KR102016067B1 - Sensing system - Google Patents

Abstract

According to one embodiment of the present invention, provided is a sensing system which includes: at least one of a sensor module, a memory module, a light emitting module, a power module, a memory module, an interface module, a display module, an alarm module, a heating module, a sterilization module, a communication module, and a driving module; and an operating device transmitting and receiving a signal related to a state and control.

Description

Sensing System {SENSING SYSTEM}

The present invention relates to a sensing system, and more particularly, to a sensing system capable of controlling various operating devices connected to a terminal through a wireless communication network using a sensor attached to the operating device.

Recently, with the advent of the Internet of Things (IoT) era, sensor technology, one of the core technologies of the IoT, is becoming more important. IoT devices and mobile terminals equipped with sensors are becoming common to provide mutual information in a wireless environment.

In addition, with the advent of low-power wireless communication technologies such as BLE (Bluetooth low energy) and beacon (beacon), the Internet of things (IoT) technology is rapidly developing. In this regard, sensor devices are attached to various objects and provide information of the objects.

In addition, the sensor device may be connected to various devices used in daily life, and may be used for controlling the operation of the device. In particular, various products and systems have been developed using mobile terminals, which have become a necessity of modern man, and sensor devices attached to various objects. There is a demand for a method for more conveniently controlling various devices using the mobile terminal and the sensor device.

Korean Patent Publication No. 10-2017-0049273

One aspect of the present invention provides a sensing system capable of controlling various operating devices connected to a terminal through a wireless communication network using a sensor attached to the operating device.

According to another aspect of the present invention, in statistical information displayed through a web page generated in a terminal or an operating device, a user may generate various dynamic graphs for statistical data with a simple operation.

Another aspect of the present invention is to protect important information such as user information or system information to be protected from external attacks such as hacking or ransomware, and reliable analysis of the data input by the user through a decision model. Provides a sensing system to provide.

Another aspect of the present invention is formed by connecting the terminal and the wireless communication network is possible to control through the terminal, provided to face each other thickness measuring apparatus comprising an upper sensor and a lower sensor for measuring the thickness of the specimen located between the Provides a sensing system that can be controlled.

The technical problem of the present invention is not limited to the technical problem mentioned above, and other technical problems not mentioned will be clearly understood by those skilled in the art from the following description.

The sensing system according to an embodiment of the present invention comprises at least one of a sensor module, a memory module, a light emitting module, a power module, a memory module, an interface module, a display module, an alarm module, a heating module, a sterilization module, a communication module, and a driving module. It includes, and the operating device for transmitting and receiving signals related to the status and control.

In one embodiment, a terminal for receiving the signal output from the operating device, and transmits the first control signal to the operating device in response to the received signal: and a processing result according to the task requested through the terminal A management server for displaying a web page linked to the communication network, wherein the operating device receives a response to the signal from the terminal, detects a user's access to the terminal based on the received response, A sensing module configured to generate a second control signal for operating the operating device based on a sensing result; A device control module configured to operate the operating device according to the received first control signal and the second control signal; And the sensor module, the memory module, the light emitting module, the power module, the memory module, the interface module, the display module, the alarm module, the heating module, the sterilization module, and the like controlled by the device control module. A terminal communication module including at least one of a communication module and the driving module, the terminal receiving the signal output from the operating device; And a terminal control module for outputting the first control signal including identification information of the terminal in response to the received signal, wherein the management server comprises the web page via the communication network by the terminal or the operating apparatus. When connected to the web page, the system engineering tab, construction work tab, quality control of the operating device on the web page, so that the terminal or the operating device user can perform all the tasks related to the operation of the operating device through the web page A tab, a common task tab, a customer management tab, a library tab, a community tab, an electronic payment processing status tab, and a control tab are displayed to be displayed, but the management server restricts reading in the process of using an electronic file included in the web page. Set a condition and check whether the browsing restriction condition is satisfied according to the history information recorded in the process of using the electronic file. And setting the security program to modulate the code of the electronic file when the read restriction condition is satisfied, and setting the security program to periodically check whether the terminal requesting to view the electronic file can be communicated. When it is confirmed that the communication of the terminal that has requested the reading of the electronic file is blocked, and the terminal determines that the reading or output of the electronic file is requested, the code of the electronic file regardless of whether the reading restriction condition is satisfied. Set the security program to tamper with, and the management server generates a data sheet for statistical data and displays it in the first area of the web page, and selects a predetermined area of the data sheet received from the terminal. Classify the variable name selected by the user based on the signal, Generates a dynamic graph based on variables corresponding to the selected at least one variable name and displays the dynamic graph in the second area of the web page, and prints or stores the dynamic graph for printing or storing the dynamic graph displayed in the second area. Moving to and displaying the third area of the page, and generating the dynamic graph automatically distinguishes the name of the dynamic graph and the types of variables with respect to the horizontal and vertical axes of the graph according to the order of selection signals sequentially input. Generating a dynamic graph for each group of variables belonging to the selected variable name, and displaying graphic information indicating a statistical meaning of the dynamic graph on the dynamic graph, wherein the graphic information is generated. Depending on the type of The graphic information may include at least one of information on average, standard distribution, frequency, regression line, and frequency distribution polygon, and based on a selection signal for a graph type selection region displayed in a fourth region of the web page, The dynamic graph of the form is converted into a dynamic graph of the second form for the same variable name and displayed on the second area of the web page, and the operating device is formed of a thickness measuring device including the device control module and the sensor module. The sensor module includes an upper sensor and a lower sensor which are provided to face each other and measure thicknesses of specimens located therebetween, and the device control module includes spots of light output for distance measurement from the upper sensor and the lower sensor, respectively. (spot) The center point coincides, and the measurement range of each of the upper sensor and the lower sensor may overlap. Lock the position of the upper sensor and the lower sensor, the device control module, transmits and receives information with the terminal, controls to output light from the upper sensor to the lower sensor, and controls a predetermined drive module The position of the lower sensor is selected by monitoring the spectral view of the light output from the upper sensor to the lower sensor while moving the lower sensor.

In one embodiment, the device control module monitors the distance and intensity of the data of the spectral view to select a point as the position of the lower sensor at a point where the data of the spectral view satisfies a predetermined condition, The device control module stores the data whenever the data of the spectrum view changes as a file for monitoring the spectrum view, extracts a point where the data of the spectrum view satisfies a predetermined condition by comparing the generated files in turn. When the device control module stores the data file of the spectrum view, the device control module sequentially generates and stores the primary backup file and the secondary backup file including the same data, and stores the primary backup file and the secondary backup file. Save the location differently, and save the storage location of the primary backup file and the secondary backup file that were saved at the preset interval. When changing to a preset location or a newly created location on the system, and the device control module stores the data file of the spectrum view, the device control module assigns an index to each file and stores the index in the history information database. By assigning importance to each other and building the history information database according to the importance level, when the index of the history information database reaches a preset index, the entire index of the history information database is divided into three sections in ascending order, 3 Unconditionally deletes the file corresponding to the section containing the lowest index among the sections, updates the file corresponding to the middle section among the three sections according to the importance assigned to the file, and updates the file. Solution to the interval containing the highest index of the interval Maintaining a file as it is, the device control module further comprises extracting a point where the data of the spectrum view meets a predetermined condition using artificial intelligence, the device control module, the file is generated in turn And comparing and evaluating a point at which the data of the spectral view to be compared to satisfy a predetermined condition and a point at which the data of the spectral view to be extracted using the artificial intelligence satisfy a predetermined condition.

According to one aspect of the present invention, by providing a sensing system that can control various operating devices connected to the terminal through a wireless communication network using a sensor attached to the operating device, the user without direct contact with the various operating devices The operating device can be controlled using a terminal even at a long distance.

In addition, according to the present invention, all the tasks related to the operation apparatus performed through the communication network can be integrated and managed through the web page on which the sensing system is constructed, and in the statistical information displayed through the web page, the user can perform statistics only by simple operation. Various dynamic graphs of data can be generated to improve the efficiency of data analysis.

In addition, it protects important information such as user information or system information that should be protected from external attacks such as hacking of data distributed through web pages or ransomware, and reliability of data input by users through decision model. Can provide analytical results.

Another aspect of the present invention is formed by connecting to the terminal and the wireless communication network is possible to control through the terminal, provided to face each other thickness measuring apparatus including an upper sensor and a lower sensor for measuring the thickness of the specimen located between the It is effective to provide a sensing system that can be controlled.

1 is a conceptual diagram illustrating a schematic configuration of a sensing system according to an embodiment of the present invention.
2 is a diagram illustrating a state in which a sensing system according to an embodiment of the present invention is applied to a door sensor for a vehicle.
3 is a view illustrating a state in which a sensing system according to an embodiment of the present invention is applied to a thermal belt.
4 is a diagram illustrating a state in which a sensing system according to an embodiment of the present invention is applied to a thickness measuring apparatus.
FIG. 5 is a diagram for describing position control of the upper sensor and the lower sensor illustrated in FIG. 4.
6 is an example of a spectrum measured when light is output from the upper sensor shown in FIG. 4 to the lower sensor side.
7 is a conceptual diagram illustrating a schematic configuration of a sensing system according to another embodiment of the present invention.
8 is a diagram for describing an example of generating a dynamic graph based on statistical data.
9 and 10 illustrate examples in which different graphic information is generated according to the type of dynamic graph.

DETAILED DESCRIPTION The following detailed description of the invention refers to the accompanying drawings that show, by way of illustration, specific embodiments in which the invention may be practiced. These embodiments are described in sufficient detail to enable those skilled in the art to practice the invention. It should be understood that the various embodiments of the present invention are different but need not be mutually exclusive. For example, certain shapes, structures, and characteristics described herein may be embodied in other embodiments without departing from the spirit and scope of the invention in connection with one embodiment. In addition, it is to be understood that the location or arrangement of individual components within each disclosed embodiment may be changed without departing from the spirit and scope of the invention. The following detailed description, therefore, is not to be taken in a limiting sense, and the scope of the present invention, if properly described, is defined only by the appended claims, along with the full range of equivalents to which such claims are entitled. Like reference numerals in the drawings refer to the same or similar functions throughout the several aspects.

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

1 is a conceptual diagram illustrating a schematic configuration of a sensing system according to an embodiment of the present invention.

The sensing system 1000 according to another embodiment of the present invention may include a terminal 100 and an operation device 300.

The terminal 100 is a communication capable device having an input means such as a keypad, a touch pad, etc., an output means such as a display unit, and a CPU module capable of processing information, such as a PC, a notebook, a smartphone, a mobile phone, and the like. In addition, the terminal 100 is connected to the control unit of the operation apparatus 300 to be described later in a wireless communication method. The wireless communication method is at least one of various types of wireless communication methods applicable to the technical field, such as RF (Radio Frequency), NFC (Near Field Communication), WiFi (Wireless Fidelity), Bluetooth, Bluetooth, and ZigBee. It is composed of a communication module supporting the terminal 100 and the operating device 300 can communicate with each other, it can be variously changed in a range known to those skilled in the art. The terminal 100 may be connected to the operation apparatus 300 in a wireless communication manner to control the operation apparatus 300. In one embodiment, the terminal 100 may receive a signal output from the operating device 300, and transmit a first control signal to the operating device in response to the received signal. Here, the first control signal is a signal including information for driving the operating device 300, and may be formed as a signal involved in the operation of each component of the operating device 300. In more detail, the terminal 100 controls a terminal to output a first control signal including identification information of the terminal 100 in response to the terminal communication module and the received signal output from the operating apparatus 300. It may include a module. The identification information may be formed of information indicating that the terminal 100 is permitted to control the operating apparatus 300.

The operating device 300 may be connected to the terminal 100 in a wireless communication manner to transmit and receive information with each other, and may be controlled by the terminal 100. The information is information on the operation, status, control, etc. of the components of the operating device 300, and may include information about the various operating devices 300 according to an embodiment. That is, the user may control the operation apparatus 300 at a long distance by using the terminal 100 such as a mobile phone, and operate the operation apparatus 300 automatically according to a user setting input through the terminal 100. can do. The operating device 300 includes a device control module for transmitting and receiving information to and from the terminal 100, a sensor module, a memory module, a light emitting module, a power module, a memory module, an interface module, a display module, an alarm module, It may be formed of a device including at least one of a heating module, a sterilization module, a communication module and a driving module. For example, the operating device 300 may include a fire detector, a heater, an air cleaner, a car door, a lighting device, a solar device, a sensor device, an alarm device, a security device, a display device, a low frequency treatment device, and a demo kit. ), A power supply / blocker, a temperature control device, and the like. However, this is merely an example, and may include various types of operation apparatuses 300 according to embodiments.

In one embodiment, the operating device 300 may transmit and receive signals to and from the terminal 100, and receive a first control signal for operating the operating device 300 from the terminal 100. In detail, the operating device 300 may receive a response to the signal from the terminal 100. In this case, the response from the terminal 100 is that the terminal 100 detects the operating apparatus 100, is ready to control the operation of the operating apparatus 100, or the terminal 100 operates in the operating apparatus 300. It may include various responses such as being located at a distance enough to control. Subsequently, the operating device 300 detects a user's approach of the terminal 100 based on the received response, and generates a sensing module that generates a second control signal for operating the operating device 300 based on the detection result. It may include. Here, the detection of the user's access means, for example, to activate an application installed in the terminal 100 to control the operating apparatus 300 or to control the operating apparatus 300, the terminal 100 and the operating apparatus 300. May include detecting that the connection is made through a communication network. Subsequently, the operating device 330 operates the operating device 300 according to the first control signal received from the terminal 100 and the second control signal received by the sensing module in the operating device 300. It may include. In addition, as described above, at least one of a sensor module, a memory module, a light emitting module, a power module, a memory module, an interface module, a display module, an alarm module, a heating module, a sterilization module, a communication module, and a driving module controlled by the control module. It may include one.

2 is a diagram illustrating a state in which a sensing system according to an embodiment of the present invention is applied to a door sensor for a vehicle.

Referring to FIG. 2, an operating apparatus according to an embodiment of the present invention may be applied to a vehicle door sensor 300. The vehicle door sensor 300 is connected to the device control module and the device control module for controlling and modifying and storing the memory of the piezo sensor module, the memory module, the LED light emitting module, the power module and the memory module, and access the user of the terminal 100. The sensing module may include a sensing module configured to generate a second control signal for operating the vehicle door sensor 300 based on the sensing result. In this way, the user may open or lock the door of the vehicle using a portable terminal 100 such as a mobile phone at a long distance without directly contacting the vehicle door.

3 is a view illustrating a state in which a sensing system according to an embodiment of the present invention is applied to a thermal belt.

Referring to Figure 3, the operating device according to an embodiment of the present invention can be applied to the thermal bag 300. The user can control and set the operation of the thermal bag 300 using the terminal 100 formed of a smartphone. The thermal bag 300 may include a device control module, a heating wire, a temperature setting module, a USB power module, a sensing module including a Bluetooth transceiver. At the same time, the terminal 100 may be formed with a smart phone application for controlling the heating bag 300.

4 is a diagram illustrating a state in which a sensing system according to an embodiment of the present invention is applied to a thickness measuring apparatus.

Referring to FIG. 4, the thickness measuring apparatus 300 according to an embodiment of the present invention may include a device control module and a sensor module. Specifically, the sensor module may include an upper sensor 310 and a lower sensor 320 to measure the thickness of the specimen located between the upper sensor 310 and the lower sensor 320.

The upper sensor 310 and the lower sensor 320 are optical sensors, and the light transmitting part and the light receiving part may be provided coaxially to measure the distance to the specimen. In particular, the spot diameter of the upper sensor 310 and the lower sensor 320 is, for example, is formed of 2um to enable precise measurement. In addition, the Z-axis resolution (Resolution) of the upper sensor 310 and the lower sensor 20 is formed to approximately 10nm to ensure the accuracy of the distance measurement.

The upper sensor 310 and the lower sensor 320 may be provided to face each other, and may be provided to be movable in three dimensions.

Thickness measuring apparatus 300 according to an embodiment of the present invention may further include a device control module for controlling the three-dimensional movement of the upper sensor 310 and the lower sensor 320.

The device control module controls the position of the upper sensor 310 and the lower sensor 320 so that the upper sensor 310 and the lower sensor 320 can simultaneously measure the same point of the specimen for accurate thickness or shape measurement of the specimen. can do. In addition, the device control module transmits and receives information with the terminal 100 and controls the positions of the upper sensor 310 and the lower sensor 320 based on a user input through the terminal 100. In addition, the distance and intensity, which are data of the spectrum view, may be monitored, and the result or information may be transmitted to the terminal 100 and the corresponding information may be received.

FIG. 5 is a diagram for describing position control of the upper sensor and the lower sensor illustrated in FIG. 4.

Referring to FIG. 5, the spot center points of light output for distance measurement from the upper sensor 310 and the lower sensor 320 coincide with each other, and the measurement ranges of the upper sensor 310 and the lower sensor 320 respectively overlap. In this case, since the distance to the same point of the specimen is measured at the same time, accurate thickness measurement of the specimen is possible.

The device control module may control the positions of the upper sensor 310 and the lower sensor 320 to satisfy the above conditions.

For example, the device control module controls to output light from the upper sensor 310 to the lower sensor 320, and controls the predetermined driving module to move the lower sensor 320 to lower sensor from the upper sensor 310. An optimal position of the lower sensor 320 may be selected by monitoring a spectrum view of the light output to the 320. In this regard, FIG. 6 will be described as an example.

6 is an example of a spectrum measured when light is output from the upper sensor shown in FIG. 4 to the lower sensor side.

Referring to FIG. 6, an example of a spectral view of the CHRocodile Explorer when outputting light from the upper sensor 310 to the lower sensor 320 may be confirmed. In the spectral view, the x-axis represents distance and the y-axis represents intensity.

The device control module may position the lower sensor 320 so that the distance in the spectral view is centered and the intensity is measured relatively high. That is, the device control module may stop the movement of the lower sensor 320 and fix it at the corresponding position when the distance is located at the center and the intensity is measured relatively while monitoring the spectrum view.

In this case, the spot center points of the light output for distance measurement from the upper sensor 310 and the lower sensor 320 respectively coincide with each other, and the measurement ranges of the upper sensor 310 and the lower sensor 320 respectively overlap.

The device control module can save the spectral view as a file whenever the spectral view's data (intensity and distance) changes. The device control module may compare the generated files in turn and extract a point where the distance is located at the center and the intensity is measured relatively high.

The device control module may include a backup file decentralization module for file storage of data of the spectrum view.

The backup file decentralization module sequentially generates and stores the generated file as a primary backup file and a secondary backup file including the same data, but stores the primary backup file and the secondary backup file in different storage locations.

However, the backup file is not limited to the first and second generations, and a plurality of three or more backup files may be generated in consideration of system performance.

In addition, the backup file decentralization module may be configured at a predetermined cycle (for example, once every 3 hours or once every 5 hours, which is basically a cycle set on the system). Changes the storage location of the primary backup file and the secondary backup file that have been saved to a preset location or a newly created location on the system.

In this case, it is preferable that the moving place of the backup file is designated as a folder or a sub folder created according to an arbitrary random variable, not a place previously set or designated by the user.

Accordingly, it is possible to prevent an attack program such as hacking or ransomware from predicting the existence of the folder in which the file to be attacked or the location of the folder is located and easily attacking the customer. The same important data can be prevented from being accidentally deleted or modified by the user.

In the present invention, the primary backup file and the secondary backup file are files containing data having the same contents, and no superiority exists between each other, and even when the file is moved, the secondary backup file is moved after the primary backup file. The file may be moved or the primary backup file may be moved after the secondary backup file is moved.

In one embodiment, if an intrusion is detected from the outside, the backup file distribution module continuously performs replication from the previously created primary backup file and the secondary backup file to generate a plurality of sub backup files of each backup file. In addition, the generated plurality of sub backup files may be separately stored in different locations generated according to random variables.

Accordingly, by dividing and storing a number of backup files sporadically generated on the system to any place, even if some backup files are lost or deleted due to an attack, necessary data using the backup files sporadically existing on the system Can be easily recovered.

Next, the backup file decentralization module permanently deletes a file determined to be a backup file currently under attack among a plurality of backup files on the system.

Accordingly, in the present invention, due to hacking or ransomware attack, etc. may not be able to perform a normal function on the system, or due to the attack may be changed to a zombie program that may expose other files on the system to risk. By deleting files on your system, you can prevent some files from attacking your entire system.

In one embodiment, if the backup file decentralization module stores the backup file in a synchronization folder linked with the cloud service, when the storage of the backup file is completed in the synchronization folder and the stored backup file is uploaded on the cloud, the synchronization is performed. You can turn off synchronization for a folder.

For example, when the cloud service for user synchronization is "Dropbox", the function of the backup file decentralization module as described above is implemented using the "selective synchronization service" provided by "Dropbox".

That is, when the backup file decentralization module creates a "backup folder" on the system as a space for storing the backup file, the cloud service also creates a newly created "backup folder" on the cloud in the same way.

Next, the backup file decentralization module will store the backup file in the folder, and thus the backup file is uploaded on the cloud.

Finally, upon completion of the upload of the corresponding backup file on the cloud, the backup file decentralization module selectively releases only the synchronization for the "backup folder" that was used for the backup file upload, and deletes the "backup folder" from the system.

In this case, instead of disabling system-wide synchronization, by disabling only the "backup folder" that was temporarily created for use in uploading backup files, stable synchronization service with cloud service is continuously performed. On the other hand, as the backup file is uploaded to the cloud and then deleted on the system, the backup file can be safely stored on the cloud while being constantly prevented from being continuously exposed to the attack invading the system.

In one embodiment, the backup file decentralization module downloads the backup file that was uploaded to the cloud service by performing the synchronization of the folder that has been deactivated again when the order of changing the storage location of the backup file that was uploaded on the cloud is changed. Thereafter, the downloaded backup file may be moved to a newly created place according to a random variable as described above.

In order to monitor the spectrum view, the device control module can save it as a file whenever the data (intensity and distance) of the spectrum view changes, and each file can be indexed and stored in the history information database.

In this case, the device control module may build a history information database for each file generation time. That is, the control unit assigns importance to each file generation time, and builds a history information database according to the importance, and the file corresponding to the highest priority is used in the database update target for storage space management as described below. May be excluded.

The device control module may update the history information database for efficient storage space management.

Specifically, the device control module may update the history information database when the index of the history information database reaches a preset index.

For example, the device control module may divide the entire index of the history information database into three sections in ascending order.

The device control module may delete the file corresponding to the section including the lowest index among the three sections without condition. The file corresponding to the section may be considered to have elapsed a long time since the creation / modification date, and since the file is unlikely to be referenced again, the file may be deleted without conditions.

The device control module may update the file corresponding to the middle of three sections by determining whether to delete or maintain the file according to the importance assigned to the file. That is, the device control module can assign importance to the file creation time, and keeps only the file corresponding to the type of the file with the highest importance among the files corresponding to the middle section among the three sections, and deletes all other files. The history information database can be updated in a manner.

The device control module may maintain the file corresponding to the section including the highest index among the three sections. The file corresponding to the section may be considered to have a relatively recent creation / modification date, and thus the file may be kept as it is likely to be referred to again.

Alternatively, a part of the device control module may be implemented by artificial intelligence, and may further include a decision reason presentation module.

The decision reason presentation module not only categorizes and predicts the data given or input by the user, but also analyzes the causality of the decision to find the appropriate basis for the reason why the result is presented by AI. The reason can be explained at the user level. The decision reasoning module enables reliable decision making between the user and AI, so that feedback from the user can be appropriately reflected in case of problems or errors. In addition, by providing a decision reason module, it is possible to solve the distrust that a user may have in artificial intelligence because the reason for the result of the artificial intelligence cannot be clearly explained. In this way, the overfitting problem that the optimal solution in the region can be selected, rather than the overall solution, can be prevented.

The device control module can evaluate the point where the distance from which the files are sequentially generated and extracted are located at the center and the intensity is relatively high, using the decision reason presentation module. In other words, the control unit can extract the files that are generated in order by comparing the distances generated at the center of the distance and measured with a relatively high intensity, or extract them using artificial intelligence, and by analyzing the causal relationship to the decision, the overall perspective It can be expected that the optimal solution at will be derived.

In one embodiment, the decision reason presentation module may further include a model building module and a reason explanation interface module. The model building module may be implemented as an in-depth explanatory learning module, an interpretable model generation module, and a model induction module.

The deep description learning module is a modified deep learning technique that allows the deep neural network to learn descriptive features. You can train nodes in the hidden layer to represent meaningful attributes, for example, if you are learning a model that distinguishes the image of the arms and legs, then each hidden node is a fingernail or toenail, a finger or toe, a palm or sole. By learning to show the location, etc., when the model determines that an image is a hand, the active hidden node can provide the basis for the decision. The basis of this determination may be expressed verbally through a natural language generation model such as RNN (Recurrent Neural Network). RNN is a model of deep learning, which is a kind of artificial neural network, for learning data that changes with time, such as time series data, and using input control vector, forgetting vector, and output control vector to input and output data. Get In the input control vector, the input signal receives the value after passing through the connection layer with the activation function, and the forgetting vector reflects a part of the past input to the current input. The output adjustment vector takes in the values using the activation function taking into account the past values and the modified input values. The final result is then returned to input. The circulatory neural network is mainly used for classifying document emotions or recognizing handwritten text, and can also be mainly used for speech recognition, time series prediction, or waveform generation. This is because the input data can be processed in a proper order even if the input data has a fixed shape without an order.

Also, in an embodiment, the in-depth learning module may visually display a part based on the image. For example, if the AI system classifies a cat image, the existing system derives only the cat whether the input image is a cat, but the in-depth learning module derives whether the cat is a cat and uses the basis (hair, beard, etc.) of the image. Can be provided to

The interpretable model generation module can construct structured data into an interpretable causal model. According to an embodiment of the present disclosure, an interpretable model generation module may be constructed using Bayesian program learning (BPL), and BPL is a method of learning to express a combination of small pieces, for example, learning a model that generates letters. When you do this, divide the letters into strokes to create the most reasonable combination of strokes. BPL can mimic a human being without a large amount of data, and it is an evolution of the Neural Network that can change the probability value based on a new event given. In other words, the BPL not only changes the weights of the virtual variables, but also includes creating another virtual variable in the middle. Given a new environment, understanding the phenomena in a different way, for example, toss a coin 100 times and face the front 60 times and the back 40 times to get a 60% chance of coming out, then the next time the back comes out. The probability of heading out is reduced to 59.4%.

In addition, in one embodiment, the interpretable model generation module may be implemented through a probabilistic approach. The probabilistic approach can be a learning effect with just a few samples, for example showing a long chair and a short chair to learn that there are also middle chairs. In other words, it is a technique of learning by filling out the insufficient data by itself. According to an embodiment, the probabilistic approach may include a function of correcting probabilities and programs by mathematical calculations.

Also, in one embodiment, the interpretable model generation module may be implemented using And-Or-Graph. And-Or-Graph is a graph showing the condition and conclusion of rule and AND / OR relationship in the form of graph. And-Or-Graph is structured intermediate and final data derived from artificial intelligence to logically determine the model decision process. There is an advantage that is easy to explain. That is, the graph is represented by an AND node and an OR node. Both AND nodes must be processed and only one OR node can be finished. By using the AND / OR graph, you can see a set of rules interspersed with each other as a structure and easily grasp the logical relationship between each sentence.

The model induction module can infer any black box model into a descriptive model. In one embodiment, the model induction module can be implemented with local interpretable model-agnostic explanations (LIME), which make the arbitrary black box model locally descriptive through sparse linear coupling around already descriptive data. Can be. For example, if a black box model that categorizes an image determines that an image is a heart, it is a description of the other model's heart that can already be described, that is, what part of the image is determined by comparing the pixels representing the heart with a given image. Can present

In addition, in one embodiment, the model induction module may be implemented as Bayesian rule lists (BRLs) that express the model as a series of if-then conditional statements. BRL breaks down high-dimensional, multivariate feature spaces into simple, already interpretable conditional statements to help understand complex models.

The above-described in-depth learning module, an interpretable model generation module, and a model induction module may operate independently of each other or in combination with each other, and their implementation order may also vary according to embodiments.

Next, the reason explanation interface module may express the description of the AI decision in a manner that can be understood by the user. Reason description The interface module may include necessary descriptions such as repeated descriptions, all necessary descriptions, no unnecessary descriptions, and appropriate amounts. That is, the user can easily provide the user with the language, tables, images, graphs, formulas, and the like, which process and the reason that the artificial intelligence has obtained the final result, and what factors or data influenced each step. .

Also, the reason explanation interface module may receive a correction command of the user. To this end, the reason description interface module may include correctability as essential items such that the description is flexible, respects the user's feedback, and observes the gradual change. The user can evaluate and develop the effect of the reason explanation interface module by receiving feedback about the clarity and utilization of the explanation.

In another embodiment, the decision reason presentation module may be formed of a causal model. The causal model may be formed to combine deep learning and Markov random fields. First, the probability distribution of the deep Markov random field model is modeled from the training data, and the structure of the Markov random field representing conditional independence between the random variables is studied. By inferring the latent function of the structured Markov random field into a deep neural network, it is possible to alleviate the problem of exponentially increasing the number of parameters required for the latent function as the number of input variables increases. Can learn associations According to an exemplary embodiment, the class classification problem may be learned like an auxiliary task, an attribute, and a super category, and then linearly combined at the output stage to enable an effective expression. It can also include interactive learning algorithms that allow a person to confirm that the causal relationship has been learned correctly and to provide feedback and make corrections.

In another embodiment, the decision reason presentation module may be implemented as an analysis module. As a technique for regressing a time series function into a multivariate Gaussian based on various kernels, we can learn the optimal kernel combinations representing the kernels in Gaussian processes and explain the given time series data based on the kernel combinations found above. Furthermore, a combination of a kernel that is expressed in common even when there is a plurality of time series data and a kernel that expresses characteristics of each time series data may be learned to describe characteristics common to a plurality of time series data. By writing the kernel combinations found through the time series data analysis model in natural language, the user can explain the process of deriving the decision made by artificial intelligence and the reason for it in natural language.

Through the module of presenting the decision reason, it is possible to visualize and textify the AI decision-making process from the user's point of view, to explain the components involved in the decision-making process, and to analyze the causes of the correlation between complex models. Can be explained by dividing into elements and result elements. In particular, it is written in the form of automatic reports that can be easily understood by the user, so that the artificial intelligence can interact with humans more precisely by providing the reason as well as the result of analyzing the data.

7 is a conceptual diagram illustrating a schematic configuration of a sensing system according to another embodiment of the present invention.

The sensing system 2000 according to another embodiment of the present invention performs activity processes for tasks such as system engineering (SE), supervision, customer management, construction work, quality control, and the like of various operating devices performed through a communication network. It is an enterprise resource management system that manages and shares by integrating.

Specifically, the sensing system 2000 according to an embodiment of the present invention may include a terminal 100, a management server 200, and an operation device 300.

The terminal 100 is a device for accessing the management server 200 through a communication network. The terminal 100 is an input means such as a keypad, a touch pad, etc., such as a PC, a laptop, a smartphone, a mobile phone, and an output means such as a display unit. And a CPU module capable of processing information. In addition, the terminal 100 is connected to the control unit of the operation apparatus 300 to be described later in a wireless communication method. The wireless communication method is at least one of various types of wireless communication methods applicable to the technical field, such as RF (Radio Frequency), NFC (Near Field Communication), WiFi (Wireless Fidelity), Bluetooth, Bluetooth, and ZigBee. It is composed of a communication module supporting the terminal 100 and the operating device 300 can communicate with each other, it can be variously changed in a range known to those skilled in the art. The terminal 100 may be connected to the operation apparatus 300 in a wireless communication manner to control the operation apparatus 300.

The terminal 100 downloads and installs an application provided by the management server 200, or accesses a web page interworking with the management server 200 and uses a sensing system 2000 provided by the management server 200. And it can transmit and receive data accordingly.

The management server 200 may manage web pages on which the sensing system 2000 is implemented. The management server 200 may connect the terminal 100 connected through the communication network to a web page associated with the operating device 300, and display the processing result according to the task requested through the terminal 100 on the web page. Can be. In this case, the web page may be generated by the terminal 100 or the operating device 300 in the display module.

The operating device 300 may be connected to the terminal 100 in a wireless communication manner to transmit and receive information with each other, and may be controlled by the terminal 100. In addition, the operating apparatus 300 may transmit mutual information to the management server 200. At this time, the information is the process of the activities, such as the operation, status, control of the components of the operating device 300, system engineering (SE), supervision, customer management, construction work, quality control, etc. Information relating to the present disclosure may include information on various operating devices 300 according to embodiments. That is, the user may control the operation apparatus 300 at a long distance by using the terminal 100 such as a mobile phone, and operate the operation apparatus 300 automatically according to a user setting input through the terminal 100. can do. The operating device 300 is a sensor module, a memory module, a light emitting module, a power module, an interface module, a display module, an alarm module, a heating module, a sterilization module controlled by a control module and a control module for transmitting and receiving information with the terminal 100. It may be formed of an apparatus including at least one of a communication module and a driving module. For example, the operating device 300 may include a fire detector, a heater, an air cleaner, a car door, a lighting device, a solar device, a sensor device, an alarm device, a security device, a display device, a low frequency treatment device, and a demo kit. ), A power supply / blocker, a temperature control device, and the like. However, this is merely an example, and may include various types of operation apparatuses 300 according to embodiments.

Meanwhile, the management server 200 may generate a graph that changes dynamically with respect to statistical data displayed through the web page and control the graph to be displayed through the web page. In this regard, it will be described with reference to Figure 8 together.

8 is a conceptual diagram illustrating an example of generating a dynamic graph based on statistical data.

As shown, the management server 200 may generate a data sheet for the received statistical data and output the data sheet to the first area of the web page. The web page 10 includes a first area 11 for displaying a data sheet, a second area 12 for displaying a graph generation result for the data sheet, and a third area for displaying a graph to be stored or printed. The area 13 may include an interface area 14 including icons for performing various functions. The web page 10 may be generated by the management server 200 in the display module of the terminal 100 or the operating device 300.

Statistical data may include raw data or summary data summarizing the raw data in the form of frequency distribution, and may be generated or stored in CSV (Comma Separated Value) format or JSON format.

These statistics can be input in a variety of ways. For example, the statistical data may be directly input through a web page displayed on the display module of the terminal 100 or the operating apparatus 300. The management server 200 may generate a data sheet form having a plurality of cells composed of rows and columns and display the data sheet in a first area of the web page. The user may generate statistics by inputting blanks of the data sheet displayed in the first area, that is, variables for statistical analysis in any one cell. The management server 200 may display the result of recording the variable in the data sheet based on the variable input from the user in the first area.

As another example, the management server 200 may receive statistical data in the form of a file through a web page. The user may upload the statistical data stored in the user terminal to the management server through the web page. The management server may classify the types of variables included in the received statistical data and automatically record them in a data sheet and display them in the first area.

After the statistical data is recorded in the data sheet, the management server 200 may generate a dynamic graph for the type of graph selected from the terminal 100 and output the dynamic graph on the second area.

When the management server receives the selection signal for the predetermined area on the first area 11 of the web page 10, the management server may collect variables for generating a graph among all variables recorded in the data sheet. In the data sheet, cells (hereinafter, referred to as variable name areas) for classifying types of variables may be arranged, and when the user selects one variable name area, the management server 200 selects a variable belonging to the selected variable name area. You can collect them.

Thereafter, when the management server 200 receives a selection signal for any one icon on the interface area 14 that is the fourth area of the webpage, the management server 200 may generate a dynamic graph according to the collected variables and the type of the selected icon. have. Here, the type of graph may include a bar graph, a pie graph, a band graph, a line graph, a dot graph, a histogram, a stem graph, a box graph, and a scatter plot graph. The type of graph generated by the management server 200 is not limited to the above example, and may further include various types of graphs for visually analyzing statistical data. The management server may arrange an icon corresponding to the type of each graph in the interface area 14 of the web page 10. In this case, a graphic representing a statistical meaning of the data may be displayed on the dynamic graph. In addition, according to an exemplary embodiment, the interface area 14 may be displayed on the display module of the terminal 100 or the operating apparatus 300 by the management server 200.

Thereafter, when the management server 200 receives a selection signal for an area for storing or printing a graph or a UI among the second areas of the webpage 10, the management server 200 displays the dynamic graph generated in the second area 12 as a third. It can be moved to the region 13 so that it can be displayed in the third region 13. The third area 13 is an area in which at least one graph selected by the user in the second area 12 is arranged and displayed. The third area 13 may be arranged to conform to a standard for output.

Hereinafter, a process of generating a dynamic graph using the statistical data analysis method using the dynamic graph according to the present invention will be described in more detail.

9 and 10 illustrate examples in which different graphic information is generated according to the type of dynamic graph. Specifically, FIG. 9 is a diagram illustrating an example of graphic information displayed on a dot graph, and FIG. 10 is a diagram illustrating an example of graphic information displayed on a scatter plot graph.

Graphical information on the mean and standard deviation for each group can be generated and displayed on the generated dynamic graph. On the other hand, the management server may generate graphic information about the regression line for the scatter plot graph selected and generated by the user. As such, the management server enables effective analysis of the generated graph by generating graphic information suitable for the type of dynamic graph instead of generating uniform graphic information. However, the generated graphic information is not limited to the above-described example, and various types of graphic information may be displayed on the dynamic graph according to the use environment and settings.

9 and 10, the management server 200 automatically generates a name of the dynamic graphic generated based on the selection signal received from the terminal 100, and thus the terminal 100 or the operating device. It may be displayed on the display module of (300). Specifically, the management server may sequentially determine the name of the graph according to the selection order of the user's selection signal for the first area on the web page. For example, if the user selects the variable name area for goods receipt first and the variable name area for goods issue second, the management server can create a name such as 'Receipt Amount: Scatter Plot of Goods Issue'. have.

Meanwhile, the management server may inform the user of the types of graphs that can be generated according to whether the variable included in the variable name selected in the process of generating the dynamic graph is a letter or a number. For example, the management server may not generate graphs or tables for variables of two or more selected variables. Or 'Variables in the form of characters cannot generate the graph you selected.' A guide message such as a web page may be output in a popup form of a web page.

In addition, the management server 200 may place icons for various functions in the interface area 14. In this case, the management server 200 may perform an additional function in addition to the function of generating a dynamic graph for the statistical data.

In addition, the management server 200 may provide simulation functions such as correlation coefficient simulation and regression simulation.

The management server 200 performing the function as described above may include a backup file decentralization module (not shown in the drawings for convenience of description).

The backup file decentralization module generates important information such as user information or system information to be protected from an external attack such as hacking or ransomware as a backup file, and then creates the backup file containing the same data. Create and save the secondary backup in order, but save the primary backup file and the secondary backup file in different storage locations.

However, the backup file is not limited to the first and second generations, and a plurality of three or more backup files may be generated in consideration of system performance.

In addition, the backup file decentralization module may be configured at a predetermined cycle (for example, once every 3 hours or once every 5 hours, which is basically a cycle set on the system). Changes the storage location of the primary backup file and the secondary backup file that have been saved to a preset location or a newly created location on the system.

In this case, it is preferable that the moving place of the backup file is designated as a folder or a sub folder created according to an arbitrary random variable, not a place previously set or designated by the user.

Accordingly, it is possible to prevent an attack program such as hacking or ransomware from predicting the existence of the folder in which the file to be attacked or the location of the folder is located and easily attacking the customer. The same important data can be prevented from being accidentally deleted or modified by the user.

In the present invention, the primary backup file and the secondary backup file are files containing data having the same contents, and no superiority exists between each other, and even when the file is moved, the secondary backup file is moved after the primary backup file. The file may be moved or the primary backup file may be moved after the secondary backup file is moved.

In one embodiment, if an intrusion is detected from the outside, the backup file distribution module continuously performs replication from the previously created primary backup file and the secondary backup file to generate a plurality of sub backup files of each backup file. In addition, the generated plurality of sub backup files may be separately stored in different locations generated according to random variables.

Accordingly, by dividing and storing a number of backup files sporadically generated on the system to any place, even if some backup files are lost or deleted due to an attack, necessary data using the backup files sporadically existing on the system Can be easily recovered.

Next, the backup file decentralization module permanently deletes a file determined to be a backup file currently under attack among a plurality of backup files on the system.

Accordingly, in the present invention, due to hacking or ransomware attack, etc. may not be able to perform a normal function on the system, or due to the attack may be changed to a zombie program that may expose other files on the system to risk. By deleting files on your system, you can prevent some files from attacking your entire system.

In one embodiment, if the backup file decentralization module stores the backup file in a synchronization folder linked with the cloud service, when the storage of the backup file is completed in the synchronization folder and the stored backup file is uploaded on the cloud, the synchronization is performed. You can turn off synchronization for a folder.

For example, when the cloud service for user synchronization is "Dropbox", the function of the backup file decentralization module as described above is implemented using the "selective synchronization service" provided by "Dropbox".

That is, when the backup file decentralization module creates a "backup folder" on the system as a space for storing the backup file, the cloud service also creates a newly created "backup folder" on the cloud in the same way.

Next, the backup file decentralization module will store the backup file in the folder, and thus the backup file is uploaded on the cloud.

Finally, upon completion of the upload of the corresponding backup file on the cloud, the backup file decentralization module selectively releases only the synchronization for the "backup folder" that was used for the backup file upload, and deletes the "backup folder" from the system.

In this case, instead of disabling system-wide synchronization, by disabling only the "backup folder" that was temporarily created for use in uploading backup files, stable synchronization service with cloud service is continuously performed. On the other hand, as the backup file is uploaded to the cloud and then deleted on the system, the backup file can be safely stored on the cloud while being constantly prevented from being continuously exposed to the attack invading the system.

In one embodiment, the backup file decentralization module downloads the backup file that was uploaded to the cloud service by performing the synchronization of the folder that has been deactivated again when the order of changing the storage location of the backup file that was uploaded on the cloud is changed. Thereafter, the downloaded backup file may be moved to a newly created place according to a random variable as described above.

In addition, the management server 200 having the configuration as described above may be implemented on a development environment management system (not shown in the drawings for convenience of description).

The development environment uses a number of development systems for software development by a number of developers, and each development system can develop and directly manage software components and software under developer control. Each development system uses the Trusted Platform Module (TPM) standard technology, which allows software components to be used only in licensed development systems. The Trust Platform Module (TPM) is a kind of security device that can generate and manage security keys for data encryption.

The development environment management system may restrict a developer's authority to use a software component and perform security authentication on a development system used by the developer.

When the development environment management system receives the software component generation or modification permission request message from the development system, the development environment management system may process the software component generation or modification permission request message by checking the authority information of the development system.

Here, the software component may be configured to include at least one of source code, binary including debugging information, pure binary not including debugging information, documentation for detailed description of the code, and process equation model for understanding the code. Can be.

The right information may include at least one of a read right for reading a software component, a storage right for creating and modifying a software component, and a right adjusting authority for adjusting the right information.

When a software component is generated or modified by any one development system that satisfies the authority information, the development environment management system may control the development environment management so that it can be shared by other development systems. This is because a module built by one development system may need to be used in another development system.

The development environment management system can build a database that stores the history of creation or modification of these software components. This is because the historical information can track step-by-step how the value of a particular variable has changed, and can also determine how that particular variable has affected the value change of any other variable.

Specifically, the development environment management system includes a type of software component, whether to create / modify the software component, the date of creation / modification of the software component, the frequency of generation / modification of the software component, and the development to create / modify the software component. The history information may be generated including the authority information of the system.

The development environment management system may assign an index every time the history information is generated and store it in the history information database.

At this time, the development environment management system may build a history information database for each type of software component. That is, the development environment management system may build a history information database according to the importance of the software component, and the history information database of the software component corresponding to the most important type is used in the database update target for storage space management as described below. May be excluded.

Alternatively, the development environment management system may build a history information database for each creation / modification date of the software component. For example, the development environment management system may construct a history information database of a specific date, and exclude the corresponding history information database from a database update target.

Alternatively, the development environment management system may build a history information database for each authority information. For example, the development environment management system constructs a history information database of software components by the development system corresponding to the authority adjustment authority that can adjust the authority information regarded as the highest authority information, and excludes the history information database from the database update target. You can.

The development environment management system may update the history information database for efficient storage space management as described above.

Specifically, the development environment management system may perform update of the history information database when the index of the history information database reaches a preset index.

For example, the development environment management system may divide the entire index of the history information database into three sections in ascending order.

The development environment management system may unconditionally delete history information corresponding to a section including the lowest index among the three sections. The history information corresponding to the section may be considered to have elapsed a long time since the creation / modification date, and since the history information is unlikely to be referenced again, it may be deleted without conditions.

The development environment management system may update the history information corresponding to the middle of three sections by determining whether to delete or maintain the information according to the type of software component. That is, the development environment management system can classify the importance according to the type of software component, and keep only the history information corresponding to the type of software component having the highest importance among the history information corresponding to the middle section among the three sections, and the remaining history. The history information database can be updated by deleting all the information.

Alternatively, the development environment management system may update the history information corresponding to the middle section among the three sections by determining whether to delete or maintain the information according to the frequency of creation / modification of the software component. That is, the history information database may be updated by deleting all the history information whose generation / modification frequency is higher than the preset reference frequency among the history information corresponding to the middle section among the three sections and maintaining the remaining history information.

Alternatively, the development environment management system may update the history information corresponding to the middle section among the three sections by determining whether to delete or maintain the information according to the authority information of the development system. That is, the history information, which is the authority adjustment authority that can adjust the authority information of which the authority information is regarded as the highest authority information among the history information corresponding to the middle section of the three sections, is kept intact, and all remaining history information is deleted. The history information database can be updated.

The development environment management system may maintain the history information corresponding to the section including the highest index among the three sections. The history information corresponding to the section may be regarded as the date of creation / modification is relatively recent, and thus the history information may be maintained as it is highly likely to be referred to again.

Some of the configurations of the management server 200 having the configuration as described above may be implemented by artificial intelligence, and may further include a decision reason presentation module (not shown in the drawings for convenience of description).

The decision reason presentation module not only categorizes and predicts the data given or input by the user, but also analyzes the causality of the decision to find the appropriate basis for the reason why the result is presented by AI. The reason can be explained at the user level. The decision reasoning module enables reliable decision making between the user and AI, so that feedback from the user can be appropriately reflected in case of problems or errors. In addition, by providing a decision reason module, it is possible to solve the distrust that a user may have in artificial intelligence because the reason for the result of the artificial intelligence cannot be clearly explained. In this way, the overfitting problem that the optimal solution in the region can be selected, rather than the overall solution, can be prevented.

In one embodiment, the decision reason presentation module may further include a model building module and a reason explanation interface module. The model building module may be implemented as an in-depth explanatory learning module, an interpretable model generation module, and a model induction module.

The deep description learning module is a modified deep learning technique that allows the deep neural network to learn descriptive features. You can train nodes in the hidden layer to represent meaningful attributes, for example, if you are learning a model that distinguishes the image of the arms and legs, then each hidden node is a fingernail or toenail, a finger or toe, a palm or sole. By learning to show the location, etc., when the model determines that an image is a hand, the active hidden node can provide the basis for the decision. The basis of this determination may be expressed verbally through a natural language generation model such as RNN (Recurrent Neural Network). RNN is a model of deep learning, which is a kind of artificial neural network, for learning data that changes with time, such as time series data, and using input control vector, forgetting vector, and output control vector to input and output data. Get In the input control vector, the input signal receives the value after passing through the connection layer with the activation function, and the forgetting vector reflects a part of the past input to the current input. The output adjustment vector takes in the values using the activation function taking into account the past values and the modified input values. The final result is then returned to input. The circulatory neural network is mainly used for classifying document emotions or recognizing handwritten text, and can also be mainly used for speech recognition, time series prediction, or waveform generation. This is because the input data can be processed in a proper order even if the input data has a fixed shape without an order.

Also, in an embodiment, the in-depth learning module may visually display a part based on the image. For example, if the AI system classifies a cat image, the existing system derives only the cat whether the input image is a cat, but the in-depth learning module derives whether the cat is a cat and uses the basis (hair, beard, etc.) of the image. Can be provided to

The interpretable model generation module can construct structured data into an interpretable causal model. According to an embodiment of the present disclosure, an interpretable model generation module may be constructed using Bayesian program learning (BPL), and BPL is a method of learning to express a combination of small pieces, for example, learning a model that generates letters. When you do this, divide the letters into strokes to create the most reasonable combination of strokes. BPL can mimic a human being without a large amount of data, and it is an evolution of the Neural Network that can change the probability value based on a new event given. In other words, the BPL not only changes the weights of the virtual variables, but also includes creating another virtual variable in the middle. Given a new environment, understanding the phenomena in a different way, for example, toss a coin 100 times and face the front 60 times and the back 40 times to get a 60% chance of coming out, then the next time the back comes out. The probability of heading out is reduced to 59.4%.

In addition, in one embodiment, the interpretable model generation module may be implemented through a probabilistic approach. The probabilistic approach can be a learning effect with just a few samples, for example showing a long chair and a short chair to learn that there are also middle chairs. In other words, it is a technique of learning by filling out the insufficient data by itself. According to an embodiment, the probabilistic approach may include a function of correcting probabilities and programs by mathematical calculations.

Also, in one embodiment, the interpretable model generation module may be implemented using And-Or-Graph. And-Or-Graph is a graph showing the condition and conclusion of rule and AND / OR relationship in the form of graph. And-Or-Graph is structured intermediate and final data derived from artificial intelligence to logically determine the model decision process. There is an advantage that is easy to explain. That is, the graph is represented by an AND node and an OR node. Both AND nodes must be processed and only one OR node can be finished. By using the AND / OR graph, you can see a set of rules interspersed with each other as a structure and easily grasp the logical relationship between each sentence.

The model induction module can infer any black box model into a descriptive model. In one embodiment, the model induction module can be implemented with local interpretable model-agnostic explanations (LIME), which make the arbitrary black box model locally descriptive through sparse linear coupling around already descriptive data. Can be. For example, if a black box model that categorizes an image determines that an image is a heart, it is a description of the other model's heart that can already be described, that is, what part of the image is determined by comparing the pixels representing the heart with a given image. Can present

In addition, in one embodiment, the model induction module may be implemented as Bayesian rule lists (BRLs) that express the model as a series of if-then conditional statements. BRL breaks down high-dimensional, multivariate feature spaces into simple, already interpretable conditional statements to help understand complex models.

The above-described in-depth learning module, an interpretable model generation module, and a model induction module may operate independently of each other or in combination with each other, and their implementation order may also vary according to embodiments.

Next, the reason explanation interface module may express the description of the AI decision in a manner that can be understood by the user. Reason description The interface module may include necessary descriptions such as repeated descriptions, all necessary descriptions, no unnecessary descriptions, and appropriate amounts. That is, the user can easily provide the user with the language, tables, images, graphs, formulas, and the like, which process and the reason that the artificial intelligence has obtained the final result, and what factors or data influenced each step. .

Also, the reason explanation interface module may receive a correction command of the user. To this end, the reason description interface module may include correctability as essential items such that the description is flexible, respects the user's feedback, and observes the gradual change. The user can evaluate and develop the effect of the reason explanation interface module by receiving feedback about the clarity and utilization of the explanation.

In another embodiment, the decision reason presentation module may be formed of a causal model. The causal model may be formed to combine deep learning and Markov random fields. First, the probability distribution of the deep Markov random field model is modeled from the training data, and the structure of the Markov random field representing conditional independence between the random variables is studied. By inferring the latent function of the structured Markov random field into a deep neural network, it is possible to alleviate the problem of exponentially increasing the number of parameters required for the latent function as the number of input variables increases. Can learn associations According to an exemplary embodiment, the class classification problem may be learned like an auxiliary task, an attribute, and a super category, and then linearly combined at the output stage to enable an effective expression. It can also include interactive learning algorithms that allow a person to confirm that the causal relationship has been learned correctly and to provide feedback and make corrections.

In another embodiment, the decision reason presentation module may be implemented as an analysis module. As a technique for regressing a time series function into a multivariate Gaussian based on various kernels, we can learn the optimal kernel combinations representing the kernels in Gaussian processes and explain the given time series data based on the kernel combinations found above. Furthermore, a combination of a kernel that is expressed in common even when there is a plurality of time series data and a kernel that expresses characteristics of each time series data may be learned to describe characteristics common to a plurality of time series data. By writing the kernel combinations found through the time series data analysis model in natural language, the user can explain the process of deriving the decision made by artificial intelligence and the reason for it in natural language.

Through the module of presenting the decision reason, it is possible to visualize and textify the AI decision-making process from the user's point of view, to explain the components involved in the decision-making process, and to analyze the causes of the correlation between complex models. Can be explained by dividing into elements and result elements. In particular, it is written in the form of automatic reports that can be easily understood by the user, so that the artificial intelligence can interact with humans more precisely by providing the reason as well as the result of analyzing the data.

Such a technique for providing a method for embedding a biological image watermark and a method for extracting a biological image watermark may be implemented in an application form or in the form of program instructions that may be executed through various computer components to be recorded on a computer-readable recording medium. Can be. The computer-readable recording medium may include program instructions, data files, data structures, etc. alone or in combination.

The program instructions recorded on the computer-readable recording medium are those specially designed and configured for the present invention, and may be known and available to those skilled in the computer software arts.

Examples of computer-readable recording media include magnetic media such as hard disks, floppy disks, and magnetic tape, optical recording media such as CD-ROMs, DVDs, and magneto-optical media such as floptical disks. media), and hardware devices specifically configured to store and execute program instructions, such as ROM, RAM, flash memory, and the like.

Examples of program instructions include not only machine code generated by a compiler, but also high-level language code that can be executed by a computer using an interpreter or the like. The hardware device may be configured to operate as one or more software modules to perform the process according to the invention, and vice versa.

The management server 200 may manage a web page for integrated management of various tasks performed through a communication network such as system engineering (SE), supervision, customer management, construction work, quality control, and the like.

As such, the management server 200 displays a document, statistical data, analysis information, and the like, on a web page interworking with the internal network, by the terminal 100, which is requested from the terminal 100 connected through the internal network. Through) can be provided with integrated enterprise resources associated with the operating device (300).

Here, the management server 200 may set a security security program for the security of the electronic file to the uploaded electronic file. Detailed information related to this will be described later.

In this process, the management server 200 may set a security program in the electronic file to improve the security of the web page.

The electronic file uploaded and stored in the management server 200 or downloaded from the management server 200 may be distributed through various paths, where the electronic file is distributed to copy, transmit, send, forward, and print the electronic file. It can be defined as including any one of the processes.

At this time, the management server 200 may set the security program according to the present invention in the electronic file managed through the web page.

That is, the management server 200 sets a reading restriction condition for restricting the reading of the corresponding electronic file of the electronic file, and if the preset reading constraint is satisfied, the management server 200 modulates the code of the corresponding electronic file to check what the electronic file was. You can set up a security program to disable it.

Here, the read restriction condition may include at least one condition of the cumulative reading count, the cumulative output count, the cumulative transmission count, the viewable time limit and the destination limit of the electronic file. The management server 200 may set the viewing constraints in various ways.

For example, the management server 200 may directly receive a viewing constraint from a user. As another example, the management server 200 may automatically generate a read restriction condition based on the feature information of the electronic file input from the user. That is, the management server 200 may receive feature information on the type, importance, creation date, destination, and the like of the electronic file from the user, and automatically set a viewing restriction on the electronic file.

In this case, the management server 200 may automatically set the viewing constraints by further considering the viewing constraint setting history. The management server 200 may analyze the history of the viewing constraints set according to the feature information input from the user, and set the conditions of the viewing constraints currently set.

Thereafter, the management server 200 may set a security program according to the viewing constraints in the electronic file.

The management server 200 may set a security program to check whether the viewing restriction condition is satisfied according to the history information recorded in the process of using the electronic file. For example, when the reading constraint is a threshold limiting at least one of the cumulative reading count or the cumulative output count, the management server 200 may include at least one of the cumulative reading count or the cumulative output count recorded in the process of using the electronic file. You can set up your security program to check whether the server meets the thresholds for viewing constraints.

The management server 200 may set a security program to modulate the code of the electronic file when the viewing constraint is satisfied according to the history information of the electronic file. In detail, the management server 200 may set a security program such that the code of the electronic file is modulated (encoded) by using any one encoding method arbitrarily selected from among a security program or a plurality of file conversion encoding methods preset in the electronic file. have. Since the electronic file in which the code is modulated cannot be read, the electronic file can have the same effect as the destruction of the electronic file, and the confidentiality of the electronic file can be maintained by setting to demodulate (decode) only under limited conditions.

The security program can check whether the expiration date has been reached in a variety of ways. For example, the security program may measure an elapsed time from the creation date of the electronic file through a timer function that may measure the elapsed time. Accordingly, the security program can check whether the elapsed time has reached a predetermined viewing time limit. Alternatively, the security program may be programmed to periodically collect the current time from the electronic device storing the electronic file.

The security program may determine whether to tamper with the code of the electronic file when it is determined that the viewable time limit is reached according to the read restriction condition. That is, the management server 200 does not set the security program to destroy the electronic file unconditionally when the available period of access arrives, but the security program to modulate or unmodify the code of the electronic file according to the situation. Can be set.

To this end, the security program analyzes the history information recording the usage process of the electronic file, and the electronic device (terminal 100) that currently stores the electronic file has a history of viewing the electronic file within the available time limit according to the viewing constraints. You can check whether it exists.

In detail, the management server 200 may set a security program to analyze the history information accumulated and accumulated in the process of using the electronic file, and to check in which electronic device the electronic file is currently stored. At this time, since the history information is accumulated and stored not only the cumulative reading frequency and cumulative distribution number of the electronic file, but also the identification information of the electronic device that reads or distributes the electronic file, the security program can check the current storage location of the electronic file. Do.

If the security program confirms that there is a history of viewing the electronic file within the available time limit according to the viewing constraint on the electronic device, the code of the electronic file is unmodified so that the electronic file is always viewed regardless of the viewing constraint. You can.

On the other hand, if it is determined that the history of viewing the electronic file does not exist within the available period of viewing in the corresponding electronic device, the security program may alter the code of the electronic file. Specific examples according to the above-described processes are as follows.

If the viewable time limit set for the specific document file is 7 days, the security program set for the electronic file by the management server 200 may check whether one week has elapsed from the first generation date or the first distribution date of the electronic file. The security program may collect identification information of the electronic device which finally stores the document file at a time point that passes one week. If it is confirmed that the security program has a history of viewing the electronic file in the corresponding electronic device, the electronic device may not tamper with the code so that the electronic file can be viewed permanently. On the other hand, if there is no history of viewing the electronic file in the corresponding electronic device, the reading of the file may be restricted by modulating the code of the electronic file.

In addition, since the security program is set in the electronic file in the form of programming code, even if the electronic file is copied, the two electronic files that are duplicated may be set to independent security programs. For example, when the first electronic file and the second electronic file are generated by copying the electronic file from the first electronic device, and the second electronic file is transmitted from the first electronic device to the second electronic device, the same electronic file is stored. It can be stored in two electronic devices. In this case, the first electronic device may not read the electronic file within the viewable period according to the read restriction condition, and the second electronic device may view the electronic file within the viewable period. In this case, the first electronic file stored in the first electronic device may be restricted from being read because the code is modulated, while the second electronic file stored in the second electronic device may be maintained in a continuously viewable state.

On the other hand, the management server 200 may set a security program to activate or deactivate the viewing constraints set in the electronic file. In detail, the management server 200 may deactivate the viewing constraint until the electronic file is first distributed, and set the security program to activate the viewing constraint at the time when the electronic file is first distributed. That is, the electronic file generated by the management server 200 may be controlled to be continuously read regardless of the available time limit when it is not distributed to the terminal 100. In addition, the management server 200 may analyze the history information and set a security program to activate the viewable time limit according to the read restriction condition when it is confirmed that the corresponding electronic file is first distributed.

The management server 200 according to another embodiment may set a security program to restrict the reading of the electronic file according to the destination according to the viewing constraint. At this time, the read constraint may include information on the intermediate destination or the final destination of the electronic file. The information on the destination may be identification information of the electronic device that can receive and view the electronic file. In addition, the identification information may include any one of an IP address or a MAC address.

If the security program set by the management server 200 confirms that the electronic file is distributed, it may compare the identification information of the electronic device to which the electronic file is distributed with the identification information of the destination according to a read restriction condition.

When the identification information of the distributed device is the same as the identification information of the destination, the security program may unmodulate the code of the electronic file.

The security program can be programmed to alter the code of the electronic file if the identification of the distributed device is different from the identification of the destination. This means that the electronic file created by the document creator is transmitted to a device different from the intended destination, and when the electronic device is read from the electronic device different from the original destination, important information such as personal information may be leaked. have. Therefore, the management server 200 may set a security program to immediately tamper with the code of the electronic file when it is determined that the electronic device distributed of the electronic file and the destination according to the read restriction condition are different.

On the other hand, in some cases, a situation may arise where the modulated electronic file needs to be restored. For example, the electronic file may not be immediately transmitted to the electronic device set as the destination, but may be distributed to the electronic device set as the destination while being viewed by another electronic device. In this case, when the electronic file is requested to be read by another electronic device, the code of the electronic file is modulated as described above. Can be solved. However, when the electronic file whose code is modulated is distributed to the terminal 100 set as a destination, there is a problem that the electronic file cannot be read even in the terminal 100.

In order to prevent the above-mentioned problem, the management server 200 according to the present invention, if the identification information of the electronic device requesting to view the electronic file is modulated code is confirmed to be the same as the identification information of the destination according to the read constraint, The security program may be set to check whether the code of the electronic file has been tampered with (53). At this time, if it is confirmed that the code has been tampered with, the security program may be set to restore the electronic file in which the code has been tampered with. In this case, the security program may restore the modulated code by using a symmetric key corresponding to the encoding method used for the modulation of the electronic file.

In some other embodiments, the security program may be programmed to determine whether the code has been tampered with according to the communication capability of the terminal 100 in which the electronic file has been distributed.

For example, when the identification information consists only of an IP address or when the IP address and the MAC assistant are combined, the process of checking the identification information on the destination is a function that can be used only when a network such as the Internet is activated. . In this case, when a specific user distributes the electronic file after blocking the Internet for malicious purposes, the security program set in the electronic file may not be able to check the identification information of the destination and may not be able to tamper with the code. .

In order to prevent such a phenomenon, the management server 200 may set a security program to check whether the electronic device that the electronic file is distributed can communicate. For example, the security program may be programmed to call an API including a function composed of a programming language such as C language to determine whether the current electronic device is in a state where external devices can communicate. Alternatively, the security program may be programmed to periodically check the IP address of the electronic device and determine that the communication is blocked when the IP address is not confirmed. In addition, the security program can check whether communication is possible using any one of various methods known in the art.

At this time, the management server 200 is confirmed that the electronic device is blocked communication, such as the Internet, and if the electronic device is viewed or requested to view or output the electronic file, regardless of whether or not to meet the viewing constraints A security program can be set up to tamper with the code in the electronic file. Accordingly, when an electronic file is attempted to be read by an electronic device having no network setting, the reading may be blocked at source.

Although the above has been described with reference to the embodiments, those skilled in the art will understand that various modifications and changes can be made without departing from the spirit and scope of the invention as set forth in the claims below. Could be.

1000, 2000: sensing system
100: terminal
200: management server
300: operating device

Claims (2)

It includes at least one of a sensor module, a memory module, a light emitting module, a power module, a memory module, an interface module, a display module, an alarm module, a heating module, a sterilization module, a communication module, and a driving module, and transmits and receives signals related to status and control. Including an operating device,
A terminal for receiving the signal output from the operating device and transmitting a first control signal to the operating device in response to the received signal; and
Further comprising a management server for displaying a processing result according to the task requested through the terminal on a web page linked with the communication network,
The operating device receives a response to the signal from the terminal, detects a user's approach of the terminal based on the received response, and generates a second control signal for operating the operating device based on a detection result. Sensing module; A device control module configured to operate the operating device according to the received first control signal and the second control signal; And the sensor module, the memory module, the light emitting module, the power module, the memory module, the interface module, the display module, the alarm module, the heating module, the sterilization module, and the like controlled by the device control module. At least one of the communication module and the drive module,
The terminal, the terminal communication module for receiving the signal output from the operating device; And a terminal control module outputting the first control signal including identification information of the terminal in response to the received signal.
The management server, when the terminal or the operating device accesses the web page through the communication network, so that the user of the terminal or the operating device through the web page can perform all the tasks related to the operation of the operating device through the web page. The web page controls the system engineering tab, construction work tab, quality control tab, common task tab, customer management tab, data center tab, community tab, electronic payment processing status tab and control tab of the operation device.
The management server sets a viewing restriction condition in the use process of the electronic file included in the web page, checks whether the viewing restriction condition is satisfied according to the history information recorded in the use process of the electronic file, When a read restriction condition is satisfied, a security program is set to modulate the code of the electronic file, and the security program is set to periodically check whether the terminal requesting the electronic file can be communicated. When it is determined that the communication of the terminal requesting the communication is blocked, and the terminal determines that the reading or output of the electronic file is requested, the terminal may modulate the code of the electronic file regardless of whether the reading restriction condition is satisfied. Set the security program,
The management server generates a data sheet for statistical data and displays the data sheet on the first area of the web page, and selects a variable name selected by the user based on a selection signal for a predetermined area of the data sheet received from the terminal. And generate a dynamic graph based on the variables corresponding to the selected at least one variable name, and display the dynamic graph on the second area of the web page, and for printing or storing the dynamic graph displayed on the second area, Move the graph to the third area of the webpage and display it.
The generating of the dynamic graph automatically classifies the name of the dynamic graph and the types of variables for the horizontal and vertical axes of the graph according to the order of selection signals sequentially input, and for the variables belonging to the selected variable name. Generating a dynamic graph for each group, and displaying graphic information on the dynamic graph indicating statistical meaning of the dynamic graph,
The graphic information is generated in different types according to the type of the generated dynamic graph, and the graphic information includes at least one of information on average, standard distribution, frequency, regression line, and frequency distribution polygon.
Based on the selection signal for the graph type selection region displayed in the fourth region of the webpage, the dynamic graph of the first form is converted into the dynamic graph of the second form for the same variable name and converted into the second region of the webpage. Display,
The operating device is formed of a thickness measuring device including the device control module and the sensor module, the sensor module is provided to face each other includes an upper sensor and a lower sensor for measuring the thickness of the specimen located between, the apparatus The control module corresponds to a spot center point of light output for distance measurement from the upper sensor and the lower sensor, respectively, and the upper sensor and the lower sensor may overlap measurement ranges of the upper sensor and the lower sensor, respectively. To control the position of the sensor,
The device control module transmits and receives information with the terminal, controls to output light from the upper sensor to the lower sensor, and controls a predetermined driving module to move the lower sensor from the upper sensor to the lower sensor. And a position of the lower sensor by monitoring a spectral view of the output light.
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