Published Paper Details:

As we all know, there is a pandemic (i.e., COVID19) that is rapidly expanding and threatening the lives of everyone on the planet. The pandemic has had an effect on nearly every industry. We saw the health-care sector's inadequate handling of the pandemic's infection rate after the pandemic. Despite the fact that both the government and the general public are taking several precautionary measures to prevent the dissemination of this virus, such as wearing masks and keeping social distance, there is still a subset of individuals who are irresponsible enough to disregard the precautions and become COVID19 victims and after being admitted to COVID centres for treatment, the majority of patients are seen escaping the centres, increasing the infection risk. As a result, there is a lot of scepticism about the surveillance's competence in the health sector. Given all of the mishaps that have occurred as a result of inadequate monitoring, this research paper explains a solution in which surveillance is completely automated, allowing us to concentrate on other aspects. This Research Paper comes up with a idea that allows us to spot compromised patients who are attempting to escape by engaging with the appropriate authorities. Not just that, but we also detect individuals who do not follow the COVID safety protocols (like wearing masks). The identification is carried out by CCTV cameras that have our software installed in them. Before recognizing, their data has been stored in the database. Here, we explain how our algorithm detects the identity of an individual attempting to leave the hospital and also determines whether or not the person is wearing a mask.