IntelliMask Automated tool for Face Mask Detection

Project Title

IntelliMask Automated tool for Face Mask Detection

Project Area of Specialization Artificial IntelligenceProject Summary

IntelliMask: An automated tool For facemask detection.

COVID-19 is the disease caused by the new corona virus that emerged in China in December 2019. COVID-19 can be severe, and some cases have caused death.There is no corona virus vaccine yet. Prevention involves frequent hand-washing, coughing into the bend of your elbow, staying home when you are sick and wearing a cloth face mask.Face Mask Detection has been an important topic in computer vision now a days due to Covid-19.It helps us visualize a person is wearing mask or not .We aim to design a face classifier which can detect any face present in the frame irrespective of its alignment using machine learning.

Project Objectives

Project Objectives 

• Using Machine Learning we will train neural network to recognize if a person is wearing mask or not . 
• Machine Learning model will be trained using supervised learning model which will take multiple images of human faces wearing mask and other with no mask.

Project Implementation Method

Project Implementation Method:

• First of all we will collect the facemask images dataset with two classes ,(i.e facemask , non-facemask) 
• Then we will make a neutal network in python(TensorFlow,Keras) using deep learning .
• Then we will start training the deep learning model on the GPU, and analyze the model using the confusion matrix .
• Then try to improve accuracy of the model by changing the nerons and other things like layers of deep learning model ,then retrain the model to get best results.
• After achieving the best results we will apply this model in realtime on  raspberry pi 4and connect LED with it so that we can see live results.

What we need to make this project ?

• GPU: It requires Training different models to come up with the good results require fast processing , which can be achived by using good quality of GPU(graphics processing units).
• raspberry pi 4 : To Execute mache Learning model to detect facemask in real time
• LED : To display the results from the raspberry pi 4.

Benefits of the Project

After making this system we can deploy the system inside of the buildings (ATMs, hospitals,banks etc) and see the live video of people wearing mask or not . and  if certain number of people are not wearing mask or not , and make decisions out of it , i.e if person is not wearing Fackmask lock the door(using raspberry pi ) and don't allow person inside the ATM we don't have to hire a person for this task, there can be multiple options for the deployment. thats how we can resuce the spread of covid-19

Technical Details of Final Deliverable

First of all we will collect the facemask images dataset with two classes ,(i.e facemask , non-facemask) Then we will make a neutal network in python(TensorFlow,Keras) using deep learning .Then we will start training the deep learning model on the GPU, and analyze the model using the confusion matrix .Then try to improve accuracy of the model by changing the nerons and other things like layers of deep learning model ,then retrain the model to get best results.After achieving the best results we will apply this model in realtime on  raspberry pi 4and connect LED with it so that we can see live results.

Final Deliverable of the Project Hardware SystemCore Industry HealthOther Industries Medical Core Technology Artificial Intelligence(AI)Other Technologies Internet of Things (IoT), OthersSustainable Development Goals Good Health and Well-Being for PeopleRequired Resources

Item Name	Type	No. of Units	Per Unit Cost (in Rs)	Total (in Rs)
			Total in (Rs)	37000
GPU	Equipment	1	15000	15000
LED	Equipment	1	10000	10000
Raspberry pi 4	Equipment	1	12000	12000