Introducing artificial intelligence to the radiation early warning system

Autor:	Ali Jaber, Yehia Taher, Mohammed Al Saleh, Rafiqul Haque, Nourhan Bachir, Béatrice Finance
Rok vydání:	2021
Předmět:	Intervention (law) Radiation level Risk analysis (engineering) Computer science Health Toxicology and Mutagenesis Continuous monitoring Environmental Chemistry Early warning system Anomaly detection General Medicine Cluster analysis Pollution Task (project management)
Zdroj:	Environmental Science and Pollution Research. 29:14036-14045
ISSN:	1614-7499 0944-1344
Popis:	Although radiation level is a serious concern which requires continuous monitoring, many existing systems are designed to perform this task. Radiation early warning system (REWS) is one of these systems which monitor the gamma radiation level in air. Such system requires high manual intervention, depends totally on experts’ analysis, and has some shortcomings that can be risky sometimes. In this paper, the approach called RIMI (refining incoming monitored incidents) will be introduced which aims to improve this system while becoming more autonomous with keeping the final decision to the experts. A new method is presented which will help in changing this system to become more intelligent while learning from past incidents of each specific system.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::5d40a5ad42cfbc90a673a2ce79e2d827 https://doi.org/10.1007/s11356-021-16771-5 Zobrazit plný text záznamu Full text from SpringerLink