A Mobile Surveillance System with Face Detection and Recognition Abilities

This paper proposes a mobile surveillance system similar to an electronic dog which has the ability to move around a certain location all while detecting and recognizing the individuals and notifying the respective authorities about the detected person. The system uses an Arduino UNO microcontroller along with IR receiver and remote to function as a remote-controlled vehicle while also providing an option for automatic movement of the vehicle. The system also has an integrated camera that constantly feeds live video to a computer system. Haar-cascades take in the frames of videos and detect appearance of human face. Then, pretrained FaceNet Convolutional Neural Network (CNN) compares the detected face to the authorized faces in an attempt to recognize the face. The system also boasts the feature of email notification for which it employs the SMTP protocol to send an email with the detected face to the authorized personnel. The methods and techniques used to implement these features are presented in depth in this paper.

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Publication Details

Journal
KEC Journal of Science and Engineering
Published
2024-09-02
DOI
https://doi.org/10.3126/kjse.v8i1.69257
Primary Topic
Face recognition and analysis
Type
article
Field-Weighted Citation Impact
0.00
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article

A Mobile Surveillance System with Face Detection and Recognition Abilities

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KEC Journal of Science and Engineering
Face recognition and analysis
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A Mobile Surveillance System with Face Detection and Recognition Abilities

Paras Pujara, Prasamsha Dotel, Rajat Dulal, Suramya Pokharel, Suramya Sharma Dahal
article en

Abstract

This paper proposes a mobile surveillance system similar to an electronic dog which has the ability to move around a certain location all while detecting and recognizing the individuals and notifying the respective authorities about the detected person. The system uses an Arduino UNO microcontroller along with IR receiver and remote to function as a remote-controlled vehicle while also providing an option for automatic movement of the vehicle. The system also has an integrated camera that constantly feeds live video to a computer system. Haar-cascades take in the frames of videos and detect appearance of human face. Then, pretrained FaceNet Convolutional Neural Network (CNN) compares the detected face to the authorized faces in an attempt to recognize the face. The system also boasts the feature of email notification for which it employs the SMTP protocol to send an email with the detected face to the authorized personnel. The methods and techniques used to implement these features are presented in depth in this paper.

KEC Journal of Science and EngineeringVol. 8(1)
Kathmandu Medical College Teaching Hospital (NP)
Openalex Percentile: Top 87%
Face recognition and analysis
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