KR101713625B1 - System for collecting and analyzing environment information data associated with regional industry and method thereof - Google Patents

Abstract

The present invention relates to a system and method for collecting and analyzing environmental information data related to a local industry, and more particularly, to a system and method for collecting and analyzing environmental information data associated with a local industry, comprising at least one data collection device for collecting and transmitting environmental information data, (OWL) ontology information data represented by a web ontology language (OWL) on the basis of the received environment information data received from the data collection device, (OWL) ontology information data together with environment-specific environment information data stored in the data storage device, converts the OWL ontology information data into an Extensible Markup Language (XML) document, A markup language (XML) document and a user query input through a user terminal And a data analysis server for semantically inferring and analyzing the generated sensor data ontology using the predetermined ontology reasoning engine and providing the result to the user terminal. It can be provided in various forms and it is possible to operate the local industry operator independently without the help of experts.

Description

[0001] SYSTEM AND METHOD FOR COLLECTING AND ANALYZING ENVIRONMENT INFORMATION DATA [0002]

The present invention relates to a system and method for automatically collecting and analyzing environmental information data using at least one data acquisition device having a plurality of sensors associated with the local industry.

Our local industry has achieved a lot of growth over the past few years, but its growth has slowed down due to changes in internal and external conditions. It has also been the result of a shortage of labor force due to aging, high weather costs due to complex weather patterns, There are many challenges.

To solve this problem, ICT (Information & Communication Technology) is applied to the local industry to expand new growth engines and create new value.

The ICT is a combination of information technology and communication technology. It is called 'information and communication technology.' It is a software technology that is used for information device management and information management, Production, processing, preservation, transmission, and utilization. In other words, ICT, which utilizes hardware, software, and communication technologies for automating computerized systems, is largely aimed at building an information society.

Such ICT can be classified into information strategy establishment, information management, information environment creation, system engineering, communication, system construction, system implementation, system evaluation, and audit technology. In addition, ICT is not only a computer and communication technology, but also a comprehensive meaning of all the technologies necessary for informatization.

Meanwhile, smart agriculture is becoming increasingly important as a way to solve the problems of rural population decline, labor shortage, decrease of agricultural land, frequent disasters due to weather changes, and information technology (IT) It is expected to become an important axis.

Recently, with the emergence of the Internet (IoT-Internet of Things), a technology that can provide additional value to users by connecting objects or devices to the Internet, (Such as wind direction, wind speed, temperature, humidity, solar radiation amount, rainfall amount, etc.) specific to the environment is becoming an important factor in the competitiveness of local industries.

Accordingly, there is an urgent need for a system for collecting environmental information data generated in the local industry and analyzing the collected environmental information data so that the environmental information data related to the local industry can be integrated and managed efficiently.

Korea Patent No. 10-0947594

SUMMARY OF THE INVENTION It is an object of the present invention to provide a method and apparatus for automatically collecting and transmitting environmental information data from at least one data collecting apparatus having a plurality of sensors associated with a local industry, In addition, it is possible to provide users with more meaningful information in various forms by semantically inferring and analyzing environmental information data through the semantic analysis and providing them to users. In addition, And a system and method for collecting and analyzing related environmental information data.

In order to accomplish the above object, a first aspect of the present invention provides a data collection system comprising: at least one data collection device for collecting and transmitting environment information data related to a local industry using a plurality of sensors; (OWL) ontology information data represented by a web ontology language (OWL) on the basis of the received environment information data received from the data collection device, A data storage device for storing the data; And the OWL ontology information data together with the sensor-specific environment information data stored in the data storage device, converts the OWL ontology information data into an Extensible Markup Language (XML) document, And generates a sensor data ontology using the user query input through the user terminal, semantically inferences and analyzes the generated sensor data ontology using a predetermined ontology inference engine, and provides the result to the user terminal And to provide a system for collecting and analyzing environmental information data associated with a local industry including a data analysis server.

Here, the data collection device may include a data collection module that includes a plurality of sensors, and collects environmental information signals associated with the local industry sensed by each sensor; A data conversion module for converting an environmental information analog signal sensed by each sensor of the data acquisition module to digital; A data transmission module for transmitting the digitized environmental information data from the data conversion module through a wireless communication method; And a control module for controlling the operation of each sensor so that environment information signals associated with the local industry are collected in real time through the data collection module and for controlling the operation of each sensor so that the digitized environmental information data is transmitted from the data conversion module to the data storage device in real- And a control module for controlling the operation of the control unit.

Preferably, the wireless communication method may be at least one of Wi-Fi communication, WiGig communication, Wibro communication, and WiMAX communication.

Preferably, the data acquisition module, the data conversion module, the data transmission module, and the control module may be mounted on an open source-based Arduino board.

The data conversion module may further include a data storage module for converting the environment information data transmitted from the data conversion module under the control of the control module into a database for each sensor.

Preferably, the environmental information data collected through the data collection device may be at least one of data of temperature, humidity, solar radiation, wind velocity, wind direction, soil moisture and salinity data.

Preferably, the data storage device further comprises: a sensor data DB for storing environmental information data transmitted from the data collection device in a DB for each sensor; An index DB consisting of a plurality of ontology DB tables for storing OWL ontology information data represented by a web ontology language (OWL) based on sensor-specific environment information data stored in the sensor data DB; And an ontology DB for selecting a domain through the index DB using a predetermined ontology editor and connecting the selected domain and the attribute information between classes to convert a domain ontology for each sensor data based product into a database (DB) can do.

Preferably, the plurality of ontology DB tables may comprise an OWLOntology table, an OWLResource table, a Namespace table, an OWLIndividual table, an RDFTriple table, an OWLRelation table, an OWLProperty table, an OWLPropertyRestriction table, and an OWLClassRestriction table.

Preferably, a unique identifier (ID) may be assigned to each instance of each concept applied to the index DB, and stored using the identifier (ID) when the concepts are mutually quoted.

Preferably, the uppermost class stored in the ontology DB is defined as a 'Product' class, and the lower class is defined as a 'Domain' class for classifying products produced through a local industry and a 'Descriptor' class for describing sensor data The 'Descriptor' class includes an 'Identifier' class indicating a unique number of the sensor data, a 'DataType' class indicating a type of sensor data, a 'Keyword' class indicating a search keyword, a 'Writer' The 'Context' class includes a 'Location' class that represents local information, a 'Spatio' class that represents spatial information, and a 'Temporal' class that represents time information. Lt; / RTI >

Preferably, the data analysis server receives OWL ontology information data together with environment-specific environment information data stored in the data storage device, parses the received OWL ontology information data, and classifies the data into classes, properties, and instances Extracting constraint conditions on the hierarchical information and properties, and converting hierarchical information on the extracted classes and properties into an extensible markup language (XML) document.

Preferably, the data analysis server stores an XML markup language (XML) document including hierarchical information of the OWL ontology information data in a separate first storage module, and stores the extracted remaining information in a separate second storage Module.

Preferably, the ontology reasoning engine used in the data analysis server may be an inference engine based on a semantic web.

Preferably, the data analysis server determines the degree of similarity and ranking of the product growth, the productivity of the product, and the production trend of the product, which are produced through the domestic industry and are semantically inferred and analyzed through the predetermined ontology inference engine And provide the result to the user terminal.

Preferably, the data analysis server may provide the user terminal with a result of semantically inferred and analyzed through the predetermined ontology reasoning engine in a visual form of at least one of a text, a chart, and a graph.

Preferably, the data analysis server may convert the semantically inferred and analyzed results through the predetermined ontology reasoning engine according to the operating system of the user terminal, and provide the converted result to the user terminal.

Preferably, the data analysis server can receive information on normal operation and normal collection of each sensor from the data collection device in real time and monitor the same.

Preferably, the data analysis server may provide a web-based monitoring service so that the user can extract, analyze, and query data in a desired form through the user terminal.

Preferably, the data analysis server receives weather information data of an area in which the data collection device is installed from a weather station weather information providing server connected through a communication network, stores the weather information in a database (DB), and stores weather information And the past and present sensor-based environmental information data stored in the data storage device, and provide the weather information required until the production completion time of the product to the user terminal.

Preferably, the native industry may be made up of at least one of agriculture, animal husbandry, and fisheries.

A second aspect of the present invention is a method for collecting and analyzing environmental information data associated with a local industry using a system comprising at least one data collection device having a plurality of sensors, a data storage device and a data analysis server, (a) collecting environmental information data related to a local industry sensed by each sensor through the data collection device and transmitting the collected environmental information data; (b) receiving the environment information data transmitted in the step (a) through the data storage device, converting the environment information data into a database (DB) for each sensor, storing the database, and displaying the database in a web ontology language (OWL) Storing OWL ontology information data in a database (DB); And (c) receiving OWL ontology information data together with environment-specific environment information data stored in the step (b) through the data analysis server and converting the OWL ontology information data into an Extensible Markup Language (XML) document; (d) generating a sensor data ontology using the extensible markup language (XML) document converted in step (c) and the user query input through the user terminal through the data analysis server; And (e) semantically inferring and analyzing the sensor data ontology generated in the step (d) using the pre-established ontology reasoning engine through the data analysis server and providing the result to the user terminal.

Advantageously, said step (a) comprises the steps of: (a-1) collecting environmental information signals associated with the local industry sensed from each sensor; (a-2) converting the environmental information analog signal sensed by each sensor in step (a-1) into digital; And (a-3) transmitting the environment information data digitized in the step (a-2) in real time in a wireless communication system.

Preferably, the wireless communication method may be at least one of Wi-Fi communication, WiGig communication, Wibro communication, and WiMAX communication.

Preferably, the data acquisition device may be mounted on an open source based Arduino board.

Preferably, after step (a-2), the step (a-2) further comprises the step of converting the environment information data digitized in step (a-2) into a database for each sensor and storing the data in a separate data storage module .

Preferably, the environmental information data collected in the step (a) may be at least one of data of temperature, humidity, radiation amount, wind speed, wind direction, soil moisture and salinity data.

Preferably, the step (b) includes the steps of: (b-1) storing environmental information data transmitted in the step (a) (b-2) storing OWL ontology information data represented by a web ontology language (OWL) in an index DB consisting of a plurality of ontology DB tables based on the sensor-specific environment information data stored in the step (b-2); And (b-3) selecting a domain through the index DB using a predetermined ontology editor, connecting the selected domain and attribute information between classes, and converting the domain ontology for each sensor data based product into a database .

Preferably, the plurality of ontology DB tables may comprise an OWLOntology table, an OWLResource table, a Namespace table, an OWLIndividual table, an RDFTriple table, an OWLRelation table, an OWLProperty table, an OWLPropertyRestriction table, and an OWLClassRestriction table.

Preferably, a unique identifier (ID) may be assigned to each instance of each concept applied to the index DB, and stored using the specified identifier (ID) when the concepts are mutually quoted.

Preferably, in the step (b-3), the uppermost class is defined as a 'Product' class, and the lower class includes a 'Domain' class for classifying products produced through the domestic industry and a 'Descriptor' A class 'DataType' indicating the type of sensor data, a class 'Keyword' indicating a search keyword, a class 'Writer' indicating an information owner, and a class 'Descriptor' And a 'Context' class for describing attributes of the class and sensor data in detail. The 'Context' class includes a 'Location' class indicating local information, a 'Spatio' class representing spatial information, Temporal 'class.

Preferably, in the step (c), the data analysis server receives the OWL ontology information data together with the sensor-specific environment information data stored in the step (b), parses the received OWL ontology information data, Property and instance information, constraints on hierarchical information and properties, and then transforms hierarchical information on the extracted classes and properties into an extensible markup language (XML) document.

Preferably, after step (c), an extensibility markup language (XML) document including hierarchical information of the OWL ontology information data is stored in a separate first storage module through the data analysis server, And storing the remaining information in a separate second storage module.

Preferably, in the step (e), the predetermined ontology reasoning engine may be a semantic web-based reasoning engine.

Preferably, in the step (e), the data analysis server analyzes the growth effect of the product produced through the domestic industry, the productivity of the product, and the quality of the product, which are semantically inferred and analyzed through the predetermined ontology reasoning engine The degree of similarity and ranking of the production trends can be analyzed and the result can be provided to the user terminal.

Preferably, in the step (e), the data analysis server analyzes the semantically inferred and analyzed results through the predetermined ontology reasoning engine as at least one of a text, a chart, and a graph, As shown in FIG.

Preferably, in the step (e), the data analysis server may convert the semantically inferred and analyzed results through the predetermined ontology reasoning engine according to the operating system of the user terminal, and provide the converted results to the corresponding user terminal .

Preferably, after step (a), information on normal operation and normal collection of each sensor is acquired and transmitted in real time through the data collection device, And receiving the information about the normal operation and the normal collection and monitoring it in real time.

Preferably, after the step (e), the data analysis server further includes a step of providing a web-based monitoring service so that the user can extract, analyze and inquire data in a desired form through the user terminal .

Preferably, after step (e), a step of receiving weather information data of an area where the data collection device is installed from a separate weather station weather information providing server through the data analysis server, converting the weather information data into a database (DB) , Comparing weather information of the stored local area with past and current environmental information data of each sensor stored in the step (b) through the data analysis server and providing the weather information required until the production completion time of the product to the user terminal The method comprising the steps of:

Preferably, the native industry may be made up of at least one of agriculture, animal husbandry, and fisheries.

A third aspect of the present invention provides a computer-readable recording medium on which a program capable of executing a method for collecting and analyzing environmental information data associated with the above-mentioned local industry is recorded.

The method for collecting and analyzing environmental information data associated with the local industry according to the present invention may be embodied in computer readable code on a computer readable recording medium. A computer-readable recording medium includes all kinds of recording apparatuses in which data that can be read by a computer system is stored.

For example, the computer-readable recording medium includes a ROM, a RAM, a CD-ROM, a magnetic tape, a hard disk, a floppy disk, a removable storage device, a nonvolatile memory, , And optical data storage devices.

According to the system and method for collecting and analyzing environmental information data associated with the local industry of the present invention as described above, environmental information data is automatically and automatically collected from at least one data collecting apparatus having a plurality of sensors associated with the local industry Semantic inference data is semantically inferred and analyzed by the ontology inference method, and more meaningful information can be provided to users in various forms, It has the advantage of independent operation.

Also, according to the present invention, environmental information data sensed from a plurality of sensors associated with the local industry are automatically collected and digitized through at least one data collection device, and wireless communication methods such as Wi-Fi By transferring data in real time without being restricted by external factors, it is possible to efficiently manage integrated environmental information data related to the local industry, as well as to improve labor-intensive production methods, thereby improving productivity and increasing profitability .

In addition, according to the present invention, a plurality of sensors and a wireless communication module are mounted on an Arduino board based on an open source, and data is converted and transmitted through system software, so that the equipment itself can be miniaturized, It is easy and easy to apply to non-crops, and even if various sensors are applied, there is an advantage that a platform capable of integrated management capable of receiving sensed data values can be constructed without applying a separate platform.

Further, according to the present invention, unnecessary waste of manpower and production loss can be saved by production management according to the optimal production schedule derived from the local industrial system, and the quality of products can be improved by improving the production environment and the competitiveness of the domestic and foreign markets There is an advantage that it can be secured.

1 is a block diagram illustrating a system for collecting and analyzing environmental information data related to a local industry according to an exemplary embodiment of the present invention.
2 is a block diagram illustrating a data collecting apparatus according to an embodiment of the present invention.
3 is a general flow diagram illustrating a method for collecting and analyzing environmental information data associated with a local industry in accordance with an embodiment of the present invention.
FIG. 4 is a table for explaining an ontology DB table for storing an OWL ontology applied to an embodiment of the present invention.
FIG. 5 is a diagram illustrating an example of construction of a domain ontology applied to an embodiment of the present invention.
6 is a table showing a configuration of a task manual descriptor concept ontology applied to an embodiment of the present invention.
FIG. 7 is a table showing definitions of object attributes applied to an embodiment of the present invention.
FIG. 8 is a diagram illustrating an example of attribute information construction using OWL applied to an embodiment of the present invention.
9 is a diagram illustrating an example of DB construction of a data storage device applied to an embodiment of the present invention.
FIG. 10 is a diagram for explaining a process of an OWL parsing process of a data analysis server applied to an embodiment of the present invention.
11 is a diagram for explaining a reasoning method using a CQEFT applied to an embodiment of the present invention.
12 is a diagram for explaining a structure for a full search using a CQEFT applied to an embodiment of the present invention.
13 is a diagram for explaining a query processing procedure using a CQEFT applied to an embodiment of the present invention.
FIG. 14 is an overall block diagram showing a configuration for providing a search result according to a user query through a data analysis server applied to an embodiment of the present invention.
15 is a diagram illustrating a data processing process for providing a search result according to a user query using a system for collecting and analyzing environment information data related to a local industry according to an embodiment of the present invention.
16 is a view illustrating a web-based monitoring service provided to a user terminal through a data analysis server applied to an embodiment of the present invention.

The above and other objects, features, and advantages of the present invention will become more apparent by describing in detail exemplary embodiments thereof with reference to the attached drawings, which are not intended to limit the scope of the present invention. In the following description, well-known functions or constructions are not described in detail since they would obscure the invention in unnecessary detail.

Terms including ordinals, such as first, second, etc., may be used to describe various elements, but the elements are not limited to these terms. The terms are used only for the purpose of distinguishing one component from another. For example, without departing from the scope of the present invention, the first component may be referred to as a second component, and similarly, the second component may also be referred to as a first component. The terminology used in this application is used only to describe a specific embodiment and is not intended to limit the invention. The singular expressions include plural expressions unless the context clearly dictates otherwise.

While the present invention has been described in connection with what is presently considered to be the most practical and preferred embodiment, it is to be understood that the invention is not limited to the disclosed embodiments. Also, in certain cases, there may be a term selected arbitrarily by the applicant, in which case the meaning thereof will be described in detail in the description of the corresponding invention. Therefore, the term used in the present invention should be defined based on the meaning of the term, not on the name of a simple term, but on the entire contents of the present invention.

When an element is referred to as "including" an element throughout the specification, it is to be understood that the element may include other elements as well, without departing from the spirit or scope of the present invention. Also, the terms "part," " module, "and the like described in the specification mean units for processing at least one function or operation, which may be implemented in hardware or software or a combination of hardware and software .

Hereinafter, embodiments of the present invention will be described in detail with reference to the accompanying drawings. However, the following embodiments of the present invention may be modified into various other forms, and the scope of the present invention is not limited to the embodiments described below. The embodiments of the present invention are provided to enable those skilled in the art to more fully understand the present invention.

Each block of the accompanying block diagrams and combinations of steps of the flowcharts may be performed by computer program instructions (execution engines), which may be executed by a general-purpose computer, special purpose computer, or other programmable data- The instructions that are executed through the processor of the computer or other programmable data processing equipment will generate means for performing the functions described in each block or flowchart of the block diagram. These computer program instructions may also be stored in a computer usable or computer readable memory capable of directing a computer or other programmable data processing apparatus to implement the functionality in a particular manner so that the computer usable or computer readable memory It is also possible for the instructions stored in the block diagram to produce an article of manufacture containing instruction means for performing the functions described in each block or flowchart of the flowchart.

Computer program instructions may also be loaded onto a computer or other programmable data processing equipment so that a series of operating steps may be performed on a computer or other programmable data processing equipment to create a computer- It is also possible that the instructions that perform the data processing equipment are capable of providing the steps for executing the functions described in each block of the block diagram and at each step of the flowchart.

Also, each block or step may represent a portion of a module, segment, or code that includes one or more executable instructions for executing the specified logical functions, and in some alternative embodiments, It should be noted that functions may occur out of order. For example, two successive blocks or steps may actually be performed substantially concurrently, and it is also possible that the blocks or steps are performed in the reverse order of the function as needed.

FIG. 1 is a block diagram illustrating a system for collecting and analyzing environmental information data related to a local industry according to an embodiment of the present invention. FIG. 2 is a block diagram of a data collecting apparatus applied to an embodiment of the present invention. And FIG.

Referring to FIGS. 1 and 2, a system for collecting and analyzing environmental information data related to a local industry according to an embodiment of the present invention includes at least one data collecting apparatus 100, a data storing apparatus 200, And a data analysis server 300.

Here, at least one data collection device 100 is installed in the vicinity of a crop or product cultivated or produced in a local industry (for example, agriculture, livestock industry, fishery industry, etc.) And collects environment information data related to the local industry using the plurality of sensors 111 and performs wireless transmission in real time. The data collection module 110, the data conversion module 120, the data transmission module 120, A control module 130, a power supply module 150, and the like.

A more detailed description of the constituent elements of each data collecting apparatus 100 constructed as described above is as follows.

That is, the data collection module 110 has a plurality of sensors 111 associated with the local industry, and collects environmental information data signals associated with the local industry sensed by each sensor 111.

At this time, the environmental information data may include, for example, at least one of temperature, humidity, solar radiation, wind velocity, wind direction, soil moisture and salinity data, but the present invention is not limited thereto. It can include all kinds of environmental information data that affect the growth and production of the product.

The plurality of sensors 111 are components for sensing environmental information signals associated with the local industry, and may be variously provided depending on the kind of the yellow loam industry. In addition, Any sensor capable of measuring environmental information affecting growth and production is applicable.

For example, when a data collection device 100 applied to an embodiment of the present invention is installed in plum farming in the local industry of Gwangyang Province, the plurality of sensors 111 may be a temperature measurement sensor, a humidity measurement sensor, Measurement sensor, wind direction measurement sensor and soil moisture measurement sensor Six kinds of measurement sensors can be installed on the production site to collect and process environmental information such as climate information necessary for plum growth environment.

In this case, the temperature measuring sensor is a sensor for comparing and analyzing the growth change of cultivated crops according to temperature by measuring the temperature of an object to be measured such as air, water, or soil, and includes a thermistor element Can be used. The thermistor element may be an NTC thermistor, a PTC thermistor, or a critical characteristic thermistor (CRT).

For example, the temperature sensor may be a contact-type temperature sensor using a thermistor element. However, the temperature sensor may be, for example, a thermocouple sensor, a bimetal, an IC temperature sensor, or an infrared sensor.

The humidity sensor is a sensor for comparing and analyzing growth changes of cultivated crops according to humidity by measuring the humidity of an object to be measured such as air or soil and measuring humidity by using a change in electrical property of the moisture- .

These humidity measurement sensors can be classified into resistance type humidity sensor and capacitance type humidity sensor, and it is widely applied to make the optimum condition of automobile and medical device, air purification system and automatic air-conditioning system as well as household appliances and mobile .

The resistance type humidity sensor measures the humidity using a change in resistance which is changed by humidity. This resistive type humidity sensor is widely used because it is relatively cost competitive as compared with the capacitance type humidity sensor.

In recent years, however, capacitive humidity sensors can be manufactured in the form of a one chip on a semiconductor substrate, so that they can secure a price competitiveness advantage over the resistance humidity sensor and use thereof is increasing. Particularly, the capacitance type humidity sensor is more reliable than the resistance type humidity sensor, and has the advantage that the sensor characteristic is linear and the influence of temperature is small.

Such a capacitive humidity sensor is a sensor using the principle that the capacitance is changed according to the amount of water molecules adsorbed on the moisture-permeable membrane, and a moisture-permeable material such as polyimide or ceramic whose dielectric constant changes when moisture is absorbed And operates in the form of a capacitor made of a dielectric. That is, there is a humidity sensing layer, and the principle is that the moisture permeates through the humidity sensing layer, and the dielectric constant changes and the capacitance changes accordingly.

The sensor for measuring the radiation dose is a sensor for measuring the amount of solar radiation in the atmosphere and comparing and analyzing the growth change of the cultivated crop according to the irradiation amount. The sensor can measure the amount of electricity by measuring the amount of electricity generated by varying the charge value according to the amount of light, It is measured in the range of 0 ~ 1800W / m ^{2 in} the form of solar radiation sensor and has about 5% accuracy.

The sensor for measuring the wind speed and direction of the wind is a sensor for measuring wind speed and direction in the air, and it is preferable to use a method of measuring the wind speed and the wind direction by measuring the cooling effect by the wind using a resistive temperature detector (RTD) However, the present invention is not limited to this, and it is possible to measure the wind speed according to the degree to which the piezo sensor vibrates by the wind using a plurality of piezo sensors, as well as to determine the wind direction vectorwise.

The sensor for measuring moisture of the soil is a sensor for comparing and analyzing the growth change of a cultivated crop according to the moisture state information of the soil by measuring the moisture state information of the soil such as the water content of the soil, Frequency signal is oscillated in a standard capacitor made of a medium to calculate each electrostatic capacitance value corresponding to the difference in permittivity between the two capacitors and the frequency or period of the high frequency signal according to the calculated electrostatic capacitance value is measured, The present invention is not limited to this. For example, it may be a measurement sensor using an electric resistance of an electrode in a gypsum block, a measurement sensor using neutron scattering, or the like. . The soil moisture information measured by the soil moisture sensor may be pF, percentage (%), or pressure unit.

Meanwhile, when the data collection device 100 applied to one embodiment of the present invention is installed in the domestic industry of Yeonggwang-gun, the plurality of sensors 111 may include a temperature measurement sensor, a humidity measurement sensor, a radiation measurement sensor, , Wind direction measurement sensor and salinity measurement sensor All six measurement sensors can be installed on the production site to collect and process environmental information such as climate information necessary for production of culverts.

The salinity measuring sensor is a sensor for measuring the salinity (salt concentration) of a measurement object such as a gulliver, and uses the principle that the electrical conductivity varies depending on the amount of salinity, that is, the current flowing through the sample is inversely proportional to the resistance And converting the measured electrical conductivity into the concentration of salinity by using the value proportional to the electrical conductivity.

The data collecting module 110 configured as described above is preferably provided with a general amplifying means for amplifying the fine environmental information analog signal sensed by each sensor 111. However, And amplified by the data conversion module 120, which will be described later.

The data conversion module 120 performs a function of converting an environmental information analog signal sensed by each sensor 111 of the data acquisition module 110 into a digital signal.

The data transmission module 130 transmits the digitized environmental information data from the data conversion module 120 through a wireless communication method.

At this time, it is preferable that the wireless communication method is at least one of Wi-Fi communication, WiGig communication, Wibro communication, and WiMAX communication, for example. (Short Range Communication) such as Bluetooth, Radio Frequency Identification (RFID), infrared data association (IrDA), Ultra Wideband (UWB), or ZigBee may be used.

The control module 140 is a module for entirely controlling each component constituting the data collecting apparatus 100 of the present invention. In particular, the data collecting module 110 collects environmental information signals The data conversion module 120 controls the operation of the sensor 111 and transmits the environment information data digitized from the data conversion module 120 to the data storage device 200 and / And performs a function of controlling the operation.

The control module 140 may also receive information about normal operation and normal collection of each sensor 111 from the data collection module 110 and may receive information from the data storage 200 and / And controls the data analysis server 300 to transmit data in real time.

At this time, the control module 140 transmits information about normal operation and normal collection of each sensor 111 to the data storage device 200 and / or the data analysis server 300 together with the digitized environment information data in real time To be transmitted.

The power supply module 150 supplies operating power required for each module. The power supply module 150 supplies the power of the built-in battery to each sensor 111 and the control module 140 and operates the charging terminal (not shown) ) Can be used to charge the battery.

In addition, the data conversion module 120 may further include a data storage module 160 for converting environment information data digitized from the data conversion module 120 into databases (DB) for each sensor under the control of the control module 140.

At least one module of the data acquisition module 110, the data conversion module 120, the data transfer module 130, the control module 140, the power supply module 150, and the data storage module 160 It is preferable to be mounted on an open source based Arduino board. Each of the sensors 111 of the data acquisition module 110 is preferably installed in a place where measurement is required and is connected to an input / output port of an open source-based Arduino board. However, Some or all of them may be mounted on the board.

By using the open source Arduino board, it is possible to build a platform that can integrate and manage multiple sensors, and it is possible to miniaturize the equipment itself, and even if there is no separate data logger system, (Wi-Fi) wireless communication to directly transmit the sensor data to the data storage device 200 and / or the data analysis server 300.

The data storage device 200 receives all the information data transmitted from each data collection device 100 and stores and manages the information data in a database (DB) (DB) of the OWL ontology information data represented by a web ontology language (OWL) based on the received information data, and stores the converted OWL ontology information data in a database (DB).

The data storage device 200 includes a sensor data DB 210 for storing environmental information data transmitted from each data collection device 100 in a DB An index DB 220 composed of a plurality of ontology DB tables for storing OWL ontology information data expressed in a web ontology language (OWL) based on environment information data, and an index DB (220) using a predetermined ontology editor. An ontology DB 230 for selecting a domain through a database 220 and connecting property information between the selected domain and class to make a database (DB) of a domain ontology for each sensor data based product, .

Although not shown in the figure, the data storage device 200 may receive environment information data transmitted from each data collection device 100 in real time by radio, or may perform wireless communication for data communication with the data analysis server 300 Module is basically provided.

The data analysis server 300 receives the OWL ontology information data along with the sensor-specific environment information data stored in the data storage device 200, converts the OWL ontology information data into an Extensible Markup Language (XML) document, And generates the sensor data ontology using the XML query document and the user query input through the user terminal 400. The generated sensor data ontology is semantically generated using a predetermined ontology inference engine And provides the result to the user terminal 400.

The data analysis server 300 receives the OWL ontology information data along with the sensor-specific environment information data stored in the data storage device 200 and parses the received OWL ontology information data to class, property, ), Constraints on hierarchical information and properties, and convert hierarchical information on the extracted classes and properties into an extensible markup language (XML) document.

In addition, the data analysis server 300 may store an XML markup language (XML) document including hierarchical information of the OWL ontology information data in a separate first storage module (e.g., XML repository) (E.g., an RDBMS) in a separate second storage module (see FIG. 10).

In addition, the ontology reasoning engine used in the data analysis server 300 may be an inference engine based on a Semantic Web, for example.

In addition, the data analysis server 300 determines the degree of similarity and rankings of the product growth, product productivity, and product production trends of the products produced through the domestic industry among semantically inferred and analyzed results through the predetermined ontology reasoning engine And provide the result to the user terminal 400. [

In addition, the data analysis server 300 analyzes the result semantically inferred and analyzed through the pre-established ontology reasoning engine in a visual form of at least one of a text, a chart, and a graph, And can provide it to the terminal 400.

Also, the data analysis server 300 converts semantically inferred and analyzed results through the predetermined ontology reasoning engine according to an operating system (e.g., Windows, IOS, Android, etc.) of the user terminal 400, (400).

In addition, the data analysis server 300 can receive information on normal operation and normal collection status of each sensor 111 from at least one data collection device 100 in real time and monitor the same.

In addition, the data analysis server 300 can provide a web-based monitoring service so that the user can extract, analyze, and query data in a desired form through the user terminal 400. [

The data analysis server 300 receives the weather information data of the region where the data collection apparatus 100 is installed from the weather station weather information providing server 500 connected via the communication network 10 and stores the weather information data in a database , The weather information of the corresponding region stored in the data storage device 200 may be compared with the past and current sensor-specific environmental information data to provide the weather information required for the completion of the product to the user terminal 400 .

The user terminal 400 is connected to the data analysis server 300 through the communication network 10 and the communication network 10 is a communication network which is a high speed period network of a large communication network capable of a large capacity and long distance voice and data service. Internet) or WiFi, Wibro, and Wimax to provide high-speed multimedia services.

The Internet includes a plurality of services such as HTTP (Hyper Text Transfer Protocol), Telnet, File Transfer Protocol (FTP), Domain Name System (DNS), Simple Mail Transfer Protocol (SMTP) Refers to a worldwide open computer network structure providing a Simple Network Management Protocol (SNMP), a Network File Service (NFS), a Network Information Service (NIS), and the like. The user terminal 400 is connected to the data analysis server 300 It provides an environment that allows for Meanwhile, the Internet may be a wired or wireless Internet, or may be a core network integrated with a wired public network, a wireless mobile communication network, or a portable Internet.

If the communication network 10 is a mobile communication network, it may be a synchronous mobile communication network or an asynchronous mobile communication network. As an example of the asynchronous mobile communication network, a WCDMA (Wideband Code Division Multiple Access) communication network is exemplified. In this case, although not shown in the drawing, the mobile communication network may include, for example, a radio network controller (RNC). Meanwhile, although the WCDMA network is described as an example, it may be a next generation communication network such as a 3G LTE network, a 4G network, and a 5G network, or an IP network based on other IPs. The communication network 10 transmits signals and data between the user terminal 400 and the data analysis server 300, the weather and weather information providing server 500, and the data analysis server 300.

The user terminal 400 is typically a computer such as a desktop PC (personal computer), a notebook PC, or the like, but is not limited thereto, and may be any type of wired / wireless communication device.

For example, the user terminal 400 includes various mobile terminals communicating through the wireless Internet or the portable Internet. In addition, the user terminal 400 may include a Palm PC, a smart phone, a mobile play-station, The present invention can comprehensively mean all wired and wireless home appliances / communication devices having a user interface for connecting to the data analysis server 300, such as a DMB (Digital Multimedia Broadcasting) phone, a tablet PC, and an iPad.

In particular, when the user terminal 400 is implemented as a normal smartphone, the smartphone can be freely used by downloading various application programs desired by a user, unlike a general mobile phone (a feature phone) It is a phone based on an open operating system that can be deleted. It has not only all the functions of voice / video call and Internet data communication, but also mobile phone with mobile office function It is desirable to be understood as a communication device including all Internet phones or Tablet PCs.

Such an open-type operating system may include, for example, Symbian of NOKIA, BlackBerry of RIMS, iPhone of Apple, Microsoft's Windows Mobile, Google's Google Android, and Samsung's ocean.

As described above, since the smartphone uses an open operating system, a user can arbitrarily install and manage various application programs, unlike a mobile phone having a closed operating system.

That is, the smartphone basically includes a control unit, a memory unit, a screen output unit, a key input unit, a sound output unit, a sound input unit, a camera unit, a wireless network communication module, a near field wireless communication module, and a battery for power supply.

The controller is a generic term for controlling the operation of the smartphone, and includes at least one processor and an execution memory, and is connected to each functional unit provided in the smart phone through a bus.

The controller controls the operation of the smartphone by loading at least one program code included in the smart phone into the execution memory through the processor and calculating the result by transmitting the result to the at least one functional unit through the bus .

The memory unit is a general term of a non-volatile memory included in a smart phone, and stores and maintains at least one program code executed through the control unit and at least one data set in which the program code is used. The memory unit basically stores a system program code and a system data set corresponding to an operating system of a smartphone, a communication program code and a communication data set for processing a wireless communication connection of the smartphone, at least one application program code and an application data set , And the program code and data set for implementing the present invention are also stored in the memory unit.

The screen output unit is composed of a screen output device (e.g., an LCD, an LED device) and an output module for driving the screen output device. The screen output unit is connected to the control unit through a bus, And outputs it to the device.

The key input unit is composed of a key input device having at least one key button (or a touch screen device interlocked with the screen output unit) and an input module for driving the key input unit. The control unit is connected to the control unit via a bus, Or inputs data necessary for the operation of the control unit.

The sound output unit includes a speaker for outputting a sound signal and a sound module for driving the speaker. The sound output unit is connected to the control unit through a bus, and outputs a result of operation corresponding to the sound output from the various operation results of the control unit through the speaker . The sound module decodes sound data to be output through the speaker and converts the sound data into a sound signal.

The sound input unit includes a microphone for receiving a sound signal and a sound module for driving the microphone, and transmits the sound data input through the microphone to the control unit. The sound module encodes and encodes a sound signal input through the microphone.

The camera unit includes an optical unit, a CCD (Charge Coupled Device) and a camera module for driving the CCD unit, and obtains bitmap data input to the CCD through the optical unit. The bitmap data may include both still image data and moving image data.

The wireless network communication module is a collective term for communicating wireless communication and includes at least one antenna, an RF module, a baseband module, and a signal processing module for transmitting and receiving a radio frequency signal of a specific frequency band. And transmits the calculation result corresponding to the wireless communication among the various calculation results of the control unit through the wireless communication or receives the data through the wireless communication and transmits the data to the control unit, , Communication, and handoff procedures.

Also, the wireless network communication module includes a mobile communication structure for performing at least one of connection, location registration, call processing, call connection, data communication, and handoff to a mobile communication network according to the CDMA / WCDMA standard. Meanwhile, according to the intention of those skilled in the art, the wireless network communication module may further include a portable Internet communication structure for performing at least one of connection to the portable Internet, location registration, data communication, and handoff according to the IEEE 802.16 standard, It is evident that the present invention is not limited by the wireless communication configuration provided by the communication module.

The short-range wireless communication module is composed of a short-range wireless communication module that connects a communication session using a radio frequency signal as a communication medium within a predetermined distance. Preferably, the short-range wireless communication module includes RFID communication, Bluetooth communication, Wi- And wireless communication. The short-range wireless communication module may be integrated with the wireless network communication module.

In particular, when the user terminal 400 applied to one embodiment of the present invention is implemented as a smart phone, the environment information integrated management application program associated with the local industry is downloaded through an App Store, Environmental information service can be provided.

Hereinafter, a method for collecting and analyzing environmental information data related to a local industry according to an embodiment of the present invention will be described in detail.

3 is a general flow diagram illustrating a method for collecting and analyzing environmental information data associated with a local industry in accordance with an embodiment of the present invention.

Referring to FIGS. 1 to 3, a method for collecting and analyzing environmental information data related to a local industry according to an embodiment of the present invention includes the steps of: (S100), and transmits the collected environment information data to the wireless communication terminal (S100).

At this time, it is preferable that the local industry includes at least one industry such as agriculture, animal husbandry, and fisheries, and the environmental information data collected in step S100 may include, for example, temperature, humidity, radiation amount, wind speed, It is preferable that the data is at least any one of salinity data.

The step S100 includes the steps of collecting environmental information signals associated with the local industry sensed by the sensors 111, converting the environmental information analog signals sensed by the sensors 111 into digital signals, And real-time transmission of the environment information data by the wireless communication method.

At this time, the wireless communication method may be at least one of Wi-Fi communication, WiGig communication, WiBro communication, and WiMAX communication, for example. Preferably, the data collection device 100 is mounted on an open source based Arduino board.

In addition, after converting the environment information analog signal sensed from each sensor 111 to digital, the digitalized environmental information data is DB-based and stored in a separate data storage module 160 As shown in FIG.

Further, after step S100, information on normal operation and normal collection of each sensor 111 is acquired and transmitted in real time through each data collecting apparatus 100, and the data analyzing server 300 And receiving information on normal operation and normal collection of each sensor 111 transmitted and monitoring it in real time.

Thereafter, the environment information data transmitted in the step S100 is received through the data storage device 200, and the environment information data is converted into a database (DB) on a sensor-by-sensor basis and is stored in a web ontology language (OWL) OWL ontology information data into a database (DB) (S200).

The step S200 includes a step of storing the environmental information data transmitted in the step S100 into a database (DB) for each sensor, and storing the environment information data in the index database 220 (220) including a plurality of ontology DB tables Storing OWL ontology information data represented by a web ontology language (OWL) in the index database 220, selecting a domain through the index DB 220 using a predetermined ontology editor, And storing the domain ontology for each sensor-based product in a database (DB).

At this time, a unique identifier (ID) may be assigned to each instance of each concept applied to the index DB 220, and the same ID (ID) may be used to store the concepts when the concepts are mutually quoted.

Hereinafter, the sensor data storage in step S200 will be described in more detail.

FIG. 4 is a diagram for explaining an ontology DB table for storing an OWL ontology applied to an embodiment of the present invention in a table form, FIG. 5 is a diagram illustrating an example of construction of a domain ontology applied to an embodiment of the present invention, FIG. 6 is a table showing a configuration of a task manual descriptor concept ontology applied to an embodiment of the present invention. FIG. 7 is a table showing the definition of an object attribute applied to an embodiment of the present invention. 8 is a view showing an example of attribute information construction using OWL applied to an embodiment of the present invention, and FIG. 9 is a view showing an example of DB construction of a data storage device applied to an embodiment of the present invention.

4 to 9, the environment information data transmitted in step S100 may be stored in a database (DB) in the data storage device 200, which is a large capacity intelligent data storage, using the ontology.

That is, the environment information data transmitted in step S100 can be constructed in a database (DB), and a sensor ontology for intelligent sensor data processing can be constructed.

The concept of 'OWL ontology description language', 'Class', 'Property', 'Individual', etc., which are to be used in the present invention, can be configured as a single table.

First, the sensor data DB 210 and the index DB 220 are constructed. When a unique identifier (ID) is specified for each instance of each concept, unnecessary duplication of data is performed using these identifiers .

For example, the 'subject', 'predicate', and 'object' fields of the RDF Triple table are represented by resource identifiers (IDs), respectively. Inheritance, inclusion, Or a special table can be constructed to enhance search efficiency.

Accordingly, in order to store the database of the ontology represented by OWL to be linked with the sensor data DB 210, a storage model for efficient processing of the ontology is required as follows.

That is, the index DB 220 may include a plurality of ontology DB tables. The plurality of ontology DB tables may include an OWLOntology table, an OWLResource table, a Namespace table, an OWLIndividual table, an RDFTriple table, an OWLRelation table, an OWLProperty table, an OWLPropertyRestriction table, and an OWLClassRestriction table, as shown in FIG.

Here, the OWLOntology table may store descriptive information about an ontology data file such as an ontology name and version information.

The OWL resource table may be configured so that resources are stored in a single table so that each association table can refer to an identifier (ID) of the corresponding resource and can be used. The resource is a very basic concept in ontology, , And the identifier (ID) can be assigned a 'UNIQUE' attribute with a primary key, and a 'type' field can be specified to specify a category to which the resource belongs (for example, class, attribute, etc.).

The Namespace table is relatively simple and can store identifiers (IDs) and names of namespaces to be used by resources, and can prevent meaningful interference between predicates.

The OWLIndividual table may include information on an object and information on a class associated with the object, and an object on the ontology has a relation with a specific class as one instance of the class.

The RDFTriple table may represent a triple including 'subject', 'predicate', and 'object' fields, and each field value may refer to a resource identifier (ID) in the OWLResource table.

The OWLRelation table may have an equivalent relationship (equivalentClass, equivalentProperty, sameAs) and an unequal relationship (differentFrom, AllDifferent) as OWL relations. In addition, 'OWLRelation table' may include 'subClass', 'subProperty' , 'superProperty', and so on. In order to reduce the joins between tables in the query of the future relations, it is possible to uniformly store them in the OWLRelation table and to classify the relation types through the 'type' field.

Since the OWLProperty table can be given two attribute values 'domain' and 'range', and these attribute values are frequently used in ontology reasoning, the OWLProperty table can be configured and stored independently. Depending on the type, it may include 'ObjectProperty', 'DatatypeProperty' and 'SymmetricProperty', 'TransitiveProperty', 'FunctionalProperty', and 'InverseFunctionalProperty' that represent the relationship between the properties. can do.

The OWLPropertyRestriction table may include 'Restriction', 'onProperty', 'allValuesFrom', 'someValuesFrom', 'hasValue', etc. as constraints on the relationship between the attributes in the ontology and 'minCardinality', ' The constraints on these properties are stored in the OWLPropertyRestriction table. The constraint type is described using the 'type' field and the 'type' value is set to 'hasValue', ' "minCardinality", "maxCardinality", and "cardinality".

In the OWLClassRestriction table, there may exist relations such as 'intersectionOf', 'unionOf', 'complementOf', and 'disjointWith' between classes, and the relation can be stored in the OWLClassRestriction table.

The database schema of the system to be developed through the present invention can be designed in consideration of the utilization rate of the storage space, search efficiency, ease of query configuration, and the like.

The ontology DB 230 for designing the ontology DB 230 for storing the domain ontology database (DB) for each sensor data based product (or each crop) is designed. For example, The ontology can be shared and reused as a unique purpose of the ontology, and development time and resources can be shortened.

For this, the domain can be selected through the established index DB 220 and a subclass corresponding thereto can be selected. As shown in FIG. 5, the ontology editor "OntoMan" can be utilized for constructing the domain ontology, and has the following advantages over other editors.

In other words, it has an easy user interface structure based on tree structure, supports automatic ontology construction for specific domain (built-in WordNet based automatic frame ontology), and provides ontology vocabulary library (based on web ontology language user guide ), Can be expressed in OWL ontology parsing and OWL ontology language, and can support automatic ontology construction for specific domain.

The overall structure of the domain ontology to be constructed in order to express information to be used in the data analysis server 300 of the present invention should be designed. The definition of each concept necessary for constructing the sensor ontology is as follows. Can be defined.

That is, 'Product' is a top class, and it has 'Domain' class and 'Descriptor' class which describes sensor data as a subclass.

At this time, the 'Domain' class is a subclass classified according to the products produced through the local industry, and can be used for classifying agricultural products, agricultural products, and major data classified by agricultural products.

The 'Descriptor' class includes an 'Identifier' class indicating a DB key or the like to replace the unique number of the sensor data and a title, a class of 'Sensor' indicating the type of the sensor data, and a temperature, humidity, , A 'Keyword' class indicating a search keyword, a 'Writer' class indicating an information owner, and a 'Context' class describing attributes of sensor data in detail .

The 'Context' class can be designed so as to be able to retrieve information such as the area and time at which data is generated by describing the attributes of the sensor data in detail. That is, the 'Context' class may be composed of a 'Location' class that represents local information, a 'Spatio' class that represents spatial information (indoor, outdoor), and a 'Temporal' class that represents time information.

The object properties defined in the OWL ontology of the present invention are as shown in FIG. 7, and the restriction indicates that some members of the classes are members of the class Can specify the conditions that must be described in order to be

On the other hand, it is necessary to link attribute information between the selected domain and classes for establishing the ontology, and attribute information according to a specific task can be set as shown in FIG. This upper ontology design can be constructed using the index DB 220.

As shown in FIG. 9, the DB schema is designed to minimize the complexity in the database and improve the data processing speed between the ontology and the DB, as shown in FIG.

Then, the OWL ontology information data is received together with the sensor-specific environment information data stored in the step S200 through the data analysis server 300, and converted into an Extensible Markup Language (XML) document in operation S300.

At this time, in step S300, the data analysis server 300 receives the OWL ontology information data together with the per-sensor environment information data stored in step S200, parses the OWL ontology information data, and classifies, extracts constraints on the instance information, the hierarchical information and the property, and then converts the hierarchical information on the extracted class and property into an extensible markup language (XML) document.

In addition, after the step S300, an XML document including the hierarchical information of the OWL ontology information data is stored in a separate first storage module (for example, an XML repository) through the data analysis apparatus 300 And storing the extracted remaining information in a separate second storage module (e.g., an RDBMS).

Next, the sensor data ontology is generated using the extensible markup language (XML) document converted in step S300 and the user query input through the user terminal 400 through the data analysis server 300 (S400) .

Then, the sensor data ontology generated in step S400 is semantically inferred and analyzed using the predetermined ontology reasoning engine through the data analysis server 300, and the result is provided to the user terminal 400 (S500) .

Here, the predetermined ontology reasoning engine may be a semantic web based reasoning engine.

In addition, in step S500, the data analysis server 300 determines whether or not the result of semantically inferred and analyzed through the pre-established ontology reasoning engine, the growth effect of the product produced through the domestic industry, the productivity of the product, And provides the result to the user terminal 400. [0050]

In step S500, the data analysis server 300 determines whether at least one of a text, a chart, and a graph is semantically inferred and analyzed through the predetermined ontology inference engine To the user terminal 400 in a visual form of FIG.

In step S500, the data analysis server 300 analyzes the semantically inferred and analyzed results through the predetermined ontology reasoning engine according to the operating system (e.g., Windows, IOS, Android, etc.) of the user terminal 400 And provide the converted user terminal 400 with the converted information.

In addition, after step S500, the data analysis server 300 further includes a step of providing a web-based monitoring service so that the user can extract, analyze and inquire data in a desired form through the user terminal 400 .

After step S500, weather information data of the area where the data collecting apparatus 100 is installed is received from another weather station weather information providing server 500 via the data analyzing server 300 and converted into a database (DB) And comparing the weather information of the stored corresponding area with the past and current sensor-specific environmental information data stored in step S200 through the data analysis server 300, To the terminal 400 according to the present invention.

Hereinafter, the sensor data processing in steps S300 to S500 will be described in more detail.

FIG. 10 is a diagram for explaining a procedure of an OWL parsing process of a data analysis server applied to an embodiment of the present invention, FIG. 11 is a view for explaining a reasoning method using a CQEFT applied to an embodiment of the present invention , FIG. 12 is a diagram for explaining a structure for a full search using a CQEFT applied to an embodiment of the present invention, FIG. 13 is a diagram for explaining a query processing procedure using a CQEFT applied to an embodiment of the present invention And FIG. 14 is a block diagram showing a configuration for providing a search result according to a user query through a data analysis server applied to an embodiment of the present invention. FIG. And a data processing process for providing a search result according to a user query using a system for collecting and analyzing related environment information data Side, and Figure 16 is through a data analysis server applied to an embodiment of the present invention showing an exemplary screen of a web-based monitoring service provided to the user terminal.

10 to 16, the sensor data processing through the data analysis server 300 of the present invention first generates a sensor data ontology. In the sensor data ontology, the DB schema pre-built in the data storage device 200 and the stored data And generates ontology data from the data stored in the data storage device 200 in accordance with the generated ontology schema.

For this purpose, when an ontology is created considering the view definition, additional classes and upper / lower relationships can be created in the ontology created through the existing method, and the generated class can be used for query processing and integration on the ontology. Lt; / RTI >

Since OWL data is expressed in XML format, OWL data has hierarchical structure for class or property as well as hierarchical XML data, and data retrieval considering the sub-structure of class or property at query is required Do.

At this time, in order to maintain hierarchical information about the class and the property, it can be stored in the XML database system in the form of XML data. It is possible to store unique identifier (ID) information of a class and a property having inheritance among the class and property information declared in the schema part of the OWL document.

10, when the OWL information is input, the OWL parser parses the document and extracts class information, property information, instance information, hierarchical information, and constraint conditions on the property. do.

At this time, the hierarchical information about the class and the property is converted into the XML document by the layer information manager, the XML document including the layer information of the OWL data is stored in the XML repository, and the extracted information is stored in the RDBMS through the ontology manager .

The OWL parser extracts an RDF triple (Subject, Predicate, Object) from an ontology constructed by OWL, and can be used for an ontology search engine application. Through the above process, it is stored in the RDF Triple database (DB), and the function of providing triple information to the query processing module in the future can be performed.

On the other hand, the contents related to the RDF Triple are described in Korean Patent Registration No. 10-0820746 (Browsing system and method of information using ontology) filed by the present applicant, and a detailed description thereof will be omitted.

Next, the ontology reasoning engine and reasoning rules applied to an embodiment of the present invention will be described in detail. The search method in the semantic search system is based on refining whole resources by applying inference, and using a semantic reasoning search engine, It is a way to respond to a query. This semantic search can accurately grasp the user 's intention and lead to the extension of the rich search area through inference by the result that is not caused by general keyword matching.

The intelligent sensor data analysis method applied in the present invention can construct a semantic reasoning search engine based on the Prolog language. In the semantic reasoning search engine, meta data generated by OWL is read in KIF (Knowledge Interchange Format) format, and inference and searching are performed through a conversion process into a predicate form so as to perform forward reasoning.

On the other hand, typical inference engines include CLASSIC, RACER, FaCT, and DLP, which are pure DL inference engines. Semantic Web based reasoning engines include Jena, F-OWL, Pellet, Euler, . There are Horn Logic based reasoning engines such as Prolog, CLP, Alf System, Oz, and TRIPLE.

In addition, a query processing engine and an inference engine applied in an embodiment of the present invention are CQEFT (Controlled Query Engine For Triple), and are structured as shown in FIG.

The CQEFT is composed of a query processing engine and an inference engine. A total of 55 inference rules are loaded for query processing. There are 30 existing graph models, 20 inference rules supporting the web ontology vocabulary, 5 consistency check rules And the like.

The reasoning engine should be selected according to the use and characteristics of the reasoning engine, and since there are various reasoning engines, it is necessary to select the reasoning engine that meets the conditions of the present invention.

In addition, the data analysis server 300 of the present invention can include an intelligent sensor data search interface, and includes a query processing engine for intelligent query processing and a CQEFT (Controlled Query Engine For Triple) as an inference engine. The entire intelligent search system is as shown in FIG.

Since the ontology search is difficult for the user to easily access, there is a need to add the automatic completion function and the visualization function while maintaining the text input as it is, and the query processing procedure using the CQEFT is shown in FIG. 13 .

In order to search the intelligent sensor data through the data analysis server 300 of the present invention, as shown in FIG. 14, a module for generating and inferring a sensor data ontology using a user interface, a preprocessor and a user query, And a search module serving as a center of the search.

In addition, as shown in FIG. 15, if the flow of data is largely classified, it can be classified into a preprocessing process and a search process process for a user query. In Fig. 15, the dotted line represents that the ontology or database (DB) is referred to, and the solid line represents the flow of actual data.

That is, the data in the sensor data DB 210 undergoes a preprocessing process, and the annotation database (DB) generated as annotation database data processes the user query in the user interface to classify the keywords and the remaining query terms.

The OWL-type document annotation information data, which is a search result queryed by the keyword in the query management module, is transmitted to the ontology generation module, and the remaining query words are transmitted to the inference engine by generating an OWL-QL query.

In addition, the ontology generation module generates an OWL document ontology corresponding to the XML metadata, and transmits the ontology to the inference engine. The inference engine proceeds on the inference based on the OWL-QL query on the OWL document ontology. The OWL document ontology configuration classes 'Identifiers' returned by the inference result are delivered to the result processing module and refer to this 'Identifier' to provide the final result to the user.

The data analysis server 300 according to the present invention systematically classifies or groups the data and results obtained through analysis of the sensor data (or environmental information data) growth environment analysis service related to the local industry, that is, the mass sensor data analysis, And provide analysis and related services to the user through the user terminal 400. [

Also, the data analysis server 300 can determine the similarity and rankings of the product growth, the productivity of the product, and the product production trend among the results obtained through the analysis of the large-capacity sensor data, and provide meaningful information to the user using the service have.

In addition, the data analysis server 300 may perform data analysis based on the connectivity between weather and climate through data mining analysis.

In addition, the data analysis server 300 can provide local industry trend / prediction and visualization services to the user through the user terminal 400, as shown in FIG. In other words, by combining various kinds of visualization techniques, users can intuitively understand the data, and by designing and developing a visualization technique suitable for the use of the public service, The developed visualization algorithm can be applied to the service, and the service can be provided so that the user can intuitively grasp the data or analysis results through various visualization functions such as text, chart, and graph.

Meanwhile, the method for collecting and analyzing environmental information data related to the local industry according to an embodiment of the present invention can also be implemented as a computer-readable code on a computer-readable recording medium. A computer-readable recording medium includes all kinds of recording apparatuses in which data that can be read by a computer system is stored.

For example, the computer-readable recording medium includes a ROM, a RAM, a CD-ROM, a magnetic tape, a hard disk, a floppy disk, a removable storage device, a nonvolatile memory, , And optical data storage devices.

In addition, the computer readable recording medium may be distributed and executed in a computer system connected to a computer communication network, and may be stored and executed as a code readable in a distributed manner.

Although the preferred embodiments of the system and method for collecting and analyzing environmental information data related to the local industry according to the present invention have been described above, the present invention is not limited thereto, It is to be understood that the invention is not limited thereto and that various changes and modifications can be made within the scope of the appended drawings.

100: data collecting device, 110: data collecting module,
111: sensor, 120: data conversion module,
130: data transmission module, 140: control module,
150: power supply module, 160: data storage module,
200: data storage device, 210: sensor data DB,
220: index DB, 230: ontology DB,
300: data analysis server, 400: user terminal,
500: weather station weather information server

Claims (41)

At least one data collection device collecting and transmitting environmental information data related to a local industry using a plurality of sensors;
(OWL) ontology information data represented by a web ontology language (OWL) on the basis of the received environment information data received from the data collection device, A data storage device for storing the data; And
The OWL ontology information data is converted into an extensible markup language (XML) document by receiving the OWL ontology information data together with environment-specific environment information data stored in the data storage device, Generates a sensor data ontology using a user query input through a user terminal, semantically inferences and analyzes the generated sensor data ontology using a predetermined ontology inference engine, and provides the result to the user terminal A system for collecting and analyzing environmental information data associated with a local industry including an analysis server.
The data acquisition system according to claim 1,
A data collection module that includes a plurality of sensors and collects environmental information signals associated with the local industry sensed by each sensor;
A data conversion module for converting an environmental information analog signal sensed by each sensor of the data acquisition module to digital;
A data transmission module for transmitting the digitized environmental information data from the data conversion module through a wireless communication method; And
The data conversion module controls the operation of each sensor so that environment information signals related to the local industry are collected in real time through the data collection module and the environment information data is transmitted from the data conversion module to the data storage device in real- A system for collecting and analyzing environmental information data associated with a local industry comprising a control module for controlling operation.
3. The method of claim 2,
Wherein the wireless communication method comprises at least one of Wi-Fi communication, WiGig communication, Wibro communication, and WiMAX communication. A system for collecting and analyzing environmental information data.
3. The method of claim 2,
Wherein the data acquisition module, the data conversion module, the data transmission module, and the control module are mounted on an open source-based Arduino board. system.
3. The method of claim 2,
Further comprising a data storage module for storing environment information data transmitted from the data conversion module under the control of the control module in a DB format for each sensor and collecting and analyzing environmental information data related to the local industry ≪ / RTI >
The method according to claim 1,
Wherein the environment information data collected through the data collecting device is at least one of data of temperature, humidity, solar radiation, wind speed, direction, soil moisture and salinity data. A system for analysis.
The method according to claim 1,
The data storage device includes:
A sensor data DB configured to store environmental information data transmitted from the data collection device in a DB for each sensor;
An index DB consisting of a plurality of ontology DB tables for storing OWL ontology information data represented by a web ontology language (OWL) based on sensor-specific environment information data stored in the sensor data DB; And
And an ontology DB for selecting a domain through the index DB using a predetermined ontology editor and connecting the selected domain and attribute information between classes to form a database (DB) for a domain ontology for each sensor data based product, Wherein the system is adapted to collect and analyze environmental information data associated with the local industry.
8. The method of claim 7,
Wherein the plurality of ontology DB tables comprise an OWLOntology table, an OWLResource table, a Namespace table, an OWLIndividual table, an RDFTriple table, an OWLRelation table, an OWLProperty table, an OWLPropertyRestriction table, and an OWLClassRestriction table. A system for analysis.
8. The method of claim 7,
(ID) is specified for each instance of each concept applied to the index DB, and is stored using the specified identifier (ID) when the concepts are mutually quoted. And a system for analyzing.
8. The method of claim 7,
The top class stored in the ontology DB is defined as a 'Product' class. The subclass is defined as a 'Domain' class for classifying products produced through the local industry and a 'Descriptor' class for describing sensor data.
The 'Descriptor' class includes a 'Identifier' class indicating a unique number of the sensor data, a 'DataType' class indicating a type of sensor data, a 'Keyword' class indicating a search keyword, a 'Writer''Context' class which describes in detail the attributes of '
Wherein the 'Context' class comprises a 'Location' class that represents local information, a 'Spatio' class that represents spatial information, and a 'Temporal' class that represents time information. A system for analysis.
The method according to claim 1,
The data analysis server receives OWL ontology information data together with environment-specific environment information data stored in the data storage device and parses the OWL ontology information data to obtain information on classes, properties, and instances Extracting constraints on hierarchical information and properties, and converting hierarchical information on the extracted classes and properties into extensibility markup language (XML) documents. ≪ / RTI >
12. The method of claim 11,
The data analysis server stores an XML document including an OWL ontology information data layer information in a separate first storage module and stores the extracted remaining information in a separate second storage module Wherein the system is adapted to collect and analyze environmental information data associated with the local industry.
The method according to claim 1,
Wherein the ontology reasoning engine used in the data analysis server comprises an inference engine based on a semantic web.
The method according to claim 1,
The data analysis server analyzes the degree of similarity and rankings of the growth effects of the products produced through the domestic industry, the productivity of the products, and the production trends of the products among the semantically inferred and analyzed results through the predetermined ontology reasoning engine, And providing the result to the user terminal. ≪ Desc / Clms Page number 20 >
The method according to claim 1,
Wherein the data analysis server provides the user terminal with a result of semantically inferred and analyzed through the predetermined ontology reasoning engine in a visual form of at least one of text, A system for collecting and analyzing associated environmental information data.
The method according to claim 1,
Wherein the data analysis server converts the semantically inferred and analyzed result through the predetermined ontology inference engine according to the operating system of the user terminal and provides the converted result information to the corresponding user terminal. A system for collecting and analyzing.
The method according to claim 1,
Wherein the data analysis server receives information on normal operation and normal collection status of each sensor from the data collection device in real time and monitors the same.
The method according to claim 1,
Wherein the data analysis server provides a web-based monitoring service for extracting, analyzing, and inquiring data in a form desired by the user through the user terminal, and collecting and analyzing environmental information data related to the local industry For the system.
The method according to claim 1,
The data analysis server receives weather information data of an area in which the data collection device is installed from a weather station weather information providing server connected through a communication network, and stores the weather information in a database (DB) And comparing and analyzing past and present environment-specific environmental information data stored in the storage device to provide the user terminal with necessary weather information until the production completion time of the product. system.
The method according to claim 1,
Wherein the local industry comprises at least one of agricultural, livestock, and fishery industries.
CLAIMS 1. A method for collecting and analyzing environmental information data associated with a local industry using a system comprising at least one data collection device having a plurality of sensors, a data storage device and a data analysis server,
(a) collecting environmental information data related to a local industry sensed by each sensor through the data collection device and transmitting the collected environmental information data;
(b) receiving the environment information data transmitted in the step (a) through the data storage device, converting the environment information data into a database (DB) for each sensor, storing the database, and displaying the database in a web ontology language (OWL) Storing OWL ontology information data in a database (DB); And
(c) receiving the OWL ontology information data along with the sensor-specific environment information data stored in the step (b) through the data analysis server and converting the OWL ontology information data into an Extensible Markup Language (XML) document;
(d) generating a sensor data ontology using the extensible markup language (XML) document converted in step (c) and the user query input through the user terminal through the data analysis server; And
(e) semantically inferring and analyzing the sensor data ontology generated in the step (d) by using a predetermined ontology reasoning engine through the data analysis server, and providing the result to the user terminal A method for collecting and analyzing environmental information data associated with an industry.
22. The method of claim 21, wherein step (a)
(a-1) collecting environmental information signals associated with the local industry sensed by each sensor;
(a-2) converting the environmental information analog signal sensed by each sensor in step (a-1) into digital; And
(a-3) transmitting the digitized environmental information data in real-time in a wireless communication system in the step (a-2).
23. The method of claim 22,
Wherein the wireless communication method comprises at least one of Wi-Fi communication, WiGig communication, Wibro communication, and WiMAX communication. A method for collecting and analyzing environmental information data.
23. The method of claim 22,
Wherein the data collection device is mounted on an open source based Arduino board. ≪ RTI ID = 0.0 > 11. < / RTI >
23. The method of claim 22,
Further comprising the step of, after the step (a-2), converting the environment information data digitized in the step (a-2) into a database for each sensor and storing the data in a separate data storage module A method for collecting and analyzing environmental information data associated with an industry.
22. The method of claim 21,
Wherein the environment information data collected in step (a) is at least one of data of temperature, humidity, radiation amount, wind speed, direction, soil moisture and salinity data. Methods for analysis.
22. The method of claim 21, wherein step (b)
(b-1) storing environmental information data transmitted in the step (a) in a database (DB) for each sensor;
(b-2) storing OWL ontology information data represented by a web ontology language (OWL) in an index DB composed of a plurality of ontology DB tables based on the sensor-specific environment information data stored in the step (b-1); And
(b-3) a domain is selected through the index DB using a predetermined ontology editor, and the domain ontology for each sensor data-based product is connected to the selected domain and the attribute information between classes to form a database (DB) ≪ / RTI > wherein the method comprises the steps of: (a) collecting and analyzing environmental information data associated with a local industry.
28. The method of claim 27,
Wherein the plurality of ontology DB tables comprise an OWLOntology table, an OWLResource table, a Namespace table, an OWLIndividual table, an RDFTriple table, an OWLRelation table, an OWLProperty table, an OWLPropertyRestriction table, and an OWLClassRestriction table. Methods for analysis.
28. The method of claim 27,
(ID) is specified for each instance of each concept applied to the index DB and is stored using the specified identifier (ID) when the concepts are mutually quoted. And methods for analyzing.
28. The method of claim 27,
In the step (b-3), the top class is defined as a 'Product' class, and the subclass is defined as a 'Domain' class for classifying products produced through the domestic industry and a 'Descriptor' class for describing sensor data However,
The 'Descriptor' class includes a 'Identifier' class indicating a unique number of the sensor data, a 'DataType' class indicating a type of sensor data, a 'Keyword' class indicating a search keyword, a 'Writer' A 'Context' class that describes in detail the attributes of the '
Wherein the 'Context' class comprises a 'Location' class that represents local information, a 'Spatio' class that represents spatial information, and a 'Temporal' class that represents time information. Methods for analysis.
22. The method of claim 21,
In the step (c), the data analysis server receives OWL ontology information data together with environmental information data per sensor stored in the step (b), parses the OWL ontology information data, and classifies, Extracts information on an instance, constraints on hierarchical information and properties, and then converts hierarchical information on the extracted classes and properties into an extensible markup language (XML) document. A method for collecting and analyzing associated environmental information data.
32. The method of claim 31,
After the step (c), an extensibility markup language (XML) document including hierarchical information of the OWL ontology information data is stored in a separate first storage module through the data analysis server, Further comprising the steps of: storing the environmental information in a second storage module in a separate second storage module.
22. The method of claim 21,
Wherein the pre-established ontology reasoning engine comprises a semantic web-based reasoning engine in the step (e).
22. The method of claim 21,
In the step (e), the data analysis server analyzes the results of semantically inferred and analyzed through the pre-established ontology reasoning engine, and analyzes the growth effect of the products produced through the domestic industry, the productivity of the products, Analyzing the similarity and ranking, and providing the result to the user terminal. ≪ Desc / Clms Page number 21 >
22. The method of claim 21,
In the step (e), the data analysis server may provide the user terminal with a result of semantically inferred and analyzed through the predetermined ontology reasoning engine, in a visual form of at least one of a text, a chart, and a graph ≪ / RTI > wherein the environmental information data is associated with a local industry.
22. The method of claim 21,
Wherein the data analysis server converts the semantically inferred and analyzed results through the predetermined ontology reasoning engine according to an operating system of the user terminal and provides the converted results to the corresponding user terminal in step (e) A method for collecting and analyzing environmental information data associated with an industry.
22. The method of claim 21,
Obtaining information on normal operation and normal collection of each sensor through the data collection device after the step (a), and transmitting the acquired information in real time;
And collecting and analyzing environmental information data related to the local industry, wherein the information about the normal operation and the normal collection of each sensor is received and monitored in real time through the data analysis server. Way.
22. The method of claim 21,
After the step (e), the data analysis server further includes a step of providing a web-based monitoring service so that the user can extract, analyze and inquire data in a desired form through the user terminal A method for collecting and analyzing environmental information data associated with a local industry.
22. The method of claim 21,
Receiving weather information data of a region in which the data collection device is installed from a separate weather station weather information providing server through the data analysis server after the step (e) and converting the weather information data into a database (DB)
Comparing the weather information of the stored corresponding region with the past and current sensor-specific environment information data stored in the step (b) through the data analysis server, and providing the weather information required until the production completion time of the product to the user terminal Further comprising the steps < RTI ID = 0.0 > of: < / RTI > collecting and analyzing environmental information data associated with the local industry.
22. The method of claim 21,
Wherein the local industry comprises at least one of agriculture, livestock industry, and fishery industry.
40. A computer-readable recording medium having recorded thereon a computer-executable method of any one of claims 21 to 40.

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