Data analytics on real-time air pollution monitoring system derived from a wireless sensor network

Abstract:

Air pollution is a problem that causes adverse effects, which tends to interfere with human comfort, health or well-being, and that may cause serious environmental damage. In this regard, this study aims to analyze large data sets generated by real-time wireless sensor networks that determine different air pollutants. Business Intelligence and Data Mining techniques have been applied in order to support subsequent decision-making strategies. For normalization and modeling, we applied the CRISP-DM methodology using the Pentaho Data Integration. Then, the Sap Lumira has been applied in order to acquire models of tables and views. For the data analysis, R-Studio has been used. For validation, Clustering has been applied using the k-means algorithm by the Jambu method, where it has been proceeded to check the consistency of these, being later stored and debugged in PostgreSQL. Results demonstrate …

Año de publicación:

2019

Keywords:

Fuente:

google