Virtual assistant for tutorials

The Project

With a passion for programming, scientific and technical research to create Informatics products, the introduction of a new programming language is easy for students to use. - The evolution of the Covid-19 epidemic is quite complicated, Limit contact, limit risks. For medical staff, to support medical staff to meet the needs of patients in a timely manner. Our team has tried to research many projects to contribute a part in fighting the epidemic and serving the health care needs of everyone. - With the initial idea, our group made a model of a nurse. On the model, we install a microbit circuit device, Webcam. - As a computer character, instead of a medical staff - Build artificial intelligence characters with Scratch AI - Acquire the patient's desire for medical examination and treatment + Receiving comments: + Give feedback (instructions) This will be a practical solution in the current situation, contributing to raising awareness about the prevention of covid 19. Besides, instructing us more about going to the hospital. The students well implemented the 5k message, helping them to prevent illness for themselves, their families and those around them. When facing the situation of the outbreak of the Covid-19 epidemic, everyone needs to strictly follow the 5k message: masks - disinfection - distance - do not gather - medical declaration. In the five messages above, our group has applied one message to integrate into the model, which is the message "mask, distance". • Structure and operating principle. Nurse virtual assistants can do: 1. Facial recognition of patients coming for medical examination. - If not wearing a mask, the patient will be reminded to wear a mask. (if not worn 3 times - each time 5s apart) - After wearing a mask. The virtual assistant thanked and reminded to wash hands before entering the clinic - use the hand sanitizer next to it. 2. Ask the patient which clinic he wants to go to? And give detailed instructions. Voice request recognition. Implementation steps. Step 1: Build the program. Step 2: Train machine learning on faces with 3 states: Wearing a mask, not wearing a mask, background. Step 3: Program the image processing

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