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Bayesian Modeling Based on Data from the Internet of Things
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Farzad Eskandari *   , Sima Naghizadeh Ardebili |
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Abstract: (2257 Views) |
The Internet of Things is suggested as the upcoming revolution in the Information and communication technology due to its very high capability of making various businesses and industries more productive and efficient. This productivity comes from the emergence of innovation and the introduction of new capabilities for businesses. Different industries have shown varying reactions to IOT, but what is clear is that IOT has applications in all Businesses. These applications have made significant progress in some industries such as health and transportation but is under development in others, namely agriculture and animal husbandry. In fact, the production of data bases on the Internet of Things is one of the main pillars in the field of big data and data science, Therefore, statistical concepts and models that are used in data science can be beneficially implemented in such data. Among the valid statistical models, Bayesian statistics for data is being utilized in these studies. In this research the fundamentals of Bayesian statistics for big data and most notably the data produced by IOT is explained. They have been Pragmatically examined in both road traffic as well as people’s social behavior towards using vehicles, which have had practically and scientifically valid results.
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| Keywords: Internet of Things, Bayesian Theory, Classification, Visualization. |
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Full-Text [PDF 387 kb]
(887 Downloads)
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Type of Study: Research |
Subject:
Special
Received: 2020/11/20 | Accepted: 2021/03/17 | Published: 2021/03/18
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