CN113869779A

CN113869779A - People flow monitoring method and system based on city management and cloud platform

Info

Publication number: CN113869779A
Application number: CN202111194529.8A
Authority: CN
Inventors: 杨翰翔; 肜卿
Original assignee: Shenzhen Lianhe Intelligent Technology Co ltd
Current assignee: Shenzhen Lianhe Intelligent Technology Co ltd
Priority date: 2021-10-13
Filing date: 2021-10-13
Publication date: 2021-12-31
Anticipated expiration: 2041-10-13
Also published as: CN113869779B

Abstract

The embodiment of the invention provides a people stream monitoring method, a system and a cloud platform based on city management, firstly, people stream monitoring data corresponding to each monitoring area obtained by people stream monitoring of the corresponding monitoring area by each unmanned aerial vehicle is obtained from each people stream monitoring terminal, then, performing data analysis according to the people stream monitoring data corresponding to each monitoring area, confirming whether any monitoring area meets the preset people stream dispersion triggering condition according to the data analysis result, and finally obtaining the corresponding people stream dispersion scheme when any monitoring area meets the preset people stream dispersion triggering condition, and determining the pedestrian flow dispersion indication information aiming at each unmanned aerial vehicle according to the pedestrian flow dispersion scheme, and controlling each unmanned aerial vehicle to carry out pedestrian flow dispersion corresponding to the monitoring area according to the corresponding pedestrian flow dispersion indication information. Therefore, an effective mechanism is provided for people stream monitoring and leading, and the intelligent degree and level of smart city management are further improved.

Description

People flow monitoring method and system based on city management and cloud platform

Technical Field

The invention relates to the technical field of smart city management and unmanned aerial vehicles, in particular to a people flow monitoring method and system based on city management and a cloud platform.

Background

Unmanned Aerial Vehicles (UAVs) are also known as drones. With the rapid development of unmanned flight technology, consumer unmanned aerial vehicles are widely applied in various industries and used for replacing people to execute corresponding work.

Further, with the continuous acceleration of the progress of smart cities, the application of the unmanned aerial vehicle in the field of smart cities (such as smart city management) is also widely popularized. For example, unmanned aerial vehicle is used for various fields such as wisdom city environmental monitoring and commander, automatic food delivery, wisdom city commodity circulation, very big make things convenient for people daily work and life, makes the city become more and more "intellectuality" simultaneously.

In the implementation process of smart city management, people flow monitoring and people flow dispersion aiming at a target monitoring scene are required aiming at a special city area and a special time node. However, the conventional method of manually monitoring and guiding people flow does not meet the intelligent requirement of the smart city. Based on this, unmanned aerial vehicle also obtains the sufficient development and application in wisdom city stream of people control field. However, in some specific situations, such as large-scale public meetings and large-scale city event projects, the situation that the flow of people is too large and the partitioned people flow monitoring and evacuation are required often occurs, and at present, an effective people flow monitoring and evacuation mechanism is not provided to deal with some sudden people flow situations.

Disclosure of Invention

In order to solve the above problems, in one aspect, an embodiment of the present invention provides a people flow monitoring method based on city management, which is applied to a cloud platform of a people flow monitoring system, where the people flow monitoring system further includes an unmanned aerial vehicle in communication connection with the cloud platform and configured to respectively monitor people flows in different monitoring areas of a target monitoring scene, and multiple people flow monitoring terminals configured to receive people flow monitoring data fed back by each unmanned aerial vehicle, and the multiple people flow monitoring terminals are respectively disposed in different monitoring areas. The method comprises the following steps:

acquiring people flow monitoring data corresponding to each monitoring area, which is obtained by carrying out people flow monitoring on the corresponding monitoring area through each unmanned aerial vehicle, from each people flow monitoring terminal;

performing data analysis according to the people flow monitoring data corresponding to each monitoring area, and determining whether any monitoring area meets the preset people flow dispersion triggering condition according to the data analysis result;

when any monitoring area meeting preset people stream dispersion triggering conditions exists, acquiring a corresponding people stream dispersion scheme, determining people stream dispersion indicating information for each unmanned aerial vehicle according to the people stream dispersion scheme, and sending the people stream dispersion indicating information to each unmanned aerial vehicle so as to control each unmanned aerial vehicle to conduct people stream dispersion corresponding to the monitoring area according to the corresponding people stream dispersion indicating information.

Further, the people flow monitoring data is obtained by analyzing the people flow image information shot by each unmanned aerial vehicle by each people flow monitoring terminal according to a pre-established image analysis model, or the people flow image information is obtained by analyzing the people flow image information by the image analysis model pre-loaded on the unmanned aerial vehicle and fed back to the corresponding people flow monitoring terminal, the people flow grooming scheme is one of two or more than two pre-designed and stored people flow grooming actions, and the people flow grooming indication information includes the people flow grooming actions and the people flow grooming strategy contents which are required to be executed by each unmanned aerial vehicle.

Further, the method further comprises:

when a scheme updating instruction which is fed back by a first people stream monitoring terminal in a plurality of people stream monitoring terminals and adjusts an ongoing first people stream grooming scheme into a second people stream grooming scheme is received, determining a grooming strategy of an alternative second people stream grooming scheme, wherein the grooming strategy comprises one or more scheme implementation descriptions, and the scheme implementation descriptions comprise one or more preset regional grooming quantitative indexes;

determining index data configured for each region grooming quantization index described by the implementation of the scheme;

updating a people flow dispersion rule file, and adding people flow dispersion information into the people flow dispersion rule file to obtain a second people flow dispersion scheme for carrying out people flow dispersion on the monitoring area in the target monitoring scene; wherein the crowd evacuation information includes evacuation policy information of the second crowd evacuation scheme and the index data, and the evacuation policy information includes rule content of the evacuation policy;

adjusting the second people stream dispersion scheme from a standby scheme to a main scheme, and sending the second people stream dispersion scheme to each unmanned aerial vehicle so as to implement the main scheme through each unmanned aerial vehicle to carry out people stream dispersion on the corresponding monitoring area;

the leading strategy is formed by planning of a preset scheme planning staff and uploaded to the cloud platform, the cloud platform stores a plurality of leading strategies, and each leading strategy carries unique leading strategy identification information;

the determining of the grooming strategy of the alternative second people stream grooming scheme includes:

receiving grooming strategy identification information sent by the first personal flow monitoring terminal when the scheme updating indication is fed back;

searching the rule content of the dispersion strategy corresponding to the dispersion strategy identification information from a rule content library of the cloud platform according to the dispersion strategy identification information;

and writing the rule content into a preset people stream grooming rule file to obtain a grooming strategy of the alternative second people stream grooming scheme.

Further, the updating the people flow dispersion rule file, and adding the people flow dispersion information to the people flow dispersion rule file to obtain the second people flow dispersion scheme for carrying out people flow dispersion on the monitoring area in the target monitoring scene, further includes:

sending the second people stream grooming scheme to a monitoring area corresponding to a second people stream monitoring terminal except the first people stream monitoring terminal, and acquiring scheme feedback information about the second people stream grooming scheme from the monitoring area corresponding to the second people stream monitoring terminal, wherein the scheme feedback information represents whether a people stream grooming strategy corresponding to the second people stream grooming scheme is considered reasonable by the corresponding people stream monitoring terminal;

and if the second people flow control terminal confirms the people flow control strategy corresponding to the second people flow control scheme according to the acquired scheme feedback information, adjusting the second people flow control scheme from a standby scheme to a main scheme, and sending the main scheme to each unmanned aerial vehicle so as to implement the main scheme to control the people flow in the corresponding monitoring area through each unmanned aerial vehicle.

before the second people stream persuasion scheme is applied, obtaining a scheme feedback opinion, wherein the scheme feedback opinion is opinion information replied by any people stream monitoring terminal according to the scheme confirmation notification described in the scheme implementation, or feedback opinion returned by the cloud platform according to feedback instructions about the scheme feedback opinion; the acquired scheme feedback opinions have a first information identifier;

if the scheme feedback opinions are obtained from any people stream monitoring terminal, the scheme feedback opinions are sent to a second people stream monitoring terminal except the first people stream monitoring terminal, feedback information of the second people stream monitoring terminal about the scheme feedback opinions is received, whether the scheme feedback opinions agree with the second people stream persuasion scheme or not is determined according to the received feedback information, and if the second people stream persuasion scheme is agreed, the obtained scheme feedback opinions are adjusted to be a second information identifier from the first information identifier;

if the proposal feedback opinions are obtained from the cloud platform, the proposal feedback opinions are sent to each people flow monitoring terminal in the people flow monitoring system, and if the opinion feedback about the proposal feedback opinions fed back by each people flow monitoring terminal is not obtained within a set time period, the obtained proposal feedback opinions are adjusted from the first information identifier to a second information identifier;

if the scheme feedback opinions are determined not to agree with the second people stream persuasion scheme according to the received feedback information, sending a confirmation instruction for confirming the scheme feedback opinions again to the cloud platform according to a set time interval, and obtaining a confirmation result of the scheme feedback opinions from the cloud platform; when the confirmation result represents that the scheme feedback opinion agrees with the second people stream persuasion scheme, adjusting the information identifier of the scheme feedback opinion to be a second information identifier;

and when the information identifier of the proposal feedback opinion is adjusted to be a second information identifier, adjusting the second people stream dispersion proposal to be a main proposal.

Further, the method further comprises:

when a strategy implantation instruction which is sent by the first people flow monitoring terminal and used for implanting a target grooming strategy into the second people flow grooming scheme is received, sending the strategy implantation instruction, the target grooming strategy and index data configured for a region grooming quantitative index in the target grooming strategy as strategy implantation sending information to each second people flow monitoring terminal except the first people flow monitoring terminal, and obtaining feedback information of the second people flow monitoring terminal;

when confirming that each second people flow monitoring terminal agrees to implant a target dispersion strategy according to the feedback information, adding target people flow dispersion information into the people flow dispersion rule file to obtain a people flow dispersion scheme after strategy implantation; the target people stream grooming information includes target grooming policy information and index data configured for a regional grooming quantization index in the target grooming policy, where the target grooming policy information includes rule content of the target grooming policy.

Further, the determining the grooming policy of the alternative second people stream grooming scheme includes:

acquiring a people flow limiting index of different people flow nodes in each monitoring area in the people flow monitoring system, wherein the people flow limiting index comprises the maximum people flow number of the different people flow nodes;

acquiring people flow information monitored in a set time period in the people flow monitoring system;

according to the scheme implementation description included in the dredging strategy, carrying out people flow dredging simulation on the monitored people flow information in the set time period through a people flow dredging simulation model on the monitoring area in the people flow monitoring system according to the scheme implementation description, and obtaining the number of simulated people flows of different people flow nodes in the monitoring area, wherein the number of the simulated people flows is obtained through the people flow dredging simulation;

according to the simulated people flow number of different people flow nodes and the maximum people flow number of different people flow nodes, whether the dredging strategy of the alternative people flow dredging scheme represented by the scheme updating indication accords with a set rule or not is confirmed;

if the second people flow dispersion scheme meets the set rule, the second people flow dispersion scheme is adjusted to be the main scheme so as to apply the second people flow dispersion scheme; if the current situation does not accord with the set rule, sending prompt information of incomplete scheme updating to a monitoring area corresponding to the first personal flow monitoring terminal, and enabling the first personal flow monitoring terminal to feed back scheme updating instructions about the flow grooming scheme again according to the prompt information so as to update the grooming strategy;

when the quotient of the simulated people flow number of at least one people flow node and the maximum people flow number of the people flow node is larger than a set quotient threshold value, it is determined that the dredging strategy of the alternative people flow dredging scheme represented by the scheme updating indication does not accord with the set rule, and if the quotient of the simulated people flow number of all people flow nodes and the maximum people flow number of the people flow nodes is smaller than the set quotient threshold value, it is determined that the dredging strategy of the alternative people flow dredging scheme represented by the scheme updating indication accords with the set rule.

Further, the method further comprises:

after the second people stream grooming scheme is applied, when an indication representing the end of the second people stream grooming scheme grooming sent by the first people stream monitoring terminal is received:

adjusting the second stream break-off scheme to be a standby scheme, and adjusting the first stream break-off scheme to be a main scheme so as to restart the first stream break-off scheme; or

Sending a scheme restart notification to each people stream monitoring terminal in a monitoring area in the people stream monitoring system, and when receiving a scheme restart confirmation instruction fed back by each people stream monitoring terminal in the monitoring area, adjusting the second people stream grooming scheme to be a standby scheme, and adjusting the first people stream grooming scheme to be a main scheme so as to restart the first people stream grooming scheme; or

Collecting first people flow monitoring information in the monitoring area when the first people flow dispersion scheme is implemented and obtaining second people flow monitoring information in the monitoring area when the second people flow dispersion scheme is implemented from people flow monitoring terminals in the monitoring area; confirming whether a condition for restarting a first pedestrian flow grooming scheme is met or not according to the first pedestrian flow monitoring information and the second pedestrian flow monitoring information; when the condition of restarting a first stream grooming scheme is met, adjusting the second stream grooming scheme to be a standby scheme, adjusting the first stream grooming scheme to be a main scheme, and restarting the first stream grooming scheme; when a first people stream density distribution obtained by analyzing according to the first people stream monitoring information is superior to a second people stream density distribution obtained by analyzing according to the second people stream monitoring information, a condition for restarting a first people stream grooming scheme is met; the first people flow density profile comprises first people flow congestion indices for all monitored areas within the people flow monitoring system; the second people flow density distribution includes a second people flow congestion index for all monitored areas within the people flow monitoring system.

On the other hand, an embodiment of the present invention further provides a people stream monitoring system based on city management, where the people stream monitoring system includes a cloud platform, multiple unmanned aerial vehicles which are in communication connection with the cloud platform and are used to respectively monitor people streams in different monitoring areas of a target monitoring scene, and multiple people stream monitoring terminals which are used to receive people stream monitoring data fed back by each of the unmanned aerial vehicles, the multiple people stream monitoring terminals are respectively disposed in different monitoring areas, and the cloud platform includes:

the people flow data monitoring module is used for acquiring people flow monitoring data which correspond to each monitoring area and are obtained by monitoring the corresponding monitoring area through each unmanned aerial vehicle from each people flow monitoring terminal;

the monitoring data analysis module is used for carrying out data analysis according to the people flow monitoring data corresponding to each monitoring area and confirming whether any monitoring area meets the preset people flow dispersion triggering condition or not according to the result of the data analysis;

and the stream of people grooming module is used for acquiring a corresponding stream of people grooming scheme when any monitoring area meeting preset stream of people grooming trigger conditions exists, determining stream of people grooming indication information for each unmanned aerial vehicle according to the stream of people grooming scheme, and sending the stream of people grooming indication information to each unmanned aerial vehicle so as to control each unmanned aerial vehicle to carry out stream of people grooming corresponding to the monitoring area according to the corresponding stream of people grooming indication information.

In still another aspect, an embodiment of the present invention further provides a cloud platform, where the cloud platform is respectively connected to a plurality of drones for respectively performing people flow monitoring on different monitoring areas of a target monitoring scene and a plurality of people flow monitoring terminals for receiving people flow monitoring data fed back by each of the drones in a communication manner, and the cloud platform includes a processor and a machine-readable storage medium, where the machine-readable storage medium is connected to the processor, and is used to store a program, an instruction, or a code, and the processor is used to execute the program, the instruction, or the code in the machine-readable storage medium, so as to implement the method according to any one of claims 1 to 8.

In summary, the method, the system and the cloud platform for people stream monitoring based on city management according to the embodiments of the present invention first obtain people stream monitoring data corresponding to each monitoring area obtained by people stream monitoring of the corresponding monitoring area by each unmanned aerial vehicle from each people stream monitoring terminal, then, performing data analysis according to the people stream monitoring data corresponding to each monitoring area, confirming whether any monitoring area meets the preset people stream dispersion triggering condition according to the data analysis result, and finally obtaining the corresponding people stream dispersion scheme when any monitoring area meets the preset people stream dispersion triggering condition, and determining the pedestrian flow dispersion indication information for each unmanned aerial vehicle according to the pedestrian flow dispersion scheme, and sending the pedestrian flow dispersion indication information to each unmanned aerial vehicle, and controlling each unmanned aerial vehicle to dredge the pedestrian flow corresponding to the monitoring area according to the corresponding pedestrian flow dredging indication information. Therefore, an effective mechanism is provided for people stream monitoring and leading, and the intelligent degree and level of smart city management are further improved.

In addition, when the people flow monitoring terminal in a certain monitoring area finds that the current dredging scheme conflicts with the current sudden situation according to the current actual situation, the change request of the dredging scheme can be put forward in time, and the cloud platform adjusts the corresponding dredging scheme according to the change request, so that the implementation of people flow monitoring and dredging can be matched with the actual application situation.

Drawings

In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings needed to be used in the embodiments will be briefly described below, it should be understood that the following drawings only illustrate some embodiments of the present invention and therefore should not be considered as limiting the scope, and for those skilled in the art, other related drawings can be obtained according to the drawings without inventive efforts.

Fig. 1 is a schematic flow chart of a people flow monitoring method based on city management according to an embodiment of the present invention.

Fig. 2 is a schematic application environment diagram of a people flow monitoring system based on city management according to an embodiment of the present invention.

Fig. 3 is a flowchart of steps further included in the method for monitoring people flow based on city management according to the embodiment of the present invention.

Fig. 4 is a flowchart illustrating the sub-steps of step S31 in fig. 3.

Fig. 5 is a schematic structural diagram of a cloud platform for implementing the people flow monitoring method based on city management according to an embodiment of the present invention.

Fig. 6 is a functional block diagram of the people flow monitoring device in fig. 5.

Detailed Description

Referring to fig. 1, fig. 1 is a schematic flow chart of a people flow monitoring method based on city management according to an embodiment of the present invention. In the embodiment of the present invention, as shown in fig. 2, the method may be implemented by a people flow monitoring system 100 based on city management. In this embodiment, the people flow monitoring system 100 based on city management may include a cloud platform 11, a plurality of unmanned aerial vehicles 12, and a plurality of people flow monitoring terminals 13. In this embodiment, the cloud platform 11 is configured to manage and schedule the unmanned aerial vehicles 12, and each of the unmanned aerial vehicles 12 corresponds to each of the people stream monitoring terminals 13, and is configured to perform people stream monitoring and people stream dispersion when necessary on a plurality of monitoring areas in a target monitoring scene in a mutually-matched manner. In this embodiment, the cloud platform 11 may be a service platform which is set up based on a smart city and is used for performing remote communication with a plurality of unmanned aerial vehicles 12 in a set management and control area to remotely control and schedule the unmanned aerial vehicles 12. The cloud platform 11 may be, but is not limited to, a server with communication control capability and big data analysis capability, a computer monitoring area, a cloud service center, a machine room control center, a cloud platform, and other monitoring areas. The people flow monitoring terminal 13 may be a computer device disposed in a corresponding monitoring area for communicating with the unmanned aerial vehicle 12 and controlling the unmanned aerial vehicle 12.

The people flow monitoring method based on city management of the above method is described in detail below with reference to the accompanying drawings, and in this embodiment, the method includes the following steps S11-S13, which are exemplarily described below.

Step S11, obtaining, from each of the people flow monitoring terminals, people flow monitoring data corresponding to each of the monitoring areas, which is obtained by each of the unmanned aerial vehicles performing people flow monitoring on the corresponding monitoring area.

In this embodiment, the people flow monitoring data may be obtained by each people flow monitoring terminal analyzing the people flow image information captured by each unmanned aerial vehicle according to a pre-established image analysis model, or the people flow image information is analyzed by the image analysis model pre-loaded on the unmanned aerial vehicle and fed back to the corresponding people flow monitoring terminal, the people flow grooming scheme is one of two or more than two pre-designed and stored people flow grooming schemes, and the people flow grooming indication information includes the people flow grooming actions required to be executed by each unmanned aerial vehicle and the people flow grooming policy contents (e.g., corresponding sound grooming information, sound and light indication grooming information, etc.).

And step S12, performing data analysis according to the people flow monitoring data corresponding to each monitoring area, and determining whether any monitoring area meets the preset people flow dispersion triggering condition according to the result of the data analysis.

Step S13, when there is any monitoring area that meets the preset pedestrian flow dispersion trigger condition, acquiring a corresponding pedestrian flow dispersion scheme, determining pedestrian flow dispersion indication information for each unmanned aerial vehicle according to the pedestrian flow dispersion scheme, and sending the pedestrian flow dispersion indication information to each unmanned aerial vehicle, so as to control each unmanned aerial vehicle to perform pedestrian flow dispersion in the corresponding monitoring area according to the corresponding pedestrian flow dispersion indication information.

In this embodiment, the people flow monitoring data may include implementation people flow image information of each region shot by the unmanned aerial vehicle through the pan-tilt, and each people flow monitoring terminal analyzes the people flow according to a pre-established image analysis model to obtain a monitoring result of each people flow. Or, the image analysis model may be preloaded on the unmanned aerial vehicle to analyze the result of monitoring the flow of people in the corresponding area, and then the monitoring result is directly fed back to the corresponding people flow monitoring terminal. The people flow monitoring terminal can be computer equipment at a monitoring management position arranged in a corresponding monitoring area, and can display people flow information of the corresponding area in real time, wherein the people flow information comprises people flow pictures, visual data of people flow change and the like. Meanwhile, the people flow monitoring terminal can also realize the field control of each unmanned aerial vehicle, for example, the flight attitude, the flight position and the like of the unmanned aerial vehicle are controlled through a control command input by a user.

In addition, each people stream monitoring terminal can respectively send corresponding people stream monitoring data to the cloud platform for data summarization, the cloud platform analyzes the people stream real-time data of each area through the artificial intelligence model according to the analysis result of the data summarization, and when a preset people stream grooming condition is triggered according to the analysis result of the people stream data of any monitoring area (if the people stream congestion index corresponding to the people stream of a certain monitoring area reaches a set value), the people stream monitoring result of each monitoring area is input into the artificial intelligence model to obtain a people stream grooming scheme meeting the current condition.

The people flow dispersion scheme may be two or more than two people flow dispersion schemes which are designed in advance and stored in the artificial intelligence model. When the people stream dispersion scheme is obtained, the people stream dispersion indication information for each unmanned aerial vehicle is determined according to the people stream dispersion scheme, and the people stream dispersion indication information is sent to each unmanned aerial vehicle so as to control each unmanned aerial vehicle to conduct people stream dispersion corresponding to a monitoring area according to the people stream dispersion indication information. For example, the people flow dispersion indication information may include people flow dispersion actions that the drone needs to perform and specific people flow dispersion policy contents, for example, the people flow dispersion actions may include broadcasting the dispersion contents in voice or directing the people flow to a set direction for distribution by means of acousto-optic indication.

For example, the unmanned aerial vehicle may broadcast the corresponding people flow dispersion information according to an indication in the people flow dispersion indication information, and guide the corresponding personnel to distribute the flow in a set direction. Or, the unmanned aerial vehicle may broadcast the corresponding pedestrian flow evacuation information according to an instruction in the pedestrian flow evacuation instruction information, and may display the corresponding personnel distribution path in a projection medium by projection while broadcasting the pedestrian flow evacuation information. For example, for some monitoring areas, people flow grooming may not be required to be performed, the people flow grooming indication information obtained by the corresponding unmanned aerial vehicle may be empty or may keep the current status. If the pedestrian flow dispersion may be required for some monitoring areas, the pedestrian flow dispersion indication information obtained by the corresponding unmanned aerial vehicle includes corresponding operations and contents that need to be executed by the unmanned aerial vehicle.

Further, in this embodiment, in the process of performing people stream grooming through the current people stream grooming scheme, a sudden situation may occur, for example, when a people stream monitoring terminal in a certain monitoring area finds that the current grooming scheme conflicts with the current sudden situation according to the current actual situation, a change request of the grooming scheme may be provided in time, and the cloud platform adjusts the corresponding grooming scheme according to the change request. Based on this, as shown in fig. 3, the method for monitoring people flow based on city management provided by this embodiment may further include the following steps S31-S33, which are exemplarily described as follows.

Step S31, when receiving a scheme update instruction for adjusting the ongoing first people stream breakout scheme to the second people stream breakout scheme, which is fed back by the first people stream monitoring terminal of the multiple people stream monitoring terminals, determining a breakout policy of the alternative second people stream breakout scheme.

Any ongoing traffic grooming scheme may be considered as the first traffic grooming scheme and the traffic grooming scheme not employed for implementation may be the second traffic grooming scheme.

In this embodiment, the grooming policy includes one or more implementation descriptions of the solution, where the implementation descriptions of the solution include one or more preset regional grooming quantization indexes. The grooming policy may be provided by the first people stream monitoring terminal and carried in the scheme update instruction, and the cloud platform matches the second alternative people stream grooming scheme according to the scheme update instruction.

Step S32, determining index data configured for each region grooming quantization index described in the implementation of the solution.

In this embodiment, for example, the area grooming quantization index may include a congestion index of the flow of people corresponding to the monitored area that needs to be groomed currently, the flow of people in unit time, and a grooming target that needs to be achieved. The index data corresponds to the specific index value of the index corresponding to the corresponding quantization index.

Step S33, updating the people flow dispersion rule file, and adding the people flow dispersion information to the people flow dispersion rule file to obtain the second people flow dispersion scheme for carrying out people flow dispersion on the monitoring area in the target monitoring scene.

Step S34, the second people stream grooming scheme is adjusted from the standby scheme to the active scheme, and is sent to each of the unmanned aerial vehicles, so that the active scheme is implemented by each of the unmanned aerial vehicles to groom the corresponding monitored area.

The crowd evacuation information includes evacuation policy information of the second crowd evacuation scheme and the index data, and the evacuation policy information includes rule content of the evacuation policy.

In addition, the people stream grooming rule file may be a grooming rule description file with a specific format included in the corresponding people stream grooming scheme, and is used to record the corresponding grooming rule description, and may be decoded and obtained by the corresponding people stream monitoring terminal and/or the unmanned aerial vehicle according to the corresponding protocol, so as to execute the corresponding grooming scheme.

The rule content may be, for example, feature information of a rule respectively corresponding to the corresponding breakout policies, for example, rule information about a restriction that may correspond to each breakout policy, such as a certain traffic breakout policy for a certain scenic spot, and a corresponding restriction rule may include a restriction rule by which the traffic of a certain scenic spot road or entrance cannot exceed.

In another possible implementation scheme, after the second alternative traffic diversion scheme is determined, before implementation, model simulation of traffic diversion can be performed according to current monitoring data and actual conditions of each monitoring area through a pre-established simulation model, and after the simulation is passed, implementation can be performed again, so that the implementation of the corresponding traffic diversion scheme can meet current actual requirements. Based on this, the method provided by the embodiment of the present invention may further include the following.

(1) And acquiring people flow limiting indexes of different people flow nodes in the monitoring area in the people flow monitoring system, wherein the people flow limiting indexes comprise the maximum people flow quantity of the different people flow nodes.

The people flow node may be an important people flow node set in the monitoring area, such as a certain intersection or a certain road segment.

(2) And acquiring the people flow information monitored in the people flow monitoring system at a set time period. For example, information on the flow of people monitored in the past 15 minutes is acquired.

(3) And according to the scheme implementation description included in the dredging strategy, carrying out people flow dredging simulation on the monitored people flow information in the set time period through a people flow dredging simulation model on the monitoring area in the people flow monitoring system according to the scheme implementation description, and acquiring the number of simulated people flows of different people flow nodes in the monitoring area, which is obtained by the people flow dredging simulation. The artificial intelligence model may be obtained in advance according to big data analysis based on the actual situation of the monitored target range, and the obtaining method or the training method of the artificial intelligence model is not described in detail in this embodiment.

(4) And according to the simulated people flow number of different people flow nodes and the maximum people flow number of different people flow nodes, determining whether the dredging strategy of the alternative people flow dredging scheme represented by the scheme updating indication conforms to a set rule.

(5) If the second people flow dispersion scheme meets the set rule, the second people flow dispersion scheme is adjusted to be the main scheme so as to apply the second people flow dispersion scheme; and if the current situation does not accord with the set rule, sending prompt information of incomplete scheme updating to a monitoring area corresponding to the first personal flow monitoring terminal, so that the first personal flow monitoring terminal feeds back scheme updating instructions about the flow grooming scheme again according to the prompt information to update the grooming strategy.

In detail, in a possible example, when a quotient of the simulated number of people flow of at least one people flow node and the maximum number of people flow of the people flow node is greater than a set quotient threshold, it may be determined that the plan update indicates that the grooming policy of the represented alternative people flow grooming plan does not comply with the set rule, and if the quotient of the simulated number of people flow of all people flow nodes and the maximum number of people flow of the people flow node is less than the set quotient threshold, it may be determined that the plan update indicates that the grooming policy of the represented alternative people flow grooming plan complies with the set rule.

For example, alternatively, when a quotient of the simulated number of people flow of at least one people flow node and the maximum number of people flow of the people flow node is greater than a set quotient threshold (e.g., 90% or 95%), it is determined that the plan update indicates that the breakout policy of the represented alternative people flow breakout plan does not comply with the set rule, and if the quotient of the simulated number of people flow of all people flow nodes and the maximum number of people flow of the people flow node is less than the set quotient threshold, it is determined that the plan update indicates that the breakout policy of the represented alternative people flow breakout plan complies with the set rule.

Further, in a possible implementation manner, the grooming policy may be formed by planning by a preset plan planner and uploaded to the cloud platform, where the cloud platform stores a plurality of grooming policies, and each grooming policy carries unique grooming policy identification information. Based on this, as shown in fig. 4, regarding the step S31, determining the grooming policy of the alternative second people stream grooming scheme may include the following contents of steps S311-S313, which are exemplarily introduced as follows.

Step S311, receiving the grooming policy identifier information sent when the first personal flow monitoring terminal feeds back the scheme update instruction.

Step S312, according to the breakout policy identification information, searching a rule content of a breakout policy corresponding to the breakout policy identification information from a rule content library of the cloud platform.

Step S313, writing the rule content into a preset people stream grooming rule file to obtain a grooming policy of the second alternative people stream grooming scheme.

In addition, in this embodiment, there may be a special case that the obtained second people stream guidance scheme does not match the actual situation of other monitored areas, and the second people stream guidance scheme is implemented for avoiding this situation. Based on this, in a possible implementation, regarding the above step S33, the following sub-steps S331 and S332 may be included, which are exemplarily described as follows.

Step S331, sending the second people stream grooming plan to a monitoring area corresponding to a second people stream monitoring terminal other than the first people stream monitoring terminal, and obtaining scheme feedback information about the second people stream grooming plan from the monitoring area corresponding to the second people stream monitoring terminal. In this embodiment, the scheme feedback information represents whether the people flow monitoring terminal corresponding to the second people flow dispersion scheme considers that the people flow dispersion strategy corresponding to the second people flow dispersion scheme is reasonable.

Step S332, if it is determined that the second people flow monitoring terminal agrees with the people flow grooming policy corresponding to the second people flow grooming scheme according to the acquired scheme feedback information, then the step S34 of adjusting the second people flow grooming scheme from the standby scheme to the main scheme is performed, and the adjusted second people flow grooming scheme is sent to each of the unmanned aerial vehicles, so that each of the unmanned aerial vehicles implements the main scheme to perform people flow grooming on the corresponding monitoring area.

Therefore, whether the people flow monitoring terminals corresponding to other monitoring areas conflict with the second people flow dispersion scheme to be implemented or not is judged based on the inquiry mode.

Further, in another possible embodiment, regarding the above step S33, the following steps S333 to S337 can also be implemented, which are exemplarily described as follows.

Step S333, before applying the second people stream grooming plan, obtaining a plan feedback opinion, where the plan feedback opinion is opinion information that any people stream monitoring terminal confirms a notification reply according to the plan described in the plan implementation, or a feedback opinion returned by the cloud platform according to a feedback instruction about the plan feedback opinion. The acquired scheme feedback opinions have first information identification.

Step S334, if the scheme feedback opinion is obtained from any one of the people flow monitoring terminals, sending the scheme feedback opinion to a second people flow monitoring terminal other than the first people flow monitoring terminal, receiving feedback information of the second people flow monitoring terminal about the scheme feedback opinion, determining whether the scheme feedback opinion agrees with the second people flow grooming scheme according to the received feedback information, and if the scheme feedback opinion agrees with the second people flow grooming scheme, adjusting the obtained scheme feedback opinion from the first information identifier to a second information identifier.

Step S335, if the plan feedback opinions are obtained from the cloud platform, sending the plan feedback opinions to each people stream monitoring terminal in the people stream monitoring system, and if opinion feedback about the plan feedback opinions fed back by each people stream monitoring terminal is not obtained within a set time period, adjusting the obtained plan feedback opinions from the first information identifier to a second information identifier.

Step S336, if it is determined that the scheme feedback opinions do not agree with the second people stream persuasion scheme according to the received feedback information, then sending a confirmation instruction for confirming the scheme feedback opinions again to the cloud platform according to a set time interval, and obtaining a confirmation result of the scheme feedback opinions from the cloud platform; and when the confirmation result represents that the scheme feedback opinion agrees with the second people stream persuasion scheme, adjusting the information identifier of the scheme feedback opinion to be a second information identifier.

Therefore, after a certain time is delayed, the second stream of people is dredged after the situation changes and the second stream of people is dredged after the situation changes, so that the implementation of stream of people can be more intelligent and more matched with the actual situation.

Step S337, when the information identifier of the plan feedback opinion is adjusted to be a second information identifier, adjusting the second people stream grooming plan to be a primary plan for application.

In this embodiment, when performing grooming based on the designed people flow grooming scheme, in actual application, there may be a situation that a specific grooming policy needs to be added to meet the current actual condition. Based on this, the method provided by the embodiment of the present invention may further include the following.

Firstly, when a policy implantation instruction for implanting a target grooming policy into the second people stream grooming scheme, which is sent by the first people stream monitoring terminal, is received, the policy implantation instruction, the target grooming policy, and index data configured for a region grooming quantitative index in the target grooming policy are sent to each second people stream monitoring terminal other than the first people stream monitoring terminal as policy implantation sending information, and feedback information of the second people stream monitoring terminal is obtained.

And when confirming that each second people flow monitoring terminal agrees to implant a target dispersion strategy according to the feedback information, adding the target people flow dispersion information into the people flow dispersion rule file to obtain a people flow dispersion scheme after strategy implantation.

In this embodiment, the target people stream grooming information may include target grooming policy information and index data configured for a regional grooming quantization index in the target grooming policy, where the target grooming policy information includes rule content of the target grooming policy. Furthermore, the target people flow dispersion information may be dispersion information corresponding to the target dispersion strategy, for example, specific people flow dispersion information required for a specific road segment.

Further, in the embodiment of the present invention, after the second people stream breakout scheme is applied, when an indication representing that the second people stream breakout scheme is ended is received, which is sent by the first people stream monitoring terminal, the following method may be further executed to restart the previous first people stream breakout scheme. Since the second traffic grooming scheme is only temporarily used for emergency, it may also be necessary to restore the previously used first traffic grooming scheme. Several possible embodiments can be exemplarily described as follows.

Firstly, the second people stream grooming scheme is directly adjusted to be a standby scheme, the first people stream grooming scheme is adjusted to be a main scheme, and the first people stream grooming scheme is restarted.

Or secondly, sending a scheme restart notification to each people stream monitoring terminal in a monitoring area in the people stream monitoring system, and when receiving a scheme restart confirmation instruction fed back by each people stream monitoring terminal in the monitoring area, adjusting the second people stream grooming scheme to be a standby scheme, and adjusting the first people stream grooming scheme to be a main scheme, so as to restart the first people stream grooming scheme.

Or, thirdly, collecting first people stream monitoring information in the monitoring area when the first people stream grooming scheme is implemented to people stream monitoring terminals in each monitoring area, and obtaining second people stream monitoring information in the monitoring area when the second people stream grooming scheme is implemented;

then, whether a condition for restarting a first people stream grooming scheme is met or not is confirmed according to the first people stream monitoring information and the second people stream monitoring information; when the condition of restarting a first stream grooming scheme is met, the second stream grooming scheme is adjusted to be a standby scheme, the first stream grooming scheme is adjusted to be a main scheme, and the first stream grooming scheme is restarted.

In one possible mode, when a first people stream density distribution obtained by analyzing according to the first people stream monitoring information is better than a second people stream density distribution obtained by analyzing according to the second people stream monitoring information, a condition for restarting a first people stream grooming scheme is met; the first people flow density profile comprises first people flow congestion indices for all monitored areas within the people flow monitoring system; the second people flow density distribution includes a second people flow congestion index for all monitored areas within the people flow monitoring system. In this embodiment, the first and second people stream density distributions may be differences between the people stream densities of each monitoring area in all the monitoring areas and a preset people stream density or a people stream density average value of each area, and the optimization degree of the people stream density distribution may be determined according to the differences. For example, if the people flow density in each monitoring area fluctuates around the preset people flow density or the average people flow density and the fluctuation is small, the people flow density distribution is excellent. Conversely, if the people flow density of each monitoring area is larger in the vicinity of the preset people flow density or the people flow density average value, the people flow density distribution is poor.

As shown in fig. 5, an architectural schematic diagram of a cloud platform 11 provided by the embodiment of the present invention for implementing the method described above is provided. In this embodiment, the cloud platform 11 may include a people flow monitoring apparatus 110, a machine-readable storage medium 120, and a processor 130.

In this embodiment, the machine-readable storage medium and the processor may be located in the cloud platform 11 and separately provided. The machine-readable storage medium 120 may also be independent of the cloud platform 11 and accessed by the processor 130. The people flow monitoring device 110 may include a plurality of functional modules stored in a machine-readable storage medium, such as various software functional modules included in the people flow monitoring device 110. When the processor executes the software function module in the human flow monitoring device 110, the block chain big data processing method provided by the foregoing method embodiment is implemented.

In this embodiment, the cloud platform 11 may include one or more processors. The processor may process information and/or data related to the service request to perform one or more of the functions described in this disclosure. In some embodiments, a processor may include one or more processing engines (e.g., a single-core processor or a multi-core processor). For example only, the processor may include one or more hardware processors such as one of a central processing unit CPU, an application specific integrated circuit ASIC, an application specific instruction set processor ASIP, a graphics processor GPU, a physical arithmetic processing unit PPU, a digital signal processor DSP, a field programmable gate array FPGA, a programmable logic device PLD, a controller, a microcontroller unit, a reduced instruction set computer RISC, a microprocessor, or the like, or any combination thereof.

A machine-readable storage medium may store data and/or instructions. In some embodiments, a machine-readable storage medium may store the obtained data or material. In some embodiments, a machine-readable storage medium may store data and/or instructions for execution or use by the cloud platform 11, which the cloud platform 11 may execute or use to implement the example methods described herein. In some embodiments, a machine-readable storage medium may include mass storage, removable storage, volatile read-write memory, read-only memory, ROM, the like, or any combination thereof. Exemplary mass storage devices may include magnetic disks, optical disks, solid state disks, and the like. Exemplary removable memories may include flash drives, floppy disks, optical disks, memory cards, compact disks, magnetic tape, and the like. Exemplary volatile read-write memories may include random access memory RAM. Exemplary random access memories may include dynamic RAM, double-rate synchronous dynamic RAM, static RAM, thyristor RAM, zero-capacitance RAM, and the like. Exemplary ROMs may include masked ROMs, programmable ROMs, erasable programmable ROMs, electrically erasable programmable ROMs, compact disk ROMs, digital versatile disk ROMs, and the like.

The people flow monitoring apparatus 110 included in the cloud platform 11 may include one or more software functional modules. The software functional modules may be stored as programs, instructions in the machine-readable storage medium, which when executed by a corresponding processor, are configured to implement the above-described method, e.g., when executed by a processor of a drone, or when executed by the cloud platform, are configured to implement the above-described method steps performed by the drone, or the cloud platform.

As shown in fig. 6, the people flow monitoring apparatus 110 may include a people flow data monitoring module 1101, a monitoring data analyzing module 1102, and a people flow grooming module 1103.

A people flow data monitoring module 1101, configured to obtain, from each people flow monitoring terminal, people flow monitoring data corresponding to each monitoring area, which is obtained by performing people flow monitoring on the corresponding monitoring area by each unmanned aerial vehicle;

the monitoring data analysis module 1102 is configured to perform data analysis according to the people flow monitoring data corresponding to each monitoring area, and determine whether any monitoring area meets a preset people flow dispersion triggering condition according to a result of the data analysis;

the pedestrian flow dispersion module 1103 is configured to, when there is any monitoring area that meets a preset pedestrian flow dispersion trigger condition, acquire a corresponding pedestrian flow dispersion scheme, determine, according to the pedestrian flow dispersion scheme, pedestrian flow dispersion indication information for each unmanned aerial vehicle, and send the pedestrian flow dispersion indication information to each unmanned aerial vehicle, so as to control each unmanned aerial vehicle to perform pedestrian flow dispersion corresponding to the monitoring area according to the corresponding pedestrian flow dispersion indication information.

The people flow monitoring data is obtained by analyzing the people flow image information shot by each unmanned aerial vehicle by each people flow monitoring terminal according to a pre-established image analysis model, or the people flow image information is obtained by analyzing the people flow image information by the image analysis model pre-loaded on the unmanned aerial vehicle and fed back to the corresponding people flow monitoring terminal, the people flow dispersion scheme is one of two or more than two types which are pre-designed and stored, and the people flow dispersion indication information comprises the people flow dispersion actions and the people flow dispersion strategy contents which are respectively required to be executed by each unmanned aerial vehicle.

It should be understood that the people flow data monitoring module 1101, the monitoring data analyzing module 1102, and the people flow grooming module 1103 described above may be respectively configured to perform the steps S11-S13 shown in fig. 1, and for more contents of these modules, details of these steps may be referred to, and are not described herein again.

Further, in this embodiment, the people flow monitoring apparatus 110 may further include a grooming scheme adjusting module, configured to:

determining index data configured for each region grooming quantization index described by the implementation of the scheme; and

updating a people flow dispersion rule file, and adding people flow dispersion information into the people flow dispersion rule file to obtain a second people flow dispersion scheme for carrying out people flow dispersion on the monitoring area in the target monitoring scene; the crowd evacuation information includes evacuation policy information of the second crowd evacuation scheme and the index data, and the evacuation policy information includes rule content of the evacuation policy.

the grooming scheme adjustment module 1104 is further specifically configured to:

While the invention has been described with reference to a particular embodiment, it will be understood by those skilled in the art that various changes in form and details may be made therein without departing from the spirit and scope of the invention as defined by the appended claims. Furthermore, the detailed description of the embodiments of the present invention provided in the accompanying drawings is not intended to limit the scope of the invention, but is merely representative of selected embodiments of the invention. Therefore, the protection scope of the present invention shall be subject to the protection scope of the claims. Moreover, all other embodiments that can be made available by a person skilled in the art without inventive step based on the embodiments of the present invention shall fall within the scope of protection of the present invention.

Claims

1. The utility model provides a people flow monitoring method based on city management, is applied to people flow monitoring system's cloud platform, its characterized in that, people flow monitoring system still include with cloud platform communication connection and be used for respectively to the different monitoring area of target monitoring scene carry out the unmanned aerial vehicle of people flow control and be used for receiving each a plurality of people flow monitor terminal of people flow control data that unmanned aerial vehicle fed back, a plurality of people flow monitor terminal set up respectively in different monitoring area, the method includes:

2. The method according to claim 1, wherein the people flow monitoring data is obtained by each people flow monitoring terminal analyzing the people flow image information shot by each unmanned aerial vehicle according to a pre-established image analysis model, or the people flow image information is obtained by analyzing the people flow image information by the image analysis model pre-loaded on the unmanned aerial vehicle and fed back to the corresponding people flow monitoring terminal, the people flow grooming scheme is one of two or more than two pre-designed and stored people flow grooming actions, and the people flow grooming indication information includes the people flow grooming actions and the people flow grooming policy contents that each unmanned aerial vehicle needs to execute respectively.

3. The method according to claim 1 or 2, characterized in that the method further comprises:

4. The method of claim 3, wherein the updating the people flow grooming rule file, adding people flow grooming information to the people flow grooming rule file, and obtaining the second people flow grooming scheme for people flow grooming the monitoring area in the target monitoring scene further comprises:

and if it is determined that a second people stream monitoring terminal accepts the people stream grooming strategy corresponding to the second people stream grooming scheme according to the acquired scheme feedback information, adjusting the second people stream grooming scheme from a standby scheme to a main scheme, and sending the main scheme to each unmanned aerial vehicle so as to implement the steps of people stream grooming on the corresponding monitoring area through the main scheme by each unmanned aerial vehicle.

5. The method of claim 3, wherein the updating the people flow grooming rule file, adding people flow grooming information to the people flow grooming rule file, and obtaining the second people flow grooming scheme for people flow grooming the monitoring area in the target monitoring scene further comprises:

6. The method of claim 3, further comprising:

7. The method of claim 3, wherein determining the grooming policy of the alternative second traffic grooming scheme comprises:

8. The method according to any one of claims 3-7, further comprising:

9. The utility model provides a people flow monitored control system based on city management, its characterized in that, people flow monitored control system include the cloud platform, with cloud platform communication connection just is used for respectively carrying out a plurality of unmanned aerial vehicles of people flow control and being used for receiving each the people flow monitor terminal of the people flow monitor data of unmanned aerial vehicle feedback to the different monitoring area of target monitoring scene, a plurality of people flow monitor terminal set up respectively in the monitoring area of difference, the cloud platform includes:

10. A cloud platform, wherein the cloud platform is respectively in communication connection with a plurality of drones for respectively performing people flow monitoring on different monitoring areas of a target monitoring scene and a plurality of people flow monitoring terminals for receiving people flow monitoring data fed back by each drone, and the cloud platform comprises a processor, a machine-readable storage medium, the machine-readable storage medium is connected with the processor, the machine-readable storage medium is used for storing a program, an instruction or a code, and the processor is used for executing the program, the instruction or the code in the machine-readable storage medium to implement the method according to any one of claims 1 to 8.