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Auto mechanic in his pocket: Skoda taught smartphones “by ear” to identify problems in the car using AI
Aftermarket department of automaker Skoda Auto and Skoda Auto DigiLab test new smartphone app – Sound Analyzer. The application uses artificial intelligence (AI) and helps to quickly and accurately determine the need for any service through sound analysis.
The software records the noises made by the respective vehicle while driving and compares them with stored samples. In case of any discrepancies, the application uses the algorithm, determining their nature and how to fix the problems. Sound Analyzer helps improve vehicle maintenance, reduce garage time and improve customer satisfaction, the company says.
The Sound Analyzer app uses AI to reliably, clearly and quickly assess the current condition of wearing parts and notify technicians of any required maintenance. To do this, the program examines various vehicle-specific parameters and analyzes the usage profile of the respective vehicle. Sound Analyzer allows technicians to simplify the task of accurately diagnosing a car, because the application requires only a regular smartphone or tablet to use the application.
According to the company, the software is already able to recognize ten problem patterns with more than 90% accuracy, including for components such as the steering system, air conditioning compressor, clutch in a robotic DSG gearbox. The app can also recognize other sound patterns.
Sound Analyzer is based on a trained neural network: the app first converts an audio file into a spectrogram that visually displays acoustic signals. Then, using AI, this view is compared with the stored records to identify deviations. After analysis, the software classifies the potential need for upcoming maintenance or repair and gives advice.
Since June 2021, the smartphone app has been tested in 14 countries, including Russia, Germany, Austria and France. 245 Skoda dealers took part in the pilot project. The information from them made it possible to obtain a number of records that play a key role in the learning process of the neural network. The company is going to gradually expand the range of application-specific acoustic abnormalities – this should open up many new opportunities in terms of preventive maintenance.