The Internet of Things has been introduced as the next revolution in information and communication technology with its high potential to make businesses more productive in various fields, including industries. This productivity is in the field of innovation and providing new capabilities for businesses. Different industries have shown different reactions to the Internet of Things, but what is clear is that the Internet of Things has applications in all businesses and industries. These applications have made significant progress in some industries, such as health and the health sector or transportation, but are developing in other industries, such as agriculture and animal husbandry. In fact, data production based on the Internet of Things will be one of the main pillars in the field of fog data and data science. Therefore, the use of statistical concepts and models used in data science can be used well in this type of data. Among the valid statistical models is Bayesian statistics for fog data, which is the basis for use in this research. In this research, while introducing important and valid concepts used in the field of fog data, the principles of Bayesian statistics for fog data and specifically for data from the Internet of Things have been explained. In practical terms, the social behavior of individuals has been studied in two areas for interest in using vehicles and urban traffic, which has yielded valid results from a scientific and practical point of view.