Implementing Rolling Averages

April 22nd, 2016|Categories: Programming, Remote Monitoring|Tags: , , |0 Comments

When dealing with fluctuating data rolling averages are needed to even out the highs and the lows. For example a methane detector could bounce between 9% and 11% LEL with very little change in the actual methane in the air. An alarm set at 10% would constantly be alarming and then clearing causing operators or [...]