Real Time Face Mask Monitoring and Face Identification
COVID-19 is a contagious disease caused by a newly discovered coronavirus. It spread very quickly between people due to directly or indirectly close interaction. The things, surface infected person interact with, all become infected. Which is dangerous for other people because they can also be infec
2025-06-28 16:34:42 - Adil Khan
Real Time Face Mask Monitoring and Face Identification
Project Area of Specialization Computer ScienceProject SummaryCOVID-19 is a contagious disease caused by a newly discovered coronavirus. It spread very quickly between people due to directly or indirectly close interaction. The things, surface infected person interact with, all become infected. Which is dangerous for other people because they can also be infected with it.
So this idea is basically for the purpose of prevention of covid-19 pandemic. Because it is spreading very fast due to not following the SOP's. It becomes very difficult in crowded areas to detect everyone whether they are wearing mask or not. Manually checking is very tough now. So to overcome this problem we will assemble a project in which a camera will detect the person whether he is wearing mask or not. If he is not wearing mask, it will generate an alarm to alert admin and the user through an app after recognizing their faces. And the application will also update the user about the ongoing situation of covid-19,news etc.
Project ObjectivesIn the present scenario due to Covid-19, there were no efficient face mask detection applications which are now in high demand for educational institutions, densely populated areas, residential districts, large-scale manufacturers and other enterprises to ensure safety. This system can therefore be used in real-time applications which require face-mask detection for safety purposes due to the outbreak of Covid-19. This project can be integrated with embedded systems for application in educational sectors, airports, offices, and public places to ensure that public safety guidelines are followed.
The mask monitor project will meet the following objectives:
- The system is easy to implement in any existing organizational system.
- Alerts can be sent of the person without a face mask to the admin system or the user.
- At the end of every month we will receive a report containing information that how many times we have to notify everyone.
We will build a real-time system for face mask detection using YOLOv3 with darknet, this algorithm is for the feature extraction and detection in the training, validation, and testing phase. We will train a model with custom objects and apply the triangle network to perform mask detection with the use of openCV. First we will record a videos of peoples with or without mask and then use these videos to build and train a model for face mask detection. It will be an effective model to find a masked face on input image file, webcam feed or video file.
Then we will use YOLOv3 for detecting the features of the face too because it is fast and accurate, this method classify machine learning-based and deep learning. We will provide a platform to user where they can upload their photos that will store in the database. YOLOv3 made connections with CNN by hidden layers which through research easily fetch the algorithm and can detect and localize any type image. So, If the camera captures a recognized face, sends them a reminder to wear a mask through this application. Training the model is the first part of this project and testing using webcam or any other existing IP camera using openCV is the second part.
Benefits of the ProjectThe face mask recognition system uses the technology to detect the person with or without a mask. It can be connected with any surveillance system installed at your premise. It will only identify that person whose data has already stored in database. The authorities or admin can check the person through the system to confirm their identity. The system sends an alert message to the authorized person if someone has entered without a face mask.
Government and private organizations want to make sure that everyone working or visiting a public or private place is wearing masks. The face mask detection platform can quickly identify the person with a mask, using cameras.
Technical Details of Final DeliverableOur final deliverable app will include the integration of mobile application with IP camera (built-in microphone and two-way bi-directional audio) to give it a friendly environment to users.
So that the system will have a IP camera that will capture the people of its surrounding whether they are wearing masks or not. Then it will notify the admin. And if the same person will be recognized for about 2-3 times not wearing masks that the system will automatically notify the user by sending an alert to wear mask properly. We will be using the Yolov3 algorithm with the combination of OpenCv, to easily extract and detect the features with accuracy.
Final Deliverable of the Project HW/SW integrated systemCore Industry ITOther IndustriesCore Technology Artificial Intelligence(AI)Other TechnologiesSustainable 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) | 80000 | |||
| IP Camera (Samsung 4Channel 2 IP66 720T ) | Equipment | 1 | 50000 | 50000 |
| Mobile Phone (To linked with IP Camera, Samsung Galaxy A02s) | Equipment | 1 | 20000 | 20000 |
| Report, Printing, Poster and etc | Miscellaneous | 1 | 10000 | 10000 |