ABSTRACT
Emergencies such as the COVID-19 and natural disasters have brought severe ordeals to the current grid emergency dispatch system, and there is an urgent need to improve and consummate the existing backup dispatch system. This paper firstly analyzes the existing three kinds of backup dispatch systems and their advantages and disadvantages, and then compares in detail the construction of national dispatch, provincial dispatch, and prefectural dispatch, and points out several existing problems of backup dispatch at all levels under the current emergency system. In order to gradually solve these problems, a backup dispatch system combining emergency and disaster recovery has been proposed based on the two-place three-center mode, it gradually realizes the prevention of risks from social security incidents such as public health incidents and serious natural disasters. © 2022 IEEE.
ABSTRACT
The use of face mask is advised by World Health Organization (WHO) for preventing transmission of Coronavirus disease 2019 (COVID-19). It is of great value to solve the multi-task object detection problem of non-wearing mask, wrong way wearing mask and standard wearing mask. In this paper, a network YOLOv3-Slim based on YOLOv3 is implemented. It's faster than YOLOv3. Detection speed increased from 15.67 fps to 16.89 fps. In the mean time, we found the effect of the difference of inner class on the classification ability of the model. The large error of inner class will reduce the accuracy of the model and make the attention mechanism ineffective. So after changing the labels of the third data set, We add ECA module to our network. YOLOv3-Slim is more accurate than YOLOv4 in face mask recognition based on our data set. The mAP increased from 89.45% to 92.50%. © 2021 Published under licence by IOP Publishing Ltd.