All-terrain mobile robot desinfectant sprayer to decrease the spread of COVID-19 in open area

The application of disinfection is becoming popular in recent months due to the COVID-19. Usually, the disinfection is used by spraying the liquid into an object. However, the disinfection process for humans and objects in the human environment is still done manually and takes time and increases exposure to viruses. Robotic technology can be a solution to handle that problem. Following that problem, robot design is proposed with many abilities and features. The robot can operate in remote conditions and full function for approximately 56 minutes and spray the liquid for more than 1 meter. This research can effectively be applied in COVID-19 handlings

Transfer deep learning approach for detecting coronavirus disease in X-ray images

Currently, the whole world is fighting a very dangerous and infectious disease caused by the novel coronavirus, called COVID-19. The COVID-19 is rapidly spreading around the world due to its high infection rate. Therefore, early discovery of COVID-19 is crucial to better treat the infected person as well as to slow down the spread of this virus. However, the current solution for detecting COVID-19 cases including the PCR test, CT images, epidemiologically history, and clinical symptoms suffer from high false positive. To overcome this problem, we have developed a novel transfer deep learning approach for detecting COVID-19 based on x-ray images. Our approach helps medical staff in determining if a patient is normal, has COVID-19, or other pneumonia. Our approach relies on pre-trained models including Inception-V3, Xception, and MobileNet to perform two tasks: i) binary classification to determine if a person infected with COVID-19 or not and ii) a multi-task classification problem to distinguish normal, COVID-19, and pneumonia cases. Our experimental results on a large dataset show that the F1-score is 100% in the first task and 97.66 in the second task