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IoT Utilization for Predicting the Risk of Circulatory System Diseases and Medical Expenses Due to Short-term Carbon Monoxide Exposure

Journal of The Korea Internet of Things Society / Journal of The Korea Internet of Things Society, (P)2799-4791;
2020, v.6 no.4, pp.7-14
https://doi.org/https://doi.org/10.20465/kiots.2020.6.4.007


Abstract

This study analyzed the effect of the number of deaths of circulatory system diseases according to 12-day short-term exposure of carbon monoxide from January 2010 to December 2018, and predicted the future treatment cost of circulatory system diseases according to increased carbon monoxide concentration. Data were extracted from Air Korea of Korea Environment Corporation and Korea Statistical Office, and analyzed using Poisson regression analysis and ARIMA intervention model. For statistical processing, SPSS Ver. 21.0 program was used. The results of the study are as follows. First, as a result of analyzing the relationship between the impact of short-term carbon monoxide exposure on death of circulatory system diseases from the day to the previous 11 days, it was found that the previous 11 days had the highest impact. Second, with the increase in carbon monoxide concentration, the future circulatory system disease treatment cost was estimated at 10,123 billion won in 2019, higher than the observed value of 9,443 billion won at the end of December 2018. In addition, when summarized by month, it can be seen that the cost of treatment for circulatory diseases increases from January to December, reflecting seasonal fluctuations. Through such research, the future for a healthy life for all citizens can be realized by distributing various devices and equipment utilizing IoT to preemptively respond to the increase in air pollutants such as carbon monoxide.

keywords
일산화탄소, 순환계통 질환, 진료비용, 포아송 회귀분석, ARIMA 개입 모형, Carbon Monoxide, Circulatory System Disease, Medical Expenses, Poisson Regression Analysis, ARIMA Intervention Model

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Journal of The Korea Internet of Things Society