基于物联网的智能考勤系统

Prajwal Gujarkar, Sarthak Lonkar, T. Jain, Shubham Nigal, Pramod Patil, Pallavi Deshpande, Ketki P. Kshirsagar, Shraddha K. Habbu, Gauri Ghule, A. Ratnaparkhi
{"title":"基于物联网的智能考勤系统","authors":"Prajwal Gujarkar, Sarthak Lonkar, T. Jain, Shubham Nigal, Pramod Patil, Pallavi Deshpande, Ketki P. Kshirsagar, Shraddha K. Habbu, Gauri Ghule, A. Ratnaparkhi","doi":"10.1109/ESCI56872.2023.10099839","DOIUrl":null,"url":null,"abstract":"Nowadays, as attendance is taken using the tra-ditional pen and paper method, it increases the workload for employees and employers. This increases the cost of maintaining records and will also increase the manipulation in the system. So, there is a dire need of proper attendance management system. As it will help in Accurate tracking, increase productivity and reduces time for marking attendance. As the world around us becomes more modern, organizations are adopting more advanced methods for managing attendance and recording. But there are still some organizations that are using traditional methods for maintaining attendance records. A smart loT-based attendance system can improve the effectiveness of work in the industry. The purpose of this study is to design a system that would be used for fingerprint attendance. This system consists of ESP 8266, R307 Fingerprint Sensor and OLED Display. The ESP8266 WiFi module will collect fingerprint data from multiple users and send it over the internet. The experimental study showed the designed system has a high level of efficiency and 99.9% accuracy. The designed system completed attendance in 7.86 seconds on average, which is quicker than many other systems in use. The outcome also demonstrates a trustworthy, well-secured system that can prevent impersonation. Novelty In our system is that we have allow access to attendance records from anywhere, and provide real-time data to the management. We have also used biometric technology which allows for a more accurate and secure way to track attendance, as it uses unique physical characteristics of an individual to identify them.","PeriodicalId":441215,"journal":{"name":"2023 International Conference on Emerging Smart Computing and Informatics (ESCI)","volume":"79 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"IoT based Smart Attendance System\",\"authors\":\"Prajwal Gujarkar, Sarthak Lonkar, T. Jain, Shubham Nigal, Pramod Patil, Pallavi Deshpande, Ketki P. Kshirsagar, Shraddha K. Habbu, Gauri Ghule, A. Ratnaparkhi\",\"doi\":\"10.1109/ESCI56872.2023.10099839\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Nowadays, as attendance is taken using the tra-ditional pen and paper method, it increases the workload for employees and employers. This increases the cost of maintaining records and will also increase the manipulation in the system. So, there is a dire need of proper attendance management system. As it will help in Accurate tracking, increase productivity and reduces time for marking attendance. As the world around us becomes more modern, organizations are adopting more advanced methods for managing attendance and recording. But there are still some organizations that are using traditional methods for maintaining attendance records. A smart loT-based attendance system can improve the effectiveness of work in the industry. The purpose of this study is to design a system that would be used for fingerprint attendance. This system consists of ESP 8266, R307 Fingerprint Sensor and OLED Display. The ESP8266 WiFi module will collect fingerprint data from multiple users and send it over the internet. The experimental study showed the designed system has a high level of efficiency and 99.9% accuracy. The designed system completed attendance in 7.86 seconds on average, which is quicker than many other systems in use. The outcome also demonstrates a trustworthy, well-secured system that can prevent impersonation. Novelty In our system is that we have allow access to attendance records from anywhere, and provide real-time data to the management. We have also used biometric technology which allows for a more accurate and secure way to track attendance, as it uses unique physical characteristics of an individual to identify them.\",\"PeriodicalId\":441215,\"journal\":{\"name\":\"2023 International Conference on Emerging Smart Computing and Informatics (ESCI)\",\"volume\":\"79 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-03-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2023 International Conference on Emerging Smart Computing and Informatics (ESCI)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ESCI56872.2023.10099839\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2023 International Conference on Emerging Smart Computing and Informatics (ESCI)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ESCI56872.2023.10099839","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

摘要

如今,由于使用传统的纸笔考勤,增加了员工和雇主的工作量。这增加了维护记录的成本,也将增加系统中的操作。因此,迫切需要一个合适的考勤管理系统。因为它将有助于准确跟踪,提高生产力和减少标记出勤的时间。随着我们周围的世界变得越来越现代化,组织正在采用更先进的方法来管理出勤和记录。但仍有一些组织使用传统的方法来保存考勤记录。智能考勤系统可以提高行业的工作效率。本研究的目的是设计一个指纹考勤系统。该系统由ESP 8266、R307指纹传感器和OLED显示屏组成。ESP8266 WiFi模块将收集多个用户的指纹数据,并通过互联网发送。实验研究表明,所设计的系统具有较高的效率和99.9%的准确率。设计的考勤系统平均考勤时间为7.86秒,比目前使用的许多系统都要快。结果还展示了一个可信赖的、安全良好的系统,可以防止冒充。我们系统的新颖之处在于,我们可以从任何地方访问考勤记录,并向管理层提供实时数据。我们还使用了生物识别技术,这种技术可以更准确、更安全地跟踪出勤情况,因为它使用个人独特的身体特征来识别他们。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
IoT based Smart Attendance System
Nowadays, as attendance is taken using the tra-ditional pen and paper method, it increases the workload for employees and employers. This increases the cost of maintaining records and will also increase the manipulation in the system. So, there is a dire need of proper attendance management system. As it will help in Accurate tracking, increase productivity and reduces time for marking attendance. As the world around us becomes more modern, organizations are adopting more advanced methods for managing attendance and recording. But there are still some organizations that are using traditional methods for maintaining attendance records. A smart loT-based attendance system can improve the effectiveness of work in the industry. The purpose of this study is to design a system that would be used for fingerprint attendance. This system consists of ESP 8266, R307 Fingerprint Sensor and OLED Display. The ESP8266 WiFi module will collect fingerprint data from multiple users and send it over the internet. The experimental study showed the designed system has a high level of efficiency and 99.9% accuracy. The designed system completed attendance in 7.86 seconds on average, which is quicker than many other systems in use. The outcome also demonstrates a trustworthy, well-secured system that can prevent impersonation. Novelty In our system is that we have allow access to attendance records from anywhere, and provide real-time data to the management. We have also used biometric technology which allows for a more accurate and secure way to track attendance, as it uses unique physical characteristics of an individual to identify them.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
A Novel Approach to Maze Solving Algorithm Android Based Smart Appointment System (SAS) for Booking and Interacting with Teacher for Counselling A Compact Asymmetric Coplanar Strip (ACS) Antenna for WLAN and Wi-Fi Applications Insight on Human Activity Recognition Using the Deep Learning Approach Patients' Health Analysis using Machine Learning
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1