aranet4r

The Aranet4 is a portable indoor air quality sensor for measuring CO², temperature, atmospheric pressure and relative humidity. These devices are accurate and fun to use, however they are unable to store historic measurements for longer than a fortnight. This package is designed to combine exported Aranet files (in CSV format) into a single dataframe.

Currently, this package has a single function which combines all your Aranet files into one and removes duplicate entries. Eventually this package will include functions to plot these results, add them to a database, and potentially connect directly to one’s device.

Installation

You can install the development version of aranet4r from GitHub with:

# install.packages("pak")
pak::pkg_install("samherniman/aranet4r")

Recommended workflow

The following is the workflow that I use, feel free to use whatever method you would like. The main takeaway is to save all of your aranet4 CSVs to a single folder and then run read_aranet on that folder. This will then return a dataframe with all of them combined.

1. Connect to your Aranet4 through Bluetooth on your phone 📱 using the Aranet4 app (available on the App Store and Google Play Store)
2. Export Aranet data to a cloud drive that syncs with your computer, like iCloud. Share menu >> save to files >> new folder (name it Aranet4 or something) >> save
3. Use read_aranet("path/to/your/aranet/files") to read in the files

library(aranet4r)

df <- read_aranet(system.file("extdata", package = "aranet4r"))

dplyr::glimpse(df)
#> Rows: 499
#> Columns: 7
#> $ recorded_date_time        <dttm> 2022-10-20 20:21:24, 2022-10-20 20:23:24, 2…
#> $ carbon_dioxide_ppm        <int> 1459, 507, 483, 1073, 1150, 1088, 1057, 1019…
#> $ relative_humidity_percent <int> 63, 40, 45, 54, 54, 53, 52, 52, 51, 51, 50, …
#> $ atmospheric_pressure_hpa  <int> 1015, 1014, 1015, 1014, 1015, 1014, 1014, 10…
#> $ temperature_celcius       <dbl> 22.5, 22.7, 20.7, 20.8, 21.3, 21.7, 22.1, 22…
#> $ sensor_display_name       <fct> device1, device1, device1, device1, device1,…
#> $ export_date_time          <dttm> 2022-10-22 01:55:22, 2022-10-22 01:55:22, 2…

Saving an Aranet4 CSV from an iOS device