Recently India along with almost all big and small countries stated emergency conditions for the novel coronavirus (COVID-19). Practically, the whole population of the world is under lockdown and people are maintaining social distances as suggested by the World Health Organization (WHO). This deadly virus has infected tens of lakhs individuals and continues to spread globally. According to recent reports, the next few months are life-threatening in the current efforts to hold COVID-19 spread among communities. Across India, persons are losing jobs, working from home, being hospitalized, and even vanishing life as a result of COVID-19 infections. The epidemic placed great stress on medico professionals. Hospitals are experiencing higher than normal patient loads and treating all patients quickly and effectively now becomes a very challenging task. Due to fear, country-wise lockdown, and suspended OPDs in Hospitals regular patients are also not able to approach doctors.
Precaution is always better than cure. But since there isn't any cure yet available, the only option we are left with is to follow the precautions. And failing to do so may has severe consequences. Since there is no vaccine yet available in the market, the only way to be safe is by taking precautions. It is suggested to wear a face mask and maintain social distancing to avoid coming in contact with novel corona-virus. Studies have proven that masks help in slowing down the spread of infection as the virus mainly gets transmitted with the aerosols which come out of an infected person's nose or mouth while coughing or sneezing.Therefore, we are going to build a Raspberry Pi-based face mask detector which detects whether the person is wearing a mask or not.
According to data obtained by the World Health Organization, the global pandemic of COVID-19 has severely impacted the world and has now infected more than eight million people worldwide. Wearing face masks and following safe social distancing are two of the enhanced safety protocols need to be followed in public places in order to prevent the spread of the virus. To create safe environment that contributes to public safety, we propose an efficient computer vision-based approach focused on the real-time automated monitoring of people to detect both safe social distancing and face masks in public places by implementing the model on raspberry pi4 to monitor activity and detect violations through camera. After detection of breach, the raspberry pi4 sends alert signal to control centre at state police headquarters and also give alarm to public.
In this proposed system modern deep learning algorithm have been mixed with geometric techniques for building a robust modal which covers three aspects of detection, tracking, and validation. Thus, the proposed system favours the society by saving time and helps in lowering the spread of corona virus. It can be implemented effectively in current situation when lockdown is eased to inspect persons in public gatherings, shopping malls, etc. Automated inspection reduces manpower to inspect the public and also can be used in any place.
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