| Summary: | Lorenz Georg Görne presents a method (PrOComp) for optimal usage of the transmission path between the vehicle and the data backend. The compression ratio of vehicle measurement data could be improved from roughly a factor of ten in conventional methods, to up to 27. The method allows vehicle measurement data to be transmitted optimally in terms of data volume via the mobile internet and via traditional transmission routes. Through the PrOComp method, real-time data analysis over the mobile internet is feasible, as well as the collection of big data in the field. This enables key features like predictive maintenance, reactive event evaluation (for example crash events) or fast generation of AI training data. Through the usage of standardized interfaces and data formats, PrOComp can be adapted to the needs of many industry branches that feature field data collection. Content Foundation and State-of-the-Art Model of the Transmission Pipeline Introduction of the Processing, Optimization and Compression (PrOComp) Method Measurement Results and Validation of the Method Target Groups Scientists in the field of remote vehicle diagnostics Software developers in the field of big data science and data analysis About the Author Lorenz Georg Görne is currently employed as a systems engineer at an automotive supplier. The focus of his work is steer-by-wire technology. He completed his doctorate in automotive mechatronics at the Institute of Automotive Engineering Stuttgart (IFS) at the University of Stuttgart
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