CN113473592A - Passenger flow monitoring system and method - Google Patents
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Abstract
The invention provides a passenger flow monitoring system and a method; the system comprises: the system comprises a data acquisition layer, a network connection layer, a data resolving layer and an application layer; the data acquisition layer is connected with the network connection layer; the network connection layer is connected with the data resolving layer; the data resolving layer is connected with the application layer; the application layer comprises: the system comprises a passenger flow statistics module, a passenger flow prediction module and an early warning module; the invention can accurately identify the position of the customer, count and monitor the passenger flow in a certain area range in a market, and timely dredge the passenger flow when the passenger flow exceeds a certain limit value; the number of users in any time period and the peak time of people flow can be intelligently predicted according to historical data, and therefore management and operation efficiency is improved.
Description
Technical Field
The invention relates to the field of physics, in particular to a crowd path prediction technology, and particularly relates to a passenger flow monitoring system and a passenger flow monitoring method.
Background
The business surpasses as one of the most important indoor business environments in cities, and has the unwear effect in the aspects of city transformation development, population mobility, regional gathering and the like. Large shopping malls in China are numerous and are distributed in various places of large, medium and small cities, the largest shopping square area of the shopping mall and the shopping square area of the shopping mall is 121.5 ten thousand square meters, and the daily consumers are more than 20 ten thousand people. Every weekend or holiday, the number of the passenger flows in the superstore can reach a high peak value, the passenger flows are dense, the passenger flow is increased suddenly in a short time often, and managers cannot accurately predict the passenger flow trend and cannot dredge the passenger flows in time, so that a series of potential safety hazards and even trample accidents occur.
The traditional shopping mall passenger flow monitoring mode mainly comprises video passenger flow monitoring, manual passenger flow monitoring and the like, a large amount of manpower and material resources are required to be input, the efficiency is low, the accuracy is low, dead corners are left, the input cost is high, the intelligent degree is low, certain defects exist, and the large-scale popularization is difficult; meanwhile, a monitoring and early warning mechanism is lacked, and when the passenger flow of a shopping mall is huge, managers cannot be reminded to dredge and manage the passenger flow of the shopping mall.
Disclosure of Invention
In view of the above disadvantages of the prior art, an object of the present invention is to provide a passenger flow monitoring system and method, which are used to solve the problems of low intelligence degree, lack of monitoring and early warning mechanism, and incapability of timely passenger flow dispersion and management in the existing passenger flow monitoring technology.
To achieve the above and other related objects, the present invention provides a passenger flow monitoring system, comprising: the system comprises a data acquisition layer, a network connection layer, a data resolving layer and an application layer; the data acquisition layer is connected with the network connection layer and is used for acquiring position data information of a customer; the network connection layer is connected with the data resolving layer and used for providing a network link so as to send the position data information to the data resolving layer; the data resolving layer is connected with the application layer and used for analyzing and processing the position data information, resolving target position data and sending the target position data to the application layer so as to enable the application layer to realize passenger flow monitoring based on the target position data; the application layer comprises: the system comprises a passenger flow statistics module, a passenger flow prediction module and an early warning module; the passenger flow counting module is used for counting the number of people in the designated area in any time period and counting the number of people in the designated area in any time period; the passenger flow prediction module is used for predicting the number of people in the designated area in the designated time period and predicting the number of people in the designated area in the designated time period; the early warning module includes: a passenger flow volume early warning submodule and an emergency condition early warning submodule; the passenger flow early warning submodule is used for early warning passenger flow; and the emergency condition early warning sub-module is used for giving an alarm when an emergency occurs in the shopping mall.
In an embodiment of the invention, the data acquisition layer includes: positioning a functional hardware unit and a 5G intelligent indoor distribution system; wherein the positioning function hardware unit comprises: positioning a micro base station and positioning a micro tag; the positioning micro base station sends a request for acquiring the position data information to the positioning micro tag at intervals of preset time so as to monitor the position information of the positioning micro tag in real time; and after receiving the request, the positioning micro tag sends the position data information to the positioning micro base station.
In an embodiment of the present invention, the target location data includes: positioning the position coordinates of the micro-tags; the data resolving layer is used for analyzing and processing the position data information by utilizing a positioning algorithm and a ranging algorithm; wherein, the positioning algorithm adopts any one of the following algorithms: positioning algorithm based on arrival time, positioning algorithm based on arrival time difference and positioning algorithm based on arrival angle; the distance measurement algorithm adopts a distance measurement method based on signal flight time, and the distance measurement method based on the signal flight time is realized in a bilateral two-way distance measurement mode.
In an embodiment of the present invention, the number of the positioning micro base stations is at least two; the angle-of-arrival-based positioning algorithm comprises the following steps: selecting two positioning micro base stations from at least two positioning micro base stations as a first base station and a second base station respectively; respectively acquiring a first angle between the reference line and a connecting line of the positioning micro tag and the first base station and a second angle between the reference line and a connecting line of the positioning micro tag and the second base station by taking the connecting line of the first base station and the second base station as reference lines; positioning the position coordinates of the positioning micro-tag by using a triangulation method; the calculation formula of the position coordinates of the positioning micro-tag is as follows:
wherein the position coordinates of the positioning micro-tag are expressed as (x, y); (x)1，y1)、(x2，y2) Respectively representing the position coordinates of the two positioning micro base stations; theta1Representing the first angle; theta2Representing the second angle.
In an embodiment of the present invention, the number of the positioning micro base stations is at least three; the time-of-arrival based positioning algorithm comprises the following steps: selecting three positioning micro base stations from at least three positioning micro base stations; acquiring the time when each positioning micro base station receives the positioning micro label sending signal; acquiring the position coordinates of the positioning micro-label based on the positioning micro-base station and the time; the calculation formula of the position coordinates of the positioning micro-tag is as follows:
the positioning algorithm based on the arrival time difference comprises the following steps: selecting three positioning micro base stations from at least three positioning micro base stations; obtaining the distance from each positioning micro base station to the positioning micro tag; acquiring the position coordinates of the positioning micro-label based on the positioning micro-base station and the distance; the calculation formula of the position coordinates of the positioning micro-tag is as follows:
wherein the position coordinates of the positioning micro-tag are expressed as (x, y); the position coordinate of the nth positioning micro base station is expressed as (x)n，yn)；tnThe time that the positioning micro-tag transmits a signal at the time t and the nth positioning micro base station receives the signal transmitted by the positioning micro-tag is represented; c represents the speed of light; dnDenotes the nth numberThe distance from the bit micro base station to the positioning micro tag; n is 1, 2, 3.
In an embodiment of the present invention, the distance between each of the positioning micro base stations and the positioning micro tag is obtained by a time difference of arrival of two signals with different propagation speeds, or a time difference generated when the same signal arrives at different nodes.
In an embodiment of the present invention, the application layer further includes: the system comprises a display management module, a system management module and a map management module; the display management module includes: a display submodule and a base station submodule; the display submodule is used for displaying a market map and positioning the positions of the labels, the base stations and the passenger flow on the market map in real time; the base station submodule is used for managing base station information; the system management module comprises: the system comprises a user management submodule, a shop management submodule, a floor management submodule and a behavior log submodule; the user management submodule is used for managing user information; the shop management submodule is used for carrying out addition, deletion, modification and check on the basic information of the shopping mall; the floor management submodule is used for carrying out addition, deletion, modification and check on the basic information of each floor of the shopping mall; the behavior log submodule is used for recording the behavior of the user; the map management module includes: a market information management submodule and a map information management submodule; the market information management submodule is used for carrying out addition, deletion, modification and check on market information; and the map information management submodule is used for carrying out addition, deletion, modification and check on the map information.
In an embodiment of the present invention, the communication mode of the network connection layer includes any one or a combination of the following: 5G, Bluetooth and ZigBee.
The invention provides a passenger flow monitoring method realized by adopting the passenger flow monitoring system, which comprises the following steps: acquiring position data information of a customer; and analyzing and processing the position data information to realize passenger flow monitoring.
As described above, the passenger flow monitoring system and method of the present invention have the following advantages:
(1) compared with the prior art, the invention can accurately identify the position of the customer, and carry out statistics and monitoring on the passenger flow in a certain area range in a market, so as to carry out passenger flow dispersion in time when the passenger flow exceeds a certain limit value.
(2) The invention can intelligently predict the number of users and the peak time of people flow in any time period according to historical data, thereby improving the management and management efficiency.
Drawings
Fig. 1 is a diagram illustrating a network architecture of a 5G fusion indoor positioning technique according to an embodiment of the present invention.
Fig. 2 is a network architecture diagram illustrating another embodiment of the 5G fusion indoor positioning technique of the present invention.
Fig. 3 is a schematic diagram of a passenger flow monitoring system according to an embodiment of the invention.
FIG. 4 is a system architecture diagram illustrating a 5G/UWB indoor positioning based technology in one embodiment of the present invention.
FIG. 5 is a diagram illustrating the architecture of UWB and 5G intelligent room subsystem of the present invention in one embodiment.
FIG. 6 is a schematic diagram of an AOA location algorithm of the present invention in one embodiment.
FIG. 7 is a schematic diagram of the TOA location algorithm of the present invention in one embodiment.
FIG. 8 is a schematic diagram of a TDOA location algorithm in an embodiment of the present invention.
Fig. 9 is a diagram illustrating a TOF implementation process in an embodiment of the invention.
Fig. 10 is a flowchart illustrating a passenger flow monitoring method according to an embodiment of the invention.
Description of the reference symbols
1-a data acquisition layer; 2-network connection layer; 3-a data resolving layer; 4-application layer.
Detailed Description
The following description of the embodiments of the present invention is provided by way of specific examples, and other advantages and effects of the present invention will be readily apparent to those skilled in the art from the disclosure herein. The invention is capable of other and different embodiments and of being practiced or of being carried out in various ways, and its several details are capable of modification in various respects, all without departing from the spirit and scope of the present invention. It is to be noted that the features in the following embodiments and examples may be combined with each other without conflict.
It should be noted that the drawings provided in the following embodiments are only for illustrating the basic idea of the present invention, and the drawings only show the components related to the present invention rather than being drawn according to the number, shape and size of the components in actual implementation, and the type, number and proportion of the components in actual implementation may be changed arbitrarily, and the layout of the components may be more complicated.
Compared with the prior art, the passenger flow monitoring system and the passenger flow monitoring method can accurately identify the position of a customer, carry out statistics and monitoring on the passenger flow in a certain area range in a market, and carry out passenger flow dispersion in time when the passenger flow exceeds a certain limit value; the invention can intelligently predict the number of users and the peak time of people flow in any time period according to historical data, thereby improving the management and management efficiency.
With 5G stepping into commerce, the low-delay, large-bandwidth and high-reliability performance of the system enables the system to have extremely important advantages in the aspect of indoor positioning, 5G can realize high-precision positioning, a 5G indoor positioning technology provides important support for intelligent transformation of a business circle, provides real-time passenger flow quantity, passenger flow lines, residence time and visiting frequency data for a market while providing accurate market positioning, navigation and shopping guide services for consumers, analyzes passenger flow in each time period, assists to efficiently finish management work of the market, records quantitative statistical analysis data of the number of people coming in and going out and the composition of residence conditions of public places in a 5G indoor positioning technical mode, can monitor the saturation degree and operation state of the market in real time, and can predict the change trend of the passenger flow at a certain moment by utilizing high-precision passenger flow statistical big data, therefore, related managers can reasonably schedule manpower, material resources and resources according to the passenger flow statistical analysis data, the best operation effect is obtained, once the detained passenger flow reaches the determined passenger flow peak value, automatic early warning is achieved, and a manager in a shopping mall can reasonably arrange staff to dredge the passenger flow, so that safety accidents are avoided.
The 5G technology greatly improves the performance of a mobile network, provides the networking capability of large bandwidth, low time delay and wide connection, and provides necessary technical guarantee for digitization in the vertical industry; Ultra-WideBand (UWB) is a new communication technology that uses pulses with a nanosecond width as wireless communication signals, and is particularly prominent in terms of time resolution, positioning accuracy can be accurate to a centimeter level, UWB high-accuracy positioning can reach centimeter-level positioning accuracy, and the Ultra-WideBand (UWB) has strong penetration capability and high positioning accuracy, can complete ranging and positioning tasks in a closed room or under the condition of a large number of obstacles, and can perform better performance even in an underground space.
As shown in fig. 1 and fig. 2, in combination with the requirements of communication and positioning accuracy, the invention provides a passenger flow monitoring system based on 5G fusion high-accuracy indoor positioning technologies such as indoor UWB and AOA, so as to realize monitoring and early warning of the passenger flow in a shopping mall.
The currently common indoor positioning technology pairs are shown in table 1 below.
The invention mainly considers that the positioning base station and the 5G intelligent indoor distribution system are jointly deployed in a combined mode, the positioning base station reuses site resources, power supply resources and transmission resources of the 5G pico-cell base station, and meanwhile, the advanced technologies such as edge calculation and big data are combined, the sub-meter positioning precision is provided, and various positioning service requirements under indoor scenes of large shopping malls and the like are met.
The invention discloses a passenger flow monitoring system, which is a shopping mall passenger flow monitoring method based on a 5G indoor positioning technology, and integrates a UWB positioning scheme, a positioning base station is connected with a cascade port of a 5G intelligent room branch to provide power supply for positioning base station equipment, and simultaneously, data of the UWB base station is finally transmitted to a Mobile Edge Computing (MEC) server for positioning resolving service through a 5G intelligent room branch system (BBU, PB and PRRU), so that the real-time statistical analysis of the human flow in a shopping mall is further performed.
The passenger flow monitoring system of the present invention will be explained in detail below with reference to the accompanying drawings.
The invention provides a whole set of solution from bottom layer sensing to top layer application by considering the characteristics of a 5G/UWB hybrid positioning shopping mall passenger flow monitoring method, which needs to integrate various technologies.
As shown in fig. 3, in an embodiment, the passenger flow monitoring system of the present invention includes four parts, namely a data acquisition layer 1, a network connection layer 2, a data calculation layer 3, and an application layer 4, each layer has different key technologies corresponding thereto for development and deployment, and mainly depends on a 5G mobile communication network to merge UWB/AOA indoor positioning technology, and the final purpose of the method is to implement statistical monitoring analysis of the market passenger flow.
Specifically, the data acquisition layer 1 is connected with the network connection layer 2 and is used for acquiring position data information of a customer; the network connection layer 2 is connected with the data calculation layer 3 and used for providing a network link so as to send the position data information to the data calculation layer 3; the data calculation layer 3 is connected to the application layer 4, and is configured to analyze and process the position data information, calculate target position data, and send the target position data to the application layer 4, so that the application layer 4 realizes passenger flow monitoring based on the target position data.
In one embodiment, the data acquisition layer 1 comprises a positioning function hardware unit and a 5G intelligent room subsystem.
Specifically, the positioning function hardware unit comprises a positioning micro base station and a positioning micro tag; the positioning micro base station sends a request for acquiring the position data information to the positioning micro tag at intervals of preset time so as to monitor the position information of the positioning micro tag in real time; and after receiving the request, the positioning micro tag sends the position data information to the positioning micro base station.
It should be noted that the data acquisition layer 1 is a main part of a mall indoor positioning system for implementing communication and positioning functions, and includes the positioning micro base station, the positioning micro tag, and the 5G intelligent room subsystem (BBU, PB, and PRRU); the positioning micro base station and the positioning micro tag are positioning functional hardware units; BBUs, PB, and PRRUs are 5G communication function hardware units.
Further, the hardware infrastructure of the data acquisition layer 1 further comprises a server, a storage medium, a network and a security device; the adopted API interfaces comprise OpenStack API and Cloud Storage API.
In an embodiment, the communication mode of the network connection layer 2 includes, but is not limited to, any one or a combination of the following: 5G, Bluetooth and ZigBee.
It should be noted that the network connection layer 2 has a main function of providing a network link for transmitting data (referred to the above location data information) collected by the positioning micro base station back to the MEC, and the main communication modes include 5G, bluetooth, ZigBee and the like; by utilizing the characteristics of large coverage area, low time delay, high equipment compatibility and the like of the 5G mobile communication network, the communication network based on the 5G can not only communicate, but also support high-precision and high-coverage positioning, and realize seamless and real-time transmission of positioning data.
As shown in fig. 4, the passenger flow monitoring system based on the 5G/UWB indoor positioning technology realizes real-time online positioning of passenger flow through a positioning tag, a 5G intelligent room distribution system, and a UWB positioning base station, and position information of passenger flow can be visually displayed on a background visual interface; specifically, the 5G base station sends a request for acquiring location information to the location tag at regular intervals, the location information of each tag is monitored in real time, the location tag immediately sends the location information to the base station after receiving the request for acquiring the location information sent by the base station, the base station immediately uploads the location information sent by the location tag to the MEC after receiving the location information of each tag, the MEC cloud platform performs a series of data processing by using a location algorithm after receiving the location information of each tag, and stores the processed location data such as coordinate values into a database on one hand, and displays the location of a customer on a visual interface on the other hand.
As shown in fig. 5, in the framework of the UWB and 5G intelligent indoor convergence networking system provided by the present invention, the 5G access unit, the extension unit, and the remote unit implement the indoor coverage of the 5G communication signal in the shopping mall, and at the same time, provide the backhaul required by UWB, complete the data aggregation and separation in the 5G access unit, and report the UWB positioning related data to the device management and location server.
For the convenience Of Application, for the UWB base station, star and daisy chain networking is supported, positioning technologies such as Time Of Arrival (TOA), Time Difference Of Arrival (TDOA), Angle Of Arrival (AOA) are adopted, a wireless clock synchronization method is adopted between the base stations, a device management and location server realizes related functions such as monitoring management and location engine Of the UWB base station, and an Application Programming Interface (API) is provided to the outside to output open classification (Tag) location coordinates.
In one embodiment, the target location data includes, but is not limited to, location coordinates of a location micro tag.
In an embodiment, the data calculation layer 3 is configured to analyze and process the position data information by using a positioning algorithm and a ranging algorithm.
It should be noted that the data calculation layer 3 is a key for implementing the tag position calculation, and the position calculation engine performs data cleaning on the data returned by the positioning micro base station and calculates the tag position coordinates according to different positioning algorithms.
It should be noted that, the calculation engine is deployed in the MEC, and can fully utilize the computing resources, storage capacity and processing capability provided by the MEC platform, and exert the advantages of high speed, low time delay and large connection of the 5G network, thereby improving the network utilization efficiency and the value-added value.
It should be noted that, after the position data information of the customer is collected by the data collection layer 1 and transmitted to the back-end cloud platform by the network connection layer 2, the position analysis processing is performed by the data calculation layer 3 by using a positioning algorithm, a ranging algorithm, and the like.
In one embodiment, the positioning algorithm is, but not limited to, any one of the following algorithms: time of arrival (TOA) -based location algorithms, time difference of arrival (TDOA) -based location algorithms, and angle of arrival (AOA) -based location algorithms.
It should be noted that, the three positioning algorithms have advantages and disadvantages, wherein the TDOA derives and calculates the distance between the anchor node and the tag node by using the time difference information, so that the TDOA has high positioning accuracy, and also conforms to the characteristic of high time resolution of the ultra-wideband system, and the system has low complexity and low cost; by comprehensive comparison, the TDOA location algorithm is selected as the 5G/UWB hybrid location method.
In one embodiment, the number of the positioning micro base stations is at least two; the angle-of-arrival-based positioning algorithm comprises the following steps:
(11) and selecting two positioning micro base stations from the at least two positioning micro base stations as a first base station A and a second base station B respectively.
(12) And respectively acquiring a first angle between the reference line and a connecting line of the positioning micro tag and the first base station A and a second angle between the reference line and a connecting line of the positioning micro tag and the second base station B by taking the connecting line of the first base station A and the second base station B as reference lines.
(13) And positioning the position coordinates of the positioning micro-label by using a triangulation method.
As shown in fig. 6, the position coordinates of the positioning micro-tag can be found according to the sine theorem; specifically, the calculation formula of the position coordinates of the positioning micro tag is as follows:
wherein the position coordinates of the positioning micro-tag are expressed as (x, y); (x)1，y1)、(x2，y2) Respectively representing the position coordinates of the two positioning micro base stations; theta1Representing the first angle; theta2Representing the second angle.
It should be noted that the AOA positioning algorithm requires an additional antenna during operation, which increases the cost of the system; because the AOA algorithm is an angle-based algorithm, the measurement requirement for the angle is high, and the AOA algorithm is easily influenced by non-line-of-sight.
As shown in fig. 7, in an embodiment, the number of the positioning micro base stations is at least three; the time-of-arrival based positioning algorithm comprises the following steps:
(21) selecting three positioning micro base stations from at least three positioning micro base stations.
(22) And acquiring the time when each positioning micro base station receives the positioning micro label sending signal.
(23) And acquiring the position coordinates of the positioning micro-label based on the positioning micro-base station and the time.
Specifically, the calculation formula of the position coordinates of the positioning micro tag is as follows:
as shown in fig. 8, in one embodiment, the positioning algorithm based on the time difference of arrival includes the following steps:
(31) selecting three positioning micro base stations from at least three positioning micro base stations.
(32) And acquiring the distance from each positioning micro base station to the positioning micro tag.
(33) And acquiring the position coordinates of the positioning micro-label based on the positioning micro-base station and the distance.
Specifically, the calculation formula of the position coordinates of the positioning micro tag is as follows:
wherein the position coordinates of the positioning micro-tag are expressed as (x, y); the position coordinate of the nth positioning micro base station is expressed as (x)n，yn)；tnThe time that the positioning micro-tag transmits a signal at the time t and the nth positioning micro base station receives the signal transmitted by the positioning micro-tag is represented; c represents the speed of light; dnRepresenting the distance from the nth positioning micro base station to the positioning micro label; n is 1, 2, 3.
It should be noted that, the main idea of the TOA positioning algorithm is as follows: the central processor processes the arrival time between each base station and the target node, and each base station establishes a positioning model by using a trilateration method, aiming at obtaining the coordinate information of the moving object.
It should be noted that, in the TOA positioning algorithm, the requirement on the accuracy of the time of the arrival signal in the synchronization is relatively high, because the time needs to be multiplied by the speed of light c, and therefore, the time error multiplied by the speed of light no matter how small the time error is, becomes a large error, and has a serious influence on the accuracy of indoor positioning.
It should be noted that the main ideas of the TDOA location algorithm are as follows: the time difference measured by a group of base stations can establish a pair of hyperbolas, the focus of the hyperbolas is two base stations, and the moving object is a certain point on the hyperbolas; the TDOA algorithm is different from the TOA algorithm in that the distance can be measured by the arrival time difference of 2 signals with different propagation speeds or the arrival time difference of the same signal at different nodes; the same is true in that trilateration is also used.
It should be noted that a hyperbolic positioning model is finally displayed in the TDOA positioning algorithm, and the solution obtained by the model is the position coordinates of the positioning micro-tag, but the model is a nonlinear equation set; the solving process of the nonlinear equation set is difficult, and the current solving algorithm mainly comprises the following steps: the Fang algorithm, the Chan algorithm, the Friedlander algorithm, the Taylor algorithm, and the like.
Furthermore, the positioning method of the invention is to finish distance estimation by a hardware module, and precise distance estimation is a premise for realizing a high-precision indoor positioning system, therefore, the invention combines the characteristics of UWB indoor positioning technology and adopts a distance estimation method based on signal time of flight (TOF).
In an embodiment, the Ranging algorithm adopts a Ranging method based on signal flight time, the Ranging method based on signal flight time is implemented in a Double-Sided Two-Way Ranging (DS-TWR), that is, multiple polling and response communication are required between a positioning base station and a tag, and the implementation process is as shown in fig. 9.
In FIG. 9, T ispollingThe time from sending a polling signal to device B to receiving a response signal from device B for device a; t isanswerThe time from the time when the device B receives the polling signal sent by the device A to the time when the device B sends a response signal to the device A; t isflightWhich is the transmission time of a signal, can be expressed by the following formula:
Tflight＝1/2(Tpolling-Tanswer)。
it should be noted that, after the application layer 4 processes the real-time data through the positioning algorithm and the ranging algorithm, the application layer 4 mainly displays and applies the final effect; specifically, the 5G fusion indoor positioning technology is utilized to complete the presentation of a business layer, realize the monitoring of the passenger flow of a market based on the position data of the customer, assist the market in carrying out the passenger flow management, provide the passenger flow statistics, the passenger flow analysis, the emergency rescue and the emergency search and rescue based on the accurate position information, and provide the position services such as the indoor navigation of the market for the customer.
It should be noted that the functions finally exhibited by the application layer 4 in the present invention include:
1. in order to realize early warning analysis of the passenger flow in the shopping mall and avoid safety accidents.
2. The management and analysis of the market are carried out through the change of the passenger flow, and whether the management condition of the market is good or not is judged according to the change of the passenger flow, so that an operator can clearly know the operation condition of the market, and a solid precondition and a foundation are laid for the adjustment of the recruit.
3. And displaying the current real-time passenger flow data, the combined chart of each dimension and the analysis of the system on the combined chart and the passenger flow of each time period, helping a manager to efficiently finish the management work of a market and the like.
In an embodiment, the application layer 4 includes a passenger flow statistics module, a passenger flow prediction module, and an early warning module.
The passenger flow counting module is used for counting the number of people in the designated area in any time period and counting the number of people in the designated area in any time period; specifically, the statistical information can be obtained through the module after entering the system, and the real-time passenger flow in a shopping mall is obtained; meanwhile, the statistical information can be used for carrying out accurate customer group analysis, whether the actual customer group is consistent with the expected customer group or not is compared, and if not, the business over-sale strategy or the product is adjusted in time.
The passenger flow prediction module is used for predicting the number of people in a specified area in a specified time period and predicting the number of people in the specified area in the specified time period; specifically, the shopping mall can adjust security arrangement, promotion time and goods purchasing quantity in advance according to the prediction information, and avoids risks brought to shopping mall operation by people flow rate misprediction.
In one embodiment, the early warning module includes, but is not limited to, a passenger flow early warning sub-module and an emergency situation early warning sub-module.
It should be noted that the passenger flow volume early warning submodule is used for early warning the passenger flow volume; specifically, when the passenger flow in a certain area analyzed by the data calculation layer 3 is about to reach or exceed a limit value, the passenger flow early warning sub-module is started to generate early warning information and display the warning information on a visual page to prompt a manager of a shopping mall to dredge the passenger flow in time.
It should be noted that the emergency condition early warning sub-module is configured to alarm when an emergency occurs in the mall; specifically, when an emergency or an emergency occurs in a mall, an alarm is given in time to prompt a mall manager to take measures as soon as possible to process, so that greater damage is avoided.
In an embodiment, the application layer 4 further includes a display management module, a system management module, and a map management module.
Specifically, the display management module includes, but is not limited to, a display sub-module and a base station sub-module.
The display submodule is used for displaying a market map, positioning the position of the tag, the base station and the passenger flow on the market map in real time, having the functions of area statistics, page screenshot, tag search and plane ranging, and displaying the floor map and the shop information of the market.
It should be noted that, the area counting function can automatically count the number of people and the passenger flow information in the area by randomly selecting one area; the page screenshot function can automatically screenshot the current page condition of the home page and store the current page condition; the tag searching function can quickly locate the tag and centralize the position of the tag and simultaneously display the detailed information of the tag; the planar ranging function can measure the actual distance between any two points on the map or the actual area of a graph.
The base station submodule is used for managing base station information, wherein the base station information comprises binding and unbinding with personnel, and the base station information is added, modified and deleted according to a certain rule by a check sum when the base station information is added.
In one embodiment, the system management module includes, but is not limited to, a user management sub-module, a shop management sub-module, a floor management sub-module, and a behavior log sub-module.
It should be noted that the user management submodule is used for managing user information; specifically, the management of information of users who have permission to log in the UWB background management system in a shopping mall mainly comprises the steps of carrying out addition and deletion investigation on basic information of the users, wherein the steps of modifying a login password of a certain user and carrying out role distribution on the certain user are included; the search box above the list can input corresponding content for query, and clicking the reset button can quickly empty the content of the search box and display all users in the list.
It should be noted that the shop management submodule is used for performing addition, deletion, modification and check on the basic information of the shopping mall; specifically, basic information such as the category, location, and type of goods sold of the shop is included.
It should be noted that the floor management submodule is configured to add, delete, modify and check basic information of each floor of the mall; specifically, the page displays the information of each floor of the shopping mall in a tree structure chart and a list mode respectively.
It should be noted that the behavior log sub-module is configured to record a behavior of a user, and at the same time, includes functions of viewing, querying, deleting, exporting, clearing, and the like of a behavior log.
The map management module includes, but is not limited to, a mall information management sub-module and a map information management sub-module.
Specifically, the market information management submodule is used for performing addition, deletion, modification and check on market information; and the map information management submodule is used for carrying out addition, deletion, modification and check on the map information.
Furthermore, the map information management submodule mainly displays the specific floor of a shopping mall, the position of the shopping mall, the position of a customer, regional passenger flow statistics and the like; specifically, the operation notes: when a map is added and edited, the market name, the floor number, the shop name, the map width, the map length and the map origin cannot be empty, the map must be uploaded, the market name and the shop name cannot exceed 25 characters, and the floor number, the map width, the map length and the map origin must be numbers. During query, the input market name and shop name can not exceed 25 characters.
In combination with the above, the working principle of the passenger flow monitoring system is as follows:
the data acquisition layer 1 is a foundation for realizing indoor positioning of a 5G market, and is used for receiving and transmitting 5G signals and acquiring position data by installing a positioning micro base station and a 5G intelligent room subsystem (BBU, PB and PRRU) in the market and in the peripheral range, and transmitting the position data back to the MEC through a 5G network for storage, processing and use; the network connection layer 2 plays a role of an intermediate medium between the data acquisition layer 1 and the data calculation layer 3, namely the network connection layer 2 is used for rapidly transmitting acquired position data information to a database in the MEC cloud platform for storage and transmitting data by means of a 5G network; the data resolving layer 3 analyzes and processes the acquired position data information through a positioning algorithm, compares the position data in real time and provides the position data to the application layer 4; the application layer 4 can realize passenger flow volume statistics, monitoring and early warning for a shopping mall or a whole business district by using position data generated by communication equipment such as a customer mobile phone, and comprises a passenger flow statistics module, a passenger flow prediction module, a display management module, a system management module, a map management module, an early warning module and the like.
Further, the invention provides a passenger flow monitoring method based on the passenger flow monitoring system; specifically, the data acquisition layer 1 is responsible for acquiring data of the passenger flow position, transmitting the data to the server, analyzing the data by a positioning algorithm, and transmitting the data to the visual interface for real-time display.
As shown in fig. 10, in an embodiment, the passenger flow monitoring method implemented by the passenger flow monitoring system of the present invention includes the following steps:
step S1 is to acquire the position data information of the customer.
And step S2, analyzing and processing the position data information to realize passenger flow monitoring.
It should be noted that the protection scope of the passenger flow monitoring method according to the present invention is not limited to the execution sequence of the steps listed in this embodiment, and all the solutions implemented by adding, subtracting, and replacing steps in the prior art according to the principle of the present invention are included in the protection scope of the present invention.
It should be noted that the working principle of the passenger flow monitoring method is the same as that of the passenger flow monitoring system, and therefore, the detailed description thereof is omitted here.
In summary, compared with the prior art, the passenger flow monitoring system and method of the invention can accurately identify the position of the customer, count and monitor the passenger flow in a certain area range in the market, and conduct passenger flow dispersion in time when the passenger flow exceeds a certain limit value; according to the invention, the number of users and the peak time of people flow in any time period can be intelligently predicted according to historical data, so that the management and management efficiency is improved; therefore, the invention effectively overcomes various defects in the prior art and has high industrial utilization value.
The foregoing embodiments are merely illustrative of the principles and utilities of the present invention and are not intended to limit the invention. Any person skilled in the art can modify or change the above-mentioned embodiments without departing from the spirit and scope of the present invention. Accordingly, it is intended that all equivalent modifications or changes which can be made by those skilled in the art without departing from the spirit and technical spirit of the present invention be covered by the claims of the present invention.
Claims (9)
1. A passenger flow monitoring system, comprising: the system comprises a data acquisition layer, a network connection layer, a data resolving layer and an application layer;
the data acquisition layer is connected with the network connection layer and is used for acquiring position data information of a customer;
the network connection layer is connected with the data resolving layer and used for providing a network link so as to send the position data information to the data resolving layer;
the data resolving layer is connected with the application layer and used for analyzing and processing the position data information, resolving target position data and sending the target position data to the application layer so as to enable the application layer to realize passenger flow monitoring based on the target position data;
the application layer comprises: the system comprises a passenger flow statistics module, a passenger flow prediction module and an early warning module;
the passenger flow counting module is used for counting the number of people in the designated area in any time period and counting the number of people in the designated area in any time period;
the passenger flow prediction module is used for predicting the number of people in the designated area in the designated time period and predicting the number of people in the designated area in the designated time period;
the early warning module includes: a passenger flow volume early warning submodule and an emergency condition early warning submodule; wherein the content of the first and second substances,
the passenger flow early warning submodule is used for early warning passenger flow;
and the emergency condition early warning sub-module is used for giving an alarm when an emergency occurs in the shopping mall.
2. The passenger flow monitoring system of claim 1, wherein the data acquisition layer comprises: positioning a functional hardware unit and a 5G intelligent indoor distribution system; wherein the content of the first and second substances,
the positioning function hardware unit includes: positioning a micro base station and positioning a micro tag;
the positioning micro base station sends a request for acquiring the position data information to the positioning micro tag at intervals of preset time so as to monitor the position information of the positioning micro tag in real time;
and after receiving the request, the positioning micro tag sends the position data information to the positioning micro base station.
3. The passenger flow monitoring system of claim 2, wherein the target location data comprises: the position coordinates of the positioning micro-tag; the data resolving layer is used for analyzing and processing the position data information by utilizing a positioning algorithm and a ranging algorithm; wherein the content of the first and second substances,
the positioning algorithm adopts any one of the following algorithms: positioning algorithm based on arrival time, positioning algorithm based on arrival time difference and positioning algorithm based on arrival angle;
the distance measurement algorithm adopts a distance measurement method based on signal flight time, and the distance measurement method based on the signal flight time is realized in a bilateral two-way distance measurement mode.
4. The passenger flow monitoring system of claim 3, wherein the number of said positioning micro base stations is at least two; the angle-of-arrival-based positioning algorithm comprises the following steps:
selecting two positioning micro base stations from at least two positioning micro base stations as a first base station and a second base station respectively;
respectively acquiring a first angle between the reference line and a connecting line of the positioning micro tag and the first base station and a second angle between the reference line and a connecting line of the positioning micro tag and the second base station by taking the connecting line of the first base station and the second base station as reference lines;
positioning the position coordinates of the positioning micro-tag by using a triangulation method; the calculation formula of the position coordinates of the positioning micro-tag is as follows:
wherein the position coordinates of the positioning micro-tag are expressed as (x, y); (x)1，y1)、(x2，y2) Respectively representing the position coordinates of the two positioning micro base stations; theta1Representing the first angle; theta2Representing the second angle.
5. The passenger flow monitoring system of claim 3, wherein the number of said positioning micro base stations is at least three; the time-of-arrival based positioning algorithm comprises the following steps:
selecting three positioning micro base stations from at least three positioning micro base stations;
acquiring the time when each positioning micro base station receives the positioning micro label sending signal;
acquiring the position coordinates of the positioning micro-label based on the positioning micro-base station and the time; the calculation formula of the position coordinates of the positioning micro-tag is as follows:
the positioning algorithm based on the arrival time difference comprises the following steps:
selecting three positioning micro base stations from at least three positioning micro base stations;
obtaining the distance from each positioning micro base station to the positioning micro tag;
acquiring the position coordinates of the positioning micro-label based on the positioning micro-base station and the distance; the calculation formula of the position coordinates of the positioning micro-tag is as follows:
wherein the position coordinates of the positioning micro-tag are expressed as (x, y); the position coordinate of the nth positioning micro base station is expressed as (x)n，yn)；tnThe time that the positioning micro-tag transmits a signal at the time t and the nth positioning micro base station receives the signal transmitted by the positioning micro-tag is represented; c represents the speed of light; d％Representing the distance from the nth positioning micro base station to the positioning micro label; n is 1, 2, 3.
6. The passenger flow monitoring system according to claim 5, wherein the distance from each of the positioning micro base stations to the positioning micro tag is obtained by the time difference of arrival of signals of two different propagation speeds, or the time difference of arrival of the same signal at different nodes.
7. The passenger flow monitoring system of claim 1, wherein the application layer further comprises: the system comprises a display management module, a system management module and a map management module;
the display management module includes: a display submodule and a base station submodule; wherein the content of the first and second substances,
the display sub-module is used for displaying a shopping mall map and positioning the positions of the labels, the base stations and the passenger flow on the shopping mall map in real time;
the base station submodule is used for managing base station information;
the system management module comprises: the system comprises a user management submodule, a shop management submodule, a floor management submodule and a behavior log submodule; wherein the content of the first and second substances,
the user management submodule is used for managing user information;
the shop management submodule is used for carrying out addition, deletion, modification and check on the basic information of the shopping mall;
the floor management submodule is used for carrying out addition, deletion, modification and check on the basic information of each floor of the shopping mall;
the behavior log submodule is used for recording the behavior of the user; the map management module includes: a market information management submodule and a map information management submodule; wherein the content of the first and second substances,
the market information management submodule is used for carrying out addition, deletion, modification and check on market information;
and the map information management submodule is used for carrying out addition, deletion, modification and check on the map information.
8. The passenger flow monitoring system according to claim 1, wherein the communication mode of the network connection layer comprises any one or a combination of the following: 5G, Bluetooth and ZigBee.
9. A passenger flow monitoring method implemented with a passenger flow monitoring system according to any one of claims 1 to 8, characterized by comprising the steps of:
acquiring position data information of a customer;
and analyzing and processing the position data information to realize passenger flow monitoring.
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