Multi-sensor devices and systems for evaluating vehicle conditions

A system, comprising:

• at least one computer hardware processor;
• and
• at least one non-transitory computer-readable storage medium storing processor executable instructions that, when executed by the at least one computer hardware processor, cause the at least one computer hardware processor to perform a method for using a trained machine learning (ML) model to detect presence of vehicle defects from audio and vibration acquired at least in part during operation of an engine of a vehicle, the method comprising:
• obtaining, via at least one communication network,
• a first audio recording that was acquired, using at least one acoustic sensor, at least in part during operation of the engine, and
• a first vibration signal that was acquired, using at least one vibration sensor, at least in part during operation of the engine;
• and
• processing both the first audio recording and the first vibration signal using the trained ML model to detect presence of at least one vehicle defect, wherein the trained ML model has been trained to detect presence of one or more defects of vehicle from audio and vibration features about the vehicle, the processing comprising:
• generating audio features from the first audio recording,
• generating vibration features from the first vibration signal, and
• processing both the audio features and the vibration features using the trained ML model, by providing both the audio features and the vibration features as inputs to the trained ML model for processing, to obtain output indicative of presence or absence of the at least one vehicle defect.

At least one non-transitory computer-readable storage medium storing processor executable instructions that, when executed by at least one computer hardware processor, cause the at least one computer hardware processor to perform a method for using a trained machine learning (ML) model to detect presence of vehicle defects from audio and vibration acquired at least in part during operation of an engine of a vehicle, the method comprising:

• obtaining, via at least one communication network,
• a first audio recording that was acquired, using at least one acoustic sensor, at least in part during operation of the engine, and
• a first vibration signal that was acquired, using at least one vibration sensor, at least in part during operation of the engine;
• and
• processing both the first audio recording and the first vibration signal using the trained ML model to detect presence of at least one vehicle defect, wherein the trained ML model has been trained to detect presence of one or more defects of vehicle from audio and vibration features about the vehicle, the processing comprising:
• generating audio features from the first audio recording,
• generating vibration features from the first vibration signal, and
• processing both the audio features and the vibration features using the trained ML model, by providing both the audio features and the vibration features as inputs to the trained ML model for processing, to obtain output indicative of presence or absence of the at least one vehicle defect.