Abstract: In the rapid development of information technologies including big data and cloud computing, national parks—key carriers of ecological civilization construction—are shifting from static, top-down governance toward dynamic, data-driven approaches. This paper proposes the concept of "real-time management" for national parks, which breaks through the spatiotemporal limitations of conventional models through high-frequency data acquisition and intelligent optimization algorithms. It requires management entities to quickly analyze large-scale multidimensional data, generate timely management decisions, and when necessary, implement them directly through automated systems, thus forming a closed-loop mechanism of sensing, decision-making, and execution. The study demonstrates the necessity and feasibility of real-time management, explores its significance in both methodological and practical dimensions. Specifically, it effectively responds to dynamic ecosystem changes, optimizes the balance between ecological conservation and recreational use, and enhances the scientific rigor and flexibility of management practices. Furthermore, the integration of real-time management with existing adaptive management frameworks is recommended to better achieve ecological protection goals of national parks alongside public interest.