关键词: 智慧国家公园, 人工智能, 生态质量与服务功能, 人为干扰

Abstract:

Objective: In this study, a smart national park technology system was built with artificial intelligence (AI) as the core, through integrating space-air-ground monitoring data, AI algorithms, and ecological mechanism knowledge, to break through the technical bottlenecks of precise understanding of the dynamic processes of complex ecosystems in national parks, intelligent fusion of multi-source heterogeneous data, and precise simulation and deduction of management strategies. The system construction aims to realize the intelligent management of the entire process and cycle of monitoring, analysis, evaluation, decision-making in national parks, comprehensively improving the governance capacity and protection effectiveness of national parks. Method: Based on the demand for intelligent development of national parks, a smart national park system architecture with AI as the core was proposed, and a four layer system framework including infrastructure layer, data resource layer, business function layer, and application service layer was constructed. Design key technical modules included the space-air-ground integrated perception network, a big data intelligent fusion processing platform, an AI intelligent analysis center, and a digital twin decision-making platform. Focusing on five typical application scenarios of intelligent protection, intelligent monitoring, intelligent evaluation, intelligent management, and intelligent utilization, the implementation path and core technical support of AI based smart national parks were systematically elaborated. Result: This system utilized an integrated space-air-ground perception network to achieve comprehensive precision monitoring of ecological elements across the entire area. Based on a big data platform, it integrated and cleaned multi-source heterogeneous data. An AI analysis hub was used to deeply mine and predict ecological processes and change patterns. The digital twin platform was used to achieve the real-time 3D reproduction of the ecological situation and precise deduction of management strategies, which enhanced the data processing capability and intelligent decision-making efficiency of national parks, and provided scientific, precise, and intelligent decision-making solutions for intelligent management. Conclusion: The smart national park technology system can effectively address the inefficiency and insufficient intelligence of existing management models, and realize a comprehensive, multi-dimensional, long-term, and refined understanding and efficient management of national park ecosystems. It provides a technical pathway and practical example for addressing the theoretical challenges of understanding complex systems in nature reserves and adaptive management. It has important theoretical value and promotion significance for driving the transformation of the national park governance system towards being data-driven and intelligently decided, thereby strengthening the function of the national ecological security barrier.

Key words: smart national park, artificial intelligence (AI), ecological quality and service function, human interference