Artificial Intelligence (AI) intent is to facilitate human limits. It is getting a standpoint on human administrations, filled by the growing availability of restorative clinical data and quick progression of insightful strategies. Motivated by the need to highlight the need for employing AI in battling the COVID-19 Crisis, this survey summarizes the current state of AI applications in clinical administrations while battling COVID-19. Furthermore, we highlight the application of Big Data while understanding this virus. We also overview various intelligence techniques and methods that can be applied to various types of medical information-based pandemic. We classify the existing AI techniques in clinical data analysis, including neural systems, classical SVM, and edge significant learning. Also, an emphasis has been made on regions that utilize AI-oriented cloud computing in combating various similar viruses to COVID-19. This survey study is an attempt to benefit medical practitioners and medical researchers in overpowering their faced difficulties while handling COVID-19 big data. The investigated techniques put forth advances in medical data analysis with an exactness of up to 90%. We further end up with a detailed discussion about how AI implementation can be a huge advantage in combating various similar viruses.
It is irrefutable that blockchain and artificial intelligence (AI) paradigms are spreading at an incredible rate. The two paradigms have distinctive level of innovative nature and multidimensional business propositions. Blockchain innovation can robotize instalments to grant a way for exchanging personal records, information, and logs in a secure, and decentralized manner and can be revealed digitally in the digital currency era. As of late, blockchain and AI are two of the most trending technologies. Blockchain can administer connections among members with no mediator via smart contracts. AI, then, offers insight and dynamic capacities for machines just like people. In this survey, we provide a comprehensive overview about the applications of AI in blockchain. We audit, and sum up the rise of blockchain applications, and stages explicitly focusing on the AI research area. We likewise recognize and summarize open challenges in using blockchain and AI techniques. We also classify the effect of the cloud with these two innovations with respect to the computerized economy, which includes Blockchain as a Cloud and Blockchain as a Service. We moreover survey difficulties and issues identified while provisioning these technologies. It has been found that the integration of AI and blockchain is trusted to make various prospects. Such techniques provide scientists and authorities with an accuracy of up to 90% when taken properly into consideration.
In this paper, machine learning (ML) strategies have been utilized in predicting vehicles’ prices and good deals. Vehicle value prediction has been considered one of the most significant research topics with the rise of IoT for sustainability. This is because it requires observable exertion and massive field information. Towards generating a model that anticipates the vehicles’ price, we applied three ML methods (neural network, decision tree, support vector machine, and linear regression). However, the referenced methods have been applied to function together as a group in a hybrid model. The information utilized was gathered from an information and computer science school that houses different datasets. Separate exhibitions of several ML techniques were contrasted to reveal which one is suitable for the accessible information index. Various difficulties and challenges associated with this design have also been discussed. Moreover, the model was experimented, and a 90% precision was achieved. This potential result can help in providing precise vehicle deals in the emerging Internet of Things (IoT) for the sustainability paradigm.
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