KR20220036672A - Control system capable of 3d visualization based on data and the method thereof - Google Patents

Abstract

The present invention includes a control system capable of performing data-based 3D visualization. The control system comprises: a disaster prevention facility control panel (30) for outputting status information; a sensor having a plurality of sensors; an image monitoring unit (10) having a plurality of cameras; and a control device (40) that analyzes control information including at least one of image data of the image monitoring unit (10), detection data of the sensor unit (20), and state information of the disaster prevention facility control panel (30) to detect and predict the occurrence of events and signs of danger and outputs the result value, wherein the control device (40) processes visual information in which image data and sensing data are fused, and non-visual information in which at least one of a plurality of sensing data and state information of the disaster prevention facility control panel (30) is fused are output after being processed into 3D visual information.

Description

A control system and method capable of data-based 3D visualization

The present invention relates to a control system and method capable of data-based 3D visualization.

In the case of a general control system, by installing a sensor together with CCTV, etc., the administrator can check the image and the detection value detected by the sensor, thereby monitoring a specific area as a whole and preventing accidents such as fire and crime.

In such a control system, the manager must directly check the collected data, so a manpower who checks the control system must always be there.

However, even if the manpower is resident and the control system is checked in real time, the concentration is not always maintained, and the reality is that accidents continue to occur.

That is, in the prior art, as a communication network between a monitoring image device and a control system, and a sensor and a control system, is separately constructed, an erroneous situation determination for a disaster situation such as a fire may be made.

Therefore, conventionally, since the sensor network and the surveillance video network are separately constructed, there is a possibility of false detection.

In addition, the conventional control system is composed of a system that detects an event based on image data and detection information of the sensor, and alerts it.

Such a conventional control system is classified into information that is visual information and information that is non-visual information based on image data and sensor detection information, and is output to the monitor. Therefore, the control system outputs information that is visually verifiable information on the monitor for immediate confirmation, but information that is non-visual information cannot be immediately confirmed by the eye, so the signs were determined through analysis and predictions through various algorithms. .

That is, in the prior art, various algorithms are required for the analysis of information, which is non-visual information, and the error is very large as it is to calculate a predicted value for a future situation through current information, and the final judgment is actually made by a human. This required skilled manpower.

Therefore, in recent years, there is a demand for a technology capable of providing intuitive control information for such non-visual information.

Republic of Korea Patent Publication No. 10-2012-0050073 (published on May 18, 2012)

Therefore, the present invention has been devised to solve this problem, and an object of the present invention is to visualize invisible information and provide intuitive control information based on the correlation of a large amount of sensing information based on data-based 3D visualization. To provide a possible control system and method.

In addition, another object of the present invention is a control system capable of data-based 3D visualization in which sensor data is intuitively visualized on image data, visibility can be expanded, accurate prediction of disaster situations, and situation propagation can be made quickly, and to provide a method.

The present invention includes the following examples to achieve the above object.

An embodiment of the present invention provides at least one disaster prevention facility control panel for outputting status information, a sensor having a plurality of sensors, an image monitoring unit and a video monitoring unit having a plurality of cameras, and detection data of the sensor unit and a disaster prevention facility and a control device that analyzes control information including at least one of the status information of the control panel to detect and predict whether an event has occurred and a danger sign and output a result value, wherein the control device is a visual fusion of image data and detected data. and a control system capable of data-based 3D visualization for outputting non-visual information in which information and at least one of a plurality of detection data and state information of a disaster prevention facility control panel are fused as 3D visual information.

Therefore, the present invention provides a data-based decision-making means by providing visual information and/or non-visual control information listed on a plurality of monitors as 3D visualization information so that the controller can intuitively generate an event and/or It has the effect of enabling accurate and rapid response when predicting danger signs.

In addition, the present invention can provide an image output rule to a plurality of monitors, so that an image output method according to the control environment can be arbitrarily set, thereby improving the control environment.

1 is a diagram showing the configuration of a control system capable of data-based 3D visualization according to the present invention.
2 is a block diagram illustrating a sensor unit.
3 is a block diagram illustrating a diagnostic processing unit.
4 is a flowchart illustrating a data-based 3D visualization possible control method according to the present invention.
5 is a diagram illustrating an example of 3D visualization of non-visual information.
6 is a diagram illustrating an example of visualization of visual information and non-visual information.
7 is a diagram illustrating an example of a playback image of control information.

The terms or words used in the present specification and claims are not to be construed as limited in their ordinary or dictionary meanings, and on the principle that the inventor can appropriately define the concept of the term in order to best describe the user's invention. It should be interpreted as meaning and concept consistent with the technical idea of the present invention.

Throughout the specification, when a part "includes" a certain component, it means that other components may be further included, rather than excluding other components, unless otherwise stated. In addition, the “… wealth", "… energy", "… However, terms such as “module”, “device” and the like mean a unit that processes at least one function or operation, which may be implemented as a combination of hardware and/or software.

Hereinafter, embodiments of the present invention will be described in detail with reference to the accompanying drawings.

1 is a diagram showing the configuration of a control system capable of data-based 3D visualization according to the present invention, and FIG. 2 is a block diagram illustrating a sensor unit.

1 and 2 , the present invention provides a sensor unit 20 including a plurality of sensors, an image monitoring unit 10 outputting image data, a sensor unit 20 and an image monitoring unit 10 . It may include a control device 40 for detecting an event and predicting a danger sign by analyzing the information, and a mobile terminal 50 for receiving an alert from the control device 40 .

The mobile terminal 50 may receive event information, a danger sign, and/or a predicted value from the control device 40 .

The image monitoring unit 10 may include a plurality of cameras (eg, CCTV, video camera, IR camera) for transmitting image data by wire or wirelessly.

Here, the video monitoring unit 10 may set at least one or more cameras among the plurality of cameras as a group, set a channel for each group, and transmit image data belonging to the group to the control device 40 for each channel. .

The sensor unit 20 includes heterogeneous sensors, for example, at least one of a sound sensor, an illuminance sensor, a human body detection sensor, a temperature and humidity sensor, an ultrasonic sensor, a proximity sensor, a flame sensor, a gas sensor, and a radar sensor.

Here, each of the sensors is a fixed sensor built into the camera, a USB type sensor that is detachable with USB, and a communication type sensor that can communicate by wire or wirelessly, and may be built-in or stand-alone in the camera.

The disaster prevention facility control panel 30 is connected to the video monitoring unit 10 and/or the control device 40 by wire/wireless communication to output an operation command, or a disaster prevention facility (eg, a gas alarm, a fire alarm, a fire door, It outputs information on the operation status of fire hydrants, disaster storage boxes, emergency medical devices).

The control device 40 collects detection data (eg, image data word, AI metadata, IoT sensor data) of the image monitoring unit 10 and the sensor unit 20 and state information of the disaster prevention facility control panel 30 . and analysis, correlation, state, and threshold values are analyzed and processed using a deep learning engine, and non-visual information is processed into 3D visualization information to enable data-based decision-making when disaster situations and dangerous situations occur. do. Here, the control device 40 may transmit the result value of the occurrence of the event and the danger sign to the mobile terminal 50 .

To this end, the control device 40 includes a data analysis unit 410 that collects data from the sensor unit 20 and the image monitoring unit 10 , a DB 420 that stores the collected information, and a DB 420 . It may include a diagnostic processing unit 430 that processes and analyzes the stored information to provide it as 3D visualization information, and a display unit 440 that outputs the information converted and image-processed by the diagnostic processing unit 430 .

The data analysis unit 410 collects the image data captured by the image monitoring unit 10, the detection data of the sensor unit 20, and the state information of the disaster prevention facility control panel 30, classifies and stores it in the DB 420, Based on the set reference value, the data is analyzed to detect the event.

Here, the data analysis unit 410 selectively detects an object according to a user selection (eg, a person, a car, a bag, a bogie, etc.), and sets a specific event (eg, trespassing, swarming, roaming, person/object detection, path/moondam/intrusion, etc.) can be detected.

DB 420 classifies and stores the information collected by the data analysis unit 410 and control information including previous event and/or risk symptom prediction information according to a set classification condition. In addition, the DB 420 includes the video data of the video monitoring unit 10, the monitoring data of the sensor unit 20, and other information (eg, criminal behavior patterns, weather, temperature, access records, mobile terminal 50). ) information) can be stored.

The display unit 440 is one or more monitors, and one or more screens are shared or divided and output. The screen output of such monitors is defined by the operation scenario for each situation as a rule of information output according to the arrangement of the monitors is given.

The diagnosis processing unit 430 converts the collected control information, event detection information, and danger sign detection and prediction values into 3D visual information and outputs the converted information. At this time, the 3D visual information is based on non-visual information that is not provided as image data because image data and/or sensor data are fused with visual information, the plurality of sensor units 20 sensed data, and stored information of the DB 420 are fused. can be created with The detailed configuration of the diagnostic processing unit 430 will be described with reference to FIG. 3 .

3 is a block diagram illustrating a diagnostic processing unit.

Referring to FIG. 3 , the diagnostic processing unit 430 includes a visualization module 431 for generating 3D visual information, a prediction module 432 for predicting danger signs, and a monitoring custom module 433 for building and operating a display scenario. and a playback module 434 for specifying characteristics by interworking with control information, and an image processing module 435 for condensing and transmitting image data.

The visualization module 431 analyzes a large amount of control information (at least one of image data, sensor detection data, and state information of the bar material control panel 30) to analyze visual information and non-visual information (for example, image data information not included) is processed and generated into 3D visual information and output to the display unit 440 . Here, the 3D visualization information may include control information, event detection information of the data analysis unit 410 , and risk symptom detection and prediction values of the prediction module 432 . Such a visualization module 431 will be described with reference to FIGS. 5 and 6 .

FIG. 5 introduces an example of 3D visualization of non-visual information, and FIG. 6 is a diagram illustrating an example of 3D visualization of visual information.

First, referring to FIG. 5 , the visualization module 431 is characterized by visualizing a situation that is not visually visible, such as gas leakage or overheating, in 3D. The visualization module 431 includes, in addition to gas and temperature detection data, a radar sensor and/or a human body detection sensor, an access record stored in the DB 420 , operation information of the disaster prevention facility control panel 30 , and an electronic map including a corresponding area. By converging a plurality of information such as the following, the space of the location where the fire occurred is realized in 3D, and the number of people and the movement of people are expressed in 3D space using the detection data of the sensors installed in the fire area.

For example, as shown in FIG. 5 , the visualization module 431 is a space in which an event such as a fire occurred or a disaster prevention facility control panel 30 in operation according to the event detection information of the data analysis unit 410 (eg For example, the space where the alarm, fire door, fire extinguisher, blower, emergency medical device, and disaster equipment storage) is installed is realized in 3D, and the detection signals of the radar sensor and the human body detection sensor are fused to determine the number of people in the 3D image. , movement and position.

In addition, the visualization module 431 may generate (detect) an event by comparing a set threshold value and a change in non-visual information and alarm.

That is, the visualization module 431 may process 3D visual information based on a plurality of non-visual data such as state information of different types of sensors and the disaster prevention facility control panel 30 and state information of a system.

Therefore, the present invention can solve a situation that is difficult for a controller to intuitively accept by outputting non-visual information such as sensor data in a way that is listed on the monitors as in the prior art. That is, according to the present invention, as described above, non-visual information is generated based on physical information including state information of a plurality of sensors and the disaster prevention facility control panel 30 , detection data, and storage information of the DB 420 . was used as 3D spatial data to visualize the event in 3D so that the current situation of the area not confirmed by the image could be intuited.

In addition, the visualization module 431 may fuse the visual information and the non-visual information to output them on the display unit 440 . Here, the visual information corresponds to any one of image data, data in which image data and monitoring data are fused, and data in which image data, monitoring data, and state information are fused.

The non-visual information corresponds to any one of one or more sensed data, data in which one or more sensed data and state information are fused, one or more sensed data and state information, and data stored in the DB 420 . Here, the data stored in the DB may include at least one of an electronic map of the field, previous control information, event information and danger sign information, external environment information, and information downloaded from a portal site.

An example of this is introduced in FIG. 6 .

6 is a diagram illustrating an example of visualization of visual information.

Referring to FIG. 6 , the visualization module 431 may fuse the image data of the image monitoring unit 10 and the sensing data of the sensor unit 20 to display the sensor data in the captured image. At this time, the visualization module 431 displays the sensor data in the image data, but displays spatial information in which the sensor is disposed and related data in a 3D visualization form.

For example, as shown in FIG. 6 , the visualization module 431 displays information such as the progress direction of the leaked gas in the case of gas detection, the predicted additional accident, and the reason for the leak in 3D on the image as shown in FIG. It creates 3D visualization information that the controller can intuit.

The prediction module 432 may use the image data of the image monitoring unit 10 and/or the detection data of the sensor unit 20 to predict events and accidents to alert warnings and dangerous situations. To be more specific, the prediction module 432 is a deep learning-based engine that learns metadata of sensors and previous event information stored in the DB 420 and sets the data as a reference before an event occurs. In addition, the prediction module 432 may issue an alarm when it corresponds to data set based on the current control information and a set range.

In addition, the prediction module 432 may predict a danger sign by analyzing a pattern of the past sensed data and a human behavior pattern. That is, the prediction module 432 may, for example, detect an abnormal image of a hazardous substance pipeline and an abnormal pattern of a sensing temperature value to issue an alert to the display unit 440 or the mobile terminal 50 before the pipeline is damaged. there is. Alternatively, the prediction module 432 may analyze an intruder's behavior pattern when a suspicious person is found in the image to determine the degree of risk, and may issue an alert to the display unit 440 or the mobile terminal 50 .

The monitoring custom module 433 provides a rule for a plurality of pieces of information including image data and/or sensed data output from a plurality of monitors according to the arrangement of the monitors, and a monitor that outputs information for each situation (different information A plurality of monitors are controlled to output an image according to an operation scenario for each situation specifying a monitor to output or a plurality of monitors to output the same information) and an output method (sharing or division of a screen).

The operation scenario for each situation may include, for example, screen sharing, screen division, and/or information transfer by specifying monitors that output image information when a fire situation occurs among a plurality of monitors, or gas during a fire situation. It can be specified to output information about leaks, intruder detection, and the like. In this case, the operation scenario for each situation may be set to output one piece of information to one monitor, or one or more monitors may be integrated to output one piece of information.

That is, according to the present invention, the monitor construction of the control environment is different for each control environment, and the change of the control environment due to seat change and personnel relocation and the monitoring custom module so that the main control information can supplement the environment that is different according to the characteristics of the controller (433) is characterized in that it provides.

The playback module 434 specifies characteristics by interworking control information (eg, image data and sensor detection data), searches for past control information related to the specified control information, and outputs it to the display unit 440 . can do. An example of such a playback module 434 will be described with reference to FIG. 7 .

7 is a diagram illustrating an example of a playback image of control information.

Referring to FIG. 7 , the playback module 434 specifies the characteristics of the currently sensed control information by interworking the data of the image monitoring unit 10 and the sensor unit 20 . The characteristics of the control information include, for example, image information within a specific area (space) and detection data (eg, temperature, gas, illuminance, humidity, human body detection) of the sensor unit 20 of the corresponding area (space). , flame, smoke, vibration).

The playback module 434 searches for any one or more of the detection data of the control information as described above for past event, time, and situational data associated with the specified feature, and as shown in FIG. 7 , the display unit It can output to (440).

In addition, the playback module 434 can search the video for each channel of the video monitoring unit 10 by date and time, and process and provide the features for each event as a thumbnail to quickly search for changes in the video. make it possible

In addition, the playback module 434 provides a function that allows the controller to quickly search for a desired scene by generating snapshots for each search time period.

That is, the playback module 434 may output past information of the control information for each event, time, and situation to the display unit 440 , and to shorten the search time, use thumbnails and snapshots. can provide

The image processing module 435 applies automatic resolution control technology and compression technology, for example, reduces the bandwidth to a level of 10 Mbps, and separates real-time image information and recording mode for streaming. Therefore, the image processing module can reduce and transmit the image captured by the image monitoring unit 10 , thereby minimizing network load, and preventing image damage such as screen buffering or image distortion.

The present invention includes the configuration as described above, and a control method capable of data-based 3D visualization according to the present invention will be described below.

4 is a flowchart illustrating a data-based 3D visualization possible control method according to the present invention.

Referring to FIG. 4 , the present invention includes a step S100 of collecting data, a step S200 of analyzing the collected data to predict an event and/or risk sign and outputting the result as 3D visualization information, and a set operation scenario for each situation according to the step S300 of outputting the control information.

Step S100 is a step of collecting data from the image monitoring unit 10 and the sensor unit 20 and storing the data in the DB 420 . Here, the DB 420 classifies and stores the collected data for each set item.

Step S200 is a step of processing the collected data into 3D visualization information, and analyzing the collected data to detect whether a danger sign and/or event has occurred.

To this end, step S200 includes a step S210 of detecting an event by analyzing the collected data, a step S220 of analyzing the collected data and outputting a detection and/or prediction value of a danger sign, and the collected data and an event and/or a danger sign It includes a step S230 of processing and outputting visual information as 3D visualization information among the detection and prediction values of , and a step S240 of processing and outputting non-visual information into 3D visualization information.

Step S210 is set by analyzing the image data stored in the DB 420 and/or the detection data of the sensor unit 20 and the state information of the disaster prevention facility control panel 30 in the data analysis unit 410 or the prediction module 432 . It is a step of detecting whether an event corresponding to a threshold has occurred.

Here, the data analysis unit 410 selectively detects an object according to a user selection (eg, a person, a car, a bag, a bogie, etc.), and sets a specific event (eg, trespassing, swarming, roaming, person/object detection, path/moondam/intrusion, etc.) can be detected.

Step S220 is a step in which the prediction module 432 analyzes the image data stored in the DB 420 and/or the detected data of the sensor unit 20 to detect and predict a danger sign. Here, the prediction module 432 detects or predicts a danger sign by extracting feature points by interworking the image data and the sensed data.

In this case, the prediction module 432 may predict a danger sign by setting a threshold value (reference value) of a feature point by analyzing past event information, patterns of past sensed data, and human behavior patterns.

That is, the prediction module 432 is a deep learning-based engine that learns metadata of sensors and previous event information stored in the DB 420, sets data before an event occurs as a reference, and controls the current By analyzing the information, an alarm can be issued when the reference value is met.

In addition, the prediction module 432 may predict a danger sign by analyzing a pattern of the past sensed data and a human behavior pattern. That is, the prediction module 432 may, for example, detect an abnormal image of a hazardous substance pipeline and an abnormal pattern of a sensing temperature value to issue an alert to the display unit 440 or the mobile terminal 50 before the pipeline is damaged. there is. Alternatively, the prediction module 432 may analyze an intruder's behavior pattern when a suspicious person is found in the image to determine the degree of risk, and may issue an alert to the display unit 440 or the mobile terminal 50 .

Step S230 is a step of converting visual information in which the image data of the image monitoring unit 10, the detection data of the sensor unit 20, and the state information of the disaster prevention facility control panel 30 are fused into 3D visual information in the visualization module 431 am. The visualization module 431 fuses the image data with the sensor type, location, and detection data (eg, at least one of time, temperature and humidity, gas flow, person, flame, and illuminance). The image data is processed into 3D visualization information so that

For example, the 3D visual information of the visual information may be implemented as an image in which the position of the sensor or the position of the disaster prevention facility control panel 30 and the sensed data are three-dimensionally implemented, as shown in FIG. 6 . Here, the 3D visual information may also include event information, danger sign detection and prediction messages.

Step S240 is a step of processing and outputting non-visual information into 3D visualization information. The visualization module 431 stores non-visual information (detected data of the sensor unit 20 in an area (space) not included in the image) among the control information with the sensor unit 20 of a different type of data and the DB 420. By fusion of the stored information, the area (space) of the position where the feature point is identified is implemented in 3D, and the sensed data (eg, fire occurrence, personnel and movement) of the sensor unit 20 is expressed in 3D spatial data.

Step S300 is a step of outputting 3D visualization information to a plurality of monitors according to a set operation scenario for each situation. Here, the monitoring custom module 433 specifies a characteristic by interworking control information (eg, image data and sensor detection data), searches for past control information related to the specified control information, and provides a set operation scenario for each situation. Accordingly, it may be output to the display unit 440 .

In this case, the display unit 440 outputs one screen, a divided screen, or different information by one or more monitors specified according to an operation scenario for each situation set by the control of the playback module 434 , respectively. .

In addition, in either step S200 or step S300 , the playback module 434 specifies the characteristics of the currently sensed control information by interworking the data of the video monitoring unit 10 and the sensor unit 20 . In addition, the playback module 434 may search for any one or more of the detection data of the control information as described above for past event, time, and situational data related to the specified feature and output it to the display unit 440 . .

In addition, the playback module 434 may output past information for each event, time, and situation of the control information to the display unit 440 according to the input command, and to shorten the search time, a thumbnail and Snapshots can be provided.

Although the present invention has been described with reference to limited embodiments and drawings, the present invention is not limited thereto, and various modifications and variations are possible by those skilled in the art to which the present invention pertains.

A person of ordinary skill in the art related to this embodiment will understand that it may be implemented in a modified form within a range that does not deviate from the essential characteristics of the above description. Therefore, the disclosed methods should be considered in an illustrative and not a restrictive sense. The scope of the present invention is indicated in the claims rather than the foregoing description, and all differences within the scope equivalent thereto should be construed as being included in the present invention.

10: video monitoring unit
20: sensor unit
30: disaster prevention equipment control panel
40: control device
50: mobile terminal
410: data analysis unit
420 : DB
430: diagnostic processing unit
431: visualization module
432: prediction module
433: Monitoring custom module
434: Playback module
435: image processing module
440: display unit

Claims (10)

One or more disaster prevention equipment control panel 30 for outputting status information;
a sensor unit 20 having a plurality of sensors;
Video monitoring unit 10 having a plurality of cameras; and
Detects and predicts whether an event occurs and dangerous signs by analyzing the control information including at least one of the image data of the video monitoring unit 10, the detection data of the sensor unit 20, and the state information of the disaster prevention facility control panel 30 including a control device 40 that
The control device 40
processing and outputting visual information in which image data and detection data are fused and non-visual information in which at least one of a plurality of detection data and state information of the disaster prevention facility control panel 30 are fused into 3D visual information; A control system capable of data-based 3D visualization, characterized by
The method according to claim 1, The control device (40)
a data analysis unit 410 for detecting an event by collecting image data and detection data;
DB 420 for classifying and storing the control information collected by the data analysis unit 410 and the previous event and risk symptom prediction information according to the set classification conditions;
a display unit 440 configured of a plurality of monitors to share or divide one or more screens to output; and
A diagnostic processing unit that analyzes the collected control information, the threshold value set according to the previous information in the DB 420, and converts the detection of the danger sign and the predicted value of the danger sign, and the event information into 3D visual information and outputs it on the display unit 440 (430); A control system capable of data-based 3D visualization including
The method according to claim 1 or 2, the control device (40)
a visualization module 431 for processing and outputting control information into visual information and non-visual information into 3D visual information;
As a deep learning-based engine, it learns the metadata of sensors and previous event information stored in the DB 420, sets the data before an event as a reference, and detects danger signs by analyzing the current control information. a prediction module 432;
Controlling a plurality of monitors by specifying whether to output information, share a screen, or divide a screen for each monitor according to a situation-specific operating scenario set for a plurality of image data output to a plurality of monitors and control information including detected data monitoring custom module 433; and
a playback module 434 for specifying control information by interworking with each other, searching for past control event, time, and situational data related to the specified control information, and outputting it to the display unit 440; A data-based 3D visualization control system that includes.
The method according to claim 3, wherein the visualization module 431 detects the occurrence of an event by comparing a set threshold value and a change in non-visual information; A control system capable of data-based 3D visualization, characterized by
4. The method of claim 3, wherein the prediction module (432) is
Setting a standard by analyzing patterns of past detection data and human behavior patterns stored in the DB 420, and predicting danger signs by analyzing current control information; A control system capable of data-based 3D visualization featuring
4. The method of claim 3, wherein the playback module (434) is
generating at least one of a thumbnail including features for each event and a snapshot for each search time period; A control system capable of data-based 3D visualization, characterized by

a) collecting control information including at least one of detection data of a plurality of sensors, status information of one or more disaster prevention facility control panels 30 , and image data of an image monitoring unit 10 ;
b) processing and outputting visual information in which image data and sensing data are fused from the collected control information and non-visual information including at least one of a plurality of sensing data and state information into 3D visual information; and
c) controlling a plurality of monitors to output information by specifying each situation, time, and event according to a set operation scenario for each situation; A control method capable of data-based 3D visualization including
The method according to claim 7, b) step
b-1) detecting whether an event has occurred by analyzing the previous control information stored in the DB 420 and analyzing the set reference value and the current control information;
b-2) analyzing the previous control information stored in the DB 420 and comparing and analyzing the data and behavior patterns set as reference values with the data and behavior patterns of the current control information to detect and predict danger signs;
b-3) processing visual information in which image data and one or more sensing data are fused in control information into 3D visual information; and
b-4) processing the non-visual information in which at least one of the one or more detection data and the state information of the disaster prevention facility control panel 30 are fused into 3D visual information; comprising at least one of
The 3D visual information of steps b-3) and b-4) is
A control method capable of 3D visualization based on data, characterized in that it includes event and danger sign detection and predictive values.
The method according to claim 8, b-1) step
selectively detecting a target, and setting a specific action and specific phenomenon of the target as an event; A control method capable of data-based 3D visualization, characterized by
The method according to claim 8, b) step
b-5) outputting past information for each event, time, and situation, and generating thumbnails and snapshots to shorten the search time; A control method capable of data-based 3D visualization that further includes.

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