.Type: GrantFiled: November 12, 2021Date of Patent: July 12, 2022Assignee: Samsara Inc.Inventors: Sharan Srinivasan, Brian Tuan, John Bicket, Jing Wang, Muhammad Ali Akhtar, Abner Ayala Acevedo, Bruce Kellerman, Vincent Shieh
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Patent number: 11352013Abstract: 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.Type: GrantFiled: November 12, 2021Date of Patent: June 7, 2022Assignee: Samsara Inc.Inventors: Sharan Srinivasan, Brian Tuan, John Bicket, Jing Wang, Muhammad Ali Akhtar, Abner Ayala Acevedo, Bruce Kellerman, Vincent Shieh
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Patent number: 11352014Abstract: 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.Type: GrantFiled: November 12, 2021Date of Patent: June 7, 2022Assignee: Samsara Inc.Inventors: Sharan Srinivasan, Brian Tuan, John Bicket, Jing Wang, Muhammad Ali Akhtar, Abner Ayala Acevedo, Bruce Kellerman, Vincent Shieh