Intelligent Transportation System Based on IoT Technology and Big Data Distributed Storage Algorithm

With the accelerated urbanization in China, the contradictions and problems in the process of road traffic development are becoming more and more serious, which have a serious impact on the future healthy development of cities. In order to solve the increasingly serious urban traffic problems, this paper uses the Internet of Things (IoT) and data mining (DM) to collect, analyze and process the massive data in cities and realize the integration of various uncertain information processing models. This enables the construction of an efficient massive semantic DM platform for intelligent transportation big data, supported by this platform, Develop a software system for big data analysis and mining for intelligent transportation. It mainly studies the real-time road condition judgment and the impact of vehicle speed on road congestion, and improves the existing matching algorithm. It uses random forest, decision tree and ant colony algorithm (ACA) for comparative research, and finds that the accuracy of the ACA is as high as 92%. This method can effectively solve the path selection problem of cars during driving, thereby reducing traffic pressure and reducing transportation costs.