CN109727175A - A kind of tourist attraction flow monitoring system for passenger - Google Patents
A kind of tourist attraction flow monitoring system for passenger Download PDFInfo
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- CN109727175A CN109727175A CN201811593967.XA CN201811593967A CN109727175A CN 109727175 A CN109727175 A CN 109727175A CN 201811593967 A CN201811593967 A CN 201811593967A CN 109727175 A CN109727175 A CN 109727175A
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Abstract
The invention discloses a kind of tourist attraction flow monitoring system for passenger, and the system comprises information acquisition module, communication module and passenger flow monitoring modulars；The information acquisition module, for tourist's mobile phone in timing acquiring scenic spot Mac information and summarize；The communication module, the information for summarizing information acquisition module are sent to passenger flow monitoring modular；The passenger flow monitoring modular obtains volume of the flow of passengers data for carrying out class statistic analysis to received information in fixed time period；Realize the presentation of passenger flow heating power and early warning.System of the invention can acquire the essential information of tourist, and tourist attraction passenger flow real-time dynamic monitoring and early warning may be implemented.
Description
Technical field
The present invention relates to tourist attraction management domains, and in particular to a kind of tourist attraction flow monitoring system for passenger.
Background technique
With the rapid development of our country's economy, tourism and leisure has become the main trip mode of people, tourist attraction tourist
Increasing, especially golden week, winter and summer vacation, tourist's Relatively centralized bring serious test to tourist attraction safety management.In real time
Tourist's current intelligence and administrative staff present position are monitored, prevents the generation of swarm and jostlement event, timely early warning is simultaneously effectively disposed
Emergency event ensures tourist itself and tourist attraction safety conscientiously, it is horizontal to promote park management, it has also become tourist attraction management department
The problem of door is paid close attention to.
Currently, tourist attraction passenger flow statistics mostly use the technologies such as intelligent video analysis and infrared thermal imaging, deployed with devices
Mainly in the ticketing spot of tourist attraction, important entrance and key area, realize to the statistics of tourist's number and density of personnel into
Row monitoring.
Tourist attraction passenger flow statistics and scenic spot visitor can be effectively realized using technologies such as intelligent video analysis and infrared thermal imagings
It flows heating power to present, but tourist's essential information cannot be acquired, such as track, hobby information, be not easy to realize that tourist is personalized precisely
Service.
Summary of the invention
It is big it is an object of the invention to solve tourist attraction passenger flow personnel's flow, it is tourist attraction bring security risk
Problem proposes a kind of using tourist's flow monitoring system for passenger based on Wi-Fi probe.
To achieve the goals above, the invention proposes a kind of tourist attraction flow monitoring system for passenger, the system comprises letters
Cease acquisition module, communication module and passenger flow monitoring modular；
The information acquisition module, for tourist's mobile phone in timing acquiring scenic spot Mac information and summarize；
The communication module, the information for summarizing information acquisition module are sent to passenger flow monitoring modular；
The passenger flow monitoring modular is obtained for carrying out class statistic analysis to received information in fixed time period
To volume of the flow of passengers data；Realize the presentation of passenger flow heating power and early warning.
As a kind of improvement of above system, the information acquisition module include: several Wi-Fi probes, interchanger and
Aggregation engine；
The Wi-Fi probe, is deployed in scenic spot, for acquiring the address tourist smart phone Mac, position and time, and
The distance of probe and tourist is calculated according to the position of itself；By the address tourist smart phone Mac, away from discrete time composition data packet
It is sent；
The interchanger for connecting all Wi-Fi probes, and is connected through the internet to aggregation engine；
The aggregation engine, the data packet for sending to all Wi-Fi probes summarize.
As a kind of improvement of above system, the deployment of the Wi-Fi probe the following steps are included:
Step S1) subregion is carried out to tourist attraction, obtain N number of scenic spot subregion；
In required tourist attraction, according to scenic spot resources spatial distribution and all kinds of facility layout features, to tourist attraction
Carry out classified zoning: classical scenic spot, hot spot scenic spot and general scenic spot；Classical scenic spot is defined as a kind of scenic spot, and belonging to tourist must swim
Look at scenic spot；Hot spot scenic spot is defined as two class scenic spots, belongs to tourist scenic spot of interest；General scenic spot is defined as three classes scenic spot, belongs to
In the scenic spot that tourist less pays close attention to；
Step S2) detection range according to the scenic spot subregion gross area and Wi-Fi probe, calculate the deployment of each scenic spot subregion
The quantity of Wi-Fi probe；
The Wi-Fi probe of i-th of scenic spot subregion lays quantity DiAre as follows:
Di=Ai/πr2
Wherein: AiFor i-th of scenic spot subregion gross area；R is Wi-Fi probe radius of investigation distance；A kind of scenic spot: r=20
Rice；Two class scenic spots: r=30 meters；Three classes scenic spot: r=50 meters.
As a kind of improvement of above system, the communication module is scenic spot Intranet.
As a kind of improvement of above system, the passenger flow monitoring modular includes class statistic unit, the presentation of passenger flow heating power
Unit and passenger flow heating power prewarning unit；
The packet statistics of the class statistic unit, all Wi-Fi probes for being sent using aggregation engine are each
The real-time volume of the flow of passengers of scenic spot subregion, and made up the difference using user's Mac data probability and to correct the real-time volume of the flow of passengers and obtain passenger flow heating power data；
Passenger flow heating power display unit forms the passenger flow heat of scenic spot subregion for the passenger flow heating power data according to scenic spot subregion
Power and ownership place histogram；
Passenger flow heating power prewarning unit, for comparing the passenger flow heating power data of each scenic spot subregion and 5 level thresholds
Compared with judging 5 states of the passenger flow bearing capacity of scenic spot subregion: rationally, tolerable, early warning, alarm and promptly；To needing early warning
State issues real-time early warning information.
As a kind of improvement of above system, the packet statistics scape of the Wi-Fi probe sent using aggregation engine
The real-time volume of the flow of passengers in area is distinguished, specifically:
All Wi-Fi probes that statistics sends the Mac address date packet comprising tourist p find distance using nearest strategy
The smallest Wi-Fi probe deletes the address Mac of tourist p in other Wi-Fi probes.
As a kind of improvement of above system, described made up the difference using user Mac data probability corrects the real-time volume of the flow of passengers, specifically
Are as follows:
The real-time volume of the flow of passengers T of i-th of scenic spot subregioniAre as follows:
Ti=STi+STi×λi
Wherein, STiFor the real-time volume of the flow of passengers of i-th of scenic spot subregion, λiFor passenger flow data coefficient.
As a kind of improvement of above system, 5 level thresholds include: level-one threshold value, secondary threshold, three-level threshold
Value, level Four threshold value and Pyatyi threshold value；The level-one threshold value is the maximum passenger flow bearing capacity C of scenic spot subregioni；The secondary threshold is
Maximum bearing capacity Ci× 20%, the three-level threshold value is the C of maximum bearing capacityi× 40%, the level Four threshold value is maximum bearing capacity
Ci× 60% Pyatyi threshold value is the C of maximum bearing capacityi× 80%；
The maximum passenger flow bearing capacity C of i-th of scenic spot subregioniAre as follows:
Ci=(ri+li+gi)/yi
Wherein: riFor the area of the pedestrian walkway of i-th of scenic spot subregion, liFor the face idly of i-th of scenic spot subregion
Product, giFor the area of the interior space of i-th of scenic spot subregion；yiFor area, y can be accounted for per capitai=2m2/ people；1≤i≤N.
Present invention has an advantage that
The real-time monitoring and statistics of tourist's passenger flow not only may be implemented in system of the invention, but also can acquire the base of tourist
This information, to realize the real-time dynamic early-warning of tourist attraction passenger flow.
Detailed description of the invention
Fig. 1 is the schematic diagram that class statistic of the invention is analyzed；
Fig. 2 is the schematic diagram of acquisition information flow of the invention；
Fig. 3 is the frame diagram of tourist attraction flow monitoring system for passenger of the invention.
Specific embodiment
The present invention will be described in detail in the following with reference to the drawings and specific embodiments.
As shown in Figure 1, system framework is by system administration and spy the present invention provides a kind of tourist attraction flow monitoring system for passenger
Needle information collection two parts composition
(1) system administration: it is divided into: application layer, service layer, data Layer and information network basal layer composition.
Application layer: passenger flow monitoring modular is mainly dredged and prediction scheme pipe by heating power presentation, information publication, passenger flow early warning, passenger flow
The application modules such as reason composition.
Service layer: it is mainly made of middlewares such as database access, transaction monitor and Tomcat.
Data Layer: it is mainly made of system database and corresponding service software.
Information network basal layer: it is mainly made of internet, mobile Internet and scenic spot Intranet etc..
(2) detecting probe information acquires
Mainly it is made of acquisition converging information engine, interchanger and several Wi-Fi probes.
Wherein, the deployment of Wi-Fi probe is the following steps are included: first is that divide tourist attraction subregion, and calculating scenic spot passenger flow is most
Big bearing capacity.Second is that acquiring passenger flow information in real time using Wi-Fi probe technique.According to scenic spot subregion and Wi-Fi probe detection away from
From in the seamless laying Wi-Fi probe in scenic spot.Specifically:
Step S1) tourist attraction subregion.
In required tourist attraction, according to scenic spot resources spatial distribution and all kinds of facility layout features, to tourist attraction
Carry out classified zoning.The purpose of classified zoning is easy for the passenger flow of each subregion of monitoring and statistics, predicts the passenger flow situation at scenic spot.Point
The principle of class subregion are as follows: classical scenic spot, hot spot scenic spot and general scenic spot.
Classical scenic spot is defined as a kind of scenic spot, belongs to classical scenic spot, and tourist must go sight-seeing scenic spot；Hot spot scenic spot is defined as two classes
Scenic spot belongs to tourist scenic spot of interest；General scenic spot is defined as three classes scenic spot, belongs to the scenic spot that tourist less pays close attention to.
Step S2) calculating of scenic spot subregion passenger flow maximum bearing capacity.
According to " scenic spot maximum bearing capacity appraises and decides directive/guide ", region is effectively gone sight-seeing in the region that tourist can walk in garden,
The volume of the flow of passengers that visit region can carry is exactly bearing capacity namely pavement and vacant lot, and the indices of scenic spot bearing capacity are arranged,
Calculate piecemeal scenic spot resource space maximum bearing capacity.Tourist's bearing capacity classification are as follows: rationally, tolerable, early warning, alarm and promptly
Deng.
Scenic spot maximum passenger flow bearing capacity measuring and calculating: Basis are as follows: the scenic spot gross area, pedestrian walkway, idly (including the water surface
Deng), the interior space (including in landscape room, shop, food and drink, toilet etc.), area etc. can be accounted for per capita.
According to " scenic spot maximum bearing capacity appraises and decides directive/guide ", occupied area is 1-3m per capita at the national scenic spot 5A grades of2/ people, carrying
Amount calculates can be by 2m2/ people calculates.
Bearing capacity are as follows:
Ci=(ri+li+gi)/yi
Wherein: CiFor the passenger flow maximum bearing capacity of i-th of scenic spot subregion, riFor the face of the pedestrian walkway of i-th of scenic spot subregion
Product, liFor the area idly of i-th of scenic spot subregion, giFor the area of the interior space of i-th of scenic spot subregion；
Step S3) scenic spot subregion Wi-Fi probe deployment and information collection.
According to scenic spot subregion, several Wi-Fi probes are laid, Mac data is acquired in real time, is stored in space after handling data
Database.
Scenic spot subregion Wi-Fi probe uses seamless laying, lays principle are as follows: first is that according to the subregion gross area；Second is that foundation
Scenic spot maximum passenger flow bearing capacity；Third is that the detection range according to Wi-Fi probe.To acquire and precisely counting passenger flow information comprehensively,
For a kind of scenic spot, Wi-Fi probe detection range is defined as 20 meters of radius；Two class scenic spot Wi-Fi probe detection ranges are defined as
30 meters of radius；Three classes scenic spot Wi-Fi probe detection range is defined as 50 meters of radius.Wi-Fi number of probes is calculated, in practical cloth
If middle according to scenic spot scene appropriate adjustment and increase and decrease.
Scenic spot Wi-Fi probe lays quantity are as follows:
Di=Ai/πr2
Wherein: AiFor i-th of scenic spot subregion gross area；R is Wi-Fi probe radius of investigation distance；A kind of scenic spot: r=20
Rice；Two class scenic spots: r=30 meters；Three classes scenic spot: r=50 meters.
Passenger flow monitoring modular includes class statistic unit, passenger flow heating power display unit, passenger flow heating power prewarning unit；
The class statistic unit, the data packet of the Wi-Fi probe for being sent using aggregation engine count scenic spot subregion
The real-time volume of the flow of passengers, and made up the difference using user's Mac data probability and to correct the real-time volume of the flow of passengers and obtain the volume of the flow of passengers, while counting the spy
The user Mac quantity of needle acquisition information and corresponding ownership place；
Collecting flowchart is as shown in Figure 3；
Relative distance, the acquisition time of main the acquisition address tourist's smart phone Mac and probe, pass through the address tourist Mac
Tourist's mobile phone ownership place etc. is matched, scenic spot volume of the flow of passengers class statistic is carried out.
Wi-Fi probe collection information is as shown in table 1, it is main acquire the address tourist's smart phone Mac, with probe it is opposite away from
From, acquisition time, pass through tourist's Mac address matching tourist's mobile phone ownership place.
Table 1
Wi-Fi probe collection informational strategy: first is that it is primary to define acquisition in Wi-Fi probe every 30 seconds；Second is that acquisition is complete
Portion's user's Mac initial data is stored in spatial database；Third is that carrying out within every 10 minutes a class statistic analysis, corresponding scenic spot is formed
Passenger flow heating power and ownership place data.
Using scenic spot as statistical analysis unit, the Mac of certain tourist p may be by multiple Wi-Fi probe collections, in class statistic
Using nearest strategy, first the probe collection and distance of reconnaissance probe to p point, the nearest probe of distance p point is found, p is included in most
In close probe, at the same in other probes delete p point mac, while count the probe collection information user Mac quantity and
Corresponding ownership place, as shown in Figure 3.
P1, p3, p6 are respectively that probe 1,3,2 detects, and will be respectively present in probe 1,3,2；P4 is detected by probe 1 and 2
It arrives, is incorporated into probe 1 according to right algorithm is schemed, while deleting the p4 in probe 2；Similarly, p2 is incorporated to probe 2, deletes probe 3
In p2, p5 is incorporated in probe 1, deletes the p2 in probe 3.
User's Mac data probability is made up the difference: Wi-Fi probe collection user's Mac data, user's Wi-Fi function necessarily are in out
It opens state, therefore acquires user Mac data and have omissions, the present invention is made up the difference mode using probability, and the probability for providing certain scenic spot is objective
Flow data.According to the maximum bearing capacity in scenic spot day and instantaneous maximum bearing capacity, scenic spot historical data is statisticallyd analyze, the same period compares related
Data show that corresponding probability is made up the difference weight coefficient, obtains real-time passenger flow data, although the data have error, are used for scenic spot
Passenger flow monitoring and statistics and early warning can meet application requirement.It is specific to calculate such as:
Ti=STi+STi×λi
Wherein, TiFor the volume of the flow of passengers of i-th of scenic spot subregion, STiFor the real-time volume of the flow of passengers of i-th of scenic spot subregion, λiFor passenger flow
Data coefficient.
Passenger flow heating power display unit forms the passenger flow heat of scenic spot subregion for the passenger flow heating power data according to scenic spot subregion
Power and ownership place histogram；According to the tourist's cluster data formed, passenger flow heating power data is formed, is in chromaticity diagram and digital form
It is existing.Passenger flow heating power data and scenic spot maximum bearing capacity data are compared in real time, if passenger flow heating power data is more than or equal to maximum bearing capacity,
Then Realtime Alerts, system are disposed by instant video communication modes.Foundation tourist Mac cluster data and ownership place data,
Divide scenic spot passenger flow heating power and ownership place histogram based on tourist attraction formation.
Passenger flow heating power prewarning unit according to scenic spot area, can go sight-seeing area, per capita occupied area and maximum bearing capacity, meter
The reasonable bearing capacity of scenic spot passenger flow is calculated, scenic spot passenger flow is defined as and is carried as level-one threshold value, is reported according to the emergency at related scenic spot, works as trip
20% of objective number more than reasonable bearing capacity is defined as secondary threshold, is tolerable situation.As shown in table 2, the present invention sets threshold value
It is set to 5 ranks: rationally, tolerable, early warning, alarm, urgent.And so on, three-level threshold value is the C of maximum bearing capacityi×
40%, level Four threshold value is the C of maximum bearing capacityi× 60%, Pyatyi threshold value is the C of maximum bearing capacityi× 80%.If threshold value reaches
To being more than the 80% of reasonable bearing capacity, tourist is excessive, and the situation is critical, needs emergency action, evacuates tourist and limits into scenic spot people
Number.
Table 2
It should be noted last that the above examples are only used to illustrate the technical scheme of the present invention and are not limiting.Although ginseng
It is described the invention in detail according to embodiment, those skilled in the art should understand that, to technical side of the invention
Case is modified or replaced equivalently, and without departure from the spirit and scope of technical solution of the present invention, should all be covered in the present invention
Scope of the claims in.
Claims (8)
1. a kind of tourist attraction flow monitoring system for passenger, which is characterized in that the system comprises information acquisition module, communication module and
Passenger flow monitoring modular；
The information acquisition module, for tourist's mobile phone in timing acquiring scenic spot Mac information and summarize；
The communication module, the information for summarizing information acquisition module are sent to passenger flow monitoring modular；
The passenger flow monitoring modular obtains visitor for carrying out class statistic analysis to received information in fixed time period
Data on flows；Realize the presentation of passenger flow heating power and early warning.
2. tourist attraction flow monitoring system for passenger according to claim 1, which is characterized in that the information acquisition module packet
It includes: several Wi-Fi probe, interchanger and aggregation engines；
The Wi-Fi probe, is deployed in scenic spot, for acquiring the address tourist smart phone Mac, position and time, and according to
The position of itself calculates the distance of probe and tourist；It is carried out by the address tourist smart phone Mac, away from discrete time composition data packet
It sends；
The interchanger for connecting all Wi-Fi probes, and is connected through the internet to aggregation engine；
The aggregation engine, the data packet for sending to all Wi-Fi probes summarize.
3. tourist attraction flow monitoring system for passenger according to claim 2, which is characterized in that the deployment of the Wi-Fi probe
The following steps are included:
Step S1) subregion is carried out to tourist attraction, obtain N number of scenic spot subregion；
In required tourist attraction, according to scenic spot resources spatial distribution and all kinds of facility layout features, tourist attraction is carried out
Classified zoning: classical scenic spot, hot spot scenic spot and general scenic spot；Classical scenic spot is defined as a kind of scenic spot, and scape must be gone sight-seeing by belonging to tourist
Area；Hot spot scenic spot is defined as two class scenic spots, belongs to tourist scenic spot of interest；General scenic spot is defined as three classes scenic spot, belongs to trip
The scenic spot that visitor less pays close attention to；
Step S2) detection range according to the scenic spot subregion gross area and Wi-Fi probe, calculate the Wi- of each scenic spot subregion deployment
The quantity of Fi probe；
The Wi-Fi probe of i-th of scenic spot subregion lays quantity DiAre as follows:
Di=Ai/πr2
Wherein: AiFor i-th of scenic spot subregion gross area；R is Wi-Fi probe radius of investigation distance；A kind of scenic spot: r=20 meters；Two
Class scenic spot: r=30 meters；Three classes scenic spot: r=50 meters.
4. tourist attraction flow monitoring system for passenger according to claim 1, which is characterized in that the communication module is in scenic spot
Net.
5. tourist attraction flow monitoring system for passenger according to claim 3, which is characterized in that the passenger flow monitoring modular includes
Class statistic unit, passenger flow heating power display unit and passenger flow heating power prewarning unit；
The class statistic unit, each scenic spot of packet statistics of all Wi-Fi probes for being sent using aggregation engine
The real-time volume of the flow of passengers of subregion, and made up the difference using user's Mac data probability and to correct the real-time volume of the flow of passengers and obtain passenger flow heating power data；
Passenger flow heating power display unit, for according to scenic spot subregion passenger flow heating power data, formed scenic spot subregion passenger flow heating power and
Ownership place histogram；
Passenger flow heating power prewarning unit is sentenced for the passenger flow heating power data of each scenic spot subregion to be compared with 5 level thresholds
5 states of the passenger flow bearing capacity of disconnected scenic spot subregion: rationally, tolerable, early warning, alarm and promptly；To the state for needing early warning
Issue real-time early warning information.
6. tourist attraction flow monitoring system for passenger according to claim 5, which is characterized in that described to be sent using aggregation engine
Wi-Fi probe packet statistics scenic spot subregion the real-time volume of the flow of passengers, specifically:
Statistics sends all Wi-Fi probes of the Mac address date packet comprising tourist p, and using nearest strategy, it is minimum to find distance
Wi-Fi probe, delete the address Mac of tourist p in other Wi-Fi probes.
7. tourist attraction flow monitoring system for passenger according to claim 5, which is characterized in that described to utilize user Mac data
Probability, which is made up the difference, corrects the real-time volume of the flow of passengers, specifically:
The real-time volume of the flow of passengers T of i-th of scenic spot subregioniAre as follows:
Ti=STi+STi×λi
Wherein, STiFor the real-time volume of the flow of passengers of i-th of scenic spot subregion, λiFor passenger flow data coefficient.
8. tourist attraction passenger flow monitoring and statistics system according to claim 3, which is characterized in that 5 level thresholds
It include: level-one threshold value, secondary threshold, three-level threshold value, level Four threshold value and Pyatyi threshold value；The level-one threshold value be scenic spot subregion most
Large passenger flow bearing capacity Ci；The secondary threshold is maximum bearing capacity Ci× 20%, the three-level threshold value is the C of maximum bearing capacityi×
40%, the level Four threshold value is the C of maximum bearing capacityi× 60% Pyatyi threshold value is the C of maximum bearing capacityi× 80%, step
S2 the maximum passenger flow bearing capacity of each scenic spot subregion) is calculated；
The maximum passenger flow bearing capacity C of i-th of scenic spot subregioniAre as follows:
Ci=(ri+li+gi)/yi
Wherein: riFor the area of the pedestrian walkway of i-th of scenic spot subregion, liFor the area idly of i-th of scenic spot subregion, gi
For the area of the interior space of i-th of scenic spot subregion；yiFor area, y can be accounted for per capitai=2m2/ people；1≤i≤N.
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| CN114547228B (en) * | 2022-04-22 | 2022-07-19 | 阿里云计算有限公司 | Track generation method, device, equipment and storage medium |
| CN115204678A (en) * | 2022-07-14 | 2022-10-18 | 奕资武汉商务咨询有限公司 | Tourist evaluation and analysis system based on scenic spot tourism platform |
| CN115204678B (en) * | 2022-07-14 | 2024-02-09 | 贵州全域旅游产业科技有限责任公司 | Tourist evaluation analysis system based on scenic spot tourist platform |
| CN117313923A (en) * | 2023-09-14 | 2023-12-29 | 青岛大数据科技发展有限公司 | Scenic spot passenger flow prediction method, scenic spot passenger flow prediction system, storage medium and electronic equipment |
| CN117314119A (en) * | 2023-11-07 | 2023-12-29 | 北京凯泰铭科技文化发展有限公司 | Precise online real-time analysis system based on number of tourists in universe and scenic spot |
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