In the new normal era, many activities began to operate again, and people had to follow health protocols including wearing masks and checking the temperature. This study tested a tool in which artificial intelligence was embedded to help carry out health protocols. This tool connects RaspberryPi, Thermalcam, PiCamera, ultrasonic sensors with Multiple Linear Regression and DeepLearning algorithms. This tool aims to detect body temperature and use a mask. The system will check whether the person is wearing a mask or not, using the DeepLearning method. The system will check body temperature and the distance between humans and the tool, the data is entered in the regression formula to get more accurate results. The processed system results will be displayed on the monitor screen if detected using a mask and the normal temperature will be green, if it is detected as inappropriate it will be red and give a warning sound. The data is sent to the server and displayed via the web. We found that this tool succeeded in detecting body temperature with a distance of 1 to 3 meters with an average MSE temperature is 0.18, the reading accuracy using a mask is 94.71%, and the reading accuracy is not using a mask is 97.70%.