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    BME680 questionable accuracy and comparability over devices

    BME680 questionable accuracy and comparability over devices


    Hello Bosch,

    we are evaluating the BME680 sensors within a series of IoT device prototypes. Attached you find some images, screenshots and more information on the used setup. Unfortunately, we see two major issues with the results of the sensor and hope you can help us to overcome those.

    1. The devices IAQ value has a very high deviation, hence low accuracy. The standard deviation of the 15 tested sensors is around 50 on multiple occasions. See e.g. tags a and b in the screenshot. The devices where located very close to each other. See image in the attached zip. How can this be? Or in other words: Who can a better accuracy over devices be reached?
    2. The IAQ values repeatedly peak to “unhealthy” up to “very unhealthy” levels when someone is cooking e.g. only a soup around 10m away from the desk the devices are located on. This seems way to extreme and would render all results useless. Can you help finding a solution on this?

    Furthermore some minor topics:

    • The IAQ value keeps in the range of 25 to 250, but the official scale is bigger. Can you supply information on this? Why are there no smaller values possible? We only see some rare drops below 25.
    • Can you supply us information about the different meaning of “static IAQ” and “IAQ”, please?
    • Can you elaborate the exact difference between the 4d and 28d configuration and when to use which?

    In the following you see some highlights to elaborate our findings.

    All but graph 3 show the IAQ value of 15 sensors over time. Graph 3 shows the average IAQ value as well as the standard deviation. Graph 1 shows the overall measuring period of arround 9 days. There where 3 days where the apartment was empty, as easily can be seen.

    Tags a and b show moments where the standard deviation is very high.

    Tag c shows the moment, when the apartment was left for 3 days. Tag d shows a small peak in an empty apartment. No explanation here.

    Tag e and f show a drastic increase after 2 people enter the apartment. The was no cooking or similar and no human can within 5m of the sensor. But the IAQ value indicates a environment that is “unhealthy for sensitive groups”. This means the sensor tells us that apparently this apartment becomes an unhealthy place only when 2 people are somewhat in the same air. This renders every room unhealthy as soon as a human is close by.

    Tag g shows another extrem peak. All sensors saturate arround 250 after there was a soup cooked in the kitchen arround 10m distance. The IAQ value indicates "very unhealthy" air according to the official scale. This obviously is way to drastic.

    You find code, the gathered sensor data and setup information attached. We would highly appreciate assistance on these issues, as the results are currently without value for our use case and far away from the performance one can read in the brochure.

    graph 1Report-BME-ELK- 001-Overview.png

    graph 2 Report-BME-ELK- 002-LargeStdDev.png

    graph 3Report-BME-ELK- 003-LargeStdDev.png

    graph 4 Report-BME-ELK- 004-EmptyPeriod.png

    graph 5Report-BME-ELK- 005-RiseAfterReturn.png

    graph 6Report-BME-ELK- 006-RiseAfterReturnZoom.png

    graph 7Report-BME-ELK- 007-InsaneButUsualDinnerPeak.png


    5 REPLIES 5

    Community Moderator
    Community Moderator

    @Isarvation wrote:

    This sounds very similar to the design behind IAQ and static IAQ. So is it either 4d and IAQ versus 28d and static IAQ or is there more to it?
    Or in a table:

      IAQ static IAQ
    4d mobile environment ???
    28d ??? static environment

    I guess one could find cases for any combination, but this table should cover the most common use-cases.