Date of Award


Document Type


Degree Name

Doctor of Philosophy (PhD)


Computer Engineering and Sciences

First Advisor

Ivica Kostanic

Second Advisor

Ersoy Subasi

Third Advisor

Carlos Otero

Fourth Advisor

Josko Zec


In highly populated world areas, such as metropolises, hazardous air pollution has been linked to the presence of damaging climate and health issues, which are becoming increasingly common. Indeed, a major problem facing urban areas today is air pollution. Gas emissions from vehicles can be seen as the most important source of this kind of pollution. Pollutant gases emitted as parts of car exhaust consist of chemicals such as carbon monoxide (CO), nitrogen dioxide (NO2), and sulphur dioxide (SO2), and ozone (O3), as well as particulate matter (PM). In some places in the world, non-governmental and foreign corporations have also referred to growing visibility issues, and they have called for the rapid identification of toxic ambient contaminants to counteract the increasing rate of air pollution adequately, as the results seem alarming. The Environmental Protection Agency (EPA) provides guides to measure these chemicals by several methods to calculate the gases’ concentration. In this research, the measurement of the Air Quality using a set of inexpensive electrochemical sensors is considered. An Internet of Things (IoT) device is used to monitor air quality in real-time. The sensors measure all pollutants prescribed by the US Environmental Protection Agency for the calculation of the Air Quality Index (AQI). The sensors are placed at the street level and connected to a central server through the Internet of Things. Alongside pollution measurements, traffic density measurements next to the sensor location are performed as well. A mathematical model that relates traffic density and AQI is developed. The model shows that some gaseous pollutants have a very strong correlation with the traffic density. Overall, AQI and traffic density, as well as some other factors including temperature and humidity, show significant correlation.


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