Tourism data propagation method and device based on digital travel

Abstract

The invention discloses a travel data propagation method and device based on digital travel, and aims to solve the problems of perception data fluctuation, fault and poor service adaptability caused by complex road conditions of scenic spots in the prior art. The device comprises a mobile carrier for bearing each module, a dynamic leveling mechanism adopts an air pressure linkage adjustment mode and an electromagnetic auxiliary adjustment mode, and is combined with a pressure change signal-leveling action-data processing closed loop to cope with large-amplitude swing of steps / pits and high-frequency small vibration of bumpy roads and ensure that a carrying platform is horizontal, and a sensing module collects tourism data. The first data processing module corrects data fluctuation and removes and supplements sudden change data, the second module achieves scenic spot path planning and travel decision making, the data transmission module transmits data and instructions, and the display module displays data to tourists and scenic spot terminals. According to the invention, the tourism data acquisition stability is significantly improved, a reliable basis is provided for accurate processing and adaptive propagation, and the tourist travel experience is improved.

Description

Technical Field

[0001] This invention belongs to the field of digital cultural tourism data dissemination technology, specifically relating to a method and apparatus for disseminating tourism data based on digital cultural tourism. Background Technology

[0002] Tourism data dissemination technology is a core supporting technology for the integration of the digital economy and the cultural tourism industry. By collecting multi-dimensional data such as scenic spot information and tourist dynamics, and after processing and optimization, it is transmitted to tourist terminals and scenic spot management terminals to realize a closed loop of data collection-processing-dissemination-service. It provides tourists with services such as accurate guidance and route planning, helps scenic spots to achieve flow control and resource optimization, and is a key technology to promote the transformation of the cultural tourism industry from traffic competition to in-depth experience cultivation.

[0003] The existing digital cultural tourism sector has established a basic technical framework for data collection, processing, and dissemination. However, due to insufficient technology adaptability, the overall application effect has significant shortcomings. For example, data collection often relies on fixed cameras, turnstiles, or ordinary mobile carriers, coupled with a single type of leveling mechanism or no dedicated leveling device. Data is integrated through devices such as Wi-Fi probes and sensors. Data processing uses general big data frameworks such as Spark, correcting data based on filtering algorithms with fixed parameters, and performing path planning using traditional algorithms such as A* and Dijkstra. The dissemination stage relies on cloud platforms to push data to terminals, forming a basic service link. Fixed collection equipment has limited coverage, and ordinary mobile carriers experience severe vibrations and swaying due to complex road conditions such as scenic steps and gravel roads. Existing hydraulic leveling systems have leakage risks and high temperature sensitivity, making it impossible to simultaneously meet the dual adjustment needs of large-amplitude swaying and high-frequency small vibrations. This results in tilting of sensing devices, fluctuations and gaps in collected data, making it difficult to meet the needs of high-precision cultural tourism data. General filtering algorithms use fixed parameters, which cannot dynamically adjust the intensity to adapt to the vibration state of the vehicle. They are prone to over-filtering, losing details of scenic spots or retaining a large amount of noise. They exhibit obvious abrupt data changes (specifically, the time span of abnormal data changes covers multiple consecutive collection periods, and the magnitude of data changes significantly exceeds the upper limit of the fluctuation threshold under normal road conditions, often caused by the vehicle encountering steps, potholes, etc., resulting in large-scale swaying). Moreover, the processing of abrupt data changes relies solely on threshold judgments, without combining the characteristics of scenic spots and cultural tourism attributes such as tourist trajectories for verification. This often leads to misjudging and removing valid data or retaining invalid and interfering data, resulting in poor consistency and accuracy of output data. Path planning algorithms mostly use distance and time as core parameters, without incorporating cultural tourism elements such as scenic spot priorities and temporary performances. Furthermore, the parameter weights are fixed, making it impossible to dynamically adapt to different scenarios such as peak congestion and off-peak traffic diversion. The collection, processing, and dissemination modules are independent of each other, and the leveling status data is not linked with data processing. The processing results are not fed back to the vehicle's movement and content push in real time, forming data silos.

[0004] Due to the unstable data collection in existing technologies, resulting in poor data quality, there is an urgent need to develop an integrated technical solution that balances stable data collection, accurate processing, and scenario adaptation, so as to provide technical support for the high-quality development of the cultural and tourism industry. Summary of the Invention

[0005] To address the problems of unstable data collection, inaccurate processing, and inappropriate dissemination in existing digital cultural tourism data dissemination, this invention provides a device and method for stable data collection, accurate processing, and intelligent adaptation, thereby improving the quality of tourism data and the cultural tourism experience for tourists.

[0006] The solution to the technical problem of this invention is as follows: a tourism data dissemination device based on digital cultural tourism, comprising a mobile carrier for carrying various functional modules within a scenic area; a dynamic leveling mechanism fixed on the mobile carrier, the dynamic leveling mechanism comprising a base box, a platform, an adjustment support mechanism, a synchronous linkage mechanism, a pressure transformer acquisition module, and a drive-vibration actuator; the base box being fixed to the mobile carrier; the platform for mounting sensing components; the adjustment support mechanism connecting the base box and the platform; the synchronous linkage mechanism and the adjustment support mechanism being connected via a linkage air pipe; the pressure transformer acquisition module for acquiring pressure change signals within the synchronous linkage mechanism; and the drive-vibration actuator for driving the synchronous linkage mechanism. The system includes: a platform for adjusting the platform angle; a sensing module, mounted on the platform of the dynamic leveling mechanism, for collecting tourism data within the scenic area; a data processing module one, signal-connected to the sensing module and the voltage transformer acquisition module, for correcting minor fluctuations and removing and supplementing large-amplitude data changes in the tourism data collected by the sensing module; a data processing module two, signal-connected to the data processing module one, for planning scenic area routes and making cultural tourism scenario decisions based on the corrected tourism data; a data transmission module, signal-connected to the data processing module two, for transmitting the processed tourism data and decision instructions; and a display module, signal-connected to the data transmission module, for displaying tourism data to tourist terminals or scenic area guide terminals.

[0007] Preferably, the adjustment support mechanism of the dynamic leveling mechanism consists of four sets of elastic support components. The four sets of elastic support components are divided into two groups: front and rear, and left and right. The front and rear groups are used to coordinate the front and rear swing of the platform, and the left and right groups are used to coordinate the left and right swing of the platform. The synchronous linkage mechanism includes a first linkage mechanism and a second linkage mechanism. The first linkage mechanism is connected to the front and rear elastic support components through a linkage air pipe and is used to control the front and rear swing of the platform. The second linkage mechanism is connected to the left and right elastic support components through a linkage air pipe and is used to control the left and right swing of the platform.

[0008] Preferably, both the first and second linkage mechanisms of the synchronous linkage mechanism include a sealed linkage cylinder and a composite piston. The composite piston is fitted into the sealed linkage cylinder and includes a main piston and side pistons disposed on both sides of the main piston. A mating cavity is formed between the main piston and the two side pistons. An air cavity is formed inside the sealed linkage cylinder outside the side pistons. The pressure transducer acquisition module consists of two air pressure sensors, which are respectively installed in the two mating cavities, and the air pressure sensors are connected to the data processing module via a signal connection.

[0009] Preferably, the dynamic leveling mechanism's drive-vibration actuator includes a drive actuator and a vibration actuator. The drive actuator is connected to the sealed linkage cylinder of the synchronous linkage mechanism and is used to drive the sealed linkage cylinder to move in response to large-amplitude oscillations of the platform. The vibration actuator includes an outer cylinder, an inner piston, an electromagnet, and a connecting rod. The inner piston is fitted inside the outer cylinder and has a permanent magnet on it. The electromagnet is located on the inner walls at both ends of the outer cylinder. One end of the connecting rod is fixed to the inner piston, and the other end extends into the sealed linkage cylinder and is fixed to the main piston. The electromagnet is electrically connected to the controller and is used to drive the inner piston to move the connecting rod back and forth in small amplitudes in response to high-frequency, small-amplitude vibrations of the platform.

[0010] Preferably, the small-amplitude fluctuation correction of the data processing module one adopts an adaptive weighted Kalman filter algorithm, which adjusts the noise covariance in the filtering process based on the vibration parameters obtained by the voltage transformer acquisition module; the large-amplitude sudden change data removal and completion of the data processing module one adopts an algorithm combining sliding window and cultural tourism feature verification, which detects suspected sudden change data through sliding window, and completes the data after verifying the authenticity of the sudden change by combining scenic spot features or tourist trajectory.

[0011] Preferably, the scenic area route planning of the second data processing module adopts a multi-objective weighted path planning algorithm. The cost function of the multi-objective weighted path planning algorithm includes distance parameters, attraction priority parameters, tourist density parameters, and temporary event parameters, and the weight of each parameter can be dynamically adjusted. The cultural tourism scene decision of the second data processing module adopts a people flow-attraction fusion decision algorithm. The people flow-attraction fusion decision algorithm outputs route adjustment instructions and tourism data push instructions based on tourist density, remaining capacity of attractions, and visit duration of attractions.

[0012] A method for disseminating tourism data based on the aforementioned device includes the following steps: S1: The mobile carrier is activated, and the platform is adjusted to a horizontal state by a dynamic leveling mechanism. A sensing module collects tourism data within the scenic area, while a pressure change acquisition module collects pressure change signals within a synchronous linkage mechanism and transmits them to data processing module one; S2: Data processing module one identifies the vibration state of the mobile carrier based on the pressure change signals, performs small-amplitude fluctuation correction and removes and supplements large-amplitude sudden changes in the tourism data collected by the sensing module, outputting stable tourism data; S3: Data processing module two receives the stable tourism data, combines it with scenic spot information, visitor density information, and temporary event information, performs scenic area route planning and cultural tourism scenario decisions, and generates route instructions and tourism data to be disseminated; S4: The data transmission module receives the route instructions and the tourism data to be disseminated, transmits the route instructions to the mobile carrier to control its direction of travel, and transmits the tourism data to be disseminated to the display module; S5: The display module receives the tourism data to be disseminated and displays the tourism data to a visitor terminal or a scenic area guide terminal.

[0013] Preferably, in step S2, the data processing module one identifies the vibration state of the mobile carrier based on the pressure change signal and performs small-amplitude fluctuation correction on the tourism data collected by the sensing module, specifically including: S21: The data processing module one calculates the vibration frequency of the mobile carrier based on the pressure change signal, wherein the vibration frequency is determined by the number of fluctuations of the pressure signal per unit time; S22: The process noise covariance weight of the adaptive weighted Kalman filter algorithm is adjusted according to the vibration frequency. The lower the vibration frequency, the smaller the weight and the weaker the filtering strength; the higher the vibration frequency, the larger the weight and the stronger the filtering strength; S23: The adjusted adaptive weighted Kalman filter algorithm is used to filter the tourism data to complete the small-amplitude fluctuation correction.

[0014] Preferably, in step S3, the data processing module two receives stable tourism data and, in conjunction with scenic spot information, tourist density information, and temporary event information, performs scenic spot route planning, specifically including: S31: Constructing a multi-objective cost function, wherein the cost function includes the actual distance from the starting point to the current node, the estimated distance from the current node to the target scenic spot, the priority score of the target scenic spot, the tourist density around the current node, and the cost of temporary events; S32: Dynamically adjusting the weight of each parameter in the cost function according to the scenic spot time period, increasing the weight of the tourist density parameter during peak hours, increasing the weight of the scenic spot priority parameter during off-peak hours, and increasing the weight of the temporary event cost parameter when there are temporary performance events; S33: Iteratively calculating the path nodes based on the adjusted cost function, selecting the node with the lowest cost to form the planned path, and recalculating the tourist density and temporary event cost at preset intervals to dynamically update the path.

[0015] The beneficial effects of this invention are as follows: 1. Based on a dual-mode design of air pressure linkage regulation combined with electromagnetic auxiliary regulation and a closed-loop linkage of pressure transformer signal-leveling action-data processing, the dynamic leveling mechanism can be specifically adapted to complex road conditions such as scenic steps and bumpy roads. When facing large-amplitude swaying (such as over steps / potholes), the air pressure regulation is linked to drive the actuator to quickly counteract the vehicle tilt; when facing high-frequency small-amplitude vibration (such as gravel roads), precise leveling is achieved through electromagnetic drive to ensure that the platform always remains level. This effect directly solves the data fluctuation and discontinuity problems caused by vehicle shaking in the sensing module in the prior art, significantly improving the stability of tourism data such as images and locations collected by the sensing module, and providing a reliable basic data source for subsequent data processing.

[0016] 2. Building upon physical vibration damping, the data processing module utilizes an adaptive weighted Kalman filter algorithm combined with a sliding window and a cultural tourism feature verification algorithm. This allows the module to precisely adapt to the unique characteristics of cultural tourism data. On one hand, it dynamically adjusts the filtering intensity based on the vehicle vibration frequency, effectively suppressing data fluctuations under bumpy road conditions while preserving scenic spot details (such as sculpture textures and inscriptions) under smooth road conditions, avoiding excessive loss of key information due to general filtering. On the other hand, it verifies the authenticity of sudden changes through scenic spot features and tourist trajectories, accurately distinguishing between real sudden changes caused by vehicle bumps and normal data changes caused by temporary obstruction by tourists. Furthermore, it interpolates and completes data based on scenic spot features, ensuring that the completed data is consistent with the preceding and following scenes. This solves the problems of data processing misjudgment and disconnection in existing technologies, significantly improving the accuracy and continuity of the output tourism data.

[0017] 3. Relying on the closed-loop collaboration of mobile carrier, dynamic leveling, perception, dual data processing, transmission, and display, each module forms an efficient working mechanism through signal linkage. Stable data acquisition through dynamic leveling provides high-quality input for data processing, and accurately processed data provides a reliable basis for route planning and decision-making. Adapted planning decisions are synchronized to the display terminal in real time through the transmission module. Ultimately, the tourism data displayed on visitor terminals, scenic area guide screens, etc. (such as attraction information, real-time images, and route suggestions) is both stable and consistent, and also tailored to individual preferences and the actual situation of the scenic area. The convenience of tourists obtaining information and the cultural and tourism experience are significantly improved, while helping scenic areas to achieve reasonable control of visitor flow and optimize the overall quality of digital cultural and tourism services. Attached Figure Description

[0018] Figure 1 This is a flowchart illustrating the logical relationships of tourism data dissemination methods based on digital cultural tourism. Figure 2 This is a hierarchical architecture diagram of tourism data dissemination devices based on digital cultural tourism. Figure 3 This is a schematic diagram showing the coordination relationship between the adjustment support mechanism and the linkage cylinder. Figure 4This is a schematic diagram showing the assembly relationship between the voltage transformer acquisition module and the vibration actuator; Figure 5 This is a block diagram showing the relationship between the system's operating signals; Figure 6 This is a schematic diagram of the assembly relationship of a device; Figure 7 This is a diagram showing the pitch adjustment states. Figure 8 This is a diagram illustrating the data correction and comparison.

[0019] Numbered in the diagram: 1-Electric guided vehicle; 2-Base box; 3-Sensing module; 4-Platform; 41-Dustproof cover pressure plate; 5-Adjustable support mechanism; 51-Air pipe one; 52-Air pipe two; 53-Air pipe three; 54-Air pipe four; 55-Pressure adapter bladder; 56-Upper hinge seat; 57-Lower hinge seat; 58-Flipping shaft seat; 59-Fixed shaft hole; 6-Synchronous linkage mechanism; 61-Linkage cylinder; 62-Composite piston; 621-Main piston; 622-Side piston; 7-Pressure transformer acquisition module; 71-Air pressure sensor; 72-Signal line; 8-Drive actuator; 9-Vibration actuator; 91-Outer cylinder; 92-Inner piston; 93-Connecting rod; 94-Front and rear electromagnets. Detailed Implementation

[0020] Example 1: This embodiment aims to detail the specific implementation process of a tourism data dissemination method and device based on digital cultural tourism, solving the technical problems of unstable tourism data collection, inaccurate processing, and poor dissemination adaptability in the existing digital cultural tourism field, such as... Figure 1 and Figure 2 As shown, through the coordinated work of core components such as electric tour guide vehicles, dynamic leveling mechanisms, and dual data processing modules, stable collection, accurate processing, and adaptive dissemination of tourism data are achieved. The following is a detailed description of each core module of the technical solution.

[0021] First, assemble the various components of the device, such as... Figure 3 and Figure 5 As shown, using the electric tour bus 1 as a mobile carrier, the base box 2 of the dynamic leveling mechanism is fixed to the top of the frame of the electric tour bus 1 with bolts to ensure that there is no relative sway between the base box 2 and the frame. An adjustment support mechanism 5 is installed above the base box 2. The adjustment support mechanism 5 includes four sets of pneumatic support rods (front, rear, left, and right). Figure 3The four pneumatic support rods are labeled A, B, C, and D respectively. The front side is A, the rear side is B, the left side is C, and the right side is D. The medium can be a gas such as compressed air or a liquid such as hydraulic oil (this embodiment takes gas as an example). The top of each of the four pneumatic support rods is connected to the bottom of the platform 4 through an upper hinge seat 56. That is, the top of the upper hinge seat 56 is welded and fixed to the bottom of the platform 4, and the bottom is hinged to the top of the pneumatic support rod. The bottom of each of the four pneumatic support rods is equipped with a lower hinge seat 57. The bottom of the lower hinge seat 57 is connected to the fixed shaft hole 59 on the top of the electric guide vehicle 1 frame through a flip shaft seat 58. The inner ring of the flip shaft seat 58 is interference-fitted with the rotating shaft at the bottom of the lower hinge seat 57, and the outer ring is clearance-fitted with the fixed shaft hole 59, so that each pneumatic support rod can swing flexibly around the flip shaft seat 58. The angle adjustment of the platform 4 is achieved by the coordinated swing of the four pneumatic support rods. The top of the platform 4 is fitted with a sensing module by screws. The sensing module includes a camera and a radar. The lenses and detection directions of both are facing the forward direction of the electric tour bus 1 and the areas on both sides to ensure coverage of the attractions and tourist activity areas within the scenic area. The platform 4 is fitted with a flexible dust cover and fixed with a pressure plate.

[0022] like Figure 4 As shown in the enlarged view of part A, the synchronous linkage mechanism 6 includes a first linkage mechanism and a second linkage mechanism, which are respectively fixed to the front and rear sides or left and right sides of the bottom of the base box 2. The first linkage mechanism is used to control the back-and-forth swing of the platform 4, and its linkage cylinder 61 is fixed to the front side of the base box 2 by a bracket; the second linkage mechanism is used to control the left and right swing of the platform 4, and its linkage cylinder 61 is fixed to the left side of the base box 2 by a bracket. The compound piston 62 of each linkage mechanism is fitted inside the corresponding sealed linkage cylinder 61. The compound piston 62 includes a main piston 621 in the middle and side pistons 622 on the front and rear sides. A front mating cavity is formed between the main piston 621 and the front side piston 622, and a rear mating cavity is formed between the main piston 621 and the rear piston 622. A front air chamber is formed inside the linkage cylinder 61 at the front end of the front piston 622, and a rear air chamber is formed inside the linkage cylinder 61 at the rear end of the rear piston 622. Figure 4 As shown, the pressure transducer acquisition module 7 includes two pressure sensors 71, which are respectively installed on the inner walls of the front and rear mating chambers. The signal line 72 of each pressure sensor 71 is connected to the signal input terminal of the controller through a wire. At the same time, the signal output terminal of the controller is connected to the drive actuator 8 and the vibration actuator 9 through wires. The drive actuator 8 includes a first actuator and a second actuator, which are respectively connected to the linkage cylinder 61 of the first linkage mechanism and the linkage cylinder 61 of the second linkage mechanism through a connector. The drive end of the first actuator is fixed to the linkage cylinder 61 of the first linkage mechanism and can drive the linkage cylinder 61 to move back and forth. The drive end of the second actuator is fixed to the linkage cylinder 61 of the second linkage mechanism and can drive the linkage cylinder 61 to move left and right. like Figure 4 As shown in the enlarged view of section B, the vibration actuator 9 includes a first vibration mechanism and a second vibration mechanism, which are respectively set up to correspond to the first linkage mechanism and the second linkage mechanism: the outer cylinder 91 of the first vibration mechanism is fixed on the base box 2, and the inner piston 92 inside it is fitted inside the outer cylinder 91. A permanent magnet is fixed at the center of the inner piston 92, and front and rear electromagnets 94 are fixed at the front and rear ends of the inner wall of the outer cylinder 91. The rear end of the inner piston 92 is fixed to the center of the main piston 621 of the first linkage mechanism through the connecting rod 93. The through hole opened at the center of the rear piston 622 is fitted on the outside of the connecting rod 93 and can slide along the connecting rod 93; the structure of the second vibration mechanism is the same as that of the first vibration mechanism. The rear end of its connecting rod 93 is fixed to the center of the main piston 621 of the second linkage mechanism, and the rear piston 622 is also fitted on the outside of the connecting rod 93 through the through hole. like Figure 3 As shown, the linkage airway includes airway 1 51, airway 2 52, airway 3 53, and airway 4 54. A pressure adapter bladder 55 is installed in the middle of each of the airways 51, 52, 53, and 54. The pressure adapter bladder 55 is a sealed bladder made of elastic rubber, used to balance pressure fluctuations within the airway. The connection relationships of each airway are as follows: one end of airway 1 51 is connected to the bottom air pressure chamber of the front pneumatic support rod A, and the other end is connected to the front air chamber of the first linkage mechanism; one end of airway 2 52 is connected to the bottom air pressure chamber of the rear pneumatic support rod B, and the other end is connected to the rear air chamber of the first linkage mechanism; one end of airway 3 53 is connected to the bottom air pressure chamber of the left pneumatic support rod C, and the other end is connected to the front air chamber of the second linkage mechanism; one end of airway 4 54 is connected to the bottom air pressure chamber of the right pneumatic support rod D, and the other end is connected to the rear air chamber of the second linkage mechanism. All airway connections are sealed with sealing sleeves to prevent media leakage from affecting the adjustment accuracy. It should be noted that the "air" in this dynamic leveling mechanism is not limited to gaseous media. If a liquid medium (such as hydraulic oil) is used, the pneumatic support rod will be replaced with a hydraulic support rod, the linkage air pipe will be replaced with a high-pressure resistant hydraulic pipe, and the pressure adapter bladder 55 will be pre-filled with the appropriate liquid medium. Its adjustment principle is the same as that of the gaseous medium, and the angle of the platform 4 is adjusted by the change of the medium pressure. Only the material of the sealing element needs to be adjusted according to the type of medium (such as nitrile rubber sealing element for gaseous medium and fluororubber sealing element for liquid medium), without changing the overall structure. Both data processing modules 1 and 2 are integrated into the control box of the electric sightseeing vehicle 1. The signal input terminal of data processing module 1 is connected to the sensing module and the voltage transformer acquisition module 7 via wires, and the signal output terminal is connected to the signal input terminal of data processing module 2. The signal output terminal of data processing module 2 is connected to the driving control system of the electric sightseeing vehicle 1 on one hand to output path adjustment commands, and on the other hand to the data transmission module. The data transmission module uses a 5G module and an edge computing node. The edge computing node is connected to data processing module 2 via a data cable. The 5G module is wirelessly connected to the scenic area cloud platform, tourist terminals (mobile APP, dedicated cultural tourism communication devices), and various guide screens (floor guide screens, high-pole guide screens, and sightseeing vehicle display screens) via an antenna. All display terminals are pre-loaded with receiving programs that match the scenic area, and can receive and display real-time tourism data sent by the data transmission module. The dynamic leveling mechanism, through two modes—large-amplitude swing adjustment and small-amplitude high-frequency vibration adjustment—combines the flexible swing characteristics of the upper hinge seat 56, lower hinge seat 57, and flip shaft seat 58 with the pressure balancing effect of the pressure adapter bladder 55, ensuring that the platform 4 always remains horizontal, thereby guaranteeing the stability of the data collected by the sensing module. Figure 5 As shown. For large-amplitude swing adjustment when the electric tour bus encounters steps or potholes: When the electric tour bus 1 encounters an upward step while traveling in the scenic area, the front of the vehicle body will lift up with the step, causing the front of the base box 2 to tilt upward. At this time, the front pneumatic support rod A is compressed, and the air pressure in its bottom air pressure chamber increases. This pressure is transmitted to the front air chamber of the first linkage mechanism through air pipe 1 51. The pressure adapter bladder 55 on air pipe 1 51 expands slightly due to the increase in air pressure, absorbing part of the pressure peak and avoiding adjustment lag caused by sudden pressure changes in the air pipe. At the same time, the rear pneumatic support rod B is in a stretched state due to the lifting of the front of the vehicle body, and the air pressure in its bottom air pressure chamber decreases. This pressure is transmitted to the rear air chamber of the first linkage mechanism through air pipe 2 52. The pressure adapter bladder 55 on air pipe 2 52 contracts slightly due to the decrease in air pressure, releasing the pre-stored medium and replenishing the pressure in the air pipe, ensuring the continuity of pressure transmission. During this process, the front pneumatic support rod A rotates around the bottom of the platform 4 via the upper hinge seat 56, and the lower hinge seat 57 rotates around the fixed shaft hole 59 via the flipping shaft seat 58, to prevent the pneumatic support rod from being damaged due to rigid connection; the air pressure sensor 71 in the front mating cavity of the first linkage mechanism detects that the air pressure signal is continuously increasing, and the air pressure sensor 71 in the rear mating cavity detects that the air pressure signal is continuously decreasing. The pressure change acquisition module 7 transmits the above air pressure signal changes to the controller. The controller determines that the vehicle body is currently in a large swing state with the front side raised, and then sends a control command to retract backward to the first actuator. Upon receiving the command, the first actuator retracts backward, causing the linkage cylinder 61 of the first linkage mechanism to move backward. The movement of the linkage cylinder 61 pulls the connecting rod 93 backward, which in turn moves the main piston 621 backward. During the backward movement of the main piston 621, the gas in the rear air chamber of the first linkage mechanism is compressed and forced into the bottom air pressure chamber of the rear pneumatic support rod B through the second air pipe 52, causing the rear pneumatic support rod B to extend. Its top pushes the rear side of the platform 4 upward through the upper hinge seat 56, and its bottom rotates around the fixed shaft hole 59 through the lower hinge seat 57 and the flipping shaft seat 58 to adapt to the angle change. At the same time, the volume of the front air chamber of the first linkage mechanism increases, and air is drawn from the bottom air pressure chamber of the front pneumatic support rod A through the first air pipe 51, causing the front pneumatic support rod A to shorten. Its top drives the front side of the platform 4 downward through the upper hinge seat 56, and its bottom rotates flexibly through the flipping shaft seat 58. Through the coordinated action of lowering the front and raising the rear, the platform 4 counteracts the swaying of the front of the vehicle body and always maintains a horizontal state. When the electric tour bus 1 encounters a downward-facing depression causing the front of the vehicle to sink, the air pressure sensor 71 in the front mating chamber of the first linkage mechanism detects a continuous decrease in the air pressure signal, while the air pressure sensor 71 in the rear mating chamber detects a continuous increase in the air pressure signal. The controller determines that the vehicle body is in a state of front-side sinking and sends a command to the first actuator to extend forward. The first actuator extends forward, pushing the linkage cylinder 61 and connecting rod 93 forward. The main piston 621 moves forward and compresses the gas in the front air chamber, which is then pushed into the front pneumatic support rod A through the air pipe 51, causing it to extend. The pressure on the air pipe 51 is adjusted by the pressure matching bladder 55 to balance the air pressure fluctuation. At the same time, air is drawn from the front air chamber to shorten the rear pneumatic support rod B. The front pneumatic support rod A and the rear pneumatic support rod B swing flexibly through the upper hinge seat 56, the lower hinge seat 57, and the flipping shaft seat 58, respectively, so that the front of the platform 4 is raised and the rear is lowered, ensuring that the platform 4 is level. When the electric tour bus 1 encounters a protruding obstacle, causing the right side of the vehicle to lift, the air pressure sensor 71 in the front mating chamber of the second linkage mechanism detects a continuous increase in air pressure signal, while the air pressure sensor 71 in the rear mating chamber detects a continuous decrease in air pressure signal. The controller sends a command to the second actuator to retract backward. The second actuator drives the linkage cylinder 61 and connecting rod 93 of the second linkage mechanism to move backward. Through the air pipe 4 54, the gas in the rear air chamber of the second linkage mechanism is forced into the right pneumatic support rod D. The pressure adapter bladder 55 on the air pipe 4 54 balances the air pressure, causing the right pneumatic support rod D to extend. Its top pushes the right side of the platform 4 to lift through the upper hinge seat 56, and its bottom rotates through the flipping shaft seat 58. At the same time, air is drawn from the left pneumatic support rod C through the air pipe 3 53, causing the left pneumatic support rod C to shorten, which causes the left side of the platform 4 to drop, counteracting the swaying of the right side of the vehicle. If the right side of the vehicle sinks, the second actuator extends forward. Through the opposite medium flow and the extension and retraction of the pneumatic support rod, combined with the flexible swinging of the hinge structure, the platform 4 is ensured to be level. Suitable for small-amplitude high-frequency vibration adjustment when the electric tour bus is traveling on bumpy roads: When the electric tour bus 1 travels on gravel roads or uneven roads in the scenic area, the vehicle body generates a slight high-frequency vibration in the front and back direction, which causes the base box 2 to swing slightly back and forth. This causes the air pressure in the bottom air pressure chambers of the front pneumatic support rod A and the rear pneumatic support rod B to change repeatedly in a short period of time. The air pressure in the first air pipe 51 and the second air pipe 52 fluctuates at a high frequency accordingly. At this time, the pressure adapter bladder 55 on the first air pipe 51 and the second air pipe 52 absorbs the high-frequency pressure fluctuations through rapid expansion and contraction, preventing pressure pulses from being transmitted to the linkage mechanism and improving the stability of the adjustment. At the same time, the front pneumatic support rod A and the rear pneumatic support rod B adapt to the vehicle body vibration through the high-frequency small-angle swing of the upper hinge seat 56, the lower hinge seat 57, and the flipping shaft seat 58, avoiding rigid impact. The aforementioned air pressure changes cause the air pressure sensors 71 in the front and rear mating chambers of the first linkage mechanism to detect a brief increase or decrease in air pressure signals, and this change exhibits a high-frequency reciprocating trend. The pressure transducer acquisition module 7 transmits the high-frequency air pressure signal changes to the controller. The controller determines that the vehicle body is in a state of small-amplitude high-frequency vibration, and then sends a control command to alternately energize the front and rear electromagnets 94 of the first vibration mechanism. When the front electromagnet 94 is energized, the magnetic field it generates attracts the permanent magnet at the front end of the inner piston 92, causing the inner piston 92 and connecting rod 93 to move forward slightly. Subsequently, the rear electromagnet 94 is energized, attracting the permanent magnet and causing the inner piston 92 and connecting rod 93 to move backward slightly. Through the alternating energization of the front and rear electromagnets 94, the high-frequency small-amplitude reciprocating movement of the connecting rod 93 is achieved. The reciprocating movement of the connecting rod 93 drives the main piston 621 of the first linkage mechanism to move back and forth at a high frequency and a small amplitude. The movement of the main piston 621 causes a slight change in the volume of the front air chamber and the rear air chamber of the first linkage mechanism at a high frequency. Through the air pipe 1 51 and the air pipe 2 52, a slight exchange of medium is realized in the air pressure chamber at the bottom of the front pneumatic support rod A and the rear pneumatic support rod B. The pressure adapter bladder 55 assists in balancing the slight pressure change, causing the front pneumatic support rod A and the rear pneumatic support rod B to extend and retract slightly at a high frequency. At the same time, through the flexible swing of the upper hinge seat 56, the lower hinge seat 57 and the flipping shaft seat 58, the platform 4 is slightly adjusted back and forth at a high frequency to counteract the high-frequency vibration of the vehicle body. If the vehicle body generates a slight high-frequency vibration in the left-right direction, the air pressure sensor 71 of the second linkage mechanism detects the high-frequency air pressure change. The controller controls the front and rear electromagnets 94 of the second vibration mechanism to be alternately energized, driving the connecting rod 93 and the main piston 621 to move left and right at a high frequency and a small amplitude. Through the air pipe three 53 and air pipe four 54, a small amount of medium exchange is realized between the left and right pneumatic support rods C and D. The pressure matching bladder 55 balances the air pressure. The left and right pneumatic support rods swing slightly at a high frequency through the hinge structure, so that the platform 4 is slightly adjusted left and right and always keeps horizontal, avoiding fluctuations in the collected data caused by the high-frequency vibration of the sensing module.

[0023] Data processing module one receives raw data collected by the sensing module (including image data captured by the camera and location data collected by the radar), and simultaneously receives vibration parameters transmitted by the voltage transformer acquisition module 7. Based on data correction by the vibration actuator, it supplements and corrects small fluctuations through data processing, completely avoiding vibration data. This module mainly performs the process of eliminating and supplementing data with large, sudden changes. This achieves accurate data processing and provides a stable data source for data processing module two.

[0024] Based on the data correction by the vibration actuator, a small-amplitude fluctuation data correction is then applied using an adaptive weighted Kalman filter algorithm. First, the data processing module obtains the real-time air pressure signals output by the air pressure sensors corresponding to the front, rear, left, and right mating chambers from the pressure transformer acquisition module. Each air pressure signal is continuously sampled with a sampling period of 0.02 seconds. The number of times the absolute value of the air pressure difference between adjacent sampling points is greater than 0.5 kPa within 1 second is counted as the fluctuation number N. The current vibration frequency f of the vehicle body is calculated using the formula f = 1 / (2 × 0.02) × N. Based on the calculated vibration frequency f, the data processing module adjusts the noise covariance Q of the Kalman filter algorithm: When f is less than 1 Hz, the current road surface is determined to be smooth, the weighting coefficient k is set to 0.1, and Q is the product of 0.1 and the basic covariance Q0 (Q0 is preset to 0.01). At this time, the filtering strength is relatively weak, which can preserve the details of the scenic spots (such as sculpture textures and inscriptions) in the data collected by the sensing module; when f is between 1 Hz and 3 Hz, the current road surface is determined to be moderately bumpy, the weighting coefficient k is set to 0.5, and Q is the product of 0.5 and Q0, balancing the filtering strength and detail preservation; when f is greater than 3 Hz, the current road surface is determined to be severely bumpy, the weighting coefficient k is set to 0.9, and Q is the product of 0.9 and Q0, increasing the filtering strength to suppress data fluctuations.

[0025] Subsequently, Kalman filtering iterations are performed. The first step is prediction: based on the filtering result from the previous time step and the state transition matrix A and control matrix B, the predicted value for the current time step is calculated. The second step is covariance prediction: combining the state transition matrix A and the adjusted Q, the predicted covariance for the current time step is calculated. The third step is Kalman gain calculation: based on the predicted covariance, the observation matrix H, and the observation noise covariance R (preset to 0.02), the Kalman gain value is determined. The fourth step is data update: combining the Kalman gain, the original data from the sensing module at the current time step, and the predicted value, the corrected stable data is obtained. Through the above process, the image data collected by the sensing module is unblurred, and the point location data is unoffset, meeting the requirements of subsequent processing. Based on the sliding window combined with the cultural tourism feature verification algorithm, large-scale data abrupt changes are eliminated and supplemented. Data processing module one first sets the sliding window duration to 0.1 seconds, corresponding to 5 frames of sensing data (sampling period 0.02 seconds). The continuous data output by the sensing module slides frame by frame according to the window, calculating the gradient value g_k (i.e., the absolute difference between the current frame data and the previous frame data) of two adjacent frames within each window. Meanwhile, the data processing module calculates the average gradient value of the first 10 sliding windows, sets 1.5 times the average gradient value as the dynamic threshold T_g, and marks the region where the two consecutive frames of data are located as a "suspected abrupt change region" when the gradient value g_k of two consecutive frames of data is greater than T_g.

[0026] Next, cultural and tourism feature verification is performed to determine the authenticity of the sudden change: Data processing module one calls the pre-stored scenic area map database and obtains the "scenic spot area mask" corresponding to the current location based on the electric guide vehicle's positioning information (provided by the vehicle positioning module). If the current location is within the scenic spot coverage area (such as the ancient city wall or stele forest area), the mask is marked as a scenic spot area; if it is in a non-scenic spot area such as a passageway or rest area, the mask is marked as a non-scenic spot area. If the mask corresponding to a suspected sudden change area is a scenic spot area, data processing module one extracts scenic spot feature points from the perceived data in that area (such as the eaves corners and pillar edges in camera images, and the scenic spot outline points in radar data) and matches them with the pre-stored standard feature points of that scenic spot. If the feature point matching degree exceeds 80%, the data in the suspected sudden change area is determined to be normal data (such as temporary data changes caused by temporary obstruction by tourists) and is not removed; if the feature point matching degree is less than 30%, it is determined to be a real sudden change (such as a data collection discontinuity caused by the vehicle body passing over a pothole), and the data in that area is removed. If the mask corresponding to a suspected abrupt change area is a non-scenic area, the data processing module 1 uses the camera's target detection function to identify whether there are dynamic tourist trajectories within that area. If continuous tourist movement trajectories are detected (e.g., tourists crossing the detection range from left to right), the data is considered normal and not removed. If no tourist trajectories are detected and the data change matches the characteristics of an abrupt change, it is determined to be a genuine abrupt change and removed. For the removed genuine abrupt change areas, the data processing module 1 selects the effective data from the 3 frames before and 3 frames after the abrupt change, extracts the coordinates of scenic spot feature points from these 6 frames (or, for non-scenic areas, extracts the coordinates of environmental feature points, such as road edge points), and constructs a completion model using a cubic spline interpolation function. This interpolation function consists of multiple piecewise cubic polynomials, with adjacent piecewise polynomials satisfying continuity of the first and second derivatives. Furthermore, by using the coordinates of all selected feature points, it ensures seamless connection between the completed data and the effective data before and after the abrupt change, without obvious discontinuities, thus guaranteeing the continuity of the perceived data.

[0027] Data processing module 2 receives stable data output from data processing module 1 and combines it with temporary event information pushed by the scenic area cloud platform (such as attraction closures and performance times). Through multi-objective weighted A* path planning and visitor flow coordination with scenic spot integration decision-making, it achieves intelligent processing that adapts to cultural tourism, provides path instructions for electric tour guide vehicles, and provides suitable dissemination content for the display module.

[0028] Multi-objective weighted A* path planning algorithm: First, initialization is performed. Data processing module two obtains the current position of the electric tour bus as the starting point of the path, and at the same time receives tourist preference tags sent by tourist terminals (mobile APP or dedicated cultural tourism communication devices). Such tags include "historical culture", "natural scenery" and "popular photo spots". Based on the preference tags, 3 to 5 matching target attractions are selected from the scenic area map database. For example, if the preference is "historical culture", attractions such as the Stele Forest and the ancient city wall are selected.

[0029] Subsequently, a cost function for path planning is constructed, which includes five parameters: first, the actual distance g(n) from the starting point to the current node, calculated by the positioning module of the electric tour bus and the node coordinates; second, the estimated distance h(n) from the current node to the target attraction, calculated using Manhattan distance (i.e., the sum of the absolute values ​​of the differences between the horizontal and vertical coordinates of the node and the target attraction in the map coordinate system); and third, the priority score p(n) of the target attraction, combined with tourist preference survey data (e.g., tourists with a preference for historical and cultural sites assign a priority score of 10 to the Stele Forest and a priority score of 10 to popular photo spots). The priority score is calculated by combining the visitor density d(n) of the current node with the visitor density within the past hour (the higher the visitor density, the higher the priority score). The priority score ranges from 1 to 10 points. The priority score is calculated by combining the visitor density within the 50-meter radius of the current node with the visitor density within the radar target detection and camera people counting functions of the perception module. The priority score is calculated by combining the visitor density within the 50-meter radius of the current node with the visitor density within the 50-meter radius (unit: people / square meter). The priority score is calculated by combining the visitor density within the 50-meter radius of the current node with the visitor density within the 50-meter radius of the current node with the visitor density within the 50-meter radius of the current node with the visitor density within the 50-meter radius of the current node. The priority score is calculated by combining ... current node. The priority score is calculated by combining the visitor density within the current node with the visitor density within the current node. The priority score is calculated by combining the visitor density within the current node with the visitor density within the current node. The priority score is calculated by combining the visitor density within the current node with the visitor density within the current node. The priority score

[0030] Based on the current time period and the status of events at the scenic area, the weight coefficients of each parameter are dynamically adjusted to ensure that the sum of the weight coefficients is 1: During the peak period from 10:00 to 14:00 every day, the tourist density has a greater impact on the path, so the weight coefficients w1 (corresponding to g(n)) are set to 0.1, w2 (corresponding to h(n)) are set to 0.1, w3 (corresponding to p(n)) are set to 0.2, w4 (corresponding to d(n)) are set to 0.5, and w5 (corresponding to e(n)) are set to 0.1; During the off-peak period from 8:00 to 10:00 every day, the priority of the attractions is more important, so w1 is set to 0.2, w2 to 0.2, w3 to 0.4, w4 to 0.1, and w5 to 0.1; When there are temporary performance events (such as the fountain show at 15:00 every day), the weight of the temporary event cost increases, so w1 is set to 0.1, w2 to 0.1, w3 to 0.2, w4 to 0.1, and w5 to 0.5. Based on the aforementioned cost function and weight coefficients, iterative calculations are performed on the path nodes corresponding to each target attraction: starting from the starting point, the total cost of each adjacent node is calculated (i.e., the sum of the products of each parameter and its corresponding weight coefficient), and the node with the smallest total cost is selected as the next path node. This process is iterated until the target attraction is reached, forming the initial planned path. Subsequently, data processing module two re-acquires visitor density data and temporary event information every 30 seconds, recalculates the cost function and path nodes, and dynamically adjusts the initial path (if the visitor density around the original path node suddenly increases, it switches to an adjacent low-density path with a smaller total cost).

[0031] The decision-making algorithm for combining visitor flow with scenic spot integration: The data processing module 2 obtains the number of tourists within a 50-meter radius of the electric tour bus in real time through the sensing module, calculates the tourist density P based on the area of ​​the region, and divides P into three levels: P1 is less than 5 people / square meter (low density), P2 is 5 to 10 people / square meter (medium density), and P3 is more than 10 people / square meter (high density); At the same time, it obtains the remaining capacity and average tour duration of the current area and three surrounding scenic spots from the scenic area cloud platform. The remaining capacity C is divided into three levels: C1 is more than 50% (high remaining capacity), C2 is 20% to 50% (medium remaining capacity), and C3 is less than 20% (low remaining capacity); the average tour duration T is divided into three levels: T1 is less than 30 minutes (short duration), T2 is 30 to 60 minutes (medium duration), and T3 is more than 60 minutes (long duration). Based on the above parameters, if the current tourist density P is P3 (high density), priority is given to evacuating tourists and avoiding congestion. If one of the three surrounding attractions has a remaining capacity of C1, the data processing module sends a route adjustment command to the electric tour bus's driving control system, setting the attraction with high remaining capacity as the new target attraction. At the same time, it sends the attraction's introduction (including its features and estimated tour duration) to the data transmission module, which then pushes it to the surrounding tourist terminals and guide screens. If only one of the surrounding attractions has a remaining capacity of C2, a deceleration command is sent (reducing the electric tour bus's speed to avoid collisions with tourists), and real-time images of the attraction are pushed to the display terminal to reduce the concentration of tourists at the same attraction. If all surrounding attractions are C3, a detour command is sent (avoiding the current high-density area), and the location information of surrounding dining and rest areas is pushed to guide the flow of tourists. If the current visitor density P is P2 (medium density), then the system balances attraction visits with visitor flow control. If there are attractions with an average visit duration of T1 and remaining capacity of C1, a command to prioritize passing through that attraction is sent, along with a "quick tour guide" (including key attractions and recommended routes). If only attractions with an average visit duration of T3 and remaining capacity of C2 exist, then the system maintains the regular route and sends "off-peak visit suggestions" (e.g., suggesting visiting an hour later to avoid current crowds). If the current visitor density P is P1 (low density), the focus is on enhancing the visitor experience. The system maintains the original route while simultaneously pushing in-depth content about the attraction (such as historical anecdotes and best photography angles) to the display terminals to enrich the visitor's cultural and tourism experience.

[0032] The edge computing node of the data transmission module receives the path information, decision instructions, and content to be disseminated from the data processing module 2. First, it preprocesses this data (such as compressing image data to reduce transmission bandwidth usage and encrypting sensitive information to ensure data security). Then, the 5G module divides the preprocessed data into two categories for transmission: one category is transmitted to the driving control system and display screen of the electric tour bus to control the direction of travel and display the current path, real-time images of attractions, and suggestions for the next tour on the tour bus's display screen; the other category is transmitted to the scenic area cloud platform. After the scenic area cloud platform aggregates the data, it pushes it synchronously to the ground-mounted guide screens, high-pole guide screens, and tourist terminals (mobile APP, dedicated cultural and tourism communication devices) within the scenic area.

[0033] During data transmission, the 5G module monitors transmission latency in real time, ensuring it is less than 100 milliseconds to prevent the displayed content from becoming disconnected from the actual scene due to transmission delays. The edge computing node verifies the transmitted data in real time; if data loss or errors are detected, it immediately retransmits the data to ensure data transmission reliability. After receiving the data, the various terminals of the display module adapt the display according to the terminal type: After receiving the data, the mobile APP combines the tourist's location information (obtained through Bluetooth linkage with the electric guide vehicle to ensure that the tourist's location matches the guide vehicle's location). When the tourist approaches a certain attraction, an AR animation of that attraction (such as displaying a historical scene restoration animation of the attraction combined with camera footage) and real-time visitor flow data automatically pop up. The floor-standing and high-pole guide screens display a heat map of the area's visitor flow (different colors mark areas of different densities), the opening status of attractions, and temporary performance announcements (including performance time and location) in a combination of text and graphics. The guide vehicle display screen displays the current path (marked in map form), real-time images of the attractions ahead (data collected by the perception module and corrected by the data processing module), and suggestions for the next step of the tour, divided into areas.

[0034] It should be noted that the component connection details not mentioned in this embodiment (such as the specific routing of the wires and the specifications of the screws) are all implemented using conventional technical means in the field and can be achieved without additional limitations; the control logic and algorithm parameters of each module can be adjusted according to the scene requirements of different scenic spots, and all of them are within the protection scope of this technical solution.

Claims

1. A tourism data dissemination device based on digital cultural tourism, characterized in that, include: Mobile carriers are used to move various functional modules within the scenic area. A dynamic leveling mechanism is fixed on the mobile carrier. The dynamic leveling mechanism includes a base box, a platform, an adjustment support mechanism, a synchronous linkage mechanism, a pressure transformer acquisition module, and a drive-vibration actuator. The base box is fixed to the mobile carrier. The platform is used to install sensing components. The adjustment support mechanism connects the base box and the platform. The synchronous linkage mechanism and the adjustment support mechanism are connected through a linkage air pipe. The pressure transformer acquisition module is used to acquire pressure change signals within the synchronous linkage mechanism. The drive-vibration actuator is used to drive the synchronous linkage mechanism to adjust the platform angle. The sensing module is installed on the platform of the dynamic leveling mechanism and is used to collect tourism data within the scenic area. Data processing module one is connected to the sensing module and the voltage transformer acquisition module respectively, and is used to correct small fluctuations and remove and supplement large sudden changes in tourism data collected by the sensing module. Data processing module two is signal-connected to data processing module one and is used for scenic area route planning and cultural tourism scenario decision-making based on the corrected tourism data; The data transmission module is signal-connected to the data processing module two and is used to transmit processed tourism data and decision instructions. The display module is signal-connected to the data transmission module and is used to display tourism data to tourist terminals or scenic area guide terminals.

2. The tourism data dissemination device based on digital cultural tourism according to claim 1, characterized in that, The dynamic leveling mechanism comprises four sets of elastic support components. These four sets of elastic support components are divided into two groups: front and rear, and left and right. The front and rear groups are used to coordinate the front-back swing of the platform, while the left and right groups are used to coordinate the left-right swing of the platform. The synchronous linkage mechanism includes a first linkage mechanism and a second linkage mechanism. The first linkage mechanism is connected to the front and rear elastic support components via a linkage air pipe and is used to control the front-back swing of the platform. The second linkage mechanism is connected to the left and right elastic support components via a linkage air pipe and is used to control the left-right swing of the platform.

3. The tourism data dissemination device based on digital cultural tourism according to claim 2, characterized in that, The first and second linkage mechanisms of the synchronous linkage mechanism both include a sealed linkage cylinder and a composite piston. The composite piston is fitted into the sealed linkage cylinder and includes a main piston and side pistons located on both sides of the main piston. The main piston and the two side pistons form a mating cavity, and an air cavity is formed inside the sealed linkage cylinder outside the side pistons. The pressure transducer acquisition module consists of two air pressure sensors, which are installed in the two mating cavities respectively, and the air pressure sensors are connected to the data processing module via a signal connection.

4. The tourism data dissemination device based on digital cultural tourism according to claim 3, characterized in that, The dynamic leveling mechanism's drive-vibration actuator includes a drive actuator and a vibration actuator. The drive actuator is connected to the sealed linkage cylinder of the synchronous linkage mechanism and is used to drive the sealed linkage cylinder to move in response to large-amplitude swaying of the platform. The vibration actuator includes an outer cylinder, an inner piston, an electromagnet, and a connecting rod. The inner piston is fitted inside the outer cylinder and has a permanent magnet on it. The electromagnet is located on the inner walls at both ends of the outer cylinder. One end of the connecting rod is fixed to the inner piston, and the other end extends into the sealed linkage cylinder and is fixed to the main piston. The electromagnet is electrically connected to the controller and is used to drive the inner piston to move the connecting rod back and forth in small amplitudes to respond to high-frequency, small-amplitude vibrations of the platform.

5. The tourism data dissemination device based on digital cultural tourism according to claim 1, characterized in that, The small-amplitude fluctuation correction of the data processing module one adopts an adaptive weighted Kalman filter algorithm. The adaptive weighted Kalman filter algorithm adjusts the noise covariance in the filtering process based on the vibration parameters obtained by the voltage transformer acquisition module. The large-amplitude sudden change data removal and completion of the data processing module one adopts an algorithm combining sliding window and cultural tourism feature verification. The algorithm combining sliding window and cultural tourism feature verification detects suspected sudden change data through sliding window, and performs data completion after verifying the authenticity of the sudden change by combining scenic spot features or tourist trajectory.

6. The tourism data dissemination device based on digital cultural tourism according to claim 1, characterized in that, The scenic area route planning in the second data processing module adopts a multi-objective weighted path planning algorithm. The cost function of the multi-objective weighted path planning algorithm includes distance parameters, attraction priority parameters, tourist density parameters, and temporary event parameters, and the weight of each parameter can be dynamically adjusted. The cultural tourism scenario decision-making in the second data processing module adopts a people-attraction fusion decision-making algorithm. The people-attraction fusion decision-making algorithm outputs route adjustment instructions and tourism data push instructions based on tourist density, remaining capacity of attractions, and visit duration of attractions.

7. A method for disseminating tourism data based on the device described in any one of claims 1-6, characterized in that, Includes the following steps: S1: Start the mobile carrier and adjust the platform to a horizontal state through the dynamic leveling mechanism. The sensing module collects tourism data in the scenic area, and at the same time, the pressure transformer acquisition module collects the pressure change signal in the synchronous linkage mechanism and transmits it to the data processing module one. S2: Data processing module 1 identifies the vibration state of the moving vehicle based on pressure change signals, performs small-amplitude fluctuation correction and large-amplitude sudden change data removal and supplementation on the tourism data collected by the sensing module, and outputs stable tourism data. S3: Data processing module 2 receives stable tourism data, combines scenic spot information, tourist density information and temporary event information to carry out scenic spot route planning and cultural tourism scenario decision-making, and generates route instructions and tourism data to be disseminated; S4: The data transmission module receives the route instructions and the tourism data to be disseminated, transmits the route instructions to the mobile carrier to control its driving direction, and transmits the tourism data to be disseminated to the display module; S5: The display module receives the tourism data to be disseminated and displays the tourism data to tourist terminals or scenic area guide terminals.

8. The tourism data dissemination method according to claim 7, characterized in that, In step S2, the data processing module one identifies the vibration state of the moving vehicle based on pressure change signals and performs minor fluctuation corrections on the tourism data collected by the sensing module, including: S21: Data processing module one calculates the vibration frequency of the moving carrier based on the pressure change signal, wherein the vibration frequency is determined by the number of fluctuations of the pressure signal per unit time. S22: Adjust the process noise covariance weight of the adaptive weighted Kalman filter algorithm according to the vibration frequency. The lower the vibration frequency, the smaller the weight and the weaker the filtering strength; the higher the vibration frequency, the larger the weight and the stronger the filtering strength. S23: The tourism data is filtered using an adjusted adaptive weighted Kalman filter algorithm to correct for minor fluctuations.

9. The tourism data dissemination method according to claim 7, characterized in that, In step S3, data processing module two receives stable tourism data and, combined with scenic spot information, tourist density information, and temporary event information, performs scenic route planning, including: S31: Construct a multi-objective cost function, which includes the actual distance from the starting point to the current node, the estimated distance from the current node to the target attraction, the priority score of the target attraction, the density of tourists around the current node, and the cost of temporary events; S32: Dynamically adjust the weights of each parameter in the cost function according to the time period of the scenic area. Increase the weight of the tourist density parameter during peak hours, increase the weight of the attraction priority parameter during off-peak hours, and increase the weight of the temporary event cost parameter when there are temporary performance events. S33: Iteratively calculate the path nodes based on the adjusted cost function, select the node with the lowest cost to form the planned path, and recalculate the tourist density and temporary event cost at preset intervals to dynamically update the path.

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