Radiation protection using embedded application

Abstract

Several nuclear power plant accidents that occurred in the past cause not only great damage to us, but also the aftereffects persist for a long time. The purpose of this study is to protect the lives and property of individuals from radiation accidents by predicting the radiation diffusion path and the arrival time at nuclear power plant accidents. Oil prices, which have hovered around $50~60 per barrel for many years, rose to $75again. Therefore, experts are expected to maintain nuclear power plants as part of an energy policy due to soaring oil prices. In addition, countries are pushing to build nuclear power plants to meet the global energy shortage. With an increasing number of nuclear power plants worldwide, the possibility of accidents is also increased. In this paper, we analyze the current status of nuclear power plants in Korea and abroad and the accidents of nuclear power plants in the past. In this paper, we analyze the expected diffusion path of radiation contaminants using the Big Data on the homepage of the Korea Meteorological Administration and the weather data on the homepage of KHNP (Korea Hydro and Nuclear Power) at the time of radiation accident. For this purpose, this paper explains how to develop radiation protection apps using embedded system. By using this system, it is possible to evacuate quickly by anticipating the time when radioactive pollutants spread from the accident point to the point where the person is active in the case of a radiation accident at a nuclear power plant through his own smartphone. People can take quick precautionary measures, such as preparing protective masks and protective clothing. By using the radiation protection application based on the embedded system developed in this study, it is possible to more quickly grasp the spreading time of the radiation pollutant in the case of radiation accident at the nuclear power plant, and by taking preventive measures promptly and safely, people can protect his property.