Analysis of air quality parameters on climate change phenomenon using Markov autoregressive model

In the present era, increased levels of air pollution have become a major threat to humankind, ecosystems, and climate. Nowadays, the level of noxious emissions in the environment is increasing tremendously owing to industrialization, urbanization, and population growth. The increased pollutant concentrations affect ecosystems, meteorological factors, and human health issues. In light of this, a portable device that can monitor and quantify air quality and harmful gas emissions in response to environmental factors like humidity and temperature is presented in this work. An Internet of Things (IoT) platform with ThingSpeak is employed to monitor all air quality data in real-time by inculcating Air Quality Monitoring System (AQMS). By comparing the recorded data with the standard parameters of the Air Quality Index (0-50 PPM) and NOx emission with 250-350 ppm, the data may be analysed with a data retrieval rate of 2 seconds from the cloud to smart devices. This study will aid in developing an adaptive method for forecasting climatic conditions using a Markov autoregressive model to alarm the environment to take remedial action on the desired environmental aspects.