ML-based Power Seat Control system

We propose the power seat control system based on a machine learning approach from passengers’ control actions. More specifically, the system adjusts seat in cars by referring to the trained model on behalf of passengers. If they manually adjust the car seat, the system re-trains the inference model. Whenever manual adjustment happens, the model update is repeated. The system can be used in any area of adjustment system such as a power seat and a power mirror. Consequently, the proposed system can improve passenger’s safety and satisfaction in driving.