1. A method of developing a virtual sensor, the method comprising: receiving an inference model configured to accept sensor data from a mobile device and to output inferences based on the sensor data; inputting training data from another mobile device into the inference model to obtain a set of inferences and associated certainty values based on training data from the other mobile device; and determining, based at least in part on the set of inferences and associated certainty values, another inference model configured to accept other sensor data from the other mobile device and to output other inferences based on the other sensor data.
1. A method of developing a virtual sensor, the method comprising: receiving an inference model configured to accept sensor data from a mobile device and to output inferences based on the sensor data; inputting training data from another mobile device into the inference model to obtain a set of inferences and associated certainty values based on training data from the other mobile device; and determining, based at least in part on the set of inferences and associated certainty values, another inference model configured to accept other sensor data from the other mobile device and to output other inferences based on the other sensor data. 7. The method of claim 1 , wherein the inference model is a substitute inference model based on an initial inference model, the method further comprising: receiving test sensor data and associated training labels, the test sensor data associated with a set of mobile devices including the mobile device; and utilizing machine learning to determine the initial inference model based on the test sensor data and the associated training labels.