Implementasi Metode Unsupervised Learning Pada Sistem Keamanan Dengan Optimalisasi Penyimpanan Kamera IP

Implementing Unsupervised Learning Method in Security System With IP Camera Storage Optimization

  • Desta Yolanda Universitas Andalas
  • Mohammad Hafiz Hersyah Universitas Andalas
  • Eno Marozi Universitas Andalas
Keywords: Face Recognition, CCTV, Unsupervised Learning, Raspberry Pi, Datasets, IP Forwarding


Security monitoring systems using face recognition can be applied to CCTV or IP cameras. This is intended to improve the security system and make it easier for users to track criminals is theft. The experiment was carried out by detecting human faces for 24 hours using different cameras, namely an HD camera that was active during the day and a Night Vision camera that was active at night. The application of Unsupervised Learning method with the concept of an image cluster, aims to distinguish the faces of known or unknown people according to the dataset built in the Raspberry Pi 4. The user interface media of this system is a web-based application built with Python Flask and Python MySQL. This application can be accessed using the domain provided by the IP Forwarding device which can be accessed anywhere. According to the test results on optimization of storage, the system is able to save files only when a face is detected with an average file size of ± 2.28 MB for 1x24 hours of streaming. So that this storage process becomes more efficient and economical compared to the storage process for CCTV or IP cameras in general.


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How to Cite
Desta Yolanda, Mohammad Hafiz Hersyah, & Eno Marozi. (2021). Implementasi Metode Unsupervised Learning Pada Sistem Keamanan Dengan Optimalisasi Penyimpanan Kamera IP . Jurnal RESTI (Rekayasa Sistem Dan Teknologi Informasi), 5(6), 1099 - 1105.
Artikel Teknologi Informasi