Mobile Near-Infrared Sensing - A Systematic Review on Devices, Data, Modeling and Applications

IF 23.8 1区计算机科学 Q1 COMPUTER SCIENCE, THEORY & METHODS

ACM Computing Surveys Pub Date : 2024-03-16 DOI:10.1145/3652596

Weiwei Jiang, Jorge Goncalves, Vassilis Kostakos

引用次数: 0

Abstract

Mobile near-infrared sensing is becoming an increasingly important method in many research and industrial areas. To help consolidate progress in this area, we use the PRISMA guidelines to conduct a systematic review of mobile near-infrared sensing, including 1) existing prototypes and commercial products; 2) data collection techniques; 3) machine learning methods; 4) relevant application areas. Our work measures historical and current trends, and identifies current challenges and future directions for this emerging topic.

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移动近红外传感--关于设备、数据、建模和应用的系统综述

在许多研究和工业领域，移动近红外传感正成为一种日益重要的方法。为了帮助巩固这一领域的进展，我们利用 PRISMA 准则对移动近红外传感进行了系统性回顾，包括：1）现有原型和商业产品；2）数据收集技术；3）机器学习方法；4）相关应用领域。我们的工作衡量了历史和当前趋势，并确定了这一新兴课题的当前挑战和未来方向。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

ACM Computing Surveys 工程技术-计算机：理论方法

CiteScore

33.20

自引率

0.60%

发文量

372

审稿时长

12 months

期刊介绍： ACM Computing Surveys is an academic journal that focuses on publishing surveys and tutorials on various areas of computing research and practice. The journal aims to provide comprehensive and easily understandable articles that guide readers through the literature and help them understand topics outside their specialties. In terms of impact, CSUR has a high reputation with a 2022 Impact Factor of 16.6. It is ranked 3rd out of 111 journals in the field of Computer Science Theory & Methods. ACM Computing Surveys is indexed and abstracted in various services, including AI2 Semantic Scholar, Baidu, Clarivate/ISI: JCR, CNKI, DeepDyve, DTU, EBSCO: EDS/HOST, and IET Inspec, among others.

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