ABSTRACT
This paper presents a control system for indoor safety measures using a Faster R-CNN (Region-based Convolutional Neural Network) architecture. The proposed system aims to ensure the safety of occupants in indoor environments by detecting and recognizing potential safety hazards in real time, such as capacity control, social distancing, or mask use. Using deep learning techniques, the system detects these situations to be controlled, notifying the person in charge of the company if any of these are violated. The proposed system was tested in a real teaching environment at Rey Juan Carlos University, using Raspberry Pi 4 as a hardware platform together with an Intel Neural Stick board and a pair of PiCamera RGB (Red Green Blue) cameras to capture images of the environment and a Faster R-CNN architecture to detect and classify objects within the images. To evaluate the performance of the system, a dataset of indoor images was collected and annotated for object detection and classification. The system was trained using this dataset, and its performance was evaluated based on precision, recall, and F1 score. The results show that the proposed system achieved a high level of accuracy in detecting and classifying potential safety hazards in indoor environments. The proposed system includes an efficiently implemented software infrastructure to be launched on a low-cost hardware platform, which is affordable for any company, regardless of size or revenue, and it has the potential to be integrated into existing safety systems in indoor environments such as hospitals, warehouses, and factories, to provide real-time monitoring and alerts for safety hazards. Future work will focus on enhancing the system's robustness and scalability to larger indoor environments with more complex safety hazards.
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.
ABSTRACT
Digital technologies that could meet these new challenges and aid manufacturing scale-up and speed to market, such as automated digital data collection and augmented and virtual reality (AR/VR) remote collaboration tools, were already available and had been adopted by some, but the new demand spurred greater adoption. "There is a cultural aspect to digitalization because it's a significant investment that results in changes to the operational structure of a facility;it is beneficial when the digitalization comes from the top," explains Yvonne Duckworth, automation engineer and Industry 4.0 subject matter expert at the CRB Group, a life sciences engineering and construction company. Machine sensors and process analytical technology (PAT) instruments can communicate directly with data collection systems using the NoT. Efficient development and tech transfer for mRNA vaccine manufacturing The data analysis and clear communication allowed by digital tools has demonstrated its benefits for process development and technical transfer, making time to market faster.
ABSTRACT
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.
ABSTRACT
This paper presents the development of a dynamical tropical algebra-based model of a vaccination center, which can be used to control and optimize the admission of users during center's operation. In addition, an analysis of closed-loop control methods designed to maximize the system performance in terms of service rate and minimize users' waiting time, while observing occupancy constraints due to social distancing protocols recommended by sanitary authorities due to Covid epidemic, is presented. © 2023, Brazilian Society for Automatics--SBA.
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.
ABSTRACT
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.
ABSTRACT
High hygiene standards were established during the COVID-19 epidemic, and their adherence was closely monitored. They included the need to regularly wash one's hands and the requirement to cover person's upper airways or keep at least a two-meter space between individuals. The ITS (Information Technology Systems) community made a big contribution to this by developing methods and applications for the ongoing observation of people and the environment. Our major objective was to create a low-cost, straightforward system for tracking and assessing the danger of spreading COVID-19 in a space.The proposed system collects data from various low-cost environmental sensors such as temperature, humidity, CO2, the number of people, the dynamics of speech, and the cleanliness of the environment with a significant connection to elements of wearable electronics and then evaluate the level of contamination and possible risks and, in the event of a high level of risk, alerts the person to take actions that can reduce or eliminate favourable conditions for the spread of the virus. The system was created at the Laboratory of industrial control systems of the University of Žilina, Slovakia. The experiment demonstrates the ability and feasibility to control the number of people in a space depending on particular symptoms like fever, coughing, and hand hygiene. On the other hand, the laboratory's temperature, humidity, and air quality should be controlled to reduce the spread of illness.
ABSTRACT
In load frequency control (LFC) study of a large power system, the key concept is control area, which is the segment of the system consisting of strongly interconnected buses, generator buses thereof working in unison. For accurate linearization of load frequency control problem, proper determination of control area is important. In the present work, a novel deterministic method is proposed and formulated to calculate the sharing of load changes by the generators to determine the control areas for LFC study of multimachine systems. This method is applied on a weakly interconnected two-area system and then on the 10-Machine New England Test System for area segmentation of each of the two systems. Furthermore, LFC studies are carried out with proposed Fuzzy Rule-tuned PID controllers (FRT-PID Controllers) for both the systems incorporated with Dish-Stirling Solar thermal system (DSTS) in each area. The scaling factors and the controller gains are optimized using Coronavirus Herd Immunity Optimizer Algorithm (CHIOA). Performance of the proposed FRT-PID controllers is compared with that of the Conventional PID controllers for the LFC studies of the systems. To test effectiveness of the FRT-PID controllers, effect of random step load perturbation (SLP) in load buses located in different areas are considered. © 2023 Elsevier B.V.
ABSTRACT
In view of the fact that Covid-19 is highly contagious, which poses great threat and inconvenience to people's production and life, a multifunctional robot control system with single-chip microcomputer as the control core is designed, aiming at the problems of centralized isolation points in communities, complicated situation and difficult management. Firstly, Gmapping algorithm is used to realize the robot's autonomous positioning and avoidance. Secondly, a three-degree-of-freedom robot arm is designed to disinfect any indoor space. Finally, Gmapping algorithm is used to recognize and measure the temperature of human face. Through the simulation experiment, this method can improve the efficiency of searching the shortest path and carry out disinfection work while reducing human contact, improving public safety and has practical value. © 2023 IEEE.
ABSTRACT
There are many inevitable disruptive events, such as the COVID-19 pandemic, natural disasters and geopolitical conflicts, during the operation of the container port supply chain (CPSC). These events bring ship delays, port congestion and turnover inefficiency. In order to enhance the resilience of the CPSC, a modified two-stage CPSC system containing a container pretreatment system (CPS) and a container handling system (CHS) is built. A two-dimensional resilience index is designed to measure its affordability and recovery. An adaptive fuzzy double-feedback adjustment (AFDA) strategy is proposed to mitigate the disruptive effects and regulate its dynamicity. The AFDA strategy consists of the first-level fuzzy logic control system and the second-level adaptive fuzzy adjustment system. Simulations show the AFDA strategy outperforms the original system, PID, and two pipelines for improved dynamic response and augmented resilience. This study effectively supports the operations manager in determining the proper control policies and resilience management with respect to indeterminate container waiting delay and allocation delay due to disruptive effects.
ABSTRACT
Office-based environmental control systems are centralized and designed to control entire spaces, ignoring use dynamics and requirements, and despite being regulated by standardized comfort models, they fail to satisfy real occupants, mainly due to their varied individual characteristics. This research is field-based with a quantitative approach and correlational design. Its objective is to empirically demonstrate that open-plan design, where different users share the same space and generalized environmental conditions, lacks a holistic view of IEQ criteria and the integration of other factors that affect health and well-being. Four buildings are chosen in different Chilean cities, measuring temperatures and CO2 levels at different desks, and applying a survey, which was designed as part of the research to analyze the estimation of relationships between variables and to reveal the factors that cause differences among occupants. The results show that people's satisfaction is multivariable and depends on other factors that positively or negatively stimulate their sensations and perceptions, such as, for example, the option to personally control their environmental conditions. Likewise, it is evident that to achieve comfort, health is being affected while in the building.
ABSTRACT
In this paper, we propose and investigate the SIQR epidemic model with a generalized incidence rate function, a general treatment function and vaccination term. We firstly consider the existence and uniqueness of the global nonnegative solution to the deterministic model. Further, we show the locally asymptotic stability of the disease-free equilibrium and endemic equilibrium of the deterministic model, and obtain the basic reproduction number R0. Then we study the existence and uniqueness of the global positive solution to the stochastic model with any positive initial value. Meanwhile, we obtain sufficient conditions for the extinction of the disease in the stochastic epidemic model, and find that the large noise can make the disease die out exponentially. Finally, we make an empirical analysis by the COVID-19 data of Russia and Serbia. By the performance comparison of different models, it shows that the model with vaccination and treatment we proposed is better for the real situation, which is also verified by different estimation methods. Especially, that shows the recovery rate of the infected increases by 0.042 and the death rate of the recovered is 1.525 times that of normal human in Russia. Through statistical analysis, the short-term trend of epidemic transmission is predicted: under the condition of unchanged prevention and control policies, it may reach a stable endemic equilibrium state in Russia and the epidemic will eventually extinct in Serbia. © 2023 Elsevier Inc.
ABSTRACT
Increasing demand for automation is being observed especially during the recent scenarios like the Covid-19 pandemic, wherein direct contact of the healthcare workers with the patients can be life-threatening. The use of robotic manipulators facilitates in minimizing such risky interactions and thereby providing a safe environment. In this research work, a single link robotic manipulator (SLRM) system is taken, which is a nonlinear multi–input–multi–output system. In order to address the limitations like heavy object movements, uncontrolled oscillations in positional movement, and improper link variations, an adaptive fractional-order nonlinear proportional, integral, and derivative (FONPID) controller has been suggested. This aids in the effective trajectory tracking of the performance of the SLRM system under step input response. Further, by tuning the controller gains using genetic algorithm optimization (GA) based on the minimum objective function (JIAE ) of the integral of absolute error (IAE) index, the suggested controller has been made more robust for trajectory tracking performance. Finally, the comparative analysis of the simulation results of proportional & integral (PI), proportional, integral, & derivative (PID), fractional-order proportional, integral, & derivative (FOPID), and the suggested FONPID controllers validated that the FONPID controller has performed better in terms of minimum JIAE and lower oscillation amplitude in trajectory tracking of positional movement of SLRM system. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
ABSTRACT
The recent outbreak of novel coronavirus has highlighted the need for a benefit-cost framework to guide unconventional public health interventions aimed at reducing close contact between infected and susceptible individuals. In this paper, we propose an optimal control problem for an infectious disease model, wherein the social planner can control the transmission rate by implementing or lifting lockdown measures. The objective is to minimize total costs, which comprise infection costs, as well as fixed and variable costs associated with lockdown measures. We establish conditions concerning model primitives that guarantee the existence of a straightforward optimal policy. The policy specifies two switching points (Formula presented.), whereby the social planner institutes a lockdown when the percentage of infected individuals exceeds (Formula presented.), and reopens the economy when the percentage of infected individuals drops below (Formula presented.). We subsequently extend the model to cases where the social planner may implement multiple lockdown levels. Finally, numerical studies are conducted to gain additional insights into the value of these controls. © 2023 Wiley Periodicals LLC.
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This study presents a new auto-tuning nonlinear PID controller for a nonlinear electric vehicle (EV) model. The purpose of the proposed control was to achieve two aims. The first aim was to enhance the dynamic performance of the EV regarding internal and external disturbances. The second aim was to minimize the power consumption of the EV. To ensure that these aims were achieved, two famous controllers were implemented. The first was the PID controller based on the COVID-19 optimization. The second was the nonlinear PID (NPID) optimized controller, also using the COVID-19 optimization. Several driving cycles were executed to compare their dynamic performance and the power consumption. The results showed that the auto-tuning NPID had a smooth dynamic response, with a minimum rise and settling time compared to other control techniques (PID and NPID controllers). Moreover, it achieved low continuous power consumption throughout the driving cycles. © 2023 by the author.
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This article discusses about the design and deployment of a smart robotic system on university campuses for monitoring the indoor environment, health protocols, and sanitation. The designed VEX autonomous robotic system performed the following tasks: (a) moving around the university classrooms and scanning the body temperature of students and staff, as well as tracking environmental parameters in classrooms;(b) executing sanitation function by disinfecting objects in classrooms;and (c) performing security function by sending an alert signal to health and safety officer if a student or staff with fever enters the classroom, or if staff or student is not wearing face mask indoors. Particle Photon microcontrollers linked to sensors and actuators were used to detect and manage indoor environmental conditions as well as track individuals' body temperatures from a distance, with the data being stored in the ThingSpeak and Particle cloud platforms and displayed on smartphone apps. Transfer learning through MIT App Inventor's Personal Image Classifier was used to detect health protocol violations with 93.33% accuracy. The maximum distance traversed by the robot prototype was 38 meters, with an average time of 220 seconds and an average speed of 0.17 meters per second. The robot had an 88.89% success rate in following the black-lined course. This intelligent robotic system can limit staff and student exposure to infectious diseases and implement "new normal"health and safety practices on campus as post-COVID-19 precautions. © 2023 IEEE.
ABSTRACT
Ventilators we are available with have several drawbacks such as difficult to port, expensive and meant to be operated by professionals which create hardness in fighting with medical care. Thus, it creates suffering for people in the pandemic like COVID19. So, it is required to develop a ventilator that can be affordable, easy to port and install. We aimed to design a IoT based ventilator system using various electronic devices such as microcontroller and sensors that could monitor patient's body status. People suffering from COVID19 or any lung disease find difficulty in breathing so in such condition of emergency this smart ventilator system can be used. Ambu bag is used to provide certain volume of air that is pressed by using motor mechanism. A portable low-cost ventilator with computerized controlling and feedback system is installed. Ventilator designed can be connected to an interface for smart functioning. This paper provides us with different methods to monitor the patient's health condition by measurement of pressure, level of breathing to know whether the condition is healthy or unhealthy. The designing and developing of low-cost portable ventilator deliver breaths to patients when Ambu bag is compressed by using a piston connected to servo motor whose speed can be varied. Input of the designed system is patient's heart beat and breathing rate and the volume of oxygen provided to patient's lung with required beathing rate is the output of the system. PID (proportional Integral Derivative) and Full state feedback H2 controllers are used for the performance analysis of the system. Result of this review paper is found that a low-cost ventilator is developed removing all the possible shortcomings of existing conventional ventilator. Ventilator designed is portable and smart by using Arduino, servo motor and ambu bag preferred for emergency uses and available for clinical application. © 2023 IEEE.