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Aiming to address the issues of low data execution efficiency and slow storage speed on traditional tourism cloud service platforms, a rural tourism management cloud service platform based on an embedded system is proposed. The embedded device components, such as the ARM processor, NOR Flash memory, and RTL network chip, are utilized to optimize the hardware structure of the cloud service platform. This optimization aims to enhance data processing and storage efficiency, as well as improve the reliability and durability of system operation. The unstructured feature grasping algorithm is employed to gather rural tourism resource data for target demand characterization. Associated algorithms are then utilized to develop data analysis, service recommendation, and tourism management modules, creating a comprehensive tourism cloud service platform. Additionally, the shortest path algorithm is used to enhance database storage speed, improve business docking efficiency, establish a big data monitoring center, comprehensively monitor changes in the scenic area and related industries, and enhance platform service efficiency. It has been proven through experiments that the latency of the tourism management cloud service platform, based on the embedded system, is reduced by almost 46.7% compared to the traditional approach, and the throughput is increased to 0.69 b/s. The practical application effect is positive, as it contributes to the development of tourism resources and the economic growth of rural areas. It also brings about economic and social benefits.
Shanshan Luo (Fri,) studied this question.