There are many ways to slice and dice environmental data, here's how we do it
The way averages are calculated is slightly different depending on the context. Is the average part of a report based on spaces, or is it a single sensor in the analytics view?
Conserv offers several types of reports that can create aggregate statistics for spaces. This is a bit different from looking at data from an individual sensor. When running a report, the averages in the report are the averages for all sensors in that space. For example, if you have three sensors in a space, the average temperature shown for that space is the mean of the readings across all three sensors in the space over the time period covered by the report.
Averages in the analytics view are simpler. Since the current analytics view shows you data based on sensors, not spaces, the averages shown are the mean values for that specific sensor over a specific time period. For example, when viewing a temperature data series for a sensor, aggregated by day, the average shown in the pop up on the graph is the mean temperature for that specific sensor for the selected day. If the data is aggregated by hour, then you'll see the mean temperature for the selected sensor for that hour.
One of the features of Conserv Cloud that is present in both the reports and the analytics view is the "Metrics", such as the percentage of time that a space or sensor was in / out of range. These metrics do not use averages. Instead, they look at the percentage of readings taken that are in and out of the ranges defined in your "Levels" in Conserv Cloud. For a single sensor, this means if 100 readings were taken over the selected time period, and 95 of them were in range, the "in range" percentage would be 95. When metrics are calculated for spaces (such as in reports, or in the weekly summary), we look at all of the readings in that space over the selected time period. For example, if you ran a report for a space that had three sensors, and each sensor had taken 100 readings, we would calculate the percentage of the 300 readings (100 readings per sensor x 3 sensors) that were in range, and display the result:
|Sensor 1||Sensor 2||Sensor 3|
|80 readings in range||100 readings in range||60 readings in range|
80 + 100 + 60 = 240 in range readings, out of 300 taken.
240 / 300 * 100 = 80% of readings in range