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In 2020, the Covid-19 virus has become a global pandemic, which started in the Chinese province of Wuhan and spread around the world, The aim of the present study is to discuss the most important and latest methods of tracking Covid-19 patients and the strategies followed by developed countries in integrating digital technology to control the epidemic, it also covers the most important issues and discusses the difficulties these technologies as well as how people interact with and feel about the use of this type of technology. Among these methods used, are those developed by technology companies in cooperation with telecom companies, such as Covid-19 patient tracking applications that rely on raising case information. These applications have been effective (GPS, Wi-Fi, and Bluetooth), as also the most important prevention measures to be followed and symptoms that are likely to appear on infected or carriers of the virus have been announced by global health agencies, which have been accepted all over the world. In this paper we present. A progressive of digital solutions technologies from the methods used to confront COVID-19 since the appearance of the first case used to control and stop the spread of the pandemic and track infected people, to the contemporary technologies in use, depending on the country used for each of these strategies as well, in addition to the most prominent issues that impede these preventive methods. Then there are the advantage and disadvantages of these technologies, by analyzing the different features of contemporary technology in order to combat the COVID-19 pandemic, we provide a window of ideas for reviewing technological advances used to reduce and control the spread of the epidemic. Despite the emergence of various studies related to modern technology towards COVID-19, there are still limited applications and contributions of technology in this battle. On-going progress in modern technology has contributed to improving people's lives and hence there is a solid conviction that validated research plans including artificial intelligence will be of significant advantage in helping people to fight this infection. [ABSTRACT FROM AUTHOR]

During the COVID-19 pandemic, the world has witnessed rampant use of digital technology in almost every facet of huma lives. However, these digital techniques like use of mobile apps have certain drawbacks and constrains. These could be addressed with the use of emerging technologies like Internet of Things (IoT). In healthcare, that is Internet of Medical Things (IoMT). A number of ongoing studies show that integrating security measures with technology will lead to the adoption of stable IoMT applications. Emerging IoMT technologies used in conjunction with Blockchain, Artificial Intelligence, and Big Data, provide feasible solutions. The paper focuses on IoMT models, innovations, and security progress made to tackle COVID-19 issues. This paper contains the bibliometric research highlighting the use of disruptive technology for the diagnosis of COVID-19. It reviews the adoption of contactless services in the post-COVID-19 period along with potential opportunities as well as challenging obstacles for healthcare agencies, policymakers, and customers. [ABSTRACT FROM AUTHOR]

During the COVID-19 pandemic, the world has witnessed rampant use of digital technology in almost every facet of huma lives. However, these digital techniques like use of mobile apps have certain drawbacks and constrains. These could be addressed with the use of emerging technologies like Internet of Things (IoT). In healthcare, that is Internet of Medical Things (IoMT). A number of ongoing studies show that integrating security measures with technology will lead to the adoption of stable IoMT applications. Emerging IoMT technologies used in conjunction with Blockchain, Artificial Intelligence, and Big Data, provide feasible solutions. The paper focuses on IoMT models, innovations, and security progress made to tackle COVID-19 issues. This paper contains the bibliometric research highlighting the use of disruptive technology for the diagnosis of COVID-19. It reviews the adoption of contactless services in the post-COVID-19 period along with potential opportunities as well as challenging obstacles for healthcare agencies, policymakers, and customers. [ABSTRACT FROM AUTHOR]

Since the emerging coronavirus pandemic spreads worldwide, countries continue to find new ways to combat and control the spread of "Covid-19." As part of the virus-fighting efforts, information on diagnostic procedures, infection and symptoms, and the most recent therapy and vaccine research have been updated. The main objective of this paper is to reduce the enormous load on the healthcare system by providing the best way to diagnose patients and predict the infection of COV-19 effectively. As a result of the scientific development in computers and their applications, this science has treated many medical problems. However, clinical trials and human skills are still required despite the undeniable contributions of artificial intelligence (AI) and data research responsible for fighting the pandemic. They are a global and open-source tool capable of assisting in this health emergency. However, due to the severity of the threat of this virus to global health and its rapid development, these solutions remain insufficient to combat it. This research paper uses data mining based on algorithms of AI and machine learning (ML) to detect and diagnose COVID-19 infection based on clinical diagnostic tests prepared previously in the Iraqi Ministry of Health. The model was provided with a dataset of the COVID-19 virus using the Python programming language. To create the model where the model predicts whether this person is infected or not infected with the virus, and if it is proven that he is in the danger zone (reaching death), can he bypass the virus and be cured. The current study results showed that the model was developed using the Random Forest Classifier algorithm more efficiently to predict infection with the Coronavirus. This represents the best model developed among other models that used various algorithms, such as Gaussian Naive Bayes, k-nearest neighbors, Support vector machine, Logistic Regression, Random Forest, Gradient boosting, Multi-layer Perceptron. [ABSTRACT FROM AUTHOR]

The COVID-19 (Corona virus disease 2019) outbreak induced millions of human beings the loss of life, still spread of the disease was unstoppable and was declared a pandemic with the aid of the WHO (World Health Organization). Therefore, human beings across the world are nevertheless getting contaminated every day. Reverse Transcription Polymerase Chain Reaction (RT-PCR) to identify COVID-19 is not feasible in terms of both cost and time of identification, which might cost the patient's life. Therefore, to make identification economical and feasible, researchers were attempting to use clinical images (x-ray and CT etc.,) to detect COVID-19 with the assist of Machine Learning (ML) and Artificial Intelligence (AI) approaches to aid in automating the identification of the pandemic. This paper helps in understanding some ML and AI approaches for detecting COVID-19 from clinical lung images. The amassed records about accessible research sources and inspected a complete of 30 research papers until august 2021. This paper includes the exploration and analysis of data sets, pre-processing methods, segmentation approaches, feature extraction, classification, and test effects, which can be useful for discovering future lookup instructions in the area of automated analysis of COVID-19 sickness the usage of AI-based frameworks. [ABSTRACT FROM AUTHOR]

Since early months of 2020s, when Corona virus disease-2019 (COVID-19) first appeared, the major challenge for the healthcare sector was to identify, monitor the disease and take timely decision for the treatment and management of the patients. However, the extreme spread of the disease in 2020 brought scarcity of laboratory diagnostic kits. This is how radiology became a forefront method during the outbreak of COVID-19 for diagnosis and treatment of the disease. Several studies have recently been reported using AI-based methods to diagnose COVID-19 from non-COVID pictures after training them on X-ray and CT scan images. However, to overcome the limitations of the CT, the purpose of the present paper is to develop a deep learning model to distinguish and diagnose COVID-19 and non-COVID pneumonia in chest radiographs using ResNet50 model. Only three steps: Resizing, Training and Heatmap generation were conducted on dataset. An overall accuracy of predicting COVID-19 pneumonia on ResNet50 model was found to be 85% with a specificity of 88% and sensitivity of 81% using Confusion matrix. The precision value for COVID and non-COVID pneumonia cases was 90% and 80% respectively. Thus, the current model of ResNet50 would aid radiologists in the deployment of AI-based approaches for the speedy and accurate classificationof COVID-19 cases and further control future behavior of the pandemic. [ABSTRACT FROM AUTHOR]

In this modern era the automation and artificial intelligence plays an important role. Automation not onlyincreases the quality and the productivity but it also improves the efficiency and safety of the labor or workers. By using automation we can reduce the production time. On the other hand artificial intelligence enables us to do the multitasking. By using it we can take our decision faster and smarter. In this paper we had combined the artificial intelligence with automation, in which the robotic ARM will firstly detect the cylinder by using camera. Then the gripper will moves towards the cylinder, then open its hands and pick up the cylinder and place it at required destination. We used a general purpose robot simulator in an integrated develop environment. After simulation we successfully implement it on a robotic ARM with the help of Arduino board using 18 channel servomotors. This robotic arm will firstly detect the vegetable and move towards it. While picking and placing the vegetable it had been take care that the shape of the vegetable was not deformed, so that vegetable can used in cooking vegetable. This process can also play a major role in delivering the fruits in a hospital room and living room to a person who is infected by a coronavirus disease. [ABSTRACT FROM AUTHOR]

The goal to promote human limits is for Artificial Intelligence (AI). It takes a posture on public administrations, represents the increasing availability of regaining clinical data and the rapid creation of intelligent strategies. The need to stress the need to use AI in the fight against the COVID-19 crisis. The paper outlines the main role played by Ai technologies in this unprecedented war and introduces a survey of AI methods used for multiple purposes in the fight against the outbreak of COVID-19. This paper also explains how the body temperature and coughing of the incoming person are assessed and whether the incoming person has not a protective facial mask. Should either of the above tests disqualify the participant, an alarming device invokes the local officials; the entrant may otherwise enter the premises after his/her hand has been sanitized. [ABSTRACT FROM AUTHOR]

Due to the huge fast spread of Covid-19 around the world, which resulted in the loss of many lives, the maximum level of emergency was triggered all over the world. The best way to reduce COVID-19 infection is to prediction it early based on artificial intelligence (AI). To determine whether the patient has COVID-19 infection or not. An accurate and effective diagnosis system for Covid-19 was proposed in this paper. The diagnostic parameters for right and left lungs, D-dimer, and physiological parameters such as SpO2, temperature, and heart rate were collected from CT scans (three RGB colors) for right and left lungs, D-dimer, and physiological parameters such as SpO2, temperature, and heart rate. The data was collected from 300 patients, with each patient receiving 10 samples; 114 of them were infected with Covid-19, while the remaining 186 were uninfected. For training, testing, and verifying the gathered data, an artificial neural network (ANN) on one hidden layer at 20 nodes-based Backpropagation method was used. For all diagnostic parameters, a total of 30,000 samples were obtained (300 patient x 10 parameters x 10 samples per patient). The 3,000 data samples (300 individuals, 10 samples each) were divided into three datasets: 70% for training ANN (2,100 out of 3,000 samples), 15% for testing ANN (450 out of 3,000 samples), and 15% for validation ANN (450 out of 3,000 samples) (450 out of 3,000 samples). In terms of ANN performance, correlation coefficient, error, mean absolute error (MAE), and histogram, the results of COVID-19 diagnosis based on ANN were studied. The MAE for training, validation, and testing at 20 nodes, respectively, was 0.0012, 0.012, and 0.013, indicating that the ANN achieves good diagnostic accuracy. In training, validation, and testing at 20 nodes, the correlation coefficient (R2) between the actual and estimated value was 0.9999, 0.9996, and 0.9998, respectively. In terms of correlation coefficient and MAE, the suggested technique beat the current state-of-the-art. [ABSTRACT FROM AUTHOR]

During the evolution of the COVID-19 outbreak, the necessity for companies to re-evaluate and restructure themselves is still not greater. It will make sense for things to change in the business operations. Most companies redesigned current existing ways of running business operations and capacity to make choices to benefit. The present condition sees Artificial Intelligence as a significant facilitator for companies to make their existing situation better (recover from their economic crisis), reconsider (prepare for a long-term change) and reinvent (completely re-engineer) their business model for long-term gain. Automated bots that could identify items and carry out duties that were previously reserved for people would make companies and other infrastructures operational around the clock, through more significant numbers, and at a lower cost. Simulated actual working conditions, including labour forces, would be created by using Artificial intelligence platforms. Businesses would use machine learning and sophisticated business intelligence to use artificial intelligence to explore better market dynamics and provide consumers with "hyper-personalized" goods. Some of the most compelling case studies can have human intelligence and expertise mixed with AI. Many firms should revamp current business processes and capacity to benefit the company in the near future. In this research paper, we have showcased how artificial intelligence would benefit businesses as they adopt with these current developments and during a condition of pandemic without inhibiting their activities. The research is carried in a descriptive way, choosing the diverse sectors in the economy like Banking & Finance, Manufacturing, Education, Retail, Telecommunications, Entertainment and media to make the research more robust and reliable. [ABSTRACT FROM AUTHOR]

The recent outbreak of COVID-19 across the globe has been a challenge not just to the health & well-being of people. However, it has also led to a downturn in the economy throughout the world. The purpose of this study is to thoroughly investigate the possible use of emerging technologies such as robotic process automation (RPA) and artificial intelligence (AI) in order to find ways to tackle corona virus, its impact on the economy, and the people. The other technology involved is RPA which is a type of process that can easily and efficiently make it convenient for any machine to handle a repetitive task. When these two technologies are coupled, they can be used in a wide range of applications. This paper explains how RPA and AI can separately, used in various industries and sectors to tackle and effectively reduce the corona virus pandemic's negative impact. [ABSTRACT FROM AUTHOR]

The Latest emergency issues are impacting the world as a result of the new 2019 corona virus rise and pandemic. It has spread to the worldwide and afflicted people to Covid-19. The virus transmitting has regarded as being transmitted by individuals who find it a convenient disease explosion. While coughing and sneezing the infection spreads from the infectious droplets. Although in the air, these droplets will still survive and transfer the virus on to humans. In worldwide, robots have been used to alleviate the proliferation of new corona virus infections, COVID-19 with food preservation, food supplies, sanitation tasks, spraying disinfectant, temperature monitoring, hand sanitizers distributing, work on sensitizing, etc. For fast strategizing, that are considered hazardous for human beings. This paper discuss the difficulties and opportunities associated with using humanoid robots to minimize the risk of spread of COVID-19 in.public healthcare. The primary application of humanoid robots is the minimization of individual interaction in public places, and the provision of containment to hygiene, disinfectants and helping. The following discussion aims to underline the value of humanoid robot's purposes in specific and to link their use as the COVID-19 perspectives. Throughout the testing, review and diagnosis of a vulnerability and for subset of events, artificial intelligence plays a crucial role. It may be used during potential for the forecast of events but also to record the number of alternative cases, restored instances and deaths. Technology based on artificial intelligence is being used to provide outstanding services such as the detection and substitution of drugs for the care of employees by robotics for the provision of prescriptions and nutrition in clinics. It also disinfects the substances in response to the spread of Covid-19. [ABSTRACT FROM AUTHOR]