CN112215572A - Intelligent park saturation analysis model - Google Patents
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Abstract
The invention discloses an intelligent park saturation analysis model, which comprises the following steps: obtaining the total order placing amount X0-X24 of each time interval through the ticketing platform, subtracting two adjacent time intervals, and obtaining the order placing amount of the ticketing platform of each time interval through the formula, wherein the increment y is X3-X2; after the user finishes placing the order, entering the garden through the gate, verifying the number of tickets through the gate, and monitoring the number Z of people entering the garden in the period of time, wherein the number Z is Z0-Z24; tourists get out of the garden through the rolling gate, the gate can report the number of people getting out of the garden, and each time node can count the total number o getting out of the garden in the scenic spot, so that the number i of people in the garden in each time period of the scenic spot is z-o, and the obtained value i is the total number of the tourists in the garden in the scenic spot in each time period; the total X24 may map the daily inventory for the scenic spot throughout the year, from which the inventory and number of visitors for the scenic spot today in the next year may be estimated. The intelligent park saturation degree analysis method has the advantages that an intelligent park saturation degree analysis model is established, and the management method for improving the management efficiency of the park is convenient to analyze.
Description
Technical Field
The invention relates to the technical field of park operation management, in particular to an intelligent park saturation analysis model.
Background
The intelligent scenic spot is characterized in that the intelligent scenic spot comprehensively, thoroughly and timely senses geographical objects, natural resources, tourist behaviors, scenic spot worker trails, scenic spot infrastructure and service facilities of the scenic spot through an intelligent network; visual management is realized for tourists and scenic spot workers; forming a strategic alliance with upstream and downstream enterprises in the travel industry; and comprehensive, coordinated and sustainable development of environment, society and economy in scenic spots is realized.
The generalized intelligent scenic spot refers to a low-carbon intelligent operation scenic spot which is highly integrated by scientific management theory and modern information technology and realizes harmonious development of human and nature. The ecological environment can be more effectively protected, better service is provided for tourists, and greater value is created for the society. The narrow intelligent scenic spot is the perfection and the upgrade of a digital scenic spot, and means that visual management and intelligent operation can be realized, and the three aspects of environment, society and economy can be more thoroughly perceived, and the scenic spot is more extensive in interconnection and deeper in intelligence. The narrow sense of "intelligent scenic spot" emphasizes technical factors, and the broad sense of "intelligent scenic spot" emphasizes not only technical factors but also management factors.
The management of the existing park is mainly based on manual management, but the manual management firstly has high labor intensity, secondly has slow response speed, and finally has poor management effect, so that the management efficiency of the park is reduced, and therefore, the establishment of the intelligent park saturation analysis model has important practical significance and engineering significance for the management efficiency of the park.
Disclosure of Invention
The invention aims to provide a smart park saturation analysis model, which has the advantages of establishing the smart park saturation analysis model and facilitating the analysis of a management method for improving the management efficiency of a park, and solves the problems that the existing management of the park is mainly based on manual management, but the manual management firstly has high labor intensity, secondly has slow response speed and finally has poor management effect and further reduces the management efficiency of the park, so the establishment of the smart park saturation analysis model has important practical significance and engineering significance for the management efficiency of the park.
In order to achieve the purpose, the invention provides the following technical scheme: wisdom garden saturation analysis model includes the following steps:
s1, acquiring the total order placing amount X0-X24 of each time interval through the ticketing platform, and subtracting the two adjacent time intervals, wherein the order placing amount of the ticketing platform of each time interval can be obtained through the formula, for example, the increment y is X3-X2;
s2, after the user finishes placing the order, entering the garden through the gate, verifying the number of tickets through the gate, and monitoring the number Z of people entering the garden at the time, wherein the number Z is Z0-Z24;
s3, the tourists get out of the garden through the rolling gate, the gate reports the number of the tourists, and each time node can count the total number o of the tourists out of the garden in the scenic spot, so that the number i of the tourists in the garden in each time period of the scenic spot is z-o, and the obtained value i is the total number of the tourists in the scenic spot in each time period;
s4, the total amount X24 can be used for drawing the daily inventory of the scenic spot all the year around, and through the data, the inventory and the number of visitors in the scenic spot at the next year can be estimated.
Preferably, X0-X24 is 0-24.
Preferably, in the step S1, the increment y value of each time interval is the largest, that is, the current ordering concurrency peak value is obtained, and the ordering total number X24 can be used to obtain the ordering total number in the current park.
Preferably, the Z value is a total number, including the number of people who have previously entered the garden.
Preferably, the total number of scenic spots entering the garden per time period ranges from 0 to 24 in Z0-Z24.
Preferably, assuming that the saturation number of the scenic spot is s, when i is less than or equal to 80% s, the tourists are in a comfortable state without early warning; when i is more than 80% s and less than 100% s, the tourists are in a crowded state, and the early warning manager controls the tourists to place the order in the period and guides the tourists to place the order in the next period; when i is larger than 100% s, the scenic spot is in an overload state, the early warning manager closes the time interval platform and places orders, and the staff controls the number of visitors entering the scenic spot.
Compared with the prior art, the invention has the beneficial effects that: the number of people in the scenic spot is calculated by calculating data such as the number of single under the ticketing system, the actual ticket checking number of the scenic spot gate, the actual number of people out of the garden of the scenic spot gate and the like, the number of people in the scenic spot is calculated, the number of people loaded in the scenic spot is obtained, the saturation of the scenic spot in the period of time is analyzed to be used as a data base, the number and the saturation of visitors in the scenic spot in the holiday in the next year are analyzed to evaluate whether the capacity of the scenic spot is improved or not, the number of people entering the garden in the period of placing the ticket and the period of time is controlled, and the orders.
Drawings
Figure 1 is a block diagram of the park saturation analysis model framework of the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
In the description of the present invention, it should be noted that the terms "upper", "lower", "inner", "outer", "front", "rear", "both ends", "one end", "the other end", and the like indicate orientations or positional relationships based on those shown in the drawings, and are only for convenience of description and simplicity of description, but do not indicate or imply that the referred device or element must have a specific orientation, be constructed in a specific orientation, and be operated, and thus, should not be construed as limiting the present invention. Furthermore, the terms "first" and "second" are used for descriptive purposes only and are not to be construed as indicating or implying relative importance.
In the description of the present invention, it is to be noted that, unless otherwise explicitly specified or limited, the terms "mounted," "disposed," "connected," and the like are to be construed broadly, such as "connected," which may be fixedly connected, detachably connected, or integrally connected; can be mechanically or electrically connected; they may be connected directly or indirectly through intervening media, or they may be interconnected between two elements. The specific meanings of the above terms in the present invention can be understood in specific cases to those skilled in the art.
The invention provides a technical scheme of an intelligent park saturation analysis model
Example 1:
wisdom garden saturation analysis model includes the following steps:
s1, obtaining the total number of orders to be placed in each time period X0-X24 through the ticketing platform, subtracting two adjacent time periods, for example, the increment y is X3-X2, obtaining the total number of orders to be placed in each time period through the formula, obtaining the total number of orders to be placed in the garden of today when X0-X24 is 0-24, obtaining the maximum value of y through the increment y value of each time period, namely the peak value of the concurrency of orders to be placed of today, and obtaining the total number of orders to be placed in the garden of today through the total number of orders to be placed X24.
S2, after the user finishes placing the order, the user enters the garden through the gate, the gate verifies the number of the tickets to monitor the number Z of people entering the garden in the time period, the number Z of people entering the garden is Z0-Z24, the value Z is the total number and comprises the number of people who enter the garden before, and the total number of people entering the garden in the scenic spot in each time period is Z0-Z24 is 0-24.
S3, visitors leave the garden through the rolling gate, the gate can report the number of the visitors, each time node can count the total number o of the visitors leaving the garden in each time period, so that the number i of the visitors in the garden in each time period is z-o, the obtained value i is the total number of the visitors in the garden in each time period, the number of the saturation degrees of the scenic area is assumed to be S, and when i is less than or equal to 80% S, the visitors are in a comfortable state without early warning; when i is more than 80% s and less than 100% s, the tourists are in a crowded state, and the early warning manager controls the tourists to place the order in the period and guides the tourists to place the order in the next period; when i is larger than 100% s, the scenic spot is in an overload state, the early warning manager closes the time interval platform and places orders, and the staff controls the number of visitors entering the scenic spot.
S4 and total X24 can draw daily sales volume of the scenic spot all the year round, sales volume and number of tourists of the scenic spot at the next year can be estimated through the data, the number of people in the scenic spot at the next year round is calculated through calculating data such as the number of single sales of a ticketing system, the actual ticket checking number of scenic spot gates, the actual number of people going out of the scenic spot gates and the like, the number of people in the scenic spot is calculated, the number of people in the scenic spot at the next year round is obtained, the saturation of the scenic spot at the time is analyzed to serve as a data base, the number and the saturation of tourists in the scenic spot at the next year are analyzed, whether the capacity of the scenic spot is improved or not is evaluated, the number of people going into the scenic spot at the time of sales at the sales period and each.
The number of orders placed in the scenic spot today can be known through the total number of orders placed X24; the increment Y can know the single peak value, namely the interval, under the platform; the number of people in the garden i can know the saturation state of the scenic spot in each time period, the number of people in the garden i is x3-x2, the number of people in the garden i is z-o, the saturation s, the number of signed platform scenes n, and the number of y n is the concurrency amount of the bills under each time period of the platform, and compared with the maximum concurrency amount of the platform, whether a network communication vehicle needs to be added to ensure the stability of the bills under the platform; through being in at the time length of crowded and overload of garden person number i, scenic spot managers can improve scenic spot load, improves the scenic spot load volume and improves visitor's comfort level.
Example 2:
and S1, acquiring the order placing quantity of the 5.1 day ticket payment platform, counting the order placing quantity in each time period, taking hours as units, and comprehensively obtaining the total order placing data of the whole day.
And S2, constructing a model by the obtained data, analyzing the peak value and the ordering trend of the day, and whether server construction and time-sharing ordering are needed or not, staggering ordering people flow and reasonably distributing scenic spot network resources.
S3, after placing an order, acquiring the number of entering the garden and the number of leaving the garden of each time period of the gate, the total number of entering the garden and the total number of leaving the garden of a single day, analyzing the saturation degree of the scenic spot, analyzing whether the number of people in the scenic spot exceeds the comfortable bearing degree of the scenic spot, suggesting and early warning the scenic spot to perform time-sharing entering of the garden and time control of tourists in the garden, or improving effective suggestions such as the capacity of the scenic spot.
S4, drawing a trend chart of the coming and going in and out of the garden on the day of the scenic spot 5.1 according to actual coming and going in and out data of the scenic spot, analyzing peak values of the coming and going in and out of the garden, and judging whether suggestions such as a manual guiding mode of the scenic spot are needed or not, so that the carrying speed of the scenic spot is improved.
The data can be used for obtaining 5.1-5.3 days of overall data and corresponding data trends, evaluating the data and saturation of the scenic spot of the overall holiday, analyzing the peak time and duration of the scenic spot of the holiday in the next year, and deploying in advance. Effective suggestions for time-sharing reservation, time-sharing ordering, time-sharing park entry and the like can be provided to shunt peak data. And the timely and effective ordering can be ensured by deploying the communication signal vehicle, and the ordering sales volume and the ordering peak value of the ticketing system are improved.
It will be evident to those skilled in the art that the invention is not limited to the details of the foregoing illustrative embodiments, and that the present invention may be embodied in other specific forms without departing from the spirit or essential attributes thereof. The present embodiments are therefore to be considered in all respects as illustrative and not restrictive, the scope of the invention being indicated by the appended claims rather than by the foregoing description, and all changes which come within the meaning and range of equivalency of the claims are therefore intended to be embraced therein. Any reference sign in a claim should not be construed as limiting the claim concerned.
Claims (6)
1. Wisdom garden saturation analytical model, its characterized in that includes the following step:
s1, acquiring the total order placing amount X0-X24 of each time interval through the ticketing platform, and subtracting the two adjacent time intervals, wherein the order placing amount of the ticketing platform of each time interval can be obtained through the formula, for example, the increment y is X3-X2;
s2, after the user finishes placing the order, entering the garden through the gate, verifying the number of tickets through the gate, and monitoring the number Z of people entering the garden at the time, wherein the number Z is Z0-Z24;
s3, the tourists get out of the garden through the rolling gate, the gate reports the number of the tourists, and each time node can count the total number o of the tourists out of the garden in the scenic spot, so that the number i of the tourists in the garden in each time period of the scenic spot is z-o, and the obtained value i is the total number of the tourists in the scenic spot in each time period;
s4, the total amount X24 can be used for drawing the daily inventory of the scenic spot all the year around, and through the data, the inventory and the number of visitors in the scenic spot at the next year can be estimated.
2. The intelligent campus saturation analysis model of claim 1 further comprising: X0-X24 is 0-24.
3. The intelligent campus saturation analysis model of claim 1 further comprising: and in the S1, the maximum y value is taken according to the increment y value of each time period, namely the maximum y value is the current ordering concurrency peak value, and the ordering total number can be obtained according to the ordering total number X24.
4. The intelligent campus saturation analysis model of claim 1 further comprising: z-value is the total, including the number of people who have previously entered the garden.
5. The intelligent campus saturation analysis model of claim 1 further comprising: Z0-Z24 is 0-24 times of the total number of scenic spots entering the garden per time period.
6. The intelligent campus saturation analysis model of claim 1 further comprising: assuming that the saturation number of the scenic spot is s, when i is less than or equal to 80% s, the tourists are in a comfortable state without early warning; when i is more than 80% s and less than 100% s, the tourists are in a crowded state, and the early warning manager controls the tourists to place the order in the period and guides the tourists to place the order in the next period; when i is larger than 100% s, the scenic spot is in an overload state, the early warning manager closes the time interval platform and places orders, and the staff controls the number of visitors entering the scenic spot.
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Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
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| CN113487457A (en) * | 2021-06-18 | 2021-10-08 | 浪潮卓数大数据产业发展有限公司 | Method, device and medium for automatically adjusting enrollment quota |
| CN113538744A (en) * | 2021-07-09 | 2021-10-22 | 中科迅(深圳)科技有限公司 | Block chain-based passenger flow volume big data analysis management and processing system |
| CN114111790A (en) * | 2021-11-17 | 2022-03-01 | 上海园林（集团）有限公司 | Outdoor water forest landscape system |
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