Methods and apparatus for network-based monitoring and serving of media to in-vehicle occupants

1. An apparatus comprising:

a comparator to link media exposure data corresponding to a panelist to first telemetry data collected by a first vehicle corresponding to the panelist to create linked panelist-telemetry data; and

a neural network trainer to train a neural network to estimate vehicle occupant demographics based on second telemetry data collected by a second vehicle, the neural network trainer to train the neural network using a first subgroup of the linked panelist-telemetry data.

2. The apparatus of claim 1 , wherein the neural network trainer, when an accuracy of the neural network is below a threshold, uses a second subgroup of the linked panelist-telemetry data to further train the neural network.

3. The apparatus of claim 1 , further including:

a targeted media selector to select targeted media for a vehicle occupant based on the estimated demographics; and

an interface to transmit the targeted media to at least one of an infotainment system of the second vehicle or a mobile device of the vehicle occupant.

4. The apparatus of claim 3 , wherein the interface transmits the targeted media to the mobile device via the infotainment system of the second vehicle.

5. The apparatus of claim 4 , wherein the interface transmits the targeted media to the infotainment system via a server corresponding to the second vehicle.

6. The apparatus of claim 1 , wherein the comparator links the media exposure data to the first telemetry data by finding first media exposure data corresponding to the panelist that matches second media exposure data from the first telemetry data.

7. The apparatus of claim 1 , wherein the media exposure data is collected using a meter of the panelist.

8. The apparatus of claim 1 , wherein the media exposure data includes first demographics of the panelist, the neural network trainer to train the neural network by training the neural network to generate probability values indicative of second demographics of panelists based on corresponding telemetry data.

9. The apparatus of claim 1 , wherein the comparator links the linked panelist-telemetry data to reference data corresponding to the first vehicle to create linked panelist-telemetry-reference data, the neural network trainer to train the neural network based on second reference data using the first subgroup of the linked panelist-telemetry-reference data.

10. The apparatus of claim 9 , wherein:

the first telemetry data includes at least one of a make of the first vehicle, a model of the first vehicle, media presented by the first vehicle, or a location of the first vehicle; and

the reference data includes at least one of the make of the first vehicle, the model of the first vehicle, an estimated demographic of a person linked to the first vehicle, or a home address of the person linked to the first vehicle.

11. A non-transitory computer-readable storage medium, having instructions that, upon execution, by a processor, cause performance of a set of operations comprising:

linking media exposure data to first telemetry data to create linked panelist-telemetry data, the media exposure data corresponding to a panelist, the first telemetry data collected by a first vehicle corresponding to the panelist; and

train a neural network to estimate vehicle occupant demographics based on second telemetry data collected by a second vehicle, the neural network trained using a first subgroup of the linked panelist-telemetry data.

12. The non-transitory computer-readable storage medium of claim 11 , the set of operations further comprising: using, when an accuracy of the neural network is below a threshold, a second subgroup of the linked panelist-telemetry data to further train the neural network.

13. The The non-transitory computer-readable storage medium of claim 11 , the set of operations further comprising:

selecting targeted media for a vehicle occupant based on the estimated demographics; and

transmitting the targeted media to at least one of an infotainment system of the second vehicle or a mobile device of the vehicle occupant.

14. The The non-transitory computer readable storage medium of claim 13 , the set of operations further comprising: transmitting the targeted media to the mobile device via the infotainment system of the second vehicle.

15. The The non-transitory computer-readable storage medium of claim 14 the set of operations further comprising: transmitting, the targeted media to the infotainment system via a server corresponding to the second vehicle.

16. The The non-transitory computer-readable storage medium of claim 11 , linking the media exposure data to the first telemetry data by finding first media exposure data corresponding to the panelist that matches second media exposure data from the first telemetry data.

17. The The non-transitory computer-readable storage medium of claim 11 , wherein the media exposure data is collected using a meter of the panelist.

18. A method comprising:

linking, by executing an instruction with a processor, media exposure data corresponding to a panelist to first telemetry data collected by a first vehicle corresponding to the panelist to create linked panelist-telemetry data; and

training, by executing an instruction with the processor, a neural network to estimate vehicle occupant demographics based on second telemetry data collected by a second vehicle, the neural network trained using a first subgroup of the linked panelist-telemetry data.

19. The The non-transitory computer-readable storage medium of claim 11 , wherein the media exposure data includes first demographics of the panelist; and where the set of operations further comprises training the neural network by training the neural network to generate probability values indicative of second demographics of panelists based on corresponding telemetry data.

20. The The non-transitory computer-readable storage medium of claim 11 , the set of operations further comprising:

linking the linked panelist-telemetry data to reference data corresponding to the first vehicle to create linked panelist-telemetry-reference data; and

training the neural network based on second reference data using the first subgroup of the linked panelist-telemetry-reference data.

21. The non-transitory computer-readable storage medium of claim 20 , wherein:

the first telemetry data includes at least one of a make of the first vehicle, a model of the first vehicle, media presented by the first vehicle, or a location of the first vehicle; and

the reference data includes at least one of the make of the first vehicle, the model of the first vehicle, an estimated demographic of a person linked to the first vehicle, or a home address of the person linked to the first vehicle.

22. The method of claim 18 , further including, when an accuracy of the neural network is below a threshold, using a second subgroup of the linked panelist-telemetry data to further train the neural network.

23. The method of claim 18 , further including:

selecting targeted media for a vehicle occupant based on the estimated demographics; and

transmitting the targeted media to at least one of an infotainment system of the second vehicle or a mobile device of the vehicle occupant.

24. The method of claim 23 , wherein the targeted media is transmitted to the mobile device via the infotainment system of the second vehicle.

25. The method of claim 24 , wherein the targeted media is transmitted to the infotainment system via a server corresponding to the second vehicle.

26. The method of claim 18 , wherein the linking of the media exposure data to the first telemetry data includes finding first media exposure data corresponding to the panelist that matches second media exposure data from the first telemetry data.

27. The method of claim 18 , wherein the media exposure data is collected using a meter of the panelist.

28. The method of claim 18 , wherein the media exposure data includes first demographics of the panelist, and the training of the neural network includes training the neural network to generate probability values indicative of second demographics of panelists based on corresponding telemetry data.

29. The method of claim 18 , further including linking the linked panelist-telemetry data to reference data corresponding to the first vehicle to create linked panelist-telemetry-reference data, the training of the neural network based on second reference data using the first subgroup of the linked panelist-telemetry-reference data.

30. The method of claim 29 , wherein:

the first telemetry data includes at least one of a make of the first vehicle, a model of the first vehicle, media presented by the first vehicle, or a location of the first vehicle; and

the reference data includes at least one of the make of the first vehicle, the model of the first vehicle, an estimated demographic of a person linked to the first vehicle, or a home address of the person linked to the first vehicle.

31. A computing system comprising:

creating linked panelist-telemetry data by linking media exposure data corresponding to a panelist to first telemetry data collected by a first vehicle corresponding to the panelist; and

training a neural network to estimate vehicle occupant demographics based on second telemetry data collected by a second vehicle, the neural network trained using a first subgroup of the linked panelist-telemetry data.

32. The computing system of claim 31 , the set of operations further comprising:

using, when an accuracy of the neural network is below a threshold, a second subgroup of the linked panelist-telemetry data to further train the neural network.

33. The computing system of claim 31 , the set of operations further comprising:

selecting targeted media for a vehicle occupant based on the estimated demographics; and

transmitting the targeted media to at least one of an infotainment system of the second vehicle or a mobile device of the vehicle occupant.

34. The computing system of claim 33 , the set of operations further comprising:

transmitting the targeted media to the mobile device via the infotainment system of the second vehicle.

35. The computing system of claim 34 , the set of operations further comprising:

transmitting the targeted media to the infotainment system via a server corresponding to the second vehicle.

36. The computing system of claim 31 , the set of operations further comprising:

linking the media exposure data to the first telemetry data by finding first media exposure data corresponding to the panelist that matches second media exposure data from the first telemetry data.

37. The computing system of claim 31 , wherein the media exposure data is collected using a meter of the panelist.

38. The computing system of claim 31 , wherein the media exposure data includes first demographics of the panelist; training the neural network by training the neural network to generate probability values indicative of second demographics of panelists based on corresponding telemetry data.

39. The computing system of claim 31 , the set of operations further comprising:

linking the linked panelist-telemetry data to reference data corresponding to the first vehicle to create linked panelist-telemetry-reference data; and

training the neural network based on second reference data using the first subgroup of the linked panelist-telemetry-reference data.

40. The computing system of claim 39 , wherein:

the first telemetry data includes at least one of a make of the first vehicle, a model of the first vehicle, media presented by the first vehicle, or a location of the first vehicle; and

the reference data includes at least one of the make of the first vehicle, the model of the first vehicle, an estimated demographic of a person linked to the first vehicle, or a home address of the person linked to the first vehicle.