دسته بندی:
بینایی ماشین - Machine vision
سال انتشار:
2022
عنوان انگلیسی مقاله:
A turnaround control system to automatically detect and monitor the time stamps of ground service actions in airports: A deep learning and computer vision based approach
ترجمه فارسی عنوان مقاله:
یک سیستم کنترل چرخش برای شناسایی و نظارت خودکار بر مهرهای زمانی اقدامات خدمات زمینی در فرودگاهها: یک رویکرد مبتنی بر یادگیری عمیق و بینایی کامپیوتری
منبع:
ScienceDirect- Elsevier- Engineering Applications of Artificial Intelligence, 114 (2022) 105032: doi:10:1016/j:engappai:2022:105032
نویسنده:
None
چکیده انگلیسی:
As it is widely known, several ground services are provided by the airports for the domestic and international
flights of the commercial passenger aircraft. Some of these services are conducted during the period called
as the turnaround which starts with the parking of the aircraft in the aprons before the flight and ends with
their leave from the aprons for the flight. Turnaround processes achieved in short time periods allow using the
limited airport resources including the service vehicles and staff effectively. In addition, commercial reputation
losses and financial losses that may arise from delays can be reduced as well as the delay-associated turnaround
penalties. In this article, a deep learning and computer vision based system that detects and allows monitoring
the airport service actions is proposed. The proposed system is capable of analyzing all the primary ground
services for an aircraft parking on its apron by employing the RGB video frame sequences obtained from a
single fixed camera focusing on the apron. In the service detection and analysis modules of the proposed airport
ground service analysis system, some deep learning-based subsystems and in-house-developed algorithms were
included and utilized. For the training of the machine learning models, a study-specific dataset was used and
the constructed learning models were evaluated on real-life cases. Experimental results obtained as a result of
the performance evaluations show that the proposed system is quite successful with precision rates over 90%
in the detection and analysis of the airport ground services. This study is one of the limited research studies
in which deep learning and computer vision techniques have been applied to detect and analyze the ground
service actions. The proposed system is also capable of real-time data processing/analysis and concurrent
service action monitoring. Furthermore, it allows monitoring when the service is received by stamping the
times of service start/end. In a consideration of industrial relevance or operational perspective, such a system
may facilitate the airport ground service management noticeably and reduce the delay-associated costs caused
by the timing of the ground services.
keywords: سیستم کنترل گردش فرودگاه | نظارت بر حرکت چرخشی | شناسایی وسایل نقلیه فرودگاهی | تشخیص چرخش | خدمات فرودگاهی | Airportturnaroundcontrolsystem | Turnaroundactionmonitoring | Airportvehicledetection | Turnaroundactiondetection | Airportgroundservices
قیمت: رایگان
توضیحات اضافی:
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