Roboswab: A Covid-19 Thermal Imaging Detector Based on Oral and Facial Temperatures

I Nyoman Gede Arya Astawa - Politeknik Negeri Bali, Badung, 80361, Indonesia
I.D.G Ary Subagia - Universitas Udayana, Badung, Bali, 80361,Indonesia
Felipe P. Vista IV - Northern Iloilo State University, Iloilo,5017, Philippines
IGAK Cathur Adhi - Mataram University, Mataram, 83126, Indonesia
I Made Ari Dwi Suta Atmaja - Politeknik Negeri Bali, Badung, 80361, Indonesia

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The SARS-CoV-2 virus has been the precursor of the coronavirus disease (COVID-19). The symptoms of COVID-19 begin with the common cold and then become very severe, such as those of Middle East Respiratory Syndrome (MERS) and Severe Acute Respiratory Syndrome (SARS). Currently, polymerase chain reaction (PCR) is used to detect COVID-19 accurately, but it causes some side effects to the patient when the test is performed. Therefore, the proposed "Roboswab" was developed that uses thermal imaging to measure non-contact facial and oral temperature. This study focuses on the performance of the proposed equipment in measuring facial and oral temperature from various distances. Face detection also involves checking whether the subject is wearing a mask or not. Image processing methods with thermal imaging and robotic manipulators are integrated into a contact-free detector that is inexpensive, accurate, and painless. This research has successfully detected masked or non-masked faces and accurately detected facial temperature. The results showed that the accurate measurement of facial temperature with a mask is 90% with an error of +/- 0.05%, while it was 100% without a mask. On the other hand, the oral temperature was measured with 97% accuracy and an error of less than 5%. The optimal distance of the Roboswab to the face for measuring temperature is an average of 60 cm. The Roboswab tool equipped with masked or non-masked face detection can be used for early detection of COVID-19 without direct contact with patients.


Thermal imaging; face and oral temperature; COVID-19; mask; roboswab

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N. Y. Damo, J. P. Porotu’o, G. I. Rambert, and F. E. S. Rares, “Diagnostik Coronavirus Disease 2019 (COVID-19) dengan Pemeriksaan Laboratorium Mikrobiologi Klinik,†Jurnal e-Biomedik, vol. 9, no. 1, pp. 77–86, 2021, doi: 10.35790/ebm.v9i1.31899.

M. J. Thomas, V. Lal, A. K. Baby, M. Rabeeh VP, A. James, and A. K. Raj, “Can technological advancements help to alleviate COVID-19 pandemic? a review,†Journal of Biomedical Informatics, vol. 117, p. 103787, 2021, doi: 10.1016/j.jbi.2021.103787.

A. F. Henwood, “Coronavirus disinfection in histopathology,†Journal of Histotechnology, vol. 43, no. 2, pp. 102–104, 2020, doi: 10.1080/01478885.2020.1734718.

W. Ding, J. Nayak, H. Swapnarekha, A. Abraham, B. Naik, and D. Pelusi, “Fusion of intelligent learning for COVID-19: A state-of-the-art review and analysis on real medical data,†Neurocomputing, vol. 457, pp. 40–66, 2021, doi: 10.1016/j.neucom.2021.06.024.

N. Van Doremalen, T. Bushmaker, and V. J. Munster, “Stability of Middle East respiratory syndrome coronavirus ( MERS-CoV ) under different environmental conditions,†vol. 2009, pp. 1–4, 2013.

P. Bhairawa, I. Widianingsih, S. Ningrum, S. Suryanto, and Y. Rianto, “Overcoming the COVID-19 Pandemic in Indonesia : A Science , technology , and innovation ( STI ) policy perspective,†Health Policy and Technology, vol. 11, p. 100650, 2022.

M. Ahmad et al., “Industry 4.0 technologies and their applications in fighting COVID-19 pandemic using deep learning techniques,†Computers in Biology and Medicine, vol. 145, no. March, 2022, doi: 10.1016/j.compbiomed.2022.105418.

M. Abdel-Basset, V. Chang, and N. A. Nabeeh, “An intelligent framework using disruptive technologies for COVID-19 analysis,†Technological Forecasting and Social Change, vol. 163, no. July 2020, 2021, doi: 10.1016/j.techfore.2020.120431.

J. Andreani et al., “Evaluation of six commercial SARS-CoV-2 rapid antigen tests in nasopharyngeal swabs: Better knowledge for better patient management?,†Journal of Clinical Virology, vol. 143, no. April, pp. 2–7, 2021, doi: 10.1016/j.jcv.2021.104947.

G. C. K. Mak, A. Y. Y. Ng, E. T. K. Lam, R. C. W. Chan, and D. N. C. Tsang, “Assessment of SARS-CoV-2 viral loads in combined nasal-and-throat swabs collected from COVID-19 individuals under the Universal Community Testing Programme in Hong Kong,†Journal of Virological Methods, vol. 300, no. October 2021, p. 114396, 2022, doi: 10.1016/j.jviromet.2021.114396.

Y. Uwamino et al., “Accuracy of rapid antigen detection test for nasopharyngeal swab specimens and saliva samples in comparison with RT-PCR and viral culture for SARS-CoV-2 detection,†Journal of Infection and Chemotherapy, vol. 27, no. 7, pp. 1058–1062, 2021, doi: 10.1016/j.jiac.2021.04.010.

A. Kline et al., “Dacron swab and PBS are acceptable alternatives to flocked swab and viral transport media for SARS-CoV-2,†Diagnostic Microbiology and Infectious Disease, vol. 99, no. 1, p. 115209, 2021, doi: 10.1016/j.diagmicrobio.2020.115209.

L. Jansson, Y. Akel, R. Eriksson, M. Lavander, and J. Hedman, “Impact of swab material on microbial surface sampling,†Journal of Microbiological Methods, vol. 176, no. July, 2020, doi: 10.1016/j.mimet.2020.106006.

S. Wang, K. Wang, H. Liu, and Z. Hou, “Design of a low-cost miniature robot to assist the COVID-19 nasopharyngeal swab sampling,†IEEE Transactions on Medical Robotics and Bionics, vol. 3, no. 1, pp. 1–5, 2021, doi: 10.1109/tmrb.2020.3036461.

X. V. Wang and L. Wang, “A literature survey of the robotic technologies during the COVID-19 pandemic,†Journal of Manufacturing Systems, vol. 60, pp. 823–836, 2021, doi: 10.1016/j.jmsy.2021.02.005.

M. Podpora, A. Gardecki, R. Beniak, B. Klin, J. L. Vicario, and A. Kawala-Sterniuk, “Human interaction smart subsystem—extending speech-based human-robot interaction systems with an implementation of external smart sensors,†Sensors (Switzerland), vol. 20, no. 8, 2020, doi: 10.3390/s20082376.

Y. Chen et al., “A collaborative robot for COVID-19 oropharyngeal swabbing,†Robotics and Autonomous Systems, vol. 148, p. 103917, 2022, doi: 10.1016/j.robot.2021.103917.

M. Abdel-Basset, K. A. Eldrandaly, L. A. Shawky, M. Elhoseny, and N. M. AbdelAziz, “Hybrid Computational Intelligence Algorithm for Autonomous Handling of COVID-19 Pandemic Emergency in Smart Cities,†Sustainable Cities and Society, vol. 76, no. October 2021, 2022, doi: 10.1016/j.scs.2021.103430.

P. Cinquin, “How today’s robots work and perspectives for the future.,†Journal of visceral surgery, vol. 148, no. 5 Suppl, 2011, doi: 10.1016/j.jviscsurg.2011.08.003.

M. Liu et al., “Value of swab types and collection time on SARS-COV-2 detection using RT-PCR assay,†Journal of Virological Methods, vol. 286, no. May, 2020, doi: 10.1016/j.jviromet.2020.113974.

Y. Li, C. Lin, Y. Peng, J. He, and Y. Yang, “High-sensitivity and point-of-care detection of SARS-CoV-2 from nasal and throat swabs by magnetic SERS biosensor,†Sensors and Actuators B: Chemical, vol. 365, no. April, p. 131974, 2022, doi: 10.1016/j.snb.2022.131974.

E. Mbunge, I. Chitungo, and T. Dzinamarira, “Unbundling the significance of cognitive robots and drones deployed to tackle COVID-19 pandemic: A rapid review to unpack emerging opportunities to improve healthcare in sub-Saharan Africa,†Cognitive Robotics, vol. 1, no. September, pp. 205–213, 2021, doi: 10.1016/j.cogr.2021.11.001.

A. L. Wicaksana, N. D. Kusumawati, E. P. Wibowo, and H. Nirwati, “Development of a COVID-19 University-Based Clinic in Indonesia:A Pilot Project of The Gadjah Mada Electronic Nose Center,†Open Access Macedonian Journal of Medical Sciences, vol. 10, no. February, pp. 286–293, 2022, doi: 10.3889/oamjms.2022.8391.

L. Maurya, P. Mahapatra, and D. Chawla, “Non-contact breathing monitoring by integrating RGB and thermal imaging via RGB-thermal image registration,†Biocybernetics and Biomedical Engineering, vol. 41, no. 3, pp. 1107–1122, 2021, doi: 10.1016/j.bbe.2021.07.002.

A. Sharma and A. R. Yadav, “Image processing based body temperature estimation using thermal video sequence,†Proceedings of the International Conference on Computing Methodologies and Communication, ICCMC 2017, vol. 2018-Janua, no. Iccmc, pp. 846–852, 2018, doi: 10.1109/ICCMC.2017.8282585.

Y. Qu, Y. Meng, H. Fan, and R. X. Xu, “Low-cost thermal imaging with machine learning for non-invasive diagnosis and therapeutic monitoring of pneumonia,†Infrared Physics and Technology, vol. 123, p. 104201, 2022, doi: 10.1016/j.infrared.2022.104201.

X. Wang, X. Zhao, and Z. Wu, “Fatigue degradation and life prediction of basalt fiber-reinforced polymer composites after saltwater corrosion,†Materials and Design, vol. 163, p. 107529, 2019, doi: 10.1016/j.matdes.2018.12.001.

J. Yi, H. Zhang, J. Mao, Y. Chen, H. Zhong, and Y. Wang, “Review on the COVID-19 pandemic prevention and control system based on AI,†Engineering Applications of Artificial Intelligence, vol. 114, p. 105184, 2022, doi: 10.1016/j.engappai.2022.105184.

M. Alhasan and M. Hasaneen, “Digital imaging, technologies and artificial intelligence applications during COVID-19 pandemic,†Computerized Medical Imaging and Graphics, vol. 91, no. December 2020, p. 101933, 2021, doi: 10.1016/j.compmedimag.2021.101933.

S. Hassantabar, M. Ahmadi, and A. Sharifi, “Diagnosis and detection of infected tissue of COVID-19 patients based on lung x-ray image using convolutional neural network approaches,†Chaos, Solitons and Fractals, vol. 140, 2020, doi: 10.1016/j.chaos.2020.110170.

A. Barnawi, P. Chhikara, R. Tekchandani, N. Kumar, and B. Alzahrani, “Artificial intelligence-enabled Internet of Things-based system for COVID-19 screening using aerial thermal imaging,†Future Generation Computer Systems, vol. 124, pp. 119–132, 2021, doi: 10.1016/j.future.2021.05.019.

A. Sorto, T. Marquez, A. Carrasco, and J. Ordoñez, “Face Recognition and Temperature Data Acquisition for COVID-19 Patients in Honduras,†Journal of Physics: Conference Series, vol. 1710, no. 1, 2020, doi: 10.1088/1742-6596/1710/1/012009.

A. Ghahramani, G. Castro, B. Becerik-Gerber, and X. Yu, “Infrared thermography of human face for monitoring thermoregulation performance and estimating personal thermal comfort,†Building and Environment, vol. 109, pp. 1–11, 2016, doi:

J.-H. Choi and V. Loftness, “Investigation of human body skin temperatures as a bio-signal to indicate overall thermal sensations,†Building and Environment, vol. 58, pp. 258–269, 2012, doi:

B. B. Lahiri et al., “Infrared thermography based studies on the effect of age on localized cold stress induced thermoregulation in human,†Infrared Physics & Technology, vol. 76, pp. 592–602, 2016, doi:

K. H. Chan, J. S. M. Peiris, S. Y. Lam, L. L. M. Poon, K. Y. Yuen, and W. H. Seto, “The effects of temperature and relative humidity on the viability of the SARS coronavirus,†Advances in Virology, vol. 2011, 2011, doi: 10.1155/2011/734690.

C. W. Chan and C. H. Huang, “Comparison of different novel COVID-19 swab testing devices,†Journal of the Formosan Medical Association, vol. 121, no. 4, pp. 865–867, 2022, doi: 10.1016/j.jfma.2021.10.019.

A. S. Adly, A. S. Adly, and M. S. Adly, “Approaches Based on Artificial Intelligence and the Internet of Intelligent Things to Prevent the Spread of COVID-19: Scoping Review,†J Med Internet Res, vol. 22, no. 8, Aug. 2020, doi: 10.2196/19104.

O. S. Albahri et al., “Systematic review of artificial intelligence techniques in the detection and classification of COVID-19 medical images in terms of evaluation and benchmarking: Taxonomy analysis, challenges, future solutions and methodological aspects,†Journal of Infection and Public Health, vol. 13, no. 10, pp. 1381–1396, 2020, doi: