Abstract
On the edge of the worldwide public health crisis, the COVID-19 disease has become a serious headache for its destructive nature on humanity worldwide. Wearing a facial mask can be an effective possible solution to mitigate the spreading of the virus and reduce the death rate. Thus, wearing a face mask in public places such as shopping malls, hotels, restaurants, homes, and offices needs to be enforced. This research work comes up with a solution of mask surveillance system utilizing the mechanism of modern computations like Deep Learning (DL), Internet of things (IoT), and Blockchain. The absence or displacement of the mask will be identified with a raspberry pi, a camera module, and the operations of DL and Machine Learning (ML). The detected information will be sent to the cloud server with the mechanism of IoT for real-time data monitoring. The proposed model also includes a Blockchain-based architecture to secure the transactions of mask detection and create efficient data security, monitoring, and storage from intruders. This research further includes an IoT-based mask detection scheme with signal bulbs, alarms, and notifications in the smartphone. To find the efficacy of the proposed method, a set of experiments has been enumerated and interpreted. This research work finds the highest accuracy of 99.95% in the detection and classification of facial masks. Some related experiments with IoT and Block-chain-based integration have also been performed and calculated the corresponding experimental data accordingly. A System Usability Scale (SUS) has been accomplished to check the satisfaction level of use and found the SUS score of 77%. Further, a comparison among existing solutions on three emergent technologies is included to track the significance of the proposed scheme. However, the proposed system can be an efficient mask surveillance system for COVID-19 and workable in real-time mask detection and classification.
Highlights
The Severe Acute Respiratory Syndrome Coronavirus 2(SARS-CoV-2) is the newly arisen infectious disease that originated in Wuhan, China, in December 2019 [1]
The paper reflects on the embodiment of a scheme with the help of Deep Learning (DL), the Internet of things (IoT), and Blockchain
The proposed model further includes an IoT-based architecture to create an analog response like alarm and notification upon mask detection and classification
Summary
The Severe Acute Respiratory Syndrome Coronavirus 2(SARS-CoV-2) is the newly arisen infectious disease that originated in Wuhan, China, in December 2019 [1]. Recent evidence suggests that the virus transmits mainly between people in close interaction, where the distance between them is less than 1 m [3]. To prevent infection is the key way to protect from the disease, WHO recommended that people should maintain a social distance of at least 2 m [2] and wear face masks appropriately to avoid virus transmission. Protective masks lower the probability of viruses transmitting to the human respiratory system through infected people’s droplets. If 50% of people wear face masks, only 50% of the population would be attacked by the virus [5]. This paper presents an approach to prevent the coronavirus from spreading by detecting mask displacement in public areas
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
