PERTANIKA JOURNAL OF SCIENCE AND TECHNOLOGY

Protective face mask identification is essential today to users as it is a prominent protective wearable to shield from being infected by Covid-19 viruses. Protective face masks consist of layers of fibers that can capture large respiratory droplets and microscopic particles such as viruses or dust. Thus, mask filtration efficiency results depend on the materials used for each layer. Detail about mask description and efficiency are still anonymous to users, which is vital in this COVID-19. Therefore, this paper reviews designing 3D augmented reality for the protective mask with its detail parameter and mask sizing recommendation on android mobile. About 73 articles on the protective face mask, 3D augmented reality modeling, masks inward leakage testing, breathing resistance, and measuring faces have been reviewed. The result examines the existing protective face mask, inward leakage testing parameter, breathing resistance parameters, 3D modeling techniques, mobile applications, and the application used for measuring faces. The identified result shows six recent and familiar masks with 8% of arithmetic mean for inward leakage testing. The best flow efficiency is determined a 0.3 Microns bigger than 95%. The result also shows a detailed parameter for inward leakage testing in terms of inhalation resistance and flow rate. The comparison for 3D AR parameters is identified for application type, evaluated parameter, technical support parameter, AR platform, and software. This research is significant for developing AR mobile applications that ease and transparency information to the community for safety and health issues in Malaysia.

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