ACV Auctions. has been granted a patent for a mobile vehicle diagnostic device (MVDD) that utilizes acoustic sensors to detect vehicle defects. The system captures audio during engine operation, processes it using machine learning, and identifies potential issues based on the acquired data. GlobalData’s report on ACV Auctions gives a 360-degree view of the company including its patenting strategy. Buy the report here.
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According to GlobalData’s company profile on ACV Auctions, Social media analytics was a key innovation area identified from patents. ACV Auctions's grant share as of June 2024 was 20%. Grant share is based on the ratio of number of grants to total number of patents.
Mobile device for diagnosing vehicle defects using audio data
The patent US12046254B2 describes a system designed to detect vehicle defects through audio analysis, particularly during engine operation. Central to this system is a mobile vehicle diagnostic device (MVDD) that is mechanically attached to the vehicle. The MVDD is equipped with multiple acoustic sensors, strategically oriented in various directions to capture sound generated by the vehicle. This device works in conjunction with a mobile computing device that receives audio data from the MVDD and transmits it to a computing device via a communication network. The computing device processes the audio recordings using a trained machine learning (ML) model to identify the presence or absence of vehicle defects by generating and analyzing audio features.
Additionally, the MVDD may include vibration sensors and dampening devices to enhance the accuracy of defect detection by minimizing interference from vibrations. The system is capable of processing audio frequencies ranging from 200 Hz to 60 kHz and vibration frequencies from 5 to 800 Hz. The audio data is transformed into various representations, such as waveforms and time-frequency representations, to facilitate detailed analysis. The system can also integrate metadata from the vehicle's onboard computer, further enriching the data set for the ML model. Overall, this innovative approach leverages advanced audio and vibration analysis to improve vehicle diagnostics and maintenance.
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