ABSTRACT
For decades artificial intelligence (AI) has been used for various applications in the healthcare industry. Machine learning and artificial intelligence algorithms allow us to diagnose and customize medical care and follow-up plans to get better results, and during the covid19 pandemic, it was found that AI models have been using to predict the Covid-19 symptoms, understanding how it spreads, speeding up research and treatment using medical data. However, it is very challenging to make a robust AI model and use it in a real-time and real-world environment since most organizations do not want to share their data with other third parties due to privacy concerns, furthermore, it is difficult to build a generalized prediction model because of the fragmented nature of the patient data across the healthcare system. To solve the above problems, this paper presents a solution based on blockchain and AI technologies. The blockchain will securely protect the data access and AI-based federated learning for building a robust model for global and real-time usage. © 2022 Global IT Research Institute-GiRI.
ABSTRACT
COVID-19 contact tracing, maintaining social distance from an infected person, and spotting the hotspots is a difficult and time taking process. Many traditional methods can be used for this purpose but these methods have limited capabilities. Using these methods the process becomes more complex, slower, and difficult. This process involves the storage and sharing of personal data that requires security and privacy. To address these issues, we have proposed a blockchain, AI, and IoT-based framework for COVID-19 contact tracing and distancing. In this framework, Every user registers on the blockchain and gets public and private key pairs, the access level of every user is defined in the smart contract. The activity data of the user is collected using the smartwatch, which ensures real-time and accurate data collection. The data is encrypted with the keys of the data owner and stored on the cloud. So in case of data leakage, no one can decrypt the data without keys, so in this way, the secure data storage issue is resolved. Every transaction is recorded on the blockchain, it makes auditing easy in case of any malicious data transaction. Every user can access data according to its access level defined in the smart contract, it ensures the security of data. By the analysis of data, the ML model predicts the infected person and spot the COVID-19 hotspot areas. © 2021 IEEE.
ABSTRACT
For decades artificial intelligence (AI) has been used for various applications in the healthcare industry. Machine learning and artificial intelligence algorithms allow us to diagnose and customize medical care and follow-up plans to get better results, and during the covid19 pandemic, it was found that AI models have been using to predict the Covid-19 symptoms, understanding how it spreads, speeding up research and treatment using medical data. However, it is very challenging to make a robust AI model and use it in a real-time and real-world environment since most organizations do not want to share their data with other third parties due to privacy concerns, furthermore, it is difficult to build a generalized prediction model because of the fragmented nature of the patient data across the healthcare system. To solve the above problems, this paper presents a solution based on blockchain and AI technologies. The blockchain will securely protect the data access and AI-based federated learning for building a robust model for global and real-time usage.
ABSTRACT
The year 2020 continues to be nerve-racking for each of us with unaccomplished promises, dubious challenges and frustrating milieu in the wake of novel COVID-19 rife. The current scenario impels us to attune a new lifestyle which seems to be common among the rich and the poor despite the varying social standards. This pandemic has a deep impact on our lives at the individual and communal level;including the educational sector, agricultural sector, business, industry, tourism, medical sphere, government and non-governmental organizations. With the increasing Corona reports, our country remains shut since the month of March, affecting the lives of millions of students and teachers. As the saying goes, “Our progress as a nation can be no swifter than our progress in education. The human mind is our fundamental resource.” (John F. Kennedy);education is the key to unlock the enthralling future. Hence, the education system cannot stay frozen until everything becomes run-of-the-mill as it may take a long period for the virus to be immobilized globally. Thus, the education experts came up with the proposal to incorporate distance education mode into proximate education system, which is quite appreciable, but challenging at the same time. This paper shall decode the stand of different methodologies like mind-mapping, instructional design, adaptive learning, classroom-flipping, situational language teaching, task-based language teaching, multiple intelligence, content and language integrated learning (CLIL), self-learning, and how these techniques can be integrated to enhance online learning without hampering cognitive learning styles: visual, auditory, and kinesthetic;in a way useful, multi-sensory, friendly, effective and interesting especially for the Arts stream, thereby discussing how we can solve the ramifications of online-learning to a great extent, provided both learner and teacher autonomy are encouraged. Besides, this paper shall discuss the integration of learning and teaching strategies as per the global trends of education system curtailing rote learning. © 2021, Universitatea de Vest Vasile Goldis din Arad. All rights reserved.