Gesture Control Revolution: Enhancing Automotive Infotainment through Advanced Hand Gesture Recognition

In the ever-developing industry of automobiles, a focus should be made on the innovation of the car’s user experience while keeping the driver safe. The following paper therefore aims at proposing a new hand gesture recognition system to be implemented in car infotainment, which employs a modified CNN model enhanced with KNN for enhanced gesture mapping. The efficiency of the system was tested on a data of samples consisting of 10000 images of 10 different gestures performed by different users under different lighting conditions. The results obtained for the experimental evaluation proved that the used CNN reached the accuracy of 92,5% with the validation set and the further use of KNN for post-processing increased the classification accuracy up to 95,2%. Resource consumption was low, the CNN occupied roughly 50 MB of memory, that is why it is possible to use it for the in-vehicle system. A similar survey that targeted users showed that 85% of them were comfortable with the system as it was easy to learn and did not interfere with the control of infotainment functions. This research discusses the possibility of using gesture recognition technology to improve the user experience in vehicles making infotainment systems safer and more efficient.