IoT Based Automated Entry System for Covid Prevention: A Review

Abstract

Since the onset of Covid-19 pandemic, a disease caused by SARS-CoV-2, there has been a significant rise in the research and development for various technologies for the prevention of the pandemic from spreading further. Many technologies like Face Mask Recognition, Facial Recognition, Non-Contact Temperature Measurement, Non-Contact SPO2 measurement systems have been developed with significant quality and efficiency. This paper discusses the results of some of the research done in the same field.

Introduction

I. INTRODUCTION

After the outbreak of the dangerous new flu-like infectious respiratory disease SARS-Cov-2 virus causes COVID-19 (also known as coronavirus), billions of lives were at stake globally. This disease was generally getting spread through respiratory droplets from symptomatic persons but later discovered that it can also be transmitted from asymptomatic persons also. This led to the rise of some special rules, often called as Standard Operating Procedures(SOPs) which involved social distancing, wearing masks and being quarantined in case of any symptoms, etc. These were followed to some extent in High-Standard Offices but due to economic breakdown, small businesses often could not afford the staff to comply with these rules. This contributed significantly in allowing the diseases to spread to various places. This called for automated systems which could allow entry to only those persons who comply with the rules and at the same time are cost-effective and efficient enough. These have been helpful to some extent in controlling the spread of the disease. Various techniques are implemented and embedded in these systems. Some of the most important and widespread techniques are Facial and Mask Detection, Non-Contact Temperature Measurement, Non-Invasive SPO2 Measurement, Automatic hand Sanitizer Systems and Remote Monitoring of these systems through web-based dashboards involving IoT at its backend. Face Mask Detection System is an offset of Object Detection System which incorporates Deep Convolutional Neural Networks(CNNs) to provide better accurate results in recognising identities of persons with masks. Primary objective of these systems is to check whether the person is wearing masks or not and also to correctly recognise the identity of the persons with masks with sufficiently required databases. Non-Contact Temperature Measurement Systems often use Infrared-based Thermal Cameras which detect elevations in Body Surface Temperature values mainly of Face. This is often done incorporating AI with real-time monitoring systems at the backend. Upon detecting any said elevations of a person’s temperature, the system sends alert signals to authorized personnel in charge of monitoring the system. This, too, contributed greatly to the disease's control and eventual reduction in the number of cases. Non-invasive SPO2 measurement devices can be made in two ways. The first is to employ a digital camera to extract signals using the imaging PhotoPlethysmography (iPPG) method. Afterwards various signal processing techniques are implemented to deduct the SPO2 value. This is undoubtedly an efficient way of measurement as it does not require the person to be fitted with a fixed measurement system but not much developed and the current systems need the person to be in a stationary position. Second method of measurement is using IR sensors which detect the pulses of blood flow from a person’s finger. Though non-invasive but it needs to have contact with the person’s finger to detect the minute pulses. Then implementing appropriate algorithms, the SPO2 levels of a person can be estimated. This currently is a more proven technique and quite developed with near exact and reliable output. Other systems like automatic hand sanitizer systems and remote-monitoring of the systems’ observations through databases and dashboards further enhances in restricting the spread of the so-discussed disease.

More and more research and developments are taking place in this very instant which pave the way for completely eradicating this disease and also providing a means of safety and clean environment which can reduce the chances of new disease to spread easily. For making life on Earth more safe and secure. Furthermore, this paper provides the detailed analysis observed in various research papers in the same field and summarized them in a more understanding manner.

II. LITERATURE REVIEW

The table given below represents the review of various papers. These papers focus on parameters such as mask detection, temperature scanning, oxygen level measurements, authorized entry and database management. Several comparisons can be established between the papers for selection of an appropriate and a cost effective design.

Table 1: Detailed findings of various technologies

III. DISCUSSION

The study of this paper was to understand current technology used for protection against Covid19 by enhancing their techniques and designing a better version of the existing prototype. Firstly, the essential part of every system is detection of face masks with the help of a suitable architecture to minimize the time constraint for training and execution. Many papers proposed the use of MobileNet architecture as the finest network due to its advantage of less time taken to train and yields a good accuracy(0.439oC Root-Mean-Squared Error compared with Standard Thermometer) with a minimum memory utilization(400Kb). There are some limitations with this network, for example, the accuracy of MobileNet can be compromised as per training parameters and there are multiple neural networks which provide a better validation output than the existing network. This work can be extended more by studying and comparing it with different architectures and trying to select a model which yields better performance.

Moving forward, another essential variable to prevent the spread of virus is to scan the temperature of an individual and verify whether he/she satisfies the given criteria. The given papers suggest the use of a temperature sensor named MLX90614 which is a contactless sensor and can be used in a proximity range to verify the results. This sensor gives a better accuracy(+0.3oC) when the individual is in an appropriate range.

In this study, there are some papers focusing on heart rate and oxygen levels to monitor the health of patients. The papers illustrate two different approaches to detect SpO2 levels. The first approach uses a digital camera to detect the motion and contraction of the muscles of an individual whereas another one uses a direct contact with the help of a RED and IR led. The former one is time consuming as it needs time to record the motion of an individual and provide an approximate result. Hence, the accuracy of this model is compromised. The latter one gives better accuracy as compared to the former one because it is faster and more invasive.

Succeeding to detection and scanning, an individual may be granted entry if all the parameters are satisfied. The entry systems usually are too expensive and can affect the cost of the whole design. To move to a cost effective design, the entry systems can be designed in a way that consumes less power and provides accurate results. Advancing with the entry systems, a paper implemented a QR code based authentication system to maintain the records to the visitors and store the data in the cloud for further use.

Multiple papers indicate the use of hand sanitizer systems with different techniques to prevent the spread of virus. These include a hand sanitizer dispenser, spray dispenser and spray using a nozzle machine. A major drawback of these systems is that they are costly and some of them suffer from wastage of sanitizer liquid. An effective system can be designed to minimize these effects which can give a better reliability.

All the papers focus on some or the other parameters and have designed a system according to it. These different systems can perform better, faster and can be more reliable by tuning some parameters. Furthermore, a sustainable system can be designed which includes all these parameters embedded in a single system giving better performances and saving more time for the prevention process.

Conclusion

The techniques discussed above can prove to be extremely helpful in getting the pandemic under control and also raise chances of reducing any chance for uprising of future similar pandemic causing diseases. The techniques like Facial Mask Recognition, Temperature Measurement and SPO2 Measurement are being implemented and being developed to increase their efficiency, accuracy and reliability. Even though these devices are available individually, but no research or implementation has been done to integrate these devices into a single device which could increase reliability and also can be highly cost-effective. The main objective of this study was to provide a summarized analysis of various technologies which are necessary to implement a single device incorporating these technologies with reliable accuracy and effectiveness, and also to encourage other researchers to do research in this field so development can take place eventually helping the world to move towards a better future. Further work is to use the results of these papers and devise a system incorporating these technologies and implement a cost-effective system.

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Copyright

Copyright © 2022 Smita Nayak, Sudarshan Srinivasan, Abhishek Padiya, Prof. Sushma Kadge. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.