KR20150134811A - Sensor web system based on social data - Google Patents

Abstract

Provided is a sensor web system based on social data, configured to utilize social big data which is a great quantity of social data on a social network. The sensor web system based on social data according to the present invention comprises: a social data input unit for receiving social data on a social network through a network; a social sensor measurement unit for analyzing the received social data to measure social sensor data; an external data recognition unit for receiving external data through the network; a sensor data integration and analysis unit for drawing values by index item for the social sensor data by using index items based on the external data; and a sensor information visualization unit for providing the values by index item for the social sensor data through the network.

Description

[0002] Sensor web system based on social data [

The present invention relates to a sensor web system based on social data, and more particularly, to a sensor web system that can utilize social big data, which is a large amount of social data on a social network.

The present invention is derived from the research conducted by Korea Institute of Construction Technology and conducted by Saltlux Co., Ltd. as part of the international joint technology development project of the Ministry of Commerce, Industry and Energy.

[Research period: 2013. 06. 01 ~ 2014. 05. 31, Research institute: Korea IT Industry Promotion Agency, Research title: Sensor-based citizen observation community development to improve the quality of life of city - CiTi-SENSE platform Architecture design and development of urban environment information sensor data Core Ontology model -, task number: NO15800207]

In addition to the basic requirements for living in health facilities, education facilities, security / safety, traffic, etc., various information related to life satisfaction such as environment (climate, air quality, water quality) It should be analyzed. Usually, this information is obtained through sensor data measured by physical sensors through the sensor web, survey data, and related research activities. However, in the case of physical sensors, it is advantageous to measure the correct value, but sensor data can be acquired only in the directly installed region, and the measurable range is limited due to the constraints such as cost and installable environment. In addition, research and other activities take a long time to analyze and analyze, making it difficult for people to provide the information they want in real time.

Disclosure of Invention Technical Problem [8] Accordingly, the present invention has been made in view of the above problems, and it is an object of the present invention to provide a sensor web system based on social data that can utilize social big data, which is a large amount of social data on a social network, There is.

In order to solve the above technical problem, there is provided a sensor web system based on a social data, which can perform residential environment or commercial analysis by utilizing social big data, which is a large amount of social data on a social network.

The present invention provides a sensor network system based on a social data, comprising: a social data input unit for receiving social data on a social network through a network; A social sensor measuring unit for analyzing the inputted social data and measuring the social sensor data; An external data receiving unit for receiving external data through the network; A sensor data integration analyzer for deriving an index item value for the social sensor data by using an index number item based on the external data; And a sensor information visualization unit for providing an index item value for the social sensor data through the network.

A user input unit for receiving a user request through the network; And a sensor data comparator configured to normalize the external data and the derived index value for the extracted social sensor data to calculate a regional ranking of the user's request, Can be provided together with the regional ranking of the needs of the users.

The sensor data comparison and measurement unit may calculate the regional ranking by reflecting the weight on the value of the index item for the derived social sensor data based on the demand of the user.

Wherein the social sensor measuring unit comprises: a social sensor measurement value analyzer for measuring the social sensor data; And a social sensor-related information recognition unit for recognizing social sensor-related information including a link or an image related to the social sensor data.

The sensor information visualization unit may provide the social sensor-related information together through the network.

The external data may be sensor data of a physical sensor or database-based geospatial information.

The social sensor measurement value analyzing unit may include a subject sensing module for sensing a subject from the inputted social data; A subject clustering module for clustering the detected subject; And a social data conversion module for converting the social data into a measurement, a time, or a geographical location based on the collected topic and extracted numerical values can do.

The subject detection module can detect the subject from morphological analysis and object name recognition from the inputted social data.

The subject clustering module may group the detected subject based on a document frequency (DF) and a term frequency (TF).

According to another aspect of the present invention, there is provided a sensor web system based on a social data, comprising: a social data input unit for receiving social data on a social network through a network; An external data receiving unit for receiving external data including sensor data of a physical sensor or geospatial information in a database through the network; A social sensor measuring unit for analyzing the inputted social data and measuring the social sensor data; A social data analyzer for converting or correcting the social sensor data based on the external data; And a sensor information providing unit for providing the external data and the converted or corrected social sensor data.

The sensor information providing unit may provide the external data and the converted or corrected social sensor data by leveling and summing the data.

And a sensor data combining unit for combining the converted or corrected social sensor data with a space or a time not included in the external data with the external data to form integrated sensor data, Sensor data can be provided.

The social data based sensor web system according to the present invention By using social data as sensor data measured through a physical sensor, it is possible to supplement one or more physical sensors to the entire sensor web to supplement the sensor data for the area, time, etc., which the physical sensor can not detect, It is possible to expand the measurement range of the physical sensor, which is insufficient due to constraints such as an installable environment.

Also, the sensor web system according to the present invention utilizes social data as sensor data measured through a physical sensor, recognizes the sensor web as one or a plurality of physical sensors, and provides a sensor web system with a wider range of measurement and a complementary sensor web system can do.

In addition, the sensor web system according to the present invention can provide rankings based on the social data and the external data based on the request of the user.

1 is a conceptual diagram of a sensor web in which a social sensor system according to an embodiment of the present invention is utilized.
2 is a schematic diagram showing the configuration of a sensor web system according to an embodiment of the present invention.
3 is a schematic view showing a configuration of a social sensor measurement unit of a sensor web system according to an embodiment of the present invention.
FIG. 4 is a schematic diagram illustrating a configuration and analysis process of a social sensor measurement value analysis unit of a sensor web system according to an embodiment of the present invention.
FIG. 5 is a schematic diagram illustrating a configuration and analysis process of a social sensor measurement value analysis unit of a sensor web system according to an embodiment of the present invention.
6 is a schematic diagram showing the configuration of a sensor web system according to another embodiment of the present invention.
7 is a schematic view showing a configuration of a sensor web system according to another embodiment of the present invention.
8 is a schematic diagram showing the configuration of an external data recognizing unit according to an embodiment of the present invention.

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS Hereinafter, a sensor data base based on a social data according to embodiments of the present invention will be described in detail with reference to the accompanying drawings. However, the present invention is not limited to the following embodiments, The present invention may be embodied in various other forms without departing from the spirit of the invention. That is, it is to be understood that the specific structural or functional descriptions are merely illustrative of the embodiments of the present invention, and that the embodiments of the present invention may be embodied in various forms and are construed as being limited to the embodiments described herein No. It is to be understood that the invention is intended to cover all modifications, equivalents, and alternatives falling within the spirit and scope of the invention, as defined by the following claims.

The terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the invention. The singular expressions include plural expressions unless the context clearly dictates otherwise. In the present application, the terms "comprises ", or" comprising ", etc. are intended to specify the presence of stated features, integers, steps, operations, elements, or combinations thereof, But do not preclude the presence or addition of steps, operations, elements, or combinations thereof.

Unless defined otherwise, all terms used herein, including technical or scientific terms, have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs. Terms such as those defined in commonly used dictionaries are to be interpreted as having a meaning consistent with the meaning in the context of the relevant art and are not to be construed as ideal or overly formal in meaning unless expressly defined in the present application .

In the present specification, social data refers to data constituting a stream that is transmitted to the world in real time on a social network. For example, conventional webs are made up of static files, but social data generated by social network services on social networks, such as Twitter, have a dynamic flow of delivering very small amounts of information to the world in real time. That is, however, social data can have a dynamic flow on a social network.

In this specification, the term 'social sensor' means to operate as a physical sensor for obtaining space-time sensor data by utilizing social data. That is, a single social sensor can monitor conditions at different locations, such as a single physical sensor. In addition, the term "social sensor model" means a language based on which a social sensor can be implemented. That is, the social sensor can monitor the condition by the social sensor model constituting the social sensor, such that the physical sensor monitors the condition by the components constituting the sensor.

1 is a conceptual diagram of a sensor web in which a social sensor system according to an embodiment of the present invention is utilized.

Referring to FIG. 1, a conceptual diagram illustrating the concept of a sensor web is shown. Sensor Web is a sensor network that is easy to access the web and sensor data measured through physical sensors that can be accessed and discovered using standard protocols and application program interfaces (APIs). In order to provide various services in a ubiquitous environment, a geosensor capable of directly or indirectly acquiring a position, such as an RFID reader, a mobile RFID, a sensor node telematics terminal, a CCTV, etc., (GeoSensor), there is an increasing research to utilize the space-time sensing data of a sensor having a global positioning system (GPS) function. OGC has established SWE (Sensor Web Enablement) as a standard for using all types of sensor systems and web-connected physical sensors.

A sensor network is a network that is accessible to a variety of spatial distributed devices using sensors that monitor conditions at different locations, such as temperature, sound, vibration, pressure, motion, or contaminants. The sensor web refers to web accessible sensor networks and archived sensor data that can be discovered and accessed using standard protocols and application program interfaces (APIs). For example, sensor webs can be connected to flood gauges, air pollution monitors, high-volume strain gages, mobile heart monitors, webcams, satellite-based geo-imaging devices, and numerous sensor and sensor systems.

Accordingly, the sensor web can be applied to science, environmental monitoring, traffic management, public safety, facility security, disaster management, disease management, device supervision and data collection operations, industrial control, facility management, and various forms of activities . The sensor web can acquire data from a region directly installed by a physical sensor that can be accessed via the web.

2 is a schematic diagram showing the configuration of a sensor web system according to an embodiment of the present invention.

2, the sensor web system 1000 includes a social data input unit 100 for receiving social data on the social network 1 via the network 10. [ The network 10 may be a wired Internet service, a local area network (LAN), a wide area network (WAN), an intranet, a wireless Internet service, a mobile computing service, a wireless data communication service, a wireless Internet access service, And can transmit / receive data through wire / wireless. When the network 10 is connected to a smart phone or a tablet, the network 10 may be a wireless data communication service such as 3G, long term evolution (LTE), wireless LAN such as Wi-Fi, Bluetooth,

The social data input unit 100 can collect social data generated on a social network, such as a service such as Twitter and Facebook, in real time using an API or a web page collector provided by a social network service. The social data collected by the social data input unit 100 is transmitted to the social sensor measurement unit 200.

The social sensor measuring unit 200 can analyze the collected social data, measure the social sensor data, and recognize the information related to the social sensor. The social sensor measuring unit 200 senses a subject from the texts included in the collected social data through morphological analysis and object name recognition and outputs the sensed subject to a document frequency (DF) and word frequency (TF , Term Frequency) to generate clustering. In addition, the social sensor measurement unit 200 may convert the social data into a measurement, a time, or a geographic location based on the clustering subject. Alternatively, the social sensor measuring unit 200 can extract the numerical value of the social data through its own analysis of the social data, and convert the social data into the measured value, time, or geographical position based on the extracted numerical value have.

For example, the social sensor measuring unit 200 can convert the measured value, time, or geographical position into the social data in consideration of the amount of the social data and the frequency of the subject included in the social data, You can convert the included values to a measure, time, or geographic location. For example, the social sensor measuring unit 200 may provide analysis results related to fine dust in the social data. In this case, the information on the fine dust and various main subjects related thereto, information on the area and time, Information about the amount of the dust, and quantitative analysis of the social data related to the fine dust. The analysis result related to the fine dust may include various information related to the fine dust as well as the information corresponding to the physical sensor such as the actual fine dust concentration.

In addition, the social sensor measuring unit 200 can provide statistical results regarding the users of the social network through analysis of the entire social data. For example, the social sensor measurement unit 200 can provide information on the number of users of the social network in each region or time, through analysis of the entire social data.

In addition, the social sensor measuring unit 200 may update the social sensor model or generate the social sensor model based on the analysis result of the social data. The social sensor model refers to a model that can be implemented based on Seosor Model Language (OGC) of the Open Geospatial Consortium (OGC), and can implement a social sensor that can obtain similar results as sensor data of a physical sensor from social data .

For example, the social sensor measurement unit 200 can update the existing social sensor model based on the analysis result of the social data, that is, the grouped subject, the extracted numerical value, A new social sensor model can be created when there are subjects / numerical values that can not be applied to the social sensor model.

For example, in the case where there is only a social sensor model for yellow sand in the past, a social sensor model for fine dust can be generated when information related to fine dust other than dust is found as a result of analysis of social data.

For example, if you have a social sensor model for DSS, you can update the social sensor model for DSS if new keywords related to DSS are extracted. In the past, there was an analytical model for the concentration in the social sensor model for the yellow dust. However, when the information related to the heavy metal is analyzed in the social data on the sulfur, an analytical model for the heavy metals contained in the yellow dust in the social sensor model for the yellow dust You can update it.

The social sensor measurement unit 200 may generate or update the social sensor model by reflecting the analyzed social data in real time, but may accumulate the analyzed social data for a certain period of time and generate or update the social sensor model after a predetermined period of time It is possible. The social data may reflect the information in real time, but the information may be reflected at a time difference according to the user. Accordingly, in consideration of this point, the social sensor measurement unit 200 may generate or update the social sensor model after accumulating the analyzed social data for a predetermined period.

Also in this process, the distribution of the information according to the time lag and the time lag where the user's reaction to the same information appears can also be used together to generate or update the social sensor model. In this way, even when the information of the users of the social network for the specific conditions appears in the social data, the social sensor model can be analyzed through the information displayed at the early stage. Can be done.

When the social sensor measurement unit 200 generates or updates the social sensor model, the measurement result of the sensor web as shown in FIG. 1 or the statistical data having the past information (for example, weather information, traffic information , Population information, flow population information, etc.) can be used to create or update the social sensor model.

For example, the amount of social data for a particular condition may vary depending on the number of users of the social network. The number of social network users may vary from region to region, or from time to time. Thus, the amount of social data for a specific condition can be normalized by reflecting such information. The number of users of the social network by region or time may be obtained through the use of the statistical data or the analysis of the total social data by the social sensor measuring unit 200.

Also, in this process, a social sensor model capable of matching social data to sensor data can be created or updated by reflecting sensor data measured with a physical sensor or various statistical data obtained by actual investigation.

The social sensor measurement unit 200 can measure the social sensor data from the analyzed social data based on the social sensor model. The social sensor data means sensor data obtained from a physical sensor or sensor data obtained from social data, which can be matched with an irradiated statistical data. That is, the social sensor measuring unit 200 may convert the analyzed social data into a measurement, a time, or a geographical location based on the collected subject and extracted numerical values.

The social sensor measurement unit 200 may convert the analyzed social data based on the social sensor model into social sensor data to support the OGC's Sensor Web Enablement (SWE) interface.

The social sensor data measured by the social sensor measuring unit 200 from the social data may be stored in the social data store 300.

The social sensor measurement unit 200 measures social sensor data based on the social sensor model, for example, based on the amount of the social data referred to by the users on the social network for a specific condition, Can be measured.

The social sensor measurement unit 200 can recognize and collect social cell-related information including a link or an image related to the measured social sensor data.

The social sensor data measured by the social sensor measuring unit 200 and the collected social sensor related information may be stored in the social data store 300. The social data store 300 may be a space capable of storing data in any form such as NoSQL, relational database, file system, or the like. The social data storage 300 may be a logical storage device, a storage unit logically dividing one storage device or a plurality of storage devices, or a storage device physically separated or a logically divided one .

The external data recognition unit 400 can recognize and collect the external data 3 via the network. The external data 3 may be sensor data of a physical sensor connected to a social web or database or geospatial information.

The sensor data integration analyzer 500 derives the value of the index item for the social sensor data measured by the social sensor measurement unit 200 using index numbers based on the collected external data 3 can do. For example, the sensor data integration analyzer 500 can derive the measured value of the social sensor data by the index items such as the traffic environment, the education facility, the sanitation, the floating population, the occupation, and the distribution of the commercial value. In this case, each index item may be measurable by the social sensor measuring unit 200, but it is also possible to obtain an accurate value through the external data 3, for example, a physical sensor, Information can also be utilized. The sensor data integration analyzer 500 refers to the external data 3 such as the sensor data of the physical sensor or the database of the geospatial information recognized through the external data recognition unit 400, Normalize and derive the value for each index item. , All these data are synthesized and normalized, and the value of each index is derived.

The sensor web system 1000 includes a user input unit 600 and external data 3 for receiving the request of the user 5 via the network 10 and the external data 3 for the social sensor data derived from the sensor data integration analysis unit 500. [ And a sensor data comparison measuring unit 700 for normalizing the values of the exponent items and calculating the ranking according to the request of the user 5 inputted from the user input unit 600. [

The sensor data comparison measuring unit 700 can calculate the ranking according to the region by reflecting the weight on the value of the index item for the derived social sensor data based on the request of the user 5. [ For example, the sensor data comparison and measurement unit 700 may be configured to measure the air pollution level in accordance with the requirements of the user 5, such as preferring an area having a low level of air pollution or preferring an area where a well- It is possible to derive the ranking by region by reflecting the weight on the item-specific value. For example, when the request of the user 5 is a residential environment analysis, the sensor data comparison measuring unit 700 can select and analyze index items such as a traffic environment, an educational facility, and sanitation, When the demand of the user 5 is a commercial analysis, the user can select the exponential items such as the floating population, the occupation,

The calculated regional ranking can be stored in the integrated sensor data store 800. The integrated social data store 800 may be a space capable of storing data in any form such as NoSQL, relational database, file system, or the like. The integrated social data store 800 may be a logically separated storage device or may be a storage unit that logically separates one or a plurality of storage devices or a storage unit that is physically separated or a logical unit It can be a part.

The social sensor repository 300 and the integrated sensor data repository 800 may be logically separated storage units or may be divided into logically separate storage units or logically separated physical units, And may be part of one distinguishing unit. For example, the social sensor repository 300 and the integrated sensor data repository 800 may be part of one storage unit or logically distinct division unit, each physically separated. In this case, the social sensor repository 300 may be a portion where the measured social sensor data and the social sensor related information among the integrated sensor data repository 800 are stored.

The sensor information visualization unit 900 can provide the user 5 with the index value for the derived social sensor data through the network 10. [ The sensor information visualization unit 900 can provide the index value for the derived social sensor data together with the regional ranking for the request of the user 5. [ The sensor information visualization unit 900 can also provide the social sensor related information recognized by the social sensor measurement unit 200 through the network 10. [ The sensor information visualization unit 900 may provide an API (Application Program Interface) supporting the HTTP-based communication to the user 5. [

3 is a schematic view showing a configuration of a social sensor measurement unit of a sensor web system according to an embodiment of the present invention.

Referring to FIG. 3, the social sensor measurement unit 200 includes a social sensor measurement value analysis unit 210 and a social sensor related information recognition unit 220.

The social sensor measurement value analyzer 210 may analyze the collected social data to measure the social sensor data and recognize the information related to the social sensor. The social sensor measurement value analysis unit 210 detects a subject from morphological analysis and object name recognition from the text included in the collected social data, and classifies the detected subject into groups based on the document frequency (DF and word frequency (TF) The social sensor measurement value analyzer 210 may convert the social data into a measurement, a time, or a geographic location based on the grouped subject matter. The value analyzer 210 can extract the numerical value of the social data through its own analysis of the social data and convert the social data into the measured value, time, or geographical position based on the extracted numerical value.

For example, the social sensor measurement value analyzer 210 may convert the measured value, time, or geographical position of the social data into the social data, in consideration of the amount of the social data and the frequency of the subject included in the social data, You can convert the values contained in itself to a measure, time, or geographic location.

In addition, the social sensor measurement value analyzer 210 may provide statistical results regarding users of the social network through analysis of the entire social data. For example, the social sensor measurement value analysis unit 210 may provide information on the number of users of the social network in each region or time, through analysis of the entire social data.

In addition, the social sensor measurement value analyzer 210 may update the social sensor model or generate the social sensor model based on the analysis result of the social data. A social sensor model is a model that can be implemented based on OGC's SensorML and can implement a social sensor that can obtain similar results as sensor data of a physical sensor from social data.

For example, the social sensor measurement value analyzer 210 can update the existing social sensor model based on the analysis result of the social data, that is, the grouped topic, the extracted numerical value, If there are subjects / values that can not be applied to the sensor model, a new social sensor model can be created.

The social sensor measurement value analyzer 210 may generate or update the social sensor model by reflecting the analyzed social data in real time. However, the social sensor measurement value analyzer 210 may accumulate the analyzed social data for a certain period of time, You can also update. The social data may reflect the information in real time, but the information may be reflected at a time difference according to the user. Therefore, in consideration of this point, the social sensor measurement value analyzer 210 may generate or update the social sensor model after accumulating the analyzed social data for a predetermined period.

Also in this process, the distribution of the information according to the time lag and the time lag where the user's reaction to the same information appears can also be used together to generate or update the social sensor model. In this way, even when the information of the users of the social network for the specific conditions appears in the social data, the social sensor model can be analyzed through the information displayed at the early stage. Can be done.

When generating or updating the social sensor model, the social sensor measurement value analyzer 210 may output the measurement result of the sensor web as shown in FIG. 1, or statistical data (for example, weather information, Traffic information, population information, floating population information, etc.) can be used to create or update the social sensor model.

For example, the amount of social data for a particular condition may vary depending on the number of users of the social network. The number of social network users may vary from region to region, or from time to time. Thus, the amount of social data for a specific condition can be normalized by reflecting such information. The number of users of the social network by region or time may be obtained through the use of the statistical data or the analysis of the total social data by the social sensor measurement value analyzer 210.

Also, in this process, a social sensor model capable of matching social data to sensor data can be created or updated by reflecting sensor data measured with a physical sensor or various statistical data obtained by actual investigation.

The social sensor measurement value analysis unit 210 may measure the social sensor data from the analyzed social data based on the social sensor model. That is, the social sensor measurement value analyzer 210 may convert the analyzed social data into a measurement value, a time, or a geographical location based on the collected subject and extracted numerical values.

The social sensor measurement value analyzer 210 may convert the social data analyzed based on the social sensor model into social sensor data to support the OGC's Sensor Web Enablement (SWE) interface. The social sensor data measured by the social sensor measurement value analyzer 210 from the social data may be stored in the social data store 300.

The social sensor measurement value analyzing unit 210 analyzes the social sensor measurement value based on the social sensor model, for example, the amount of social data referred to by the users on the social network for a specific condition, Data can be measured.

The social sensor-related information recognition unit 220 can recognize and collect social-cell-related information including a link or an image related to the measured social sensor data.

The social sensor-related information recognized and collected by the social sensor-related information recognition unit 220 may be stored in the social data storage 300.

FIG. 4 is a schematic diagram illustrating a configuration and analysis process of a social sensor measurement value analysis unit of a sensor web system according to an embodiment of the present invention.

4, the social sensor measurement value analysis unit 210 includes a subject detection module 212, a subject grouping module 214, and a numerical value conversion module 216. [ The subject sensing module 212 may sense the subject from the entered social data. The subject clustering module 214 may cluster the detected subject matter. The numeric conversion module 216 can extract numerical values from the inputted social data.

The subject detection module 212 can detect the subject from morphological analysis and object name recognition from the inputted social data. The subject clustering module 212 may group the detected subject based on a document frequency (DF) and a term frequency (TF). Clustering topics can represent the nature of the information contained in the social data in the form of a word vector. The word vector may include keywords indicating characteristics of the social data and a weight of each keyword. The weights are obtained by using the word frequency (TF) and the term frequency of each keyword and the document frequency (DF) or frequency of each keyword in the Internet document set (IDF, Inverse Document Frequency). Word frequency is a measure of how much a particular keyword represents the content of social data as the number of occurrences of a particular keyword in individual social data. In addition, the document frequency indicates the ratio of the number of Internet documents in which the specific keyword appears in the social data, the reverse document frequency is inverse to the document frequency, the keyword in which the reverse document frequency is low in the social data is different from the social data And the ability to distinguish them from others.

The numerical value conversion module 216 may extract information related to the numerical value of the inputted social data. For example, the numeric conversion module 216 may extract sensor data of independent physical sensors not connected to the sensor web or numerical information individually collected by users of the social network. For example, as recent interest in radioactivity increases, individual users may use radioactivity measurement sensors to measure radiation levels, refer to them as social data on a social network, or to collect such information . In this way, a physical sensor not connected to the sensor web can be used as a physical sensor connected to the sensor web through analysis of the social data.

The numerical value conversion module 216 compares the subject grouped by the physical sensor subject grouping module 214 in which the inputted social data is contained and the numerical value extracted from the numeric value conversion module 2160 to the social data conversion module 218, May be used to create or update a social sensor model, as described above, or may be used to transform social sensor data.

The social data conversion module 218 can convert social data analyzed into numerical values extracted from the subject and numerical conversion module 2160 in the subject cluster module 214 based on the social sensor model into social sensor data . The social sensor data means sensor data obtained from a physical sensor or sensor data obtained from social data, which can be matched with an irradiated statistical data. That is, the social data conversion module 218 may convert the analyzed social data into a measurement, a time, or a geographic location based on the clustering subject and the extracted numerical value.

The social data conversion module 218 may convert the analyzed social data based on the social sensor model into social sensor data to support the OGC's Sensor Web Enablement (SWE) interface.

The social sensor data generated by converting the social data in the social data conversion module 218 may be stored in the social data storage 300.

FIG. 5 is a schematic diagram illustrating a configuration and analysis process of a social sensor measurement value analysis unit of a sensor web system according to an embodiment of the present invention.

5, the social sensor measurement value analyzer 210a includes a subject detection module 212, a subject grouping module 214, and a numeric conversion module 216. [ The subject sensing module 212 may sense the subject from the entered social data. The subject clustering module 214 may cluster the detected subject matter. The numeric conversion module 216 may extract numerical values from the inputted social data based on the clustering subjects.

The social sensor measurement value analyzer 210 shown in FIG. 4 and the social sensor measured value analyzer 210a shown in FIG. 5 have substantially the same components as the subject sensor module 212, the subject cluster module 214, In the same social sensor measurement value analysis unit having the conversion module 216, the analysis process may be different depending on the nature of the social data.

For example, when the inputted social data itself includes information related to the numerical value, the analysis is performed like the social sensor measured value analysis unit 210 shown in FIG. 4, and the statistical meaning of individual social data in the social data In the case of analysis, the analysis can be performed in the same manner as the social sensor measurement value analysis unit 210a shown in FIG.

For example, the number of social data mentioned in relation to a specific condition, the number of social data mentioned in relation to a specific condition in each region, the number of social data mentioned in a specific condition in each time, the number of social network users in each region or hour The analysis can be performed in the same manner as the social sensor measurement value analysis unit 210a shown in FIG. In this case, the numerical analysis module 216 analyzes information on the number of social data and the number of users, considering not only the statistical analysis of the number of social data but also the overlapping number by retouching, quoting, can do.

The subjects grouped in the subject clustering module 214 and the values extracted from the numeric conversion module 216 based thereon are transmitted to the social data conversion module 218 and used to generate or update the social sensor model as described above , And can be used to transform social sensor data.

6 is a schematic diagram showing the configuration of a sensor web system according to another embodiment of the present invention.

6, the sensor web system 2000 includes a social data input unit 100, a social sensor measurement unit 200, a social data storage 300, an external data recognition unit 400, and an integrated sensor data storage 800. [ . ≪ / RTI > The social data input unit 100, the social sensor measurement unit 200, the social data storage 300, the external data recognition unit 400, and the integrated sensor data storage 800 are identical or similar to those described in FIGS. The same description will be omitted.

The external data recognition unit 400 can receive external data 3 including sensor data of a physical sensor or geospatial information in a database through the network 10.

The social data analysis unit 510 may convert or correct the social sensor data based on the inputted external data 3. For example, the social sensor data measured by the social sensor measuring unit 200 may be different from actual sensor data of the physical sensor or database-based geospatial information. Therefore, the social data analysis unit 510 can refer to the inputted external data 3 to convert or correct the social sensor data to approximate sensor data of actual physical sensors or database-based geospatial information. The social data analyzing unit 510 may convert or convert the social sensor data so as to match the input external data 3 with respect to a common region or a common time with the social sensor data measured by the social sensor measuring unit 200, A conversion / correction model to be corrected can be generated, and the measured total social sensor data can be converted or corrected.

2, the social data analysis unit 510 may use the index numbers based on the collected external data 3 to determine the social sensor measurement unit 200 ) Can be deduced from the measured value of the social sensor data.

The sensor information providing unit 910 can provide the user 5 with the inputted external data 3 and the converted or corrected social sensor data through the network 10. [ The sensor information providing unit 910 may separately provide the converted external data 3 and the converted or corrected social sensor data to the user 5 but may also output the inputted external data 3 and the converted or corrected social sensor Data may be leveled and summed and provided. For example, when a specific numerical value is described in the external data 3 and a more subjective numerical value such as an evaluation is described in the converted or corrected social sensor data, the sensor information providing unit 910 equalizes them They can be provided in total. For example, even if the values of the sensor data of the physical sensors are the same, there may be a difference in response to the difference in season / time or region, and vice versa. Therefore, when there are results in which the sensor data of the physical sensor and responses to the sensor data are staggered, it may be difficult for the user 5 to judge, so that they can be leveled and summed to provide a judgment of the user 5 .

7 is a schematic view showing a configuration of a sensor web system according to another embodiment of the present invention. The description of FIG. 7 which is the same as the description of FIG. 6 may be omitted.

Referring to FIG. 7, the sensor web system 2002 may further include a sensor data combining unit 710.

The sensor data combining unit 710 can combine the converted or corrected social sensor data with the external data 3 inputted to the space or time not included in the inputted external data 3 to generate the integrated sensor data . The sensor information providing unit 910 can provide the generated integrated sensor data to the user through the network 10. [

That is, the sensor web system 2002 recognizes both the external data 3 and the social data as physical sensors, and can provide the user 5 with the sensor web system 2002 as a single sensor web.

For example, there may be differences between weather forecast information and actual weather conditions for specific weather conditions. However, since the social data reflects the reference of the social network users to the actual weather situation, it can provide accurate weather conditions in real time. Especially, it is possible to estimate the specificity of the weather phenomenon only in a relatively small area, or to collect the actual weather conditions at the Meteorological Agency, It can provide accurate weather conditions in real time.

For example, in the case of traffic information, traffic information may not be specifically provided in a specific area, or may be difficult to be actually sensed. However, since the social data reflects the reference of the social network users to the actual traffic situation, accurate traffic information can be provided in real time.

Alternatively, the sensor data combining unit 710 may be configured to equalize the converted external data 3 and the converted or corrected social sensor data, to weight the added external data 3, and to add the converted external data 3 and the converted or corrected social sensor data Can be combined. Alternatively, the sensor data combining unit 710 may provide both the input external data 3 and the converted or corrected social sensor data together.

As described above, the sensor web system according to the present invention utilizes the social data as sensor data measured through the physical sensor to further support one or a plurality of physical sensors to the entire sensor web, Time and the like can be supplemented, and the measurement range of the deficient physical sensor can be widened due to the constraints such as cost and installable environment.

Also, the sensor web system according to the present invention utilizes social data as sensor data measured through a physical sensor, recognizes the sensor web as one or a plurality of physical sensors, and provides a sensor web system with a wider range of measurement and a complementary sensor web system can do.

8 is a schematic diagram showing the configuration of an external data recognizing unit according to an embodiment of the present invention.

Referring to FIG. 8, the external data recognition unit 400 includes a physical sensor measurement unit 410 and a geospatial information collection unit 420. The physical sensor measurement unit 410 is connected to the physical sensor 3a through the network 10 to recognize the physical sensor 3a and collect sensor data. That is, the physical sensor measuring unit 410 and the physical sensor 3a may correspond to the normal sensor web shown in FIG. The geospatial information collection unit 420 can search and collect the database geospatial information 3b. The database-formatted geospatial information (3b) is all information including information on the geospatial space that can be directly used as a database. Statistical data such as climate records, results of population sensitivities, and questionnaires or related research data from individual or multiple regions may all be included.

Further, the embodiments of the present invention can be made into a program executable in a computer system. In addition, the program read from the computer-readable recording medium containing the program can be executed in the digital computer system.

Examples of the computer-readable recording medium include a ROM, a RAM, a CD-ROM, a DVD-ROM, a magnetic tape, a floppy disk, an optical data storage device and the like. Further, a carrier wave (for example, And the like. The computer readable recording medium may also be distributed over a networked computer system so that computer readable code can be stored and executed in a distributed manner. And functional programs, codes, and code segments for implementing the present invention can be easily inferred by programmers skilled in the art to which the present invention pertains.

1: Social network, 3: External data, 3a: Physical sensor, 3b: Geospatial information, 5: User, 10: Network, 100: Social data input unit, 200: Social sensor measurement unit, 300: A sensor data comparison unit 710 a sensor data combination unit 800 an integrated sensor data store 900 a sensor data comparison unit 900 a sensor data integration unit 800 a sensor data integration unit 900 a sensor data integration unit Information visualization unit 910: sensor information providing unit 1000, 2000, 2002: social sensor system

Claims (12)

A social data input unit for receiving social data on a social network through a network;
A social sensor measuring unit for analyzing the inputted social data and measuring the social sensor data;
An external data receiving unit for receiving external data through the network;
A sensor data integration analyzer for deriving an index item value for the social sensor data by using an index number item based on the external data; And
And a sensor information visualization unit for providing an index item-specific value of the social sensor data through the network. The method according to claim 1,
A user input unit for receiving a user request through the network;
And a sensor data comparison and measurement unit for normalizing the external data and the derived index value for the derived social sensor data and calculating a regional ranking for the user's request,
Wherein the sensor information visualization unit is provided with a ranking according to a region of the user's request. 3. The method of claim 2,
Wherein the sensor data comparison and measurement unit comprises:
Based on the demand of the user, the weights are added to the values of the index items for the derived social sensor data, and the ranking for the regions is calculated. The method according to claim 1,
Wherein the social sensor measuring unit comprises:
A social sensor measurement value analyzer for measuring the social sensor data; And
And a social sensor-related information recognition unit for recognizing social sensor-related information including a link or an image related to the social sensor data. 5. The method of claim 4,
Wherein the sensor information visualization unit provides the social sensor related information together through the network. The method according to claim 1,
Wherein the external data is sensor data of a physical sensor or geospatial information in a database. 5. The method of claim 4,
Wherein the social sensor measurement value analyzer comprises:
A subject sensing module for sensing a subject from the inputted social data; A subject clustering module for clustering the detected subject; And a social data conversion module for converting the social data into a measurement, a time, or a geographical location based on the collected topic and extracted numerical values Wherein the sensor web system is based on a social data. 8. The method of claim 7,
Wherein the subject detection module senses a subject from morphological analysis and object name recognition from the inputted social data. 8. The method of claim 7,
Wherein the subject clustering module clusters the sensed subject based on a document frequency (DF) and a word frequency (TF). A social data input unit for receiving social data on a social network through a network;
An external data receiving unit for receiving external data including sensor data of a physical sensor or geospatial information in a database through the network;
A social sensor measuring unit for analyzing the inputted social data and measuring the social sensor data;
A social data analyzer for converting or correcting the social sensor data based on the external data; And
And a sensor information providing unit for providing the external data and the converted or corrected social sensor data. 11. The method of claim 10,
The sensor information providing unit,
Wherein the external data and the converted or corrected social sensor data are respectively leveled and summed and provided. 11. The method of claim 10,
And a sensor data combining unit for combining the converted or corrected social sensor data with a space or a time not included in the external data with the external data to form integrated sensor data,
And the sensor information providing unit provides the integrated sensor data.

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