  This work presents a proposal for a wireless sensor network for participatory
sensing, with IoT sensing devices developed especially for monitoring and
predicting air quality, as alternatives of high cost meteorological stations.
The system, called pmSensing, aims to measure particulate material. A
validation is done by comparing the data collected by the prototype with data
from stations. The comparison shows that the results are close, which can
enable low-cost solutions to the problem. The system still presents a
predictive analysis using recurrent neural networks, in this case the LSTM-RNN,
where the predictions presented high accuracy in relation to the real data.
