POLLUTION CONTROL BY MONITORING OF SOX AND NOX EMISSIONS USING SMART SENSORSNALLAMILLI P.G. BHAVANI, K. SUJATHA AND R.S. PONMAGAL
Human resource is a great asset, as it is the gift of nature. Exploitation of human resources should strictly be monitored on health aspects. The power generation sectors in view to increase the combustion quality for enhancing the power production contribute to green house gases which is a threat to human health. The flue gas containing Oxides of Nitrogen (NOx) and Oxides of Sulphur (SOx) has mammoth impact in the dominion of human health. Hence a secluded screening scheme using image processing, Artificial Neural Network (ANN) and Internet of Things (IoT) to powerfully curtail the flue gas emissions is enforced here. The prime aspiration is in detection, recognition and understanding of combustion conditions in power plants ensuring low SOx and NOx emissions for protecting the human health from hazardous gases. This method applies the colour information from the flame images captured from the furnace of the boiler, where feed water is converted to super heated steam for power generation. The process of estimating the NOx and SOx emissions using a feed forward controller is implemented using Back propagation Algorithm (BPA) which is used to train the ANN. The preliminary step involves the extraction of the attributes from each flame image which is thereafter used for estimation of flue gases by ANN. The challenge lies in identification of the attributes responsible for this. Initially 7 attributes are used for training the ANN and from subsequent analysis it is inferred that 10 attributes could substantially yield good results during training process for estimating the NOx and SOxemissions. These estimated values by ANN are the intelligent sensors which are connected to the embedded computing system to monitor using Internet of Things (IoT). This method proves to be indispensable because this IoT based online monitoring has reduced the percentage of emissions by 19% thereby increasing the combustion quality which has profound effect on reducing the pollution.
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