CN112794197B - Rail transit escalator control system and method - Google Patents
Rail transit escalator control system and method Download PDFInfo
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- CN112794197B CN112794197B CN202011580227.XA CN202011580227A CN112794197B CN 112794197 B CN112794197 B CN 112794197B CN 202011580227 A CN202011580227 A CN 202011580227A CN 112794197 B CN112794197 B CN 112794197B
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B66—HOISTING; LIFTING; HAULING
- B66B—ELEVATORS; ESCALATORS OR MOVING WALKWAYS
- B66B29/00—Safety devices of escalators or moving walkways
- B66B29/005—Applications of security monitors
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B66—HOISTING; LIFTING; HAULING
- B66B—ELEVATORS; ESCALATORS OR MOVING WALKWAYS
- B66B25/00—Control of escalators or moving walkways
- B66B25/003—Methods or algorithms therefor
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B66—HOISTING; LIFTING; HAULING
- B66B—ELEVATORS; ESCALATORS OR MOVING WALKWAYS
- B66B27/00—Indicating operating conditions of escalators or moving walkways
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Abstract
The invention provides a rail transit escalator control system and a rail transit escalator control method, wherein the system comprises an image acquisition module, a data acquisition module and a data acquisition module, wherein the image acquisition module is used for acquiring image data of a station in real time, and the image data is used for indicating passenger flow density, passenger flow trend speed, passenger taking conditions on an escalator and article conditions on the escalator in different areas in the station; the image analysis module is used for receiving the image data in real time, analyzing and judging the image data and generating an analysis result; the central control module is used for receiving the analysis result and sending a control instruction; the escalator execution module is used for receiving the control command and controlling the escalator to perform an action matched with the control command; by adopting the system and the method, the escalator is intelligently controlled, and passengers on the escalator are intelligently monitored.
Description
Technical Field
The invention belongs to the technical field of rail transit escalators, and particularly relates to a rail transit escalator control system and method.
Background
In recent years, escalators have become increasingly used and become one of the essential transportation means in public places such as stations, shopping malls and subways. The escalator is used as large-scale mechanical equipment, and once an accident occurs, the consequences are unreasonable. The abnormal behavior of passengers is the main reason of safety accidents of the escalator; meanwhile, the escalator is used as the most main passenger transport equipment of a subway station and is also used as equipment with high energy consumption in the station, and no matter the number of passengers on the escalator, the escalator generally needs only to accelerate the passengers to the set nominal speed for running, and if the number of the passengers is small, the escalator still maintains the high speed, so that the energy consumption is high and waste is caused.
Disclosure of Invention
In order to overcome the technical defects, the invention provides a control system and a control method for a rail transit escalator, and aims to solve the problems.
In order to solve the above problems, the present invention provides a rail transit escalator control system, including:
the image acquisition module is used for acquiring image data of a station in real time, wherein the image data is used for indicating passenger flow density, passenger flow moving speed, passenger condition on an escalator and article condition on the escalator in different areas in the station;
the image analysis module is used for receiving the image data in real time, analyzing and judging the image data and generating an analysis result;
the central control module is used for receiving the analysis result and sending a control instruction;
and the escalator execution module is used for receiving the control command and controlling the escalator to perform an action matched with the control command.
Further, the method also comprises the following steps:
and the information transmission module is used for transmitting the image data to the image analysis module in a wired or wireless transmission mode, and the information transmission module is also used for transmitting the analysis result to the central control module in a wired or wireless transmission mode.
Further, the analysis result comprises an abnormal behavior analysis result of the passenger on the escalator;
and the image analysis module generates an abnormal behavior analysis result of the passenger when the passenger falls down or moves in the reverse direction or the head and the hands extend out of the hand strap of the escalator according to the image data.
And the central control module receives the abnormal behavior analysis result of the passenger on the escalator and sends out an alarm instruction or a control instruction of the corresponding escalator running speed.
And the escalator execution module receives the alarm instruction or the running speed control instruction and controls the corresponding voice broadcast and running speed of the escalator.
Further, the analysis result comprises a passenger flow density analysis result;
the image analysis module generates a passenger flow-free analysis result when judging that the same area or adjacent areas have no passenger flow according to the image data;
the central control module receives the passenger flow-free analysis result and sends a control instruction for maintaining the energy-saving running speed;
and the escalator execution module receives the control instruction for maintaining the energy-saving running speed and controls the escalator in the area to maintain the energy-saving running speed.
Further, the analysis result comprises the analysis result of the speed change of the escalator when different passengers flow;
the image analysis module synchronously generates corresponding escalator speed change analysis results when the escalator passenger flow density with the running direction consistent with the passenger flow direction in the same image data analysis region is within preset different density thresholds; and tracking and analyzing the walking of the passengers, and sending an analysis result of the speed change of the escalator when the passengers reach a preset position.
The central control module receives the escalator speed change analysis result and sends an escalator speed control instruction to the corresponding escalator;
and the escalator execution module receives the escalator speed change instruction and accelerates or decelerates the escalator to the running speed matched with the preset density threshold value.
Further, also comprises
And the display module is used for displaying a video corresponding to the abnormal behavior analysis result of the passenger when the central control module receives the abnormal behavior analysis result of the passenger on the escalator.
In order to solve the above problems, the present invention also provides a method for controlling a rail transit escalator, the method comprising:
s1, acquiring image data of the station in real time, wherein the image data are used for indicating passenger flow density, passenger flow moving speed, passenger condition on the escalator and article condition on the escalator in different areas in the station;
s2, receiving the image data in real time, analyzing and judging the image data, and generating an analysis result;
s3, receiving the analysis result and sending a control instruction;
and S4, receiving the control command, and controlling the escalator to perform an action matched with the control command.
Further, the analysis result comprises an abnormal behavior analysis result of the passenger on the escalator;
and analyzing the image data to generate an abnormal behavior analysis result of the passenger when the passenger falls down or moves in the reverse direction or the head and the hands extend out of the hand strap of the escalator.
And the escalator execution module receives the alarm instruction or the running speed control instruction and controls the corresponding voice broadcast and running speed of the escalator.
Further, the analysis result comprises a passenger flow density analysis result;
when judging that the same area or adjacent areas have no passenger flow according to the image data, generating a passenger flow-free analysis result;
receiving the passenger flow-free analysis result and sending a control instruction for maintaining the energy-saving running speed;
and receiving the control instruction for maintaining the energy-saving running speed, and controlling the escalator in the area to maintain the energy-saving running speed.
Further, the analysis result comprises the analysis result of the speed change of the escalator when different passengers flow;
when the passenger flow density of the escalator with the running direction consistent with the passenger flow direction in the same region is within a preset density threshold value through image data analysis, generating an escalator speed change analysis result;
receiving the escalator speed change analysis result and sending an escalator speed control instruction to the corresponding escalator;
and receiving the escalator speed control instruction, and accelerating or decelerating the escalator to the running speed matched with the preset density threshold value.
Compared with the prior art, the invention has the beneficial effects that: according to the control system and method for the rail transit escalator, disclosed by the invention, the escalator is intelligently controlled by acquiring and analyzing the passenger flow density and the passenger flow trend of different areas of a station and the image data of passengers and articles on the escalator in real time, so that the energy is saved and the environment is protected; meanwhile, passengers on the escalator can be monitored, and the safety of the passengers is guaranteed.
Drawings
Embodiments of the invention are described in further detail below with reference to the attached drawing figures, wherein:
fig. 1 is a block diagram of a control system of an escalator for rail transit according to embodiment 1 of the present invention;
fig. 2 is a schematic flow chart of a control method of a rail transit escalator according to embodiment 2 of the present invention.
Reference numerals: 1. an image acquisition module; 2. an image analysis module; 3. a central control module; 4. staircase execution module.
Detailed Description
The preferred embodiments of the present invention will be described in conjunction with the accompanying drawings, and it will be understood that they are described herein for the purpose of illustration and explanation and not limitation.
The technical solution of the present invention is described below with reference to the specific embodiments and the accompanying drawings.
Example 1
As shown in fig. 1, a control system of an escalator for rail transit according to embodiment 1 of the present invention includes:
the image acquisition module 1 is used for acquiring image data of a station in real time, wherein the image data is used for indicating passenger flow density, passenger flow moving speed, passenger conditions on an escalator and article conditions on the escalator in different areas in the station.
Specifically, the image acquisition module 1 comprises a camera and a video collector, and is used for acquiring the passenger flow density and the passenger flow direction in different areas of a station and the conditions of passengers and articles on an escalator, and uploading monitored and acquired data to the image analysis module 2 in real time through the signal transmission module.
More specifically, the visual recognition algorithm of the image acquisition module mainly comprises: crowd density extraction, human body action abnormity detection and pedestrian detection and tracking, and object retention detection. The visual identification algorithm of the station passenger flow identification device mainly relates to the following steps: crowd density extraction, pedestrian detection and tracking.
(1) Crowd density (passenger flow density) extraction method
The algorithm is mainly divided into two parts: feature extraction and feature classification. The feature extraction comprises wavelet transformation and gray level co-occurrence matrixes, and the support vector machine is used for classification.
Firstly, 3-level wavelet decomposition is carried out on a crowd image, 9/7 filter banks are adopted to carry out three-level wavelet transformation, nine high-frequency sub-bands are used as the basis of feature extraction, and texture features are extracted from the nine sub-bands respectively. The detail subgraphs with different resolutions can display the texture condition of the crowd image in different directions.
In the texture image, the statistical probability of the common occurrence of a pair of pixel gray scales separated by a certain distance in a certain direction can reflect the texture feature of the image. The gray level co-occurrence matrix method is an important texture analysis method based on the second-order joint conditional probability density function of the estimated image. The gray co-occurrence matrix p (i, j | d, phi) is defined as the probability (or frequency) of a gray value j at a point that is a fixed position (separated by a distance d, azimuth phi) away from the point with the gray value i. Corresponding to the texture image with slow change, the value on the diagonal line of the gray level co-occurrence matrix is larger; and corresponding to the image with fast texture change, the value on the diagonal line of the gray level co-occurrence matrix is small, and the values on the two sides of the diagonal line are large.
The gray level co-occurrence matrix p (i, j | d, phi) reflects the comprehensive information of the image gray level distribution on the direction, the local neighborhood and the variation amplitude, but the data volume is too large, and the data volume is generally not directly used as the characteristic for distinguishing the texture, but some statistic is constructed on the basis of the data volume as the texture classification characteristic, the corresponding statistical texture characteristic is calculated, the characteristic vector is generated, and the characteristic classification is carried out by utilizing a support vector machine to obtain the crowd density level.
(2) Method for detecting human body action abnormity
When a person enters a detection area, the camera acquires a target, performs position positioning on the target and performs certain calculation on the posture of the target, judges whether the target acts abnormally according to the calculation result, and performs corresponding alarm operation when the person acts abnormally.
(3) Pedestrian detection and tracking method
The pedestrian detection and tracking is divided into three parts: firstly, obtaining a moving target area; secondly, establishing a pedestrian detection template; and thirdly, detecting and counting pedestrians. Since the monitoring device is mounted above the escalator, the system identifies the head and shoulders of the person as an identifying feature. The working principle of the algorithm is as follows: firstly, acquiring pedestrian images with obvious head and shoulder combination characteristics and different walking directions by a system as a sample set; then carrying out gray processing on the image to detect the contour of the object; and finally, comparing the matching degrees of the head and the shoulders of the profile, if the matching degree is greater than a threshold value, judging that the pedestrian is a pedestrian, and updating the sample set, thereby optimizing the function of counting the pedestrians.
(4) The object retention detection method adopts a background difference method to carry out foreground detection, firstly a background model is established, then a foreground image is obtained through the difference between a current image and the background image, target extraction is completed, and finally the background model is updated according to a preset strategy. The system adopts a background updating strategy based on a foreground mask to complete object detection, and when the object detection duration is too long, the floor plate object retention detection is judged.
Through the above algorithm, the image data required by the present embodiment can be acquired.
In some embodiments, the system further comprises an information transmission module for transmitting the image data to the image analysis module 2 and for transmitting the analysis result to the central control module 3 by a wired or wireless transmission mode.
Specifically, the information transmission module can adopt wired network transmission or wireless network transmission, and when the wireless network transmission is adopted, a signal receiving and sending device needs to be added to the corresponding module, but the laying of cables can be reduced. The wireless network transmission adopts a 5G mobile communication technology wireless transmission mode, three operator SIM card slots and a signal receiving and transmitting device are reserved in a transmission device of the equipment, and a station monitoring video file and an analysis result receiving file are transmitted through a 5G cellular data signal.
The image analysis module 2 is used for receiving the image data in real time, analyzing and judging the image data and generating an analysis result;
specifically, the image analysis module 2 analyzes and processes the image data of each area, determines whether an abnormal condition exists on an escalator in a certain station, determines and predicts the passenger flow condition of the escalator in the same area in a certain time next, and transmits the corresponding result to the central control module 3 of the corresponding station through the information transmission module.
The central control module 3 is used for receiving the analysis result and sending a control instruction;
and the escalator execution module 4 is used for receiving the control command and controlling the escalator to perform the action matched with the control command.
In some embodiments, the analysis results include passenger abnormal behavior analysis results;
and the image analysis module 2 is used for receiving the image data in real time, and generating an abnormal behavior analysis result of the passenger when the passenger falls down to go backwards or the head and the hands extend out of the hand strap of the escalator through the image data analysis.
Specifically, horizontal coordinates of handrail belts on the left side and the right side of the escalator are set as X1 and X2(X1 is less than X2), coordinates of left positions and right positions of the passenger model are set as X3 and X4(X3 is less than X4), when the image analysis module 2 detects that the passenger position is X4 > X2 or X3 is less than X1, the situation that a head of a user stretches out of the handrail belts is indicated, and a passenger abnormal signal is output; the passenger X3 is more than X2 or X4 is less than X1, which indicates that the passenger climbs the handrail belt and outputs a passenger abnormal signal. After receiving the abnormal signal of the passenger, the central control module 3 can send a control instruction to control the alarm module to work and the like.
When the height and the width of the rectangle for detecting the passenger are respectively H and W, the threshold value of the falling model is A, and when H/W < A, the passenger falls. And after receiving the signal, the central control module 3 stops the escalator.
In some embodiments, the analysis results include passenger abnormal behavior analysis results;
the image analysis module 2 generates an abnormal behavior analysis result of the passenger when the passenger falls down or moves in the reverse direction or the head and the hands extend out of the hand strap of the escalator according to the image data.
The central control module 3 receives the abnormal behavior analysis result of the passenger on the escalator and sends out an alarm instruction or a control instruction of the corresponding escalator running speed.
The escalator execution module 4 receives the alarm instruction or the operation speed control instruction and controls the corresponding voice broadcast and the operation speed of the escalator.
The alarm instruction can be sent out through the voice control module, specifically, the central control module outputs a signal to the voice control module, and the voice control module plays information (for example, do not stretch the head and hands out of the hand strap "); when the situation that passengers stay at the floor plates of the access and the passage are influenced is monitored, the voice control module outputs a signal to play information (for example, the situation that the passengers stay at the access of the escalator and the passage is influenced) is monitored; when the situation that large articles stay on the floor plates of the entrance and the exit to influence passing is monitored, the voice control module outputs a signal to play information (for example, please pay attention to obstacles below the feet of the entrance and the exit of the escalator, and fall down carefully).
In some embodiments, the analysis results include passenger flow density analysis results, escalator speed change analysis results.
Specifically, the passenger flow density on the escalator is classified into unmanned riding, medium-low, medium-high and high levels according to the operation requirements. For the escalator with no passenger at the energy-saving running speed, the image analysis module 2 analyzes that no passenger flow exists in the same area or adjacent areas, and the escalator maintains the energy-saving running speed; when the passenger flow density and direction of the escalator in the same area or adjacent areas are analyzed, and the passenger flow density of the escalator in which the running direction is consistent with the passenger flow direction in the same area is medium or low, the passenger walking speed is analyzed, when the passenger arrives at a certain specific position, the image analysis module 2 sends a signal, the central control module 3 controls the escalator to accelerate to 0.5m/s before the passenger enters the escalator, and the riding comfort of the escalator is improved; when the passenger flow degree of the escalator is about to be changed from unmanned to medium-high or high passenger flow, the running speed of the escalator is adjusted to 0.65m/s from the energy-saving speed in advance; when the passenger flow rate of the escalator is analyzed from medium low to medium high or high, the central control module 3 controls the running speed of the escalator to be adjusted from 0.5m/s to 0.65m/s in advance, and the acceleration is not more than 0.05m/s in the period2And is favorable for quickly evacuating passenger flow.
More specifically, for an escalator with up-down sections, after a passenger enters a lower escalator, the image analysis module 2 analyzes that when the passenger takes a certain position of the lower escalator, the linkage of the upper escalator is started in advance. Taking the situation of intelligent linkage between the ascending escalator at the upper section and the ascending escalator at the lower section as an example, after the ascending escalator at the lower section takes passengers and arrives at a specific position, the central control module 3 sends a signal to accelerate the ascending escalator at the upper section to a corresponding nominal speed in advance. Meanwhile, if the upper-section ascending escalator has a fault or a dangerous condition, the escalator is decelerated to run or stopped to run, the condition that passengers who arrive at the transfer platform are blocked is monitored and analyzed, the lower-section ascending escalator correspondingly links to perform deceleration running or stopped running, and the dangerous condition caused by the fact that the lower-section ascending escalator continuously runs to cause the large amount of accumulation of the passengers on the transfer platform is avoided.
In some embodiments, the system further comprises a display module, configured to display a video corresponding to the passenger abnormality analysis result when the central control module 3 receives the passenger abnormality analysis result.
Example 2
As shown in fig. 2, a method for controlling a rail transit escalator in embodiment 2 of the present invention includes:
s1, acquiring image data of the station in real time, wherein the image data are used for indicating passenger flow density, passenger flow moving speed, passenger condition on the escalator and article condition on the escalator in different areas in the station;
s2, receiving the image data in real time, analyzing and judging the image data, and generating an analysis result;
specifically, the image data of each area is analyzed and processed to judge whether an abnormal condition exists on an escalator at a certain station, and meanwhile, the passenger flow condition of the escalator in the same area in the next certain time is judged and predicted.
S3, receiving the analysis result and sending a control instruction;
and S4, receiving the control command, and controlling the escalator to perform the action matched with the control command.
In some embodiments, the analysis results include passenger abnormal behavior analysis results;
and analyzing the image data to generate an abnormal behavior analysis result of the passenger when the passenger falls down or moves in the reverse direction or the head and the hands extend out of the hand strap of the escalator.
And receiving the abnormal behavior analysis result of the passenger and sending an alarm instruction.
Specifically, horizontal coordinates of handrail belts on the left side and the right side of the escalator are set as X1 and X2(X1 is less than X2), coordinates of left positions and right positions of a passenger model are set as X3 and X4(X3 is less than X4), when an image analysis module detects that the position of a passenger is X4 > X2 or X3 is less than X1, the situation that a head of a user stretches out of the handrail belts is indicated, and a passenger abnormal signal is output; the passenger X3 is more than X2 or X4 is less than X1, which indicates that the passenger climbs the handrail belt and outputs a passenger abnormal signal. After receiving the abnormal signal of the passenger, the central control module can send a control instruction to control the alarm module to work and the like.
When the height and the width of the rectangle for detecting the passenger are respectively H and W, the threshold value of the falling model is A, and when H/W < A, the passenger falls. And after receiving the signal, the central control module stops the escalator.
In some embodiments, the analysis results include passenger flow density analysis results, escalator speed change analysis results;
specifically, the passenger flow density on the escalator is classified into unmanned riding, medium-low, medium-high and high levels according to the operation requirements. For the escalator with no passenger at the energy-saving running speed, the image analysis module analyzes that no passenger flow exists in the same area or adjacent areas, and the escalator maintains the energy-saving running speed; when the passenger flow density and direction of the escalator in the same area or adjacent areas are analyzed, the passenger flow density of the escalator in which the running direction is consistent with the passenger flow direction in the same area is medium or low, the passenger walking speed is analyzed, when the passenger arrives at a certain specific position, the image analysis module sends a signal, the central control module controls the escalator to accelerate to 0.5m/s before the passenger enters the escalator, and the riding comfort of the escalator is improved; when the passenger flow degree of the escalator is about to be changed from unmanned to medium-high or high passenger flow, the running speed of the escalator is adjusted to 0.65m/s from the energy-saving speed in advance; when the passenger flow rate of the escalator is analyzed from medium low to medium high or high, the central control module controls the running speed of the escalator to be adjusted from 0.5m/s to 0.65m/s in advance, and the acceleration is not more than 0.05m/s in the period2And is favorable for quickly evacuating passenger flow.
The above description is only a preferred embodiment of the present invention, and is not intended to limit the present invention in any way, so that any modification, equivalent change and modification made to the above embodiment according to the technical spirit of the present invention are within the scope of the technical solution of the present invention.
Claims (2)
1. A rail transit escalator control system, comprising:
the image acquisition module is used for acquiring image data of a station in real time, the image data is used for indicating passenger flow density, passenger flow moving speed, passenger conditions on an escalator and article conditions on the escalator in different areas in the station, and an algorithm of the passenger flow density extraction method comprises two parts: extracting characteristics and classifying the characteristics, wherein the characteristic extraction comprises wavelet change and gray level co-occurrence matrixes, and a support vector machine is used for classifying the characteristics;
the image analysis module is used for receiving the image data in real time, analyzing and judging the image data and generating an analysis result;
the central control module is used for receiving the analysis result and sending a control instruction;
the escalator execution module is used for receiving the control instruction and controlling the escalator to perform an action matched with the control instruction;
the analysis result comprises an abnormal behavior analysis result of the passenger on the escalator;
the image analysis module generates an abnormal behavior analysis result of the passenger when the passenger falls down or moves in the reverse direction or the head and the hands extend out of the hand strap of the escalator according to the image data;
the central control module receives the abnormal behavior analysis result of the passenger on the escalator and sends out an alarm instruction or a control instruction of the corresponding escalator running speed;
the escalator execution module receives the alarm instruction or the running speed control instruction and controls the corresponding voice broadcast and the running speed of the escalator;
the analysis result comprises a passenger flow density analysis result;
the image analysis module generates a passenger flow-free analysis result when judging that the same area or adjacent areas have no passenger flow according to the image data;
the central control module receives the passenger flow-free analysis result and sends a control instruction for maintaining the energy-saving running speed;
the escalator execution module receives the control instruction for maintaining the energy-saving running speed and controls the escalator in the area to maintain the energy-saving running speed;
the analysis result comprises the analysis result of the speed change of the escalator when different passengers flow;
the image analysis module synchronously generates corresponding escalator speed change analysis results when the escalator passenger flow density with the running direction consistent with the passenger flow direction in the same image data analysis region is within preset different density thresholds; tracking and analyzing the walking of the passengers, and sending an analysis result of the speed change of the escalator when the passengers arrive at a preset position;
the central control module receives the escalator speed change analysis result and sends an escalator speed control instruction to the corresponding escalator;
the escalator execution module receives the escalator speed control command and accelerates or decelerates the escalator to the running speed matched with the preset density threshold value;
further comprising:
the information transmission module is used for transmitting the image data to the image analysis module in a wired or wireless transmission mode, and the information transmission module is also used for transmitting an analysis result to the central control module in a wired or wireless transmission mode;
also comprises
And the display module is used for displaying a video corresponding to the abnormal behavior analysis result of the passenger when the central control module receives the abnormal behavior analysis result of the passenger on the escalator.
2. A method of controlling a rail transit escalator, the method comprising:
s1, acquiring image data of the station in real time, wherein the image data are used for indicating passenger flow density, passenger flow moving speed, passenger condition on the escalator and article condition on the escalator in different areas in the station, and the algorithm of the passenger flow density extraction method comprises two parts: extracting characteristics and classifying the characteristics, wherein the characteristic extraction comprises wavelet change and gray level co-occurrence matrixes, and a support vector machine is used for classifying the characteristics;
s2, receiving the image data in real time, analyzing and judging the image data, and generating an analysis result;
s3, receiving the analysis result and sending a control instruction;
s4, receiving the control instruction, and controlling the escalator to perform an action matched with the control instruction;
the analysis result comprises an abnormal behavior analysis result of the passenger on the escalator;
analyzing whether a passenger falls down or moves in the reverse direction or whether the head and the hands extend out of a hand strap of the escalator according to the image data to generate an abnormal behavior analysis result of the passenger;
the escalator execution module receives an alarm instruction or an operation speed control instruction and controls the corresponding voice broadcast and operation speed of the escalator;
the analysis result comprises a passenger flow density analysis result;
when judging that the same area or adjacent areas have no passenger flow according to the image data, generating a passenger flow-free analysis result;
receiving the passenger flow-free analysis result and sending a control instruction for maintaining the energy-saving running speed;
receiving the control instruction for maintaining the energy-saving running speed, and controlling the escalator in the area to maintain the energy-saving running speed;
the analysis result comprises the analysis result of the speed change of the escalator when different passengers flow;
when the passenger flow density of the escalator with the running direction consistent with the passenger flow direction in the same region is within a preset density threshold value through image data analysis, generating an escalator speed change analysis result;
receiving the escalator speed change analysis result and sending an escalator speed control instruction to the corresponding escalator;
and receiving the escalator speed control instruction, and accelerating or decelerating the escalator to the running speed matched with the preset density threshold value.
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| CN101695983B (en) * | 2009-10-23 | 2011-12-21 | 浙江工业大学 | Omnibearing computer vision based energy-saving and safety monitoring system of escalator |
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