Luoli, Amit Yadav, Asif Khan, Naushad Varish, Priyanka Singh & Hiren Kumar Thakkar2024-10-242023978-981-99-4071-4https://doi.org/10.1007/978-981-99-4071-4_56http://136.232.12.194:4000/handle/123456789/934International Conference on Innovative Computing and Communications Proceedings of ICICC 2023, Volume 2 Conference proceedingsThis paper designs an epidemic prevention and control mask wearing detection system based on STM32, which is used to monitor the situation of people wearing masks. Tiny-YOLO detection algorithm is adopted in the system, combined with image recognition technology, and two kinds of image data with and without masks are used for network training. Then, the trained model can be used to carry out real-time automatic supervision on the wearing of masks in the surveillance video. When the wrong wearing or not wearing masks are detected, the buzzer will send an alarm, so as to effectively monitor the wearing of masks and remind relevant personnel to wear masks correctly.en-USInnovative Communication Networks and SecurityInnovative ComputingInternet of Things (IoT)Machine LearningMask Wearing Detection System for Epidemic Control Based on STM32Book chapter