Based on the wireless sensor network unmanned driving infringement identification system, this paper focuses on the application of data mining technology and state machine technology and designs and implements a set of practical and effective. Self-driving cars can reduce the frequency of traffic accidents, alleviate urban traffic congestion, improve people’s travel efficiency, and lower the threshold of driving and other social values. The data processing program and a number of algorithms are given, and a complete set of data processing procedures and algorithms are proposed, including the collection of raw sensor data, the preprocessing of the collected data, and the feature extraction of the processed data. In the experiment, the unmanned driving infringement monitoring network was first designed to conduct real-time monitoring of unmanned driving infringements during transportation and application. Aiming at the characteristics of unmanned driving infringements, a monitoring network platform was designed for remote control and large-scale monitoring. Secondly, according to the characteristics of the unmanned driving infringement monitoring sensor network, the unmanned driving infringement node monitoring terminal is designed. The monitoring terminal part mainly designs the sensor module, the wireless communication module, the display warning module power module, and the data mining processing module. The sensor modules, respectively, include temperature, humidity, and concentration sensors, and the communication mode in the communication module mainly adopts Wi-Fi. At the same time, the research is based on wireless sensor network, combined with data mining technology, puts forward a sensory data display system model based on data mining technology, and conducts an in-depth analysis of the sensory data display system model, including the logical level of the system, system architecture, and functional modules. Finally, it focuses on the specific application of data mining technology in environmental information analysis and prediction, uses JAVA programming and realizes a data analysis and display system based on wireless sensor network, and verifies the accuracy of the data mining algorithm. The experimental results analyze the application of data mining technology in the driverless infringement determination system and use a large number of unmanned driving infringements to analyze the determination rules, so as to realize the interaction between active people and driverless cars.
A distributed system model for managing data ingestion in a wireless sensor network