# How do I predict if it is rainy or not?

I'm building a weather station, where I'm sensing temperature, humidity, air pressure, brightness, $$CO_2$$, but I don't have a raindrop sensor.

Is it possible to create an AI which can say if it's raining or not, with the help of the given data above and maybe analyzing the slope from the last hour or something? Which specific technology should I use and how can I train it?

• I think this question would be better suited for stats.stackexchange.com, even though, there, this question may sound too basic, given that this question is about "prediction"/"inference", in general. There you will find a lot more competent people that can answer this question. But, honestly, this is the type of questions that I would like to see more on this website, because they are actually useful.
– nbro
Nov 13 '18 at 18:21
• Anyway, just to give you an idea. What you're sensing, e.g. the temperature, the humidity, are usually called, in the context of machine learning (and AI, in general), features. In statistics, these are called variables. These variables can be independent or confounding. Anyway, the idea is to combine these variables in certain way, so as to create an output which needs to correspond to the output of the raindrop sensor. Which model to use and how to deal with your variables, it's more technical, and sometimes the choice of model, etc., requires a little domain knowledge.
– nbro
Nov 13 '18 at 18:27