In recent years, public security safety has been one of the core issues of high concern to the whole society. Building a smart patrol command and dispatch system has become one of the development directions for public security organs in response to the increasingly complex and ever-changing public security situation. This article was based on big data technology, analyzing the characteristics and value of patrol data, and using methods such as machine learning and deep learning to construct a smart patrol command and scheduling system for public security, in order to improve the efficiency and level of public security work. By applying experimental testing methods and comparing with traditional methods, performance data of the public security intelligent patrol command and dispatch system can be obtained. Experimental data showed that the stability of the intelligent patrol command and scheduling system based on big data technology reached 86%, accuracy reached 88%, security reached 84%, and work efficiency reached 85%. After comprehensive testing, the performance, safety, and stability of the public security intelligent patrol command and dispatch system have been effectively verified.