Abstract: A wireless mobile device for personalizing the control and IVI settings of a connected vehicle according to a seat position of a user of the mobile device. The wireless mobile device is configured to: i) receive a radio signal from each of a plurality of beacons in the vehicle; ii) determine a received signal strength indicator (RSSI) value for each received radio signal; iii) apply a seat prediction model M to the RSSI value for each received radio signal to predict a seat position P; and iv) transmit a predicted seat position P to a server. The seat prediction model M is generated by a machine learning process and stored in a server. A beacon array configuration, data collection and generalization procedure optimizes the coverage and accuracy of the model M. The wireless mobile device is further configured to receive an identification (ID) value of the vehicle. The wireless mobile device retrieves the seat prediction model M from the server and caches in memory in the wireless mobile device.

Abstract: A wireless mobile device for personalizing the control and IVI settings of a connected vehicle according to a seat position of a user of the mobile device. The wireless mobile device is configured to: i) receive a radio signal from each of a plurality of beacons in the vehicle; ii) determine a received signal strength indicator (RSSI) value for each received radio signal; iii) apply a seat prediction model M to the RS SI value for each received radio signal to predict a seat position P; and iv) transmit a predicted seat position P to a server. The seat prediction model M is generated by a machine learning process and stored in a server. A beacon array configuration, data collection and generalization procedure optimizes the coverage and accuracy of the model M. The wireless mobile device is further configured to receive an identification (ID) value of the vehicle. The wireless mobile device retrieves the seat prediction model M from the server and caches in memory in the wireless mobile device.