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Traditional access control systems have a series of security and experiential issues, such as easy key forgery, single unlocking method, and difficulty in real-time monitoring and data analysis of access control areas. Combining IoT technology, a smart access control system with high security, intelligence, and networking capabilities was designed using the Smart Microelectronics MM32F5270 development board as the main controller; The system is developed using MindSDK and MircoPython as platforms. Image data is collected by the camera module and processed by MM32F5270. The data is then transmitted to the server through the WIFI module. Obtain facial feature point data based on the received image data combined with the LBP algorithm. And input it into the convolutional neural network to achieve the purpose of face detection. The experimental results show that the smart access control system can effectively solve problems such as poor security, difficult data management, and inability to monitor in real time, improving user experience and system reliability.