Spatial Data Analysis in the Internet of Things

Overview

This repository supports our research on spatial data analysis in IoT environments, focusing on sensor deployment for air quality monitoring.

Contents

• 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.

Research Paper

Details in our paper: in progress...

Previous paper: MDPI

Objective

Framework for effective sensor placement in IoT using spatial statistical methods.

Usage

For researchers and practitioners in IoT and environmental monitoring.