Face mask and temperature screening system at entrance gate

Project Title

Face mask and temperature screening system at entrance gate

Project Area of Specialization Internet of ThingsProject 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 case, an IOT-enabled smart door that will use 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 Tensor Flow software library. Besides, the body temperature of the individual will be monitored using a noncontact temperature sensor. This proposed system will detect the users from COVID 19 by enabling the Internet of Things (IOT) technology.

Convolution Neural Networks (CNN) Algorithm In this case, a deep learning algorithm will be used to identify face mask recognition and, Convolution Neural Networks (CNN) classification. A CNN is a form of artificial neural network that is specifically built to interpret pixel input and is mainly used for image recognition and analysis, in which each layer applies to a different set of filters. Around 100’s to 1000’s of filters is combined to give a final result and then the obtained output will be sent to the next layer in this neural network. Evaluation of the proposed framework is done by the face mask detection algorithm using the Tensor Flow software library. The Mask detector model is trained by using Keras and Tensor Flow.

Project Objectives

The objectives of study is stated as follows

1. To study about COVID-19 Prevention.
2. To know about preventive measures from COVID-19.
3. To detect body temperature.
4. To detect people wearing face mask or not.
5. To Improve implementation of COVID-19 SOPs.
6. To save others from someone effected from COVID-19 Virus.
7. To measure temperature and check face mask wearing automatically.

Project Implementation Method

Convolution Neural Networks (CNN) Algorithm In this case, a deep learning algorithm will be used to identify face mask recognition and, Convolution Neural Networks (CNN) classification. A CNN is a form of artificial neural network that is specifically built to interpret pixel input and is mainly used for image recognition and analysis, in which each layer applies to a different set of filters. Around 100’s to 1000’s of filters is combined to give a final result and then the obtained output will be sent to the next layer in this neural network. Evaluation of the proposed framework is done by the face mask detection algorithm using the TensorFlow software library. The Mask detector model is trained by using Keras and TensorFlow. The steps involved in the algorithm are given below

STEP 1: DATASET COLLECTION

 STEP 2: PRE-PROCESSING

 STEP 3: SPLITTING

STEP 4: TRAINING

STEP 5: TESTING/EVALUATION

According to the above-mentioned algorithm, all the required dataset and components for building the network will be collected from various categories. Once the initial dataset will ready, the next step will to train and test the set. This test dataset will used only in evaluating the performance of the network. Next training will be done, so the neural network will be used to identify different categories. Finally, the dataset will be evaluated and compared with the ground truth labels.

Benefits of the Project

The main purpose of the developed system is to avoid the spread of COVID-19 in public places such as shopping malls, offices, and so on. The system can monitor an individual’s body temperature and can perform face mask detection. This study is need of today because COVID-19 is spreading day by day.

The main benefits of the system are stated as follows

1. Full automatic system

Automatic operation

Technical Details of Final Deliverable

The system that we established is fully automated.

We technically made a smart door that will sense human temperature through Digital Infrared Temperature sensor and it will also detect the face mask through camera  if temperature is high than normal and face mask is missing then the gate will not be opened and if both required are fulfilled then the LED show a welcome message and the indicator will show the green light if even requirement is not fulfilled the indicator will show red light and buzzer will be rung and LED will show missing requirement and gate will not be opened.

Final Deliverable of the Project HW/SW integrated systemCore Industry HealthOther Industries Medical Core Technology Internet of Things (IoT)Other Technologies Cloud InfrastructureSustainable 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)	69950
Raspberry pi 4	Equipment	1	22900	22900
ESP-32 cam	Equipment	2	3500	7000
TTL serial	Equipment	4	450	1800
Digital Infrared Temperature sensor	Equipment	1	3500	3500
Ultrasonic Sensor SR04	Equipment	1	5000	5000
LEDs	Equipment	2	2000	4000
Buzzer	Equipment	1	400	400
Servo moter	Equipment	1	1000	1000
Jumping wire	Equipment	20	30	600
12v Charger	Equipment	4	900	3600
12 v DC to DC Converter	Equipment	1	850	850
Lights	Equipment	4	1500	6000
Arduino UNO	Equipment	1	8000	8000
Chargeable cell	Equipment	4	800	3200
Bread board	Equipment	3	600	1800
Arduino cable	Equipment	2	150	300