Social Distance Monitoring And Face Mask Detection System For Covid-19 Pandemic

In this time when COVID-19 is spreading rapidly, it is essential to maintain social distance and wearing a mask is compulsory and to avoid large public gatherings at one place to break the chain of corona infection. But maintaining this is not easy. Many people, knowingly or unknowingly, gather and roam on the streets without wearing a mask. Keeping an eye fixed on of these activities isn't a simple job. The authorities need reliable technology to keep track of these activities. This Project can help in monitoring the social distance and also it detects face mask. This whole system is placed in Public gatherings, traffic signals, on roads and also at the entrance of schools and college gates. This system uses a Raspberry Pi with an RPi camera for capturing live video. The video is then processed frame-by-frame. By using image processing with the help of TensorFlow and OpenCV people, vehicles in the video and are identified. First, it detects the presence of the crowd and then with the help of object tracking algorithm and distance algorithm the centroid distances from one person to another person is measured if the distance is violated it gives an alert and by using Keras, OpenCV and Mobilenet people without a mask are detected when this happens it gives alert by speaking.

BNT162b2 vaccine induces divergent B cell responses to SARS-CoV-2 S1 and S2.

The first ever US Food and Drug Administration-approved messenger RNA vaccines are highly protective against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)1-3. However, the contribution of each dose to the generation of antibodies against SARS-CoV-2 spike (S) protein and the degree of protection against novel variants warrant further study. Here, we investigated the B cell response to the BNT162b2 vaccine by integrating B cell repertoire analysis with single-cell transcriptomics pre- and post-vaccination. The first vaccine dose elicits a recall response of IgA+ plasmablasts targeting the S subunit S2. Three weeks after the first dose, we observed an influx of minimally mutated IgG+ memory B cells that targeted the receptor binding domain on the S subunit S1 and likely developed from the naive B cell pool. This response was strongly boosted by the second dose and delivers potently neutralizing antibodies against SARS-CoV-2 and several of its variants.