Supplementary material (data & R script) for the CIEES 2022 manuscript authored by B Stoyanovski, T Iliev, R Cesarec, R Filjar

A single ZIP file contains 119 Android smartphone sensors trajectory observations on the path in the city centre of Krapina, Croatia, as well as the R script for data aggregation, trajectory formation, analysis, and machine learning-based prediction model development, for the CIEES 2022 Conference manuscript.

Trajectory observations were taken using AndroSensors smartphone application (https://play.google.com/store/apps/details?id=com.fivasim.androsensor&hl=en_US&gl=US), which collects obseravtion on the move and stores them into a CSV file. Content depends on the available smartphone sensors. Data sets supplied consist of observations of the following variables: ACCELEROMETER X (m/s²)ACCELEROMETER Y (m/s²)ACCELEROMETER Z (m/s²)GRAVITY X (m/s²)GRAVITY Y (m/s²)GRAVITY Z (m/s²)LINEAR ACCELERATION X (m/s²)LINEAR ACCELERATION Y (m/s²)LINEAR ACCELERATION Z (m/s²)GYROSCOPE X (rad/s)GYROSCOPE Y (rad/s)GYROSCOPE Z (rad/s)LIGHT (lux)MAGNETIC FIELD X (μT)MAGNETIC FIELD Y (μT)MAGNETIC FIELD Z (μT)ORIENTATION Z (azimuth °)ORIENTATION X (pitch °)ORIENTATION Y (roll °)PROXIMITY (i)ATMOSPHERIC PRESSURE (hPa)SOUND LEVEL (dB)LOCATION Latitude : LOCATION Longitude : LOCATION Altitude ( m)LOCATION Altitude-google ( m)LOCATION Altitude-atmospheric pressure ( m)LOCATION Speed ( Kmh)LOCATION Accuracy ( m)LOCATION ORIENTATION (°)Satellites in rangeTime since start in ms YYYY-MO-DD HH-MI-SS_SSS

The analysis and prediction model R script is developed by authors in the R environment for statistical computing (https://www.r-project.org/), using additional R libraries: trajr (https://cran.r-project.org/web/packages/trajr/index.html) and caret (https://topepo.github.io/caret/), among the others.