Why sensor calibration and precision is the wrong conversation
Regarding the calibration and precision of the sensors we are using, this is the hot-button question that will continue to crop up. Before I answer it again, I want to reiterate that the PRIMARY purpose of this project is accessibility. Everything is based on open source designs and we are choosing the sensor components based on affordability and availability. (However, now that the Egg is being designed to be modular, any sensor can be incorporated. But that's not the point.)
I think Leif said it really nicely in the video we posted a week or so ago that what we are doing is deconstructing a process that in the past has been unknown and closed to us. There are already scientific sensors systems available out there. They gather "better, more reliable" data that the Egg will. But, "better" for WHO? We are not out to contribute to the agenda of the scientific community or otherwise. We are our own community of people with our own goals, our own momentum and our own vision. No one need pass judgement or proclaim success but we. This community has understood from the beginning that any single datapoint that we collect has low value while the breadth, resolution, and update frequency of the network has high value. We aim to understand whether that strategy will allow us to produce the leverage to start conversations or contribute to those already occurring.
MOST IMPORTANTLY, to build a product or system that requires the involvement of expensive test equipment and specialized knowledge about how to use it is undermining what we are doing here. It inserts a dependency on someone. We need to figure out how to look at that dataset in a way that distributes the calibration across the network versus focusing the calibration requirement on a service provider.
Therefore, we can, and will, look at trends in the data. Smart people among us will find savvy ways to interpret this data, match it up with calibrated datasets (government or scientific institutions may be able to provide these), and learn things we never thought we would learn due to the unique nature of the dataset. Trends will allow us to see, albeit cloudily, the hints of problems/anomalies that are occurring in real-time. Those problems may require further investigation by other methods to understand fully, but what we've achieved by even getting to that point is a massive shift away from NOTHING, NON-EXISTENT, NOT INVOLVED. This is the fundamental difference between what we are doing here and crowdsourcing/citizen science.
This most certainly is progress. We are becoming #sensemakers.
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Sensor up a CITY. Let's do a big rally to kick it off. We'll come with 100 Air Quality Eggs, run a clinic, do some talks about sensing/science/community, have an exchange of ideas. Our travel is included to anywhere in US/Europe. 100 people will take home Eggs. Instant critical mass. This is a great way for corporations who want to sponsor this project to get involved, either to give back to the community or engage their own employees in the movement.Estimated delivery:
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