PROTOTIPE SISTEM DETEKSI SUHU TUBUH DAN MASKER WAJAH MENGGUNAKAN ALGORITMA LOCAL BINARY PATTERN (LBP) DAN ARDUINO NANO
Abstract
The COVID-19 pandemic has changed the lifestyle of everyone around the world. In this change, wearing a mask is very important for every individual. Detection of people not wearing masks is a challenge as the outbreak of the Coronavirus pandemic has created large populations. In addition, detection of body temperature is also very important because one of the symptoms of COVID-19 is a high body temperature, therefore an effective method against the virus is to use a face mask and check body temperature in real time, and which will be the main focus in this prototype. how the LBP Algorithm can detect the use of masks and the Arduino Nano design with an infrared camera to measure body temperature which can be implemented in public places as a digital scanning tool. This testing prototype aims to be used in evaluating, preventing, and planning actions against COVID-19 and maintaining a distance between officers and the public in an environment where masks are mandatory and normal body temperature is required. The steps for building the model are collecting data, pre-processing, testing the model, and implementing the model. The results of this prototype test show an F1 score of 0.99 accuracy for mask detection and body temperature measurement in real time every second in degrees Celsius (C) with the highest average percentage error of 3.10% at a distance of 4 meters.
References
D. S. Hui et al., “The continuing 2019-nCoV epidemic threat of novel coronaviruses to global health — The latest 2019 novel coronavirus outbreak in Wuhan, China,” Int. J. Infect. Dis., vol. 91, pp. 264–266, 2020.
H. Nishiura, N. M. Linton, and A. R. Akhmetzhanov, “Serial interval of novel coronavirus (COVID-19) infections,” Int. J. Infect. Dis., vol. 93, pp. 284–286, 2020.
N. Zhi et al., “Treatment of pulmonary fibrosis in one convalescent patient with corona virus disease 2019 by oral traditional Chinese medicine decoction: A case report,” J. Integr. Med., no. xxxx, 2020.
M. Abdul, R. Irham, and D. A. Prasetya, “Untuk Kendali Pintu Otomatis Berbasis Deep Learning,” Simp. Nas. RAPI XIX, pp. 47–55, 2020.
M. Loey, G. Manogaran, M. H. N. Taha, and N. E. M. Khalifa, “Fighting against COVID-19: A novel deep learning model based on YOLO-v2 with ResNet-50 for medical face mask detection,” Sustain. Cities Soc., vol. 65, no. June 2020, p. 102600, 2021.
P. Nagrath, R. Jain, A. Madan, R. Arora, P. Kataria, and J. Hemanth, “SSDMNV2: A real time DNN-based face mask detection system using single shot multibox detector and MobileNetV2,” Sustain. Cities Soc., vol. 66, no. December 2020, p. 102692, 2021.
S. Yang, P. Luo, C. C. Loy, and X. Tang, “From facial parts responses to face detection: A deep learning approach,” Proc. IEEE Int. Conf. Comput. Vis., vol. 2015 Inter, no. 3, pp. 3676–3684, 2015.
S. Meivel, K. I. Devi, S. U. Maheswari, and J. V. Menaka, “Materials Today : Proceedings Real time data analysis of face mask detection and social distance measurement using Matlab,” Mater. Today Proc., no. xxxx, 2021.
Q. Chen and L. Sang, “Face-mask recognition for fraud prevention using Gaussian mixture model,” J. Vis. Commun. Image Represent., vol. 55, pp. 795–801, 2018.
Farady, C. Y. Lin, A. Rojanasarit, K. Prompol, and F. Akhyar, “Mask Classification and Head Temperature Detection Combined with Deep Learning Networks,” 2020 2nd Int. Conf. Broadband Commun. Wirel. Sensors Powering, BCWSP 2020, pp. 74–78, 2020.
K. Naveenkumar, S. Surya, M. N. S. S, S. Suranthar, and M. K. A, “Automatic Covid-19 Face Mask And Body Temperature Detection With,” vol. 9, no. 4, pp. 255–259, 2021.
Sorto, T. Marquez, A. Carrasco, and J. Ordoñez, “Face Recognition and Temperature Data Acquisition for COVID-19 Patients in Honduras,” J. Phys. Conf. Ser., vol. 1710, no. 1, 2020.
R. Purwati and G. Ariyanto, “Pengenalan Wajah Manusia berbasis Algoritma Local Binary Pattern,” Emit. J. Tek. Elektro, vol. 17, no. 2, pp. 29–38, 2017.
M. Safitri and G. A. Dinata, “Non-Contact Thermometer Berbasis Infra Merah,” Simetris J. Tek. Mesin, Elektro dan Ilmu Komput., vol. 10, no. 1, pp. 21–26, 2019.
U. Achlison, “Analisis Implementasi Pengukuran Suhu Tubuh Manusia dalam Pandemi Covid-19 di Indonesia,” J. Ilm. Komput. Graf., vol. 13, no. 2, pp. 102–106, 2020
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