July 21, 2024

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Forecasting next hours algorithm to work offline

2 min read
Forecasting next hours algorithm to work offline

Hello fellows,I’m into the idea of building an algorithm to predict the probability of rain for the next few hours using only local sensors, without the necessity of internet connection. It will be used to postphone an eminent irrigation if there’s a high probability of rain in the next few hours >70%.
The sensors I’m willing to include are:
1) Thermometer
2) Hygrometer
3) Barometer

4) Luximeter (to identify the darkening of the sky)

5) Pluviometer (used only when developing the algorithm, it will give the feedback to the machine-learning (if rained or not)).

The idea is simple: Training a machine-learning model into using the changes in temperature, humidity, air pressure and luminosity in order to guess if it’s going to rain in the next hours. I just care about the higher end of probability (>70% of chance). Also, my system will be conservative, so in case the expected rain don’t arrive, it will turn on irrigation anyway or if the soil moisture sensor detects the soil as too dry.

I’m aware I won’t get a great accuracy with that. But let’s say my algorithm detects rain only 25% of the time. If I get 100 rains/year, I could save 25 unnecessary irrigations, which IS A LOT of water saved.
For sure, I could have used a open-API and get weather forecast online, however my device needs to work OFFLINE. My system also uses a high-accuracy soil humidity sensor, so I’m not worried about edge cases .

Do you think it’s possible to develop such algorithm for my application?

I thinked about that after looking to my desk clock which, I DON'T KNOW HOW, can guess the weather quite well (given it's totally offline).


submitted by /u/macusking


2024-07-05 19:52:02

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