KR102661630B1 - Apparatus for controlling of automatic counting machine - Google Patents

Abstract

The embodiment relates to a control device for automatic dog kennel marking.
Specifically, this control device uses two-dimensional information, such as time and distance, to accurately distinguish between various adults, teenagers, children, and travelers with luggage passing through automatic kennel markings. Recognize patterns. Therefore, by comparing with the corresponding reference pattern, it is accurately determined whether the passenger is a normal passenger or an illegal passenger.
This two-dimensional information is detected by installing multiple ToF sensors from the automatic counting area to the counting area.
Therefore, the automatic dog tag accurately distinguishes between various adults, teenagers, children, and travelers with luggage, and accurately reads whether they are normal or fraudulent passengers.
In this way, passengers and luggage can be accurately read from the automatic kennel markings of urban railways, improving the operational reliability of the automatic kennel markings and improving passenger convenience through accurate detection.

Description

{Apparatus for controlling of automatic counting machine}

The content disclosed in this specification relates to the field of automatic kennel marking. More specifically, it relates to a control device for automatic kennel markings that can accurately read passengers and baggage in automatic kennel markings on urban railways, improve the operation reliability of automatic kennel markings, and improve passenger convenience.

Unless otherwise indicated herein, the material described in this section is not prior art to the claims of this application, and is not admitted to be prior art by inclusion in this section.

In general, automatic dog tags automatically process dog tags by reading and recording the information recorded on tickets for the convenience of passengers using public transportation such as trains, buses, and airplanes, and control the movement of customers between waiting rooms and platforms. It is a device.

Existing automatic dog tagging uses multiple infrared sensors with separate light emitting and receiving sections, and when a passenger enters, the presence or absence of a passenger is determined at a point adjacent to the multiple infrared sensors.

Since the sensors attached to existing urban railway dog tags can only determine the presence or absence of passengers, they often misidentify more than one person passing by or suitcases.

Because of this, there was a problem that when passing a passenger accompanied by an infant or carrying luggage such as a suitcase or bag, the infant or carrier may be mistakenly recognized as a passenger.

In addition, in the existing automatic dog tagging system, multiple ultraviolet sensors are separated into a light emitting unit and a light receiving unit, so the ultraviolet sensor may malfunction depending on the installation location of the ultraviolet sensor. Additionally, since multiple ultraviolet sensors are wired in a star-shaped structure, there is a problem in that wiring is complicated. Here, the star-shaped structure means a structure in which an ultraviolet sensor is placed in the center and a plurality of ultraviolet sensors are radially connected to the ultraviolet sensor.

In particular, in terrestrial history, there have been frequent cases of ultraviolet ray sensors malfunctioning due to direct sunlight in the early morning or late afternoon when the sun's altitude is low during the winter season.

The prior art in this background is as follows.

Document 1 Korean Patent Publication No. 10-2018-0005893 Document 2 Korean Patent No. 10-2512353 Document 3 Korean Registered Utility Model No. 20-0269891 Document 4 US Patent No. 10-1734423

The disclosed content is intended to provide a control device for an automatic kennel tag that can accurately distinguish between various adults, teenagers, children, and travelers with luggage passing through an automatic kennel tag and accurately read whether they are normal or illegal passengers. .

The control device for automatic kennel marking according to the embodiment is:

In order to accurately distinguish between adults, teenagers, children, and travelers with luggage, the two-dimensional information of time and distance is used to recognize the traffic patterns of passengers passing through the automatic dog tag. Therefore, by comparing with the corresponding reference pattern, it is accurately determined whether the passenger is a normal passenger or an illegal passenger.

This two-dimensional information is detected by installing multiple ToF sensors from the automatic counting area to the counting area.

Specifically, the rated separation distance and rated transit time patterns are set for each passenger type for each ticket of the automatic dog tag.

The rated separation distance is the standard distance between the ToF sensor installed on the ballot counting area and the passenger, and the rated passing time pattern is the standard time when a passenger passes through multiple ToF sensors installed from the ballot counting area to the counting area. This is the pattern.

In this state, the passenger's ticket is recognized, the separation distance is detected for the passenger, and compared with the rated separation distance for each passenger type of the ticket. Therefore, the passenger type whose two distances match is determined as the passenger type of the corresponding passenger.

The passenger's transit time pattern is detected for the passenger type determined in this way, and if there is a difference compared to the corresponding rated transit time pattern, the passenger is identified as an unauthorized passenger.

According to an embodiment, the automatic dog tag accurately distinguishes between various passing adults, teenagers, children, travelers with luggage, etc., and accurately reads whether they are normal passengers or illegal passengers.

In addition, in this way, passengers and luggage can be accurately read from the automatic kennel markings of urban railways, improving the operation reliability of the automatic kennel markings and improving passenger convenience through accurate detection.

In addition, it accurately recognizes passengers entering with luggage, etc., eliminating discomfort that may arise from misrecognition. When a passenger enters without permission, a warning sound can be used to prevent free riding, thereby preventing loss of transportation revenue and maintaining order in the proper use of tickets. establish

Additionally, multiple TOF sensors for accurate reading are connected in a linked structure with simple wiring, reducing manufacturing costs compared to existing automatic kennel marking.

1 is a diagram conceptually illustrating a control device for automatic dog tagging according to an embodiment.
Figure 2 is a diagram for explaining the passenger and baggage reading operation of the automatic dog tag control device according to an embodiment
Figure 3 is a diagram for explaining the operation of detecting the passenger type of the automatic dog tag control device according to an embodiment
Figure 4 is a diagram for explaining the operation of determining the passenger type of the automatic dog tag control device according to an embodiment
Figure 5 is a diagram for explaining the passenger traffic pattern of the automatic dog tag control device according to an embodiment
Figure 6 is a diagram showing a system applied to an automatic dog tag control device according to an embodiment.
Figure 7 is a block diagram showing the configuration of an automatic kennel marking control device according to an embodiment.
Figure 8 is a flow chart sequentially showing the operation of the automatic dog marking control device according to one embodiment.

1 is a diagram for conceptually explaining a control device for automatic kennel marking according to an embodiment.

As shown in FIG. 1, the control device of the automatic dog tag according to one embodiment accurately distinguishes between various adults, teenagers, children, and travelers with luggage passing through the automatic dog tag, and determines whether they are normal passengers or illegal passengers. Read accurately.

To this end, the two-dimensional information of time and distance is used to recognize the traffic patterns of passengers passing through the automatic dog kennel markings. Therefore, by comparing with the corresponding reference pattern, it is accurately determined whether the passenger is a normal passenger or an illegal passenger.

This two-dimensional information is detected by installing multiple ToF sensors from the automatic counting area to the counting area.

Specifically, the rated separation distance and rated transit time pattern are set for each passenger type for each ticket of the automatic dog tag.

The rated separation distance is the standard distance between the ToF sensor installed on the ballot counting area and the passenger, and the rated passing time pattern is the standard time when a passenger passes through multiple ToF sensors installed from the ballot counting area to the counting area. This is the pattern.

In this state, the passenger's ticket is recognized, the separation distance is detected for the passenger, and compared with the rated separation distance for each passenger type of the ticket. Therefore, the passenger type whose two distances match is determined as the passenger type of the corresponding passenger.

For the passenger type determined in this way, the passenger's transit time pattern is detected, and compared to the corresponding rated transit time pattern, if there is a difference, it is determined as an fraudulent passenger.

Compared to the existing method, this automatic kennel marking uses multiple infrared sensors with separate light emitting and receiving parts, and determines the presence or absence of a passenger at a point adjacent to the multiple infrared sensors when a passenger enters. .

For reference, the upper left part of Figure 1 is a perspective view of an existing automatic dog tag, and the lower left part of Figure 1 is a graph of the output signal of the infrared sensor over time.

Referring to Figure 1, the existing automatic dog tagging system uses a plurality of infrared sensors with separate light emitting and receiving parts to determine the presence or absence of a passenger at a point adjacent to the plurality of infrared sensors when a passenger enters. Since only the presence or absence of passengers can be determined in this way, more than one person passing by or suitcases, etc. may be misrecognized. Therefore, when passing a passenger accompanied by an infant or carrying luggage such as a suitcase or bag, the infant or carrier may be mistakenly recognized as a passenger.

On the other hand, in one embodiment, a plurality of ToF sensors are installed from the counting area of the automatic counting machine to the counting area, and the traffic pattern passing through the automatic dog marking machine is recognized using the separation distance and passage time for passengers to accurately track passengers and baggage. Read it.

In other words, the automatic dog tag accurately distinguishes between various adults, teenagers, children, and travelers with luggage, and accurately reads whether they are normal or fraudulent passengers.

Figure 2 is a diagram for explaining the passenger and baggage reading operation of the automatic dog tag control device according to one embodiment.

As shown in FIG. 2, the passenger and baggage reading operation according to one embodiment first installs a plurality of ToF sensors from the automatic counting area to the counting area. The vote counting area is to distinguish between adults, teenagers, children, travelers with luggage, etc., and the counting area is to determine the passing pattern of each passenger in connection with the vote counting area.

For example, in the vote counting area, adults have relatively larger gestures and are taller than teenagers and children, so the distance from the ToF sensor to the passenger in question is relatively close, the time is short, and the height is recognized up to A1. Also, for sensors that detect adults, the LS and S areas detect body size, so the distance will be relatively short, while the A area, which is toward the shoulders and face, will be longer.

On the other hand, for teenagers, the distance and time will increase relatively more than for children, and for children, area A can be excluded. On the other hand, if you are a traveler with luggage, the distance and time will be shorter than for an average adult with this luggage.

Since the same passengers pass from this vote counting area to the counting area, under normal conditions, the distance and time will generally be the same or have only a slight difference. On the other hand, in the case of fraudulent passengers, the distance may be irregular or the time may be very fast. Therefore, it is possible to determine whether a passenger is a normal passenger or an illegal passenger, and can be accurately distinguished by classifying each passenger type. These passenger types can be classified by determining the passenger type by ticket. For example, in the case of a regular ticket or a youth ticket, general adults or teenagers can be variously divided into men and women.

Additionally, these passenger types can also be distinguished by the location and number of sensors that simultaneously detect passengers. In the case of adults, the location of this sensor will include area A, and the number will be relatively greater than that of teenagers.

Figure 3 is a diagram for explaining an operation of detecting a passenger type of an automatic dog tag control device according to an embodiment.

As shown in FIG. 3, the passenger type detection operation according to one embodiment uses a ToF sensor located in the vote counting area.

For example, if there are LS1, S0, LS2, and S1 at the bottom of the ballot counting area and A1 at the top, adults will detect all of LS1 to A1, and children will be shorter, so A1 can be excluded. . Each of these appearances can have various variations.

The number, installation height, installation interval, etc. of sensors in these vote counting areas can be determined according to the gestures and heights of various types of passengers.

Figure 4 is a diagram for explaining the operation of determining the passenger type of the automatic dog tag control device according to one embodiment.

As shown in FIG. 4, the passenger type discrimination operation according to one embodiment uses the separation distance from the ToF sensor in the vote counting area to the passenger. This separation distance is calculated using the installation location of the ToF sensor, the time when light is emitted from the ToF sensor to the passenger, and the time when the light is returned.

For example, for adults, the separation distance is shorter than for teenagers and children, for teenagers, the separation distance is shorter than for children, and for travelers with luggage, the separation distance is shorter than normal.

This separation distance can be accurately detected using a single ToF sensor or multiple sensors.

Figure 5 is a diagram for explaining a passenger traffic pattern of an automatic dog tag control device according to an embodiment.

As shown in FIG. 5, the passenger passage pattern according to one embodiment is created as a passenger passage time pattern between ToF sensors from the vote counting area to the counting area.

For example, in the case of adults, LS1 = t1, S0 = t1, LS2 = t1, S1 = t1, A1 = t4, ... in the counting area, A4 = t4, S6 = t1, LS3 = t1, S7 in the counting area. = t1, LS4 = t1.

On the other hand, in the case of children, LS1 = t4, S0 = t4, LS2 = t4, S1 = t4, A1 = 0, ... in the vote counting area, A4 = 0, S6 = t4, LS3 = t4, S7 = t4 in the counting area. , can be made as LS4 = t4.

Therefore, the rated transit time pattern of the passenger between the ToF sensors from the ballot counting area to the counting area is determined, and in this state, the passage time pattern of the passenger who inserted the ticket is detected, and if there is a difference, it is determined as an fraudulent passenger.

The rated transit time pattern can be determined in various ways for each passenger for each ticket.

Figure 6 is a diagram showing a system applied to an automatic kennel marking control device according to an embodiment.

As shown in FIG. 6, the system according to one embodiment largely includes an automatic dog tag control device 100 and a management information processing device 200 installed at each boarding and disembarking location within a specific station.

The control device 100 of the automatic dog tag accurately distinguishes between various adults, teenagers, children, and travelers with luggage passing through the automatic dog tag, and accurately reads whether they are normal passengers or illegal passengers. The reading result can be transmitted to the management information processing device 200 to generate an alarm. On the other hand, the number of passages of fraudulent passengers can be counted and added to calculate the traffic volume of fraudulent passengers, or the traffic volume of used passengers can be calculated and transmitted to the management information processing device 200 to be reflected in improving the passenger's transportation convenience.

The management information processing device 200 can collect the reading results of the control device 100 of the automatic dog tag and send an alarm in the relevant area for fraudulent passengers, and collect the traffic volume of fraudulent passengers or passengers. It is reflected in improving travel convenience. Additionally, various conveniences can be provided by linking with information processing devices such as police stations and troubleshooting centers as additional linkages.

Figure 7 is a block diagram showing the configuration of an automatic kennel marking control device according to an embodiment.

As shown in FIG. 7, the control device for automatic dog tagging according to an embodiment includes an interface unit 101, a signal processing unit 102, a flap adjusting unit 103, a control unit 104, and a ToF sensor unit 105. , including a storage unit 106 and a display unit 107.

The interface unit 101 transmits and receives information with the passenger's transportation card or the management information processing device 200, and may include various ticket media in addition to the transportation card.

The signal processing unit 102 is for converting, processing, or recognizing the passenger's transportation card or information with the management information processing device 200 and the ToF sensor unit 105, and includes a ticket recognition unit.

The flap control unit 103 controls the opening and closing operation of the flap to control the entry and exit of passengers for each ballot counting area and counting area.

The ToF sensor unit 105 includes a plurality of ToF sensors (105-1 to 105-f) for detecting passengers recognized by the signal processing unit 103 in the vote counting area, and a plurality of ToF sensors for detecting passengers in the passing area and counting area. Equipped with ToF sensors (105-g~105-x).

The storage unit 106 includes the rated separation distance between the corresponding ToF sensors (105-1 to 105-f) and the passenger in the ballot counting area, and the corresponding ToF sensors (105-1 to 105-x) from the ballot counting area to the counting area. ) Passenger's rated transit time pattern information, etc. are registered for each ticket and passenger type.

The display unit 107 displays the result of determining fraudulent passengers, etc.

The control unit 104 controls the flap control unit 103 by interlocking with the signal processing unit 102, the ToF sensor unit 105, and the storage unit 106 to determine whether there is an illegal passenger for each passenger type of the ticket. do. For example, if an illegal passenger is identified, the flap in the collection area is closed.

Figure 8 is a flow chart sequentially showing the operation of the automatic dog marking control device according to one embodiment.

As shown in FIG. 8, the automatic kennel marking according to one embodiment first registers the above-described rated separation distance and rated passing time pattern for each passenger type for each ticket of the automatic kennel marking (S801).

In this state, the separation distance from the ToF sensor on the ticket counting area to the passenger whose ticket has been recognized through the recognition unit is detected (S802).

The separation distance detected in this way is compared with the rated separation distance for each passenger type of the corresponding ticket (S803).

As a result of the above comparison, the passenger type of the rated separation distance corresponding to the separation distance is determined as the passenger type of the passenger (S804).

Then, for this determined passenger type, a time pattern when the passenger passes through multiple ToF sensors from the ballot counting area to the counting area is detected (S805).

Next, the detected passing time pattern is compared with the corresponding rated passing time pattern (S806).

As a result of the above comparison, if the passage time pattern differs from the corresponding rated passage time pattern, the passenger is determined to be fraudulent (S807).

Therefore, the flap of the target area is closed for the identified fraudulent passenger through the flap adjuster (S808).

As described above, in one embodiment, the automatic dog tag accurately distinguishes between various adults, teenagers, children, and travelers with luggage, and accurately reads whether they are normal passengers or illegal passengers.

In addition, in this way, passengers and luggage can be accurately read from the automatic kennel markings of urban railways, improving the operation reliability of the automatic kennel markings and improving passenger convenience through accurate detection.

In addition, it accurately recognizes passengers entering with luggage, etc., eliminating discomfort that may arise from misrecognition. When a passenger enters without permission, a warning sound can be used to prevent free riding, thereby preventing loss of transportation revenue and maintaining order in the proper use of tickets. establish

On the other hand, when the flap is closed for an illegal passenger, such a kennel sign allows adults, teenagers, etc. to variably perform the operation appropriately, thereby safely protecting the passenger and providing an alarm.

For example, the flap closing state of the collecting area or the flap closing speed of the collecting area is varied depending on the type of passenger of the fraudulent passenger.

If the fraudulent passenger is an adult, the flaps can be closed normally, and if the passenger is a teenager, the flaps can be closed a little more slowly for safety. Alternatively, in the case of passengers who need to be protected, such as children, the flap can be closed and released to trigger an alarm, etc.

In addition, the traffic volume of fraudulent passengers can be calculated by counting and adding up the number of passages of fraudulent passengers, and the flap closing state of the collecting area or the flap closing speed of the collecting area can be varied according to the traffic volume of fraudulent passengers.

To this end, a standard value for the traffic volume of illegal passengers can be set, and the standard value can be set as a value that makes it difficult to pass at the relevant station due to the large volume of illegal passengers.

The traffic volume of fraudulent passengers is compared with the reference value, and if the comparison results show that the traffic volume of fraudulent passengers is greater than or equal to the reference value, the flap closing speed at the relevant station or automatic dog gate can be made a little faster.

In other words, the flap closing speed may be slightly increased in stations where there are a lot of fraudulent passengers or at automatic kennel markings. In this way, appropriate prevention of fraudulent passengers can be done individually at the station or automatically.

In this case, the flap closing speed is determined in response to the difference between the traffic volume of illegal passengers and the reference value.

Additionally, this automatic counting machine can use the reading operation for fraudulent passengers to measure traffic volume and take action by variably adjusting the movement of entering and exiting the counting area or counting area according to the traffic volume of passengers.

For example, the number of detections of passenger types for fraudulent passengers is counted and added to calculate the passenger traffic volume of the automatic counting machine, and the flap opening and closing operation of the counting area or the counting area is performed according to the passenger traffic volume of the automatic dog marking machine. It is variable.

When the passenger traffic volume of the automatic counting marking machine is large, the speed of opening and closing the flap of the ballot counting area or tabulation area can be slightly faster for smooth entry and exit of passengers, and when the passenger traffic volume is relatively small, the speed can be slightly slower.

For this purpose, a standard value for the traffic volume of passengers is set, and the standard value can be set as a value that causes confusion to users or makes passage difficult at the relevant station due to the large volume of passenger traffic.

The passenger traffic volume is compared with the reference value, and if the comparison result shows that the passenger traffic volume is greater than or equal to the reference value, the flap closing speed at the relevant station or automatic dog gate can be made a little faster.

In addition, the traffic volume of such passengers can be compared with the traffic volume of unauthorized passengers and adjusted individually for each vote counting area and collection area.

That is, one of the vote counting area or the counting area in which the flap opening and closing operation is to be varied is selected according to the proportion of the traffic volume of illegal passengers to the passenger traffic volume of the automatic counting machine. The above ratio is a preset standard ratio.

When the traffic volume of illegal passengers accounts for a large proportion of the traffic volume of using passengers, the speed of opening and closing the flaps in the counting area can be slightly increased, and when the traffic volume of fraudulent passengers is relatively small, the speed of opening and closing the flaps in the counting area can be increased slightly.

100: Control device for automatic kennel marking
200: Management information processing device

Claims (6)

An interface unit 101 and a signal processing unit 102 for recognizing a passenger's ticket using an automatic kennel marker; a flap control unit 103 that adjusts flaps installed for each ballot counting area and counting area to control entry and exit of the passengers; In the control device 100 for automatic dog tagging, including a control unit 104,
A plurality of ToF sensors (105-1 to 105-f) for detecting passengers recognized by the signal processing unit 103 in the vote counting area, and a plurality of ToF sensors (105-g to 105-g) for detecting passengers in the passing area and counting area. ToF sensor unit 105 having 105-x); and
The rated separation distance between the relevant ToF sensor (105-1~105-f) and the passenger in the vote counting area, and the rated passage time of the passenger of the relevant ToF sensor (105-1~105-x) from the vote counting area to the counting area. a storage unit 106 in which pattern information is registered for each ticket and passenger type;
The control unit 104 is
The passenger type is identified by comparing the separation distance between the ToF sensors (105-1 to 105-f) and the passenger with the rated separation distance, and the passenger's passage time pattern of the ToF sensors (105-1 to 105-x) Controls the flap adjuster 103 by comparing the rated transit time pattern to determine an unauthorized passenger,

The control unit 104 is
A first step of registering the rated separation distance and the rated transit time pattern information for each passenger type for each ticket of the automatic dog tag in the storage unit 106;
The rated separation distance is
It is the standard distance between the ToF sensor installed in the vote counting area and the passenger,
The rated transit time pattern is
This is the standard time pattern when passengers sequentially pass through multiple ToF sensors installed from the ballot counting area to the counting area,
A second step of detecting the separation distance for the passenger recognized by the signal processing unit 102;
A third step of identifying the type of passenger by comparing the separation distance detected in the second step with the rated separation distance;
a fourth step of detecting a passenger transit time pattern for the type of passenger identified in the third step;
A fifth step of comparing the transit time pattern detected in the fourth step with the corresponding rated transit time pattern and identifying the passenger as an unauthorized passenger when a difference occurs; and
A sixth step of closing the flap of the target area through the flap adjuster 103 for the fraudulent passenger identified in the fifth step,

In the sixth step, the flap closing speed of the collecting area or the flap closing state of the collecting area is determined and varied for each type of passenger for the identified fraudulent passenger,

In the sixth step, the traffic volume of fraudulent passengers is calculated by counting and adding up the number of passages of the identified fraudulent passengers, and the flap closing speed of the collecting area or the flap closing state of the collecting area is determined according to the traffic volume of the fraudulent passengers. variable,

In the fourth step, the number of detected times is counted and added to calculate the passenger traffic volume, and the opening/closing speed or open/closing state of the flap in the counting area or the ballot counting area is varied according to the passenger traffic volume,

In the fourth step, one of the vote counting area or the counting area in which the flap opening and closing operation is to be varied is selected according to a preset reference ratio,
The above standard ratio is
A control device for automatic kennel marking, characterized in that it is a ratio of the traffic volume of the fraudulent passenger to the traffic volume of the passenger in the automatic kennel marking.













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