Temperature and mask detection walk through gate to limit covid

COVID 19 pandemic is causing a global health epidemic. The most powerful safety tool is wearing a face mask in public places and everywhere else. The COVID 19 outbreak forced governments around the world to implement

Project Title

Temperature and mask detection walk through gate to limit covid

Project Area of Specialization

Computer Science

Project Summary

COVID 19 pandemic is causing a global health epidemic. The most powerful safety tool is wearing a face mask in public places and everywhere else. The COVID 19 outbreak forced governments around the world to implement lockdowns to deter virus transmission. According to survey reports, wearing a face mask at public places reduces the risk of transmission significantly. In this paper, an IoT-enabled smart door that uses a machine learning model for monitoring body temperature and face mask detection. The proposed model can be used for any shopping mall, hotel, apartment entrance, etc. As an outcome a cost-effective and reliable method of using AI and sensors to build a healthy environment. Evaluation of the proposed framework is done by the Face Mask Detection algorithm using the TensorFlow software library. Besides, the body temperature of the individual is monitored using a non-contact temperature sensor. This proposed system can detect the users from COVID 19 by enabling the Internet of Things (IoT) technology

Project Objectives

Objectives:

•Our proposed SSDWG includes multi-features to disinfect many people from the
COVID-19 without using a manual disinfection system.
• Our proposed system can help to track vulnerable individuals’ records for further
trace and control.
• The proposed model also includes the module to check an individual’s temperature
while using a contact-free temperature sensor without any human intervention and
store the temperature in the database.
• According to the WHO, wearing a face mask in public places can protect an individual
from COVID-19, as evidenced by experiments. The second module of SSDWG is to
detect individuals wearing a mask or not and classify individuals in three classes,
which are face with proper mask (FWPM), face with improper mask (FWIPM), and face
without a mask (FWOM). In this module, we trained our machine learning models
using three datasets, and we attained significant accuracy.
• The sub-module of our face mask identification system is to identify the types of face
masks, either N-95 or surgical masks.

Project Implementation Method

Materials and Methods
In developing countries, where people are not strictly following the Government,
standard operating procedures (SOP’s) suspects are rising rapidly. To prevent the spread
out of COVID-19, we proposed IoT based rapid screening models that can publicly be
located to disinfect the virus and identify the people’s face mask in three categories as we
mentioned before further our proposed model can identify and classify the types of face
masks, either N-95 or surgical mask.

1.IoT Based Smart Screening and Disinfection Walkthrough Gate (SSDWG)

2. Body Temperature Detection

3. Mask Detection Module

4. Dataset

5. Fine-Tuning with Transfer Learning

6. The VGG-16

7. ResNet-50

8. Inception V3

9. MobileNetV2

10. Convolutional Neural Network (CNN)

Benefits of the Project

this project help to limit covid-19.also helpful to strict people to follow SOPs.and this walkthrough gate gives better accuracy than human being. And this project also minimize the expenses of extra employee to check mask and temperature.

Technical Details of Final Deliverable

1.CNN

2 Fine-Tuning with Transfer Learning

3. The VGG-16

4. ResNet-50

5. Inception V3

6. MobileNetV2

7. Convolutional Neural Network (CNN)

Final Deliverable of the Project

Hardware System

Core Industry

Medical

Other Industries

Core Technology

Internet of Things (IoT)

Other Technologies

Sustainable Development Goals

Good Health and Well-Being for People

Required Resources

If you need this project, please contact me on contact@adikhanofficial.com