Environmental Modeling and Traffic Simulation: A multivariate approach to monitor urban air pollutant agents.

This work presents an interdisciplinary assessment examining air quality tracking in urban environments. application is well suited to be approached with wireless sensor networks' paradigm their overall variations. The proposed modeling takes advantage of Vehicle Sensor Networks (VSN) by embedding nodes public transportation, addressing this study case bus lines so that the mobiles spread sampling activity through many different places visited during route. Simultaneously, it alleviates power management restrictions, packaging dimensions (size and weight), general maintenance issues. We perform environmental based on real data considering temporal spatial multivariate behavior observed phenomena. consider city São Paulo our parse asserted create a map samples, showing five pollutants from fossil-fueled vehicles (CO, O3, PM10, NO2 SO2) simultaneously while also varies time. Furthermore, experiment considers detailed description roads, lines, vehicle itineraries, traffic information. input has unformatted or missing information due being sourced sensors handled mentioned above. Our methodology addresses following: 1) simulation, 2) deployment mobile performing sensing process, 3) implementation network delivery collected data, 4) visualization monitored environment gathered using Voronoi Diagrams fill blank at non-reached areas. Finally, VSN-based approach improved 126 times lower error 11 higher coverage compared conventional monitoring stations.