Intelligent Airport Collaborative Decision Making (A-CDM) System

Zheng, Yinger; Miao, Jiahe; Le, Ningning; Jiang, Yunpeng; Li, Yang

doi:10.1109/iccasit48058.2019.8973206

Cited by 7 publications

(5 citation statements)

References 9 publications

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“…However, these articles provide only broad outlines regarding the applicability of 5G with potential use cases and lack detail on the technical aspects of its implementation. Another study, [4], explores areas within an airport that could reap significant benefits from 5G, such as the enhancement of wireless security systems, extensive development in IoT due to an increased number of sensors, the implementation…”

Section: A Related Workmentioning

confidence: 99%

“…High level use case analysis 5G in airports 5G scenarios 5G applicability to airport use cases General analysis of 5G scenarios and user radio exposure [1]- [4], [5]- [7] Specialized study…”

Section: A Related Workmentioning

confidence: 99%

“…[16]- [18], [19]- [22], [23]- [27] 5G network solution Different scenarios Frequency and bandwidth solutions for different scenarios [28], [29] Current manuscript 5G in airports, use cases and solutions 5G applicability for airports, use cases, frequency and bandwidth solutions for the different airport applications and prototype deployment and testing of Internet of Things (IoT) and eMBB use cases of autonomous driving on platforms to enhance safety, and the improvement of customer experience and smart client services. Nevertheless, [4] fails to delve deeper into these areas.…”

Section: A Related Workmentioning

confidence: 99%

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Analysis of 5G Technology in Airports: Requirements, Challenges, and Use Cases Evaluation

Cantizani-Estepa,

Vera-Soto,

Baena

et al. 2023

IEEE Access

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The purpose of this paper is to fill a gap in the existing literature about the general analysis of airport activities and detailed specifications for 5G implementation. The gap spans from overgeneralized studies to highly specific ones as will be mentioned in the paper. This research aims to bridge this gap by identifying the requirements of 5G implementation in various airport use cases, proposing detailed 5G solutions for these cases. As is well known, 5G is the Fifth Generation of cellular communications, aiming to provide high-throughput high-reliability connectivity to greatly diversified scenarios. With this objective, it shall act as a viable solution for environments as complex as an airport terminal, whose dynamic work cycle includes a wide range of diversified activities. As such, 5G capacities are assessed, identifying those airport processes that can benefit from its application as well as the general requirements of the network deployed for such scenarios. From the identified use cases, the streaming of high quality video for aircraft visual inspection as well as the monitoring of luggage trolleys via an IoT system are developed and evaluated, showing the capabilities of the approach.

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Section: A Related Workmentioning

confidence: 99%

Section: A Related Workmentioning

confidence: 99%

Section: A Related Workmentioning

confidence: 99%

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Analysis of 5G Technology in Airports: Requirements, Challenges, and Use Cases Evaluation

Cantizani-Estepa,

Vera-Soto,

Baena

et al. 2023

IEEE Access

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“…The operational rules used to aid object detection at transport airports are not fully applicable at general aviation airports, especially for the helicopter entry and departure process, which differs markedly from that for fixed-wing aircraft [ 1 , 2 ]. Therefore, the recognition method for helicopter entry and departure positions at general aviation airports has strong research and application value [ 3 , 4 ].…”

Section: Introductionmentioning

confidence: 99%

A Self-Learning Mechanism-Based Approach to Helicopter Entry and Departure Recognition

Lyu

Chang

et al. 2022

Sensors

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In order to accurately record the entry and departure times of helicopters and reduce the incidence of general aviation accidents, this paper proposes a helicopter entry and departure recognition method based on a self-learning mechanism, which is supplemented by a lightweight object detection module and an image classification module. The original image data obtained from the lightweight object detection module are used to construct an Automatic Selector of Data (Auto-SD) and an Adjustment Evaluator of Data Bias (Ad-EDB), whereby Auto-SD automatically generates a pseudo-clustering of the original image data. Ad-EDB then performs the adjustment evaluation and selects the best matching module for image classification. The self-learning mechanism constructed in this paper is applied to the helicopter entry and departure recognition scenario, and the ResNet18 residual network is selected for state classification. As regards the self-built helicopter entry and departure data set, the accuracy reaches 97.83%, which is 6.51% better than the bounding box detection method. To a certain extent, the strong reliance on manual annotation for helicopter entry and departure status classification scenarios is lifted, and the data auto-selector is continuously optimized using the preorder classification results to establish a circular learning loop in the algorithm.

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“…The balance between the increasing demand for air traffic and the limited air transportation resources cannot be maintained. Flight delays are increasing day by day, which brings great challenges to the normal operation and security of busy airports [1].…”

Section: Introductionmentioning

confidence: 99%

Research and design of flight plan adjustment system based on cooperative decision mechanism

Li¹,

Liu²,

Shen³

et al. 2022

International Conference on Mechanisms and Robotics (ICMAR 2022)

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Recently, with the continuous improvement of living standards and the rapid development of civil aviation industry, more and more people choose convenient and efficient aircraft as a means of travel, and the number of flights increases rapidly. However, in the process of flight operation, it is inevitable to encounter complicated weather, other airspace user activities or air resource flow restrictions, which seriously affect the flight normality and passenger satisfaction. In order to solve such problems, people also put forward higher requirements for flight time resource management. In this paper, based on the collaborative decision-making mechanism, this paper carries out flight plan adjustment through the early predictions, assessment analysis, dynamic update and so on, implementation of passengers, airlines and flights running related units and efficient coordination, make the flight security requirements and Air traffic control, integrated airport security ability to achieve the optimal matching, to ensure flight safety, stable, orderly, and maintain flight release order, Improve the normal rate of flight clearance.

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Intelligent Airport Collaborative Decision Making (A-CDM) System

Cited by 7 publications

References 9 publications

Analysis of 5G Technology in Airports: Requirements, Challenges, and Use Cases Evaluation

Analysis of 5G Technology in Airports: Requirements, Challenges, and Use Cases Evaluation

A Self-Learning Mechanism-Based Approach to Helicopter Entry and Departure Recognition

Research and design of flight plan adjustment system based on cooperative decision mechanism

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