Monitoring Vehicle Noise and Pollution with a Smart IOT System

https://doi.org/10.55529/jaimlnn.31.47.58

Authors

  • B Ravi Chandra G Pullaiah College of Engineering &Technology, Kurnool, Andhra Pradesh, India
  • Thota Teja G Pullaiah College of Engineering &Technology, Kurnool, Andhra Pradesh, India
  • S.Thirupathaiah G Pullaiah College of Engineering &Technology, Kurnool, Andhra Pradesh, India
  • Syed Shashavali G Pullaiah College of Engineering &Technology, Kurnool, Andhra Pradesh, India
  • Patan Sohail Khan G Pullaiah College of Engineering &Technology, Kurnool, Andhra Pradesh, India

Keywords:

Internet of Things, NODEMUC ESP8266, MQ7 Gas Sensor, CO.

Abstract

The ozone layer is deteriorating due to pollution in India and other parts of the world, which also greatly increases air pollution. The project's objective is to create a carbon monoxide detection system that can measure values in any application as well as track and monitor CO levels. The Internet of Things (IoT) connects things (physical objects like lights, phones, and cars) to the Internet by acting as a bridge connector to the current Internet infrastructure.Currently, only after receiving a fitness certificate (FC) from the RTO office can the vehicle's emissions be verified utilizing pollution control stations positioned across various cities. Health certificates for private vehicles are valid for 15 years, after which they must be renewed every 5 years. The fitness certificate is provided for two years and then renewed annually when it comes to vehicles. Until FC is fitted, this method prohibits us from identifying emissions brought on by car maintenance.Blynk is a cloud-based IoT analytics platform that allows you to gather, view, and analyze live data streams. This article focuses on using an MQ7 Gas sensor to prevent accidents caused by vehicle-generated carbon monoxide.

Published

2023-01-29

How to Cite

B Ravi Chandra, Thota Teja, S.Thirupathaiah, Syed Shashavali, & Patan Sohail Khan. (2023). Monitoring Vehicle Noise and Pollution with a Smart IOT System. Journal of Artificial Intelligence,Machine Learning and Neural Network , 3(01), 47–58. https://doi.org/10.55529/jaimlnn.31.47.58

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