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CN-121998692-A - Intelligent scenic spot ticketing dynamic capacity adaptation and verification system perceived by Internet of things

CN121998692ACN 121998692 ACN121998692 ACN 121998692ACN-121998692-A

Abstract

The invention discloses an intelligent scenic spot ticket dynamic capacity adapting and verifying system perceived by the Internet of things, which relates to the intelligent management field of intelligent scenic spot ticket capacity synergy perceived by the Internet of things, and comprises the following steps: the system comprises a multi-mode data acquisition module, a data preprocessing and anonymizing module, a feature cluster extraction and dynamic capacity calculation module, a ticket aggregation verification and decision module and a flexible intervention and dynamic optimization module; according to the invention, the low-power consumption sensor network is deployed, so that multi-dimensional data acquisition and anonymization processing are realized, and privacy safety is ensured; the static capacity limitation is broken through according to the algorithm, and the passenger flow regulation accuracy is improved; meanwhile, the linkage ticketing system builds a verification mechanism, flexible intervention reduces influence on tourists, acquires effect data, realizes full-flow coordination, effectively balances scenic spot operation efficiency, tourist experience and safety, and promotes scenic spot management to be intelligently upgraded.

Inventors

  • ZHOU LILI

Assignees

  • 上海卓磐网络科技有限公司

Dates

Publication Date
20260508
Application Date
20260124

Claims (9)

  1. 1. The intelligent scenic spot ticket dynamic capacity adapting and checking system perceived by the Internet of things is characterized by comprising a multi-mode data acquisition module, a data preprocessing and anonymizing module, a feature cluster extracting and dynamic capacity calculating module, a ticket aggregation checking and deciding module and a flexible intervention and dynamic optimizing module; The multi-mode data acquisition module is used for deploying a low-power consumption non-recognition Internet of things sensor network in a scenic spot, acquiring group biological behavior data in real time, and transmitting the acquired group biological behavior data to the data preprocessing and anonymizing module, wherein the group biological behavior data comprises group walking speed, profile compactness, movement track characteristics and acoustic intensity change; The data preprocessing and anonymizing module sequentially performs abnormal data rejection, data screening, anonymizing treatment and format standardization treatment on the received group biological behavior data to generate group characteristic data and transmit the group characteristic data to the characteristic cluster extraction and dynamic capacity calculation module; The feature cluster extraction and dynamic capacity calculation module is used for carrying out data aggregation on the feature data of the group by adopting a group behavior coordination degree aggregation algorithm, extracting feature cluster data and generating a unique identifier; the ticket aggregation verification and decision module is used for linking the authorization data of the scenic spot ticket system, combining the received characteristic cluster data and the threshold data to complete ticket aggregation verification, generating a hierarchical decision instruction and transmitting the hierarchical decision instruction to the flexible intervention and dynamic optimization module; the flexible intervention and dynamic optimization module executes flexible intervention operation according to the received hierarchical decision instruction, acquires intervention effect data and feeds the intervention effect data back to the feature cluster extraction and dynamic capacity calculation module to optimize parameters of the two core algorithms.
  2. 2. The intelligent scenic spot ticketing dynamic capacity adapting and checking system based on the perception of the internet of things according to claim 1 is characterized in that a low-power consumption non-recognition internet of things sensor network in the multi-mode data acquisition module adopts a distributed layered deployment structure, the intelligent scenic spot ticketing dynamic capacity adapting and checking system comprises sensing nodes, aggregation nodes and gateway nodes which are deployed in scenic spot entrances, core sightseeing areas, channels and edge areas, the sensing nodes are composed of environment sensing sensors and are used for acquiring group biological behavior data and transmitting the acquired data to the aggregation nodes in corresponding areas, the aggregation nodes are used for initially converging the data of the sensing nodes in the areas under the jurisdiction and then uploading the data to the gateway nodes in a low-power consumption wireless transmission mode, and the gateway nodes are used for uniformly transmitting the data to the data preprocessing and anonymizing module after data format conversion and protocol adaptation.
  3. 3. The intelligent scenic spot ticketing dynamic capacity adapting and checking system perceived by the Internet of things according to claim 1 is characterized in that the data preprocessing and anonymizing module sequentially executes abnormal data rejection, data screening, anonymizing treatment and format standardization treatment on received group biological behavior data, and specific steps of generating group characteristic data are that abnormal data rejection is carried out according to a normal fluctuation range of the group biological behavior data, invalid data exceeding a reasonable fluctuation range is rejected, data screening is carried out according to a follow-up characteristic cluster extraction requirement, effective data of group walking speed, profile compactness, movement track characteristics and acoustic intensity change are reserved, anonymizing treatment is carried out on the screened effective data, information of associated individual identities is removed, format standardization treatment is carried out on the effective data after anonymizing treatment, a storage format and field type of the data are unified, standardized group characteristic data are generated, and the standardized group characteristic data are transmitted to the characteristic cluster extraction and dynamic capacity calculating module.
  4. 4. The intelligent scenic spot ticketing dynamic capacity adapting and checking system perceived by the Internet of things is characterized in that a group behavior synergy degree aggregation algorithm is adopted in a feature cluster extracting and dynamic capacity calculating module to conduct data aggregation on group feature data, feature cluster data are extracted and unique identification is generated, the group feature data are associated and grouped according to scenic spot partitions and data acquisition time slices, the group walking speed, the contour compactness, the moving track characteristics and acoustic intensity change data in the same area and the same time slices are classified into a group of to-be-processed data, the group behavior synergy degree aggregation algorithm is adopted, the group behavior synergy degree is calculated according to the grouped to-be-processed data, a group internal behavior synergy degree index is obtained through analyzing consistency and relevance of each data dimension, the group to-be-processed data are aggregated according to the group behavior synergy degree index, multiple groups of data with the synergy degree index meeting preset conditions are aggregated to form feature cluster data, the feature attribute of each feature cluster data is extracted, the area identification, the time identification and the unique feature cluster identification is generated according to the feature cluster attribute corresponding to the feature cluster assignment data, and the unique feature cluster serial number is completed.
  5. 5. The intelligent scenic spot ticketing dynamic capacity adapting and verifying system perceived by the internet of things according to claim 4, wherein the formula of the group behavior synergy degree aggregation algorithm in the feature cluster extracting and dynamic capacity calculating module is as follows: Wherein, the The degree of synergy for group behavior; the number of dimensions for the population feature data; Is the first Weight coefficients for the individual feature dimensions; Is the first Single-dimensional synergy of the individual feature dimensions; Is the first Standard deviation of population data in individual feature dimensions; Is the first And the average value of the population data in each characteristic dimension.
  6. 6. The intelligent scenic spot ticket dynamic capacity adapting and verifying system perceived by the Internet of things as claimed in claim 1, wherein the feature cluster extracting and dynamic capacity calculating module calculates the dynamic capacity threshold value and the early warning threshold value of each area of the scenic spot by adopting a cooperation degree linkage dynamic capacity algorithm, and the specific steps are that the data of each area and the group feature data in the scenic spot are associated, and the linkage mapping relation between the cooperation degree of the group feature data and the area capacity is established; according to the adjustment basis, dynamic adaptation calculation is carried out on the reference capacity of each region by combining a cooperation degree linkage dynamic capacity algorithm, a dynamic capacity threshold conforming to the state of the group behaviors is generated, an early warning threshold of a corresponding region is deduced according to the dynamic capacity threshold, and a matching relation between the dynamic capacity threshold and the early warning threshold is formed.
  7. 7. The intelligent scenic spot ticketing dynamic capacity adapting and verifying system as set forth in claim 6, wherein the formula of the synergy linkage dynamic capacity algorithm in the feature cluster extracting and dynamic capacity calculating module is: Early warning threshold value calculation: , wherein, A dynamic capacity threshold for a scenic spot target area; the early warning threshold value is the target area; A reference capacity for the target area; correcting the coefficient for the group behavior synergy level; Adapting coefficients for the region type; and the early warning threshold proportionality coefficient is obtained.
  8. 8. The intelligent scenic spot ticket dynamic capacity adapting and checking system perceived by the internet of things according to claim 1 is characterized in that the ticket aggregation checking and deciding module links the authorization data of the scenic spot ticket system, and completes ticket aggregation checking by combining the received characteristic cluster data and threshold data, and the specific steps of generating a grading decision instruction are that the scenic spot ticket system acquires tourist authorization data in a corresponding period, extracts area identification, time identification and real-time passenger flow associated information in the characteristic cluster data, completes ticket aggregation checking according to the extracted associated information, checks the validity of the authorization data, compares the real-time passenger flow data associated with the characteristic cluster data with a dynamic capacity threshold and an early warning threshold of the corresponding area, and generates the grading decision instruction according to a ticket aggregation checking result.
  9. 9. The intelligent scenic spot ticket dynamic capacity adapting and checking system of the perception of the internet of things according to claim 1, wherein the flexible intervention and dynamic optimization module collects intervention effect data and feeds the intervention effect data back to the characteristic cluster extraction and dynamic capacity calculation module comprises the specific processes of defining the collection dimension of the intervention effect data, screening and de-duplicating the collected intervention effect data through the low-power consumption non-recognition internet of things sensor network deployed in the scenic spot and the authorized data collected in real time by the ticket system, eliminating the intervention effect data and reserving the data capable of truly reflecting the intervention effect; and feeding the processed intervention effect data back to the feature cluster extraction and dynamic capacity calculation module through a data transmission channel in the ticketing system.

Description

Intelligent scenic spot ticketing dynamic capacity adaptation and verification system perceived by Internet of things Technical Field The invention relates to the field of intelligent management of intelligent scenic spot internet of things perception and ticket business capacity coordination, in particular to an intelligent scenic spot ticket business dynamic capacity adaptation and verification system perceived by the internet of things. Background With the rapid development of the intelligent tourism industry, the scenic spot reception scale is continuously enlarged, and the dynamic fluctuation of tourist flow puts higher demands on ticket management, capacity regulation and operation safety. The traditional scenic spot management mode depends on static capacity standards and manual verification means, is difficult to capture passenger flow change rules in real time, is prone to problems of local congestion, unbalanced resource allocation and the like, influences tourist experience, and brings potential safety hazards. The popularization of technologies such as the Internet of things and big data provides technical support for intelligent scenic spot upgrading, and a set of integrated system based on multidimensional sensing, dynamic capacity adaptation and accurate ticket checking needs to be established, so that dynamic matching of passenger flow and scenic spot capacity is realized, and operation efficiency, tourist experience and safety guarantee are considered. The related management system of the existing scenic spot has a plurality of defects, and is difficult to meet the requirements of dynamic and accurate management. In terms of data acquisition, a single dimension sensor or an identification type acquisition device is adopted, data dimension is limited, capturing of behavior characteristics such as group walking speed and moving track relativity is lacked, individual privacy leakage risks exist, a standardized flow is not formed in a data processing link, anonymization processing and format unification are not performed on group data, so that data availability and safety are insufficient, capacity calculation is based on fixed reference values, characteristics of group behavior coordination are not associated, dynamic suitability is poor, early warning threshold setting is stiff, real-time passenger flow state change cannot be responded, ticket verification and capacity data are disjointed from each other, linkage verification of authorization effectiveness and real-time passenger flow capacity is difficult to achieve, intervention modes are mainly rigid flow limiting, regional closing and other passive management and control, a flexible guide mechanism is lacked, closed loop feedback optimization links are not available, core algorithm parameters cannot be adjusted according to intervention effects, management and control accuracy and adaptability are continuously insufficient, and complex and changeable scenic region operation scenes are difficult to deal with. In sum, the existing intelligent scenic spot ticketing and capacity management system has the problems of single data acquisition dimension, privacy protection deficiency, low dynamic capacity calculation accuracy, insufficient ticketing and passenger flow linkage verification, stiff intervention mode, no feedback optimization and the like, cannot adapt to the actual requirements of dynamic operation of scenic spots, and easily causes resource waste, poor tourist experience or accumulated safety risks. Therefore, a dynamic capacity adaptation and ticket aggregation verification system integrating multi-mode non-recognition perception, anonymization data processing and group behavior collaborative linkage is developed, the management and control efficiency is improved through flexible intervention and closed loop optimization, the pain point in the prior art is solved, and the urgent need for high-quality development of intelligent scenic spots is met. Disclosure of Invention The invention aims to make up the defects of the prior art and provides an intelligent scenic spot ticket dynamic capacity adapting and checking system perceived by the Internet of things, which can collect multidimensional group biological behavior data in real time by deploying a low-power consumption sensor network, extract characteristic cluster data according to an algorithm after preprocessing and anonymization, and realize intelligent adaptation of a dynamic capacity threshold and an early warning threshold; meanwhile, the linkage ticketing system builds a verification mechanism, performs flexible intervention, collects effect data to form closed-loop feedback, optimizes algorithm parameters, achieves full-flow coordination, and improves the refinement and dynamic level of scenic spot management. The intelligent scenic spot ticket dynamic capacity adapting and checking system perceived by the Internet of things comprises a multi-mode data acquisition module