Enabling Healthcare 4.0 for Pandemics. Группа авторов
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Figure 1.4 Machine learning approach for reuse of drug in COVID-19.
1.3 AI and Machine Learning as a Support System for Robotic System and Drones
Although the life is quite difficult during these pandemic times, still the AI is enabling to make it somehow easy by providing assistance. All of us know well that in order to avoid the spread of the virus, the easies and the best solution is the avoidance of social gathering [15]. AI-based drones are being used by the government to perform this task without any need of manpower. Government is using these drones and robots in the public areas to keep an eye on people and to check whether the people are actually following social distancing or not. Drones are also used in hospitals and COVID centers to transfer food, medicines and other utility items to the patient without getting in direct touch with the patient [16]. AI-based robots can be used in the areas where patients are being kept to sanitize the area. Positioning of these AI-based systems can help out the medical staff by reducing the direct contact with the patient and observing the patient’s health status too [17].
1.3.1 AI-Based Location Tracking of COVID-19 Patients
One more AI-based technology adopted by the government is to track the location of person by the information obtained from their mobile phone to determine the contact history of the patient and to isolate the contacted people for further avoiding the transmission [18]. Many of the countries including China, Spain etc. are adopting this system to control the spread of pandemic. New Zealand has no new COVID case and all of the previous cases have been recovered, and the main reason behind this was to track the patient and all its contacts by using AI-based location tracker and keep them in strict isolation [19]. Apart from these AI technologies has been used in multiple ways to fight with the pandemic. Artificial Intelligence can be used to recognize and check the outspread of the virus transmission. Different AI technologies are being used by the researchers, experts, doctors etc. Various AI-enabled chatbots can be used to provide information about the COVID-19 [19]. Its real life example is “Aarogyasetu” App used by the Indian government to track the corona patient and to provide information about COVID-19 to all the registered users.
1.3.2 Increased Number of Screenings Using AI Approach
It is concluded that the nations having large number of COVID tests are somehow working better in controlling the spread of COVID-19. More the number of tests more is the information received about how to control the transmission of the pandemic. So in that case, government can plan better strategies for controlling the transmission. Precise screening at various places must be considered on high priority [19]. So manual screening in such a large amount on everyday basis is not possible. Hence, AI-based approach for conducting large number of tests can be used in such scenario. This AI-based approach for screening of people can work by monitoring the temperature of the population even when they are on the move [20]. If any variation in the temperature is to be found, the system notify the same to the authorities for taking any further action and the person is kept in isolation for further controlling the transmission. Many countries have already started this technology to control the situation caused by pandemic including China, Israel etc.
1.3.3 Artificial Intelligence in Management of Resources During COVID-19
This pandemic is spreading more by each passing day and till the time of development of vaccine; the resources like PPE kit, COVID testing kit etc. which are limited and related to the pandemic l are needed to be managed. So with the help of machine learning approach, it can be easily identified which person is more susceptible towards the disease and needed to be tested first, in order to decide the healthcare professionals that the person should be tested or not leading to the better management of the resources [21].
1.3.4 Influence of AI on Manufacturing Industry During COVID-19
COVID-19 pandemic impacted a lot on the manufacturing market because of lockdown on the whole country. A report stated that around seventy five percent of the business got declined in the manufacturing industry in the month of March. So in general it can be said that COVID-19 affected overall manufacturing process ranging from purchasing, repository, shipping, handling, dispatching, distribution and customer market [21]. However, Artificial Intelligence can somehow control the negative impacts of pandemic on manufacturing industry. The key areas where the machine learning and artificial intelligence approach can be used in manufacturing industry are as:
1 Pre-prediction of the upcoming demand of the product for the management and planning of stock manufacturing and distribution: Stock pre planning is an important task needed to be done before the start of manufacturing because the demand of customer is varying in the market due to lockdown. The situation even gets worse because in order to plan, there is no previous data available of any pandemic. Thus there may be the possibility that due to this variation in the demand, there will be overbuying or under buying of the product [22]. With the help of pre prediction of product demand, the stock manufacturing and distribution can be managed in a better way, leading to the increasing profit and more customer satisfaction. The available prediction approaches are capable of predicting market needs only on the basis of previously available data. As there is no previous data available of inventory in pandemic, Artificial Intelligence can easily plan the upcoming demand of the product even in the tough circumstances like COVID-19. Usage of social media content, analytical data of market demographics including stocks and earnings to the predictive model, complementing the previous traces of inventory inputs is one of the best indicators of demand pattern of the product. Through this arrangement, it is feasible to have a customer centric manufacturing mechanism exhibiting better efficiency for inventory control in order to maintain optimum inventory costs [23].
2 Remote maintenance of the products: At the time of this pandemic, producers want to control their instruments and manage their employees from home or any other remote location, as a fault in the any of the component or unit can lead to the failure of the entire production system. This can lead to the non availability of the product in the market and thus cause loss in the business. Machine Learning based prognostic maintenance approach can be used in such an area for the purpose of monitoring the data, observing the records of staff, accounts, finances, expenditure, revenue etc. using real time data. Machine learning methodology has the ability to uncover even the slight patterns in the records or any document. It can also reveal that which areas are needed to be focused as they are at high risk. It actively diverts the supplies, material and staff towards that area before a threat matures into a real time disaster. This results into the cost cutting, optimal use of manpower, improvisation of management process and above all contentment of the client thus upgrading the overall manufacturing process [18].
3 Social Distance Monitoring in the repositories: The best possible solution to deal with this pandemic is to main social distancing so Artificial Intelligence based tool to manage and monitor the social distancing between the employees can be used. Such tools work by first monitoring the location of the employee and then apply some AI-based protocol to keep them away if they are in contact with each other either by sending signal or the message to the employee [24].
4 Automatic Checking/Evaluation for maintaining the quality of the product in the organization: Automatic checking for maintaining the product’s quality can be done in the industries visually using Artificial Intelligence based approach. Various processes can be evaluated ranging from packing, transportation etc. in the stockroom. It has been discovered that evaluation that can be done visually, can find out more faults in manufacturing and packaging [25]. Automatic evaluation is fruitful in areas such as:a) Finding of any fault in the auto industry.b) Finding of fault in very large scale integration IC foundryc)