Abstract
With the rapid development of big data, image analysis technology, and artificial intelligence, the related businesses of smart subways have been gradually realized. Facing the huge passenger flow during peak hours, how to guide passengers to relatively spacious compartments has become a hot issue of concern. This article utilizes big data processing and existing image analysis technology in combination with the original subway system to develop an intelligent subway passenger flow monitoring and guidance system. This system consists of three parts: multi-terminal collection, data analysis, and intuitive guidance. The system has the advantages of high reliability, low cost, and real-time guidance, which is expected to help improve passengers' ride experience and ensure the normal operation of the subway.
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