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Introducing self-sustainable cloud platform for data management and extraction of actionable knowledge for smart healthcare industry: a COVID-19 case study

January, 1970

Journal Name:

DOI: 10.1049/icp.2022.0311 move

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The novel COVID-19 is a highly contagious disease. Data scientists worldwide are attempting to respond to the pandemic by building Artificial Intelligence (AI) solutions like forecasting pandemic growth, speculating possible mutations, identifying the symptoms caused, and many more. The models require vast quantities of data to make predictions. For a newly identified virus, it may take many months or sometimes years to collect related data and prepare it for data analysis purposes, which can further delay the process of making AI solutions. Hence, there is a need for a pipeline system which can facilitate a quick transmission of medical data from healthcare providers to data scientists. This paper proposes a cloud computing platform that allows smart cities to respond to the pandemic faster, with the collaboration of public health centers and data scientists. The platform provides a structured way of identifying and utilizing collaboration opportunities between health centers and the data science community, generating actionable knowledge. The system consists of two parts: 1) The software on the hospital's side, allowing real-time data gathering and automated uploading to cloud servers, 2) The cloud system to facilitate data storing along with model building and deploying. Customers can use the deployed models on a prepaid basis, the money collected will be divided among data scientists and data providers. This unique feature ensures the healthy participation of data providers in the process of making healthcare solutions for the smart cities. A sponsor can also sponsor a project. Hence, the system will sustain on its own with the involvement of stakeholders.