COVID-19 SOP-based Smart Entrance System
In the current awake of the COVID-19 pandemic, preventing and limiting the community spread of the virus is a massive task, with governments and administrations across the world applying different strategies to restrict population movement and social interaction. A recent survey conducted on 5800 sm
2025-06-28 16:26:01 - Adil Khan
COVID-19 SOP-based Smart Entrance System
Project Area of Specialization Internet of ThingsProject SummaryIn the current awake of the COVID-19 pandemic, preventing and limiting the community spread of the virus is a massive task, with governments and administrations across the world applying different strategies to restrict population movement and social interaction. A recent survey conducted on 5800 small US businesses concluded that 43% of businesses were temporarily closed and falls in the employment of 40%. According to a news article, one pharmacy business in New South Wales (NSW), Australia, had to spend AUD 1000–1500 per week to higher staff for monitoring temperature and ensuring distancing.
So, we propose a low-cost option for small businesses to measure COVID precautions. COVID-19 workplace safety parameters such as body temperature (fever), if peoples are wearing masks or not number of people per square meter, and distance between individuals in the queue area.
The first step to detect COVID is by scanning for fever, or we need to monitor every person for a mask. We have temperature checking systems for every entrance for scanning because There is human error in reading values. The scanning is skipped by the personnel if supervisors are not watching we propose a fully automated temperature scanner and entry provider system. It is a multipurpose system that has a wide range of applications. The system makes use of a contactless temperature scanner and a mask monitor. The scanner is connected directly with a human barrier to stop entering person if temperature is high or no mask is detected.Any person will not be provided entry without temperature and mask scan. Only person having both conditions is instantly allowed inside. The system uses temperature sensor and camera connected with a raspberry pi system to control the entire operation.
Project ObjectivesOur main objective for developing this system is:
Ø Reduce the burden of humans through Fully automated monitoring of compliance with face mask and body temperature requirements
Ø Make Detection System which can be used at university, office, premises to detect if student, employees, or entering persons are maintaining safety standards or not. Ø Saves staff resources
Ø As machines can do work more efficiently as compared to the humans so we developed this system.
Ø Machines can do work 24/7 a day and humans need to take rest so by developing this system we can get work from it 24/7.
Ø System should work in place of, or in conjunction with, any physical barrier currently prevalent in the industry to ensure COVID-19 safety
Ø System should extract the barcode through student.
Ø System should check if person is wearing a mask or not
Ø System should check if persons temperature is normal or not.
Ø System should check in record if coming person is vaccinated or not
Project Implementation MethodTo test the feasibility of the proposal, lab space was used to set up sensors as per the layout. Raspberry Pi was configured to run. The two IR sensors were placed at the entrance at a height of the ground and the individual count (in and out) was communicated to the graphical dashboard. Based on which IR sensor—outer or inner—detected the obstacle first, the counter was incremented or decremented. Based on the inputs from these sensors, parameters such as people in, people out, current people count. The temperature sensor was positioned just after the entrance at a height . Incoming individuals were required to place their forehead close to the sensor and the temperature reading was recorded and sent to the serve. When the participant was within this range, a green light turned on indicating the correct distance. The temperature sensor used can measure contactless temperature in Celsius The first section showed the numerical data regarding thec ounting and the total number of violations. The second section displays the list of any warnings active at any given time
order to train a custom face mask detector, we need to break our project into two distinct phases, each with its own respective sub-steps (as shown by Figure 1 above):
- Training: Here we’ll focus on loading our face mask detection dataset from disk, training a model (using Keras/TensorFlow) on this dataset, and then serializing the face mask detector to disk
- Deployment: Once the face mask detector is trained, we can then move on to loading the mask detector, performing face detection, and then classifying each face as
with_mask or without_mask
then we will see database if person is vaccinated or not . System will check in record if coming person is vaccinated or not.we will implement system at universities,banks and other comercial areas
Benefits of the Projectwe propose a low-cost option for small businesses to measure covid precautions. COVID-19 workplace safety parameters such as body temperature (fever), if peoples are wearing masks or not number of people per square meter, and distance between individuals in the queue area.
system will Reduce the burden of humans through Fully automated monitoring of compliance with face mask and body temperature requirements
system will Make Detection System which can be used at university, office, premises to detect if student, employees, or entering persons are maintaining safety standards or not.
system will Saves staff resources
As machines can do work more efficiently as compared to the humans so we developed this system.
Machines can do work 24/7 a day and humans need to take rest so by developing this system we can get work from it 24/7.
we propose a low-cost option for small businesses to measure covid precautions. COVID-19 workplace safety parameters such as body temperature (fever), if peoples are wearing masks or not number of people per square meter, and distance between individuals in the queue area.
system will Reduce the burden of humans through Fully automated monitoring of compliance with face mask and body temperature requirements
system will Make Detection System which can be used at university, office, premises to detect if student, employees, or entering persons are maintaining safety standards or not.
system will Saves staff resources
As machines can do work more efficiently as compared to the humans so we developed this system.
Machines can do work 24/7 a day and humans need to take rest so by developing this system we can get work from it 24/7.
Technical Details of Final DeliverableSystem will extract the barcode through student id card with the help of data base.
System will check if person is wearing a mask or not our face mask detector will work like
- Having limited training data
- The with_mask
class being artificially generated (see the “How was our face mask dataset created?”
While our artificial dataset will work well in this case, there’s no substitute for the real thing.
System will check if persons temperature is normal or not.The temperature sensor used can measure contactless temperature in Celsius The first section showed the numerical data regarding thec ounting and the total number of violations. The second section displays the list of any warnings active at any given time
System should check in record if coming person is vaccinated or not
An effective solution to ensure COVID-19 safety compliance is presented in this work. The system relies on open source software and widely available sensors to make a low cost and easy to configure and customize set up. It relays useful real-time information wirelessly to a dashboard which can be used to monitor and assist in COVID-19 SOP. ). Future efforts will be focused to expand the detection for the complete floor area, contact tracing, and support for additional queues. The system can be extended easily with minimal time and is quickly adaptable to different situations.
Final Deliverable of the Project Software SystemCore Industry ITOther Industries Health , Security Core Technology Internet of Things (IoT)Other Technologies Artificial Intelligence(AI)Sustainable Development Goals Good Health and Well-Being for People, Industry, Innovation and InfrastructureRequired Resources| Item Name | Type | No. of Units | Per Unit Cost (in Rs) | Total (in Rs) |
|---|---|---|---|---|
| Total in (Rs) | 46370 | |||
| Raspberry Pi | Equipment | 1 | 25500 | 25500 |
| sensor | Equipment | 4 | 400 | 1600 |
| ESP8266 12-E Wifi Module | Equipment | 1 | 500 | 500 |
| 12V 122 RPM W/Encoder DC Motor | Equipment | 1 | 3600 | 3600 |
| resistor | Equipment | 12 | 30 | 360 |
| Transistor D313 | Equipment | 6 | 100 | 600 |
| camera | Equipment | 2 | 7000 | 14000 |
| documentation prints | Miscellaneous | 70 | 3 | 210 |