Optimizing the mathematical model of IoT data processing in smart cities using artificial intelligence algorithms

This article explores how to use artificial intelligence algorithms to optimize the processing of IoT data in smart cities. Firstly, the concepts of artificial intelligence, smart cities, and IoT data processing were introduced; Secondly, the BP algorithm and ant colony algorithm were introduced; Subsequently, taking the optimization of dangerous goods transportation management in smart cities as an example, the most optimized path was explained. The ant colony algorithm simulates the foraging behavior of ants to optimize the search for the optimal path and solution. Therefore, this article proposes a mathematical model that combines BP algorithm and ant colony algorithm for data processing in smart city IoT. By dividing the data into different processing levels, the BP algorithm is used to preprocess and classify the raw data, while the ant colony algorithm is used to find the optimal path and solution during data transmission and storage. This model can improve the speed and accuracy of data processing, providing strong technical support for the construction of smart cities. This study is of great significance for promoting the development of IoT technology in smart cities, providing new ideas and methods for data processing in future smart cities.