Patents by Inventor Alexandru Popovici

Alexandru Popovici 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).

  • Publication number: 20240085185
    Abstract: Embodiments are disclosed for submersion detection and underwater depth and low-latency temperature estimation. In an embodiment, a method comprises: determining a first set of vertical accelerations obtained from an inertial sensor of a wearable device; determining a second set of vertical accelerations obtained from pressure data; determining a first feature associated with a correlation between the first and second sets of vertical accelerations; and determining that the wearable device is submerged or not submerged in water based on a machine learning model applied to the first feature. In another embodiment, a method comprises: determining a submersion state of a wearable device; and responsive to the submersion state being submerged, computing a forward estimate of water temperature based on measured ambient water temperature at the water surface, a temperature error lookup table, and a rate of change of the ambient water temperature.
    Type: Application
    Filed: September 6, 2023
    Publication date: March 14, 2024
    Inventors: Stephen P. Jackson, Ti-Yen Lan, Yi Wen Liao, Alexandru Popovici, Igor Tchertkov, Rose M. Wahlin, Natisa Jeyakanthan, Amit K. Jain, Kenneth M. Lee
  • Publication number: 20240075895
    Abstract: Embodiments are disclosed for crash detection on one or more mobile devices (e.g., smartwatch and/or smartphone). In some embodiments, a method comprises: detecting, with at least one processor, a crash event on a crash device; extracting, with the at least one processor, multimodal features from sensor data generated by multiple sensing modalities of the crash device; computing, with the at least one processor, a plurality of crash decisions based on a plurality of machine learning models applied to the multimodal features; and determining, with the at least one processor, that a severe vehicle crash has occurred involving the crash device based on the plurality of crash decisions and a severity model.
    Type: Application
    Filed: September 6, 2023
    Publication date: March 7, 2024
    Inventors: Vinay R. Majjigi, Sriram Venkateswaran, Aniket Aranake, Tejal Bhamre, Alexandru Popovici, Parisa Dehleh Hossein Zadeh, Yann Jerome Julien Renard, Yi Wen Liao, Stephen P. Jackson, Rebecca L. Clarkson, Henry Choi, Paul D. Bryan, Mrinal Agarwal, Ethan Goolish, Richard G. Liu, Omar Aziz, Alvaro J. Melendez Hasbun, David Ojeda Avellaneda, Sunny Kai Pang Chow, Pedro O. Varangot, Tianye Sun, Karthik Jayaraman Raghuram, Hung A. Pham
  • Publication number: 20210396619
    Abstract: Described herein are techniques to enable a mobile device to perform multi-source estimation of an altitude for a location. A baseline altitude may be determined at ground level for a location and used to calibrate a barometric pressure sensor on the mobile device. The calibrated barometric pressure sensor can then estimate changes in altitude relative to ground level based on detected pressure differentials, allowing a relative altitude to ground to be determined. Baseline calibration for the barometric sensor calibration can be performed to determine an ambient ground-level barometric pressure.
    Type: Application
    Filed: January 29, 2021
    Publication date: December 23, 2021
    Inventors: Lei Wang, William J. Bencze, Kumar Gaurav Chhokra, Fatemeh Ghafoori, Stephen P. Jackson, Cheng Jia, Yi-Wen Liao, Glenn D. Macgougan, Isaac T. Miller, Alexandru Popovici, Christina Selle, Aditya Narain Srivastava, Richard Warren, Michael P. Dal Santo, Pejman Lotfali Kazemi