Object Detection Based Security System Using Machine learning algorthim and Raspberry Pi

Hasan Hashib, M. Leon, A. Salaque
{"title":"Object Detection Based Security System Using Machine learning algorthim and Raspberry Pi","authors":"Hasan Hashib, M. Leon, A. Salaque","doi":"10.1109/IC4ME247184.2019.9036531","DOIUrl":null,"url":null,"abstract":"Conventional security systems that use surveillance cameras to monitor the property lacks the ability to notify the security administrator in the event of trespassing. A security camera when used along with a digital video recorder (DVR) is only effective as a source to gather evidence unless the video feed is constantly being monitored by a dedicated personnel. This paper discusses the implementation of a cost effective, intelligent security system that overcomes drawbacks of conventional security cameras by utilizing a machine learning and Viola-Jones algorithm under image processing literature to identify trespassers and multiple object detection in real time. The paper presents the design and implementation details of the intelligent object detection based security system in two different computing environment, MATLAB and Python respectively using Raspberry Pi 3 B single board computer. The security system is capable of alerting the security administrator through email via internet while activating an alarm locally.","PeriodicalId":368690,"journal":{"name":"2019 International Conference on Computer, Communication, Chemical, Materials and Electronic Engineering (IC4ME2)","volume":"60 6 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 International Conference on Computer, Communication, Chemical, Materials and Electronic Engineering (IC4ME2)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IC4ME247184.2019.9036531","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1

Abstract

Conventional security systems that use surveillance cameras to monitor the property lacks the ability to notify the security administrator in the event of trespassing. A security camera when used along with a digital video recorder (DVR) is only effective as a source to gather evidence unless the video feed is constantly being monitored by a dedicated personnel. This paper discusses the implementation of a cost effective, intelligent security system that overcomes drawbacks of conventional security cameras by utilizing a machine learning and Viola-Jones algorithm under image processing literature to identify trespassers and multiple object detection in real time. The paper presents the design and implementation details of the intelligent object detection based security system in two different computing environment, MATLAB and Python respectively using Raspberry Pi 3 B single board computer. The security system is capable of alerting the security administrator through email via internet while activating an alarm locally.
基于机器学习算法和树莓派的目标检测安全系统
使用监控摄像头监控物业的传统安全系统缺乏在非法侵入事件中通知安全管理员的能力。当与数字视频录像机(DVR)一起使用时,安全摄像机只能作为有效的证据来源,除非视频馈送由专门人员持续监控。本文讨论了一种具有成本效益的智能安全系统的实现,该系统通过利用图像处理文献下的机器学习和Viola-Jones算法来实时识别入侵者和多目标检测,从而克服了传统安全摄像机的缺点。本文介绍了利用树莓派3b单板计算机在MATLAB和Python两种不同的计算环境下,基于智能目标检测的安防系统的设计与实现细节。安全系统能够在本地激活警报的同时,通过互联网通过电子邮件提醒安全管理员。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
自引率
0.00%
发文量
0
×
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
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
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 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信