Social Awareness and Safety Assistance of COVID-19 based on DLN face mask detection and AR Distancing - Tenriawaru, Andi; Basori, Ahmad Hoirul; Mansur, Andi Besse Firdausiah; Al-Qurashi, Qusai; Al-Muhaimeed, Abdullah; Al-Hazmi, Majid (Universitas Dharma Wacana, 2021)
The outbreak of coronavirus disease (COVID-19) has forced major countries to apply strict policy toward society. People must wear a facemask and always keep their distance from each other's to avoid virus contamination. Government employ officers to monitor citizen and warn them if not wearing a face mask. The warning message also spread through SMS and social media to ensure people about safety and awareness. This paper aims to provide face mask detection using the Deep Learning Network(DLN) and warning system through video stream input from CCTV or images then analyzed. If people not wearing a mask are detected, they will alert them through the speaker and remind them about a penalty. AR distancing very useful to give position toward violator location based on the detected person in a certain area. The system is designed to work intelligently and automatically without human intervention. With the accuracy of 99% recognition, it's expected that the system can help the government to increase people awareness toward the safety of themselves and people around them.