Augmented reality is a ground-breaking technology that allows users to communicate with an enticing real-world experience to receive messages or knowledge. Today, mask inspection is essential to relay information to society through an augmented reality where extensive information about masks is required and identifying them is challenging. Furthermore, with augmented reality, society may have access to the fascinating way of getting information on the masks, assisting in spreading knowledge, particularly during this pandemic. The augmented reality on a visual inspection mask (ARVIM) was created utilizing 3D images on an Android smartphone platform. The models were created using Blender Animation and Unity 3D software. Vuforia Engine and Android Studio applications were used to build a personalized mobile Augmented Reality application. Google Cloud was used to store data that are accessible to users. ARVIM has facilitated teaching and interaction with 3D AR effects enjoyable for users. The analysis results on the use of ARVIM revealed that ARVIM obtained a high easiness rating of 80%. While 83% of respondents say ARVIM can help distinguish between different types of masks, 88% of respondents agreed that ARVIM's design is acceptable and approachable. This initiative enhances society's education in interactive and mixed-reality innovation settings through a long-distance and innovative teaching method that gives a comprehensive Google Platform experience.

The outbreak of COVID-19 has spread rapidly across the globe, affecting how people interact, work and experience their daily lifestyles. The face mask is essential to personal protective equipment (PPE) even though COVID-19 is endemic today. A face mask is required to protect humans, and its description is important. Augmented reality is one new attractive technology for distributing information. This research presents a 3D augmented reality mobile application that visualizes a protective face mask and its material layers called 3DAR-FML. It was designed by utilizing 3D marker-based images on an Android smartphone platform. Ten types of protective face masks and each layer were designed in 3D images using Blender Animation and Unity 3D software. Vuforia Engine applications were used to build a personalized mobile Augmented Reality application. This initiative educates society and markets products in interactive ways that allow visualization of the 3D model of various face masks from android phones. Results present that successful mobile apps were developed. A survey shows that 70% of respondents agreed on the design app based on menu interactivity. This app also has been identified as a helper tool for The National Institute for Occupational Safety and Health (NIOSH) agency Malaysia for safety and health apps for the market and public. This product is significant in societies to gain information on face mask characteristics that help to contribute content based on the standard mask in Malaysia.

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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.