ABSTRACT
Transportation problems have always been a global concern. The challenges in traffic congestion were easily observed during pre-pandemic times. However, traffic congestion still persists even during the COVID-19 pandemic (2020 and present) where there has been less number of vehicles because of travel restrictions. The emergence of wireless communication technologies and intelligent transportation systems (ITS) pave the way for solving some of the problems found in the transportation industry. Subsequently, traffic control systems are used at various intersections to manage the flow of traffic and reduce car collisions. However, some intersections are better off without these traffic control systems. The proposed study will analyze a T-junction road in five different setups using different types of traffic controllers. The simulation tool used is SUMO. The study found that an adaptive or vehicle-actuated traffic controller is the ideal method for regulating traffic flow in a T-junction with a one-way or two-way main road. It was observed in the simulation that it reduced the potential car collisions in the non-TL junction. However, the average speed and completion time of the road network was affected by the method. © 2022 IEEE.
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The whole world has been witnessing the gigantic enemy in the form of COVID-19 since March 2020. With its super-fast spread, it has devastated a major part of the world and found to be the most dangerous virus of the 21st Century. All countries went into a lockdown to control the spread of the virus, and the economy dropped down to an all- time low index. The major guideline to avoid the spread of diseases like COVID- 19 at work is avoiding contact with people and their belongings. It is not safe to use computing devices because it may result in the spread of the virus by touching them. This paper presents an Artificial Intelligence- based virtual mouse that detects or recognizes hand gestures to control the various functions of a personal computer. The virtual mouse Algorithm uses a webcam or a built-in camera of the system to capture hand gestures, then uses an algorithm to detect the palm boundaries similar to that of the face detection model of the media pipe face mesh algorithm. After tracing the palm boundaries, it uses a regression model and locates the 21 3D hand-knuckle coordinate points inside the recognized hand/palm boundaries. Once the Hand Landmarks are detected, they are used to call windows Application Programming Interface (API) functions to control the functionalities of the system. The proposed algorithm is tested for volume control and cursor control in a laptop with the Windows operating system and a webcam. The proposedsystem took only 1ms to identify the gestures and control the volume and cursor in real-time. © 2023 IEEE.
ABSTRACT
Some problems of Filipino farmers in Nueva Ecija are irrigation systems and labor shortage. Most of them are unable to work due to old age while others chose to stop because of the COVID-19 pandemic. Meanwhile, irrigation systems have been an issue due to the lack of resources such as continuous water supply and control. Fortunately, there is a progression of smart farming in the country which could assist in optimizing farming processes. This study presents a systematic literature survey on rice farming technologies and challenges. This study also aims to help address these problems by creating a rice irrigation system that introduces a water level control system. The system was comprised of a mobile application, Arduino ESP32 module, and a tank with water level sensors. The mobile application was used to set the desired water level while the proportional- integral-derivative (PID) controller adjusted the water level automatically. When current water level is lower than the setpoint, the valves to the tank will open. Tank specifications were used to come up with a transfer function for the system. The proposed design was simulated in MATLAB Simulink and PID parameters were tuned to enhance system performance. The tuned control system obtained an output response with less overshoot and faster settling time. © 2022 IEEE.
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Sanitization is a protective and strategic approach to contain SARS-CoV2 dissemination. As there is no feasible way to deal with the new COVID-19 pandemic, sanitization has a key role to play. A modified method to reduce the spread of the virus by constructing a fogging room with a disinfectant and a base fluid mixture has been examined. The nanometer-sized corona in micron-sized cough droplets can quickly reach inaccessible areas when infection is present. Therefore, efficient spray and jet method should be used to disinfect certain inaccessible surfaces. A stand-alone photovoltaic (PV) system represents a pollutant-free and cost-effective solution to the stated issue. The present study aims to design sizing of a small-scale solar panel -powered mobile cleaning and disinfection chamber system for coronavirus in Remote Locations. The objective is to evaluate the sizing of the PV system to power the disinfection chamber system that is used to eliminate the spread of the virus at a constant daily load profile. The system is composed of a fogging room, water tank, PV panels, and storage batteries. The disinfection chamber system requires an energy of approximately 218 Wp with about 38 hours of battery storage that can operate the system continuously after the sunset. Powering a mobile cleaning and disinfection chamber system with PV panels has plenty of advantages, including free-maintenance, easy installation, and energy saving. © 2023 AIP Publishing LLC.
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Recently, virus diseases, such as SARS-CoV, MERS-CoV, and COVID-19, continue to emerge and pose a severe public health problem. These diseases threaten the lives of many people and cause serious social and economic losses. Recent developments in information technology (IT) and connectivity have led to the emergence of Internet of Things (IoT) and Artificial Intelligence (AI) applications in many industries. These industries, where IoT and AI together are making significant impacts, are the healthcare and the diagnosis department. In addition, by actively communicating with smart devices and various biometric sensors, it is expanding its application fields to telemedicine, healthcare, and disease prevention. Even though existing IoT and AI technologies can enhance disease detection, monitoring, and quarantine, their impact is very limited because they are not integrated or applied rapidly to the emergence of a sudden epidemic. Especially in the situation where infectious diseases are rapidly spreading, the conventional methods fail to prevent large-scale infections and block global spreads through prediction, resulting in great loss of lives. Therefore, in this paper, various sources of infection information with local limitations are collected through virus disease information collector, and AI analysis and severity matching are performed through AI broker. Finally, through the Integrated Disease Control Center, risk alerts are issued, proliferation block letters are sent, and post-response services are provided quickly. Suppose we further develop the proposed integrated virus disease control model. In that case, it will be possible to proactively detect and warn of risk factors in response to infectious diseases that are rapidly spreading worldwide and strengthen measures to prevent spreading of infection in no time.
ABSTRACT
Problem and Motivation. Medical device remote control technologies can enable remote experts to contribute to patient care during tele-critical care during public health emergencies like COVID-19 to address the shortage of local clinical expertise. The benefit of such technologies may be further amplified if one remote-control application can operate multiple interoperable medical devices (e.g. multiple types of ventilators or IV pumps) to support the typical diversity of deployed medical devices in one institution. However, due to the variation in capabilities of different makes/models of the same device type, this unified remote control capability requires the standardization of the data interfaces of similar devices to provide sufficient information about these devices to enable safe remote control. Method(s): Medical Device Interface Data Sheets (MDIDS) [1] can provide a useful tool for documenting current and future device interface requirements and capabilities. We examined several clinical use scenarios where externally controllable infusion pumps are used to support tele-critical care, based on which we generalized an MDIDS for remotely controllable infusion pumps. To validate this generic MDIDS, we cross-checked it with the capabilities of several externally controllable infusion pumps: the NeuroWave Accupump, Eitan Medical Sapphire, and the BD Alaris GH. Result(s): During the development of the generic remotely controllerable infusion pump MDIDS, we were able to identify the common and specific data elements that different infusion pumps need to provide at their data interfaces, considering the great diversity in these devices related to infusion mechanism, infusion programming methods, device alarms and alerts, and system settings. The resulting MDIDS includes over 100 data elements, many of which are essential for safety, including those common across different pump types (e.g., maximum settable infusion rate, occlusion alarm) and those specific to certain pump types (e.g., syringe size for syringe pumps). We developed the generic MDIDS as the theoretical basis and developed an application in our OpenICE open-source interoperability research platform [2] to remotely control the above three infusion pumps either via serial communication (representing controlling the infusion pump at a distance limited by a physical wired connection inside or outside the patient room) or across the Internet using the web extension service of OpenICE (representing situations where remote experts have no physical access to the patient). Conclusion. MDIDS for externally controllable medical devices can provide a solid basis to improve the safety and interoperability of medical device remote control technologies in the tele-critical care context. They can also benefit the research, development, and testing of physiological closed-loop control systems. We applied the MDIDS methodology to infusion pumps and ventilators to support the integration of these devices to the U.S. Army Telemedicine & Advanced Technology Research Center (TATRC) National Emergency Tele-Critical Care System.
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[Background] The COVID-19 pandemic hints at the importance of modernizing disease control system. To understand the scientific research strength of our country's disease control system in recent years is conducive to formulating more targeted policies or measures to promote the modernization of the disease control system. [Objective] To understand the scientific research strength and research hotspots of China's provincial-level centers for disease control and prevention (CDCs) from 2011 to 2020, and provide evidence for the development of scientific research work, discipline construction, and talent team construction in CDCs in the future. [Methods] The Science Citation Index Expanded (SCIE) and Social Science Citation Index (SSCI) of the Web of Science Core Collection were used to retrieve SCI-indexed English papers published by 31 provincial CDCs (excluding Taiwan Province, Hong Kong and Macau Special Administrative Regions) in our country from 2011 to 2020, and to screen literature with provincial CDCs as the first affiliation for bibliometric analysis and visual analysis. Bibliometric analysis included the SCI-indexed publications of different provincial CDCs (as co-affiliation and the first affiliation), the number of SCI-indexed papers published by provincial CDCs (as the first affiliation) and funding rates by years, the high-frequency authors of SCI-indexed papers published by provincial CDCs (as the first affiliation) and their distribution, and the characteristics of the journals. Visual analysis software Citespace 5.8.R1 was used to draw keyword co-occurrence maps, cluster information tables, and emergence maps to provide information on research hotspots and their evolution. [Results] From 2011 to 2020, the number of SCI-indexed papers from 31 provincial CDCs was 8 420 (including co-affiliation), of which 2 060 papers listed provincial CDCs as the first affiliation. The provincial CDCs of Zhejiang, Jiangsu, Shanghai, Beijing, Shandong, and Guangdong were the leading six institutes in terms of the total number of SCI-indexed papers contributed as co-affiliation or the first affiliation. There was a large gap in the total number of SCI-indexed papers among the provincial CDCs. The highest total number of SCI-indexed papers contributed by provincial CDCs as the first affiliation was Zhejiang CDC (448 papers), while the lowest number was Xinjiang CDC (only 1 paper). From 2011 to 2020, the total number of SCI-indexed papers contributed by the 31 provincial CDCs as the first affiliation showed an overall increasing trend. Except for 2011, which was 63.1%, the funding rates in other years exceeded 70%. In terms of high-frequency authors, 13 first authors published >=10 SCI-indexed papers: Zhang Yingxiu from Shandong CDC had the highest number of SCI-indexed papers (47), followed by Hu Yu from Zhejiang CDC. Zhejiang, Jiangsu, Beijing, Guangdong, Shanghai, and Shandong still ranked the top six of >=4 first authored-SCI papers. In terms of journal characteristics, the top 20 journals with the highest number of SCI papers published a total of 862 papers, accounting for 41.8% (862/2 060), and PLOS ONE ranked the first (188 papers). The research hotspots were mainly concentrated in the fields of infection, child health, and epidemiology. The main keywords of the first three cluster categories were related to the research fields of adolescent overweight and obesity, HIV, and vaccine immunity. The results of keyword emergence showed that research hotspots shifted from overweight, obesity, and body mass index to antibodies, vaccines/vaccination, and cohorts. [Conclusion] The past ten years have witnessed increasing numbers of SCI-indexed papers published by provincial CDCs in our country and a stubbornly high funding rate. However, the gap among the provincial CDCs is still large seeing that economically developed eastern provincial CDCs published more SCI-indexed papers. Research hotspots have gradually shifted from overweight, obesity, and body mass index to antibodies, vaccines/vaccination, and cohorts.Copyright © 022 Shanghai Municipal Center for Disease Control and Prevention. All rights reserved.
ABSTRACT
In the contemporary time of technology, security is the utmost concern for every building automation system. Access Control Systems are the backbone of any security system being employed in any intelligent building, and can be operated in a biometric or non-biometric manner. There are various types of recognition systems available, depending upon the required level of safety and security. The ongoing pandemic has challenged and tested Access Control System in many aspects.This paper aims to review the various forms of access control systems and their viability in the context of COVID-19. It is found that some access control solutions fail to provide the required security during this global epidemic due to their contact-based operations. So, in the midst of the worldwide pandemic, a realistic integrated electronic access control system can be designed to meet the requirements of users. © 2022 IEEE.
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There has been an increase of interest and demand in the usage of logistic indoor service robots that are designed to minimize interactions between humans due to the occurrence of the COVID-19 outbreak. The application of the rising technology in the medical sector has great benefits in the industry, such as the prevention of the spread of highly infectious diseases using distance as a factor. Rooting from the purpose of the said robot, the main focus should be the ease of navigation through achieving the desired trajectory, in order to maximize the functionality, prevent collision, reduce user maneuvering difficulties, and such. Hence, this paper is focused on improving the trajectory errors on the robot navigation performance based on different control system designs specifically, a physical joystick controller and a mobile-based Bluetooth application controller. The design of the joystick is based on a pivot as its base which is directed to all angles and the design of the Bluetooth app is based on fourdirectional buttons that will operate upon clicking, and switching to other buttons to change commands. With this, the researchers conducted linear path and rotational tests using both remote control modes that are based on five varying speed values of 0.75 m/s, 0.5m/s, 0.35m/s, 0.25m/s, and 0.15 m/s. Based on the data analysis, the yielded results showed that using the Bluetooth app lowers the robot's trajectory error by 50% to 60% compared to using ajoystick to navigate to the desired point. Thus, the researchers concluded that the design of a control system greatly affects the robot navigation in achieving the desired trajectory. Considering the nonsystematic errors, a calibration based on the hardware structure design specifically on the caster wheel is recommended. © 2023 IEEE.
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This chapter discusses lessons from the Covid-19 crisis, based on the history of the disease in France and distribution throughout the world. The Covid-19 crisis raises many questions, in addition to those addressed in the deciphering of the epidemic. In addition to the pre-positioning of the epidemic control system, for which the best organization must be found, the tools for analyzing the emergence that have just been presented can be optimized through predictive modeling, propagation scenarios and the study of the consequences of anti-epidemic measures. While no one appears "especially guilty" of the occurrence of the Covid-19 crisis, it is highly unfortunate that real-time epidemic threat analysis systems, whose annual cost can be estimated at 1/10,000th the cost of the epidemic, were not used to contain severe acute respiratory syndrome coronavirus 2. © ISTE Ltd 2022.
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Purpose: Although the use of management control systems (MCS) in crisis management has received extensive attention, limited knowledge exists regarding the benefits of the broad scope, timeliness, integration and aggregation dimensions. This study aims at examining the performance implications of the context-structure combinations of pandemic management strategy (PMS), MCS use and pandemic-induced uncertainty of public health institutions (PHIs) in Ghana. Design/methodology/approach: Data were collected using online survey questionnaire where 246 public health managers qualified for the study. Data were analyzed using covariance-based structural equations modeling (version 23). Findings: PMS was found to have a significant and positive impact on three (broad scope, timeliness and aggregation) of the four dimensions. The integrated dimension was statistically insignificant. In addition, the three dimensions had a significant impact on top managers' satisfaction with MCS use, which in turn impact on cost containment and quality of care. Finally, COVID-19 uncertainty moderated the relationship between MCS use and operational performance. Practical implications: The three dimensions of broad scope, timeliness and aggregation are critical for PHIs when it comes to crisis management. Moreover, the presence of pandemics strengthens the relationship between top manager use of MCS and performance in health care. More sophisticated MCS information is required when managing pandemic-related crisis by PHIs. Originality/value: This study presents a theoretical framework that integrates PMS, MCS use and performance of public health care from a contingency perspective. It extends the benefits of contingency theory to include the three dimensions of MCS with respect to crisis management. © 2023, Emerald Publishing Limited.
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During the current COVID-19 pandemic, the large number of positive cases of infection has resulted in medical institutions lacking personnel to treat patients who continue to arrive. As a result of these problems, supervision and monitoring of room conditions is still lacking or even non-existent, so that the recovery process can be hampered or can facilitate the transmission of the virus to other people. It takes a device or tool that can monitor conditions and regulate the isolation room so that the temperature and humidity remain in the optimal zone so that recovery can be optimal and also reduce the risk of virus transmission. Based on this description, the author applies the concept of IoT by utilizing the IoT platform system and designing a system and tool that can monitor and regulate the COVID-19 isolation room and convey this information quickly and concisely. In addition, this study also examines how well and easily understood the system is when used by end-users by using the System Usability Scale or SUS as its usability testing method. The results obtained from this study are that the system and equipment function properly, the automation system and the method used are able to mitigate changes in temperature and humidity in the isolation room, and through the SUS method, the level of usability for end-users is deemed quite sufficient. © 2022 IEEE.
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To block the epidemics like "Corona Virus Disease 2019(COVID-19)"spreading, an effective isolation of the infected patients during the transportation is an important issue, which makes the negative pressure cabin (NPC) become a key equipment. There exist some practical NPCs in service, whose pressures are mostly controlled using the conventional PID controller with parameters regulated by engineering methods. Until now, there is no report about the model of NPC system from the authors' best knowledge. In this paper, the model of the NPC system is reported, which is an inherent nonlinear system. Because of the nonlinear nature of the cabin pressure, the conventional PID controller cannot achieve desire performance to balance the transient and the steady state performance, even though the optimized PID parameters are chosen using the on-line optimization based on genetic algorithm. To solve such a problem, Tracking Differentiator (TD) and PI controller are combined to achieve the desire performance using the optimized parameters. The experiment results show the improvement of the proposed method. © 2022 IEEE.
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During the post-COVID-19 era, it is important but challenging to synchronously mitigate the infection risk and optimize the energy savings in public buildings. While, ineffective control of ventilation and purification systems can result in increased energy consumption and cross-contamination. This paper is to develop intelligent operation, maintenance, and control systems by coupling intelligent ventilation and air purification systems (negative ion generators). Optimal deployment of sensors is determined by Fuzzy C-mean (FCM), based on which CO2 concentration fields are rapidly predicted by combing the artificial neural network (ANN) and self-adaptive low-dimensional linear model (LLM). Negative oxygen ion and particle concentrations are simulated with different numbers of negative ion generators. Optimal ventilation rates and number of negative ion generators are decided. A visualization platform is established to display the effects of ventilation control, epidemic prevention, and pollutant removal. The rapid prediction error of LLM-based ANN for CO2 concentration was below 10% compared with the simulation. Fast decision reduced CO2 concentration below 1000 ppm, infection risk below 1.5%, and energy consumption by 27.4%. The largest removal efficiency was 81% when number of negative ion generators was 10. This work can promote intelligent operation, maintenance, and control systems considering infection prevention and energy sustainability.
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Internal control is an important internal governance mechanism of enterprises and plays an important role in preventing and controlling corporate risks. This paper utilizes COVID-19 shocks and uses data from listed companies in China for 2019–2021 in order to study the impact of internal control on enterprise resilience and its functioning mechanism. The findings show that internal control significantly improves enterprise resilience during a crisis. By using firm characteristic quantile regressions, it is found that under a crisis, larger firms with sufficient cash flow from operating activities are more protected by internal control and more resilient. Mechanistic analysis suggests that internal control further increases enterprise resilience by improving resource allocation efficiency, reducing operating risk, and increasing innovation output. Further analysis shows that government support can enhance the resilience of firms during crises through tax and fiscal policies;a better business environment enhances firms' ability to withstand risks in crisis situations and helps them gain a competitive advantage in crisis situations. Based on this, this paper provides empirical evidence for revising and improving the internal control system of enterprises to reduce the negative impact of public health emergencies in the context of epidemics. © 2022 by the authors.
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Purpose of Study: Assessment of an individual's postural stability serves as an indirect measure for both physiological and biomechanical stresses placed on an individual. More recently, some individuals after COVID-19 (SARS-CoV-2) infection have been identified with neurological complaints (Post-Acute Sequelae of Covid - PASC). These individuals can also be predisposed to decreased postural stability and an increased risk for falls. The purpose of the project was to incorporate two different wearable technology (virtual reality (VR) based virtual immersive sensorimotor test - VIST and pressure senor-based smart sock) to assess postural stability among healthy and individuals with PASC to quantify the overall status of the postural control system. Methods Used: All methods were conducted based on the University's Institutional Review Board (IRB# 21-296) with informed consent. A total of 12 males and females (six healthy and six with self-reported complaints of PASC) have completed the study so far. All participants were tested using the VIST, while standing on a force platform and wearing the smart sock simultaneously. The (VIST uses a VR headset and proprietary software to test an individual's integrated sensory, motor, and cognitive processes through eight unique tests (smooth pursuits, saccades, convergence, peripheral vision, object discrimination, gaze stability, head-eye coordination, cervical neuromotor control). Center of pressure (COP) data from force platform and pressure sensor data from the smart socks were used to calculate anterior-posterior and medial-lateral postural sway variables. These postural sway variables were analyzed using an independent samples t-test between the healthy and PASC groups at an alpha set at 0.05. Summary of Results: Significant differences (p < 0.05) between healthy and individuals with PASC with anteriorposterior and medial-lateral postural sway variables derived from COP measures, with individuals with PASC exhibiting significantly greater postural sway compared to healthy individuals in all eight tests of the VIST. The measures from the smart sock, while not statistically significant, exhibited the same findings of increased postural sway in individuals with PASC compared to healthy individuals. Conclusion(s): Findings from the current analysis revealed that individuals with PASC demonstrated significantly worse postural control compared to the healthy, when challenged with various sensorimotor tests in VIST, suggesting that postural control is compromised due to PASC. While not statistically significant due to a lower sample size, the measures from smart sock also indicated the same findings of the COP measures, suggesting a promising use of wearable technology in postural control assessments. In addition to other neurological signs and symptoms of PASC, assessment of postural stability using the VIST can provide more detailed clinical measures for diagnosis, treatment, and prognosis assessments. Copyright © 2023 Southern Society for Clinical Investigation.
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The aim of this paper is to provide a literature review of the Supply Chain Management Control Systems as a discipline that converges two fields: the MCS and the SCM. This convergence has as goal the enhance of the organization's performance. Faced with the critical situation and the crisis that the world is experiencing due to the Covid-19 pandemic, companies are today, more than ever, forced to ensure the efficiency of their SCs as a pledge to improve their overall performance. Therefore, the purpose of this article is to provide a review of the role of the MCS in managing and assuring the resilience and the performance of the SC. To get a solid grasp of the structure of MCS research in SCM and study the link between, we conducted a literature review of the articles published between 2016 and 2021. The aim is to provide a view of the recent researches covering the subject of the SCMCS.
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With Online Learning being essential during the COVID-19 pandemic, practical laboratories were forced to be replaced by virtual or remote alternatives. This paper proposes a Simulator App built on MATLAB environment that provides students of introductory Automatic Control System subject a simulated experimental environment to learn system and transfer function identification of DC Motor-Tachogenerator system. The features of the Simulator App are discussed, followed by design of experiments suitable to be carried out using the Simulator App. Experimental results and student feedback show that the Simulator App is a feasible virtual alternative to the physical laboratory experiments. © 2022 IEEE.
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This study examines the determinants of managerial performance which consist of management control systems, organizational culture, and organizational commitment. The analysis was carried out using multiple linear regression with the SPSS version 22 program. The object studied was a health care institution in the South Tangerang area with data collected from 52 respondents. The results of the study show that partially, the management control system, organizational culture and organizational commitment have a significant positive effect on managerial performance. Simultaneously, all independent variables have a significant effect on managerial performance. [ FROM AUTHOR]
ABSTRACT
Masked face recognition is becoming an essential requirement in most of the facial recognition based access control and authentication systems, particularly after the Covid-19 pandemic. The work analyses the capability of Region Based Convolutional Neural Networks (R-CNN) for masked face detection and demonstrates a facial recognition system with R-CNN in hardware. R-CNN uses Region Proposal Networks (RPN) that can extract non-occluded region on an image and feed it to a Deep Neural Network for recognition. The R-CNN classifier running on the region containing the non-occluded part of the face will be used for classification in case of a masked face. In case of recognition of unmasked face, the classifier will be run on the region containing the face. By this way, the system will be able to recognize face for both cases. Python modules like opencv, numpy have been used for image pre-processing, while Tensorflow has been used for image classification. Custom dataset is used for training. The trained deep learning model is evaluated using a confusion matrix heat-map which can be used to know the reliability of the model. The demonstration system consists of a Raspberry Pi module connected to a door actuator and a camera. On successful authentication, the system opens the door. © 2022 IEEE.