This repository supports our research on spatial data analysis in IoT environments, focusing on sensor deployment for air quality monitoring.
Autocorrelation.r
: Spatial autocorrelation analysis using Moran's I.Figures.R
: Visualization generation.Kriging.r
: Spatial prediction using Kriging.ParetoOptimality.R
: Pareto optimality analysis.[PhD]TimeSeries.ipynb
: Time series analysis of sensor data (Future works).- Additional scripts for data processing and analysis.
model_raster.tif
: Sample raster data.data
folder: Contains the results of our experiments along with additional data (Additional_data_link
) that supported the methodology and decisions regarding the experiments.
Details in our paper: in progress...
Previous paper: MDPI
Framework for effective sensor placement in IoT using spatial statistical methods.
For researchers and practitioners in IoT and environmental monitoring.