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All Journal Bulletin of Social Informatics Theory and Application
Omar, Abdaraouf Abdalla
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Computer Science & IT Social Sciences

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Forecasting IoT Pollution Data Using Forward Newton for Sustainable Green Environment Asghaiyer, Mohamed; Omar, Abdaraouf Abdalla
Bulletin of Social Informatics Theory and Application Vol. 6 No. 1 (2022)
Publisher : Association for Scientific Computing Electrical and Engineering

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31763/businta.v6i1.545

Abstract

IoT (Internet of Things) technology is growing rapidly because of its ease of use and low cost. One of the widely used IoT technologies is air pollution loggers in big cities. This technology is often found installed in places that are easily seen to display pollution information. The stored data is not processed so that the data seems useless. The data contains valuable information as long as it is extracted with the right method. The pollution data is consistent with time, so the use of the advanced newton method is suitable because the prediction will involve future trends. The results of this study indicate that from 12,432 the amount of data gives the result that in the next 1 year the amount of CO2 levels will increase by 3%, this needs to be taken into account by planting trees around the location so that the environment becomes friendly to human health.
Co-Authors Asghaiyer, Mohamed