Biometric Voting using IoT to Transfer Vote to Centralized System: A Bibliometric

Author:

Essah Richard1,Anand Darpan2,Singh Surender3,Senior Ampofo Isaac Atta4

Affiliation:

1. Department of Computer Science and Engineering, Chandigarh University, Chandigarh, India

2. Padampat Singhania University, Udaipur, India

3. Apex Institute of Technology, Department of Computer Science and Engineering, Chandigarh University, Chandigarh, India

4. Kwame Nkrumah University of Science and Technology, Kumasi, Ghana

Abstract

Several studies have empirically explored biometric voting using the IoT to transfer votes to the central system. There aren't many bibliometric studies that categorize the output in this area, though. By keeping an eye on the papers posted on the Scopus platform, this study’s goal is to present a research bibliometric analysis of biometric voting utilizing IoT to transfer votes to a central system, classifying trends, the state of the art, and other indications. 267 different materials made up the sample. Using the VOS viewer program, the data was processed and the outcomes graphically represented. According to a study, that examined publications’ simultaneous occurrence by year, trends of keyword, co-citations, coupling bibliographic, and coauthorship analysis, institutions, and countries, the body of knowledge on biometric voting that uses the Internet of Things to transfer votes to a central system is expanding quickly. More than 530 citations were found in just eight works. However, there are other industrious writers. The most significant of the 267 sources used in the review were published in 26.066 percent of the papers. China is the world's leader in this field. This study offers knowledge about the current state of the art and indicates research opportunities and gaps in IoT-based biometric voting.<br>

Publisher

BENTHAM SCIENCE PUBLISHERS

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3