RANCANG BANGUN PROTOTYPE KUNCI PINTU PINTAR DENGAN SISTEM KEAMANAN FACE RECOGNITION MENGGUNAKAN ESP32 CAM DAN BERBASIS INTERNET OF EVERYTHING

Sayaf, Abdurrasyid (2022) RANCANG BANGUN PROTOTYPE KUNCI PINTU PINTAR DENGAN SISTEM KEAMANAN FACE RECOGNITION MENGGUNAKAN ESP32 CAM DAN BERBASIS INTERNET OF EVERYTHING. Skripsi thesis, Institut Teknologi Dirgantara Adisutjipto.

[img] Text (ABSTRAK)
17010027_ABSTRAK.pdf

Download (139kB)
[img] Text (BAB I)
17010027_BAB I.pdf

Download (14kB)
[img] Text (DAFTAR PUSTAKA)
17010027_DAFTAR PUSTAKA.pdf

Download (163kB)
[img] Text (FULL SKRIPSI)
17010027.pdf
Restricted to Repository staff only

Download (5MB)

Abstract

Acts of theft are so widely carried out, especially in homes or offices, one of the modes of operation is by breaking into conventional key security systems such as using duplicate keys. It is easy for thieves to steal valuables because the security system at the door of the house is not well protected. This causes the need for a solution related to a better door security system. Current technological advances have led to innovations to create a sophisticated door security system tool, namely the Face Recognition method. In this study, for face recognition using the Esp32 Cam module and for mechanical processes and indicators, they are processed using an Arduino Nano microcontroller. The results of the facial recognition process will be displayed on a 16x2 LCD. When a face is detected, it will go through the face ID adjustment process on the Esp32 Cam, then send a signal to the Arduino Nano for mechanical processing and display the facial recognition results on a 16x2 LCD. For Internet Of Everything, it uses Telegram media which receives messages and sends commands to Esp32 Cam and then sends signals to Arduino Nano for mechanical processing. The test result of registered faces, face recognition, and the internet of everything using telegram to get 100% accuracy. In facial expression recognition, it was found that flat face recognition was faster, namely 2.68 seconds. For facial recognition distance testing, it was found that a distance of 50 cm was recognized faster with a time delay of 3.24 seconds

Item Type: Thesis (Skripsi)
Subjects: T Technology > T Technology (General)
Divisions: Institut Teknologi Dirgantara Adisujtipto > Teknik Elektro
Depositing User: Mr Abdurrasyid safaf
Date Deposited: 27 Mar 2024 05:53
Last Modified: 27 Mar 2024 05:53
URI: http://eprints.stta.ac.id/id/eprint/1382

Actions (login required)

View Item View Item

Downloads

Downloads per month over past year