气候变化领域集成服务门户(CCPortal): A Classification Model Using Personal Biometric Characteristics to Identify Individuals Vulnerable to an Extremely Hot Environment

CCPortal

DOI	10.1061/JMENEA.MEENG-5495
	A Classification Model Using Personal Biometric Characteristics to Identify Individuals Vulnerable to an Extremely Hot Environment
	Choi, Yujin; Seo, Seungwon; Hong, Taehoon; Koo, Choongwan
发表日期	2024
ISSN	0742-597X
EISSN	1943-5479
起始页码	40
结束页码	2
卷号	40 期号:2
英文摘要	The rise in heatwaves due to climate change is becoming a significant concern for outdoor workers, particularly leading to an increasing number of heat-related illnesses. To address the challenge, this study aimed to propose, as a process-based approach, a classification model using personal biometric characteristics to identify individuals who are vulnerable to extremely hot environments (i.e., high-risk groups). To this end, an experimental study was conducted, and experimental conditions were set in an environmental chamber by considering the extremely hot summer weather in Korea. With the data collected from a total of 70 people who voluntarily participated in the experiment, the classification model was developed by adopting multiple methodologies such as time-series clustering, independent samples t-test, and machine-learning algorithms. Consequently, it was found that the classification performance was the best with the multilayer perceptron algorithm, resulting in 0.800 in terms of the area under the receiver operating characteristic (AUROC) and 0.811 in terms of the area under the precision-recall curve (AUPRC). This study creates new ground in identifying individuals vulnerable to extremely hot environments in the domain of management in engineering by employing machine-learning-based classification algorithms with personal biometric characteristics. The proposed approach can be realized by utilizing a simple and low-cost bioelectrical impedance method for estimating human body composition (such as body fat mass and skeletal muscle mass) before they are put into the field. It is expected to aid in providing a more systematic and individualized management system for proactively preventing personal heat-related illnesses.
英文关键词	Heat strain; Extremely hot environment; High-risk group; Classification; Personal biometric characteristics; Machine-learning algorithms
语种	英语
WOS研究方向	Engineering
WOS类目	Engineering, Industrial ; Engineering, Civil
WOS记录号	WOS:001142786200008
来源期刊	JOURNAL OF MANAGEMENT IN ENGINEERING
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/299676
作者单位	Incheon National University; Yonsei University
推荐引用方式 GB/T 7714	Choi, Yujin,Seo, Seungwon,Hong, Taehoon,et al. A Classification Model Using Personal Biometric Characteristics to Identify Individuals Vulnerable to an Extremely Hot Environment[J],2024,40(2).
APA	Choi, Yujin,Seo, Seungwon,Hong, Taehoon,&Koo, Choongwan.(2024).A Classification Model Using Personal Biometric Characteristics to Identify Individuals Vulnerable to an Extremely Hot Environment.JOURNAL OF MANAGEMENT IN ENGINEERING,40(2).
MLA	Choi, Yujin,et al."A Classification Model Using Personal Biometric Characteristics to Identify Individuals Vulnerable to an Extremely Hot Environment".JOURNAL OF MANAGEMENT IN ENGINEERING 40.2(2024).