A Survey paper on Vehicles Emitting Air Quality and Prevention of Air Pollution by using IoT Along with Machine Learning Approaches
Main Article Content
Abstract
We denoted a new method and Technology for automatic recognition of air quality, air Pollution and fog from a vehicles. Our system consists of sensors to acquire main data from emitting gases by vehicles using IoT - MQ135 and Arduino tools .It is used to Display the air quality and air pollution with the help of the instruments. When there are sufficient amount of harmful gases are present in the air like CO2, smoke, alcohol, benzene and NH3 .We discuss how this data can be collected, analyzed and merged to determine the degree of air pollution or fog. Such data is essential for control systems of moving vehicles in making autonomous decisions for avoidance. Backend systems need such data for forecasting and strategic traffic planning and control. Laboratory based experimental results are presented for weather conditions like air pollution and fog, showing that the recognition scenario works with better than adequate results. This paper demonstrates IoT - MQ135 and Arduino tools technology, already onboard for the purpose of autonomous driving, can be used to improve weather condition recognition when compared with a camera only system. We are going to make an IOT Based Vehicles Air Quality Sensors and support vector regression (SVR), to forecast pollutant and particulate levels and to predict the air quality index (AQI). Among the various tested alternatives, radial basis function (RBF) was the type of kernel that allowed SVR to obtain the most accurate predictions. Advance Technologies like Artificial Intelligence or Machine Learning based Prevention of Air Pollution system will activate an alarm when the air quality goes down beyond a certain level, means when there is sufficient amount of harmful gases are present in the air like CO2, smoke, alcohol, benzene and NH3. It will show the air elements in PPM on the LCD and as well as on webpage so that we can monitor it very easily. This paper covers the revision of the studies related to air quality and prevention of air pollution using machine learning algorithms based on sensor data in the context of vehicles.
Downloads
Metrics
Article Details
You are free to:
- Share — copy and redistribute the material in any medium or format for any purpose, even commercially.
- Adapt — remix, transform, and build upon the material for any purpose, even commercially.
- The licensor cannot revoke these freedoms as long as you follow the license terms.
Under the following terms:
- Attribution — You must give appropriate credit , provide a link to the license, and indicate if changes were made . You may do so in any reasonable manner, but not in any way that suggests the licensor endorses you or your use.
- No additional restrictions — You may not apply legal terms or technological measures that legally restrict others from doing anything the license permits.
Notices:
You do not have to comply with the license for elements of the material in the public domain or where your use is permitted by an applicable exception or limitation .
No warranties are given. The license may not give you all of the permissions necessary for your intended use. For example, other rights such as publicity, privacy, or moral rights may limit how you use the material.
