KR20220115160A - System and method of control- variable synchronization based on ai for smart systems - Google Patents

Abstract

The present invention relates to a system and a method for synchronizing control variables based on artificial intelligence for a smart system. More specifically, in accordance with one embodiment of the present invention, the system for synchronizing control variables based on artificial intelligence for a smart system, includes: a user terminal generating a first control variable; a master system operated by the first control variable, while generating first internal environment information corresponding to an internal environment factor of the master system based on the first control variable; a mediation server generating a second control variable to be delivered to a slave system based on the first control variable and the first internal environment information; and at least one slave system operated by the second control variable. Therefore, the present invention is capable of embodying the same environment with one single control variable.

Description

SYSTEM AND METHOD OF CONTROL-VARIABLE SYNCHRONIZATION BASED ON AI FOR SMART SYSTEMS

The present invention relates to an artificial intelligence-based control variable synchronization system and method for a smart system. More particularly, it relates to a control variable synchronization system and method capable of simultaneously managing a master system and a slave system with one control signal input by a user.

Unless otherwise indicated herein, the material described in this section is not prior art to the claims of this application, and inclusion in this section is not an admission that it is prior art.

Due to its nature, agriculture is inevitably affected by climate and natural environment. Recently, smart farms that can produce agricultural products while artificially controlling cultivation conditions regardless of the environment such as seasons, wind and flood damage are receiving a lot of attention at home and abroad. .

Smart farm, which is an intelligent farm created by grafting information and communication technology (ICT) to agricultural technology, uses Internet of Things (IoT) technology to control the temperature, humidity, sunlight, carbon dioxide and soil of crop cultivation facilities. It measures and analyzes, and drives the control device according to the analysis result to change to an appropriate state.

In addition, remote management is possible through a mobile device such as a smartphone. Smart farms can create high added values such as productivity, efficiency, and quality improvement throughout the agricultural production, distribution, and consumption processes.

However, when the smart farm is located in several places, there is a problem in that the user must directly visit each place and control so that the characteristics of each place are reflected.

Accordingly, Patent Publication No. 10-2020-0057831 discloses a smart farm control system.

In more detail, the prior art is equipped with a facility device including a light blocking device, a water supply device, a ventilation device, a temperature control device, a humidity control device, an oxygen concentration control device and a nutrient solution supply device, and cultivates crops in an enclosed space. a monitoring device for transmitting time schedule information for controlling the facility device so that a crop environment is created by time to cultivate the crop, and the facility for each time according to the time schedule information transmitted from the monitoring device An IOT control device for operating the device, wherein the IOT control device is configured to, when the internal temperature value of the crop cultivation facility does not fall within a set reference time temperature range, between the external temperature value of the crop cultivation facility and the internal temperature value Calculate a first deviation value and a second deviation value between the internal temperature value and the reference time temperature range, determine whether to ventilate the crop cultivation facility based on the first deviation value, and calculate the second deviation value Disclosed is a smart farm control system that resets the operating time of the facility device included in the time schedule information based on the time schedule information to operate the facility device.

Unexamined Patent Publication No. 10-2020-0057831

The disclosed embodiment is to simultaneously control a plurality of smart systems.

In addition, the disclosed embodiment implements the same environment with one control variable by introducing the concept of a master and a slave to a plurality of smart systems.

The technical problems to be achieved in the present invention are not limited to the technical problems mentioned above, and other technical problems not mentioned will be clearly understood by those of ordinary skill in the art to which the present invention belongs from the description below. will be able

In order to achieve the above object, an artificial intelligence-based control variable synchronization system for a smart system according to an embodiment of the present invention operates by a user terminal generating a first control variable and the first control variable, The master system for generating first internal environment information corresponding to the internal environment factor of the master system based on the first control variable, the first control variable and the second control variable to be transmitted to the slave system based on the first internal environment information It may include an intermediary server for generating and one or more slave systems operating according to the second control variable.

In this case, the master system includes a first internal environment adjusting unit for adjusting the internal environment factor of the master system based on the first control variable, a first internal sensor unit generating the first internal environment information, and the master system and a first external sensor unit generating first external environment information corresponding to an external environmental factor of , a second internal sensor unit generating second internal environment information corresponding to the internal environmental factor of the slave system and a second external sensor unit generating second external environmental information corresponding to the external environmental factor of the slave system can

In this case, the first internal environment control unit and the second internal environment control unit may control at least one of humidity, temperature, light intensity, PH of the soil, UV (ultraviolet rays), and carbon dioxide amount.

In this case, the first internal environment information and the second internal environment information may include information about at least one of humidity, temperature, light intensity, soil PH, UV (ultraviolet rays) and carbon dioxide amount inside each system. have.

At this time, the mediation server, a first machine learning model for calculating a first correlation between the first control variable and the first external environment information and the first internal environment information, and the first correlation and the first 2 It may include an artificial intelligence module for generating a second machine learning model that calculates the second control variable by inputting external environment information.

In addition, in order to achieve the above object, an artificial intelligence-based control variable synchronization method for a smart system according to an embodiment of the present invention comprises the steps of receiving a first control variable from a user terminal, based on the first control variable receiving first internal environment information corresponding to an internal environment factor of an operating master system; generating a second control variable based on the first control variable and the first internal environment information; and the second control variable may include the step of transmitting to one or more slave systems.

At this time, the artificial intelligence-based control variable synchronization method for a smart system according to an embodiment of the present invention includes the steps of receiving first external environment information corresponding to the external environmental factor of the master system and the internal environment of the slave system The method may further include receiving second internal environment information corresponding to the factor and second external environment information corresponding to the external environment factor of the slave system.

In this case, the generating of the second control variable may include calculating a first correlation between the first control variable and the first external environment information and the first internal environment information through an artificial intelligence module; and calculating the second control variable by inputting the first correlation and the second external environment information through an intelligent module.

According to the disclosed embodiment, it is possible to simultaneously control a plurality of smart systems.

In addition, according to the disclosed embodiment, the same environment can be implemented with one control variable by introducing the concept of a master and a slave to a plurality of smart systems.

The effects obtainable in the present invention are not limited to the above-mentioned effects, and other effects not mentioned may be clearly understood by those of ordinary skill in the art from the following description. will be.

Other aspects, features and benefits as described above of certain preferred embodiments of the present invention will become more apparent from the following description taken in conjunction with the accompanying drawings.
1 is a block diagram of an artificial intelligence-based control variable synchronization system for a smart system according to an embodiment of the present invention.
2 is an exemplary diagram of a master system or a slave system according to an embodiment of the present invention.
3 is a view showing a master system and a slave system operating with the same control variable according to an embodiment of the present invention.
4 is an exemplary diagram of generating a second control variable through an artificial intelligence module according to an embodiment of the present invention;
5 is a flowchart of an artificial intelligence-based control variable synchronization method for a smart system according to an embodiment of the present invention.
It should be noted that throughout the drawings, like reference numerals are used to denote the same or similar elements, features, and structures.

Advantages and features of the present invention, and a method of achieving them will become apparent with reference to the embodiments described below in detail in conjunction with the accompanying drawings. However, the present invention is not limited to the embodiments disclosed below, but may be implemented in a variety of different forms, and only these embodiments allow the disclosure of the present invention to be complete, and common knowledge in the art to which the present invention pertains. It is provided to fully inform the possessor of the scope of the invention, and the present invention is only defined by the scope of the claims. Like reference numerals refer to like elements throughout.

In describing the embodiments of the present invention, if it is determined that a detailed description of a well-known function or configuration may unnecessarily obscure the gist of the present invention, the detailed description thereof will be omitted. In addition, the terms described below are terms defined in consideration of functions in an embodiment of the present invention, which may vary according to intentions or customs of users and operators. Therefore, the definition should be made based on the content throughout this specification.

At this time, it will be understood that each block of the flowchart diagrams and combinations of the flowchart diagrams may be performed by computer program instructions. These computer program instructions may be embodied in a processor of a general purpose computer, special purpose computer, or other programmable data processing equipment, such that the instructions performed by the processor of the computer or other programmable data processing equipment are not described in the flowchart block(s). It creates a means to perform functions. These computer program instructions may also be stored in a computer-usable or computer-readable memory that may direct a computer or other programmable data processing equipment to implement a function in a particular manner, and thus the computer-usable or computer-readable memory. It is also possible for the instructions stored in the flowchart block(s) to produce an article of manufacture containing instruction means for performing the function described in the flowchart block(s). The computer program instructions may also be mounted on a computer or other programmable data processing equipment, such that a series of operational steps are performed on the computer or other programmable data processing equipment to create a computer-executed process to create a computer or other programmable data processing equipment. It is also possible that instructions for performing the processing equipment provide steps for performing the functions described in the flowchart block(s).

Additionally, each block may represent a module, segment, or portion of code that includes one or more executable instructions for executing specified logical function(s). It should also be noted that in some alternative implementations it is also possible for the functions recited in the blocks to occur out of order. For example, it is possible that two blocks shown in succession are actually performed substantially simultaneously, or that the blocks are sometimes performed in the reverse order according to the corresponding function.

In this case, the term '~ unit' used in this embodiment means software or hardware components such as field-programmable gate array (FPGA) or ASIC (Application Specific Integrated Circuit), and '~ unit' refers to what role carry out the However, '-part' is not limited to software or hardware. '~unit' may be configured to reside on an addressable storage medium or may be configured to refresh one or more processors. Thus, as an example, '~' denotes components such as software components, object-oriented software components, class components, and task components, and processes, functions, properties, and procedures. , subroutines, segments of program code, drivers, firmware, microcode, circuitry, data, databases, data structures, tables, arrays, and variables. The functions provided in the components and '~ units' may be combined into a smaller number of components and '~ units' or further separated into additional components and '~ units'. In addition, components and '~ units' may be implemented to play one or more CPUs in a device or secure multimedia card.

In describing embodiments of the present invention in detail, an example of a specific system will be the main subject, but the main subject matter to be claimed in this specification is to extend the scope disclosed herein to other communication systems and services having a similar technical background. It can be applied within a range that does not deviate significantly, and this will be possible at the discretion of a person with technical knowledge skilled in the art.

Hereinafter, an artificial intelligence-based control variable synchronization system for a smart system according to an embodiment of the present invention will be described with reference to the accompanying drawings.

1 is a block diagram of an artificial intelligence-based control variable synchronization system for a smart system according to an embodiment of the present invention.

Referring to FIG. 1 , an artificial intelligence-based control variable synchronization system for a smart system according to an embodiment of the present invention includes a user terminal 120 that generates a first control variable 411 , and the first control variable 411 . ), the master system 130 that generates the first internal environment information 413 corresponding to the internal environment factor of the master system 130 based on the first control variable 411, the first control By the mediation server 110 and the second control variable 435 that generate the second control variable 435 to be transmitted to the slave system 140 based on the variable 411 and the first internal environment information 413 It may include one or more slave systems 140 that operate.

At this time, the master system 130 and the slave system 140 relate to smart systems such as smart factories, smart farms, and smart aqua, and refer to systems that can operate factories, agriculture, fisheries, etc. using smart facilities. can do. The master system 130 and the slave system 140 will be described later in more detail with reference to FIG. 2 .

According to the present invention, the control variable of the slave system 140 is changed by changing the control variable (the watt value of the electric heater, the fan horsepower value of the air conditioner, etc.) of the master system 130 (plant factory or smart factory, etc.) through the above-described configuration. It can also be synchronized and controlled.

In addition, through this, even when the technical expert instantaneously changes the control variable of the master system 130, the control variables of the slave system 140 are synchronized, and the internal environmental factors (luminance, PH, UV) of the master system 130 are synchronized. , carbon dioxide, temperature, humidity, etc.) and the internal environmental factors of the slave system 140 can be equally managed.

In more detail, an embodiment of the present invention uses the internal and external environmental factors and control variables of the master system 130 and the internal and external environmental factors of the slave system 140 as inputs to optimize the It is possible to quickly synchronize the internal environmental factors of the slave system 140 with the internal environmental factors of the master system 130 by finding the control variables of the slave system 140 . In this regard, it will be described later in more detail with reference to FIG. 4 .

At this time, the user terminal 120 is a computer, a smart phone, a mobile phone, a smart TV, a set-top box (set-top box), a tablet PC, a digital camera, a camcorder, an e-book terminal, a digital broadcasting terminal, PDA (Personal Digital Assistants) , PMP (Portable Multimedia Player), navigation, MP3 player, wearable device, air conditioner, microwave oven, audio, DVD player, etc., including a microphone (MIC) and may include all devices capable of communication, where Computers may include laptop computers, desktops, and the like.

2 is an exemplary diagram of the master system 130 or the slave system 140 according to an embodiment of the present invention.

The master system 130 according to an embodiment of the present invention includes a first internal environment adjusting unit that adjusts the internal environmental factors of the master system 130 based on the first control variable 411, the first internal It may include a first internal sensor unit generating the environment information 413 and a first external sensor unit generating the first external environment information 415 corresponding to the external environment factor of the master system 130, the slave The system 140 includes a second internal environment adjusting unit that adjusts the internal environmental factors of the slave system 140 based on the second control variable 435 , and a second internal environment adjusting unit corresponding to the internal environmental factors of the slave system 140 . 2 It may include a second internal sensor unit generating the internal environment information and a second external sensor unit generating the second external environment information 431 corresponding to the external environment factor of the slave system 140 .

At this time, the first internal environment information 413 and the second internal environment information is information on at least one or more of humidity, temperature, light intensity, soil PH, UV (ultraviolet rays) and carbon dioxide amount inside each system. may include Alternatively, the first internal environment information 413 and the second internal environment information may be determined differently depending on the type of system operated by the master system 130 and the slave system 140 , that is, a factory, agriculture, fishery, etc. may be

For example, in the case of fishery, the first internal environment information 413 and the second internal environment information may include water temperature, dissolved oxygen amount, cleanliness, and the like.

In this case, the first internal environment control unit and the second internal environment control unit may be a device for controlling at least one of humidity, temperature, luminosity, soil PH, UV (ultraviolet rays), and carbon dioxide amount.

For example, when the first internal environment control unit and the second internal environment control unit are devices for controlling humidity, the humidity control device 204 shown in FIG. 2 may be a device for controlling temperature or carbon dioxide amount. In this case, it may be the air conditioner 203 shown in FIG.

In addition, although not shown in FIG. 2 , the first internal environment adjusting unit and the second internal environment adjusting unit may be a ceiling covering control device or a light bulb capable of adjusting the light intensity.

Alternatively, the first internal environment control unit and the second internal environment control unit may be devices for comprehensively controlling the humidity control device 204 , the air conditioner 203 , the light bulb, and the like.

In addition, the first internal sensor unit, the first external sensor unit, the second internal sensor unit, and the second external sensor unit are devices capable of measuring the environmental factors inside and outside the master system 130 and the slave system 140, as shown in FIG. Referring to 2, for example, it may be a temperature sensor 201, a humidity sensor 202, a land PH sensor 205, and the like, and may be an all-inclusive control device.

At this time, as described above, the sensors used may vary according to the types of the master system 130 and the slave system 140 .

3 is a diagram illustrating the master system 130 and the slave system 140 operating with the same control variable according to an embodiment of the present invention.

Referring to FIG. 3 , in a smart system generally composed of a plurality of systems, external environmental factors (weather, temperature, humidity, land PH, etc.) of the master system 130 and the slave system 140 are different from each other. , the same control variables as the internal environment information (temperature, humidity, land PH, light intensity, UV (ultraviolet rays) and carbon dioxide concentration, etc.) when the master system 130 is operated based on the control variables generated by the user terminal 120 The internal environment information when the slave system 140 is operated based on can be different from each other.

For example, if there is a difference in temperature among the external environmental factors between the master system 130 and the slave system 140 , even if the heater of the slave system 140 operates the same as the heater setting wattage of the master system 130 , It may be different from the temperature inside the master system 130 .

4 is an exemplary diagram of generating a second control variable 435 through the artificial intelligence module 300 according to an embodiment of the present invention.

Referring to FIG. 4 , the mediation server 110 calculates a first correlation 420 between the first control variable 411 and the first external environment information 415 and the first internal environment information 413 . A first machine learning model 310 and a second machine learning model 320 for calculating the second control variable 435 by inputting the first correlation 420 and the second external environment information 431 may include an artificial intelligence module 300 that generates

In this case, the second machine learning model 320 may also input the second internal environment information to calculate the second control variable 435 .

At this time, the artificial intelligence module 300 may perform learning so that an accurate correlation can be derived using a deep learning technique, which is a field of machine learning.

In addition, the artificial intelligence module 300 may calculate the weight of a plurality of inputs in the function through deep learning through learning. In addition, various models such as a Recurrent Neural Network (RNN), a Deep Neural Network (DNN), and a Dynamic Recurrent Neural Network (DRNN) may be used as an AI network model used for such learning.

Here, RNN is a deep learning technique that simultaneously considers current data and past data. A recurrent neural network (RNN) represents a neural network in which connections between units constituting an artificial neural network constitute a directed cycle. Furthermore, various methods may be used for a structure capable of constructing a recurrent neural network (RNN), for example, a fully recurrent network, a hopfield network, an Elman network, an ESN (Echo). State network), long short term memory network (LSTM), bi-directional RNN, continuous-time RNN (CTRNN), hierarchical RNN, and secondary RNN are representative examples. In addition, as a method for learning a recurrent neural network (RNN), methods such as gradient descent, Hessian Free Optimization, and Global Optimization Method may be used.

5 is a flowchart of an artificial intelligence-based control variable synchronization method for a smart system according to an embodiment of the present invention.

Referring to FIG. 5 , the artificial intelligence-based control variable synchronization method for a smart system according to an embodiment of the present invention may first receive a first control variable 411 from the user terminal 120 ( S501 ).

In addition, in the artificial intelligence-based control variable synchronization method for a smart system according to an embodiment of the present invention, the first control variable synchronization method corresponding to the internal environment factor of the master system 130 operating based on the first control variable 411 . The internal environment information 413 may be input (S503).

At this time, in the artificial intelligence-based control variable synchronization method for a smart system according to an embodiment of the present invention, the first external environment information 415 corresponding to the external environmental factor of the master system 130, the slave system ( The second internal environment information corresponding to the internal environmental factor of 140 and the second external environmental information 431 corresponding to the external environmental factor of the slave system 140 may be further received.

In addition, the artificial intelligence-based control variable synchronization method for a smart system according to an embodiment of the present invention includes a second control variable 435 based on the first control variable 411 and the first internal environment information 413 . ) can be generated (S505).

At this time, step S505 is a first correlation between the first control variable 411 and the first external environment information 415 and the first internal environment information 413 through the artificial intelligence module 300 ( 420), and by inputting the first correlation 420 and the second external environment information 431 through the artificial intelligence module 300, the second control variable 435 may be calculated.

In addition, the artificial intelligence-based control variable synchronization method for a smart system according to an embodiment of the present invention may transmit the second control variable 435 to one or more slave systems 140 (S507).

The artificial intelligence-based control variable synchronization method for a smart system according to an embodiment of the present invention can operate in the same manner as the artificial intelligence-based control variable synchronization system for the smart system, and overlapping contents are omitted. do.

Embodiments of the present invention disclosed in the present specification and drawings are merely provided for specific examples in order to easily explain the technical contents of the present invention and help the understanding of the present invention, and are not intended to limit the scope of the present invention. That is, it will be apparent to those of ordinary skill in the art to which the present invention pertains that other modifications can be implemented based on the technical spirit of the present invention. In addition, each of the above embodiments may be operated in combination with each other as needed.

In addition, the method for synchronizing control variables according to the present invention may be implemented in the form of a program command that can be executed through various computer means and recorded in a computer-readable medium.

As such, various embodiments of the present invention may be embodied as computer readable code on a computer readable recording medium in a particular aspect. A computer readable recording medium is any data storage device capable of storing data that can be read by a computer system. Examples of computer readable recording media include read only memory (ROM), random access memory (RAM), and compact disk-read only memory (CD-ROM). ), magnetic tapes, floppy disks, optical data storage devices, and carrier waves (such as data transmission over the Internet). The computer readable recording medium may also be distributed over network-connected computer systems, so that the computer readable code is stored and executed in a distributed manner. In addition, functional programs, codes, and code segments for achieving various embodiments of the present invention may be easily interpreted by programmers skilled in the field to which the present invention is applied.

In addition, it will be appreciated that the apparatus and method according to various embodiments of the present invention can be realized in the form of hardware, software, or a combination of hardware and software. Such software may contain, for example, a volatile or non-volatile storage device such as a ROM, or a memory such as, for example, RAM, a memory chip, device or integrated circuit, whether erasable or rewritable, or For example, the storage medium may be stored in an optically or magnetically recordable storage medium such as a compact disk (CD), DVD, magnetic disk or magnetic tape, and at the same time, a machine (eg, computer) readable storage medium. The method according to various embodiments of the present invention may be implemented by a computer or portable terminal including a control module and a memory, and such memory is configured to store a program or programs including instructions implementing embodiments of the present invention It can be seen that this is an example of a machine-readable storage medium suitable for

Accordingly, the present invention includes a program including code for implementing the apparatus or method described in the claims of the present specification, and a machine (computer, etc.) readable storage medium storing such a program. Further, such a program may be transmitted electronically over any medium, such as a communication signal transmitted over a wired or wireless connection, and the present invention suitably includes the equivalent thereof.

The embodiments of the present invention disclosed in the present specification and drawings are merely provided for specific examples to easily explain the technical contents of the present invention and help the understanding of the present invention, and are not intended to limit the scope of the present invention. In addition, the embodiments according to the present invention described above are merely exemplary, and it will be understood by those skilled in the art that various modifications and equivalent ranges of embodiments are possible therefrom. Accordingly, the true technical protection scope of the present invention should be defined by the following claims.

110: mediation server 120: user terminal
130: master system 140: slave system
201: temperature sensor 202: humidity sensor
203: air conditioning device 204: humidity control device
205: land PH sensor 300: artificial intelligence module
310: first machine learning model 320: second machine learning model
411: first control variable 413: first internal environment information
415: first external environment information 420: first correlation
431: second external environment information 435: second control variable

Claims (8)

a user terminal generating a first control variable;
a master system operating according to the first control variable and generating first internal environment information corresponding to an internal environment factor of the master system based on the first control variable;
a mediation server for generating a second control variable to be transmitted to a slave system based on the first control variable and the first internal environment information; and
one or more slave systems operating according to the second control variable; Artificial intelligence-based control variable synchronization system for smart systems that includes The method according to claim 1,
The master system is
a first internal environment adjusting unit for adjusting an internal environmental factor of the master system based on the first control variable;
a first internal sensor unit generating the first internal environment information; and
a first external sensor unit generating first external environmental information corresponding to the external environmental factor of the master system; including,
The slave system is
a second internal environment adjusting unit for adjusting an internal environmental factor of the slave system based on the second control variable;
a second internal sensor unit generating second internal environment information corresponding to the internal environmental factor of the slave system; and
and a second external sensor unit generating second external environmental information corresponding to the external environmental factors of the slave system. 3. The method according to claim 2,
The first internal environment adjusting unit and the second internal environment adjusting unit,
An artificial intelligence-based control variable synchronization system for a smart system, characterized in that it controls at least one of humidity, temperature, light intensity, soil PH, UV (ultraviolet rays), and carbon dioxide amount. 3. The method according to claim 2,
The first internal environment information and the second internal environment information,
Artificial intelligence-based control variable synchronization system for smart systems, characterized in that it includes information on at least one of humidity, temperature, light intensity, soil PH, UV (ultraviolet rays) and carbon dioxide amount inside each system. 3. The method according to claim 2,
The intermediary server,
A first machine learning model for calculating a first correlation between the first control variable and the first external environment information and the first internal environment information, and the first correlation and the second external environment information as inputs An artificial intelligence-based control variable synchronization system for a smart system, comprising an artificial intelligence module for generating a second machine learning model for calculating a second control variable. receiving a first control variable from a user terminal;
receiving first internal environment information corresponding to an internal environmental factor of the master system operating based on the first control variable;
generating a second control variable based on the first control variable and the first internal environment information; and
transmitting the second control variable to one or more slave systems; An artificial intelligence-based control variable synchronization method for a smart system comprising a. 7. The method of claim 6,
receiving first external environmental information corresponding to the external environmental factor of the master system; and
receiving second internal environmental information corresponding to the internal environmental factor of the slave system and second external environmental information corresponding to the external environmental factor of the slave system; Artificial intelligence-based control variable synchronization method for a smart system, characterized in that it further comprises. 8. The method of claim 7,
The step of generating the second control variable comprises:
calculating a first correlation between the first control variable and the first external environment information and the first internal environment information through an artificial intelligence module; and
calculating the second control variable by inputting the first correlation and the second external environment information through an artificial intelligence module; An artificial intelligence-based control variable synchronization method for a smart system, comprising:

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