CN112291494A - Unmanned aerial vehicle 4K video directional forwarding system based on 5G communication - Google Patents
Unmanned aerial vehicle 4K video directional forwarding system based on 5G communication Download PDFInfo
- Publication number
- CN112291494A CN112291494A CN202011173485.6A CN202011173485A CN112291494A CN 112291494 A CN112291494 A CN 112291494A CN 202011173485 A CN202011173485 A CN 202011173485A CN 112291494 A CN112291494 A CN 112291494A
- Authority
- CN
- China
- Prior art keywords
- monitoring
- video data
- video
- marking
- sub
- 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
Images
Classifications
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
- H04N7/00—Television systems
- H04N7/18—Closed-circuit television [CCTV] systems, i.e. systems in which the video signal is not broadcast
- H04N7/181—Closed-circuit television [CCTV] systems, i.e. systems in which the video signal is not broadcast for receiving images from a plurality of remote sources
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
- H04N19/00—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals
- H04N19/40—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using video transcoding, i.e. partial or full decoding of a coded input stream followed by re-encoding of the decoded output stream
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
- H04N19/00—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals
- H04N19/42—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals characterised by implementation details or hardware specially adapted for video compression or decompression, e.g. dedicated software implementation
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
- H04N5/00—Details of television systems
- H04N5/76—Television signal recording
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W4/00—Services specially adapted for wireless communication networks; Facilities therefor
- H04W4/02—Services making use of location information
- H04W4/021—Services related to particular areas, e.g. point of interest [POI] services, venue services or geofences
Landscapes
- Engineering & Computer Science (AREA)
- Signal Processing (AREA)
- Multimedia (AREA)
- Computer Networks & Wireless Communication (AREA)
- Closed-Circuit Television Systems (AREA)
Abstract
The invention discloses an unmanned aerial vehicle 4K video directional forwarding system based on 5G communication, which relates to the technical field of video monitoring and comprises a video acquisition module, a data processing module, a server, a storage module, a data entry module and a video forwarding module; the video acquisition module is used for acquiring video data inside and outside the operation site, dividing the monitoring area into a plurality of monitoring sub-areas, calculating to obtain a monitoring value of each monitoring sub-area, and sequentially transmitting the video data of the corresponding monitoring sub-areas to the data processing module according to the sequence of the monitoring values from large to small, so that the video data transmission is more hierarchical and orderly, and the video data transmission efficiency is accelerated; the video forwarding module is used for forwarding the video data corresponding to the monitoring sub-area to the user terminal, firstly decoding the acquired video data, and then re-encoding the decoded video data in a predetermined encoding mode, so that a user can conveniently and safely view the video data.
Description
Technical Field
The invention relates to the technical field of video monitoring, in particular to a 5G communication-based 4K video directional forwarding system for an unmanned aerial vehicle.
Background
The video monitoring system is used as a component of a safety precaution system, bears image information of monitoring points in the governed area mastered by monitoring personnel, records and pre-warns events, avoids damage to company and personal property, or carries out remote command and comprehensive processing on emergency events of the monitoring points, and has the requirements of high definition, stability and real-time performance; the security of video data itself is receiving more and more attention;
the video monitoring system is subject to the evolution of the third generation, the third generation digital system is based on the network camera technology, the video information is completely transmitted through the standard Ethernet protocol and the channel, the video code rate is low, the universality and the maintainability of the network are obviously improved, but for the monitoring camera, different manufacturers may adopt the coding modes of H.263, H.264, MJPEG, MPEG4 and the like. When watching the monitoring video, the user needs to adopt a corresponding decoding mode to decode, which brings great trouble to the user; the network security and the dispersion of video monitoring areas cause difficulty in management, and the network security situation meets great challenges; secure, stable and efficient forwarding of video streams is becoming a problem to be solved.
Disclosure of Invention
Aiming at the defects in the prior art, the invention aims to provide a 5G communication-based unmanned aerial vehicle 4K video directional forwarding system. According to the invention, the monitoring area is divided into a plurality of monitoring sub-areas, the monitoring value of each monitoring sub-area is obtained through calculation, and then the video data of the corresponding monitoring sub-areas are sequentially transmitted to the data processing module according to the sequence of the monitoring values from large to small, so that the video data transmission is more hierarchical and orderly, and the video data transmission efficiency is accelerated; the video forwarding module is used for forwarding the video data corresponding to the monitoring subarea to the user terminal, firstly decoding the acquired video data, and then re-encoding the decoded video data in a predetermined encoding mode; encrypting the recoded video data by adopting a Data Encryption Standard (DES) algorithm; the encrypted video data is forwarded to the client; the client side decrypts the received video data by adopting a corresponding decryption algorithm, and can check the required video data after decoding by adopting a corresponding decoding algorithm; the video data can be conveniently and safely viewed by the user.
The purpose of the invention can be realized by the following technical scheme: the unmanned aerial vehicle 4K video directional forwarding system based on 5G communication comprises a video acquisition module, a data processing module, a server, a storage module, a data entry module and a video forwarding module;
the video acquisition module is used for acquiring video data inside and outside the operation site and sending the video data to the data processing module; the data processing module is used for receiving the video data transmitted by the video acquisition module and processing the video data, and the specific processing steps are as follows:
s1: classifying the video data according to the monitoring subareas;
s2: compressing video data of the same monitoring subarea according to the monitoring subarea at intervals of preset interval time, and temporarily storing the compressed video data into a cache region;
s3: after all the collected video data are compressed, sending the compressed video data to a server, and then deleting the data in the cache region;
the server transmits the compressed video data to a storage module through a 5G network for real-time storage;
when a user needs to retrieve video data, the user inputs a video retrieval request for a designated monitoring sub-area through the data entry module; the data entry module transmits the video retrieval request to a server; the video retrieval request comprises a request for retrieving video data acquired in real time and a request for retrieving video data in a specified time period;
the server acquires video data corresponding to the monitoring subarea from the storage module according to the video retrieval request and sends the video data corresponding to the monitoring subarea to the video forwarding module;
the video forwarding module is used for forwarding the video data corresponding to the monitoring sub-area to the user terminal, and the specific forwarding steps are as follows:
SS 1: acquiring video data corresponding to the monitoring subarea, and decoding the acquired video data, wherein the method comprises the following steps:
SS 11: automatically acquiring a corresponding monitoring camera from a monitoring mapping table in a storage module according to a monitoring sub-region;
SS 12: the video forwarding module acquires a decoding algorithm of a corresponding monitoring camera from the database, and decodes the acquired video data by applying the decoding algorithm; the database stores decoding algorithms corresponding to each monitoring camera;
SS 2: re-encoding the decoded video data in a predetermined encoding manner; the predetermined coding mode is an H.264 coding mode;
SS 3: encrypting the recoded video data by adopting a data encryption standard algorithm;
SS 4: and forwarding the encrypted video data to the client.
Furthermore, the video acquisition module is a plurality of surveillance cameras distributed at various positions inside and outside the operation site, and the surveillance cameras are provided with position marks.
Further, the specific working steps of the video acquisition module are as follows:
the method comprises the following steps: dividing a monitoring area into a plurality of monitoring sub-areas, setting a plane coordinate system according to a plane where the monitoring area is located, and marking coordinates of the plurality of monitoring sub-areas as Ai (Xi, Yi); acquiring a monitoring camera of each monitoring sub-area, generating a monitoring mapping table of the monitoring sub-areas and the monitoring cameras, and transmitting the monitoring mapping table to a storage module for storage;
step two: acquiring operating equipment data in a plurality of monitoring sub-areas, wherein the operating equipment data comprises operating equipment models and operating equipment prices;
step three: marking the number of the operation equipment of the same monitoring subarea as the subarea total number according to the monitoring subarea, and marking the subarea total number as Ni;
step four: accumulating the attraction values of the operation equipment of the same monitoring subarea according to the monitoring subarea to form subarea total attraction, and marking the subarea total attraction as Fi; the method for calculating the attraction value of the working equipment comprises the following steps:
setting each operating equipment model to correspond to a preset value, matching the operating equipment model with the preset value corresponding to the model to obtain a preset value corresponding to the operating equipment, and marking the preset value as Jp;
marking the price of the operating equipment as Hp;
obtaining an attraction value Gp of the working equipment by using a formula Gp of Jp × z1+ Hp × z2, wherein z1 and z2 are preset coefficients;
step five: acquiring the number of times of reading the video data of each monitoring sub-area within preset time, marking the number of times of reading, and marking the number of times of reading as Ri;
acquiring the total time length of the video data of each monitoring subarea in the preset time, marking the total time length as the total time length of the retrieval, and marking the total time length of the retrieval as TRi;
the total retrieval time length is the sum of the retrieval time lengths of the video data of the monitoring subarea each time;
acquiring the early warning times of each monitoring sub-region within preset time and marking the early warning times as Ci;
step six: carrying out weight distribution on the total amount of the sub-regions, the total attraction of the sub-regions, the retrieval frequency, the total retrieval time and the early warning times, marking the weight of the total amount of the sub-regions as A1, marking the weight of the total attraction of the sub-regions as A2, marking the weight of the retrieval frequency as A3, marking the weight of the total retrieval time as A4 and marking the weight of the early warning times as A5;
step seven: respectively calculating a monitoring value Qi of each monitoring sub-region by using a formula of Ni multiplied by A1+ Fi multiplied by A2+ Ri multiplied by A3+ TRi multiplied by A4+ Ci multiplied by A5;
and the video acquisition module sequentially transmits the video data of the corresponding monitoring sub-regions to the data processing module according to the sequence of the monitoring values Qi from large to small.
The invention has the beneficial effects that:
1. the invention collects the video data inside and outside the operation field through the video collection module; dividing a monitoring area into a plurality of monitoring sub-areas, establishing a monitoring mapping table of the monitoring sub-areas and a monitoring camera, acquiring operating equipment data in the plurality of monitoring sub-areas, marking the number of the operating equipment in the same monitoring sub-area as the total number of the sub-areas according to the monitoring sub-areas, accumulating the attraction values of the operating equipment in the same monitoring sub-area according to the monitoring sub-areas to form total sub-area attraction, acquiring the number of times of reading video data of each monitoring sub-area in preset time and marking the frequency of reading, acquiring the total time length of reading the video data of each monitoring sub-area in the preset time and marking the total time length of reading, and acquiring the early warning number of times of each monitoring sub-area in the preset time; the monitoring value Qi of each monitoring subregion is obtained by combining the total number of the subregions, the total attraction of the subregions, the retrieval frequency, the retrieval total time and the early warning frequency, and the video acquisition module transmits the video data of the corresponding monitoring subregions to the data processing module in sequence according to the sequence of the monitoring values Qi from large to small, so that the video data transmission is more hierarchical and orderly, and the video data transmission efficiency is improved;
2. the video forwarding module forwards the video data of the corresponding monitoring subarea to the user terminal, firstly decodes the acquired video data, and then re-encodes the decoded video data in a predetermined encoding mode; encrypting the recoded video data by adopting a Data Encryption Standard (DES) algorithm; the encrypted video data is forwarded to the client; the client side decrypts the received video data by adopting a corresponding decryption algorithm, and can check the required video data after decoding by adopting a corresponding decoding algorithm; the video data can be conveniently and safely viewed by the user.
Drawings
In order to facilitate understanding for those skilled in the art, the present invention will be further described with reference to the accompanying drawings.
FIG. 1 is a block diagram of the system of the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
As shown in fig. 1, the unmanned aerial vehicle 4K video directional forwarding system based on 5G communication includes a video acquisition module, a data processing module, a server, a storage module, a data entry module, and a video forwarding module;
the video acquisition module is used for acquiring video data inside and outside an operation site and sending the video data to the data processing module for processing, the video acquisition module comprises a plurality of monitoring cameras distributed inside and outside the operation site, and the monitoring cameras are provided with position marks;
the video acquisition module comprises the following specific working steps:
the method comprises the following steps: dividing a monitoring area into a plurality of monitoring sub-areas, setting a plane coordinate system according to a plane where the monitoring area is located, and marking coordinates of the plurality of monitoring sub-areas as Ai (Xi, Yi); acquiring a monitoring camera of each monitoring sub-area, generating a monitoring mapping table of the monitoring sub-areas and the monitoring cameras, and transmitting the monitoring mapping table to a storage module for storage;
step two: acquiring operating equipment data in a plurality of monitoring sub-areas, wherein the operating equipment data comprises operating equipment models and operating equipment prices;
step three: marking the number of the operation equipment of the same monitoring subarea as the subarea total number according to the monitoring subarea, and marking the subarea total number as Ni;
step four: accumulating the attraction values of the operation equipment of the same monitoring subarea according to the monitoring subarea to form subarea total attraction, and marking the subarea total attraction as Fi; the method for calculating the attraction value of the working equipment comprises the following steps:
setting each operating equipment model to correspond to a preset value, matching the operating equipment model with the preset value corresponding to the model to obtain a preset value corresponding to the operating equipment, and marking the preset value as Jp;
marking the price of the operating equipment as Hp;
obtaining an attraction value Gp of the working equipment by using a formula Gp of Jp × z1+ Hp × z2, wherein z1 and z2 are preset coefficients;
step five: acquiring the number of times of reading the video data of each monitoring sub-area within preset time, marking the number of times of reading, and marking the number of times of reading as Ri;
acquiring the total time length of the video data of each monitoring subarea in the preset time, marking the total time length as the total time length of the retrieval, and marking the total time length of the retrieval as TRi;
the total retrieval time length is the sum of the retrieval time lengths of the video data of the monitoring subarea each time;
acquiring the early warning times of each monitoring sub-region within preset time and marking the early warning times as Ci;
step six: carrying out weight distribution on the total amount of the sub-regions, the total attraction of the sub-regions, the retrieval frequency, the total retrieval time and the early warning times, marking the weight of the total amount of the sub-regions as A1, marking the weight of the total attraction of the sub-regions as A2, marking the weight of the retrieval frequency as A3, marking the weight of the total retrieval time as A4 and marking the weight of the early warning times as A5;
step seven: respectively calculating a monitoring value Qi of each monitoring sub-region by using a formula of Ni multiplied by A1+ Fi multiplied by A2+ Ri multiplied by A3+ TRi multiplied by A4+ Ci multiplied by A5;
the video acquisition module sequentially transmits the video data of the corresponding monitoring sub-regions to the data processing module according to the sequence from large to small of the monitoring value Qi, so that the video data transmission is more hierarchical and orderly, and the video data transmission efficiency is accelerated;
the data processing module is used for receiving the video data transmitted by the video acquisition module and processing the video data, and the specific processing steps are as follows:
s1: classifying the video data according to the monitoring subareas;
s2: compressing video data of the same monitoring subarea according to the monitoring subarea at intervals of preset interval time, and temporarily storing the compressed video data into a cache region;
s3: after all the collected video data are compressed, sending the compressed video data to a server, and then deleting the data in the cache region;
the server transmits the compressed video data to a storage module through a 5G network for real-time storage;
when a user needs to retrieve video data, the user inputs a video retrieval request for a designated monitoring sub-area through the data entry module; the data entry module transmits the video retrieval request to a server; the video retrieval request comprises a request for retrieving video data acquired in real time and a request for retrieving video data in a specified time period;
the server acquires video data corresponding to the monitoring subarea from the storage module according to the video retrieval request and sends the video data corresponding to the monitoring subarea to the video forwarding module;
the video forwarding module is used for forwarding the video data corresponding to the monitoring sub-area to the user terminal, and the specific forwarding steps are as follows:
SS 1: acquiring video data corresponding to the monitoring subarea, and decoding the acquired video data, wherein the method comprises the following steps:
SS 11: automatically acquiring a corresponding monitoring camera from a monitoring mapping table in a storage module according to a monitoring sub-region;
SS 12: the video forwarding module acquires a decoding algorithm of a corresponding monitoring camera from the database, and decodes the acquired video data by applying the decoding algorithm; the database stores decoding algorithms corresponding to each monitoring camera;
SS 2: re-encoding the decoded video data in a predetermined encoding manner; the predetermined coding mode is an H.264 coding mode;
SS 3: encrypting the recoded video data by adopting a Data Encryption Standard (DES) algorithm;
SS 4: forwarding the encrypted video data to a client;
the client side decrypts the received video data by adopting a corresponding decryption algorithm, and can check the required video data after decoding by adopting a corresponding decoding algorithm; the video data can be conveniently and safely viewed by the user.
When the unmanned aerial vehicle 4K video directional forwarding system based on 5G communication works, the video acquisition module is used for acquiring video data inside and outside an operation site; dividing a monitoring area into a plurality of monitoring sub-areas, establishing a monitoring mapping table of the monitoring sub-areas and a monitoring camera, acquiring operating equipment data in the plurality of monitoring sub-areas, marking the number of the operating equipment in the same monitoring sub-area as the total number of the sub-areas according to the monitoring sub-areas, accumulating the attraction values of the operating equipment in the same monitoring sub-area according to the monitoring sub-areas to form total sub-area attraction, acquiring the number of times of reading video data of each monitoring sub-area in preset time and marking the frequency of reading, acquiring the total time length of reading the video data of each monitoring sub-area in the preset time and marking the total time length of reading, and acquiring the early warning number of times of each monitoring sub-area in the preset time; the monitoring value Qi of each monitoring subregion is obtained by combining the total number of the subregions, the total attraction of the subregions, the retrieval frequency, the retrieval total time and the early warning frequency, and the video acquisition module transmits the video data of the corresponding monitoring subregions to the data processing module in sequence according to the sequence of the monitoring values Qi from large to small, so that the video data transmission is more hierarchical and orderly, and the video data transmission efficiency is improved;
the data processing module classifies and compresses the video data according to the monitoring subarea, and then transmits the compressed video data to the storage module through the 5G network for real-time storage, so that the storage pressure of the video data is relieved, and the video data is convenient to search when a user needs to retrieve the video data;
when a user needs to retrieve video data, the user inputs a video retrieval request for a designated monitoring sub-area through the data entry module; the server acquires video data corresponding to the monitoring subarea from the storage module according to the video retrieval request and sends the video data corresponding to the monitoring subarea to the video forwarding module; the video forwarding module is used for forwarding the video data corresponding to the monitoring subarea to the user terminal, firstly decoding the acquired video data, and then re-encoding the decoded video data in a predetermined encoding mode; encrypting the recoded video data by adopting a Data Encryption Standard (DES) algorithm; the encrypted video data is forwarded to the client; the client side decrypts the received video data by adopting a corresponding decryption algorithm, and can check the required video data after decoding by adopting a corresponding decoding algorithm; the video data can be conveniently and safely viewed by the user.
The above formulas are all obtained by collecting a large amount of data to perform software simulation and performing parameter setting processing by corresponding experts, and the formulas are in accordance with real results.
The preferred embodiments of the invention disclosed above are intended to be illustrative only. The preferred embodiments are not intended to be exhaustive or to limit the invention to the precise forms disclosed. Obviously, many modifications and variations are possible in light of the above teaching. The embodiments were chosen and described in order to best explain the principles of the invention and the practical application, to thereby enable others skilled in the art to best utilize the invention. The invention is limited only by the claims and their full scope and equivalents.
Claims (3)
1. The unmanned aerial vehicle 4K video directional forwarding system based on 5G communication is characterized by comprising a video acquisition module, a data processing module, a server, a storage module, a data entry module and a video forwarding module;
the video acquisition module is used for acquiring video data inside and outside the operation site and sending the video data to the data processing module; the data processing module is used for receiving the video data transmitted by the video acquisition module and processing the video data, and the specific processing steps are as follows:
s1: classifying the video data according to the monitoring subareas;
s2: compressing video data of the same monitoring subarea according to the monitoring subarea at intervals of preset interval time, and temporarily storing the compressed video data into a cache region;
s3: after all the collected video data are compressed, sending the compressed video data to a server, and then deleting the data in the cache region;
the server transmits the compressed video data to a storage module through a 5G network for real-time storage;
when a user needs to retrieve video data, the user inputs a video retrieval request for a designated monitoring sub-area through the data entry module; the data entry module transmits the video retrieval request to a server; the video retrieval request comprises a request for retrieving video data acquired in real time and a request for retrieving video data in a specified time period;
the server acquires video data corresponding to the monitoring subarea from the storage module according to the video retrieval request and sends the video data corresponding to the monitoring subarea to the video forwarding module;
the video forwarding module is used for forwarding the video data corresponding to the monitoring sub-area to the user terminal, and the specific forwarding steps are as follows:
SS 1: acquiring video data corresponding to the monitoring subarea, and decoding the acquired video data, wherein the method comprises the following steps:
SS 11: automatically acquiring a corresponding monitoring camera from a monitoring mapping table in a storage module according to a monitoring sub-region;
SS 12: the video forwarding module acquires a decoding algorithm of a corresponding monitoring camera from the database, and decodes the acquired video data by applying the decoding algorithm; the database stores decoding algorithms corresponding to each monitoring camera;
SS 2: re-encoding the decoded video data in a predetermined encoding manner; the predetermined coding mode is an H.264 coding mode;
SS 3: encrypting the recoded video data by adopting a data encryption standard algorithm;
SS 4: and forwarding the encrypted video data to the client.
2. The unmanned aerial vehicle 4K video directional forwarding system based on 5G communication of claim 1, wherein the video acquisition module is a plurality of surveillance cameras distributed in various places inside and outside the operation site, and the surveillance cameras have position marks.
3. The unmanned aerial vehicle 4K video directional forwarding system based on 5G communication of claim 1, wherein the video acquisition module comprises the following specific working steps:
the method comprises the following steps: dividing a monitoring area into a plurality of monitoring sub-areas, setting a plane coordinate system according to a plane where the monitoring area is located, and marking coordinates of the plurality of monitoring sub-areas as Ai (Xi, Yi); acquiring a monitoring camera of each monitoring sub-area, generating a monitoring mapping table of the monitoring sub-areas and the monitoring cameras, and transmitting the monitoring mapping table to a storage module for storage;
step two: acquiring operating equipment data in a plurality of monitoring sub-areas, wherein the operating equipment data comprises operating equipment models and operating equipment prices;
step three: marking the number of the operation equipment of the same monitoring subarea as the subarea total number according to the monitoring subarea, and marking the subarea total number as Ni;
step four: accumulating the attraction values of the operation equipment of the same monitoring subarea according to the monitoring subarea to form subarea total attraction, and marking the subarea total attraction as Fi; the method for calculating the attraction value of the working equipment comprises the following steps:
setting each operating equipment model to correspond to a preset value, matching the operating equipment model with the preset value corresponding to the model to obtain a preset value corresponding to the operating equipment, and marking the preset value as Jp;
marking the price of the operating equipment as Hp;
obtaining an attraction value Gp of the working equipment by using a formula Gp of Jp × z1+ Hp × z2, wherein z1 and z2 are preset coefficients;
step five: acquiring the number of times of reading the video data of each monitoring sub-area within preset time, marking the number of times of reading, and marking the number of times of reading as Ri;
acquiring the total time length of the video data of each monitoring subarea in the preset time, marking the total time length as the total time length of the retrieval, and marking the total time length of the retrieval as TRi;
the total retrieval time length is the sum of the retrieval time lengths of the video data of the monitoring subarea each time;
acquiring the early warning times of each monitoring sub-region within preset time and marking the early warning times as Ci;
step six: carrying out weight distribution on the total amount of the sub-regions, the total attraction of the sub-regions, the retrieval frequency, the total retrieval time and the early warning times, marking the weight of the total amount of the sub-regions as A1, marking the weight of the total attraction of the sub-regions as A2, marking the weight of the retrieval frequency as A3, marking the weight of the total retrieval time as A4 and marking the weight of the early warning times as A5;
step seven: respectively calculating a monitoring value Qi of each monitoring sub-region by using a formula of Ni multiplied by A1+ Fi multiplied by A2+ Ri multiplied by A3+ TRi multiplied by A4+ Ci multiplied by A5;
and the video acquisition module sequentially transmits the video data of the corresponding monitoring sub-regions to the data processing module according to the sequence of the monitoring values Qi from large to small.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202011173485.6A CN112291494B (en) | 2020-10-28 | 2020-10-28 | Unmanned aerial vehicle 4K video directional forwarding system based on 5G communication |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202011173485.6A CN112291494B (en) | 2020-10-28 | 2020-10-28 | Unmanned aerial vehicle 4K video directional forwarding system based on 5G communication |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN112291494A true CN112291494A (en) | 2021-01-29 |
| CN112291494B CN112291494B (en) | 2022-12-16 |
Family
ID=74373103
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202011173485.6A Active CN112291494B (en) | 2020-10-28 | 2020-10-28 | Unmanned aerial vehicle 4K video directional forwarding system based on 5G communication |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN112291494B (en) |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113485992A (en) * | 2021-07-08 | 2021-10-08 | 国网冀北电力有限公司计量中心 | Data processing method and device |
Citations (10)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US6476858B1 (en) * | 1999-08-12 | 2002-11-05 | Innovation Institute | Video monitoring and security system |
| CN102860003A (en) * | 2010-03-09 | 2013-01-02 | 常州环视高科电子科技有限公司 | A surveillance system and method |
| CN104104145A (en) * | 2013-04-02 | 2014-10-15 | 南京中兴力维软件有限公司 | Transformer station monitoring realization method and transformer station monitoring system thereof |
| WO2015054816A1 (en) * | 2013-10-14 | 2015-04-23 | Microsoft Technology Licensing, Llc | Encoder-side options for base color index map mode for video and image coding |
| US20160196268A1 (en) * | 2015-01-07 | 2016-07-07 | International Business Machines Corporation | Prioritizing video surveillance media |
| CN106162109A (en) * | 2016-08-30 | 2016-11-23 | 浙江大华技术股份有限公司 | A kind of remote monitoring method and monitoring device |
| CN107318000A (en) * | 2017-06-22 | 2017-11-03 | 重庆邮电大学 | A kind of wireless video monitoring system based on cloud platform |
| CN108459941A (en) * | 2018-03-09 | 2018-08-28 | 深圳达实智能股份有限公司 | A kind of method and system of distributed data acquisition and software supervision |
| CN109697424A (en) * | 2018-12-19 | 2019-04-30 | 浙江大学 | A kind of high-speed railway impurity intrusion detection device and method based on FPGA and deep learning |
| CN110119656A (en) * | 2018-02-07 | 2019-08-13 | 中国石油化工股份有限公司 | Intelligent monitor system and the scene monitoring method violating the regulations of operation field personnel violating the regulations |
-
2020
- 2020-10-28 CN CN202011173485.6A patent/CN112291494B/en active Active
Patent Citations (10)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US6476858B1 (en) * | 1999-08-12 | 2002-11-05 | Innovation Institute | Video monitoring and security system |
| CN102860003A (en) * | 2010-03-09 | 2013-01-02 | 常州环视高科电子科技有限公司 | A surveillance system and method |
| CN104104145A (en) * | 2013-04-02 | 2014-10-15 | 南京中兴力维软件有限公司 | Transformer station monitoring realization method and transformer station monitoring system thereof |
| WO2015054816A1 (en) * | 2013-10-14 | 2015-04-23 | Microsoft Technology Licensing, Llc | Encoder-side options for base color index map mode for video and image coding |
| US20160196268A1 (en) * | 2015-01-07 | 2016-07-07 | International Business Machines Corporation | Prioritizing video surveillance media |
| CN106162109A (en) * | 2016-08-30 | 2016-11-23 | 浙江大华技术股份有限公司 | A kind of remote monitoring method and monitoring device |
| CN107318000A (en) * | 2017-06-22 | 2017-11-03 | 重庆邮电大学 | A kind of wireless video monitoring system based on cloud platform |
| CN110119656A (en) * | 2018-02-07 | 2019-08-13 | 中国石油化工股份有限公司 | Intelligent monitor system and the scene monitoring method violating the regulations of operation field personnel violating the regulations |
| CN108459941A (en) * | 2018-03-09 | 2018-08-28 | 深圳达实智能股份有限公司 | A kind of method and system of distributed data acquisition and software supervision |
| CN109697424A (en) * | 2018-12-19 | 2019-04-30 | 浙江大学 | A kind of high-speed railway impurity intrusion detection device and method based on FPGA and deep learning |
Non-Patent Citations (1)
| Title |
|---|
| 潘志庚等: "基于广域网流媒体传输的实时视频监控***", 《***仿真学报》 * |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113485992A (en) * | 2021-07-08 | 2021-10-08 | 国网冀北电力有限公司计量中心 | Data processing method and device |
Also Published As
| Publication number | Publication date |
|---|---|
| CN112291494B (en) | 2022-12-16 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN105303636B (en) | Wireless polling system and inspection management method | |
| CN108401135B (en) | Charging and battery-swapping station monitoring video data processing method and device | |
| CN204559771U (en) | Home remote monitoring system based on cloud computing | |
| CN105006109B (en) | rural meteorological disaster early warning processing system | |
| CN102938836A (en) | Real-time dynamic remote judicial evidence obtaining system | |
| CN102300079A (en) | System and method for video monitoring on agricultural insect disease | |
| CN102244767B (en) | Cloud monitoring system and method | |
| CN112291494B (en) | Unmanned aerial vehicle 4K video directional forwarding system based on 5G communication | |
| CN105072415A (en) | Transformer substation video monitoring method using distributed storage and server unified management | |
| CN108769169B (en) | Remote fault diagnosis method for power system measurement and control device | |
| CN103795987A (en) | Embedded video collecting and processing system and implementation method thereof | |
| CN209402635U (en) | A kind of monitoring of transformer substation video and intelligent analysis system | |
| CN111698526A (en) | Method and system for realizing viewing of live video by scanning two-dimensional code | |
| CN115103157A (en) | Video analysis method and device based on edge cloud cooperation, electronic equipment and medium | |
| CN111090773A (en) | Digital retina architecture and software architecture method and system | |
| CN104021144A (en) | System and method for distribution storage of law enforcement recorded information acquisition work station | |
| CN112700611A (en) | Fire-fighting big data integrated management platform | |
| CN202197366U (en) | Plant disease and insect damage video monitoring system | |
| CN103347176A (en) | Production field real-time video and audio remote monitoring system | |
| CN108833574A (en) | A kind of transmission line long-distance monitoring system suitable for Internet of Things | |
| JP2013143655A (en) | Site condition monitoring system and site image provision method | |
| CN112055178A (en) | Be applied to unmanned aerial vehicle low latency 5G communication system | |
| CN206212169U (en) | A kind of wireless emergency command terminal system of portable case type high definition | |
| CN114286059A (en) | Wireless video monitoring system for kindergarten | |
| CN100463393C (en) | Device and method for data safety share between isomerous system |
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 | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |