This paper investigates the passenger-flow-control problem, aiming to shorten the average waiting time for passengers. An intelligent flow-control scheme is proposed to optimally alleviate the congestion problem in the subway system.
Since the data that is gathered in the subway is multimodal, spatial and dynamic, the proposed intelligent assistant should ensure building complex workflows for data processing that involve a wide application of machine learning techniques (ML workflows).
In order to ensure the safe and efficient operation of subway stations, it is necessary to obtain air quality data and passenger flow information in subway stations in real time.
Furthermore, the proposed model is specifically designed to excel in foggy environments. As a practical application, we develop an intelligent assistant focused on enhancing subway passenger safety. We present case examples involving jammed objects, such as shoes, in escalator combs.
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The intelligent assistants use AI techniques for solving tasks of monitoring and management of technically complex social objects of urban infrastructure. An intelligent assistant for subway …
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The Improved-YOLO, an improved You Only Look Once algorithm based on the YOLOv4, showed satisfactory performance in passenger flow detection in subway stations and can provide …
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To fill these gaps, this study introduces a novel knowledge–data dual-driven framework augmented by deep learning, which harnesses hybrid data to enhance the …
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Article Open access Published: 23 September 2023 Urban intelligent assistant on the example of the escalator passenger safety management at the subway stations Man …
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An intelligent flow-control scheme is proposed to optimally alleviate the congestion problem in the subway system. Experiments show that the proposed flow-control scheme …
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In order to ensure the safe and efficient operation of subway stations, it is necessary to obtain air quality data and passenger flow information in subway stations in real …
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