본문 바로가기
  • Home

Air Pollution Risk Prediction System Utilizing Deep Learning Focused on Cardiovascular Disease

  • Journal of The Korea Society of Computer and Information
  • Abbr : JKSCI
  • 2022, 27(12), pp.267-275
  • DOI : 10.9708/jksci.2022.27.12.267
  • Publisher : The Korean Society Of Computer And Information
  • Research Area : Engineering > Computer Science
  • Received : September 14, 2022
  • Accepted : December 9, 2022
  • Published : December 30, 2022

Jisu Lee 1 Yoo-Jin Moon 1

1한국외국어대학교

Accredited

ABSTRACT

This paper proposed a Deep Neural Network Model system utilizing Keras for predicting air pollution risk of the cardiovascular disease through the effect of each component of air on the harmful virus using past air information, with analyzing 18,000 data sets of the Seoul Open Data Plaza. By experiments, the model performed tasks with higher accuracy when using methods of sigmoid, binary_crossentropy, adam, and accuracy through 3 hidden layers with each 8 nodes, resulting in 88.92% accuracy. It is meaningful in that any respiratory disease can utilize the risk prediction system if there are data on the effects of each component of air pollution and fine dust on oil-borne diseases. It can be further developed to provide useful information to companies that produce masks and air purification products.

Citation status

* References for papers published after 2022 are currently being built.

This paper was written with support from the National Research Foundation of Korea.