Air Sensor Data Unifier: R-Shiny Application
preprint
OA: closed
Abstract
Data is needed to understand local air quality, reduce exposure, and mitigate the neg-ative impacts on human health. Measuring local air quality often requires a hybrid monitoring approach consisting of the national air monitoring network and one or more networks of air sensors. However, it can be challenging to combine this data to produce a consistent picture of air quality largely because sensor data is produced in a variety of formats. Users may have difficulty reformatting, performing basic quality control steps, and using the data for their intended purpose. We developed an R-Shiny application that allows users to import text-based air sensor data, describe the format, do basic quality control, and export the data to standard formats through a us-er-friendly interface. Format information can be saved to speed up processing of addi-tional sensors of the same type. This tool can be used by air quality professionals (e.g., state, local, tribal air agency staff, consultants, researchers) to more efficiently work with data and do further analysis in the Air Sensor Network Analysis Tool (ASNAT), Google Earth or Geographic Information System (GIS) programs, the Real Time Geo-spatial Data Viewer (RETIGO), or other applications they already use for air quality analysis and management.
My notes (saved in your browser only)
Citation neighborhood (no data yet)
We don't have any in-corpus citations linked to this paper yet. This is a recent paper (2025) — citers typically take a year or two to land, and the OpenAlex reference graph may still be filling in.
Source provenance
- europepmc
- last seen: 2026-05-20T01:45:00.602351+00:00