Abstract
Usage of the new technology and new inventions are making the human life more and more convenient but alongside they are having several disadvantages as well. Air Pollution is a major drawback of a growth. Major sources of Air pollution are vehicle emitting lot of smoke, dust and other human generated garbage. Increasing So2 and No2 in air is the main cause of air pollution. In this paper, I am proposing a scheme to show the prediction of Air Pollution in urban areas using neuro fuzzy controller applied to the historical data. I have also discussed the scheme for the prediction of O3 based on NO2 and SO2 measurements. Several researchers have proposed different techniques to predict the pollution including application of Neuro- Fuzzy. The techniques of artificial intelligence based in fuzzy logic and neural networks have been frequently applied together. The reasons to combine these two paradigms come out of the difficulties and inherent limitations of each isolated paradigm. Such an intelligent system based on hybrid Artificial Neural Networks (ANN) and Fuzzy Inference Systems (FIS) have attracted the growing interest of researchers in various scientific and engineering areas due to the growing need of adaptive intelligent systems to solve the real world problems. Where, ANN learns from scratch by adjusting the interconnections between layers, Fuzzy Inference System is a popular computing framework based on the concept of fuzzy set theory, Fuzzy if-then rules, and fuzzy reasoning. The structure of the model is based on three-layered neural fuzzy architecture with back propagation learning algorithm and others. My Proposed Algorithm mainly oriented on the pollution occurring due to vehicle smoke in urban areas. I have applied various fuzzy rules to show the severity of the air pollution in occurring due to smoke generated from vehicles and dust in nearby areas of Jabalpur. Data has been collected from office of Survey of India in Jabalpur.
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