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All Journal Bulletin of Electrical Engineering and Informatics Bulletin of Electrical Engineering and Informatics Emerging Science Journal
Sheroz Khan
International Islamic University Malaysia
Electrical & Electronics Engineering Environmental Science

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Journal : Emerging Science Journal

 1 
Real-Time Monitoring of COVID-19 SOP in Public Gathering Using Deep Learning Technique Khel, Muhammad Haris Kaka; Kadir, Kushsairy; Albattah, Waleed; Khan, Sheroz; Noor, MNMM; Nasir, Haidawati; Habib, Shabana; Islam, Muhammad; Khan, Akbar
Emerging Science Journal Vol. 5 (2021): Special Issue "COVID-19: Emerging Research"
Publisher : Ital Publication

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28991/esj-2021-SPER-14

Abstract

Crowd management has attracted serious attention under the prevailing pandemic conditions of COVID-19, emphasizing that sick persons do not become a source of virus transmission. World Health Organization (WHO) guidelines include maintaining a safe distance and wearing a mask in gatherings as part of standard operating procedures (SOP), considered thus far the most effective preventive measures to protect against COVID-19. Several methods and strategies have been used to construct various face detection and social distance detection models. In this paper, a deep learning model is presented to detect people without masks and those not keeping a safe distance to contain the virus. It also counts individuals who violate the SOP. The proposed model employs the Single Shot Multi-box Detector as a feature extractor, followed by Spatial Pyramid Pooling (SPP) to integrate the extracted features to improve the model's detecting capabilities. The MobilenetV2 architecture as a framework for the classifier makes the model highly light, fast, and computationally efficient, allowing it to be employed in embedded devices to do real-time mask and social distance detection, which is the sole objective of this research. This paper's technique yields an accuracy score of 99% and reduces the loss to 0.04%. Doi: 10.28991/esj-2021-SPER-14 Full Text: PDF
Acoustic Photometry of Biomedical Parameters for Association with Diabetes and Covid-19 Imad, Abdulrahman; Malik, Noreha Abdul; Hamida, Belal Ahmed; Hong Seng, Gan Hong; Khan, Sheroz
Emerging Science Journal Vol. 6 (2022): Special Issue "COVID-19: Emerging Research"
Publisher : Ital Publication

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28991/esj-2022-SPER-04

Abstract

Because of their mortality rate, diabetes and COVID-19 are serious diseases. Moreover, people with diabetes are at a higher risk of developing COVID-19 complications. This article therefore proposes a single, non-invasive system that can help people with diabetes and COVID-19 to monitor their health parameters by measuring oxygen saturation (SPO2), heart rate, and body temperature. This is in contrast to other pulse oximeters and previous work reported in the literature. A Max30102 sensor, consisting of two light-emitting diodes (LEDs), can serve as a transmission spectrum to enable three synchronous parameter measurements. Hence, the Max30102 sensor facilitates identification of the relationship between COVID-19 and diabetes in a cost-effective manner. Fifty subjects (20 healthy, 20 diabetic, and 10 with COVID-19), aged 18-61 years, were recruited to provide data on heart rate, body temperature, and oxygen saturation, measured in a variety of activities and scenarios. The results showed accuracy of ±97% for heart rate, ±98% for body temperature, and ±99% for oxygen saturation with an enhanced time efficiency of 5-7 seconds in contrast to a commercialized pulse oximeter, which took 10-12 seconds. The results were then compared with those of commercially available pulse oximetry (Oxitech Pulse Oximeter) and a thermometer (Medisana Infrared Thermometer). These results revealed that uncontrolled diabetes can be as dangerous as COVID-19 in terms of high resting heart rate and low oxygen saturation. Doi: 10.28991/esj-2022-SPER-04 Full Text: PDF
Co-Authors Aboadla, Ali Aboadla, Ezzidin Hassan Aboadla, Ezzidin Hassan Ahmed Shaikh, Faraz Albattah, Waleed Arfah Che Mustapha, Nurul Baillargeat, Dominique Bin Yaacob, Mashkuri Farhan Affendi bin Yunos, Muhammad H.M. Zahirul Alam, A. Habaebi, Mohamed H. Habib, Shabana Hadi Habaebi, Mohamed Hamida, Belal A. Hamida, Belal Ahmed Hong Seng, Gan Hong Imad, Abdulrahman Kadir, Kushsairy Khan, Akbar Khel, Muhammad Haris Kaka Malik, Noreha Abdul Muhammad Islam, Muhammad Nasir, Haidawati Noor, MNMM Nurashikin Nordin, Anis Shah, Jawad Shahid, Zeeshan Teddy Surya Gunawan Wong Azman, Amelia Yaacob, Mashkuri Bin Zahirul Alam, AHM