A sports event-oriented comprehensive commercial value dynamic prediction method and system

Abstract

The application relates to the technical field of sports event operation and commercial value management, and particularly discloses a comprehensive commercial value dynamic prediction method and system for sports events. The application predefines a value script containing a physical signal activation condition, and automatically identifies a game plot by monitoring signals such as player positioning and motion posture in real time. Meanwhile, the plot evolution state is driven through a light effect component on an entity sand table model to form an intuitive visual value evolution path. When the value reaches a climax, an operation personnel inserts a physical token representing a commercial resource into a sand table slot to complete physical authorization. After the system captures the action, the system automatically verifies the resource, encapsulates and distributes a high-priority instruction to on-site equipment to realize instant value redemption. The application combines value prediction and physical interaction to construct a precise, traceable closed loop from signal collection to resource scheduling, and significantly improves the commercial operation efficiency.

Description

Technical Field

[0001] This invention belongs to the field of sports event operation and commercial value management technology, and relates to a comprehensive commercial value dynamic prediction method and system for sports events. Background Technology

[0002] As a crucial vehicle for commercial activities, the realization of commercial value in sports events heavily relies on the accurate grasp and timely response to the most exciting moments. A core challenge in current sports event operations lies in the fact that the commercial value spikes during an event are often fleeting and unpredictable. Operations personnel lack effective technological means to identify these critical moments in real time and quickly allocate commercial resources for intervention. Traditional methods of manual observation and subjective judgment suffer from delayed responses and insufficient accuracy, resulting in the loss of numerous high-value commercial opportunities during the event. Advertising placements, brand exposure, and other commercial activities cannot be precisely synchronized with the event's climax, severely impacting the return on investment of commercial resources and the realization of the event's overall commercial value.

[0003] Currently, the most common solutions used in the industry include manual monitoring based on live broadcast footage and statistical prediction models based on historical data. Manual monitoring relies on experienced broadcast directors observing the game in real time and making subjective judgments about when to allocate commercial resources. While this method can capture some exciting moments, it is highly dependent on personal experience and lacks objective standards. Statistical prediction models, on the other hand, analyze historical event data to establish a correlation between commercial value and macroeconomic factors such as match time and score differences, attempting to predict trends in commercial value fluctuations. This method provides some quantitative basis, but the prediction results are often too crude and difficult to handle unexpected situations on the field.

[0004] The fundamental drawback of traditional methods lies in the lack of real-time acquisition and refined analysis of microscopic physical signals at the event site. They fail to establish an operational mapping between abstract commercial value concepts and the specific evolution of the event's plot, and lack intuitive visualization tools to assist operators in making rapid decisions. Manual monitoring suffers from strong subjectivity, long response delays, and susceptibility to human interference, while statistical prediction models have shortcomings such as poor generalization ability, inability to capture microscopic dynamics, and lack of real-time capability. These traditional methods cannot meet the urgent needs of modern sports event commercial operations for accuracy, real-time performance, and operability. Therefore, an innovative technological solution that organically combines physical signal acquisition, value identification, visualization, and resource allocation is urgently needed. Summary of the Invention

[0005] In view of this, in order to solve the problems mentioned in the background technology, a method and system for dynamic prediction of comprehensive commercial value of sports events is proposed.

[0006] The objective of this invention can be achieved through the following technical solution: The first aspect of this invention provides a method for dynamic prediction of the comprehensive commercial value of sports events, including: S1, value script generation: defining a set of value scripts containing ordered plot nodes and corresponding physical signal activation conditions.

[0007] S2. Real-time plot recognition: Real-time monitoring of physical signals at the event site, continuous comparison of physical signals with the set of value scripts, identification and output of real-time plot node activation signals that match the activation conditions of an ordered plot node in the set of value scripts.

[0008] S3. Visual Presentation: Receives real-time plot node activation signals, drives the preset display components on the venue's physical sand table model, and generates a visual value evolution path that represents the evolution status of the value plot.

[0009] S4. Physical Authorization Capture: Based on the value growth trend indicated by the visualized value evolution path, when a physical token representing a business resource is detected being inserted into a designated physical slot on the venue's physical sand table model, a physical token authorization instruction binding the resource and timing is generated.

[0010] S5. Resource Verification and Scheduling: Parse the physical token authorization instruction, extract the resource identity and authorization time information contained therein, and generate a high-priority resource scheduling request to be executed.

[0011] S6. Intervention instruction encapsulation: Based on high-priority resource scheduling requests, retrieve and lock the corresponding execution instruction set from the preset resource package, and generate an instant intervention instruction package containing specific operation parameters.

[0012] S7. Execution Log Generation: Distribute the real-time intervention instruction package to the corresponding execution device at the event site, drive the execution device to complete the real-time realization of commercial value, and generate a value realization execution log that records the entire intervention process.

[0013] A second aspect of the present invention provides a comprehensive commercial value dynamic prediction system for sports events, comprising: a value script generation module, which defines a set of value scripts containing ordered plot nodes and corresponding physical signal activation conditions.

[0014] The real-time plot recognition module monitors the physical signals at the event site in real time, continuously compares the physical signals with the set of value scripts, identifies and outputs the real-time plot node activation signal that matches the activation conditions of a certain ordered plot node in the set of value scripts.

[0015] The visualization module receives real-time plot node activation signals, drives the preset display components on the venue's physical sand table model, and generates a visualized value evolution path that represents the evolution status of the value plot.

[0016] The physical authorization capture module generates a physical token authorization instruction that binds resources and timing when it detects that a physical token representing commercial resources has been inserted into a designated physical slot on the venue's physical sand table model, based on the value growth trend indicated by the visualized value evolution path.

[0017] The resource verification and scheduling module parses the physical token authorization instruction, extracts the resource identity and authorization time information contained therein, and generates a high-priority resource scheduling request to be executed.

[0018] The intervention instruction encapsulation module retrieves and locks the corresponding execution instruction set from the preset resource package based on the high-priority resource scheduling request, and generates an instant intervention instruction package containing specific operation parameters.

[0019] The execution log generation module distributes real-time intervention instruction packages to the corresponding execution devices at the event site, drives the execution devices to complete the real-time realization of commercial value, and generates a value realization execution log that records the entire intervention process.

[0020] Compared with the prior art, the embodiments of the present invention have at least the following advantages or beneficial effects: (1) The present invention realizes a complete closed loop from abstract value prediction to specific physical operation by constructing a value script physical sand table system, which significantly improves the efficiency and accuracy of realizing the commercial value of sports events. This method transforms the traditional business decision-making process that relies on subjective judgment into an automated identification process based on objective physical signals. By deploying a multi-dimensional sensor network in the stadium to collect physical signals such as player position, movement posture and environmental sound in real time, and continuously comparing them with the predefined value script, it can accurately identify event plots with commercial value explosion potential such as goals, last-minute kills, and reversals with a millisecond-level response speed. Compared with the traditional manual monitoring method, it captures key moments on average several seconds in advance, creating a valuable time window for the accurate placement of commercial resources, enabling commercial behaviors such as advertising and brand display to be accurately synchronized with the climax of the event, greatly improving the dissemination effect and return on investment of commercial resources.

[0021] (2) This invention innovatively uses a physical sand table model as a visualization carrier of the evolution of value plots, transforming complex data analysis results into an intuitive light effect evolution path. This allows operators to grasp the current development trend and stage of the value plot without needing to understand the underlying algorithm. The dynamically changing light effect colors and brightness on the sand table model intuitively reflect the growth trend of value intensity, providing operators with a clear basis for decision-making and significantly reducing the cognitive burden and psychological pressure of decision-making. Compared with traditional screen displays, this physical visualization method has a stronger sense of space and presence, making it particularly suitable for use in tense event environments. It can help the operations team quickly reach a consensus and coordinate actions, avoiding the loss of business opportunities due to poor information transmission or misunderstandings.

[0022] (3) This invention achieves physical confirmation and traceable recording of business resource scheduling decisions through the interaction mechanism of physical tokens and sand table slots, effectively preventing misoperation and resource abuse. Operators must actually insert the physical token representing a specific business resource into the corresponding physical slot at the value climax indicated by the sand table model. This physical action is both the trigger condition for the authorization instruction and a clear identifier of decision-making responsibility, ensuring that every allocation of business resources has undergone careful human judgment and clear physical confirmation. The unique identification code of the physical token and the precise timestamp of the insertion time are completely recorded, forming a full-link tracking log from value identification to resource realization, providing reliable data support for post-event effect evaluation, responsibility determination and process optimization. Compared with traditional software interface click operations, it has a stronger sense of ritual and constraint, which helps to cultivate the standardization awareness and sense of responsibility of the operation team. Attached Figure Description

[0023] To more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0024] Figure 1 This is a schematic diagram of the method steps of the present invention.

[0025] Figure 2 This is a schematic diagram of the system structure connection of the present invention. Detailed Implementation

[0026] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0027] Please see Figure 1 The first aspect of the present invention provides a method for dynamic prediction of comprehensive commercial value for sports events, including: S1, value script generation: defining a set of value scripts containing ordered plot nodes and corresponding physical signal activation conditions.

[0028] In a specific embodiment of the present invention, the specific steps of defining a set of value scripts containing ordered plot nodes and corresponding physical signal activation conditions include: decomposing the event plots in a sports event that meet the commercial value conditions into at least two ordered plot nodes arranged in chronological order.

[0029] It should be noted that the commercial value condition is that the event plot can be predefined and decomposed into multiple ordered plot nodes arranged in chronological order, and each ordered plot node can establish a unique mapping relationship with a set of physical signal activation conditions that can be monitored in real time by sensors.

[0030] It's also important to clarify that, firstly, a deep analysis of the inherent development logic of sporting events is necessary. In a complete sporting event, operators select specific event segments that meet the aforementioned commercial value conditions, based on the objective laws governing changes in commercial value. Taking a professional football match as an example, the "goal-scoring moment" is a typical commercial value explosion segment. This segment is not a single instant but an evolutionary process, requiring decomposition into at least two interconnected, ordered segment nodes according to a time sequence. For example, the goal-scoring moment can be broken down into at least two ordered segment nodes: the first is "the forward accelerates at the edge of the penalty area," the second is "the forward completes the shooting motion," and the third is "the ball enters the goal." This decomposition method ensures that each ordered segment node represents a clear stage in the overall event's evolution, with a clear chronological relationship between the nodes.

[0031] For each ordered plot node, a set of physical signal combinations collected by sensors in the venue is set as its unique activation condition. The physical signal combinations include player positioning data, player movement posture data, and ambient sound decibel values.

[0032] It should be noted that, secondly, a unique activation condition is assigned to each ordered plot node. This activation condition consists of a specific combination of three types of physical signals. Player location data is collected through ultra-wideband positioning base stations deployed within the stadium. These base stations continuously measure the distance to the positioning tags worn by athletes. Each base station receives ultra-wideband pulse signals transmitted by the tags and calculates the tag's position coordinates on a two-dimensional plane based on the signal arrival time difference. The sampling frequency can be set to 10 times per second. The specific form of player location data is a quadruple containing a timestamp, athlete identification number, X-axis coordinate, and Y-axis coordinate. The coordinate values ​​are in centimeters, ranging from 0 to the width and length of the field, and the timestamp is accurate to the millisecond level.

[0033] Player posture data is collected using miniature accelerometers and gyroscopes worn by athletes. The accelerometers measure the athlete's body acceleration in three orthogonal directions, measured in meters per second squared. The gyroscopes measure the athlete's rotational speed, measured in radians per second. This data is sampled at a frequency of 100 times per second to capture rapid changes in movement. The player posture data is presented as an octet containing a timestamp, athlete identification number, three-axis acceleration values, and three-axis rotational speeds.

[0034] The ambient sound decibel levels were collected using directional miniature microphones deployed in key areas of the venue. These microphones were connected to a digital audio processing module to calculate the ambient noise level in decibels in real time. The sampling frequency could be set to once per second. The decibel data was presented as a binary tuple containing a timestamp and a decibel value, with the value ranging from 50 to 120 dB.

[0035] Next, we need to define the logical relationships of physical signal combinations for each ordered plot node. A "physical signal combination" refers to the combination of certain elements from the three types of physical signals mentioned above according to logical operations. Taking the ordered plot node "a forward accelerates at the edge of the penalty area" as an example, its activation condition is defined by the following physical signal combination: the player's positioning data satisfies that the position is within the penalty area, and the combined acceleration of the three axes in the player's motion posture data exceeds 3 meters per second squared, and the time window for satisfying the above two conditions is no less than 0.5 seconds. The logical relationship of this activation condition is an AND operation, meaning that all three conditions must be satisfied simultaneously.

[0036] Secondly, the uniqueness and repeatability of the activation conditions need to be verified. Uniqueness means that the combination of conditions will not be falsely triggered due to external interference during the match. In the first ordered plot node of the aforementioned goal scenario, the acceleration threshold of 3 m / s² is selected based on the following: based on on-site tests in several professional football matches, it was found that the average daily running acceleration of ordinary athletes is 2.0 to 2.5 m / s², while the full acceleration towards the penalty area reaches 3.2 to 4.0 m / s². Choosing 3.0 m / s² as the threshold can effectively filter out false triggers while capturing sprinting behavior. The penalty area range parameter is based on the official size definition of the stadium. The time window of 0.5 seconds is selected based on the following: the shortest effective duration of acceleration sprint is usually not less than 0.5 seconds, which ensures that real sprinting behavior is captured rather than occasional body swaying. Repeatability means that under the same or similar match conditions, the activation condition can stably identify similar plots.

[0037] All ordered plot nodes and their associated physical signal activation conditions are structurally combined to form a set of valuable scripts.

[0038] It should be noted that, finally, all the decomposed ordered plot nodes and their corresponding activation conditions are structurally combined to form a value script set. This value script set is an ordered, multi-layered data structure. Its top layer consists of a unique identifier and plot name for the event plot, such as "Goal Moment." The second layer is a sequence of all ordered plot nodes contained within that plot, arranged in chronological order. The third layer is a detailed definition of each ordered plot node, including its unique number, descriptive text, logical expression for the activation condition, and specific parameter thresholds for each physical signal within the activation condition. Each ordered plot node in the value script set is uniquely identified, ensuring accurate location in subsequent steps. The activation conditions for each ordered plot node are independent and do not cause conflicts or ambiguities.

[0039] S2. Real-time plot recognition: Real-time monitoring of physical signals at the event site, continuous comparison of physical signals with the set of value scripts, identification and output of real-time plot node activation signals that match the activation conditions of an ordered plot node in the set of value scripts.

[0040] In a specific embodiment of the present invention, the specific steps of identifying and outputting a real-time plot node activation signal that matches the activation conditions of an ordered plot node in the set of value scripts include: continuously acquiring the player's real-time position, acceleration changes, and ambient sound decibel values ​​through positioning and posture sensors worn by the player and sound recording equipment deployed in key areas of the venue.

[0041] It is important to note that, firstly, a real-time physical signal acquisition system for the event needs to be established. This involves continuous monitoring of the event venue using positioning and posture sensors worn by players, as well as audio recording equipment deployed in key areas of the stadium. The positioning sensors worn by players utilize ultra-wideband (UWB) technology, with tags attached to the athletes' chests, waists, or legs. These tags continuously transmit UWB pulse signals at a sampling frequency of 10 Hz to multiple positioning base stations deployed throughout the venue. Each base station, upon receiving a signal from the tag, acquires the propagation time from transmission to reception. Using the time difference data from at least four base stations, triangulation is performed to automatically determine the athlete's real-time position coordinates in three-dimensional space. This position data includes X-axis, Y-axis, and Z-axis coordinates, along with a corresponding timestamp. The X and Y-axis coordinates range from 0 to the width and length of the venue, while the Z-axis coordinates range from 0 to 2 meters to reflect the player's jump height. The coordinate accuracy is within ±10 centimeters, and the timestamp is accurate to the millisecond level.

[0042] The athlete's posture sensors consist of high-precision triaxial accelerometers and triaxial gyroscopes. These sensors are mounted on the wrist, waist, or foot, continuously measuring the athlete's dynamic body movements at a sampling frequency of 100 Hz. The accelerometers measure triaxial acceleration values ​​corresponding to acceleration along the athlete's body in the forward / backward, left / right, and up / down directions, in meters per second squared, with a range of ±10 meters per second squared. The gyroscopes measure triaxial rotational rates corresponding to angular velocities around the athlete's body along three orthogonal axes, in radians per second, with a range of ±500 radians per second. The data from the accelerometers and gyroscopes are fused within the sensors to generate a data record containing triaxial acceleration, triaxial angular velocity, and a timestamp.

[0043] The sound-receiving equipment deployed in key areas of the venue includes multiple high-sensitivity directional microphones, installed near the penalty area, midfield, and stands. These microphones collect ambient audio once per second, with a sampling rate set to 1 Hz. The collected audio signals are analyzed in real time by a digital audio processing module to obtain the overall noise level in decibels. This decibel value is obtained based on rapid weighted processing of the audio signal within the frequency range sensitive to the human ear, resulting in a range of 50 to 130 decibels with an accuracy of ±1 decibel.

[0044] The timestamps of the acquired player's real-time position, acceleration changes, and ambient sound decibel values ​​are aligned to form a multi-dimensional real-time physical signal stream.

[0045] It's important to note that, secondly, timestamp alignment of physical signals from multiple heterogeneous sensors is necessary. Since the sampling frequencies of the positioning sensor, attitude sensor, and microphone are 10 Hz, 100 Hz, and 1 Hz respectively, their sampling times are not entirely consistent, thus requiring a unified time base for synchronization. The foundation for establishing time synchronization is the deployment of a central time server in the main control room at the event site. This server connects to a GPS receiver to obtain a microsecond-level precise time base. All sensor nodes periodically synchronize with this central time server via a wireless network, and the clock deviation within each sensor is corrected to the millisecond level. Each physical signal data point is immediately tagged with a timestamp determined by the central time server upon acquisition. The alignment process employs a buffer queue mechanism. The real-time data receiving module maintains three independent data buffer queues, storing the raw data from the positioning sensor, attitude sensor, and microphone respectively. For sensors with higher sampling frequencies, such as the 100 Hz sampling of the attitude sensor, the data is arranged in the buffer in the order of arrival. For sensors with low sampling frequencies, such as 1 Hz sampling in radio equipment, the data arrival time interval is relatively long. Therefore, a forward padding strategy is adopted, whereby when a new sound decibel value arrives, it remains unchanged until the next new data arrives. Alignment is performed as follows: whenever the system clock reaches an integer multiple of 10 milliseconds, the data with the timestamp closest to that moment is retrieved from each buffer queue. These data from different sensors are merged to form a multi-dimensional data record containing all available physical signals at that moment. This data record is appended to a data stream within a sliding time window, with a window length set to 5 seconds, to store all recently acquired physical signals.

[0046] The system performs a cyclical matching and judgment process between the real-time physical signal stream and the activation conditions of each ordered plot node in the set of value scripts. Once a match is successful, a real-time plot node activation signal is immediately generated.

[0047] It should be noted that the real-time matching executor repeatedly executes the matching judgment process through a loop control structure. Whenever the system clock reaches an integer multiple of 100 milliseconds, the executor extracts the latest physical signal data set from the sliding time window. For each event scenario in the value script set, the system traverses all ordered event nodes contained in that scenario. For each ordered event node, the system obtains its corresponding activation condition logical expression. This expression defines the specific conditions that the physical signal must meet, such as "position within the penalty area and acceleration greater than 3.0 m / s² and duration not less than 0.5 seconds". The system substitutes the current physical signal data set into this logical expression for evaluation. During the evaluation of the activation conditions, the system needs to handle condition judgments in multiple dimensions. For the position condition, the system checks whether the X, Y, and Z coordinates in the latest player positioning data fall within the predefined geometric range of the penalty area. For the acceleration condition, the system calculates the Euclidean norm of the three-axis acceleration in the player's motion posture data, i.e., the magnitude of the composite acceleration, calculated by the formula: the total acceleration is the square root of the sum of the squares of the three-axis acceleration components. Regarding the time condition, the system checks whether the continuous duration of the above conditions exceeds a threshold. If all conditions are met simultaneously, the activation condition of the ordered plot node is determined to be satisfied.

[0048] Once the activation conditions for an ordered plot node are met, the system checks whether that node is the first node in the value script that should be activated for that event plot. This involves two checks: First, if the ordered plot node has a predecessor node, the system checks whether the predecessor node has already been activated. This is achieved by querying a status record table, which records the activation status and activation timestamp of each ordered plot node. Second, if the ordered plot node has no predecessor node, or all of its predecessor nodes have been activated, the system marks the node as activated and records its precise activation timestamp.

[0049] The process of generating a real-time plot node activation signal is as follows: When the activation conditions of an ordered plot node are met and the preconditions are verified, the system immediately generates a real-time plot node activation signal. This real-time plot node activation signal is a structured data object containing the following information: a unique identifier for the plot, a unique number for the ordered plot node, a descriptive text for the ordered plot node, a precise timestamp of activation, and a snapshot of the physical signal data that triggered the activation, i.e., the complete output values ​​of each sensor at the moment the activation conditions are met.

[0050] S3. Visual Presentation: Receives real-time plot node activation signals, drives the preset display components on the venue's physical sand table model, and generates a visual value evolution path that represents the evolution status of the value plot.

[0051] In a specific embodiment of the present invention, the specific steps of generating a visualized value evolution path that represents the evolution state of value plot include: the venue physical sand table model is constructed according to the actual scale of the stadium, and programmable light effect components are embedded in the positions of the corresponding player movement paths, billboards and screens.

[0052] It should be noted that a physical stadium model needs to be built and configured. This physical stadium model is a physical three-dimensional structure, and its construction principle is to scale it down to the actual proportions of the stadium. For example, if the stadium is a football field with actual dimensions of 105 meters long and 68 meters wide, the stadium model can be built at a 1:100 scale, with physical dimensions of 1.05 meters long and 0.68 meters wide. The construction materials for the stadium model use a stable structural base, usually a wooden or aluminum alloy frame, with a green synthetic material covering the surface to simulate the stadium turf. Programmable lighting components need to be embedded in the stadium model. These components use LED chips that integrate red, green, and blue light sources, and each component can independently adjust its output color and brightness. The specific deployment locations of the programmable lighting components correspond to the key physical locations on the stadium. Lighting components need to be embedded in areas corresponding to player movement paths on the stadium model. These locations are usually distributed along tactical positions such as the penalty area, midfield, and common shooting areas for forwards, with a spacing of one component every 10 centimeters. The physical model of the venue also requires the embedding of lighting components around the corresponding on-site billboard locations to mark the visual areas of commercial resources. Additionally, lighting components need to be embedded in the model areas corresponding to the screen locations to indicate trigger points for key value moments. A total of 200 programmable lighting components are embedded in the entire physical model of the venue. These components are connected via an internal electrical bus using I2C or a similar multi-master-slave communication protocol, allowing the central controller to address and control multiple components simultaneously. Each programmable lighting component has the following technical specifications: a color gamut combining red, green, and blue, capable of outputting over 16 million colors; a brightness range from 0 to 255 grayscale levels, with a brightness of 0 when completely off and a maximum brightness of 255; a response time of less than 10 milliseconds, meaning that switching is completed within 10 milliseconds after receiving a color or brightness change command; and a power consumption of 0.5 watts to 1 watt per component, centrally powered by a central power supply.

[0053] When the first real-time plot node activation signal is received, the light effect component at the corresponding physical location on the venue's physical sand table model is lit up. As subsequent real-time plot nodes are activated in sequence, the color, brightness, or illumination range of the light effect component is dynamically changed.

[0054] This creates a visualized value evolution path on the physical sand table model of the venue, reflecting the current progress of the value script execution and the intensity of potential value.

[0055] It should be noted that, secondly, a control interface needs to be established for the physical sand table model of the venue. An embedded controller is deployed within the physical sand table model. This controller is configured as an industrial-grade programmable logic controller or a small computer unit, with a processing capacity of at least 1000 commands per second. The controller connects to the main control center at the event site via a network interface, using a local area network connection with a communication latency not exceeding 50 milliseconds. An embedded operating system runs internally within the controller, which maintains a real-time event queue to cache real-time plot node activation signals. When there is an activation signal to be processed in the queue, the controller reads the ordered plot node number, activation time, and physical signal snapshot contained in the signal.

[0056] Next, a dynamic process driven by lighting effects needs to be executed. When the first real-time plot node activation signal arrives, the controller extracts the ordered plot node number from the signal. Based on the pre-established mapping table between nodes and physical locations on the sand table, the controller finds the starting position coordinates on the stadium physical sand table model corresponding to that node. Taking the first ordered plot node of the goal plot, "The forward accelerates at the edge of the penalty area," as an example, the sand table location corresponding to this node is the area near the edge of the penalty area. The controller sends a lighting command to all relevant lighting components in this area, setting the color of these components to green, indicating the start of the plot, and the brightness to 128, a medium brightness between the darkest and brightest. These components complete the color and brightness switch within 10 milliseconds of receiving the command, forming a green light spot or area on the stadium physical sand table model. When subsequent real-time plot node activation signals arrive in sequence, the controller executes a process of dynamically changing the lighting effects. For the second ordered plot node of the goal plot, "The forward shoots," the controller finds the sand table location corresponding to this node, usually inside the penalty area near the goal. The controller sends a new color command to the lighting components in that area, changing the color from green to yellow, indicating a gradual escalation of the value phase. Simultaneously, the controller keeps the lighting components at the first node illuminated, but increases the brightness from 128 to 192, indicating an increase in the intensity of this value phase.

[0057] When the activation signal for the third ordered plot node, "Goal Completed," arrives in the goal sequence, the controller executes the final lighting effect change. The controller sends instructions to all relevant lighting components on the stadium's physical model, from the edge of the penalty area to the goal, uniformly setting the color of the entire path to red to represent the climax of the value explosion, and setting the brightness to 255, the maximum brightness. This creates a continuous, bright red visual path on the stadium's physical model, from the starting position to the ending position. This path visually demonstrates the execution progress of the value script to the operations team. While creating the visualized value evolution path, the controller also needs to record the path's development status in real time. The controller maintains a state variable to store the identifier of the currently executing event plot, the sequence of activated ordered plot nodes, the activation time of each node, and the lighting effect status at the corresponding position on the model.

[0058] The meaning of visualizing the value evolution path lies in intuitively reflecting the evolutionary state of the currently activated value narrative through a sequence of light effects of different colors and brightness on the physical model of the venue. The length and extent of the path reflect the depth of the value narrative that has progressed to. The color brightness of the path reflects the intensity of the current value. If the path has extended to the final position on the physical model of the venue and the light effect is at its maximum red brightness, it indicates that the value narrative has entered its climax stage. At this point, it provides a clear visual signal to the operations staff, indicating that corresponding business intervention should be carried out.

[0059] S4. Physical Authorization Capture: Based on the value growth trend indicated by the visualized value evolution path, when a physical token representing a business resource is detected being inserted into a designated physical slot on the venue's physical sand table model, a physical token authorization instruction binding the resource and timing is generated.

[0060] In a specific embodiment of the present invention, the specific steps of generating the physical token authorization instruction that binds resources and timing include: the physical token is a physical card with an embedded identity recognition chip, and each physical token uniquely corresponds to a commercial resource.

[0061] It should be noted that the unique commercial resource corresponding to each physical token needs to be mapped through pre-configuration before the event. This mapping is stored in a database within the embedded controller of the venue's physical model. The database is structured as key-value pairs, where the key is the 96-bit identifier of the physical token, and the value is a detailed description of the commercial resource corresponding to that token. Examples of commercial resources include "the right to play a 30-second brand advertisement for a specific sponsor A," "the right to switch to close-up shots on the live broadcast camera," and "the right to render the theme of the stadium's lighting and sound system," etc.

[0062] When the visualized value evolution path reaches the preset value climax stage, the system detects that the physical token corresponding to the commercial resource has been inserted into the physical slot of the venue's physical sand table model, reads the identity of the physical token, and generates a physical token authorization instruction in combination with the current timestamp.

[0063] It should be noted that, secondly, physical slots need to be set on the physical model of the venue. These physical slots are recessed structures on the surface of the model, and their shape and size are adapted to the physical tokens. The positions of the physical slots correspond one-to-one with the key positions in the visualized value evolution path. Taking the goal scenario as an example, one physical slot is set on the model at the edge of the penalty area, the center of the penalty area, and the goal position. The position numbers of these slots correspond to different value stages. For example, slot number 1 corresponds to the "forward acceleration" value stage, slot number 2 corresponds to the "shooting" value stage, and slot number 3 corresponds to the "goal completed" value stage. Each physical slot is equipped with a proximity sensor, which is an inductive linear displacement sensor that can detect the insertion status of the physical token. When the physical token is fully inserted into the slot, the sensor outputs a high-level signal. When the physical token is removed, the sensor output returns to a low level. At the position where the physical token is inserted, an ultra-short-range RFID reader is also installed. This reader automatically starts the reading process after detecting the token insertion.

[0064] Secondly, it is necessary to establish decision-making and operational processes for operations personnel. Operations personnel are members of the on-site commercial operations team, typically seated facing the sand table model, allowing them a clear view of the dynamic display of the visualized value evolution path. They make real-time judgments based on the development status of this path. As the visualized path gradually extends along the sand table model, and the brightness and saturation of the lighting effects continuously increase, operations personnel recognize that the value narrative is gradually escalating. When the sand table model exhibits the following three characteristics, operations personnel determine that the value climax has arrived: First, the visualized path has extended from its starting position to the preset climax position, typically representing a key value point on the sand table model. Second, all lighting components along the path are red or the color with the highest brightness. Third, the brightness of the visualized path reaches 255, the maximum brightness level. After determining that the value climax has arrived, operations personnel need to select an appropriate physical token for insertion. This selection is based on two factors: First, the current value narrative type. For example, if the currently activated narrative is "Goal Moment," operations personnel might select the token corresponding to "Brand Advertising Playback Rights." Second, the priority arrangement of available commercial resources. Before the event, planners create a resource priority list for different value scenarios. For example, during a goal, a high-priority resource might be a 30-second ad from the main sponsor, while a medium-priority resource would be a 15-second ad from a secondary sponsor. Operations personnel start with the high-priority resources and sequentially select appropriate tokens to insert. When an operations person inserts a selected physical token into the physical slot on the sandbox model that matches the current value stage, that physical action constitutes an authorization input to the system.

[0065] Finally, a sensor detection and authorization command generation mechanism needs to be established. When a physical token is inserted into a physical slot, the proximity sensor inside the slot first detects the change in the token's insertion status. After the token is fully inserted, the sensor outputs a high-level signal. The embedded controller in the sandbox model monitors the output status of all slot sensors. When the controller detects that the sensor status of a slot changes from low to high, it immediately activates the RFID reader in that slot. The reader sends an RF activation signal to the token, and the token responds to the reader's request by sending its internal 96-bit identity code back to the reader via RF signal. The reader receives and parses the identity code and forwards it to the embedded controller.

[0066] Upon receiving the token identification code, the embedded controller immediately records the current timestamp. This timestamp is synchronized by the central time server mentioned in step S2, with millisecond precision. Simultaneously, the controller queries the value stage state variable within the sandbox model. This variable records the currently executing event scenario, the activated ordered sequence of event nodes, and the corresponding value stage level. The controller structures and encapsulates the four pieces of information—the token identification code, the current millisecond timestamp, the current value stage level, and the slot number—to generate a physical token authorization instruction. This instruction is formatted as a structure containing four fields: the first field is the resource identity, storing the commercial resource number corresponding to the token identification code; the second field is the authorization time, storing the absolute timestamp of the token insertion moment in the format "hour:minute:second.millisecond"; the third field is the value stage marker, storing the current value event type and its node sequence number; and the fourth field is the slot number, used for subsequent operation traceability.

[0067] S5. Resource Verification and Scheduling: Parse the physical token authorization instruction, extract the resource identity and authorization time information contained therein, and generate a high-priority resource scheduling request to be executed.

[0068] In a specific embodiment of the present invention, the specific steps of generating a high-priority resource scheduling request to be executed include: verifying whether the resource identity contained in the physical token authorization instruction matches the type of interferable resource pre-defined in the currently activated value script.

[0069] Once the verification is successful, the execution priority of the resource that matches the pre-defined type of intervenable resource in the currently activated value script will be raised to the highest level.

[0070] By combining the authorization time information in the instruction, a high-priority resource scheduling request is formed.

[0071] It should be noted that a module for receiving and parsing physical token authorization instructions needs to be established. This module is deployed in the main control center at the event site and connected to the sand table model controller of step S4 via a wired network. The receiving module in the main control center maintains an instruction queue to cache physical token authorization instructions from step S4. When step S4 generates a new physical token authorization instruction, the instruction is immediately appended to the tail of the receiving queue. The receiving module checks the queue for any new instructions to be processed at a polling frequency of 100 times per second. When a new instruction is detected, the receiving module immediately retrieves the instruction from the head of the queue for subsequent processing. The parsing process of physical token authorization instructions involves extracting four fields from the instruction. The first field is the resource identity, which contains the number of the commercial resource, an integer value ranging from 1 to 200. In the example of the goal moment, the value of this field is 1, corresponding to the "30-second playback right of the main sponsor's brand advertisement" resource. The parsing module reads this value and records it as the resource identity to be verified. The second field is the authorization time, which contains the precise moment the physical token was inserted, formatted as a six-tuple of hours, minutes, seconds, and milliseconds. In the example of the goal moment, this field's value is 15 hours, 30 minutes, 1 second, and 620 milliseconds. The parsing module reads this value and records it as the authorization moment for the commercial resource, which is used in subsequent steps to ensure the precise timing of resource execution. The third field is the value stage marker, which contains the currently executing event plot type, the activated ordered plot node number, and the current value stage level. In the example of the goal moment, this field's value is "Goal Moment - Node 3 - Climax Stage". The parsing module reads this value and breaks it down into three sub-information: the event plot identifier is "Goal Moment", the ordered plot node number is 3, and the value stage level is "Climax". The fourth field is the slot number, which records the slot position number on the sandbox model where the physical token was inserted. In the example of the goal moment, this field's value is 3, indicating that the token was inserted into the physical slot corresponding to the goal position. The parsing module reads this value for event tracing and operation log recording.

[0072] Secondly, it is necessary to verify the matching between resource identities and currently activated value scenarios. The purpose of this verification process is to ensure that the commercial resources selected by the operations personnel match the currently executing event scenario, preventing the misuse or waste of resources. Before the event, a pre-defined list of operable resource types is configured for each event scenario. This list defines which commercial resources the system allows to intervene during the execution of that event scenario. Taking the "Goal Moment" event scenario as an example, the list of operable resource types for this scenario might include resource numbers 1, 2, 3, 4, and 5, corresponding to commercial resources such as "30-second ad for the main sponsor," "15-second ad for the secondary sponsor," "brand interaction segment," "on-site lighting rendering," and "screen content display," respectively. This list is stored in the configuration database of the event's main control center, using the event scenario identifier as the index key. The specific steps of the verification process are as follows: First, the verification module extracts the event scenario identifier from the parsed value stage markers. In the example of "Goal Moment," "Goal Moment" is extracted. The verification module uses this identifier as an index to query the configuration database and obtain the list of operable resource types corresponding to this event scenario. The query result is an array containing all resource IDs allowed for that event scenario. Next, the verification module compares the resource identity parsed from the physical token authorization instruction with this list. The verification module checks if the resource ID exists in the list array. In the example of a goal, the parsed resource identity is 1, and the list array contains 1, 2, 3, 4, and 5. The check result shows that resource ID 1 exists in the list. Therefore, the verification passes. If the verification passes, the verification module generates a successful verification flag and continues with the subsequent priority escalation process. If the verification fails, i.e., the resource ID does not exist in the list of operable resource types, the verification module generates a verification failure flag and logs the event to the system log. For instructions with failed verification, the system removes them from the processing flow and does not generate high-priority resource scheduling requests, thereby preventing non-compliant commercial resources from being executed at inappropriate times.

[0073] Secondly, the execution priority of verified commercial resources needs to be elevated to the highest level. On-site equipment, such as the broadcast control console, advertising servers, and lighting control consoles, have several task queues registered in the system. These task queues are sorted by priority, with higher-priority tasks executed first. The system defines five priority levels: lowest level 1, low level 2, medium level 3, high level 4, and highest level 5. Regular live broadcast tasks, such as normal camera transitions and regular advertising playback, are typically set to a medium level 3 or low level 2 priority. To ensure the timely realization of commercial resources at their peak value, the system needs to elevate the execution priority of these commercial resources to the highest level, 5.

[0074] The priority elevation mechanism involves the management of all execution queues in the system. Internally, the system maintains a global queue priority management table, which records all registered execution queues and their priority settings. When the execution priority of a resource needs to be elevated, the system modifies the priority flag of the execution queue corresponding to that resource, changing it from its original priority to the highest level, 5. For tasks related to that resource already waiting in the execution queue, the system calls a task reordering function to move the task to the front of the corresponding execution queue, ensuring that the task is executed before all other tasks complete. If an execution device in the system is currently executing a low-priority task, and a newly arrived commercial resource scheduling request is set to the highest priority, the system can trigger an interruption mechanism to suspend the execution of the low-priority task and immediately begin executing the high-priority commercial resource task. The low-priority task before the interruption can be recorded in the task queue to be resumed; after the commercial resource task is completed, the interrupted task will continue to execute.

[0075] Finally, a high-priority resource scheduling request needs to be generated. The structure of a high-priority resource scheduling request includes the following fields: The first field is the resource identity, directly inherited from the resource identity field in the physical token authorization instruction, which is 1 in the example of the goal moment. The second field is the authorization time, directly inherited from the authorization time field in the physical token authorization instruction, which is 15 hours 30 minutes 1 second 620 milliseconds in the example of the goal moment. The third field is the priority flag, which is set to the highest level of 5, indicating that this resource scheduling request has the highest system execution priority. The fourth field is the source information, recording that the request originated from the physical token authorization instruction in step S4, and containing complete context information when the instruction was generated. The fifth field is the verification status, recording that the request has passed resource authentication in step S5, with a value of "passed". These fields are organized into a structure, which together constitute the high-priority resource scheduling request.

[0076] S6. Intervention instruction encapsulation: Based on high-priority resource scheduling requests, retrieve and lock the corresponding execution instruction set from the preset resource package, and generate an instant intervention instruction package containing specific operation parameters.

[0077] In a specific embodiment of the present invention, the specific steps of generating an instant intervention instruction package containing specific operation parameters include: pre-configuring resource packages containing operation instructions for various commercial resources, wherein the operation instructions specify the type of equipment to be scheduled and the specific action to be performed.

[0078] It should be noted that, firstly, pre-configuration of various commercial resources needs to be completed before the event. This pre-configuration includes creating a complete resource package for each commercial resource, containing all the operational instructions required for that resource during the event execution. The resource package structure is as follows: Each resource package is organized in key-value pairs, where the key is a unique identifier for the commercial resource, an integer ranging from 1 to 200. The value is an instruction set object, containing all the specific operational instructions that the resource may need to execute at different value stages. Taking the "30-second playback right of the main sponsor's brand advertisement" corresponding to resource number 1 during the goal moment as an example, its resource package contains multiple operational instructions. The format of the operational instructions follows a unified standardized structure. Each operational instruction contains five basic fields: The first field is the device type, indicating the target execution device to which the operational instruction needs to be sent. Device types include "director console," "advertising server," "lighting control console," "sound system," "screen controller," etc. In the example of the goal moment, the device type for the advertisement playback operational instruction of resource number 1 is "advertising server." The second field is the execution action, describing the specific operation that the device needs to perform. Examples include "play video footage," "switch to a specified shot," and "change light color." For an ad playback command, the action is "play video footage." The third field is the action parameter, providing specific parameter information required to execute the action. Parameters may include the footage ID, shot ID, duration, color code, etc. Taking the ad playback command as an example, the parameter is an object containing three sub-parameters: the footage ID is "AD_001_SPONSOR_A," the playback duration is 30000 milliseconds, and the playback priority is the highest level. The fourth field is the execution time constraint, specifying the execution time or execution time window of the operation command. This field can be an absolute timestamp or a relative time offset. In the example of the goal moment, the execution time constraint is "execute immediately," meaning that execution begins immediately without delay after receiving the command packet. The fifth field is the status tracking flag. This field is initially set to "not executed" and is used to record the execution status of the operation command in subsequent steps. It will be updated to "executed" after execution is completed.

[0079] During pre-event configuration, operations personnel or system administrators need to define a corresponding resource package for each commercial resource. This process typically takes place before the event, using a centralized configuration interface or configuration file. Operations personnel first select a commercial resource and enter its resource number. The system displays a description of the resource, such as "30-second playback right for the main sponsor's brand advertisement." Operations personnel then configure one or more operation commands for the resource. For example, to achieve the goal of "playing the advertisement," operations personnel might configure the following sequence of operation commands: The first command is "Switch the control panel to the live screen source," with parameters including the screen number and source switching mode. The second command is "Play the main sponsor's advertising material on the advertising server," with parameters including the material number "AD_001_SPONSOR_A," a playback duration of 30,000 milliseconds, and a playback start time equal to the authorized time plus a 50-millisecond delay. The third command is "Render the brand-colored lighting around the screen on the lighting control panel," with parameters including the color code and rendering intensity. This sequence of operation commands is organized into an array and stored in the resource package corresponding to the resource number. The resource packages are stored in a centralized command database in the event's main control center. This database is implemented using a relational database or key-value store system, such as SQL database or Redis caching system. To support fast retrieval and access, the database establishes an index mapping from resource numbers to instruction sets. This index mapping takes the form of a hash table, where the key is the resource number and the value is the memory address or database row number of the corresponding operation instruction array for that resource.

[0080] Based on the resource identity in the high-priority resource scheduling request, a quick search is performed in the resource package to locate the unique corresponding instruction set.

[0081] It should be noted that, secondly, the retrieval module receives a high-priority resource scheduling request from step S5. The retrieval module extracts the resource identity field from this request, which contains the resource's ID. In the example of the goal moment, the resource identity is 1. The retrieval module uses this resource ID as the key to perform a fast query in the instruction database's index mapping. The query returns the operation instruction set corresponding to resource ID 1. This operation instruction set is an array containing the three operation instruction sequences described earlier. The retrieval module then executes an instruction locking process. The purpose of this process is to prevent the same operation instruction set from being reused in multiple concurrent high-priority resource scheduling requests. After retrieving the operation instruction set, the retrieval module sets a mutex lock flag on the instruction set. This flag indicates that the instruction set is currently being processed by a high-priority resource scheduling request, and other requests are not allowed to operate on it simultaneously.

[0082] Load the instruction set to generate an immediate intervention instruction package.

[0083] It should be noted that, again, the parameter loading and instruction package encapsulation process for the operation instructions needs to be performed. The purpose of the parameter loading process is to dynamically populate the parameters in the pre-configured operation instructions in the resource package. Although the basic structure of the operation instructions has been configured before the game, some parameters, such as the execution time constraint, need to be updated in step S6 based on the current high-priority resource scheduling request. The specific process is as follows: The retrieval module obtains the authorization time field from the high-priority resource scheduling request. This field records the precise moment when the physical token was inserted. Taking the moment of a goal as an example, the authorization time is 15 hours, 30 minutes, 1 second, and 620 milliseconds. The retrieval module iterates through each operation instruction in the operation instruction set. For each instruction, the retrieval module checks the value of its execution time constraint field. If the field is "Execute Immediately," it means that the instruction should be executed immediately without delay after being received, and the retrieval module does not need to modify this value. If the field is a relative time offset, such as "authorization time plus 50 milliseconds", the retrieval module calculates the absolute execution time of the instruction, that is, the authorization time of 15 hours 30 minutes 1 second 620 milliseconds plus 50 milliseconds equals 15 hours 30 minutes 1 second 670 milliseconds. The retrieval module fills this absolute execution time into the instruction's execution time constraint field.

[0084] After the parameters are loaded, the retrieval module needs to structurally encapsulate the operation instruction set to generate an instant intervention instruction package. The instant intervention instruction package contains the following fields: The first field is the instruction package identifier, a globally unique string or number used to uniquely identify the instruction package. The identifier is automatically generated by the retrieval module using a timestamp plus a random number, in the format "PKG_" followed by a 13-digit millisecond timestamp plus a 4-digit random hexadecimal number, for example, "PKG_1735689601620_A3F7". The second field is the resource identity, directly copied from the resource identity field in the high-priority resource scheduling request; in the example of the goal, it is 1. The third field is the authorization time, directly copied from the authorization time field in the high-priority resource scheduling request; in the example of the goal, it is 15:30:01.620. The fourth field is the priority flag, directly copied from the priority flag field in the high-priority resource scheduling request; in the example of the goal, it is the highest level, 5. The fifth field is the operation instruction sequence, an array containing all operation instruction objects. Each operation instruction object contains complete information after parameter loading, including device type, action to be performed, parameters, and execution time constraints. The sixth field is the generation timestamp, recording the precise moment the immediate intervention instruction package was generated, in a six-tuple format of hours, minutes, seconds, and milliseconds. The seventh field is source tracing information, containing the identifier of the original high-priority resource scheduling request, the identifier of the source physical token authorization instruction, and the chain of earlier value playbook activation signals, used for complete event tracing and logging.

[0085] S7. Execution Log Generation: Distribute the real-time intervention instruction package to the corresponding execution device at the event site, drive the execution device to complete the real-time realization of commercial value, and generate a value realization execution log that records the entire intervention process.

[0086] In a specific embodiment of the present invention, the specific steps of generating a value realization execution log that records the entire intervention process include: sending each specific instruction in the real-time intervention instruction package to the broadcast control station, advertising server and on-site lighting and sound control station respectively through the internal control network.

[0087] It is important to note that, firstly, an internal control network architecture needs to be established for the event venue. This network is a dedicated, closed communication system used to connect the main control center of the event with various execution devices on site. The internal control network adopts a star topology, with the central node being the command distribution module of the main control center. This module connects to the various execution device nodes on the periphery via wired Ethernet or an industrial-grade wireless network. To ensure network reliability and real-time performance, the internal control network uses dedicated physical links and does not share them with the venue's public network. Each execution device node in the network is assigned a unique device identifier and a fixed IP address within the local area network. The types of execution devices include five main categories of on-site execution devices: broadcast control consoles, advertising playback servers, lighting control systems, sound amplifiers, and screen display controllers. The internal control network uses a custom command communication protocol for data transmission. This protocol uses a binary message format, with each message containing a message header, message body, and checksum. The message header includes the sender identifier, receiver identifier, message type, message sequence number, and message timestamp. The message body contains the specific operation instructions. The checksum uses a cyclic redundancy check (CRC) to detect errors during message transmission. The maximum message length is 4096 bytes, the transmission rate is 100 megabits per second, and the transmission delay of instructions is guaranteed to be no more than 50 milliseconds.

[0088] Secondly, the distribution of instruction packets within the network needs to be executed. The instruction distribution module is deployed in the main control center of the event, adjacent to the instruction generation module of step S6. The instruction distribution module maintains a device routing table, which records the mapping relationship between the device type of each operation instruction in the real-time intervention instruction packet and the actual device node in the internal control network. The specific steps of the distribution process are as follows: The instruction distribution module retrieves the real-time intervention instruction packet generated by S6 from the queue of instruction packets to be distributed. The distribution module records the current timestamp as the start time of instruction distribution, with a precision of milliseconds. The distribution module traverses the sequence of operation instructions in the real-time intervention instruction packet. For each operation instruction, the distribution module first extracts the device type field of the instruction, such as "director console". The distribution module uses the device type as an index to look up the network address of the corresponding actual device node in the device routing table. Taking the moment of a goal as an example, the network address of the device corresponding to the "director console" type instruction is "192.168.10.101". The distribution module packages the operation instruction according to the format of a custom communication protocol. The packaging process includes constructing a message header, which includes information such as the sender being the "Main Control Center Command Distribution Module," the receiver being the device network address "192.168.10.101," the message type being "Operation Command," the message sequence number being an incrementing sequence number, and the message timestamp being the current millisecond-level timestamp. The packaging process also includes encoding the content of the operation command as the message body, including the action to be performed and action parameters. Finally, the packaging process calculates the cyclic redundancy check (CRC) code for the entire message and appends it to the message trailer.

[0089] The complete network message is handed over to the network sending module, which then sends the message to the designated device node via the physical link of the internal control network. Message transmission employs a reliable transmission mechanism. The sending module records the message transmission time and waits for a reception acknowledgment signal from the receiving device. If no acknowledgment signal is received within the specified timeout period, the sending module automatically retryes sending the message, up to three times. If no acknowledgment signal is received after three retries, the distribution module records the device as being in a "communication failure" state and generates an alarm log.

[0090] Upon receiving the instruction, the device immediately performs operations such as switching cameras, inserting advertisements, and rendering a light show.

[0091] It should be noted that, again, the execution process is illustrated using the director's console as an example. The director's console is equipped with an embedded device controller connected to the internal control network. The controller continuously listens for incoming messages on the network. When it receives an operation instruction message from the main control center, the controller immediately performs message format verification, including verifying the message header and the cyclic redundancy check (CRC) code. If the format verification fails, the controller discards the message and records the error. If the format verification passes, the controller extracts the operation instruction content from the message body. In the example of the goal moment, the operation instruction is to "switch to the live screen source," with action parameters including screen number 1 and source switching mode "HD live stream." The controller parses this content and generates the corresponding internal control instruction. For the director's console, the internal control instruction specifies switching its output source from the current source to the live screen source. The controller checks the execution time constraint field of the operation instruction. This field is "execute immediately," indicating that no delay is required. The controller immediately sends internal control signals to the hardware devices of the director's console, driving the director's mixer to perform the camera switching operation.

[0092] Upon receiving the internal control signal, the mixing console immediately executes the actual hardware control actions. Hardware switching typically takes between 10 and 100 milliseconds. After switching, the mixing console returns an execution completion signal to the embedded controller. The embedded controller receives the execution completion signal and records the completion time of the operation instruction with millisecond precision. The controller sends an execution confirmation message to the main control center, containing the operation instruction number, execution start time, execution completion time, and execution status as "successful." Similar execution processes occur in parallel on other execution devices. Upon receiving the "play video material" instruction, the advertising server immediately reads the video file corresponding to the material number "AD_001_SPONSOR_A" from the material library and begins playback according to the parameters in the instruction. The video playback duration is 30,000 milliseconds. The volume level is 100. The playback start time is constrained to 15:30:01.670 according to the instruction's execution time constraint. During playback, the advertising server monitors the video playback status and returns an execution confirmation message to the main control center upon completion.

[0093] Upon receiving the instruction to "render brand color scheme lighting," the lighting control system immediately adjusts the color parameters of the lighting equipment. The color code specified in the instruction is RGB values ​​255, 100, and 0, corresponding to the brand's primary color, orange. The lighting system sets the rendering intensity to 80%, meaning the light brightness is set to 80% of its maximum. The lighting system specifies the rendering range as an area with a radius of 2 meters around the screen. It retrieves the location information of the lighting equipment it controls, identifies all lighting fixtures within this range, and issues color and brightness change instructions to these fixtures. All lighting fixtures complete the color switch within 10 milliseconds, creating a bright orange area of ​​light in the corresponding area of ​​the sand table model. After the light switch is complete, the lighting control system returns an execution confirmation message to the main control center.

[0094] Synchronously record the entire timeline from the activation of the value script to the completion of the instruction execution, including timestamps, resources used, and final results, and generate a value realization execution log.

[0095] It should be noted that, finally, a complete value realization execution log needs to be generated. This log records the complete timeline and operational process from the activation of the value playbook to the completion of all instructions. The structure of the value realization execution log is designed as follows: The log is a structured data record containing the following fields: The first field is the log identifier, which is a globally unique identifier generated using a timestamp plus a random number. The second field is the event information, including basic information such as the event name, opponent, and event date. The third field is the value playbook information, including the identifier of the activated value playbook, the event plot type, and the sequence number of the ordered plot node. The fourth field is the timeline, which is the most important part of the log, containing multiple timestamp nodes: the value playbook activation time, the real-time plot node activation signal generation time, the time the visualized value evolution path is illuminated, the time the operator inserts the physical token, the time the physical token authorization instruction is generated, the time the high-priority resource scheduling request is generated, the time the immediate intervention instruction package is generated, the instruction distribution start time, the instruction reception time of each execution device, the operation execution start time of each execution device, and the operation execution completion time of each execution device. All timestamps are recorded with millisecond precision.

[0096] The fifth field is resource usage information, including the inserted physical token number, the corresponding commercial resource number, the description of the commercial resource, and the resource authorization time. The sixth field is instruction execution information, including the identifier of the generated real-time intervention instruction package, the total number of operation instructions contained within, and the detailed content of each operation instruction. The seventh field is device execution results, including the execution status of each executing device. For each executing device, it records its device type, device network address, whether the instruction was successfully received, whether the instruction was successfully executed, whether errors occurred during execution, and the final execution result. The eighth field is performance metrics, including the processing latency at each stage of the system, such as the latency from value script activation to visualization path display, the latency from physical token insertion to authorization instruction generation, the latency from authorization instruction to resource scheduling request, the latency from resource scheduling request to instruction package generation, and the latency from instruction package generation to execution completion. The ninth field is effect evaluation, including whether the final commercial resource realization was successful, whether it was completed within the specified time, and whether the expected visual or dissemination effects were achieved. The tenth field is remarks and exception records, including any abnormal situations, error messages, and the handling measures taken during execution.

[0097] The value realization execution log is fully generated after each operation command in the real-time intervention instruction package is executed and persistently stored in the event log database of the event's main control center. This database is implemented using a time-series database or a relational database, supporting fast queries based on dimensions such as date, event details, and resource number. The value realization execution log can then be used for various purposes, including post-event analysis, business value assessment, and system performance optimization.

[0098] Reference Figure 2 The second aspect of the present invention provides a comprehensive commercial value dynamic prediction system for sports events, including: a value script generation module, a real-time plot recognition module, a visualization presentation module, a physical authorization capture module, a resource verification and scheduling module, an intervention instruction encapsulation module, and an execution log generation module.

[0099] The value script generation module is connected to the real-time plot recognition module, the real-time plot recognition module is connected to the visualization presentation module, the visualization presentation module is connected to the physical authorization capture module, the physical authorization capture module is connected to the resource verification and scheduling module, the resource verification and scheduling module is connected to the intervention instruction encapsulation module, and the intervention instruction encapsulation module is connected to the execution log generation module.

[0100] The value script generation module defines a set of value scripts containing ordered plot nodes and corresponding physical signal activation conditions.

[0101] The real-time plot recognition module monitors the physical signals at the event site in real time, continuously compares the physical signals with the set of value scripts, identifies and outputs the real-time plot node activation signal that matches the activation conditions of a certain ordered plot node in the set of value scripts.

[0102] The visualization module receives real-time plot node activation signals and drives the preset display components on the venue's physical sand table model to generate a visualized value evolution path that represents the evolution state of the value plot.

[0103] The physical authorization capture module generates a physical token authorization instruction that binds resources and timing when it detects that a physical token representing commercial resources is inserted into a designated physical slot on the venue's physical sand table model, based on the value growth trend indicated by the visualized value evolution path.

[0104] The resource verification and scheduling module parses the physical token authorization instruction, extracts the resource identity and authorization time information contained therein, and generates a high-priority resource scheduling request to be executed.

[0105] The intervention instruction encapsulation module retrieves and locks the corresponding execution instruction set from the preset resource package according to the high-priority resource scheduling request, and generates an instant intervention instruction package containing specific operation parameters.

[0106] The execution log generation module distributes real-time intervention instruction packages to the corresponding execution devices at the event site, drives the execution devices to complete the real-time realization of commercial value, and generates a value realization execution log that records the entire intervention process.

[0107] The above content is merely an example and illustration of the concept of the present invention. Those skilled in the art can make various modifications or additions to the specific embodiments described, or use similar methods to replace them, as long as they do not deviate from the concept of the invention or exceed the scope defined by the present invention, and all such modifications and additions should fall within the protection scope of the present invention.

Claims

1. A method for dynamic prediction of the comprehensive commercial value of sports events, characterized in that, include: S1. Value Script Generation: Define a set of value scripts containing ordered plot nodes and corresponding physical signal activation conditions; S2. Real-time plot recognition: Real-time monitoring of physical signals at the event site, continuous comparison of physical signals with the set of value scripts, identification and output of real-time plot node activation signals that match the activation conditions of an ordered plot node in the set of value scripts. S3. Visual Presentation: Receives real-time plot node activation signals, drives the preset display components on the venue's physical sand table model, and generates a visual value evolution path that represents the evolution status of the value plot. S4. Physical Authorization Capture: Based on the value growth trend indicated by the visualized value evolution path, when a physical token representing commercial resources is detected to be inserted into a designated physical slot on the venue physical sand table model, a physical token authorization instruction binding resources and timing is generated. S5. Resource Verification and Scheduling: Parse the physical token authorization instruction, extract the resource identity and authorization time information contained therein, and generate a high-priority resource scheduling request to be executed; S6. Intervention instruction encapsulation: Based on high-priority resource scheduling requests, retrieve and lock the corresponding execution instruction set from the preset resource package, and generate an instant intervention instruction package containing specific operation parameters; S7. Execution Log Generation: Distribute the real-time intervention instruction package to the corresponding execution device at the event site, drive the execution device to complete the real-time realization of commercial value, and generate a value realization execution log that records the entire intervention process.

2. The method for dynamic prediction of comprehensive commercial value for sports events according to claim 1, characterized in that, The specific steps for defining a set of value scripts containing ordered plot nodes and corresponding physical signal activation conditions include: Break down the events in a sports event that meet the conditions for commercial value into at least two ordered event nodes arranged in chronological order; For each ordered plot node, a set of physical signal combinations collected by sensors in the venue is set as its unique activation condition. The physical signal combinations include player positioning data, player movement posture data, and ambient sound decibel values. All ordered plot nodes and their associated physical signal activation conditions are structurally combined to form a set of valuable scripts.

3. The method for dynamic prediction of comprehensive commercial value for sports events according to claim 1, characterized in that, The specific steps for identifying and outputting a real-time plot node activation signal that matches the activation condition of an ordered plot node in the value script set include: By using positioning and posture sensors worn by players, as well as sound recording equipment deployed in key areas of the stadium, the system continuously acquires the players' real-time position, acceleration changes, and ambient sound decibel levels. The timestamps of the acquired player's real-time position, acceleration changes, and ambient sound decibel values ​​are aligned to form a multi-dimensional real-time physical signal stream; The system performs a cyclical matching and judgment process between the real-time physical signal stream and the activation conditions of each ordered plot node in the set of value scripts. Once a match is successful, a real-time plot node activation signal is immediately generated.

4. The method for dynamic prediction of comprehensive commercial value for sports events according to claim 1, characterized in that, The specific steps for generating a visualized value evolution path representing the state of value plot evolution include: The physical sand table model of the venue is constructed according to the actual scale of the stadium, and programmable light effect components are embedded in the positions of the corresponding player movement paths, billboards and screens. When the first real-time plot node activation signal is received, the light effect component at the corresponding physical location on the venue's physical sand table model is lit up. As subsequent real-time plot nodes are activated in sequence, the color, brightness, or lighting range of the light effect component is dynamically changed. This creates a visualized value evolution path on the physical sand table model of the venue, reflecting the current progress of the value script execution and the intensity of potential value.

5. The method for dynamic prediction of comprehensive commercial value for sports events according to claim 1, characterized in that, The specific steps for generating the physical token authorization instruction that binds resources and timing include: The physical token is a physical card with an embedded identity recognition chip, and each physical token uniquely corresponds to a commercial resource; When the visualized value evolution path reaches the preset value climax stage, the system detects that the physical token corresponding to the commercial resource has been inserted into the physical slot of the venue's physical sand table model, reads the identity of the physical token, and generates a physical token authorization instruction in combination with the current timestamp.

6. The method for dynamic prediction of comprehensive commercial value for sports events according to claim 1, characterized in that, The specific steps for generating a high-priority resource scheduling request to be executed include: Verify that the resource identity contained in the physical token authorization instruction matches the pre-defined type of the operable resource in the currently activated value playbook; Once the verification is successful, the execution priority of the resource that matches the pre-defined type of intervenable resource in the currently activated value script will be raised to the highest level. By combining the authorization time information in the instruction, a high-priority resource scheduling request is formed.

7. The method for dynamic prediction of comprehensive commercial value for sports events according to claim 1, characterized in that, The specific steps for generating the real-time intervention instruction package containing specific operational parameters include: Resource packages containing operation instructions are pre-configured for various commercial resources. The operation instructions specify the type of equipment to be scheduled and the specific actions to be performed. Based on the resource identity in the high-priority resource scheduling request, a quick search is performed in the resource package to locate the unique corresponding instruction set; Load the instruction set to generate an immediate intervention instruction package.

8. The method for dynamic prediction of comprehensive commercial value for sports events according to claim 1, characterized in that, The specific steps for generating a value realization execution log that records the entire intervention process include: Through the internal control network, the specific instructions in the real-time intervention instruction package are sent to the broadcast control station, advertising server and on-site lighting and sound control station respectively. Upon receiving the instruction, the execution device immediately performs operations such as switching cameras, inserting advertisements, and rendering a light show; Synchronously record the entire timeline from the activation of the value script to the completion of the instruction execution, including timestamps, resources used, and final results, and generate a value realization execution log.

9. A comprehensive commercial value dynamic prediction system for sports events, characterized in that, include: The value script generation module defines a set of value scripts containing ordered plot nodes and corresponding physical signal activation conditions. The real-time plot recognition module monitors the physical signals at the event site in real time, continuously compares the physical signals with the set of value scripts, identifies and outputs the real-time plot node activation signal that matches the activation condition of a certain ordered plot node in the set of value scripts. The visualization module receives real-time plot node activation signals, drives the preset display components on the venue's physical sand table model, and generates a visualized value evolution path that represents the evolution status of the value plot. The physical authorization capture module, based on the value growth trend indicated by the visualized value evolution path, generates a physical token authorization instruction that binds resources and timing when it detects that a physical token representing commercial resources is inserted into a designated physical slot on the venue's physical sand table model. The resource verification and scheduling module parses the physical token authorization instruction, extracts the resource identity and authorization time information contained therein, and generates a high-priority resource scheduling request to be executed. The intervention instruction encapsulation module retrieves and locks the corresponding execution instruction set from the preset resource package based on the high-priority resource scheduling request, and generates an instant intervention instruction package containing specific operation parameters. The execution log generation module distributes real-time intervention instruction packages to the corresponding execution devices at the event site, drives the execution devices to complete the real-time realization of commercial value, and generates a value realization execution log that records the entire intervention process.

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