Implementation of a wireless sensor network for monitoring air pollutants in urban and industrial areas

Abstract

The study detailed in this paper focuses on the development and implementation of an air pollutant monitoring system using the Arduino Uno microcontroller and a wireless sensor network (WSN) to measure key pollutants, such as CO, CO2, NH3 (ammonia), PM2.5 (particulate matter), and NO2, in both urban and industrial environments. The system's primary objective was to monitor air quality in real-time and analyze its potential effects on human health and the environment. The monitoring system, which uses portable and low-cost sensors, was deployed in multiple locations, with sensor nodes continuously collecting pollutant data and transmitting it wirelessly to a central database. The research methodology involved hardware and software design, implementation, system testing, and data analysis, with data being processed using Python and Jupyter Notebook. The results demonstrated significant differences in pollutant levels between the industrial and urban areas. In industrial regions, NH3 levels were notably high due to inadequate waste management, while CO levels showed a concerning upward trend over time. In urban areas, the high density of motorized vehicles contributed to elevated levels of CO, CO2, NH3, NO2, and PM2.5. These findings were supported by statistical analyses, including Pearson correlation, which revealed significant positive correlations between specific pollutants, such as between CO and CO2, and between PM2.5 and NH3. This study highlights the potential of WSN and IoT-based technologies for real-time environmental monitoring, offering a practical and scalable solution to address growing concerns over air pollution in both industrial and urban settings. The data generated by the system provides valuable insights into air pollution dynamics and can support the development of targeted strategies for mitigating the negative impacts of air pollution on public health and the environment.