Abstract

Air Pollution is one of the severe hazards which affect the health quality of all living beings and the environment itself, especially in urban areas. It creates significant health issues in many countries and harms human health if its concentration exceeds tolerable levels. Monitoring these pollutants and their concentrations is a crucial preventative measure to alert the public to the air quality in the area. The primary objective of this paper is to design a smart air pollution prototype to purify the air with the help of a PM sensor, gas sensors, analog to digital converter (ADC), Raspberry Pi 3 B+ microcontroller, and multiple filters (Step-by-step filtering of particles from sizes 200 to 0.3 µm will be done by different filters). The gas sensors, MQ2 and MQ135, measure the presence/concentration of the LPG, smoke, CO, CO2, and NH4 before and after the filtering process. The PMSA003 sensor detects Particulate Matter (PM) in the range of 0.3 microns to 10 microns. ADC and Raspberry Pi 3 B+ convert the outputs of gas sensors and PM sensors into concentrations of particles. These results are transmitted to the Thingspeak Cloud platform through the WiFi Module. The sensor outputs can be viewed in any system/mobile in the Thingspeak Cloud platform. The concentration of different gases and the measured size concentration of various particles are plotted before and after the filtration, and the results are compared. It is found that the designed filter effectively filters all the particles above 0.3 µm. The performance and efficiency test of both air quality monitoring and air purifier system is done.

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call

Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.