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