UAV Fuzzy Inference System Design for Covid-19 Infection Risk Assessment

By emerging of the Covid-19 in 2020, the use of masks in indoor and outdoor areas has turned into a daily routine. In order to prevent the spread of the virus, many states supported and made it mandatory to wear masks. After the emergence of the virus, many studies have analyzed that wearing a mask reduces the risk of transmission, and even the ambient temperature is effective in spreading. In addition to the virus transmission risk studies in the literature, this study presents the evaluation of the images taken from UAVs in the fuzzy inference system by developing a model in machine learning for the control of mask use and the analysis of the virus spread environment. Ambient images and temperature information are provided from UAVs. With the machine learning model developed in the Python environment, the image file is processed and it detects whether a person is wearing mask or not as percentage data. The main contribution of the study is to evaluate the environmental risk according to the rules written in the fuzzy inferential system, mask usage information, and temperature level.