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Somewhat related, Apple’s Air Quality data source (breezometer) is now owned by Google. I wonder what Apple is going to do about it. Will it be just one of the

by 404mm 3y ago

Somewhat related, Apple’s Air Quality data source (breezometer) is now owned by Google. I wonder what Apple is going to do about it. Will it be just one of their data sources or are they going to acquire their own?

booi 3y ago
Is this really an issue? I bet Apple users use gmail too.
- speedgoose 3y ago
  They also use Google Search by default.
- 404mm 3y ago
  I don’t know. That’s not for me to judge :). I am just pointing it out because they seemed to have an issue with a similar concept in the past (Maps… moving to their own product). Unlike Google as their default search engine, accessing weather or air quality API costs money. (While they probably get paid for keeping Google as their default search engine)
zitterbewegung 3y ago
Since its Google, Apple will probably be forced to do something once Google kills it off.
lotsofpulp 3y ago
I am curious how reliable that air quality data is in the first place. I cannot find anything about Breezometer having invested in installing air quality meters all around the world. https://www.calcalistech.com/ctechnews/article/sycbrdpbi https://www.calcalistech.com/ctechnews/article/sycbrdpbi This article says they are using “machine learning” and “AI”. Makes me think it is all fake. https://www.breezometer.com/pdfs/Ultimate-Guide-to-BreezoMeter_s-Air-Quality-Technology.pdf https://www.breezometer.com/pdfs/Ultimate-Guide-to-BreezoMet... Their own documentation indicates the air quality measures they provide are just guesses based on their models. Page 4 basically says actually measuring particulates in the air is very costly, and so their solution is to come up with models to predict what it might be.
- pnpnp 3y ago
  Yes - it’s much like now weather forecasting works. Data points may come from 2 places 100 mi apart, but what if someone lives between them? Temperature or other weather data is often an extrapolation based on official weather data collection points, and AQI data is no different. How that data gets extrapolated varies wildly by implementation. edit: Also a fun fact, I live 2000ft above and 50mi from the nearest forecasting center in a valley. “Weather apps” are about as accurate as throwing darts at a board up here, because the models used to extrapolate known data completely fall apart with all the variables. Our best source of data is the “short term weather discussion” by NOAA, which just gives some generalizations based on local weather knowledge.
  - aziaziazi 3y ago
    Two differences between weather and AQI forecast: - AQI strongly varies with local human activities, e.g. a coal power plant in between the 2 places 100 miles appart. - temporal and hardly predictable human activities, e.g. a chem industry without good attenuation system that boost its production to fill a special command. Or an attenuation system that breaks.
  - crazygringo 3y ago
    Not just forecasting, but reporting values right now. Spatial interpolation is much more non-obvious than you might initially assume, when the data points are coming from arbitrary locations and not a regular grid. For anyone curious, here [1] is a good place to start, or look up "Kriging interpolation". The basic implementation of any kind of continuous temperature estimation is to have a generic equation that relates how temperature naturally varies by altitude, use that normalize the temperature reported by weather stations according to altitude to create a "flat" temperature map, interpolate to create a smooth continuous temperature map using something like Kriging, and then de-normalize the temperature at a desired point according to the altitude of that location. There are always going to be hyper-local variations that won't account for (are you on the sunny side or shaded side of a mountain? is there an air current? how is vegetation/buildings/asphalt affecting it?), but it's the basic starting point. [1] https://geobgu.xyz/r-2020/spatial-interpolation-of-point-data.html https://geobgu.xyz/r-2020/spatial-interpolation-of-point-dat...

by 404mm 3y ago

booi 3y ago

Is this really an issue? I bet Apple users use gmail too.

speedgoose 3y ago
They also use Google Search by default.
404mm 3y ago
I don’t know. That’s not for me to judge :). I am just pointing it out because they seemed to have an issue with a similar concept in the past (Maps… moving to their own product). Unlike Google as their default search engine, accessing weather or air quality API costs money. (While they probably get paid for keeping Google as their default search engine)

zitterbewegung 3y ago

Since its Google, Apple will probably be forced to do something once Google kills it off.

lotsofpulp 3y ago

I am curious how reliable that air quality data is in the first place. I cannot find anything about Breezometer having invested in installing air quality meters all around the world. https://www.calcalistech.com/ctechnews/article/sycbrdpbi https://www.calcalistech.com/ctechnews/article/sycbrdpbi This article says they are using “machine learning” and “AI”. Makes me think it is all fake. https://www.breezometer.com/pdfs/Ultimate-Guide-to-BreezoMeter_s-Air-Quality-Technology.pdf https://www.breezometer.com/pdfs/Ultimate-Guide-to-BreezoMet... Their own documentation indicates the air quality measures they provide are just guesses based on their models. Page 4 basically says actually measuring particulates in the air is very costly, and so their solution is to come up with models to predict what it might be.

pnpnp 3y ago
Yes - it’s much like now weather forecasting works. Data points may come from 2 places 100 mi apart, but what if someone lives between them? Temperature or other weather data is often an extrapolation based on official weather data collection points, and AQI data is no different. How that data gets extrapolated varies wildly by implementation. edit: Also a fun fact, I live 2000ft above and 50mi from the nearest forecasting center in a valley. “Weather apps” are about as accurate as throwing darts at a board up here, because the models used to extrapolate known data completely fall apart with all the variables. Our best source of data is the “short term weather discussion” by NOAA, which just gives some generalizations based on local weather knowledge.
- aziaziazi 3y ago
  Two differences between weather and AQI forecast: - AQI strongly varies with local human activities, e.g. a coal power plant in between the 2 places 100 miles appart. - temporal and hardly predictable human activities, e.g. a chem industry without good attenuation system that boost its production to fill a special command. Or an attenuation system that breaks.
- crazygringo 3y ago
  Not just forecasting, but reporting values right now. Spatial interpolation is much more non-obvious than you might initially assume, when the data points are coming from arbitrary locations and not a regular grid. For anyone curious, here [1] is a good place to start, or look up "Kriging interpolation". The basic implementation of any kind of continuous temperature estimation is to have a generic equation that relates how temperature naturally varies by altitude, use that normalize the temperature reported by weather stations according to altitude to create a "flat" temperature map, interpolate to create a smooth continuous temperature map using something like Kriging, and then de-normalize the temperature at a desired point according to the altitude of that location. There are always going to be hyper-local variations that won't account for (are you on the sunny side or shaded side of a mountain? is there an air current? how is vegetation/buildings/asphalt affecting it?), but it's the basic starting point. [1] https://geobgu.xyz/r-2020/spatial-interpolation-of-point-data.html https://geobgu.xyz/r-2020/spatial-interpolation-of-point-dat...