Field-deployable real-time AI System for chemical warfare agent detection using YOLOv8 and colorimetric sensors

IF 3.7 2区 化学 Q2 AUTOMATION & CONTROL SYSTEMS Chemometrics and Intelligent Laboratory Systems Pub Date : 2025-03-08 DOI:10.1016/j.chemolab.2025.105365
Sojeong Bae , Ku Kang , Young Kyun Kim , Yoon Jeong Jang , Doo-Hee Lee
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引用次数: 0

Abstract

Chemical warfare agents (CWAs) pose serious risks, requiring rapid, accurate detection. This study presents a real-time, lightweight AI system using YOLOv8 and colorimetric sensors, designed for field deployment. A dataset of 1,340 images captured under varying conditions enhances robustness. The model achieves 91.3% [email protected] and 10.4 ms/frame inference time on portable hardware. This system bridges the gap between laboratory methods and scalable field detection, ensuring efficient, on-site CWA identification for military, emergency response, and public health applications.

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来源期刊
CiteScore
7.50
自引率
7.70%
发文量
169
审稿时长
3.4 months
期刊介绍: Chemometrics and Intelligent Laboratory Systems publishes original research papers, short communications, reviews, tutorials and Original Software Publications reporting on development of novel statistical, mathematical, or computer techniques in Chemistry and related disciplines. Chemometrics is the chemical discipline that uses mathematical and statistical methods to design or select optimal procedures and experiments, and to provide maximum chemical information by analysing chemical data. The journal deals with the following topics: 1) Development of new statistical, mathematical and chemometrical methods for Chemistry and related fields (Environmental Chemistry, Biochemistry, Toxicology, System Biology, -Omics, etc.) 2) Novel applications of chemometrics to all branches of Chemistry and related fields (typical domains of interest are: process data analysis, experimental design, data mining, signal processing, supervised modelling, decision making, robust statistics, mixture analysis, multivariate calibration etc.) Routine applications of established chemometrical techniques will not be considered. 3) Development of new software that provides novel tools or truly advances the use of chemometrical methods. 4) Well characterized data sets to test performance for the new methods and software. The journal complies with International Committee of Medical Journal Editors'' Uniform requirements for manuscripts.
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Field-deployable real-time AI System for chemical warfare agent detection using YOLOv8 and colorimetric sensors Just-in-time process soft sensor with spatiotemporal graph decoupled learning Editorial Board An iterative conditional variable selection method for constraint-based time series causal discovery Mechanism- and data-driven based dynamic hybrid modeling for multi-condition processes
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