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Controller on-duty state detection system and method based on machine vision

A machine vision and state detection technology, applied in the field of aviation control, can solve the problems of waste of manpower, high misjudgment rate and low efficiency of controllers falling off duty or off duty, so as to reduce the misjudgment rate of off duty and going off duty, and improve control Service quality and the effect of preventing unsafe incidents

Pending Publication Date: 2021-12-17
CHENGDU CIVIL AVIATION AIR TRAFFIC CONTROL SCI & TECH +1
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

This method not only wastes manpower, but also is inefficient, and cannot completely prevent accidents from happening
The existing technology is aimed at the detection methods of controllers off-post and sleep-off, and mostly judges whether the controller is in the state of sleep or off-post from a single aspect, and the misjudgment rate of the controller's sleep or off-post is extremely high, which cannot meet the requirements of the on-duty control site. Detection of off-post behavior and sleep-on-post behavior of controllers

Method used

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  • Controller on-duty state detection system and method based on machine vision
  • Controller on-duty state detection system and method based on machine vision

Examples

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Embodiment 1

[0042] Such as figure 1 As shown, the embodiment of the present invention provides a machine vision-based controller duty status detection system, including:

[0043] The data acquisition device adopts a fixed-angle camera to collect control seats in a fixed area, and receives monitoring video data of the control seats in real time; it is also used to receive flight plan data, duty attendance data and GPS clock data in real time;

[0044] The on-duty information analysis module is used to detect, calculate and analyze the control seat monitoring video data, flight plan data and on-duty attendance data, and obtain the detection data of the controller's on-duty situation; specifically, analyze the flight plan data to obtain the opening and closing status of the control sector Data; analyze the on-duty and attendance data, and obtain the information on the on-duty personnel and on-duty time of the control seats. Moreover, through the GPS clock data, the system time is synchroniz...

Embodiment 2

[0055] Embodiments of the present invention provide a machine vision-based controller on-duty state detection method, such as figure 2 shown, including the following steps:

[0056] Step 1: Receive control seat monitoring video data, flight plan data, on-duty attendance data and GPS clock data in real time from the seat video data interface, flight plan data interface, on-duty attendance data interface, and GPS data interface respectively;

[0057] Step 2: Carry out data analysis, storage and preprocessing on the monitoring video data of the control seat, flight plan data, on-duty attendance data and GPS clock data;

[0058] Step 3: Analyze the flight plan data to obtain the opening and closing status data of the control sector; analyze the duty attendance data to obtain the information on the duty personnel and the on-duty time of the control seat. In addition, through the GPS clock data, the system data calculation server time is synchronized to the monitoring video data a...

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Abstract

The invention discloses a controller on-duty state detection system and method based on machine vision, and the system comprises a data collection device which is used for receiving the monitoring video data of a control seat in real time; a position analysis module which is used for carrying out regional division on the control seat monitoring video data according to the control seat spatial positions through a spatial positioning method to obtain the position coordinates of the control seats in the monitoring video data; a target detection module which is used for performing human body target detection on the control seat monitoring video data through a convolutional neural network target detection algorithm to obtain a central point coordinate of a human body target; an off-duty analysis module which is used for calculating the distance between the center point coordinate of the human body target and the position coordinate of the control seat in the monitoring video, and if the distance is larger than or equal to a preset value, judging that the controller is off-duty. The safety of air traffic control can be improved.

Description

technical field [0001] The invention relates to the field of aviation control, in particular to a machine vision-based controller duty state detection system and method. Background technique [0002] With the continuous and rapid growth of airspace flight traffic, under the impact of the two major waves of safety and development, the work of air traffic safety services is facing great challenges. Air traffic controllers are responsible for directing and monitoring the take-off, flight and landing of aircraft in the air and on the ground, which is directly related to the safety of passengers on board. On July 8, 2014, China Eastern Airlines B737-800 / B-5731 aircraft carried out the mission of flight MU2528. When it contacted the control tower during the approach phase in Wuhan, the controller fell asleep on the post, and no one answered many calls, so it failed to communicate with the control tower. Established contact and went around under the command of the approach control...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/00G06N3/04G06N3/08
CPCG06N3/08G06N3/045
Inventor 王磊邱俊王建王雪峰王浩霖王珂
Owner CHENGDU CIVIL AVIATION AIR TRAFFIC CONTROL SCI & TECH
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