How to combine features with different temporal scale in machine learning
Machine Learning does not have an specific method from mixing data with different sampling rates.

An extract from the paper:

We approach the problem of dealing with multiple sampling rates from an aggregation perspective. We propose Accordion, a new embedded method that constructs and selects aggregate features iteratively, in a memory-conscious fashion.

Our algorithms work on both classification and regression problems. We describe three experiments on real-world time series datasets, with satisfying results.

Mining Multivariate Time Series with Mixed Sampling Rates