CN115631660A - Unmanned aerial vehicle security protection supervisory systems based on cloud calculates - Google Patents
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- G—PHYSICS
- G08—SIGNALLING
- G08G—TRAFFIC CONTROL SYSTEMS
- G08G5/00—Traffic control systems for aircraft, e.g. air-traffic control [ATC]
- G08G5/0047—Navigation or guidance aids for a single aircraft
- G08G5/0069—Navigation or guidance aids for a single aircraft specially adapted for an unmanned aircraft
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- G—PHYSICS
- G08—SIGNALLING
- G08G—TRAFFIC CONTROL SYSTEMS
- G08G5/00—Traffic control systems for aircraft, e.g. air-traffic control [ATC]
- G08G5/0073—Surveillance aids
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04B—TRANSMISSION
- H04B7/00—Radio transmission systems, i.e. using radiation field
- H04B7/14—Relay systems
- H04B7/15—Active relay systems
- H04B7/185—Space-based or airborne stations; Stations for satellite systems
- H04B7/18502—Airborne stations
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- H04N7/00—Television systems
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- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W4/00—Services specially adapted for wireless communication networks; Facilities therefor
- H04W4/02—Services making use of location information
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- H04W4/00—Services specially adapted for wireless communication networks; Facilities therefor
- H04W4/30—Services specially adapted for particular environments, situations or purposes
- H04W4/40—Services specially adapted for particular environments, situations or purposes for vehicles, e.g. vehicle-to-pedestrians [V2P]
- H04W4/42—Services specially adapted for particular environments, situations or purposes for vehicles, e.g. vehicle-to-pedestrians [V2P] for mass transport vehicles, e.g. buses, trains or aircraft
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- H—ELECTRICITY
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- H04W—WIRELESS COMMUNICATION NETWORKS
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- H04W4/90—Services for handling of emergency or hazardous situations, e.g. earthquake and tsunami warning systems [ETWS]
Abstract
The invention discloses an unmanned aerial vehicle security supervision system based on cloud computing, which comprises a data acquisition module, a registration login module, a cloud server, a security supervision module, an unmanned aerial vehicle track planning module and an unmanned aerial vehicle early warning module, wherein the data acquisition module is used for acquiring a data; the data acquisition module is connected gradually with registration login module, cloud ware, security protection supervision module and unmanned aerial vehicle orbit planning module in proper order, and unmanned aerial vehicle orbit planning module is connected with unmanned aerial vehicle early warning module. According to the invention, the course track of the unmanned aerial vehicle is recorded, the special track of the unmanned aerial vehicle is controlled by adopting a linear and circular interpolation method, the flight time and the flight track of the unmanned aerial vehicle are recorded, and the course of the unmanned aerial vehicle is timely corrected according to the deviation between the flight track and the actual flight process, so that the unmanned aerial vehicle can fly according to the preset track, the security supervision efficiency is improved, the inspection time of the unmanned aerial vehicle is prolonged, and the inspection area is enlarged.
Description
Technical Field
The invention relates to the technical field of unmanned aerial vehicle security supervision, in particular to an unmanned aerial vehicle security supervision system based on cloud computing.
Background
The security monitoring system is an independent and complete system which is formed by transmitting video signals in a closed loop by using optical fibers, coaxial cables or microwaves, and shooting, image display and recording. The system can reflect the monitored object in real time, vividly and truly, not only greatly prolongs the observation distance of human eyes, but also enlarges the functions of the human eyes, can replace manpower to carry out long-time monitoring in severe environment, enables people to see all the actual conditions of the monitored site, and records the actual conditions through a video recorder. Meanwhile, the alarm system device alarms illegal intrusion, generated alarm signals are input into the alarm host, and the alarm host triggers the monitoring system to record and record videos.
The unmanned aerial vehicle and security protection ' the relation ' are ' important one reason is that for the security protection industry, the unmanned aerial vehicle has unique advantages, and can effectively solve the problems encountered when security protection events are processed at present, for example, in the face of disasters, rescue workers can not be instructed to comprehensively and macroscopically know the disaster, and the rescue workers can not enter the disaster area and the like; the urban management can not quickly find out violation of regulations, illegal construction, effective law enforcement and the like, and after the unmanned aerial vehicle is fused with the security industry, the problems are solved.
In addition, the mode of paying according to the use amount of cloud computing can provide available, convenient and on-demand network access, and better management service is provided for the unmanned aerial vehicle by entering a configurable network, a server, storage, application software, service computing and other resource sharing pools and combining with security supervision of the unmanned aerial vehicle;
for example, chinese patent CN111416961B discloses an unmanned aerial vehicle security monitoring system based on cloud computing, which includes a data acquisition module, a server, a registration login module, an information storage module, a deployment module, an unmanned aerial vehicle renting module, an unmanned aerial vehicle sharing module, a security monitoring module, an electric quantity supply module, and a user analysis module; according to the invention, the unmanned aerial vehicle is selected to perform security protection through the unmanned aerial vehicle for real-time panoramic monitoring, so that the security protection monitoring efficiency is improved; the unmanned aerial vehicle through to the security protection control selects the user that corresponds to carry out the electric quantity and supplies with, and the user rents through unmanned aerial vehicle renting module and carries out unmanned aerial vehicle, improves unmanned aerial vehicle's utilization ratio.
The system realizes sharing of the unmanned aerial vehicles through the unmanned aerial vehicle renting module, solves the problem that the electric quantity of the unmanned aerial vehicle is inconvenient to supply in the security protection process through the electric quantity supply module, but the unmanned aerial vehicle is generally manually controlled and flies under the action of manual control in the patrol process, and in an unmanned state, the optimal selection of a track is lacked, and meanwhile, when an obstacle appears, the obstacle cannot be effectively avoided, so that the unmanned aerial vehicle is damaged;
simultaneously, the unmanned aerial vehicle renting module realizes the renting of the unmanned aerial vehicle, different modes are generally adopted for the security monitoring operation of the unmanned aerial vehicle, and the recommendation of the unmanned aerial vehicle renting process can not be effectively carried out on a user, so that the experience of the unmanned aerial vehicle renting personnel is reduced, and the use amount of the personnel is reduced.
An effective solution to the problems in the related art has not been proposed yet.
Disclosure of Invention
Aiming at the problems in the related art, the invention provides an unmanned aerial vehicle security monitoring system based on cloud computing, and aims to overcome the technical problems in the prior related art.
Therefore, the invention adopts the following specific technical scheme:
an unmanned aerial vehicle security supervision system based on cloud computing comprises a data acquisition module, a registration login module, a cloud server, a security supervision module, an unmanned aerial vehicle track planning module and an unmanned aerial vehicle early warning module;
the data acquisition module is connected with the cloud server through the registration login module, the cloud server is connected with the unmanned aerial vehicle track planning module through the security monitoring module, and the unmanned aerial vehicle track planning module is connected with the unmanned aerial vehicle early warning module;
the data acquisition module is used for acquiring data information of the unmanned aerial vehicle in the security area and storing the data information of the unmanned aerial vehicle into the cloud server;
the registration login module is used for inputting user data information into the mobile terminal, registering the user data information and sending the successfully registered data information to the cloud server;
the cloud server is used for storing the data information and performing coordination recommendation on the data information;
the security monitoring module is used for security monitoring through the unmanned aerial vehicle;
the unmanned aerial vehicle management and trajectory planning module is used for providing a decision-making means for security management of the unmanned aerial vehicle and planning the optimal flight trajectory of the unmanned aerial vehicle;
the unmanned aerial vehicle early warning module is used for monitoring the distance between the flight track of the unmanned aerial vehicle and a surrounding building in real time and transmitting abnormal warning information to a controller of the unmanned aerial vehicle.
Further, the cloud server comprises an information storage module and a coordination recommendation module;
the information storage module is connected with the coordination recommendation module;
the information storage module is used for storing the data information of the unmanned aerial vehicle, the data information of the user and the operation mode;
the coordination recommendation module is used for calculating the similarity according to the options of the user, generating a recommendation data set according to the similarity calculation, constructing a tag of the recommendation data set and recommending a proper unmanned aerial vehicle to the user through the tag;
the data information of the unmanned aerial vehicle comprises real-time position, real-time electric quantity and quantity information of the unmanned aerial vehicle, and the data information of the user comprises identity information, a living address, a mobile phone number of the user and a security supervision operation mode and operation experience of the unmanned aerial vehicle; .
Further, the steps of calculating the similarity according to the options of the user, generating a recommended data set according to the similarity calculation, constructing a tag of the recommended data set, and recommending a suitable unmanned aerial vehicle to the user through the tag include:
inquiring the unmanned aerial vehicle in the corresponding supervision area according to the requirements of the user, and recording the inquiry record by the cloud server;
calculating recommendation values of similarity of the query records of the user, and generating recommendation contents of a plurality of unmanned aerial vehicles according to the calculation result;
forming a recommendation data set by the plurality of recommended contents, constructing the recommendation data set as a tag set, recommending the tag set to a user, and calculating the interest degree of the user in the tag set by using a recommendation algorithm;
and (4) counting the similarity among the labels through data, and expanding the label set to other users by using the following cosine similarity formula.
Further, the recommended value calculation formula of the similarity is as follows:
in the formula (I), the compound is shown in the specification,
a recommended value that represents the degree of similarity,
inputting an average evaluation value for the selection for the user;
for user input
And user input
The degree of similarity of (a) to (b),
number of unmanned aerial vehicles
For the average evaluation of the recommended data set,
for user input
An average estimate of recommended content.
Further, the unmanned aerial vehicle trajectory planning module comprises a road information acquisition module, a security monitoring management module, a GIS platform software module and a trajectory planning module;
the road information acquisition module is sequentially connected with the security monitoring management module, the GIS platform software module and the track planning module;
the road information acquisition module is used for acquiring distribution information of urban roads, residential areas and office buildings around the security monitoring area;
the security monitoring management module is used for calling the distribution information of each urban road, residential area and office building in the security monitoring area from the GIS platform software module;
the GIS platform software module is used for providing timely, accurate and comprehensive security monitoring information for administrative departments of security monitoring and providing decision basis and auxiliary means for areas to be monitored;
and the track planning module is used for calling data information of all urban roads, residential areas and office buildings in the security monitoring management and planning the flight track of the unmanned aerial vehicle.
Furthermore, the steps of calling data information of each urban road, residential area and office building in the security monitoring management and planning the flight path of the unmanned aerial vehicle comprise:
the expected flight path of the unmanned aerial vehicle is defined by adopting a circle and a line;
calculating the coordinate of each step of planning point by adopting numerical control interpolation;
the real-time position of the unmanned aerial vehicle is positioned by a GPS measuring sensor;
calculating an expected value of the course deviation angle of the unmanned aerial vehicle according to the error between the ideal expected point and the real-time flight point;
and measuring and calculating the proportion of the actual course deviation angle and the error information by using a GPS measuring sensor, and planning the optimal air route.
Further, the expected value is calculated as follows:
in the formula (I), the compound is shown in the specification,
for the error between the ideal desired point and the real-time flight point,
in order to plan the distance per step in the feed direction,
the deviation angle of the error between the ideal desired point and the real-time flight point.
Further, the step of measuring and calculating the ratio of the actual course deviation angle to the error information through the GPS measuring sensor and planning the optimal route comprises the following steps:
position information of longitude, latitude and altitude of the coordinates of the planning point is stored in a cloud server in advance;
measuring the current position of the unmanned aerial vehicle through instrument measurement, and comparing the error between the current position and the coordinate of the planning point;
correcting deviation through a GPS measuring sensor, planning a flight track, and sending a deployment instruction to the unmanned aerial vehicle;
and the control personnel of the unmanned aerial vehicle receives the allocation instruction and carries out track flight according to the allocation instruction.
Further, the real-time monitoring of the distance between the flight track of the unmanned aerial vehicle and the surrounding buildings and the transmission of abnormal warning information to the control personnel of the unmanned aerial vehicle comprise the following steps:
acquiring building marks of a peripheral area by using a camera based on a high-speed camera technology, and uploading the acquired building marks of the peripheral area to an unmanned aerial vehicle controller;
preprocessing the building mark of the peripheral area, calibrating the image and extracting and identifying the characteristic information by utilizing a pattern recognition technology in the unmanned aerial vehicle controller;
informing the processed picture information to a controller of the unmanned aerial vehicle in advance by adopting a voice prompt mode, and stopping voice broadcasting after feedback of the controller of the unmanned aerial vehicle is obtained;
monitoring the distance between the unmanned aerial vehicle and a building in real time by adopting an unmanned aerial vehicle video probe, and transmitting abnormal warning information to a control person of the unmanned aerial vehicle;
according to unusual alarm information, change unmanned aerial vehicle's flight orbit in time.
Further, the steps of preprocessing the building mark of the peripheral area, calibrating the image and extracting and identifying the characteristic information by using the pattern recognition technology in the unmanned aerial vehicle controller further comprise the following steps:
analyzing the marks of the building danger marks at the unmanned aerial vehicle controller, and classifying image information according to the analysis result;
carrying out model matching on the result of the image analysis, the obtained classification information and the building danger identification in the information base;
and feeding back the matching result to the unmanned aerial vehicle controller, and outputting the matching category of the building danger identification.
The invention has the beneficial effects that:
1. according to the invention, the collaborative filtering algorithm is adopted and improved, so that the accuracy of recommending the data information of the unmanned aerial vehicle can be improved, after the user selects an input item, irrelevant, basically relevant and very relevant data information of the unmanned aerial vehicle recommended by the system can be selected, and therefore, the understanding degree of the user on the data information of the unmanned aerial vehicle can be effectively improved, the user can search the needed unmanned aerial vehicle in a targeted manner, the experience of the user is enhanced, and the stability of security monitoring is ensured.
2. According to the invention, the course track of the unmanned aerial vehicle is recorded, the special track of the unmanned aerial vehicle is controlled by adopting a linear and circular interpolation method, the flight time and the flight track of the unmanned aerial vehicle are recorded, and the course of the unmanned aerial vehicle is timely corrected according to the deviation between the flight track and the actual flight process, so that the unmanned aerial vehicle can fly according to the preset track, the security supervision efficiency is improved, the inspection time of the unmanned aerial vehicle is prolonged, and the inspection area is enlarged.
3. The unmanned aerial vehicle early warning module is additionally arranged, various voice broadcasting modes are adopted, how to handle dangerous events encountered by control personnel of the unmanned aerial vehicle in the course is prompted constantly, meanwhile, an intelligent design is adopted, safety and skill knowledge of the control personnel of the unmanned aerial vehicle are enhanced through interaction of the unmanned aerial vehicle and the control personnel of the unmanned aerial vehicle, and meanwhile, the occurrence of dangerous accidents is reduced.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings needed in the embodiments will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and it is obvious for those skilled in the art to obtain other drawings without creative efforts.
Fig. 1 is a schematic block diagram of a security supervision system for an unmanned aerial vehicle based on cloud computing according to an embodiment of the present invention;
fig. 2 is a schematic block diagram of a ground system and an airborne system of an unmanned aerial vehicle in an unmanned aerial vehicle security monitoring system based on cloud computing according to an embodiment of the present invention;
fig. 3 is a course deviation angle of a straight path in a security supervision system of an unmanned aerial vehicle based on cloud computing according to an embodiment of the present invention;
fig. 4 is a heading deviation angle of a circular arc path in an unmanned aerial vehicle security supervision system based on cloud computing according to an embodiment of the present invention.
In the figure:
1. a data acquisition module; 2. a login module is registered; 3. a cloud server; 4. a security supervision module; 5. an unmanned aerial vehicle trajectory planning module; 6. unmanned aerial vehicle early warning module.
Detailed Description
For further explanation of the various embodiments, the drawings which form a part of the disclosure and which are incorporated in and constitute a part of this specification, illustrate embodiments and, together with the description, serve to explain the principles of operation of the embodiments, and to enable others of ordinary skill in the art to understand the various embodiments and advantages of the invention, and, by reference to these figures, reference is made to the accompanying drawings, which are not to scale and wherein like reference numerals generally refer to like elements.
According to the embodiment of the invention, an unmanned aerial vehicle security monitoring system based on cloud computing is provided.
The present invention will be further described with reference to the accompanying drawings and specific embodiments, as shown in fig. 1, according to an embodiment of the present invention, an unmanned aerial vehicle security monitoring system based on cloud computing includes a data acquisition module 1, a registration login module 2, a cloud server 3, a security monitoring module 4, an unmanned aerial vehicle trajectory planning module 5, and an unmanned aerial vehicle early warning module 6;
the data acquisition module is connected with the cloud server through the registration login module, the cloud server is connected with the unmanned aerial vehicle track planning module through the security monitoring module, and the unmanned aerial vehicle track planning module is connected with the unmanned aerial vehicle early warning module;
the data acquisition module 1 is used for acquiring data information of the unmanned aerial vehicle in the security area and storing the data information of the unmanned aerial vehicle into the cloud server.
And the registration login module 2 is used for inputting user data information at the mobile terminal, registering and sending the successfully registered data information to the cloud server.
The cloud server 3 is used for storing data information and performing coordination recommendation on the data information;
in one embodiment, the cloud server 3 comprises an information storage module and a coordination recommendation module;
the information storage module is connected with the coordination recommendation module;
the information storage module is used for storing data information of the unmanned aerial vehicle, data information of a user and an operation mode;
the coordination recommendation module is used for carrying out similarity calculation according to the options of the user, generating a recommendation data set according to the similarity calculation, constructing a tag of the recommendation data set and recommending a proper unmanned aerial vehicle to the user through the tag;
the data information of the unmanned aerial vehicle comprises real-time position, real-time electric quantity and quantity information of the unmanned aerial vehicle, and the data information of the user comprises identity information, a living address, a mobile phone number of the user and a security supervision operation mode and operation experience of the unmanned aerial vehicle;
in one embodiment, the performing similarity calculation according to the user option, generating a recommended data set according to the similarity calculation, constructing a tag of the recommended data set, and recommending a suitable unmanned aerial vehicle to the user through the tag includes the following steps:
inquiring the unmanned aerial vehicle in the corresponding supervision area according to the requirements of the user, and recording inquiry records by the cloud server;
calculating recommendation values of similarity of the query records of the user, and generating recommendation contents of a plurality of unmanned aerial vehicles according to the calculation result;
in one embodiment, the recommended value of similarity is calculated as follows:
in the formula (I), the compound is shown in the specification,
a recommended value that represents the degree of similarity,
inputting an average evaluation value for the selection for the user;
for user input
And user input
The degree of similarity of (a) to (b),
number of unmanned aerial vehicles
For the recommendationThe average estimate of the data set is,
for user input
An average rating for the recommended content;
forming a recommendation data set by the plurality of recommended contents, constructing the recommendation data set as a tag set, recommending the tag set to a user, and calculating the interest degree of the user in the tag set by using a recommendation algorithm;
the calculation formula of the recommendation algorithm is as follows:
in which the user enters the tag behavior
Representing a user
Number of unmanned aerial vehicles
Input label
，
Representing a user
Input label
The number of times of the operation of the motor,
number of unmanned aerial vehicles
Marked by labels
The number of times;
calculating the similarity between the labels through data, and expanding the label set to other users by using the following cosine similarity formula;
the cosine similarity formula is calculated as follows:
in the formula (I), the compound is shown in the specification,
and
are all indicative of a label to be attached to,
is provided with a label
The set of the number of drones of (c),
number of the first unmanned plane
Input label
The number of users.
The security monitoring module 4 is used for security monitoring through an unmanned aerial vehicle;
the unmanned aerial vehicle management and trajectory planning module 5 is used for providing a decision-making means for security management of the unmanned aerial vehicle and planning the optimal flight trajectory of the unmanned aerial vehicle;
in one embodiment, the unmanned aerial vehicle trajectory planning module 5 includes a road information acquisition module, a security monitoring management module, a GIS platform software module and a trajectory planning module;
the road information acquisition module is sequentially connected with the security monitoring management module, the GIS platform software module and the track planning module;
the road information acquisition module is used for acquiring distribution information of urban roads, residential areas and office buildings around the security monitoring area;
the security monitoring management module is used for calling the distribution information of each urban road, residential area and office building in the security monitoring area from the GIS platform software module;
the GIS platform software module is used for providing timely, accurate and comprehensive security monitoring information for a security monitoring department, and providing decision basis and auxiliary means for an area to be monitored;
the track planning module is used for calling data information of all urban roads, residential areas and office buildings in security monitoring management and planning the flight track of the unmanned aerial vehicle;
in one embodiment, as shown in fig. 3 to fig. 4, the retrieving data information of urban roads, residential areas and office buildings in security monitoring management, and planning the flight trajectory of the drone includes the following steps:
the expected flight path of the unmanned aerial vehicle is defined by adopting a circle and a line;
calculating the coordinate of each step of planning point by adopting numerical control interpolation;
the real-time position of the unmanned aerial vehicle is positioned by a GPS measuring sensor;
calculating an expected value of the course deviation angle of the unmanned aerial vehicle according to the error between the ideal expected point and the real-time flight point;
and measuring and calculating the proportion of the actual course deviation angle and the error information by using a GPS measuring sensor, and planning the optimal air route.
In one embodiment, the expected value is calculated as follows:
in the formula (I), the compound is shown in the specification,
for the error between the ideal desired point and the real-time flight point,
in order to plan the distance per step in the feed direction,
the deviation angle of the error between the ideal expected point and the real-time flight point;
in one embodiment, the calculating the ratio of the actual heading deviation angle to the error information through the measurement of the GPS measuring sensor and the planning of the optimal route comprises the following steps:
position information of longitude, latitude and altitude of the coordinates of the planning point is stored in a cloud server in advance;
measuring the current position of the unmanned aerial vehicle through instrument measurement, and comparing the error between the current position and the coordinate of the planning point;
correcting deviation through a GPS measuring sensor, planning a flight track, and sending a deployment instruction to the unmanned aerial vehicle;
and the control personnel of the unmanned aerial vehicle receives the allocation instruction and carries out track flight according to the allocation instruction.
The unmanned aerial vehicle early warning module 6 is used for monitoring the distance between the flight track of the unmanned aerial vehicle and surrounding buildings in real time and transmitting abnormal warning information to the control personnel of the unmanned aerial vehicle.
In one embodiment, the real-time monitoring of the distance between the flight path of the unmanned aerial vehicle and the surrounding building, and the transmission of the abnormal warning information to the control personnel of the unmanned aerial vehicle comprises the following steps:
acquiring building marks of a peripheral area by using a camera based on a high-speed camera technology, and uploading the acquired building marks of the peripheral area to an unmanned aerial vehicle controller;
preprocessing the building mark of the peripheral area, calibrating the image and extracting and identifying the characteristic information by utilizing a pattern recognition technology in the unmanned aerial vehicle controller;
informing the processed picture information to a controller of the unmanned aerial vehicle in advance by adopting a voice prompt mode, and stopping voice broadcast after feedback of the controller of the unmanned aerial vehicle is obtained;
monitoring the distance between the unmanned aerial vehicle and a building in real time by adopting an unmanned aerial vehicle video probe, and transmitting abnormal warning information to a controller of the unmanned aerial vehicle;
according to unusual alarm information, change unmanned aerial vehicle's flight orbit in time.
In specific application, in an actual unmanned plane glider structure, the mass of the unmanned plane glider structure is less than 4kg, the effective load is 1000g, an on-board computer communication and control block diagram is shown in fig. 2, and the transmitting and receiving device is used for a ground monitoring system to realize control and communication of the unmanned plane.
In one embodiment, the preprocessing, image calibration and feature information extraction and identification of the building mark of the surrounding area by using the pattern recognition technology in the drone controller further comprises the following steps:
analyzing the marks of the building danger marks at the unmanned aerial vehicle controller, and classifying image information according to the analysis result;
carrying out model matching on the result of the image analysis, the obtained classification information and the building danger identification in the information base;
when the intelligent alarm is applied specifically, different alarms are prompted according to different environments, and if the natural climate is normal, an early warning signal is not sent out;
if the bad natural climate appears, prompting the control personnel of the unmanned aerial vehicle to recover the unmanned aerial vehicle in a safe place;
and feeding back the matching result to the unmanned aerial vehicle controller, and outputting the matching category of the building danger identification.
In conclusion, by means of the technical scheme of the invention, the accuracy of recommending unmanned aerial vehicle data information can be improved by applying and improving a collaborative filtering algorithm, after a user selects an input item, irrelevant, basically relevant and very relevant unmanned aerial vehicle data information recommended by a system can be selected according to the unmanned aerial vehicle data information recommended by the user, so that the understanding degree of the user on the unmanned aerial vehicle data information can be effectively improved, the user can search for a required unmanned aerial vehicle in a targeted manner, the experience of the user is enhanced, and the stability of security monitoring is ensured.
The above description is only for the purpose of illustrating the preferred embodiments of the present invention and should not be taken as limiting the scope of the present invention, which is intended to cover any modifications, equivalents, improvements, etc. within the spirit and scope of the present invention.
Claims (8)
1. An unmanned aerial vehicle security supervision system based on cloud computing is characterized by comprising a data acquisition module, a registration login module, a cloud server, a security supervision module, an unmanned aerial vehicle track planning module and an unmanned aerial vehicle early warning module;
the data acquisition module is connected with the cloud server through the registration login module, the cloud server is connected with the unmanned aerial vehicle track planning module through the security monitoring module, and the unmanned aerial vehicle track planning module is connected with the unmanned aerial vehicle early warning module;
the data acquisition module is used for acquiring data information of the unmanned aerial vehicle in the security area and storing the data information of the unmanned aerial vehicle into the cloud server;
the registration login module is used for inputting user data information at the mobile terminal, registering and sending the successfully registered data information to the cloud server;
the cloud server is used for storing the data information and performing coordination recommendation on the data information;
the security monitoring module is used for security monitoring through the unmanned aerial vehicle;
the unmanned aerial vehicle management and track planning module is used for providing a decision-making means for the security management of the unmanned aerial vehicle and planning the optimal flight track of the unmanned aerial vehicle;
the unmanned aerial vehicle early warning module is used for monitoring the distance between the flight track of the unmanned aerial vehicle and a surrounding building in real time and transmitting abnormal warning information to a control person of the unmanned aerial vehicle;
the unmanned aerial vehicle track planning module comprises a road information acquisition module, a security monitoring management module, a GIS platform software module and a track planning module;
the road information acquisition module is sequentially connected with the security monitoring management module, the GIS platform software module and the track planning module;
the road information acquisition module is used for acquiring distribution information of urban roads, residential areas and office buildings around the security monitoring area;
the security monitoring management module is used for calling the distribution information of each urban road, residential area and office building in the security monitoring area from the GIS platform software module;
the GIS platform software module is used for providing timely, accurate and comprehensive security monitoring information for a security monitoring department, and providing decision basis and auxiliary means for an area to be monitored;
the track planning module is used for calling data information of all urban roads, residential areas and office buildings in security monitoring management and planning the flight track of the unmanned aerial vehicle;
the method for calling the data information of each urban road, residential area and office building in the security monitoring management and planning the flight path of the unmanned aerial vehicle comprises the following steps:
the expected flight path of the unmanned aerial vehicle is defined in a circular and linear mode;
calculating the coordinate of each step of planning point by adopting numerical control interpolation;
the real-time position of the unmanned aerial vehicle is positioned by a GPS measuring sensor;
calculating an expected value of the course deviation angle of the unmanned aerial vehicle according to the error between the ideal expected point and the real-time flight point;
and measuring and calculating the proportion of the actual course deviation angle to the error information by using a GPS measuring sensor, and planning the optimal air route.
2. The unmanned aerial vehicle security supervision system based on cloud computing of claim 1, wherein the cloud server comprises an information storage module and a coordination recommendation module;
the information storage module is connected with the coordination recommendation module;
the information storage module is used for storing data information of the unmanned aerial vehicle, data information of a user and an operation mode;
the coordination recommendation module is used for carrying out similarity calculation according to the options of the user, generating a recommendation data set according to the similarity calculation, constructing a tag of the recommendation data set and recommending a proper unmanned aerial vehicle to the user through the tag;
the data information of the unmanned aerial vehicle comprises the real-time position, the real-time electric quantity and the quantity information of the unmanned aerial vehicle, and the data information of the user comprises the identity information, the living address, the mobile phone number of the user and the security supervision operation mode and operation experience of the unmanned aerial vehicle.
3. The unmanned aerial vehicle security supervision system based on cloud computing as claimed in claim 2, wherein the performing similarity calculation according to the user's options, generating a recommendation data set according to the similarity calculation, constructing a tag of the recommendation data set and recommending a suitable unmanned aerial vehicle to the user through the tag comprises the following steps:
inquiring the unmanned aerial vehicle in the corresponding supervision area according to the requirements of the user, and recording inquiry records by the cloud server;
calculating recommendation values of similarity of the query records of the user, and generating recommendation contents of a plurality of unmanned aerial vehicles according to the calculation result;
forming a recommendation data set by the plurality of recommended contents, constructing the recommendation data set as a tag set, recommending the tag set to a user, and calculating the interest degree of the user in the tag set by using a recommendation algorithm;
and (4) counting the similarity among the labels through data, and expanding the label set to other users by utilizing the following cosine similarity formula.
4. The unmanned aerial vehicle security supervision system based on cloud computing of claim 3, wherein the recommended value calculation formula of similarity is as follows:
in the formula (I), the compound is shown in the specification,
a recommended value that represents the degree of similarity,
inputting an average evaluation value for the selection for the user;
for user input
And user input
The degree of similarity of (a) to (b),
number of unmanned aerial vehicles
For the average evaluation of the recommended data set,
for user input
An average estimate of recommended content.
5. The unmanned aerial vehicle security supervision system based on cloud computing of claim 1, wherein the expected value is calculated as follows:
in the formula (I), the compound is shown in the specification,
for the error between the ideal desired point and the real-time flight point,
in order to plan the distance per step in the feed direction,
the deviation angle of the error between the ideal desired point and the real-time flight point.
6. The unmanned aerial vehicle security supervision system based on cloud computing as claimed in claim 1, wherein the measuring and calculating of the ratio of the actual course deviation angle to the error information through the GPS measuring sensor and the planning of the optimal route comprises the following steps:
position information of longitude, latitude and altitude of the coordinates of the planning point is stored in a cloud server in advance;
measuring the current position of the unmanned aerial vehicle through instrument measurement, and comparing the error between the current position and the coordinate of the planning point;
correcting deviation through a GPS measuring sensor, planning a flight track, and sending a deployment instruction to the unmanned aerial vehicle;
and the control personnel of the unmanned aerial vehicle receives the allocation instruction and carries out trajectory flight according to the allocation instruction.
7. The unmanned aerial vehicle security supervision system based on cloud computing according to claim 1, wherein the distance between the flight trajectory of the unmanned aerial vehicle and the surrounding buildings is monitored in real time, and the step of transmitting abnormal warning information to the control personnel of the unmanned aerial vehicle comprises the following steps:
acquiring building marks of a peripheral area by using a camera based on a high-speed camera technology, and uploading the acquired building marks of the peripheral area to an unmanned aerial vehicle controller;
preprocessing the building mark of the peripheral area, calibrating the image and extracting and identifying the characteristic information by utilizing a pattern recognition technology in the unmanned aerial vehicle controller;
informing the processed picture information to a controller of the unmanned aerial vehicle in advance by adopting a voice prompt mode, and stopping voice broadcast after feedback of the controller of the unmanned aerial vehicle is obtained;
monitoring the distance between the unmanned aerial vehicle and a building in real time by adopting an unmanned aerial vehicle video probe, and transmitting abnormal warning information to a controller of the unmanned aerial vehicle;
according to unusual alert feelings information, change unmanned aerial vehicle's flight orbit in time.
8. The cloud computing-based unmanned aerial vehicle security supervision system according to claim 7, wherein the steps of preprocessing the building markers of the surrounding area, calibrating the image, extracting and identifying the characteristic information by using the pattern recognition technology in the unmanned aerial vehicle controller further comprise:
analyzing the marks of the building danger marks at the unmanned aerial vehicle controller, and classifying image information of the analyzed results;
carrying out model matching on the result of the image analysis, the obtained classification information and the building danger identification in the information base;
and feeding back the matching result to the unmanned aerial vehicle controller, and outputting the matching category of the building danger identifier.
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