ABSTRACT
As the COVID-19 pandemic ravaged the planet at a standstill, remote employment seemed inescapable. Still, for some businesses that rely on the on-site presence of employees, this was a lethal blow. As time passed, restrictions got looser and allowed people to strike a balance between on-site and remote work. Thus, tracking people's indoor movements for purposes involving activity inference, security, and contact tracing is more crucial than ever before. This research explores the applicability of (Radio Frequency Identification) RFID contactless smart cards in tracking people's movement within an enclosed establishment by building a proof-of-concept prototype that allows the mentioned purposes. Furthermore, the system underwent multiple test phases to verify that the system meets the functional and non-functional requirements listed to ensure the system's operational success. Consequently, the test results prove that: 1) the system is behaving as intended;2) the system is secure from known high-risk vulnerabilities;and 3) the system satisfies user requirements and standards, thus fulfilling the functional and non-functional requirements for a human-tracking movement system. © 2023 by the authors.
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This study aims to design and implement an online blockchain-based and real-time parcel monitoring and tracking system for cross-border runners and the customer via an online platform, during and post the COVID-19 pandemic. A blockchain is a distributed ledger system that serves as a transparent, understandable, and trustworthy store of data and analysis on the platform for participants to engage with each other. The result of proposing a blockchain-based tracking system is promising. The result and UAT show positive feedback on the use and features of the blockchain-based tracking system. As the world reacted to the pandemic, many organizations provided monitoring with their deliveries, which is a terrific method for businesses to prevent losing valuable customers. According to the findings of the study, organizations prefer to have blockchain-based tracking systems.
ABSTRACT
The outbreak of the novel coronavirus (SARS-CoV-2) has seriously harmed human health and economic development worldwide. Studies have shown that timely diagnosis and isolation are the most effective ways to prevent the spread of the epidemic. However, the current polymerase chain reaction (PCR) based molecular diagnostic platform has the problems of expensive equipment, high operation difficulty, and the need for stable power resources support, so it is difficult to popularize in low-resource areas. This study established a portable (<300 g), low-cost (<$10), and reusable molecular diagnostic device based on solar energy photothermal conversion strategy, which creatively introduces a sunflower-like light tracking system to improve light utilization, making the device suitable for both high and low-light areas. The experimental results show that the device can detect SARS-CoV-2 nucleic acid samples as low as 1 aM within 30 min.
Subject(s)
COVID-19 , SARS-CoV-2 , Humans , SARS-CoV-2/genetics , COVID-19/diagnosis , Polymerase Chain Reaction/methods , Sensitivity and Specificity , COVID-19 TestingABSTRACT
Infections by the Covid-19 coronavirus have proliferated since the end of 2019, and many privacy-protective contact tracing systems have been proposed to limit infections from spreading. However, the existing Bluetooth-based contact tracking systems lack accuracy and flexibility. In addition, it is desirable to have a contact tracing system that, in the future, can contribute to limiting the proliferation of new coronaviruses and as yet unknown viruses. In this study, we propose a method to extend a contact tracing system to be more flexible, accurate, and capable of dealing with unknown viruses by using trajectory data and infection factor information while protecting privacy. We also implemented the proposed extension method and measured its execution time and confirmed its practicality. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.
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This review aims to examine the writing in order to assist specialists and scientists in better understanding and dealing with the impact of Coronavirus on the tourism sector. The study examines the situations and questions created as a result of the pandemic to see why and how Coronavirus - 19 has impacted people's lives. As a result, the report identifies the qualities, establishments, and preconceptions that the travel industry should question, as well as the activities that should be made to take a step ahead. The study also looks into the considerable loss the travel sector is experiencing throughout the Coronavirus stages and proposes a solution based on the Salesforce platform to address some of the issues. This provides an overview of how the Coronavirus affects the travel business, as well as recommendations for the industry, examining and settling some of them with 'Travel Log Analysis utilizing Salesforce'. © 2022 IEEE.
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Over the past two years, COVID-19 has led to and is still leading to lots of deaths to date. Many industries have been affected by that, and governments have united in finding ways to mitigate the spread of the disease, thus leading life to return to normal. There are several ways that were followed to do that, such as social distancing, thermal screening, and virtual communication. Thermal screening has proven its practicality in certain entities that require face-to-face contact. Researchers have been contributing to finding effective ways to develop screening methods to help re-accelerate the learning process. This paper proposes a fever screening system to record and track individuals' temperature and an attendance tracking system for educational institutions. The system measures the individual's temperature and records it, and saves their attendance in a database. After completing the measurement taking of an individual, the system uses a buzzer to inform the following individual that it is their turn. This allows the institution to monitor any temperature spikes among the individuals while recording their attendance without close contact at the entrance. Our results validate the usefulness and potential of our system as a fever screening and attendance tracking tool. It also opens the door for further development, allowing regular operation in educational institutions during any upcoming pandemics. © 2022 IEEE.
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The coronavirus pandemic, which first began in December 2019, has completely changed our daily lives. In particular, daily online digital content consumption over the world has soared since the start of the coronavirus pandemic. For preventing illegal digital content distribution, various technologies have been applied, but current copyright protection technologies are still lacking to provide secure digital content distribution while preserving privacy. In this article, we introduce a new digital content distribution system, which utilizes blockchain-based decentralized identifier and format-preserving encryption to enable user privacy preserved digital content tracking. We present the system architecture with detailed message flows of the proposal and provide its analysis result in terms of security and overhead.
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Now a days maintaining the social distance has become mandatory to decrease the spread of corona. So a novel way of finding pairs automatically of people in a crowded environment that does not participate in the block of public space, that is, about 6 feet of space among them. This Will-making method does not think about crowded traffic or pedestrian directions. Here a moving robot with sensory inputs, a camera to perform non-collision navigation Jump and measure the distance among the adjacent people found in the camera view field. Moreover, this equips the robot with a hot camera that transmits hot wireless images to safety / health workers who watches when someone shows a higher temperature than required. In these situations, the robot integrated with static cameras to improve social distance maintenance Remote Culprits detected, precisely following pedestrians etc. Social segregation measures are important to reduce the spread of Covid. In order to break the chain of transmission, public distribution is strictly followed as usual. This paper centralizes a useful thing to monitor the populated such as ATMs, supermarkets and hospitals for any violations of social segregation. By using the system, I have proposed will be possible to monitor queue world who maintain social isolation in a protected area and to alert individuals in the event. © 2022 IEEE.
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This article presents an inexpensive artificial intelligence solution aimed at increasing indoor safety of COVID-19, including a number of important aspects: (1) breakdown of the process (2) Method for mask identification (3). Assessment methodology of social distancing The Arduino Uno sensor system uses an infrasound sensor or heat camera, whereas the Raspberry Pi is equipped with computer vision technologies for mask detection and social distance checks. Indoor measures are the most prevalent—people with a high body heat should stay at home, masks should be worn, and their distance should be at least 1.5–2 m. In the first case, the Arduino Uno temperature sensor board is utilized, while we utilize a single-board Pi Raspberry computer coupled with camera for two additional situations, using computer vision techniques. Due to their compact size and cost, we chose to utilize these devices. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
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Managing employee attendance is a key factor for a large organization since the staff is the main resource for them. In Sri Lanka, currently, there are various methods used to track the attendance of employees, and the traditional manually assigning paper-based signature mechanism, fingerprint method, card strap Radio Frequency Identification (RFID), and biometric-based attendance recording systems such as fingerprint recognition methods are generally used. Most of the systems offer either one-way or two-way authentication for recording the attendance.In this project, we aim to upgrade the customary used individual authentication systems into a single, integrated contactless and biometric-based identity system. To achieve this, a facial recognition mechanism along with the card strap of RFID and fingerprint authentication mechanism(optional) are combined into a singular attendance managing system which can provide the flexibility to use multi-optional biometric identification methods to verify one's identity and mark their attendance. To address the Covid 19 pandemic situation, the system is also equipped with a contactless InfraRed (IR) thermal sensor to detect the temperature of each employee before they mark attendance. As a result, it automates the manual temperature monitoring method of employees without the involvement of another person. The resultant attendance is recorded data in a cloud service platform (Amazon Web Services(AWS)) in real-Time and later analyze the stored attendance data using a Database platform. Due to the high secureness of the system, unethical activities conducted by employees when marking attendance can be avoided thus increasing the performance of the organization in the long-Term run. © 2022 IEEE.
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COVID-19 became the headlines of every nation because of its unrivalled transmission speed and outbreaks in humans, but its new variants are raising new challenges after every few months iteratively. Keeping track of travel history and maintaining a record of people coming in contact with any COVID affected individual has become a prime concern to control the spread of this pandemic disease. The existing tracking system lags in fetching records of people who came in contact with the affected one and maintaining travel history across the local boundaries of the cities. In this position paper, we are proposing a framework for an IoT driven blockchain (BC) based secured tracking system that gathers users' travel and meeting history, and it may help with remote health monitoring. The data gathered for the same is treated as immutable and achieves interoperability with the help of Smart Contracts (SC). It could be proved as a useful framework for post COVID-19 economic revival with the help of an IoT driven blockchain based secured model for remote health monitoring & chain tracking. © 2021 IEEE.
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Recently, due to COVID-19 pandemic, the classes, seminars, meetings are scheduled on virtual platform. It is a need to keep track of the presence of attendees. Earlier online attendance involved extracting the list of attendees, which was inconvenient as a lot of people mute themselves and leave the meeting altogether. Therefore, a tool is required to capture attendance through facial recognition which can effectively identify the attendees who remain online for the whole duration of the lecture. In this paper, a method has been proposed to completely automate the attendance tracking system using the concept of edge computing. The tool runs alongside any video conference platform and tracks the faces of attendees in a random interval, and using face recognition technique, find out the people who remain present for the complete duration of the class. This novel method acts as a fail-proof method to monitor attendance and improve digital transparency. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
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The outbreak of Covid-19 throughout the world caught the whole population unprepared And one of the most common problems includes the availability of medicines. People in need weren't able to get their medical supplies even after visiting number of shops. Hence a location service that helps find the nearest medical store that will display required medicines can solve this problem. This service is widely sourced for everyone to use. The data from the medical stores displays the list of medicines and their availability. A flexible reservation system is implemented to book medicines for immediate purchase and can be collected within few minutes. A location reminder feature is provided in cases where the medicines with less availability are in your vicinity. In this paper, main research on review topics that deals with reservation systems, location finder, online monitoring of medicinal drugs, algorithms to find the shortest distance between the source and the destination is summarized. © 2022 IEEE.
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Human-computer interaction (HCI) focuses on the interaction between humans and computers and it exists ubiquitously in our daily lives, especially in post COVID era where non-face-to-face interaction is common. Since HCI usually uses a physical controller such as a mouse or a keyboard, it hinders National User Interface, giving a middle ground between the user and the computer. This paper presents a vision-based hand tracking system development for non-face-to-face interaction, which aims to improve HCI by being able to track the hand which will act as the pen and functioning as a reusable writing surface for creating texts, drawings, and such as well as removing or erasing using the user's hand as the pen, and utilizing Open Computer Vision Library (OpenCV) and Mediapipe. Using the computer's camera the hand will be tracked as the pen for creating basic drawings and handwriting. The vision-based board where the user can draw on and the pen or marker will be the user's hand. The results indicate that this system is accurate enough to be a feasible application for handwriting ad basic drawings. © 2021 IEEE.
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In recent years, the coronavirus pandemic has caused and continues to cause a large number of deaths today. Governments all over the world have taken measures to reduce the spread of the virus. Home quarantine was proven to be a successful way to control and mitigate the spread of COVID-19. The current methods of tracking home-quarantined people use tracking bracelets or mobile applications, which are still in their early development stage. In this paper, we propose a quarantine tracking system to track users during their quarantine period. The system consists of a web portal designed for the concerned authorities and the quarantined user's mobile application. The proposed application randomly prompts users to verify their quarantine by uploading their selfies. We verify the user's quarantine status through an automatic location and selfie verification. Our system provides a specific set of features that can be set by the concerned authorities, such as the frequency of prompts and the allowed response time. Violation reports can also be accessed by the concerned authorities to keep track of quarantined users' violations. Our results validate the usefulness and potential of our system as a quarantine tracking tool. It also opens the door for further development, allowing governments to handle any upcoming pandemics. © 2021 IEEE.
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The COVID-19 outbreak highlighted the smart healthcare infrastructure requirement to speed up vaccination and treatment. Present vaccination supply chain models are fragmented in nature, and they are suitable for a pandemic like COVID-19. Most of these vaccination supply chain models are cloud-centric and depend on humans. Due to this, the transparency in the supply chain and vaccination process is questionable. Moreover, we con't trace where the vaccination programs are facing issues in real-time. Furthermore, traditional supply chain models are vulnerable to a single point of failure and lack people-centric service capabilities. This paper has proposed a novel supply chain model for COVID-19 using robust technologies such as Blockchain and the Internet of Things. Besides, it automates the entire vaccination supplication chain, and it records management without compromising data integrity. We have evaluated our proposed model using Ethereum based decentralized application (DApp) to showcase its real-time capabilities. The DApp contains two divisions to deal with internal (intra) and worldwide (inter) use cases. From the system analysis, it is clear that it provides digital records integrity, availability, and system scalability by eliminating a single point of failure. Finally, the proposed system eliminates human interference in digital record management, which is prone to errors and alternation. © 2021 IEEE.All rights reserved.
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The game development industry is among the leading industries globally, and in 2020, gaming emerged as a popular entertainment activity upon the COVID-19 outbreak. Thus, competition among gaming companies is high. Hence, they try to adopt new technologies often. Gaming brings multiple feelings for the gamer. At times, the conditions may get even worse from the game's end where the gamer may end up venting out his rage and annoyance. Hence, there is a massive possibility for the gamer to switch to another game which may result in the company to lose its customers. In that scenario, this system can monitor the emotional states of the gamer while playing and manipulate the gaming environment, sound environment, enemy behavior, and gamer mechanism according to the emotional state of the gamer. The sensor-based emotion tracking system identifies the gamer's emotional state using facial emotions, detected through a webcam and heart rate, detected through sensors. The development was carried out through the machine learning models, open cv, Arduino techniques, and reactive programming. The emotional state and facial emotions that will be tracked will count to an accuracy of above 95%. Through that, the target will be to make the gamer satisfied by building appreciation for the services given and by improving the gamer's gaming experience and retain the gamer with the game provider. © 2021 IEEE.
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Vehicles such as bicycles are in great demand during the current COVID-19 pandemic. Trending topics sometimes follow the needs of the community. The existence of Covid-19 makes a person must maintain the body's immunity. One way to maintain the body's immune system is by cycling. The higher the public demand and the less availability of bicycles in the market, the price of bicycles becomes expensive. The high price of bicycles attracts the attention of thieves to commit bicycle theft. Therefore, the purpose of this paper is to create a bicycle safety system that can be monitored in real time. Making a vehicle position monitor using a simple global positioning system (GPS) integrated with a smartphone. The advantage of this paper is that it uses a simple tracking system so that the price is cheaper and easier to make compared to the existing tracking system. The results obtained are that the location is shown to be quite accurate and can be accessed anywhere via a smartphone. On the smartphone, the software application is installed as a user-friendly media user interface. © 2021 IEEE.
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COVID-19 pandemic had disrupted the health, social and economic stability throughout the world. Centers for Disease Control and Prevention (CDC) had proposed various strategies to minimize the spread of virus;the government is implementing these strategies to take good care of victims. Depending on the severity of symptoms, COVID positive patients are either home quarantined or admitted to the hospital. Two essential facilities that ensure a hassle-free journey for COVID patients are i) publicly available transparent hospital management system that publishes the availability of COVID beds. ii) a transparent list of suppliers that delivers food and medicines to the home quarantined patients. Our proposed model i) builds an end-to-end tracking system for COVID patients ii) enables patients to choose their preferred hospital by checking the availability of beds and iii) guarantees a fraud free vaccination system. © 2021, IFIP International Federation for Information Processing.
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Like many countries, Jordan has resorted to lockdown in an attempt to contain the outbreak of Coronavirus (Covid-19). A set of precautions such as quarantines, isolations, and social distancing were taken in order to tackle its rapid spread of Covid-19. However, the authorities were facing a serious issue with enforcing quarantine instructions and social distancing among its people. In this paper, a social distancing mentoring system has been designed to alert the authorities if any of the citizens violated the quarantine instructions and to detect the crowds and measure their social distancing using an object tracking technique that works in real-time base. This system utilises the widespread surveillance cameras that already exist in public places and outside many residential buildings. To ensure the effectiveness of this approach, the system uses cameras deployed on the campus of Al-Zaytoonah University of Jordan. The results showed the efficiency of this system in tracking people and determining the distances between them in accordance with public safety instructions. This work is the first approach to handle the classification challenges for moving objects using a shared-memory model of multicore techniques. © Al-Zaytoonah University of Jordan (ZUJ).