Analysis of Face Mask Detection through Machine Learning Techniques in Spread of COIVD-19

To distinguish individuals wearing face masks in observation settings like banks and ATMs, this work will give a profound learning model to face mask recognition. Hoodlums and offenders perpetrate wrongdoings by disguising their elements behind face masks, which is contrary to the standard in checking environmental factors. To recognize and secure offenders and lawbreakers, the face mask locator model set forth in this study can be joined with observation cameras in independent reconnaissance frameworks. The COVID-19 pandemic has in short order disturbed worldwide exchange and transportation, influencing our everyday lives. The act of utilizing a defensive face mask has changed. Coming soon from now on, a few public specialist co-ops will expect that clients utilize the legitimate masks while utilizing their administrations. Face mask ID is turning into a significant obligation to help the worldwide civilization. This paper frames a dense strategy for accomplishing this objective using specific essential AI instruments, including Tensor Stream, Keras, OpenCV, and Scikit-Learn. The proposed procedure effectively perceives the face in the picture and afterward decides if it is covered by a mask. © 2022 IEEE.

Microplastics in the Ecosystem: An Overview on Detection, Removal, Toxicity Assessment, and Control Release

In recent decades, the accumulation and fragmentation of plastics on the surface of the planet have caused several long-term climatic and health risks. Plastic materials, specifically microplastics (MPs;sizes < 5 mm), have gained significant interest in the global scientific fraternity due to their bioaccumulation, non-biodegradability, and ecotoxicological effects on living organisms. This study explains how microplastics are generated, transported, and disposed of in the environment based on their sources and physicochemical properties. Additionally, the study also examines the impact of COVID-19 on global plastic waste production. The physical and chemical techniques such as SEM-EDX, PLM, FTIR, Raman, TG-DSC, and GC-MS that are employed for the quantification and identification of MPs are discussed. This paper provides insight into conventional and advanced methods applied for microplastic removal from aquatic systems. The finding of this review helps to gain a deeper understanding of research on the toxicity of microplastics on humans, aquatic organisms, and soil ecosystems. Further, the efforts and measures that have been enforced globally to combat MP waste have been highlighted and need to be explored to reduce its potential risk in the future. © 2022 by the authors.

Social Distancing and Face Mask Monitoring System Using Deep Learning Based on COVID-19 Directive Measures

We, the entire world is in the lock of a micro size virus named Corona we are in the urge of saving our life rather than the money. This virus had changed the attitude of people from generations together, in this two years people realized that their health worth more than their net worth. We are in an uncertain situation but, we can bring the world back to normal so, we need to follow the guidelines issued by the health organizations so our government insisted people wear the mask and maintain social distance to control the spread of the disease but 90% percent of people not following covid guidelines. The main motive in this paper, mask detection on face with social distancing which helps to overcome this pandemic situation. Our proposed system comprises of data processing, data augmentation, image classification using mobilenetv2 and object detection plays a vital role in this paper. The modules are developed using TensorFlow and open-cv python programming to detect the faces with mask. If a person wears a mask they will be in a safe zone and the system shows a green box where if the person doesn't wear a mask, then it will be shown in a red box and with the message of alert as well. Social distancing detection will detect that two or more person in a single frame are walking with maintaining social distancing with at least 2 meters of range with each other using the Euclidean distance method, it will work in a Reliable manner with accurate results during this current situation which will easily help to track the person and collect fine if they violate any government directive guidelines so our system, will prevent the spread of the disease. Every Automation process reduces manual inspection to inspect the people which can be used in public places to control the spread of the virus and this prototype could be used in many places like park, hospital, airports, temples, railway station etc.To control this pandemic situation © 2021 IEEE.

A collection of the novel coronavirus (COVID-19) detection assays, issues, and challenges.

The global pandemic of COVID-19 has rapidly increased the number of infected cases as well as asymptomatic individuals in many, if not all the societies around the world. This issue increases the demand for accurate and rapid detection of SARS-CoV-2. While accurate and rapid detection is critical for diagnosing SARS-CoV-2, the appropriate course of treatment must be chosen to help patients and prevent its further spread. Testing platform accuracy with high sensitivity and specificity for SARS-CoV-2 is equally important for clinical, regional, and global arenas to mitigate secondary transmission rounds. The objective of this article is to compare the current detection technology and introduce the most accurate and rapid ones that are suitable for pandemic circumstances. Hence, the importance of rapid detection in societies is discussed initially. Following this, the current technology for rapid detection of SARS-CoV-2 is explained and classified into three different categories: nucleic acid-based, protein-based, and point of care (PoC) detection testing. Then, the current issues for diagnostic procedures in laboratories are discussed. Finally, the role of new technologies in countering COVID-19 is also introduced to assist researchers in the development of accurate and timely detection of coronaviruses. As coronavirus continues to affect human lives in a detrimental manner, the development of rapid and accurate virus detection methods could promote COVID-19 diagnosis accessible to both individuals and the mass population at patient care. In this regard, rRT-PCR and multiplex RT-PCR detection techniques hold promise.

Real time data analysis of face mask detection and social distance measurement using Matlab.

This paper describes mask detection using Matlab when complex images in the dataset. Matlab specified the Faster R-CNN algorithm and Dataset allotment for mask detection. This paper manages complex pictures using facial recognition packages. The Faster R-CNN methodology used in the security system and the medical system. The proposed work balanced face restriction, color changes, brightness changes, and contrast changes. Segmentation and feature extraction used in face restriction of the person image. We chose RCNN, Fast RCNN, and Faster RCNN algorithm for detecting Mask detection and Social distance. Regions with Convolutional neural network Based on Mixing pictures, pixel prediction, and specific enhancements. The main objective was to solving multiple and multitask picture detection problems with speed rates. The Methodology used for face detection and detection of Unmask person in a dataset of face database.