Abstract
Meteorological observation systems are extremely data-driven. However, several factors affect measurements, which require the use of environmental metrology techniques to increase the quality of measurements, decrease errors and evaluate measurements uncertainty. In this paper, we propose and develop a framework that integrates, process and visualizes sensor data and its associated metadata (for rainfall monitoring). This task is accomplished with a workflow designed to correct raw sensor data, which uses an elastic stack based infrastructure to collect, transform, and store sensor data and metadata. We validated our framework using real precipitation data from a Tipping Bucket Rain Gauge.
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