Epidemic Prevention System Based on Voice Recognition Combined with Intelligent Recognition of Mask and Helmet

ABSTRACT

At present, COVID-19 cross-infection is easy to occur in dense places such as elevators. There are no epidemic prevention measures for construction site elevators on the market, and most of them require manual temperature measurement and reminders to wear masks and helmets to avoid the spread of the epidemic. This paper designs an intelligent epidemic prevention system for the elevator ride process in a modern construction site environment, which can achieve non-contact human temperature measurement, mask and helmet recognition and voice call elevator function. The system uses Arduino UNO as the control core, Kendryte K210 as machine vision processing module, non-contact infrared temperature sensor MLX90614, and voice recognition sensor LD3320. The system has the functions of non-contact temperature detection, mask/helmet recognition(YOLOv3) and voice call elevator. Experimental results showed that the recognition accuracy rate of helmet, mask, voice call elevator is 91.5%, 92.0% and 93.0% respectively. The temperature measurement accuracy rate is 0.2ĝ., which can effectively prevent the spread of the epidemic caused by contact and breathing, and has the advantages of stable, intelligent, and safe work. © 2021 ACM.