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All Journal Khazanah Informatika: Jurnal Ilmu Komputer dan Informatika Indonesian Journal of Artificial Intelligence and Data Mining Jurnal Teknologi Terpadu JTIULM (Jurnal Teknologi Informasi Universitas Lambung Mangkurat) JITEL (Jurnal Ilmiah Telekomunikasi, Elektronika, dan Listrik Tenaga)
Martin Clinton Tosima Manullang
Institut Teknologi Sumatera
Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Energy Engineering

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Journal : Khazanah Informatika: Jurnal Ilmu Komputer dan Informatika

 1 
Automatic Gate for Body Temperature Check and Masks Wearing Compliance Using an Embedded System and Deep Learning Rahman Indra Kesuma; Rivaldo Fernandes; Martin Clinton Tosima Manullang
Khazanah Informatika Vol. 8 No. 1 April 2022
Publisher : Department of Informatics, Universitas Muhammadiyah Surakarta, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23917/khif.v8i1.15205

Abstract

A new coronavirus variant known as n-Cov has emerged with a fast transmission rate. The World Health Organization (WHO) has declared the related disease or COVID-19 as a global pandemic that requires special handling. Many parties have shown efforts to reduce virus transmission by implementing health protocols and adapting a new normal lifestyle. Implementation of the health protocol creates new problems, especially in the health check at the main entrance. The officers in charge of measuring body temperature are at risk of getting infected by COVID. Such a measurement is prone to errors. This study proposed a solution to build an automatic gate system that worked based on the new normal health protocol. The system utilizes the MLX90614 contactless temperature sensor to probe body temperature. It applies deep learning implementing the Convolutional Neural Network (CNN) algorithm with the MobileNetV2 architecture as a determinant of the conditions of wearing face masks. The system is equipped with an IoT-based remote controller to control the gate. Experimental results prove that the system works well. Temperature measurement takes a response time of 20 seconds for each user with 99% accuracy for the sensor and masks classification model.
Co-Authors Istighfariza Aprini Jonathan Simanjuntak Muhamad Arwin Wijaya Nova Resfita Rahman Indra Kesuma Raidah Hanifah Ramdani, Ahmad Luky Rivaldo Fernandes