CN106897405A - A kind of construction method and device of geographical space Sensor Network body - Google Patents
A kind of construction method and device of geographical space Sensor Network body Download PDFInfo
- Publication number
- CN106897405A CN106897405A CN201710081846.6A CN201710081846A CN106897405A CN 106897405 A CN106897405 A CN 106897405A CN 201710081846 A CN201710081846 A CN 201710081846A CN 106897405 A CN106897405 A CN 106897405A
- Authority
- CN
- China
- Prior art keywords
- observation
- sensor network
- geographical space
- metadata
- extension
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Granted
Links
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
- G06F16/29—Geographical information databases
Landscapes
- Engineering & Computer Science (AREA)
- Databases & Information Systems (AREA)
- Theoretical Computer Science (AREA)
- Remote Sensing (AREA)
- Data Mining & Analysis (AREA)
- Physics & Mathematics (AREA)
- General Engineering & Computer Science (AREA)
- General Physics & Mathematics (AREA)
- Information Retrieval, Db Structures And Fs Structures Therefor (AREA)
Abstract
The present invention relates to geographical space observation technology field, more particularly to a kind of construction method and device of geographical space Sensor Network body, methods described includes：The attribute information of the observation data that hardware physical message, the attribute information of object of observation according to sensor, the attribute information of observation process, sensor are produced in observation process and the attribute information of observation product build geographical space Sensor Network observation resource；Resource distribution semantic description key element metadata is observed to geographical space Sensor Network；The interior class and attribute that the geographical space Sensor Network body of extension is treated according to semantic description key element metadata are extended；In the case where application scenario is specified, according to geographical space Sensor Network ontology acquisition observation data and the metadata of observation data after extension, and the structure of the structure of example class, the structure of internal correlation and outside association is carried out to the geographical space Sensor Network body after extension.Data source of the present invention is enriched, and disclosure satisfy that user observes the demand of data for multi-source.
Description
Technical field
The present invention relates to geographical space observation technology field, more particularly to a kind of structure side of geographical space Sensor Network body
Method and device.
Background technology
Development and manufacturing continuous maturation with modern science and technology, substantial amounts of sensor device are applied to human society
Various aspects, such as more by the mankind, limitation is unable in itself to help people to obtain for disaster, meteorology, agricultural production
The information of acquisition.Substantial amounts of sensor constitutes Sensor Network, and Sensor Network can continuously provide the cycle, multi-mode observation,
Formulated for accurate analysis and decision and provide more powerful data basis.
Application field according to Sensor Network body is different with key concept definition, existing Sensor Network body be broadly divided into
Built centered on sensor and build two major classes to observe data grid technology.The Sensor Network body master built centered on sensor
To include sensor association attributes, physical characteristic and measurement codomain；It is main with the Sensor Network body for observing data grid technology structure
Then lay particular emphasis on the attribute and type of sensor observation activity and data.Existing Sensor Network ontological existence problems with：Sensor Network
Data grid technology is isolated to be set up body centered on sensor or to observe, for sensor, observation process and observation data
Relation between product does not provide complete definition and description, and data source is single, for the multi-source in geographical space Sensor Network
The related semantic description of data message is not detailed enough, it is impossible to meet complicated demand of the user for multi-source heterogeneous data, it is impossible to enough
Meet the requirement of intelligentized search and decision service.
The content of the invention
In view of the above problems, it is proposed that the present invention so as to provide one kind overcome above mentioned problem or at least in part solve on
State the construction method and device of the geographical space Sensor Network body of problem.
The embodiment of the present invention provides a kind of construction method of geographical space Sensor Network body, and methods described includes：
It is hardware physical message according to the sensor, described during sensor is observed to object of observation
The observation number that the attribute information of object of observation, the attribute information of observation process, the sensor are produced in the observation process
According to attribute information and the observation product obtained based on the observation data attribute information, build the observation of geographical space Sensor Network
Resource；
Resource distribution semantic description key element metadata is observed to the geographical space Sensor Network；
The semantic description key element metadata for observing resource according to the geographical space Sensor Network treats the geographical space of extension
The interior class and attribute of Sensor Network body are extended；
In the case where application scenario is specified, according to extension after geographical space Sensor Network ontology acquisition observation data and described
Observe the metadata of data；
According to it is described observation data and the metadata, to extension after the geographical space Sensor Network body carry out example
The structure of class, to extension after the geographical space Sensor Network body carry out the structure of internal correlation and to described in after extension
Geographical space Sensor Network body carries out the structure of outside association.
Preferably, the semantic description key element metadata includes：Semantic identification metadata, scope metadata,
Observation process metadata, semantic association metadata, temporal characteristics metadata, space characteristics metadata, spectral signature
At least one metadata in the observation application metadata of metadata and the sensor.
Preferably, the sensor includes at least one sensing in space remote sensing sensor and ground home position sensing
Device.
Preferably, the geographical space Sensor Network body after described pair of extension carries out the structure of internal correlation, including：
In the geographical space Sensor Network observation resource of the geographical space Sensor Network body after to extension at least two
Information is associated；And/or
The geographical space Sensor Network of the geographical space Sensor Network body after to extension observes temporal characteristics, the sky of resource
Between feature, spectral signature and be associated using at least two features in feature.
Preferably, the geographical space Sensor Network body after described pair of extension carries out the structure of outside association, including：
The geographical space Sensor Network body after by extension is associated with the data in open geography cloud platform.
Based on same inventive concept, the embodiment of the present invention also provides a kind of construction device of geographical space Sensor Network body,
Described device includes：
First builds module, during being observed to object of observation in sensor, according to the sensor
Hardware physical message, the attribute information of the object of observation, the attribute information of observation process, the sensor were observed described
The attribute information of the attribute information of the observation data produced in journey and the observation product obtained based on the observation data, builds ground
Reason space Sensor Network observation resource；
Metadata configurations module, for wanting primitive element number to geographical space Sensor Network observation resource distribution semantic description
According to；
Expansion module, the semantic description key element metadata for observing resource according to the geographical space Sensor Network treats expansion
The interior class and attribute of the geographical space Sensor Network body of exhibition are extended；
Acquisition module, for specify application scenario under, according to extension after the geographical space Sensor Network ontology acquisition
The metadata of observation data and the observation data；
Second build module, for according to it is described observation data and the metadata, to extension after the geographical space
Sensor Network body carry out example class structure, to extension after the geographical space Sensor Network body carry out the structure of internal correlation
And to extension after the geographical space Sensor Network body carry out the structure of outside association.
Preferably, the semantic description key element metadata includes：Semantic identification metadata, scope metadata,
Observation process metadata, semantic association metadata, temporal characteristics metadata, space characteristics metadata, spectral signature
At least one metadata in the observation application metadata of metadata and the sensor.
Preferably, the sensor includes at least one sensing in space remote sensing sensor and ground home position sensing
Device.
Preferably, described second module is built, including：
First associative cell, for the geographical space Sensor Network observation of the geographical space Sensor Network body after to extension
At least two information in resource are associated；And/or
Second associative cell, for the geographical space Sensor Network observation of the geographical space Sensor Network body after to extension
The temporal characteristics of resource, space characteristics, spectral signature and it is associated using at least two features in feature.
Preferably, described second module is built, including：
3rd associative cell, in the geographical space Sensor Network body after by extension and open geography cloud platform
Data are associated.
One or more technical schemes in the embodiment of the present invention, at least have the following technical effect that or advantage：
The present invention by the hardware physical message according to sensor, the attribute information of object of observation, observation process attribute
The attribute information of the observation data that information, sensor are produced in observation process and the attribute information of observation product, build geographical
Space Sensor Network observation resource so that the foundation of geographical space Sensor Network body not only account for the static physical attribute of sensor
Dynamic observing capacity feature in feature and observation process, also account for the relation between sensor and observation data product, number
According to abundance, complete definition and description are given for the relation between sensor, observation process and observation product, together
When, by introducing the association of data, geographical space Sensor Network ontology acquisition observation data and observation data after using extension
Metadata after, according to observation data and metadata, to extension after the geographical space Sensor Network body carry out example class
Structure, to extension after the geographical space Sensor Network body carry out internal correlation structure and to extension after describedly
Reason space Sensor Network body carries out the structure of outside association, realizes the association of spatial data, meets user and is observed for multi-source
The demand of data.
Brief description of the drawings
By reading the detailed description of hereafter preferred embodiment, various other advantages and benefit is common for this area
Technical staff will be clear understanding.Accompanying drawing is only used for showing the purpose of preferred embodiment, and is not considered as to the present invention
Limitation.And in whole accompanying drawing, identical part is represented with identical reference pattern.In the accompanying drawings：
Fig. 1 shows a kind of flow chart of the construction method of geographical space Sensor Network body of the embodiment of the present invention；
Fig. 2 shows a kind of structure chart of the construction device of geographical space Sensor Network body of the embodiment of the present invention.
Specific embodiment
The exemplary embodiment of the disclosure is more fully described below with reference to accompanying drawings.Although showing the disclosure in accompanying drawing
Exemplary embodiment, it being understood, however, that may be realized in various forms the disclosure without should be by embodiments set forth here
Limited.Conversely, there is provided these embodiments are able to be best understood from the disclosure, and can be by the scope of the present disclosure
Complete conveys to those skilled in the art.
The embodiment of the present invention provides a kind of construction method of geographical space Sensor Network body, as shown in figure 1, methods described bag
Include：
Step 101：During sensor is observed to object of observation, the hardware physics letter according to the sensor
Breath, the attribute information of the object of observation, the attribute information of observation process, the sensor are produced in the observation process
The attribute information of data and the attribute information of the observation product obtained based on the observation data are observed, geographical space sensing is built
Net observation resource.
Specifically, in this application, sensor can be including in space remote sensing sensor and ground home position sensing
At least one sensor.The application builds geographical space Sensor Network observation resource SWOR first, wherein, geographical space Sensor Network is seen
Survey hardware physical message, the attribute information of object of observation, the attribute information of observation process, biography that resource SWOR can be sensor
The set of the attribute information of the observation data that sensor is produced in observation process and the attribute information of observation product, i.e. SWOR=
{ H, O, F, D, P }, H is the hardware physical message of sensor, such as temporal resolution, and O is the attribute letter of the observation process of sensor
Breath, such as orbit information of observation time and space remote sensing sensor, F are the attribute information of object of observation, i.e. area-of-interest
The longitude and latitude of attribute information, such as area-of-interest, D is the attribute information of the observation data that sensor is produced in observation process,
The time of data generation is such as observed, P is the attribute information for observing product, such as observes the type of product.Wherein, in this application,
Sensor is used to be observed object of observation, such as when object of observation is vegetation, product is observed to vegetation using sensor
Raw observation data, observation data can be image, and observation product is then observation data via the product obtained after working process, example
Such as, the image that obtains will be observed by the observation product of vegetative coverage situation after working process, can be generated.
Step 102：Resource distribution semantic description key element metadata is observed to the geographical space Sensor Network.
Specifically, semantic description key element metadata can include：Semantic identification metadata, scope characteristic element number
According to, observation process metadata, semantic association metadata, temporal characteristics metadata, space characteristics metadata, Spectral Properties
Levy at least one metadata in the observation application metadata of metadata and the sensor.
Semantic identification metadata includes identifier and description attribute, and identifier is used to identify the observation of sensor and sensor
The attribute information of data, the associated data principle of anything is identified using URIs to meet, and identifier includes data set identification
Symbol (ParentIdentifier) and/or meta-data identifier (IDentifier).Description attribute is used to sense geographical space
The attribute information of net observation resource carries out generality description, and the type (ProductType) and observed result of such as observation product are obtained
Take the time (TimePosition).
Scope metadata is used to describe the static physical observing capacity and attribute of scope, such as scope
Information (InstrumentInformation) and observation platform information (PlatformInformation), wherein, scope
Namely the sensor in the application.
Observation process metadata is used to describe dynamic observing capacity of the scope when observation is performed.According to whole
The step of observation process, observation process is divided into observation acquisition process, three sons of inspection process process and observed result process
Process, so that, accordingly, observation process metadata includes that observation acquisition process metadata, inspection process process are special
Metadata and observed result process feature metadata are levied, wherein, observation acquisition process metadata can be archive information
(Achiving), inspection process process metadata can be inspection process software information (Processor), observed result process unit
Data can be product information (ObservationProduct).
Semantic association metadata includes spatial topotaxy and other particular kind of relationships.Spatial topotaxy includes：
Comprising (Contains), intersect (Crosses), separation (Disjoint), equal (Equal), intersecting (Intersects), overlap
(Overlaps), contact (Touch) and be contained in (Within).Wherein, it is included as：The inside of one geometric figure completely includes
The inside and border of another geometric figure；Intersect and be：One inside of geometric figure and the border of another geometric figure
It is intersecting with inside, but their border is non-intersect；The border and inside for being separated into two geometric figures are non-intersect；Equal is two
Individual geometric figure has identical border and inside；Intersect for two geometric figures are not separated (Non-DisJoint)；
Overlap as (Intersect) is intersected on two borders and inside of geometric figure；Contact as two borders of geometric figure are intersecting, but
It is internal non-intersect；Be contained in is complete in the inside of another geometric figure inside and its border of geometric figure.Its
He includes particular kind of relationship：Composition (composedOf), father and son (isSubsetOf), link (linkedWith) and near
(nearby).Semantic association metadata is used to describe the foundation of internal correlation in geographical space Sensor Network body, specific bag
Include geographical space Sensor Network observation resource in each information information inside association and each information between association.
Temporal characteristics metadata is used to describe the temporal characteristics that geographical space Sensor Network observes resource, and it is mainly reflected in biography
In sensor observing capacity feature, observational characteristic and observed result feature, such as data observation obtains date and time information
(DownlinkObservationDate).Space characteristics metadata is used to describe the space that geographical space Sensor Network observes resource
Feature, spatial dimension, position and the observation of geographical space Sensor Network that it is mainly reflected in geographical space Sensor Network observation resource
Among the spatial topotaxy of the spatial dimension, position and geographical space Sensor Network observation resource of resource, such as overlay area
Profile coordinate (BoundingBox).Spectral signature metadata is used to describe the spectral signature that geographical space Sensor Network observes resource,
It is mainly reflected in the dynamic dynamic observing capacity and the related ripple of observation data observed in attribute to spectral correlation of sensor
In section attribute, such as spectral band histogram information (Histogram).The observation application metadata of sensor is used to describe to pass
The observation application feature of sensor, it increases sensor by extracting a state for real situation from sensor observation
Potential application (PotentialApplication) attribute, such as the application of flood Emergency decision in, carry out flood remote sensing
Need to carry out the identification of water body during detection, there is larger difference in reflectivity and other atural objects of near-infrared and visible light wave range water body
It is different, can be recognized well, therefore it is the sensor of " flood monitor " that can accordingly select potential application, and add it
PotentialApplication attributes；
Step 103：Extension is treated according to the semantic description key element metadata that the geographical space Sensor Network observes resource
The interior class and attribute of geographical space Sensor Network body are extended.
In this application, geographical space Sensor Network body to be extended can be existing SSNP Ontology Sensor Networks
Body, the application is passed by the geographical space that the semantic description key element metadata that geographical space Sensor Network observes resource treats extension
The associated class and attribute for feeling net body are extended, and increase sensor (Sensor) module, when sensor is passed including space remote sensing
It is separately entered when sensor and ground home position sensing, the characteristics of according to space remote sensing sensor and ground home position sensing each
The definition of row associated class, be increased for space remote sensing sensor and is defined with the description of sensor wave band associated class, and 8 are defined altogether
Class, respectively SensorType, SensorID, SensorOperation, SensorResolution,
SensorSpectralRange, WavelengthResolution, StartWavelength and EndWavelength,
SensorType represents sensor type, and SensorID represents sensor ID, and SensorOperation represents sensor operations mould
Formula, SensorResolution represents sensor resolution, and SensorSpectralRange represents sensor band classes,
WavelengthResolution represents sensor wavelength resolution ratio, namely spectral resolution, and StartWavelength represents biography
Sensor starts wave band, and EndWavelength represents that sensor terminates wave band, while 7 relations on attributes are defined, respectively
HasType, hasID, hasOperationMode, hasResolution, SensorSpectrum, startWave and
endWave。
Further, the geographical space Sensor Network body after extension increases for class：Process modules,
MeasurentCapability modules, Sensor modules, PlatformSite modules, Device modules, Observation moulds
Block, Data modules, ObservationProduct modules, ObservationCapability modules, Time modules, Space moulds
Block, Spectrum modules and PotentialAplication modules.
Process modules include：ProcessingCenter, ProcessingDate, ProcessingMode,
ProcessingName, ProcessingVersion, ProcessingMethod, ProcessingMethodVersion,
ProcessingLevel, AuxiliarDataSetFileName, DataProcessingMethod,
DataProcessingMethodVersion。
MeasurentCapability modules include：SensorSpectralRange,
RSMeasurementProperty, INSMeasurementProperty.
Sensor modules include：SensorType, SensorID, SensorOperation, SensorResolution,
SensorSpectralRange, WavelengthResolution, StartWavelength, EndWavelength.
PlatformSite modules include：PlatformID, PlatformName, PlatformPosition,
PlatformOrbittype, SatelliteAngle, StatellitePitch, StatelliteYaw,
StatelliteRoll.Device modules include：InstrumentType, InstrumentName,
InstrumentDescription, InstrumentAngle, InstrumentElevationAngle,
InstrumentAzimuthAngle, InstrumentZenithAngle.
Observation modules include：ObservationStartPosition, ObservationEndPosition,
ObservationType, ObservationSubType, DownlinkObservationDate,
DownlinkObservationStation, Orbitformation, Illumination, ObservationAngle,
Histogram, VendorSpecific, Archiving.
Data modules include：CatalogueCreationData, ExtendOf, ParentID, MetadataID,
ParameterPhenomenon, ParameterUnitOfMeasure, ResultTimePosition,
ImageQualityDegradation, ImageQualityDegradationQuotationMode, SamplingTime,
Positon。
ObservationProduct modules include：ProductStatus, ProductstatusDetail,
ProductDoi, ProductFileName, ProductSize, ProductVersion, ProductReferenceID,
NativeProductFormat, ProductCompositeType, ProductBrowse, ProductMask,
BrowseReferenceID, BrowseFileName, BrowseType, BrowseSubType, MaskReferenceID,
MaskFileName, MaskType, MaskFomat.
ObservationCapability modules include：ObservationCapability, Latency,
AquisitionDate, ProcessingDate, ObservationType, RSObservationProperty,
ImagineQuality, ExtentOf, MaskType, InstituObservationProperty.
Time modules include：ObservedObjectTemporalResolution, ObservedSourceTemporal,
ObservedSourceTemporalResolution。
Space modules include：SpatialBounding, Bbox, Reference,
ObservedObjectSpatialResolution, ObservedSourceSpatial,
ObservedSourceSpatialResolution。
Spectrum modules include：SpectrumName, SpectrumRange,
ObservedObjectStartWaveLength, ObservedObjectEndWaveLength,
ObservedObjectBandRange, ObservedSourceSpectrum, ObservedEndWaveLength,
ObservedSourceSpectralRange, ObservedStartWaveLength.
PotentialAplication modules include：PotentialAplication, Energy, Biodiversity,
Agriculture, Ecology, Climate, Water, Weather, Health, Disaster, other.
Further, the geographical space Sensor Network body after extension increases for attribute of a relation：Skeleton modules,
Process modules, Sensor modules, PlatformSite modules, Device modules, Observation modules, Data modules,
ObservationProduct modules, ObservationCapability modules, Space modules, Spectrum modules and
PotentialAplication modules.
Skeleton modules include：Derivedfrom, SensorSpectrum, hasSpectrum,
HasObservationData, beProcessed, Products.
Process modules include：HasVersion, hasProcessingDate, has ProcessingName,
HasProcessingMode, hasProcessingLevel, AuxiliaryProcessing.
Sensor modules include：HasType, hasID, hasOperationMode, hasResolution,
SensorSpectrum, startWave, endWave.
PlatformSite modules include：IsClassifiedBy, hasID, hasName, hasPosition,
statelliteStatusAngle。
Device modules include：IsClassifiedBy, hasName, isDescribedBy,
instrumentStatusAngle。
Observation modules include：IsClassifiedBy, hasObservationStation, hasOrbit,
HasID, hasCenter, hasIllumination, hasObservationAngle, hasArchiving,
HasHistogram, hasVendor, hasDataValue.
Data modules include：ObservationResultTime, observationSamplingTime, hasOrbit,
HasID, hasPosition, hasParameter, imageQualityofObservation,
ImageQualityQuotation, unitOf.
ObservationProduct modules include：IsClassifiedBy, hasStatus, hasID, hasName,
HasVersion, statusDetail, sizeOf, productFormat, browseInformation,
maskInformation。
ObservationCapability modules include：HasObservationCapability, forProperty,
hasObservationProperty。
Space modules include：HasPosition, isLocationOf, hasPart, isPart, hasComponentOf,
IsComponentOf, Geonames:Nearby, Geonames:Nearbyfeatures, SpatialRelation,
TopologicRelation, DirectionRelation, DistenceRelation, overlaps, cross, disjoint,
Touches, intersects, contains, equals, within.
Spectrum modules include：EndWave, startWave, sensorSpectrum, hasSpectrum.
PotentialAplication modules include：hasPotentialApp.
Further, the class and attribute list of the geographical space Sensor Network body after extension can also be referring to table 1 below：
Table 1
Step 104：Specify application scenario under, according to extension after the geographical space Sensor Network ontology acquisition observation number
According to the metadata with the observation data.
In specific implementation process, user can be according to the specified application scenario of actual conditions selection application, should when specifying
It it is Emergency decision stage when medium range flood occurs with situation, by taking Wuhan City Hanyang District as an example, its required emergency response is produced
The data of product are broadly divided into two major classes：Primary sources be in, the Real-time Monitoring Data of low resolution, such as satellite-remote-sensing image and
Ground monitoring data, secondary sources for disaster area geo-spatial data, such as the administrative map of this area, communication chart and
Emphasis distribution of facilities figure.Therefore, road resource satellite Landsat-5TM is chosen as remote sensing observations data source, experimental data master
To be the XML descriptions of observation data metadata, data source is earth observation data sharing service net, is come from experimental data
The geographical space Sensor Network observation resource totally 4 of space remote sensing sensor, wherein, 3 is June 1 day to 2010 January in 2010
Landsat-5TM data on the 1st, querying condition is " region：Wuhan City of Hubei China province；Satellite：Landsat-5；Beginning and ending time：
2010-01-01 to 2010-06-01 ", Query Result is the three width remote sensing images and its metadata for meeting querying condition, and 1 is
The bar reel number of on November 6th, 2000 is 125, and line number is 39 Landsat-5TM data, and Data Identification is
LE71250392000311EDC01.Data above includes remote sensing image and its metadata.Ground home position sensing data source is
2 simulation rainfall monitoring websites Rainfall_recorder_001 and Rainfall_recorder_002.
Step 105：According to it is described observation data and the metadata, to extension after the geographical space Sensor Network body
Carry out example class structure, to extension after the geographical space Sensor Network body carry out internal correlation structure and to extension
The geographical space Sensor Network body afterwards carries out the structure of outside association.
In this application, example is carried out to geographical space Sensor Network body according to observation data and metadata, is specifically included
The geographical space Sensor Network body after to extension carry out example class structure, to extension after the geographical space Sensor Network
Body carry out internal correlation structure and to extension after the geographical space Sensor Network body carry out the structure of outside association.
For the structure that the geographical space Sensor Network body after to extension carries out example class, in a kind of specific embodiment party
In formula, according to the metadata of the Landsat-5TM remote sensing satellite data for obtaining, simulation rainfall monitoring station data and TM are sensed
The relevant physical properties instantiation body of device, creates related example class and its respective outsourcing rectangle class, phase in Prot é g é softwares
It can be observation data instance class, filing metadata instance class and covering information instances class etc. to close example class, in addition, passing through phase
Close data check and understand that the longitude and latitude scope of Wuhan City, Hubei Province Hanyang District is 41 ' -115 ° 05 ' of east longitude 113 °, 29 ° 58 ' of north latitude -
31 ° 22 ', it is therefore desirable to create the outsourcing rectangle class of " Hanyang District " example class and Hanyang District in the body, and
It is " Hanyang District " addition " Source " attribute identifying it in GeoNames data sets and GADM-RDF data sets
In URI.
For the structure that the Sensor Network body after to extension carries out internal correlation, including：The biography after to extension
At least two information felt in the geographical space Sensor Network observation resource of net body are associated, for example, to sensor and Qi Guan
Structure is associated between survey data, between observation data and observation product, between observation behavior and object of observation, construction method is
Associating between class and class is built according to the relation on attributes between class in geographical space Sensor Network body design, is example class addition
Attribute of a relation, is carried out such as between Observation example class and Sensor example class by " observedBy " attribute of a relation
Association；And/or, to extension after the geographical space Sensor Network observation temporal characteristics of resource of the Sensor Network body, space it is special
Levy, spectral signature and be associated using at least two features in feature, for example, to carry out so that manifold is associated as an example
Association between observation resource is, it is necessary to topological relation according to its outsourcing rectangle is set up in two observation resource space relations
Association, outsourcing rectangular example class possesses Data Property " hasbboxValue ", specifically outer for hourly observation resource
Bag rectangular extent, then corresponding observation resource sets up attribute by Object Property " bounding box " with it
Association.For example according to the value range of each outsourcing rectangular example class, observation product example class P_INS_Rain_20110304 is built
The spatial relationship of " within " between region of interest example class " Hanyang District ", with observation product example class P_
The spatial relationship of " within " between LS5_TM_1230392011063BKT00；Observation product example class P_LS5_TM_
The spatial relationship of " contains " between 1230392011063BKT00 and region of interest example class " Hanyang District ",
The spatial relationship of " contains " between observation product example class P_INS_Rain_20110304.
And, to extension after the Sensor Network body carry out the structure of outside association, including：The geography after by extension
Space Sensor Network body is associated with the data in open geography cloud platform.Geographical cloud platform can for GeoName and/or
GADM-RDF.The method for associating is built with GeoNames is：The two simulation rainfall monitoring website example class that it will be assumed
" Rainfall_recorder_001 " and " Rainfall_recorder_002 " is introduced by from GeoNames Ontology
Object Property " nearby " and region of interest example class " Hanyang District " set up Attribute Association, associate
To in GeoNames in the URI of Hanyang District.The method for associating is built with GADM-RDF is：By observing resource and region of interest reality
The topological correlation set up between example, resource will be observed in data set will be associated with Hanyang District in GADM-RDF by topological relation
In URI.
In this application, can also include after step 105：Querying condition is defined, geographical space Sensor Network is observed
Resource carries out semantic query, and further obtain other required related datas with outside association by internal correlation.For example, first
SPARQL inquiries are carried out by taking the topological relation " contains " of " Hanyang District " as an example, this inquiry purpose is to find
There is the observation resource of inclusion relation all and Hanyang District；Input code is as follows in SPARQL enquiry machines：
PREFIX rdf:<http://www.w3.org/1999/02/22-rdf-syntax-ns#>
PREFIX owl:<http://www.w3.org/2002/07/owl#>
PREFIX xsd:<http://www.w3.org/2001/XMLSchema#>
PREFIX rdfs:<http://www.w3.org/2000/01/rdf-schema#>
PREFIX DUL:<http:/www.loa-cnr.it/ontologies/DUL.owl#>
PREFIX ssn:<http://purl.oclc.org/NET/ssnx/ssn#>
SELECTobject
WHERE{<http://purl.oclc.org/NET/LSD/lsdontologyl#Hanyang_District>
<http://purl.oclc.org/NET/LSD/lsdontologyl#contains>object.}
Query Result is observation product " P_INS_Rain_20110304 ", and observes product " P_INS_Rain_
20110304 " there is internal pass with observation data class " Atomic_data_Rain " further through attribute of a relation " isProduceBy "
Connection, region of interest class " Hanyang District " constructs association by URI with open data cloud is associated, therefore passes through
Internal correlation is associated with outside, it is possible to associate the open data cloud of observation data and association, obtains the open data of association
The Fundamental Geographic Information System such as population distribution situation on devastated in cloud.
The intelligent and relationship search of geographical space Sensor Network observation resource when the present invention occurs with specific geographic event
Demand is starting point, and sensor is observed into data product with it by the definition for observing resource carries out unified model description, makees
For the theoretical foundation that geographical space Sensor Network observation resource ontology builds.The present invention can be by the number in geographical space Sensor Network
Built according to internal correlation and with open data cloud atlas outside association is associated, realize the relationship search of spatial data, meet user
For the demand that multi-source observes data.The dynamic observing capacity that the present invention account for sensing equipment in observation process is quiet with its own
State physical attribute, and observation resource time, space, spectrum, the correlated characteristic class of application aspect and attribute are defined, construct
Resource ontology is observed in the geographical space Sensor Network for possessing feasibility and relevance, is observation resource choosing in geographical space Sensor Network
The semantic reasoning selected provides data basis.
In sum, the present invention completes the structure of the body of geographical space Sensor Network observation resource semantic association.First
Propose that geographical space Sensor Network observes the concept of resource, based on this, introduce associated data technology, specify geographical space sensing
The semantic description and exposition need of net observation resource metadata, define geographical space Sensor Network observation resource element in terms of five
Data, and further designed and Implemented geographical space Sensor Network observation resource semantic association body.With sensing common at present
Net Ontology construction method is compared, and context of methods account in the static physical attributive character and observation process of sensing equipment
Dynamic observing capacity feature, the relation between concern sensor and observation data product is realized inside Sensor Network observation resource
Association and the structure of outside association, and aid in user to obtain the multi-source heterogeneous number needed for the open data cloud of association rapidly with this
According to, association search is realized, it is that the intelligent decision of geographical space Sensor Network observation resource lays the foundation.
Based on same inventive concept, the embodiment of the present invention also provides a kind of construction device of geographical space Sensor Network body,
As shown in Fig. 2 described device includes：
First builds module 201, during being observed to object of observation in sensor, according to the sensor
Hardware physical message, the attribute information of the object of observation, the attribute information of observation process, the sensor in the observation
During produce observation data attribute information and based on it is described observation data obtain observation product attribute information, structure
Geographical space Sensor Network observes resource；
Metadata configurations module 202, for wanting primitive element to geographical space Sensor Network observation resource distribution semantic description
Data；
Expansion module 203, the semantic description key element metadata pair for observing resource according to the geographical space Sensor Network
The interior class and attribute of geographical space Sensor Network body to be extended are extended；
Acquisition module 204, for specify application scenario under, according to extension after the geographical space Sensor Network body obtain
Take the metadata of observation data and the observation data；
Second builds module 205, for according to observation data and the metadata, to extension after it is described geographical empty
Between Sensor Network body carry out example class structure, to extension after the geographical space Sensor Network body carry out the structure of internal correlation
Build and to extension after the geographical space Sensor Network body carry out the structure of outside association.
Preferably, the semantic description key element metadata includes：Semantic identification metadata, scope metadata,
Observation process metadata, semantic association metadata, temporal characteristics metadata, space characteristics metadata, spectral signature
At least one metadata in the observation application metadata of metadata and the sensor.
Preferably, the sensor includes at least one sensing in space remote sensing sensor and ground home position sensing
Device.
Preferably, second module 205 is built, including：
First associative cell, for the geographical space Sensor Network observation of the geographical space Sensor Network body after to extension
At least two information in resource are associated；And/or
Second associative cell, for the geographical space Sensor Network observation of the geographical space Sensor Network body after to extension
The temporal characteristics of resource, space characteristics, spectral signature and it is associated using at least two features in feature.
Preferably, second module 205 is built, including：
3rd associative cell, in the geographical space Sensor Network body after by extension and open geography cloud platform
Data are associated.
One or more technical schemes in the embodiment of the present invention, at least have the following technical effect that or advantage：
The present invention by the hardware physical message according to sensor, the attribute information of object of observation, observation process attribute
The attribute information of the observation data that information, sensor are produced in observation process and the attribute information of observation product, build geographical
Space Sensor Network observation resource so that the foundation of geographical space Sensor Network body not only account for the static physical attribute of sensor
Dynamic observing capacity feature in feature and observation process, also account for the relation between sensor and observation data product, number
According to abundance, complete definition and description are given for the relation between sensor, observation process and observation product, together
When, by introducing the association of data, geographical space Sensor Network ontology acquisition observation data and observation data after using extension
Metadata after, according to observation data and metadata, to extension after the geographical space Sensor Network body carry out example class
Structure, to extension after the geographical space Sensor Network body carry out internal correlation structure and to extension after describedly
Reason space Sensor Network body carries out the structure of outside association, realizes the association of spatial data, meets user and is observed for multi-source
The demand of data.
Algorithm and display be not inherently related to any certain computer, virtual system or miscellaneous equipment provided herein.
Various general-purpose systems can also be used together with based on teaching in this.As described above, construct required by this kind of system
Structure be obvious.Additionally, the present invention is not also directed to any certain programmed language.It is understood that, it is possible to use it is various
Programming language realizes the content of invention described herein, and the description done to language-specific above is to disclose this hair
Bright preferred forms.
In specification mentioned herein, numerous specific details are set forth.It is to be appreciated, however, that implementation of the invention
Example can be put into practice in the case of without these details.In some instances, known method, structure is not been shown in detail
And technology, so as not to obscure the understanding of this description.
Similarly, it will be appreciated that in order to simplify one or more that the disclosure and helping understands in each inventive aspect, exist
Above to the description of exemplary embodiment of the invention in, each feature of the invention is grouped together into single implementation sometimes
In example, figure or descriptions thereof.However, the method for the disclosure should be construed to reflect following intention：I.e. required guarantor
The application claims of shield features more more than the feature being expressly recited in each claim.More precisely, such as following
Claims reflect as, inventive aspect is all features less than single embodiment disclosed above.Therefore,
Thus the claims for following specific embodiment are expressly incorporated in the specific embodiment, and wherein each claim is in itself
All as separate embodiments of the invention.
Those skilled in the art are appreciated that can be carried out adaptively to the module in the equipment in embodiment
Change and they are arranged in one or more equipment different from the embodiment.Can be the module or list in embodiment
Unit or component be combined into a module or unit or component, and can be divided into addition multiple submodule or subelement or
Sub-component.In addition at least some in such feature and/or process or unit exclude each other, can use any
Combine to all features disclosed in this specification (including adjoint claim, summary and accompanying drawing) and so disclosed appoint
Where all processes or unit of method or equipment are combined.Unless expressly stated otherwise, this specification (including adjoint power
Profit is required, summary and accompanying drawing) disclosed in each feature can the alternative features of or similar purpose identical, equivalent by offer carry out generation
Replace.
Although additionally, it will be appreciated by those of skill in the art that some embodiments described herein include other embodiments
In included some features rather than further feature, but the combination of the feature of different embodiments means in of the invention
Within the scope of and form different embodiments.For example, in the following claims, embodiment required for protection is appointed
One of meaning mode can be used in any combination.
All parts embodiment of the invention can be realized with hardware, or be run with one or more processor
Software module realize, or with combinations thereof realize.It will be understood by those of skill in the art that can use in practice
Microprocessor or digital signal processor (DSP) realize the structure of geographical space Sensor Network body according to embodiments of the present invention
The some or all functions of some or all parts built in device.The present invention is also implemented as performing institute here
Some or all equipment or program of device of the method for description are (for example, computer program and computer program are produced
Product).It is such to realize that program of the invention be stored on a computer-readable medium, or can have one or more
The form of signal.Such signal can be downloaded from internet website and obtained, or be provided on carrier signal, or to appoint
What other forms is provided.
It should be noted that above-described embodiment the present invention will be described rather than limiting the invention, and ability
Field technique personnel can design alternative embodiment without departing from the scope of the appended claims.In the claims,
Any reference symbol being located between bracket should not be configured to limitations on claims.Word "comprising" is not excluded the presence of not
Element listed in the claims or step.Word "a" or "an" before element is not excluded the presence of as multiple
Element.The present invention can come real by means of the hardware for including some different elements and by means of properly programmed computer
It is existing.If in the unit claim for listing equipment for drying, several in these devices can be by same hardware branch
To embody.The use of word first, second, and third does not indicate that any order.These words can be explained and run after fame
Claim.
Claims (10)
1. a kind of construction method of geographical space Sensor Network body, it is characterised in that methods described includes：
During sensor is observed to object of observation, hardware physical message, the observation according to the sensor
The observation data that the attribute information of object, the attribute information of observation process, the sensor are produced in the observation process
The attribute information of attribute information and the observation product obtained based on the observation data, builds geographical space Sensor Network observation money
Source；
Resource distribution semantic description key element metadata is observed to the geographical space Sensor Network；
The semantic description key element metadata for observing resource according to the geographical space Sensor Network treats the geographical space sensing of extension
The interior class and attribute of net body are extended；
Specify application scenario under, according to extension after the geographical space Sensor Network ontology acquisition observation data and the observation
The metadata of data；
According to it is described observation data and the metadata, to extension after the geographical space Sensor Network body carry out example class
Build, to extension after the geographical space Sensor Network body carry out internal correlation structure and to extension after the geography
Space Sensor Network body carries out the structure of outside association.
2. the method for claim 1, it is characterised in that the semantic description key element metadata includes：Semantic identification element
Data, scope metadata, observation process metadata, semantic association metadata, temporal characteristics metadata,
At least one unit number in the observation application metadata of space characteristics metadata, spectral signature metadata and the sensor
According to.
3. the method for claim 1, it is characterised in that the sensor includes that space remote sensing sensor and ground are in situ
At least one sensor in sensor.
4. the method for claim 1, it is characterised in that the geographical space Sensor Network body after described pair of extension enters
The structure of row internal correlation, including：
At least two information in the geographical space Sensor Network observation resource of the geographical space Sensor Network body after to extension
It is associated；And/or
The temporal characteristics of the geographical space Sensor Network observation resource of the geographical space Sensor Network body after to extension, space are special
Levy, spectral signature and be associated using at least two features in feature.
5. the method for claim 1, it is characterised in that the geographical space Sensor Network body after described pair of extension enters
The structure of the outside association of row, including：
The geographical space Sensor Network body after by extension is associated with the data in open geography cloud platform.
6. a kind of construction device of geographical space Sensor Network body, it is characterised in that described device includes：
First builds module, during being observed to object of observation in sensor, according to the hardware of the sensor
Physical message, the attribute information of the object of observation, the attribute information of observation process, the sensor are in the observation process
The attribute information of the attribute information of the observation data of generation and the observation product obtained based on the observation data, is built geographical empty
Between Sensor Network observation resource；
Metadata configurations module, for observing resource distribution semantic description key element metadata to the geographical space Sensor Network；
Expansion module, the semantic description key element metadata for observing resource according to the geographical space Sensor Network treats extension
The interior class and attribute of geographical space Sensor Network body are extended；
Acquisition module, for specify application scenario under, according to extension after the geographical space Sensor Network ontology acquisition observation
The metadata of data and the observation data；
Second build module, for according to it is described observation data and the metadata, to extension after the geographical space sensing
Net body carry out example class structure, to extension after the geographical space Sensor Network body carry out internal correlation structure and
The geographical space Sensor Network body after to extension carries out the structure of outside association.
7. device as claimed in claim 6, it is characterised in that the semantic description key element metadata includes：Semantic identification element
Data, scope metadata, observation process metadata, semantic association metadata, temporal characteristics metadata,
At least one unit number in the observation application metadata of space characteristics metadata, spectral signature metadata and the sensor
According to.
8. device as claimed in claim 6, it is characterised in that the sensor includes that space remote sensing sensor and ground are in situ
At least one sensor in sensor.
9. device as claimed in claim 1, it is characterised in that described second builds module, including：
First associative cell, the geographical space Sensor Network for the geographical space Sensor Network body after to extension observes resource
In at least two information be associated；And/or
Second associative cell, the geographical space Sensor Network for the geographical space Sensor Network body after to extension observes resource
Temporal characteristics, space characteristics, spectral signature and be associated using at least two features in feature.
10. device as claimed in claim 6, it is characterised in that described second builds module, including：
3rd associative cell, for the data in the geographical space Sensor Network body after by extension and open geography cloud platform
It is associated.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201710081846.6A CN106897405B (en) | 2017-02-15 | 2017-02-15 | A kind of construction method and device of geographical space Sensor Network ontology |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201710081846.6A CN106897405B (en) | 2017-02-15 | 2017-02-15 | A kind of construction method and device of geographical space Sensor Network ontology |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN106897405A true CN106897405A (en) | 2017-06-27 |
| CN106897405B CN106897405B (en) | 2018-06-15 |
Family
ID=59198265
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201710081846.6A Active CN106897405B (en) | 2017-02-15 | 2017-02-15 | A kind of construction method and device of geographical space Sensor Network ontology |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN106897405B (en) |
Cited By (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109885586A (en) * | 2019-01-24 | 2019-06-14 | 武汉大学 | Support the ontology model construction method and device of remote sensing image and data product retrieval |
| CN109933794A (en) * | 2019-03-18 | 2019-06-25 | 中科院合肥技术创新工程院 | A kind of Decision Ontology modeling method based on ontology OWL technology |
| CN110097592A (en) * | 2019-04-07 | 2019-08-06 | 杭州晶一智能科技有限公司 | The Semantic of terrestrial information describes method |
| CN110727799A (en) * | 2018-06-29 | 2020-01-24 | 杭州海康威视数字技术股份有限公司 | Ontology construction method and device |
| CN111752544A (en) * | 2020-06-29 | 2020-10-09 | 郑州大学 | Method for constructing ontology model supporting semantic expression of satellite-borne sensor observation process |
Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20090172507A1 (en) * | 2007-01-26 | 2009-07-02 | Raytheon Company | Information Processing System |
| CN103235855A (en) * | 2013-04-27 | 2013-08-07 | 武汉大学 | Construction method of sensor network heterogeneous node element model |
| CN103279344A (en) * | 2013-05-27 | 2013-09-04 | 武汉大学 | Method and system for supporting isomeric sensor semantic registration |
| US20150170033A1 (en) * | 2013-12-13 | 2015-06-18 | Electronics And Telecommunications Research Institute | Context reasoning apparatus, context recognition system and context reasoning method |
| CN105224693A (en) * | 2015-11-09 | 2016-01-06 | 武汉大学 | The Geospatial Information Processing Method of knowledge based modeling |
-
2017
- 2017-02-15 CN CN201710081846.6A patent/CN106897405B/en active Active
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20090172507A1 (en) * | 2007-01-26 | 2009-07-02 | Raytheon Company | Information Processing System |
| CN103235855A (en) * | 2013-04-27 | 2013-08-07 | 武汉大学 | Construction method of sensor network heterogeneous node element model |
| CN103279344A (en) * | 2013-05-27 | 2013-09-04 | 武汉大学 | Method and system for supporting isomeric sensor semantic registration |
| US20150170033A1 (en) * | 2013-12-13 | 2015-06-18 | Electronics And Telecommunications Research Institute | Context reasoning apparatus, context recognition system and context reasoning method |
| CN105224693A (en) * | 2015-11-09 | 2016-01-06 | 武汉大学 | The Geospatial Information Processing Method of knowledge based modeling |
Cited By (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110727799A (en) * | 2018-06-29 | 2020-01-24 | 杭州海康威视数字技术股份有限公司 | Ontology construction method and device |
| CN110727799B (en) * | 2018-06-29 | 2022-08-16 | 杭州海康威视数字技术股份有限公司 | Ontology construction method and device |
| CN109885586A (en) * | 2019-01-24 | 2019-06-14 | 武汉大学 | Support the ontology model construction method and device of remote sensing image and data product retrieval |
| CN109933794A (en) * | 2019-03-18 | 2019-06-25 | 中科院合肥技术创新工程院 | A kind of Decision Ontology modeling method based on ontology OWL technology |
| CN110097592A (en) * | 2019-04-07 | 2019-08-06 | 杭州晶一智能科技有限公司 | The Semantic of terrestrial information describes method |
| CN111752544A (en) * | 2020-06-29 | 2020-10-09 | 郑州大学 | Method for constructing ontology model supporting semantic expression of satellite-borne sensor observation process |
| CN111752544B (en) * | 2020-06-29 | 2023-11-10 | 郑州大学 | Method for constructing ontology model supporting semantic expression in observation process of satellite-borne sensor |
Also Published As
| Publication number | Publication date |
|---|---|
| CN106897405B (en) | 2018-06-15 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN106897405B (en) | A kind of construction method and device of geographical space Sensor Network ontology | |
| Yang et al. | Simulation of landscape spatial layout evolution in rural-urban fringe areas: a case study of Ganjingzi District | |
| Compton et al. | The SSN ontology of the W3C semantic sensor network incubator group | |
| Kauppinen et al. | Linked brazilian amazon rainforest data | |
| Miettinen et al. | Comparison of visual and automated oil palm mapping in Borneo | |
| Zheng et al. | An eiot system designed for ecological and environmental management of the xianghe segment of china’s grand canal | |
| Zhu et al. | Multidimensional and quantitative interlinking approach for linked geospatial data | |
| Wieland et al. | Using Shapley additive explanations to interpret extreme gradient boosting predictions of grassland degradation in Xilingol, China | |
| Jin et al. | Mapping the annual dynamics of cultivated land in typical area of the Middle-lower Yangtze plain using long time-series of Landsat images based on Google Earth Engine | |
| Pokharel et al. | Ontology based data access and integration for improving the effectiveness of farming in nepal | |
| Zeng et al. | A deep neural network-based decision support system for intelligent geospatial data analysis in intelligent agriculture system | |
| Wu et al. | Boosting climate analysis with semantically uplifted knowledge graphs | |
| Wang et al. | An ontology-based framework for integrating remote sensing imagery, image products, and in situ observations | |
| Zhou et al. | A Euler number-based topological computation model for land parcel database updating | |
| Yu et al. | Automatic geospatial data conflation using semantic web technologies | |
| Onuoha et al. | Analysis of urban growth pattern in Edwardsville/Glen carbon, Illinois, using remote sensing, population change data, and landscape expansion index | |
| Pundt | Integration of context-information to support spatial decision systems | |
| Balbo et al. | A public platform for geospatial data sharing for disaster risk management | |
| Zou et al. | Spatiotemporal graph-based analysis of land cover evolution using remote sensing time series data | |
| Zhu et al. | Virtual design of urban planning based on GIS big data and machine learning | |
| Nelson et al. | Comparing the GLC2000 and GeoCover LC land cover datasets for use in economic modelling of land use | |
| Hendrik et al. | Towards semantic mashup tools for big data analysis | |
| Kawamura et al. | Toward an ecosystem of LOD in the field: LOD content generation and its consuming service | |
| Nugroho et al. | Spatial data infrastructure integrated with geospatial artificial intelligence: A systematic literature review | |
| Velu et al. | Ocean knowledge representation through integration of big data employing semantic web technologies |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| TR01 | Transfer of patent right |
Effective date of registration: 20230803 Address after: Baogu Innovation and Entrepreneurship Center, China University of Geosciences (Wuhan), No. 388, Lumo Road, Hongshan District, Wuhan, 430000, Hubei Patentee after: Dida (Wuhan) Asset Management Co.,Ltd. Address before: 430070 no.388, LUMO Road, Hongshan District, Wuhan City, Hubei Province Patentee before: CHINA University OF GEOSCIENCES (WUHAN CITY) |
|
| TR01 | Transfer of patent right | ||
| TR01 | Transfer of patent right |
Effective date of registration: 20230824 Address after: No. 99, Baogu Innovation and Entrepreneurship Center, East District, China University of Geosciences, No. 388 Lumo Road, Hongshan District, Wuhan City, Hubei Province, 430000 Patentee after: Wuhan Zhongdi University Smart City Research Institute Co.,Ltd. Address before: Baogu Innovation and Entrepreneurship Center, China University of Geosciences (Wuhan), No. 388, Lumo Road, Hongshan District, Wuhan, 430000, Hubei Patentee before: Dida (Wuhan) Asset Management Co.,Ltd. |
|
| TR01 | Transfer of patent right |