3 ms·

TL;DR: "If it’s cold outside, chances are temperature sensors sometimes outside are colder than usual." By itself, I have to admit I don’t find this particular

TL;DR: "If it’s cold outside, chances are temperature sensors sometimes outside are colder than usual." By itself, I have to admit I don’t find this particularly surprising, especially since they both averaged over space (whole cities) as well over time: There is no data presented on how well the correlation between battery temperature and outside temperature works out within a single 24-hours-period – given that most people are asleep at 2am, this would be another factor all/most batteries have in common apart from the outside temperature.

JamesCRR 13y ago
For some of the cities in the study we had only about 600 readings from 300 users per day. At this level of data the averages work well across 24 hours, but are messy when you start trying to get hourly figures. Even a couple of thousand users does not give great hourly correlations. However OpenSignal was not built for weather crowdsourcing, and battery temperature readings are only taken when the phone is plugged in, unplugged, turned on, or turned off (since we wanted to calculate average battery drain). So clearly we could more regularly poll the battery temperature. This is what WeatherSignal does. In this case we would get better spatial and temporal resolution. It's also well worth pointing out that we tested this in cities where there were already trusted, online data sources (i.e. weather stations), there are population centres where this won't be the case, or where the data is not shared. Also the case is that for dispersed populations (e.g. North of Sweden or Siberia) while we might not manage to resolve temperature to city level (until we have many more users) we could get temperature estimates across larger ares. So I guess what I'm saying is: this is the start of the story, already we're getting data that is good, more filters could make it better, but more users and faster polling is the real key.

JamesCRR 13y ago

For some of the cities in the study we had only about 600 readings from 300 users per day. At this level of data the averages work well across 24 hours, but are messy when you start trying to get hourly figures. Even a couple of thousand users does not give great hourly correlations. However OpenSignal was not built for weather crowdsourcing, and battery temperature readings are only taken when the phone is plugged in, unplugged, turned on, or turned off (since we wanted to calculate average battery drain). So clearly we could more regularly poll the battery temperature. This is what WeatherSignal does. In this case we would get better spatial and temporal resolution. It's also well worth pointing out that we tested this in cities where there were already trusted, online data sources (i.e. weather stations), there are population centres where this won't be the case, or where the data is not shared. Also the case is that for dispersed populations (e.g. North of Sweden or Siberia) while we might not manage to resolve temperature to city level (until we have many more users) we could get temperature estimates across larger ares. So I guess what I'm saying is: this is the start of the story, already we're getting data that is good, more filters could make it better, but more users and faster polling is the real key.