CN112687267A - Internet of things data semantic processing system - Google Patents
Internet of things data semantic processing system Download PDFInfo
- Publication number
- CN112687267A CN112687267A CN202011530692.2A CN202011530692A CN112687267A CN 112687267 A CN112687267 A CN 112687267A CN 202011530692 A CN202011530692 A CN 202011530692A CN 112687267 A CN112687267 A CN 112687267A
- Authority
- CN
- China
- Prior art keywords
- data
- internet
- things
- database
- real
- 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.)
- Pending
Links
- 238000012545 processing Methods 0.000 title claims abstract description 92
- 239000013598 vector Substances 0.000 claims description 11
- 238000006243 chemical reaction Methods 0.000 claims description 8
- 238000004364 calculation method Methods 0.000 claims description 4
- 230000011218 segmentation Effects 0.000 claims description 4
- 238000002372 labelling Methods 0.000 claims description 3
- 238000013507 mapping Methods 0.000 claims description 3
- 230000004044 response Effects 0.000 abstract description 4
- 238000000034 method Methods 0.000 description 6
- 238000004891 communication Methods 0.000 description 5
- 230000004927 fusion Effects 0.000 description 3
- YCKRFDGAMUMZLT-UHFFFAOYSA-N Fluorine atom Chemical compound [F] YCKRFDGAMUMZLT-UHFFFAOYSA-N 0.000 description 2
- 230000005540 biological transmission Effects 0.000 description 2
- 238000013480 data collection Methods 0.000 description 2
- 229910052731 fluorine Inorganic materials 0.000 description 2
- 239000011737 fluorine Substances 0.000 description 2
- 238000007726 management method Methods 0.000 description 2
- 238000012544 monitoring process Methods 0.000 description 2
- 230000008569 process Effects 0.000 description 2
- 230000004931 aggregating effect Effects 0.000 description 1
- 238000004458 analytical method Methods 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 238000004422 calculation algorithm Methods 0.000 description 1
- 239000003795 chemical substances by application Substances 0.000 description 1
- 238000013523 data management Methods 0.000 description 1
- 238000013500 data storage Methods 0.000 description 1
- 230000007547 defect Effects 0.000 description 1
- 238000011161 development Methods 0.000 description 1
- 230000018109 developmental process Effects 0.000 description 1
- 238000005516 engineering process Methods 0.000 description 1
- 238000002474 experimental method Methods 0.000 description 1
- 230000004907 flux Effects 0.000 description 1
- 230000003993 interaction Effects 0.000 description 1
- 230000002452 interceptive effect Effects 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 238000003058 natural language processing Methods 0.000 description 1
- 238000007619 statistical method Methods 0.000 description 1
Images
Landscapes
- Information Transfer Between Computers (AREA)
Abstract
The invention relates to a data semantic processing system of the Internet of things, which comprises a data acquisition module, a message forwarding module, a real-time processing module, a first database, a second database and an offline processing module, wherein the message forwarding module is used for forwarding a message; the data acquisition module acquires Internet of things data; the message forwarding module forwards the data of the Internet of things to the real-time processing module or the second database; the real-time processing module carries out semantic processing on the data of the Internet of things; and the offline processing module performs semantic processing on the data of the internet of things stored in the second database. Compared with the prior art, the message forwarding module is designed according to the real-time processing requirement of the data of the Internet of things, the data which does not need to be processed in real time is directly stored, semantic processing is carried out in subsequent operation, the data which needs to be processed in real time is subjected to semantic processing, and the problems of low response efficiency and poor real-time performance caused by simultaneous access of a large number of Internet of things devices are solved.
Description
Technical Field
The invention relates to the field of Internet of things, in particular to a data semantic processing system of the Internet of things.
Background
The Internet of Things (IOT, Internet of Things), i.e., "Internet with all Things connected to one another", is a huge network formed by combining various sensing devices and the Internet, and collects various data in the network in real time to realize the interconnection of Things and people.
With the deep development of the internet of things, various sensors in the internet of things are more and more, a large amount of data with multiple sources and heterogeneity is generated, and great difficulty is brought to data processing, data fusion and resource sharing. On one hand, the problems that interactive collaboration and data fusion sharing are difficult to realize among information resources of the internet of things and the like are caused by the fact that the original sensing data of various internet of things devices lack clear meanings and the representation forms are heterogeneous. Meanwhile, different terminal devices adopt different communication protocols, which also brings certain challenges to data acquisition and transmission. Therefore, shielding the heterogeneity between data and a network, and understanding semantic information of data generated by different devices become problems to be solved urgently in the field of internet of things.
The Chinese patent invention with the publication number of CN112035208A discloses a multi-form power equipment of a transformer substation and a method for accessing Internet of things collection and display big data, which divides Internet of things data into structured data, semi-structured data and unstructured data, and stores, calculates and analyzes the data in different ways according to different types of the data. In practical internet of things application, a lot of data need to be processed immediately, the patent only stores the data according to different types, although the data can be processed immediately, when a large amount of equipment is accessed to the internet, the response efficiency is low and the real-time performance is poor for the large amount of data.
Chinese patent application publication No. CN111709235A discloses a text data statistical analysis system and method based on natural language processing, which can analyze text document data, but is not suitable for other unstructured data, and also cannot solve the problems of interaction and cooperation between heterogeneous data, data fusion, and the like.
Disclosure of Invention
The invention aims to overcome the defects in the prior art and provide the data semantic processing system of the internet of things, the message forwarding module is designed according to the real-time processing requirement of the data of the internet of things, the data which does not need to be processed in real time is directly stored, the semantic processing is carried out in the subsequent operation, and the data which needs to be processed in real time is subjected to the semantic processing, so that the problems of low response efficiency and poor real-time performance caused by simultaneous access of a large number of devices of the internet of things are solved.
The purpose of the invention can be realized by the following technical scheme:
a data semantic processing system of the Internet of things comprises a data acquisition module, a message forwarding module, a real-time processing module, a first database, a second database and an offline processing module;
the data acquisition module is connected with the message forwarding module and used for acquiring the data of the Internet of things;
the message forwarding module is respectively connected with the real-time processing module and the second database and is used for forwarding the data of the internet of things to the real-time processing module or the second database;
the real-time processing module is connected with the first database and used for performing semantic processing on the Internet of things data and storing the Internet of things data and a processing result into the first database;
the offline processing module is connected with the second database and used for performing semantic processing on the internet of things data stored in the second database and storing a processing result to the second database.
Furthermore, the data acquisition module comprises data acquisition equipment and a protocol conversion gateway, wherein the number of the data acquisition equipment is at least 1, the data acquisition equipment is used for acquiring Internet of things data, and the protocol conversion gateway is used for receiving the data acquired by the data acquisition equipment, converting the data into IP data and transmitting the IP data to the message forwarding module.
Furthermore, an instant communication protocol is adopted between the data acquisition module and the message forwarding module.
Further, the first database and the second database are distributed databases.
Further, the second database is an HDFS distributed file system.
Further, the message forwarding module is configured to forward the data of the internet of things to the real-time processing module or the second database, and specifically includes: acquiring a preset real-time data type; if the data of the Internet of things belongs to the preset real-time data type, forwarding the data of the Internet of things to a real-time processing module, otherwise, forwarding the data of the Internet of things to a second database for storage.
Further, the preset real-time data type is set according to the real-time processing requirement of the data.
Further, in the real-time processing module and the offline processing module, performing semantic processing on the data of the internet of things specifically includes the following steps:
s1: acquiring a constructed ontology library, wherein the ontology library comprises a plurality of different ontologies;
s2: structuring the data of the Internet of things, expressing the data by using a uniform resource description model, and converting the data into vectors;
s3: mapping the vector to a corresponding ontology in an ontology library by a semantic similarity calculation method, and labeling semantic labels to obtain knowledge map data;
s4: storing the internet of things data and the corresponding knowledge graph data.
Further, in step S1, the ontology library includes a plurality of different ontologies, and each ontology corresponds to a different internet of things scenario.
Further, in step S2, the structuring of the data of the internet of things specifically includes: if the data of the Internet of things is text unstructured data, performing word segmentation on the data of the Internet of things, extracting keywords, and expressing the keywords by using a uniform resource description model and converting the keywords into vectors; and if the data of the Internet of things is video and audio unstructured data, structuring the data of the Internet of things in an index establishing mode.
Compared with the prior art, the invention has the following beneficial effects:
(1) according to the real-time processing requirement of the data of the Internet of things, the message forwarding module is designed, the data which does not need to be processed in real time is directly stored, semantic processing is carried out in subsequent operation, the data which needs to be processed in real time is subjected to semantic processing, and the problems of low response efficiency and poor real-time performance caused by simultaneous access of a large number of devices of the Internet of things are solved.
(2) And for different scenes of the Internet of things, the ontology is respectively constructed and subdivided into each application scene, and when the data of the Internet of things is subjected to semantic processing, the data can be classified more accurately.
(3) The communication between the data acquisition module and the message forwarding module is carried out through the instant messaging protocol, so that real-time and reliable message service is provided, and the system reliability is higher.
Drawings
FIG. 1 is a schematic view of the overall structure of the present invention;
reference numerals: 1. the system comprises a data acquisition module 11, data acquisition equipment 12, a protocol conversion gateway 2, a message forwarding module 3, a real-time processing module 4, a first database 5 and a second database.
Detailed Description
The invention is described in detail below with reference to the figures and specific embodiments. The present embodiment is implemented on the premise of the technical solution of the present invention, and a detailed implementation manner and a specific operation process are given, but the scope of the present invention is not limited to the following embodiments.
Example 1:
an internet of things data semantic processing system is shown in fig. 1 and comprises a data acquisition module 1, a message forwarding module 2, a real-time processing module 3, a first database 4, a second database 5 and an offline processing module 6.
The data acquisition module 1 is connected with the message forwarding module 2 and used for acquiring Internet of things data; the data acquisition module 1 comprises data acquisition equipment 11 and a protocol conversion gateway 12, the number of the data acquisition equipment 11 is at least 1, the data acquisition equipment is used for acquiring Internet of things data, and the protocol conversion gateway 12 is used for receiving the data acquired by the data acquisition equipment 11, converting the data into IP data and transmitting the IP data to the message forwarding module 2.
In this embodiment, the data acquisition device 11 supports wireless general technologies including bluetooth, ZigBee, WiFi, and the like, supports a corresponding communication protocol, converts the data into IP data by the protocol conversion gateway 12, and transmits the IP data to the message forwarding module 2.
The message forwarding module 2 is connected with the real-time processing module 3 and the second database 5, respectively, and is configured to forward the data of the internet of things to the real-time processing module 3 or the second database 5.
An instant messaging protocol is adopted between the data acquisition module 1 and the Message forwarding module 2, and in this embodiment, an MQTT protocol (Message Queuing teletransmission) is adopted, and the MQTT protocol is a lightweight agent-based publish/subscribe Message transmission protocol. In other embodiments, other communication protocols may be used between the data collection module 1 and the message forwarding module 2.
In this embodiment, the message forwarding module 2 adopts a frame as a Flume frame, and the Flume frame uses an NG version. The data of the internet of things collected by the data collection module 1 is transmitted to the message forwarding module 2 through an MQTT protocol, the source of the fluorine NG receives the data of the internet of things, and the channels of the fluorine NG classify the data of the internet of things and respectively forward the data of the internet of things to the real-time processing module 3 or the second database 5 through the sink.
The user presets a real-time data type, if the data of the Internet of things is one of the real-time data, the data is forwarded to the real-time processing module 3 for semantic processing, and then the data is stored in the first database 4; otherwise, the data is forwarded to the second database 5 for storage. In the subsequent process, the user performs semantic processing on the data of the internet of things in the second database 5 through the offline processing module 6.
In this embodiment, the real-time data types include: data needing real-time processing such as traffic flow, positioning, temperature and humidity and the like; data with low real-time processing requirements, such as video monitoring and weblogs, are not of the real-time data type and are forwarded to the second database 5 for storage. In other embodiments, the user may also reset the real-time data type according to actual needs, and deploy the real-time data type to the message forwarding module 2 through OTA update.
The real-time processing module 3 is connected with the first database 4 and is used for performing semantic processing on the internet of things data and storing the internet of things data and a processing result into the first database 4;
the offline processing module 6 is connected to the second database 5, and is configured to perform semantic processing on the internet of things data stored in the second database 5 and store a processing result in the second database 5.
In this embodiment, the real-time processing module 3 is a combination of a Kafka framework and a Storm framework, and monitors the Storm state by using Zookeeper. The method comprises the steps that a Producer of Kafka obtains Internet of things data forwarded by flux NG; the Consumer of Kafka then forwards the data to the Storm framework; and carrying out subsequent processing on the data of the Internet of things by Storm, and simultaneously monitoring the Storm state by using Zookeeper. The Flume is a distributed system for acquiring, aggregating and transmitting mass logs; kafka is a distributed publish-subscribe messaging system that plays the role of messaging middleware in this framework. Storm is a distributed real-time big data processing framework; zookeeper is a distributed application coordination service.
The first database 4 and the second database 5 are distributed databases, which facilitate data storage and management.
In this embodiment, the second database 5 is an HDFS distributed file system, the offline processing module 6 is a Hadoop MapReduce, and subsequent calculation is performed on internet-of-things data stored in the HDFS distributed file system through the Hadoop MapReduce.
In the real-time processing module 3 and the offline processing module 6, the steps of performing semantic processing on the data of the internet of things are the same, and the method comprises the following steps:
s1: acquiring a constructed ontology library, wherein the ontology library comprises a plurality of different ontologies; each body corresponds to a different scene of the internet of things.
In this embodiment, the internet of things scenario is divided into 6 different scenarios: the intelligent building management system comprises an intelligent building, an intelligent community, an intelligent street lamp, an intelligent management network, an intelligent trip and an intelligent charging pile, wherein each scene is used as a field, RDF and RDFS are selected as ontology description language, and Prot é software is selected as ontology editing and knowledge acquiring software, and ontologies in each field are respectively constructed to obtain an ontology base.
S2: the data of the Internet of things is structured, expressed by using a uniform resource description model and then converted into vectors.
If the data of the Internet of things is text unstructured data, performing word segmentation on the data of the Internet of things and extracting keywords, extracting the keywords from the data after word segmentation by adopting a traditional TF/IDF (Trans-flash/IDF) -based algorithm, and expressing the keywords by using a uniform resource description model and converting the keywords into vectors; and if the data of the Internet of things is video and audio unstructured data, structuring the data of the Internet of things in an index establishing mode.
S3: and mapping the vectors to corresponding ontologies in an ontology base by a semantic similarity calculation method, and labeling semantic labels to obtain knowledge map data. In this embodiment, the similarity between the vector and each ontology is calculated based on the DSSM model, if the similarity is greater than a preset threshold, the vector is mapped onto the ontology, and the ontology is combined with the data to obtain the knowledge-graph data.
S4: storing the internet of things data and the corresponding knowledge graph data.
The foregoing detailed description of the preferred embodiments of the invention has been presented. It should be understood that numerous modifications and variations could be devised by those skilled in the art in light of the present teachings without departing from the inventive concepts. Therefore, the technical solutions available to those skilled in the art through logic analysis, reasoning and limited experiments based on the prior art according to the concept of the present invention should be within the scope of protection defined by the claims.
Claims (10)
1. The data semantic processing system of the Internet of things comprises a data acquisition module (1), and is characterized by further comprising a message forwarding module (2), a real-time processing module (3), a first database (4), a second database (5) and an offline processing module (6);
the data acquisition module (1) is connected with the message forwarding module (2) and is used for acquiring Internet of things data;
the message forwarding module (2) is respectively connected with the real-time processing module (3) and the second database (5) and is used for forwarding the data of the Internet of things to the real-time processing module (3) or the second database (5);
the real-time processing module (3) is connected with the first database (4) and is used for performing semantic processing on the Internet of things data and storing the Internet of things data and a processing result into the first database (4);
the offline processing module (6) is connected with the second database (5) and is used for performing semantic processing on the internet of things data stored in the second database (5) and storing a processing result to the second database (5).
2. The data semantic processing system of the internet of things as claimed in claim 1, wherein the data acquisition module (1) comprises data acquisition devices (11) and a protocol conversion gateway (12), the number of the data acquisition devices (11) is at least 1, the data acquisition devices are used for acquiring internet of things data, and the protocol conversion gateway (12) is used for receiving the data acquired by the data acquisition devices (11) and converting the data into IP data to be transmitted to the message forwarding module (2).
3. The data semantic processing system of the internet of things as claimed in claim 1, wherein an instant messaging protocol is adopted between the data acquisition module (1) and the message forwarding module (2).
4. The data semantic processing system of the internet of things as claimed in claim 1, characterized in that the first database (4) and the second database (5) are distributed databases.
5. The data semantic processing system of the internet of things as claimed in claim 4, characterized in that the second database (5) is an HDFS distributed file system.
6. The system for semantic processing of data of the internet of things according to claim 1, wherein the message forwarding module (2) is configured to forward the data of the internet of things to the real-time processing module (3) or the second database (5), specifically: acquiring a preset real-time data type; if the data of the Internet of things belongs to the preset real-time data type, the data of the Internet of things is forwarded to the real-time processing module (3), otherwise, the data of the Internet of things is forwarded to the second database (5) for storage.
7. The IOT data semantic processing system of claim 6, wherein the preset real-time data type is set according to real-time processing requirements of data.
8. The internet of things data semantic processing system according to claim 1, wherein the semantic processing of the internet of things data in the real-time processing module (3) and the offline processing module (6) specifically comprises the following steps:
s1: acquiring a constructed ontology library, wherein the ontology library comprises a plurality of different ontologies;
s2: structuring the data of the Internet of things, expressing the data by using a uniform resource description model, and converting the data into vectors;
s3: mapping the vector to a corresponding ontology in an ontology library by a semantic similarity calculation method, and labeling semantic labels to obtain knowledge map data;
s4: storing the internet of things data and the corresponding knowledge graph data.
9. The internet of things data semantic processing system according to claim 8, wherein in step S1, the ontology library includes a plurality of different ontologies, and each ontology corresponds to a different internet of things scene.
10. The internet of things data semantic processing system according to claim 8, wherein in step S2, the structuring of the internet of things data is specifically: if the data of the Internet of things is text unstructured data, performing word segmentation on the data of the Internet of things, extracting keywords, and expressing the keywords by using a uniform resource description model and converting the keywords into vectors; and if the data of the Internet of things is video and audio unstructured data, structuring the data of the Internet of things in an index establishing mode.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202011530692.2A CN112687267A (en) | 2020-12-22 | 2020-12-22 | Internet of things data semantic processing system |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202011530692.2A CN112687267A (en) | 2020-12-22 | 2020-12-22 | Internet of things data semantic processing system |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN112687267A true CN112687267A (en) | 2021-04-20 |
Family
ID=75450664
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202011530692.2A Pending CN112687267A (en) | 2020-12-22 | 2020-12-22 | Internet of things data semantic processing system |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN112687267A (en) |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116975313A (en) * | 2023-09-25 | 2023-10-31 | 国网江苏省电力有限公司电力科学研究院 | Semantic tag generation method and device based on electric power material corpus |
Citations (13)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102799632A (en) * | 2012-06-25 | 2012-11-28 | 北京航空航天大学 | Method for acquiring and describing text information based on visual basic application (VBA) and tetrahedron data model |
| CN103412903A (en) * | 2013-07-31 | 2013-11-27 | 无锡安拓思科技有限责任公司 | Method and system for interested object prediction based real-time search of Internet of Things |
| CN104361026A (en) * | 2014-10-22 | 2015-02-18 | 北京航空航天大学 | Failure knowledge storage and push method for FMEA (failure mode and effects analysis) process |
| CN104794003A (en) * | 2015-02-04 | 2015-07-22 | 汉鼎信息科技股份有限公司 | Large data analysis system integrating real-time mode and non-real-time mode |
| CN106230768A (en) * | 2016-06-16 | 2016-12-14 | 北京数智源科技股份有限公司 | Structuring system for managing video |
| WO2017075362A1 (en) * | 2015-10-30 | 2017-05-04 | Convida Wireless, Llc | Restful operations for semantic iot |
| CN106874397A (en) * | 2017-01-16 | 2017-06-20 | 华南理工大学 | A kind of automatic semanteme marking method of internet of things oriented equipment |
| CN107908690A (en) * | 2017-11-01 | 2018-04-13 | 南京欣网互联网络科技有限公司 | A kind of data processing method based on big data OA operation analysis |
| CN108446367A (en) * | 2018-03-15 | 2018-08-24 | 湖南工业大学 | A kind of the packaging industry data search method and equipment of knowledge based collection of illustrative plates |
| CN108965804A (en) * | 2018-07-06 | 2018-12-07 | 安徽超清科技股份有限公司 | A kind of video structural technology for city security protection |
| CN109495496A (en) * | 2018-12-11 | 2019-03-19 | 泰康保险集团股份有限公司 | Method of speech processing, device, electronic equipment and computer-readable medium |
| US20190222540A1 (en) * | 2018-01-16 | 2019-07-18 | Capital One Services, Llc | Automated chat assistant systems for providing interactive data using natural language processing |
| CN111966833A (en) * | 2019-05-19 | 2020-11-20 | 苏州嘉森华碧智能科技有限公司 | Scientific semantic understanding method based on knowledge graph |
-
2020
- 2020-12-22 CN CN202011530692.2A patent/CN112687267A/en active Pending
Patent Citations (13)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102799632A (en) * | 2012-06-25 | 2012-11-28 | 北京航空航天大学 | Method for acquiring and describing text information based on visual basic application (VBA) and tetrahedron data model |
| CN103412903A (en) * | 2013-07-31 | 2013-11-27 | 无锡安拓思科技有限责任公司 | Method and system for interested object prediction based real-time search of Internet of Things |
| CN104361026A (en) * | 2014-10-22 | 2015-02-18 | 北京航空航天大学 | Failure knowledge storage and push method for FMEA (failure mode and effects analysis) process |
| CN104794003A (en) * | 2015-02-04 | 2015-07-22 | 汉鼎信息科技股份有限公司 | Large data analysis system integrating real-time mode and non-real-time mode |
| WO2017075362A1 (en) * | 2015-10-30 | 2017-05-04 | Convida Wireless, Llc | Restful operations for semantic iot |
| CN106230768A (en) * | 2016-06-16 | 2016-12-14 | 北京数智源科技股份有限公司 | Structuring system for managing video |
| CN106874397A (en) * | 2017-01-16 | 2017-06-20 | 华南理工大学 | A kind of automatic semanteme marking method of internet of things oriented equipment |
| CN107908690A (en) * | 2017-11-01 | 2018-04-13 | 南京欣网互联网络科技有限公司 | A kind of data processing method based on big data OA operation analysis |
| US20190222540A1 (en) * | 2018-01-16 | 2019-07-18 | Capital One Services, Llc | Automated chat assistant systems for providing interactive data using natural language processing |
| CN108446367A (en) * | 2018-03-15 | 2018-08-24 | 湖南工业大学 | A kind of the packaging industry data search method and equipment of knowledge based collection of illustrative plates |
| CN108965804A (en) * | 2018-07-06 | 2018-12-07 | 安徽超清科技股份有限公司 | A kind of video structural technology for city security protection |
| CN109495496A (en) * | 2018-12-11 | 2019-03-19 | 泰康保险集团股份有限公司 | Method of speech processing, device, electronic equipment and computer-readable medium |
| CN111966833A (en) * | 2019-05-19 | 2020-11-20 | 苏州嘉森华碧智能科技有限公司 | Scientific semantic understanding method based on knowledge graph |
Non-Patent Citations (4)
| Title |
|---|
| 杨晓云: "海量数据处理需求下的物联网实施数据库设计", 《电子制作》 * |
| 王书龙 等: "《基于本体的物联网设备资源描述模型》", 《北京工业大学学报》 * |
| 韩黎晶: "《面向物联网数据的自动语义标注方法研究》", 《中国优秀博硕士学位论文全文数据库（硕士） 信息科技辑》 * |
| 齐力: "《公共安全大数据案例》", 《公共安全大数据技术与应用》 * |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116975313A (en) * | 2023-09-25 | 2023-10-31 | 国网江苏省电力有限公司电力科学研究院 | Semantic tag generation method and device based on electric power material corpus |
| CN116975313B (en) * | 2023-09-25 | 2023-12-05 | 国网江苏省电力有限公司电力科学研究院 | Semantic tag generation method and device based on electric power material corpus |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN111787066B (en) | Internet of things data platform based on big data and AI | |
| CN105045820B (en) | Method for processing video image information of high-level data and database system | |
| CN110933146B (en) | Data conversion method and device and server | |
| CN110601876A (en) | Intelligent Internet of things platform | |
| US10706062B2 (en) | Method and system for exchanging data from a big data source to a big data target corresponding to components of the big data source | |
| CN111294235B (en) | Data processing method, device, gateway and readable storage medium | |
| CN113032379B (en) | Distribution network operation and inspection-oriented multi-source data acquisition method | |
| CN110858192A (en) | Log query method and system, log checking system and query terminal | |
| CN112347105B (en) | General data service platform based on resource tree | |
| CN113054743A (en) | Internet of things terminal data access system and method suitable for power distribution cloud master station | |
| CN112217805A (en) | Power distribution Internet of things multimode protocol adaptation method | |
| CN112687267A (en) | Internet of things data semantic processing system | |
| CN112817539A (en) | Industrial data storage method and system, electronic device and storage medium | |
| CN113064858A (en) | Multi-system big data extraction and collection method for crossing isolation wall | |
| CN110661999A (en) | Video monitoring system based on big data | |
| Zhang et al. | Efficient online surveillance video processing based on spark framework | |
| CN109120742B (en) | UDP-based power distribution network terminal data acquisition method and device | |
| CN115858672A (en) | Power terminal management method and device, electronic equipment and storage medium | |
| CN202231739U (en) | Large-scale internet of things gateway system | |
| CN111461915A (en) | Photovoltaic power plant operation real-time information management system and management method | |
| CN215298210U (en) | Multistage edge computing system of electric power thing networking | |
| CN114390033A (en) | Loop state patrol instrument acquisition system and method based on extensible communication protocol | |
| CN202906974U (en) | Information influx device based on cloud computing | |
| CN112115140B (en) | Universal full-text search engine real-time data synchronization method and device | |
| CN113079055A (en) | Method and device for dynamically acquiring AGV (automatic guided vehicle) running data |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| RJ01 | Rejection of invention patent application after publication |
Application publication date: 20210420 |
|
| RJ01 | Rejection of invention patent application after publication |