MonitorApp: a web tool to analyze and visualize pollution data detected by an electronic nose

The analysis of air quality data may reveal the quality of life and can prevent dangers for the citizen health. Assuming that some chemical compounds in the air produce a bad smell, people may detect that something is going wrong acting as sensors that alerts potential risks. This work presents a visual analytics approach to support air quality experts in the analysis of data produced by electronic nose devices. The approach consists in setting workflows to manage and transform raw data offering clustering and visualization techniques to analyze such information. The analysis is supported by calendar, map and line graph visualization techniques also maneuvering the clustering attributes. The interactive map is used to show the position of monitoring stations in order to support making hypothesis related to the data source locations.