How to use a multiple linear regression model built from normalized data
So, the question asks:

How to normalise incoming (individual observations)
How to get the real value predictions and not the normalised values.


When we do normalisation using the Sci-kit learn module, instead of using the very handy fit_transform() method in the scaler, you could instead perform a .fit() over your original observations and then apply the .transform() to the newly-observed values. Obviously, in this case you need separate scalers foreach feature, as they are distributed differently from one another.

Again in Sci-kit learn, there is an inverse_transform() method which reverts the normalised value back to the original scale.