The Development of a Real-Time Disease Prediction Model through Big Data-based Analysis of Crop-Pathogen-Environment Interactions

• 발행기관: 호서대학교 인문사회과학연구소
• 저자명: 임대환(Daihwan Lim) 이승보(Seung Bo Lee)
• 간행물 정보: 『AI와 인간사회』제6권 제1호, 55~69쪽, 전체 15쪽
• 주제분류: 사회과학 > 사회과학일반
• 파일형태: PDF
• 발행일자: 2025.01.31

국문 초록

This paper presents a method for developing a real-time disease prediction model for major economic crops using big data analytics. By integrating genomic and phenomics data with climate change variables, we analyzed the interactions between crops, pathogens, and environmental factors. A comprehensive disease prediction system was established based on this analysis. Various machine learning algorithms were employed to ensure effective feature selection and analysis, considering both temporal and spatial factors. This research not only focuses on developing the predictive model but also emphasizes its practical applications and challenges in real-world agricultural settings. With climate change posing increasing threats to food security, the relevance of such predictive systems is becoming ever more crucial.

목차

Ⅰ. Introduction

Ⅱ. Related Research

Ⅲ. Suggested System

Ⅳ. Results

References

키워드

빅데이터 유전체학 기상변화 실시간 예측 작물병 Big Data Genomics Climate Change Real-Time Prediction Crop Diseases