AIR POLLUTION CONTROL AND MONITORING SYSTEM USING IOT SENSOR NETWORK

Abstract

Due to the rapid urbanization, industrialization, and the increase in vehicle emissions, air pollution has become one of the most important environmental and public health issues. Pollution control and the creation of the necessary decisions can be achieved only through continuous and proper monitoring of air quality. The conventional air monitoring systems are usually constrained by high costs of deployment, very low coverage, and slow analysis of data. In order to overcome these drawbacks, the current paper introduces an Air Pollution Control and Monitoring System on the basis of IoT Sensor Network, which is aimed at offering real-time, inexpensive, and scalable air quality data. The suggested system uses a distributed network of IoT-based sensors to detect the most important air quality parameters, including particulate matter (PM 2.5 and PM 1 0), carbon monoxide (CO), nitrogen dioxide (NO 2), ambient temperature and humidity. Data is sent wirelessly to a centralized server using cloud-based infrastructure, thus providing real-time data collection and storage. By using advanced data processing and analytics, the trends of pollution, the detection of abnormal conditions and the creation of real-time notifications in case the level of pollutants exceeds the acceptable limit are identified. Moreover, the system facilitates smart pollution management systems by building up data-based knowledge with automated action measures, e.g., the activation of ventilation systems or the alerting of regulatory bodies. The outcomes of the experiments show that the proposed solution based on IoT is much more precise, less latent, and better in terms of spatial coverage than traditional approaches to monitoring. It is a stable and cost-efficient system that gives smart cities and environmental agencies an opportunity to improve on air quality management and foster the protection of the population.