Smart IOT based Pollution Forecasting(PM2.5) System For Smart City

Thakare Komal Dnyandev; Pawar Pallavi Vijay; Patil Madhuri Abhiman; Borse Harshali Sanjay; P.A.Lahare

Smart IOT based Pollution Forecasting(PM2.5) System For Smart City

Authors: Thakare Komal Dnyandev, Pawar Pallavi Vijay, Patil Madhuri Abhiman, Borse Harshali Sanjay, P.A.Lahare

Unique Paper ID: 147997
Volume: 5
Issue: 12
PageNo: 220-223

Keywords: MISC6814 MCM811 PM2.5 AWS Cloud ESP32 OLED Display

Abstract:
Today air pollution has arisen as a global public health problem and is identied as a major environmental health hazard by agencies such as the World Health Organization (WHO) . An increase in the concentration of pollutants-both gaseous and solid-is among the largest health risk in the world. Air pollution is responsible for 55 lakh deaths of people every year all over the world. Air pollution is the forth main reason for large numbers of death and causing respiratory diseases all over the world. Recently, air pollution acquired critical dimensions and the air quality in the most cities that monitor outdoor pollution fail to meet WHO guidelines for safe level. The levels of PM2.5 and PM10 (Air-born particles smaller than 2.5 micrometers in diameter and 10 micrometers in the diameter). In existing system when device detect PM2.5 particle at that time device causes jam because this device totally depend on hardware in that pipe and filter papers are used to calculate how many particle was obtain for particular time. This system can not work automatically. To overcome this problem in our project we have try to solve the real time problem In this we are using the sensor like MISC6814, MCM811,PM2.5 and used the AWS Cloud for data storage purpose,ESP32Microcontroller,OLED Display and power supply using that detects harmful gaseous and update on webapp also alert to the people.

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Cite This Article

ISSN: 2349-6002
Volume: 5
Issue: 12
PageNo: 220-223

Smart IOT based Pollution Forecasting(PM2.5) System For Smart City

Available:https://ijirt.org/Article?manuscript=147997

Impact Factor
8.01 (Year 2024)

UGC Approved
Journal no 47859

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