Finding point of interest in time series data I am working on a project where I need to figure out the point of interest in time series data.



From the picture you can probably understand a bit more what I mean.
Basically, imagine this is the electricity consumption of a washing machine. From this, I want to identify these points where the consumption changes drastically. In this way I will be able to identify more or less what the machine is doing.

I only have raw data so I can't use any supervised learning algorithm, I was wondering if there are ways to do it mathematically without spending too much computation time. 

Regards and thanks in advance.
Try derivative after either a low-pass filter or smoothing (probably exponential smoothing) to cut down on the noise. Big changes result in a big derivative (up or down).