INTRODUCING A NETWORK STRATEGY FOR REDUCING THE DAMAGES IN POLLUTANTS

Abstract

As country grows as economy improves, the financial status of each individual is raising that results owning a car or a bike for everyone. This results large amount of traffic and pollution in the cities, which causes intensive health problems like cancer, braintumour etc. In a cities like Newyork, Taiwan, Tokyo, Hongkong are concentrated to an efficient pollution monitoring systems to control pollution, density in particular areas. They are controlling it by a simple remedy called traffic diverting. A sensor network collecting information from the network from different places by monitoring their thresholds action will be taken. Based on introducing Internet of Things (IOT) into the field of environmental protection, this paper puts forward a kind of real-time air pollution monitoring and forecasting system. The existed system needs supervisor (Human) to operate it, proposed system is a standalone artificial intelligence based expert system. That can take decisions by past experiments, helps to execute stand alone as a human exporter to replace him at accurate. The system can be laid out in a large number in monitoring area to form monitoring sensor network. Besides the function of conventional air automatic monitoring system, it also exhibits the function of forecasting development trend of air pollution within a certain time range by analyzing the data obtained by front-end perception system according to neural network technology

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