Hi, recently I found out that some of the Wireless Sensor Networks (WSN) are using coefficients for unifying the measurement results based on how high the sensor is installed.
A particular example is Luftdaten.
Does anyone know what is the formula?.. and how they came to it?
Is there any scientific paper or any empirical research regarding this?
Will be great if you can share anything regarding this subject.
Hello,
I’m not sure if it’s the answer you are looking for. But the only value we unify is the air pressure value (just to be sure: Luftdaten.info == Sensor.Community). And for this we use the Barometric formula Barometric formula - Wikipedia . For the height above sea level we use the Google maps API (lat,lot => height above sea level).
But this is a normal conversion used in meteorology every day.
Got it. Thank you ricki!
Is there any research on how this improves the data set, any coefficient of determination (R2) calculated?
Have you met other ways for optimizing the data in height where other WSNs are using?
Thanks!
This is what meteorologist use in their every day work. The pressure at sea level is what you can see in any weather report.
We can only measure the absolute pressure at the sensor location. But to know if you are in a high or a low pressure area you need to have comparable values. Two places may be relatively near to each other but in very different heights. The absolute values of pressure would be very different. So these values are converted to the pressure at sea level.
So please ask a meteoroligist for further readings about research (may go back some hundred years … 
) and calculated coefficient of determination.