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Home Security against Human Intrusion using Raspberry Pi

Raju A Nadafa, Sanjeevakumar M. Hatture, Vasudha M Bonala, Susen P Naikb

2020Procedia Computer Science40 citationsDOIOpen Access PDF

Abstract

Technology has changed the world. There is a huge growth in technology connected to almost every field. The pace and diversity of advancement is very rapid. Hence, new technology and techniques are coming up and are put to use as per the need. In such advanced scenario, providing security to home has also become a major point of concern. Presently security cameras can be used for the same. But such cameras may be visible to intruders and there is possibility that cameras may be damaged. Hence, in order to serve the purpose, there is a need to find an alternative secure, accurate and quick method. Hence, an effort is made in this paper to design a home security system using Raspberry Pi. System requires Raspberry Pi, Camera, Touch screen and android mobile as hardware components. Python, Node.js and OpenCV libraries are used for software coding. Usually most of the intrusion detection systems click the photo of intruders as soon as the human is detected. But, such systems fail to click photos, so that the intruder can be identified (Face View Photo) and visible. In proposed system, a proper illustrative method is proposed so that the intrusion detection is accurate and photos thus captured are clear, so that intruder is clearly visible. The proposed system is designed as a smart mirror which will provide both information and home security. The system is developed to accept touch and mobile commands. As soon as the intrusion is detected, an alert message along with the identifiable and clear photo (Face view) of intruder will be sent to the owner’s/administrator’s mobile. The mirror owner can also see the video of deployed environment through the camera fitted on smart mirror.

Topics & Concepts

Computer scienceRaspberry piHome securityAndroid (operating system)Python (programming language)Computer securityIntrusion detection systemAndroid applicationSoftwareEmbedded systemInternet of ThingsOperating systemIoT-based Smart Home SystemsContext-Aware Activity Recognition SystemsVideo Surveillance and Tracking Methods
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