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Designing An Iot-Enabled Data Warehouse For Indoor Radon Time Series Analytics
Recently we have seen an increase in the frequency of radon concentration measurement campaigns, largely driven by directives adopted at an European level, and by increased public awareness of the problem. Many of the conducted assessments are simple concentration averages over a time range, where passive sensors are mostly used. Other assessments use portable devices that measure radon in a continuous mode, which can later be downloaded for analysis. However, other types of systems emerged, which continuously measure indoor radon concentrations, and using wireless communications make these data available in real time. This is the case of the RnMonitor platform, designed for online indoor radon monitoring in public buildings in northern Portugal using IoT devices with LoRa communication. Although the project provides a time series database, it still lacks a multidimensional data warehouse to store a large amount of these data in the long term, and to make possible the use of OLAP analytical query tools to explore the data in a multidimensional way. Thus, this article describes the development and implementation of a Data Analytical Processing Module to extend the RnMonitor platform. This module is composed by an ETL process, a multidimensional database and an OLAP server.