Abstract: Against the backdrop of the continuous advancement of biodiversity conservation strategies, Xishuangbanna, as the core distribution area of the wild Asian elephant (Elephas maximus) in China, has witnessed a significant increase in its population due to the implementation of long-term ecological conservation projects. With the in-depth integration of new-generation information technologies, an intelligent monitoring and early warning system for Asian elephants, built on cloud computing, big data analytics and artificial intelligence algorithms, has achieved a leapfrog improvement in the efficiency of ecological monitoring and conservation through the collaborative operation of multi-modal sensing devices. However, despite the adoption of infrared cameras, intelligent speakers and other multi-equipment in the existing Asian elephant monitoring and early warning system in Xishuangbanna, several critical issues persist due to the lack of unified data interface standards: low access efficiency caused by incompatible protocols of heterogeneous devices, insufficient integration efficiency resulting from fragmented data formats, and delayed early warning responses due to inconsistent transmission standards. In the system operation framework, data interface standards serve as the technical link for the interconnection and interoperability of heterogeneous devices. Their standardization level directly determines the integrity of data processing, the reliability of data transmission, and the effectiveness of analytical applications. This paper focuses on the analysis and discussion of these existing problems, aiming to provide technical references for the standardized construction of monitoring systems for Asian elephants and similar wild animals, and to promote the AI-driven upgrading of Asian elephant conservation.