A practical approach for high-resolution air quality mapping using IoT mobile devices

Official air quality assessment stations are traditionally in fixed locations and have a low spatial resolution. By the use of Internet of Things, low-cost mobile devices collect environmental data, in global initiatives for high-resolution mapping. However, standardized reference guides are rare, being an obstacle for the repeatability and quality of experiments. This paper presents methods, models, and strategies for high-resolution mapping of air quality in an urban environment, with the purpose that the experiments reduce the uncertainties generated by the non-observation of control variables in their execution. Aiming at efficient air quality mapping, practical approach for the use of low-cost sensors portray important issues incorporated into the integrity of the devices, in the methods of data processing and cartographic map composition. The results demonstrated new perspectives and reliability to spatiotemporal analysis, which may support environmental monitoring entities to complement the fixed networks for evaluating and formulating public policies.