A new study has found that the smartphones we all carry in our pockets could help collect weather data from the public to provide early warnings for wildfires and other extreme weather conditions.
All smartphones are equipped with multiple micro-sensors capable of collecting important environmental data, such as temperature, barometric pressure, humidity, magnetic field, light, sound, location, acceleration, gravity, and more. These data help us find our way or define our location and they warn us when the battery overheats or the device absorbs moisture — all in real time, without saving the data.
Professor Colin Price and student Hofit Shachaf from the Porter School of the Environment and Earth Sciences used data collected from the global public via the WeatherSignal app (OpenSignal) to develop a methodology for assessing wildfire risk based solely on smartphone data collected by the public.
The results were published in the journal Natural Hazards and Earth System Sciences (NHESS).
The researchers demonstrated that smart use of such data could support early warnings for severe wildfire events, especially since millions or even billions of data points are collected worldwide every day by our smartphones. Today, early warning systems in remote forested areas typically lack data due to the absence of weather stations in remote locations. (Some researchers are using using goats, dogs and elephants to predict the weather!)
We take our phones everywhere but the data is normally lost and not saved.
However, many companies have started to collect smartphone data to use for various purposes, with user consent. The researchers believe that this huge data source could aid in forecasting extreme weather and natural disasters.
One key parameter determining the likelihood of a wildfire is the moisture content in vegetation (essentially the fuel available for the fire), which, in turn, is determined by the temperature and relative humidity of the surrounding air. Both the temperature and relative humidity can be easily obtained from the public’s smartphones. But smartphone data do contain errors. The temperature reading might reflect the air conditioning in your office, while the humidity sensor might identify moisture when the user is taking a shower.
The researchers say the huge amount of data collected from smartphones allows us to remove outliers in the data set. Furthermore, since the micro-sensors are not calibrated before they are put in our phones, it was necessary to first calibrate the local smartphone data against commercial meteorological stations. This procedure turned out to be relatively straightforward, with just a single calibration needed to correct a smartphone’s readings.
After calibrating or “training” the device, the researchers analyzed major wildfire events: one was the massive fire in Portugal in July 2013. The results were surprising, with smartphone data collected from the public showing significant anomalies before and during these major fires.
“It’s surprising, but even though each smartphone has its own errors and biases, with large amounts of data from many smartphones, we can average out the errors and still retain useful data,” Shachaf says. “The large volume of data helps overcome issues associated with individual smartphones.”
“Given the rapid increase in the number of smartphones worldwide, we propose utilizing this data source to provide better early warnings to the public and disaster managers about impending natural disasters,” Professor Price concludes. “Better early warnings could prevent natural hazards from becoming natural disasters.”
