R package for AirBox data analysis
Air pollution has become an deteriorating environmental problem in the past decades, when the world focus its development on industry without enough environmental protection. Hence, for efficiently monitoring nearby air quality, LASS (Local Aware Sensing System) developed a low-cost air quality monitoring sensor with small volume, but with proper accuracy and reliability. Since a package to analyze datasets collected by the low-cost air quality sensors, we started to write the package to further interpret the meanings behind the collected data.
Installation of airbox from GitHub is easy using the devtools package.
require(devtools)
install_github("cclljj/R-AirBox")
airbox is designed to analyze air quality data from low cost air quality sensors mainly as “airbox”. The main pollution that could be analyzed is the particle matters having aerodynamic diameters less than 2.5 μm, aka, PM2.5. airbox can get sample data of airbox, analyze temporal distribution of PM2.5, find neighbor devices of selected device, discern anomaly within selected area, etc.
Here are the packages users will need to launch functions of airbox: purr qboxplot magick geosphere ggmap
mydata <- getData(data = "2017-01")
getLatestData(Source = 2, raw.data = FALSE)
mydata <- getData(data = "2017-01")
info(mydata = mydata)
mydata <- getData(data = ‘2017-01’)
week_day(mydata = mydata)
mydata <- getData(data = ‘2017-01’)
neighbor(mydata = mydata, id = '74DA388FF60A', dist = 3000, unit = 'm', zoom = 13)
animation(w = 450, h = 300)
spatial_anomaly(id = '74DA3895C392', time = '2017-02-24 10:10:30', dist = 3000 , unit = 'm', zoom = 13)
temporal_anomaly(id = '74DA3895C392', time = '2017-02-24 10:10:30')
This package is licensed under MIT.
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