HARDWARE DESIGN OF THE TOUCHLESS HAND CODE AND CONVOLUTIONAL NEURAL NETWORKS - BASED AUTOMATIC DOOR SECURITY SYSTEM

Surya Prihanto; Nazrul Effendy; Nopriadi Nopriadi

doi:10.52436/1.jutif.2023.4.6.1117

Surya Prihanto Intelligent and Embedded System Research Group, Departemen Teknik Nuklir dan Teknik Fisika, Fakultas Teknik, Universitas Gadjah Mada, Indonesia
Nazrul Effendy Intelligent and Embedded System Research Group, Departemen Teknik Nuklir dan Teknik Fisika, Fakultas Teknik, Universitas Gadjah Mada, Indonesia
Nopriadi Intelligent and Embedded System Research Group, Departemen Teknik Nuklir dan Teknik Fisika, Fakultas Teknik, Universitas Gadjah Mada, Indonesia

DOI: https://doi.org/10.52436/1.jutif.2023.4.6.1117

Keywords: Arduino, Automatic door, Convolutional Neural Networks, Hand Code, Virus

Abstract

The spread of viruses and bacteria through touching door surfaces is essential in maintaining public hygiene and health. In this context, a hand-coded touchless automatic door hardware design has been developed to reduce the spread of diseases through touch. This research aims to create a plan that includes interface development and hardware design to open and close doors automatically without contact. In this research, the automatic door hardware response is tested based on the numeric input from the hand code represented by the numeric database. The input and output control is connected to Python's graphical user interface (GUI). The GUI system design involves tools to connect the Python programming language and the Arduino microcontroller. Based on the experimental results, the hardware design of the automatic door security system based on hand code and Convolutional Neural Networks functions appropriately.

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