CRASH DETECTION ON MOBILE DEVICE

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 se...

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Bibliographische Detailangaben
Hauptverfasser:	Liu, Richard G, Venkateswaran, Sriram, Choi, Henry, Renard, Yann Jerome Julien, Majjigi, Vinay R, Bryan, Paul D, Agarwal, Mrinal, Aziz, Omar, Liao, Yi Wen, Melendez Hasbun, Alvaro J, Varangot, Pedro O, Aranake, Aniket, Hossein Zadeh, Parisa Dehleh, Clarkson, Rebecca L, Ojeda Avellaneda, David, Raghuram, Karthik Jayaraman, Chow, Sunny Kai Pang, Jackson, Stephen P, Popovici, Alexandru, Pham, Hung A, Bhamre, Tejal, Goolish, Ethan, Sun, Tianye
Format:	Patent
Sprache:	eng
Schlagworte:	CALCULATING COMPUTING COUNTING ELECTRIC DIGITAL DATA PROCESSING PERFORMING OPERATIONS PHYSICS TRANSPORTING VEHICLES IN GENERAL VEHICLES, VEHICLE FITTINGS, OR VEHICLE PARTS, NOT OTHERWISEPROVIDED FOR
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Beschreibung
Zusammenfassung:	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.