CN113190572B - Searching method suitable for data acquired by unmanned aerial vehicle - Google Patents
Searching method suitable for data acquired by unmanned aerial vehicle Download PDFInfo
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- G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
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- G06F16/242—Query formulation
- G06F16/2425—Iterative querying; Query formulation based on the results of a preceding query
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Abstract
The invention discloses a searching method suitable for data collected by an unmanned aerial vehicle, which comprises the following steps: p1, receiving a search task, extracting keywords of task data, performing parallel sequencing according to the relevancy, and numbering; p2, connecting a server through a network, inquiring the state of the unmanned aerial vehicle, and locking the returned unmanned aerial vehicle; p3, connecting the locked unmanned aerial vehicle structure to acquire a data packet for acquiring information; p4, carrying out iterative search on the data packets according to the serial number sorting keywords, and capturing the associated data packets; p5, arranging the data packets according to the number of the iterations of the serial numbers, and marking the data packets; p6, downloading and storing data according to the marked data packet to form retrieval data; and P7, identifying data with the correlation degree not less than 80%, integrating to form search data, finishing a search task, and finally performing overall correlation integration of the correlation degree, so that the accuracy of the data is ensured, the timeliness is improved, and the method is favorable for popularization and use.
Description
Technical Field
The invention relates to the technical field of unmanned aerial vehicle data, in particular to a searching method suitable for data collected by an unmanned aerial vehicle.
Background
In the current social life and work, the unmanned aerial vehicle is applied to various industries, a large amount of relevant industry data can be generated, and in order to facilitate the development of industry specifications, the data of the unmanned aerial vehicle needs to be searched.
However, in the existing data search method, all the unmanned aerial vehicles are mostly subjected to data downloading and then are subjected to global search, so that the normal working state of the unmanned aerial vehicles is influenced, the acquisition of latest data is delayed, the data quantity to be integrated is large, accurate and relevant large iterative search cannot be continued, the redundancy quantity is large, the efficiency is low, accurate integration cannot be performed after search, the timeliness of data search is further low, and a new search method needs to be provided.
Disclosure of Invention
The invention aims to solve the defects in the prior art, and provides a searching method suitable for unmanned aerial vehicle data acquisition.
In order to achieve the purpose, the invention adopts the following technical scheme:
a searching method suitable for data collected by an unmanned aerial vehicle comprises the following steps:
p1, receiving a search task, extracting key words of task data, performing parallel sequencing according to the relevancy, and numbering;
p2, connecting a server through a network, inquiring the state of the unmanned aerial vehicle, and locking the returned unmanned aerial vehicle;
p3, connecting the locked unmanned aerial vehicle structure to acquire a data packet for acquiring information;
p4, performing iterative search on the data packets according to the serial number sorting keywords, and capturing the associated data packets;
p5, arranging and marking the data packets according to the number of the iterations of the numbers;
p6, downloading and storing data according to the marked data packet to form retrieval data;
p7, matching the retrieval data according to the complete search task, identifying the data with the correlation degree not less than 80%, and integrating to form the search data, so that the search task can be completed;
the iterative search of the P4 step comprises the following steps:
q1, arranging according to the numbered keywords to form a serial number 1, a serial number 2, a serial number 3 and a serial number 4;
q2, firstly searching for a single serial number, and searching for data packets respectively associated with the serial number 1, the serial number 2, the serial number 3 and the serial number 4 to form a primary iteration data packet;
q3, searching two keywords in the four serial numbers, performing second search in the primary iteration data packet, and performing the search in all
Secondly, forming a secondary iteration data packet;
q4, searching for three keywords in the four serial numbers, performing third search in the secondary iteration data packet, and performing the third search in the secondary iteration data packet
Then, forming a triple iteration data packet;
and Q5, respectively storing the primary iteration data packet, the secondary iteration data packet and the tertiary iteration data packet to form an integral data packet, and finishing iterative search.
Preferably, the unmanned aerial vehicle state of the step P2 includes an outgoing flight state, a prepared return state, a recovery yard shutdown state, and a maintenance state.
Preferably, the step P2 of locking the unmanned aerial vehicle includes locking the body of the unmanned aerial vehicle and task dispatch locking, and no longer performs a flight task.
Preferably, the mark of the step P5 is a first iteration data packet, a second iteration data packet is B, and a third iteration data packet is C.
Preferably, the P6 step search data is named and sorted according to the label, and compressed backup is performed.
Preferably, the correlation degree of the step P7 is a task semantic correlation degree and a keyword correlation degree, and is a multiplication calculation.
Preferably, in the step P7, data with a correlation degree of 60% to 80% is used as a preparation data packet, and data packets with a correlation degree of less than 60% are deleted.
According to the searching method suitable for the unmanned aerial vehicle data acquisition, the state of the unmanned aerial vehicle is inquired in one step, the data of the return unmanned aerial vehicle can be downloaded without influencing the normal operation of the unmanned aerial vehicle, the timeliness and the stability of data goods are ensured, meanwhile, the keyword search is carried out on the data, redundant data is effectively removed, the searching efficiency is improved, then, iterative retrieval is carried out, the accuracy of keyword association is ensured, finally, the overall correlation degree association integration is carried out, the accuracy of the data is ensured, the timeliness is improved, and the popularization and the use are facilitated.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention is described in further detail below with reference to specific embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.
A searching method suitable for data collected by an unmanned aerial vehicle comprises the following steps:
p1, receiving a search task, extracting keywords of task data, performing parallel sequencing according to the relevancy, and numbering;
p2, connecting a server through a network, inquiring the state of the unmanned aerial vehicle, and locking the returned unmanned aerial vehicle;
p3, connecting the locked unmanned aerial vehicle structure to acquire a data packet for acquiring information;
p4, carrying out iterative search on the data packets according to the serial number sorting keywords, and capturing the associated data packets;
p5, arranging the data packets according to the number of the iterations of the serial numbers, and marking the data packets;
p6, downloading and storing data according to the marked data packet to form retrieval data;
and P7, matching the retrieved data according to the complete search task, identifying the data with the correlation degree not less than 80%, and integrating to form the search data, so that the search task can be completed.
Preferably, the unmanned aerial vehicle state of the P2 step includes an outgoing flight state, a prepared return state, a recovery yard shutdown state, and a maintenance state.
Preferably, the step P2 of locking the drone includes locking the body of the drone and task dispatching, and no longer performing a flight task.
Preferably, the iterative search of step P4 includes the following steps:
q1, arranging according to the numbered keywords to form a serial number 1, a serial number 2, a serial number 3 and a serial number 4;
q2, firstly searching for a single serial number, and searching for data packets respectively associated with the serial number 1, the serial number 2, the serial number 3 and the serial number 4 to form a primary iteration data packet;
q3, searching two keywords in the four serial numbers, performing second search in the primary iteration data packet, and performing the search together
Secondly, forming a secondary iteration data packet;
q4, searching for three keywords in the four serial numbers, performing third search in the secondary iteration data packet, and performing the third search in the secondary iteration data packet
Thirdly, forming a cubic iteration data packet;
and Q5, respectively storing the primary iteration data packet, the secondary iteration data packet and the tertiary iteration data packet to form an integral data packet, and finishing iterative search.
Preferably, the mark of the step P5 is a first iteration data packet, a second iteration data packet is B, and a third iteration data packet is C.
Preferably, the P6 step retrieval data is named and sorted according to the label, and a compression backup is performed at the same time.
Preferably, the correlation degree of the step P7 is a task semantic correlation degree and a keyword correlation degree, and is calculated by multiplication.
Preferably, in the step P7, data with a correlation degree of 60% to 80% is used as a preparation data packet, and data packets with a correlation degree of less than 60% are deleted.
According to the searching method suitable for the unmanned aerial vehicle data collection, provided by the invention, the state of the unmanned aerial vehicle is inquired in one step, the data of the returning unmanned aerial vehicle can be downloaded without influencing the normal operation of the unmanned aerial vehicle, the timeliness and the stability of data goods are ensured, meanwhile, the keyword search is carried out on the data, the redundant data is effectively removed, the searching efficiency is improved, then, the iterative retrieval is carried out, the keyword association accuracy is ensured, and finally, the overall correlation degree association integration is carried out, the data accuracy is ensured, the timeliness is improved, and the method is favorable for popularization and use.
Claims (7)
1. The utility model provides a search method suitable for unmanned aerial vehicle data collection which characterized in that: the searching method comprises the following steps:
p1, receiving a search task, extracting key words of task data, performing parallel sequencing according to the relevancy, and numbering;
p2, connecting a server through a network, inquiring the state of the unmanned aerial vehicle, and locking the returned unmanned aerial vehicle;
p3, connecting the locked unmanned aerial vehicle structure to acquire a data packet for acquiring information;
p4, carrying out iterative search on the data packets according to the serial number sorting keywords, and capturing the associated data packets;
p5, arranging the data packets according to the number of the iterations of the serial numbers, and marking the data packets;
p6, downloading and storing data according to the marked data packet to form retrieval data;
p7, matching the retrieval data according to the complete search task, identifying the data with the correlation degree not less than 80%, and integrating to form the search data, so that the search task can be completed;
the iterative search of the step P4 comprises the following steps:
q1, arranging according to the numbered keywords to form a serial number 1, a serial number 2, a serial number 3 and a serial number 4;
q2, firstly searching for a single serial number, and searching for data packets respectively associated with the serial number 1, the serial number 2, the serial number 3 and the serial number 4 to form a primary iteration data packet;
q3, searching two keywords in the four serial numbers, performing second search in the primary iteration data packet, and performing the search together
Secondly, forming a secondary iteration data packet;
q4, searching for three keywords in the four serial numbers, performing third search in the secondary iteration data packet, and performing the third search in the secondary iteration data packet
Then, forming a triple iteration data packet;
and Q5, respectively storing the primary iteration data packet, the secondary iteration data packet and the tertiary iteration data packet to form an integral data packet, and finishing iterative search.
2. A search method applicable to data acquisition by drones according to claim 1, characterized in that: the unmanned aerial vehicle state of P2 step includes the flight state of going out, prepares the state of returning to the throne, retrieves field shut down state and maintenance state.
3. The search method applicable to data acquisition by unmanned aerial vehicles according to claim 1, characterized in that: and the step P2 of locking the unmanned aerial vehicle comprises locking the body of the unmanned aerial vehicle and dispatching and locking the task, so that the flying task is not carried out any more.
4. The search method applicable to data acquisition by unmanned aerial vehicles according to claim 1, characterized in that: and marking the data packet in the step P5 as a primary iteration data packet A, marking the data packet in the step B as a secondary iteration data packet B and marking the data packet in the step C as a tertiary iteration data packet C.
5. The search method applicable to data acquisition by unmanned aerial vehicles according to claim 1, characterized in that: and the P6 step of searching data is named and sorted according to the marks, and simultaneously, compression backup is carried out.
6. The search method applicable to data acquisition by unmanned aerial vehicles according to claim 1, characterized in that: and the relevance of the step P7 is task semantic relevance and keyword relevance and is multiplication calculation.
7. A search method applicable to data acquisition by drones according to claim 1, characterized in that: and in the step P7, data with the correlation degree of 60% -80% is used as a preparation data packet, and data packets with the correlation degree of less than 60% are deleted.
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Citations (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN108293187A (en) * | 2016-02-10 | 2018-07-17 | 加拿大Bc省温哥华迷锋企业有限公司 | Using bio-identification come certification or the user of registration wearable device |
| CN109447048A (en) * | 2018-12-25 | 2019-03-08 | 苏州闪驰数控系统集成有限公司 | A kind of artificial intelligence early warning system |
| CN110971291A (en) * | 2019-12-13 | 2020-04-07 | 天宇经纬（北京）科技有限公司 | Unmanned aerial vehicle data communication method, device and system for adding key information |
| CN111353113A (en) * | 2020-02-28 | 2020-06-30 | 江苏方天电力技术有限公司 | Visual rendering method suitable for high-frequency state data of unmanned aerial vehicle |
| CN211076324U (en) * | 2019-12-04 | 2020-07-24 | 普华鹰眼科技发展有限公司 | Anti structure of falling of unmanned aerial vehicle |
| CN111452988A (en) * | 2020-01-09 | 2020-07-28 | 国网内蒙古东部电力有限公司呼伦贝尔供电公司 | A UAV multi-machine collaborative intelligent inspection system and method based on ubiquitous power Internet of Things |
| CN111479086A (en) * | 2019-01-04 | 2020-07-31 | 西南林业大学 | UAV intelligent real-time command management system |
| CN111800180A (en) * | 2020-05-12 | 2020-10-20 | 萧县航迅信息技术有限公司 | Rescue target discovery system and method for field unmanned aerial vehicle |
Family Cites Families (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US8989922B2 (en) * | 2013-03-15 | 2015-03-24 | Azure Sky Group, LLC. | Modular drone and methods for use |
| CN105737819B (en) * | 2016-02-25 | 2018-10-23 | 西北工业大学 | No-manned plane three-dimensional Route planner based on space compression and computation of table lookup |
| US10572563B2 (en) * | 2017-04-05 | 2020-02-25 | Toyota Research Institute, Inc. | Mobile computing systems and methods for accessing data |
| WO2019068076A1 (en) * | 2017-09-29 | 2019-04-04 | United Parcel Service Of America, Inc. | Predictive parcel damage identification, analysis, and mitigation |
-
2021
- 2021-04-15 CN CN202110405519.8A patent/CN113190572B/en not_active Expired - Fee Related
Patent Citations (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN108293187A (en) * | 2016-02-10 | 2018-07-17 | 加拿大Bc省温哥华迷锋企业有限公司 | Using bio-identification come certification or the user of registration wearable device |
| CN109447048A (en) * | 2018-12-25 | 2019-03-08 | 苏州闪驰数控系统集成有限公司 | A kind of artificial intelligence early warning system |
| CN111479086A (en) * | 2019-01-04 | 2020-07-31 | 西南林业大学 | UAV intelligent real-time command management system |
| CN211076324U (en) * | 2019-12-04 | 2020-07-24 | 普华鹰眼科技发展有限公司 | Anti structure of falling of unmanned aerial vehicle |
| CN110971291A (en) * | 2019-12-13 | 2020-04-07 | 天宇经纬（北京）科技有限公司 | Unmanned aerial vehicle data communication method, device and system for adding key information |
| CN111452988A (en) * | 2020-01-09 | 2020-07-28 | 国网内蒙古东部电力有限公司呼伦贝尔供电公司 | A UAV multi-machine collaborative intelligent inspection system and method based on ubiquitous power Internet of Things |
| CN111353113A (en) * | 2020-02-28 | 2020-06-30 | 江苏方天电力技术有限公司 | Visual rendering method suitable for high-frequency state data of unmanned aerial vehicle |
| CN111800180A (en) * | 2020-05-12 | 2020-10-20 | 萧县航迅信息技术有限公司 | Rescue target discovery system and method for field unmanned aerial vehicle |
Non-Patent Citations (4)
| Title |
|---|
| Control integrated query processing system for coordination of multiple UAVs;Sangwoo Shim等;《2017 14th IEEE Annual Consumer Communications & Networking Conference (CCNC)》;20170720;第528-533页 * |
| 无人机故障数据快速检索系统;贾木子;《中国优秀硕士学位论文全文数据库工程科技Ⅱ辑》;20140815(第8期);第C031-67页 * |
| 无人机海量飞行数据快速检索方法研究;徐新爱;《计算机测量与控制》;20141225;第22卷(第12期);第4181-4183、4196页 * |
| 釜溪河流域高分航空影像处理及数字平台系统;李志鹏;《中国优秀硕士学位论文全文数据库基础科学辑》;20180915(第9期);第A008-49页 * |
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