Aspinity, Inc.

Thomas Doyle

Madhumita Harish

Brandon David Rumberg

Glen Edward Clark

Lorenzo Ponzanelli

Matthew Zeleznik

According to some embodiments, a sound sensor is located in an automotive vehicle cabin. A processor coupled to the sound sensor is configured to receive an acoustic signal sensed by the sound sensor and automatically determine a vehicle event that occurred based on an analysis of the acoustic signal. The determined vehicle event may be, for example, associated with an impact to the vehicle and/or vandalism monitoring while the vehicle is parked. In some embodiments, the processor automatically triggers a vehicle action responsive to the determined vehicle event. The acoustic signal may be analyzed through linear signal processing techniques and/or machine learning performed via analog processing.

Vehicle in-cabin audio detection of vandalism

Provided is an analog-based machine learning apparatus and method that enables low-power sensing and smarter determinations on a vehicle. As an example, the method may include storing a machine learning model and configuration data for an analog processor in a storage device of a digital processor in a vehicle, receiving, via the analog processor, sensor data from one or more hardware sensors that are communicably coupled to the analog processor, extracting features from the sensor data, determining an event that occurred based on the configuration data and execution of a machine learning model on the extracted features of the sensor data, and storing an identifier of the event in the storage device.

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Laguna Niguel, CA, United States of America

Thomas Doyle