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Neural Network Model Prediction: A prediction model for Toxin release in environment from E-Waste

Swapnali Lotlikar, Sohrab Ardeshar Vakharia

Abstract


There is an exponential increase in the use of electronic devices, especially mobile gadgets. Earlier people used to replace their gadgets only when they were damaged but it is not the case now. Damages are no longer the only reason for disposing of electronic devices, where technical worn out, new product features, better aesthetics and emotional value are having strong influences to the disposal of the devices. This paper has estimated the total number of refurbished, recycled and scraped mobiles from year 2008 to 2018. Based on the survey results, this paper proposes a model to predict the toxic elements in mobiles. This model can be used by manufacturers and mobile users which will give chance to the manufacturers to replace/change to alternative technology and creating awareness among mobile users about e-waste. Model uses training set consisting of pollutants from mobile component like screen, battery, processor etc. for predicting will take place by having a “Neural Network” approach using “THE MCCULLOH-PITTS” algorithm to determine the input training dataset. Screen, Battery, Processor etc. are different components used for the prediction


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References


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