CN-121998371-A - Football field intelligent operation management method based on mobile application

CN121998371ACN 121998371 ACN121998371 ACN 121998371ACN-121998371-A

Abstract

The invention discloses a football field intelligent operation management method based on mobile application, which relates to the technical field of field operation and comprises the following steps of building a unified field resource data model, quantifying and conflict judging mechanism based on the stage availability of the resource model, building dynamic stage driving quantity and triggering load balancing for real-time requirements, cross-field collaborative stage optimization and intelligent migration decision mechanism, equipment operation load coupling prediction and maintenance scheduling linkage mechanism and multidimensional operation performance evaluation and self-adaptive strategy decision mechanism. According to the invention, a unified site resource data model is constructed, and the site stage, the facility running state, the maintenance period and the use record are cooperatively modeled, so that the dynamic linkage management of reservation scheduling, resource allocation and equipment operation and maintenance is realized, the site utilization rate can be effectively improved, the equipment operation and maintenance risk is reduced, the refinement level and user experience of the site operation and management are obviously improved, and the method has higher practical value and popularization and application prospect.

Inventors

ZHAN ZHIBIN
JIN LONG
GUO JIWEI
ZHOU XINGBO

Assignees

合肥足行体育科技有限公司

Dates

Publication Date: 20260508
Application Date: 20260211

Claims (10)

1. The intelligent operation management method for the football field based on the mobile application is characterized by comprising the following steps of: S1, constructing a field resource data model, carrying out structural modeling on type information, time-span information, facility running state information, maintenance period information and use record information of a football field, and forming a field resource semantic constraint set for representing the operational state and span marketability of the field; S2, based on the site resource data model, carrying out quantitative calculation on total operational duration, reservation occupation duration, maintenance locking duration and degradation saleable conversion duration of each site in a preset statistical window to obtain a shelf availability index representing the operational degree of the site shelf, and carrying out conflict determinable processing on reservation requests according to the shelf availability index; S3, calculating the effective schedulable capacity and the demand strength of a field by combining the real reservation demand time length generated by the mobile application terminal on the basis of the stage availability index, constructing a scheduling pressure index, and determining whether to trigger a load balancing scheduling flow according to a comparison result of the scheduling pressure index and a preset scheduling trigger threshold; s4, when a load balancing scheduling flow is triggered, screening candidate sites and candidate time shelves based on the scheduling pressure index and the site effective schedulable capacity, calculating migration rationality of reservation requests among different candidate sites or candidate time shelves through migration adaptation indexes, and generating a cross-site collaborative scheduling optimization result; S5, quantitatively analyzing the use intensity of each site in a prediction period according to the collaborative scheduling optimization result, constructing an equipment comprehensive load index by combining equipment historical operation data and inspection data, and generating equipment maintenance priority and maintenance time window suggestions according to the equipment comprehensive load index; S6, constructing an integrated operation performance index based on the stage availability index, the scheduling pressure index and the equipment integrated load index, and carrying out self-adaptive adjustment on a site operation strategy according to the integrated operation performance index.
2. The intelligent operation management method for a soccer field based on mobile application according to claim 1, wherein in step S1, dimensions of type information of the soccer field include at least indoor/outdoor, standard 11 man/7 man/5 man, natural/man/hybrid lawn types, night availability level; Each dimension corresponds to an operational constraint that can be calculated, including a "night availability level" will determine the lighting system controllable range and energy consumption billing policy, and a "lawn type" will determine the maintenance period and bearable load threshold.
3. The intelligent operation management method for the football field based on mobile application according to claim 1, wherein in the step S2, the stage availability index is constructed as follows: Wherein, the Is a stage availability index; The time length is occupied for reservation in a statistical window; Locking time length for maintenance in the statistical window; A saleable conversion duration for degradation within the statistics window; is the total operable duration within the statistical window; Using structured gear availability index Conflict determination processing of reservation requests is performed.
4. A football field intelligent operation management method based on mobile application according to claim 3, characterized in that the conflict determinable process comprises: If the locking reason corresponding to a certain stage unit has high priority, the stage is directly judged to be not saleable; if the price is downgraded and available, different prices and service clauses are generated in a reduced proportion, if the price is downgraded and available, the price is reduced and the service clause is provided Below the operation threshold, the schedule is not changed.
5. The intelligent operation management method for a football field based on mobile application according to claim 1, wherein in step S3, the manner of calculating the effective schedulable capacity of the field is as follows: Wherein, the The available schedulable capacity for the sites within the statistics window; space-efficient schedulable capacity The scheduling pressure index is constructed as follows: Wherein, the For a scheduling pressure index; In order for the strength to be required, Including the length of the expiration time for the paid reservation order, the strong intent request that is unpaid but enters the confirmation page and reappears in a short period of time, and the length of the proposed occupation for the group/event reservation application.
6. The intelligent operation management method for football field based on mobile application according to claim 5, wherein the scheduling pressure index The comparison result with the preset scheduling triggering threshold value determines whether to trigger the load balancing scheduling process, which comprises the following steps: presetting a scheduling trigger threshold Parameters are set by an operator according to venue positioning and service commitment; When (when) In this case, a trigger signal for load balancing is output, and a driving amount set { is output -As a scheduling input; When (when) And outputting a trigger signal without forced load balancing.
7. The intelligent operation management method for football field based on mobile application according to claim 1, wherein in step S4, when step S3 determines that When the system enters a scheduling optimization state, the system screens a candidate field set, and the candidate field consists of the same type of field, regional adjacent fields and degraded marketable fields with substitution functions; introducing migration adaptation index The method is used for evaluating the comprehensive rationality of a reservation request after being migrated from a target site to a candidate site, and a model is constructed as follows: Wherein, the Representing an original reservation time point of a user, and obtaining reservation request time through mobile application; Representing available alternative stage time of the candidate site, which is obtained by converting the time stamp of the candidate stage unit; A maximum acceptable migration time deviation threshold set for the operator; scoring a service match; The system calculates for all candidate sites Presetting a migration acceptance threshold and And comparing, determining the final candidate site schedule, and generating a cross-site collaborative schedule optimization result.
8. The intelligent operation management method for the football field based on mobile application according to claim 1, wherein in the step S5, a calculation model of the comprehensive load index of the equipment is as follows: Wherein, the The load index is integrated for the equipment; intensity weight coefficients are used for units; attenuating risk coefficients for the device; When (when) When the safety threshold of the preset equipment is exceeded, the system automatically triggers a maintenance scheduling strategy, including arranging a lawn maintenance window in advance, reducing the night illumination operation level or automatically limiting the high-intensity event scheduling.
9. The intelligent operation management method for the football field based on mobile application according to claim 1, wherein in the step S6, a calculation model of the comprehensive operation performance index is constructed as follows: Wherein, the The comprehensive operation performance index is used for uniformly measuring the overall quality of site operation.
10. The mobile application-based football field intelligent operation management method according to claim 9, wherein the comprehensive operation performance index is Performing adaptive adjustment on a venue operation policy, including: the system calculates at each statistical period And automatically adjusting the operation strategy according to the change trend When the system is continuously increased, the operation efficiency and the user experience are in good states, the system gradually increases the threshold value of the field utilization rate to increase the income, when When descending, the system automatically matches the optimization strategy according to the descending reason.

Description

Football field intelligent operation management method based on mobile application Technical Field The invention relates to the technical field of court operation, in particular to a football court intelligent operation management method based on mobile application. Background With the continuous advancement of the digitalized development of the sports industry, football fields are used as important sports infrastructures, and the operation management mode of the football fields is gradually changed from traditional manual management to informatization and intelligence. At present, part of football stadiums are introduced into mobile application reservation systems to realize the functions of on-line reservation, payment settlement and basic expiration date management of users, so that the field operation efficiency is improved to a certain extent. However, most of the prior art only stays at a single reservation management level, and lacks the overall co-operation capability for site resources. On the one hand, the existing system generally dispersedly manages the site shelves, the facility running states and the maintenance plans, and is difficult to realize unified modeling and dynamic linkage of multidimensional operation data, so that reservation conflict or uneven resource allocation easily occurs in the site in the peak period, and the problem of low utilization rate exists in the valley period, and the overall operation efficiency is difficult to further improve. On the other hand, the prior art generally lacks the capability of carrying out coupling analysis on operation schedule and equipment operation state, operation and maintenance works such as field schedule and lighting equipment, lawn maintenance, security inspection and the like are often mutually independent, equipment overload operation or maintenance period and actual use requirement are easily caused to be mismatched, and further operation and maintenance cost is increased and field service quality is influenced. Therefore, how to construct an intelligent operation management method capable of realizing on-site resource collaborative scheduling, equipment operation and maintenance linkage management and operation strategy dynamic optimization becomes an important technical problem to be solved in the field of digital management of football fields. Disclosure of Invention Aiming at the defects of the prior art, the invention provides a football field intelligent operation management method based on mobile application, which aims to solve the problems in the background art. In order to achieve the above purpose, the present invention provides the following technical solutions: In a first aspect, the invention provides a football field intelligent operation management method based on mobile application, which comprises the following steps: S1, constructing a field resource data model, carrying out structural modeling on type information, time-span information, facility running state information, maintenance period information and use record information of a football field, and forming a field resource semantic constraint set for representing the operational state and span marketability of the field; S2, based on the site resource data model, carrying out quantitative calculation on total operational duration, reservation occupation duration, maintenance locking duration and degradation saleable conversion duration of each site in a preset statistical window to obtain a shelf availability index representing the operational degree of the site shelf, and carrying out conflict determinable processing on reservation requests according to the shelf availability index; S3, calculating the effective schedulable capacity and the demand strength of a field by combining the real reservation demand time length generated by the mobile application terminal on the basis of the stage availability index, constructing a scheduling pressure index, and determining whether to trigger a load balancing scheduling flow according to a comparison result of the scheduling pressure index and a preset scheduling trigger threshold; s4, when a load balancing scheduling flow is triggered, screening candidate sites and candidate time shelves based on the scheduling pressure index and the site effective schedulable capacity, calculating migration rationality of reservation requests among different candidate sites or candidate time shelves through migration adaptation indexes, and generating a cross-site collaborative scheduling optimization result; S5, quantitatively analyzing the use intensity of each site in a prediction period according to the collaborative scheduling optimization result, constructing an equipment comprehensive load index by combining equipment historical operation data and inspection data, and generating equipment maintenance priority and maintenance time window suggestions according to the equipment comprehensive load index; S6, constructing an integ