A dynamic presentation strategy generation and management method for cultural relic display

Abstract

This invention provides a method for generating and managing dynamic presentation strategies for cultural relic displays, comprising: generating exhibit identifiers and establishing exhibit configuration records; constructing a parameter model including a set of display control parameters and allowed value ranges; establishing a ternary digital twin model of exhibits and defining a unified state vector; establishing a set of cultural relic protection constraints and configuring risk thresholds and operating thresholds; collecting multi-source data and performing missing data completion and anomaly correction; generating aligned data streams according to sliding time windows and updating the digital twin model to form a current state snapshot; calculating cultural relic risk indicators and the maximum risk within a prediction window based on the current state snapshot; calculating the audience experience evaluation quantity; under the constraint that the maximum risk within the prediction window does not exceed the risk threshold, solving for the dynamic presentation strategy with the audience experience evaluation quantity as the optimization objective, and generating a strategy version record; and distributing the dynamic presentation strategy to the exhibit display terminal and performing readback verification.

Description

Technical Field

[0001] This invention relates to the field of digital display and intelligent control technology for cultural relics, and in particular to a method for generating and managing dynamic presentation strategies for cultural relic display. Background Technology

[0002] With the development of digital exhibition technology, cultural relic exhibits often use display terminals, intelligent lighting systems, and interactive sensing devices to dynamically present the content. Existing cultural relic display control systems can typically collect basic data such as ambient temperature and humidity, illuminance, and visitor flow, and will issue alarms or passively intervene when the monitored values ​​exceed preset safety thresholds.

[0003] However, the fluctuations in the regional microenvironment caused by the high-intensity stay and interaction of visitors, coupled with the heat load from the long-term operation of display equipment (such as high-brightness display terminals and multi-level content playback), have a significant lag and cumulative impact on the risk indicators of the cultural relics themselves. Existing technologies only respond to a snapshot of the "current moment" and fail to pre-calculate the maximum potential risks that the combination of parameters may cause in the future prediction window before issuing new display brightness or display rhythm parameters. This "hindsight" control often results in the microenvironment deteriorating by the time an alarm is triggered, leading to a passive situation of "protection equals shutdown." Therefore, we propose a dynamic presentation strategy generation and management method for cultural relic displays.

[0004] The information disclosed in the background section is only intended to enhance the understanding of the background of this disclosure, and therefore may include information that does not constitute prior art known to those skilled in the art. Summary of the Invention

[0005] The purpose of this invention is to address the shortcomings of existing technologies by providing a method for generating and managing dynamic presentation strategies for cultural relic displays, thereby resolving the technical problems mentioned in the background section.

[0006] To achieve the above objectives, the present invention provides the following technical solution: A method for generating and managing dynamic presentation strategies for cultural relics displays includes the following steps: S1. Obtain basic information of exhibits, generate exhibit identifiers, establish exhibit configuration records, write display control parameter set, write control parameters into mapping table and allow value range of each parameter, establish exhibit ternary digital twin model and define unified state vector, establish cultural relic protection constraint set and configure risk threshold and operation threshold, configure state update input interface; S2. Collect multi-source data based on the state quantity data mapping table and perform missing completion and anomaly correction. Form an aligned data stream according to the sliding time window and calculate the quality score. Write the aligned data stream into the state update input interface. S3. Based on the aligned data stream, update the three-element digital twin model of the exhibit to obtain the current state snapshot, calculate the cultural relic risk index and obtain the maximum risk within the prediction window, and calculate the audience experience evaluation quantity. S4. With the goal of maximizing the audience experience evaluation volume, and with the constraints that the maximum risk within the prediction window does not exceed the risk threshold and the allowed value range, a dynamic presentation strategy is obtained, and a strategy version record is generated and stored. S5. Distribute the dynamic presentation strategy to the exhibit display terminal and read back for verification. Continuously generate aligned data streams and recalculate the maximum risk and audience experience evaluation within the prediction window. Generate update trigger flags and execute strategy version iteration or rollback when the continuous trigger conditions are met, and write the strategy file.

[0007] S1 specifically includes: acquiring basic information of the target cultural relic exhibit and generating exhibit identifiers; establishing an exhibit configuration record with the exhibit identifier as the primary key; establishing a set of display control parameters in the exhibit configuration record and generating control parameters to be written into a mapping table; determining the allowable value range of each display control parameter; creating a ternary digital twin model of the exhibit corresponding to the exhibit identifier and defining a unified state vector; establishing a state quantity data mapping table; establishing a set of cultural relic protection constraints; configuring risk thresholds and quality scoring thresholds, the number of windows corresponding to the prediction window length, the number of consecutively triggered windows, and the experience lower limit threshold; and configuring the state update input interface.

[0008] S2 specifically includes: determining the data source list and field list based on the state quantity data mapping table; collecting and generating original collection records containing item identifiers, field names, values, units, timestamps, and quality marks, and completing unit conversion and item binding; performing missing completion and anomaly identification and correction based on physical allowable range and mutation threshold on the original collection records, and marking the corresponding fields as unavailable when missing or exceeding the threshold; establishing a sliding time window according to the window length and generating a unified timestamp; aggregating the alignment values ​​of each field based on the sample set; generating an aligned data stream record containing window quality marks and quality scores; and writing the aligned data stream record into the state update input interface.

[0009] S3 specifically includes: writing each field of the exhibition item into the ternary digital twin model based on the aligned data stream records and the state quantity data mapping table; using the state quantity of the previous window for unavailable fields in the window and generating a state quality label; splicing them together to form a current state snapshot containing a unified state vector and marking its availability; when the current state snapshot can be used for prediction and evaluation, calculating the cultural relic risk index of the current window according to the risk index calculation caliber, and calculating the maximum risk within the prediction window based on the prediction window time point sequence; calculating and normalizing the dwell intensity, attention concentration, and information acquisition sufficiency based on the crowd behavior state quantity, calculating the audience experience evaluation quantity according to the experience weight coefficient, and generating a reliable label.

[0010] S4 specifically includes: reading the set of display control parameters and their allowed value ranges from the exhibit configuration record, assembling them into a display control parameter vector in a fixed order, and generating a parameter feasible domain composed of continuous intervals and discrete level enumerations; constructing and solving a strategy optimization problem to obtain a dynamic presentation strategy, with the audience experience evaluation quantity as the optimization objective, the maximum risk within the prediction window not exceeding the risk threshold, and each display control parameter satisfying the allowed value range as constraints; generating a strategy version number for the dynamic presentation strategy and creating a strategy version record, writing the current state snapshot index, risk prediction result index, audience experience evaluation quantity index, risk threshold version number, allowed value range version number, solution mode identifier, and rollback pointer into the strategy version record.

[0011] S5 specifically includes: generating a command package based on the control parameters written into the mapping table, writing the dynamic presentation strategy into the exhibit display terminal according to the preset writing order, reading back the effective strategy version number and parameter readback value set of the terminal and comparing them field by field to complete the execution confirmation, retrying according to the number of retries and switching the security degradation strategy when it fails; continuously generating aligned data streams according to the time window during the strategy execution process and recalculating the maximum risk and audience experience evaluation within the prediction window to form a recalculation record and a trust mark; generating an update trigger mark based on the maximum risk and risk threshold within the prediction window, as well as the audience experience evaluation and experience lower limit threshold, and executing strategy version iteration or rollback when the continuous trigger window condition is met, and writing the issuance, recalculation, triggering and handling results into the strategy file.

[0012] The beneficial effects of this invention are as follows: This invention establishes exhibit configuration records and uniformly defines the set of display control parameters, state quantity data mapping tables, and cultural relic protection constraints. This allows for the correlation calculation of the cultural relic's physical state, microenvironmental state, and crowd behavior state under a unified state vector caliber, improving the consistency and reliability of display control decisions. By performing missing data completion, anomaly identification and correction, and sliding time window alignment on multi-source collected data, and generating an aligned data stream for quality scoring, the risk of misjudgment caused by data disorder, missing data, or abrupt changes is reduced, ensuring that strategy generation is based on a more reliable data foundation.

[0013] This invention calculates the maximum risk within the prediction window before the strategy is issued and uses a risk threshold as a hard constraint in the strategy solution, achieving "pre-judgment followed by control." This effectively avoids the passive situation of "protection equals shutdown" that occurs when the microenvironment has already deteriorated by the time an alarm is triggered, as is the case with existing technologies. By incorporating audience experience assessments and cultural relic risk prediction results into the optimization objectives and constraints, it achieves synergistic optimization between improving the display experience and meeting the requirements of cultural relic protection. This allows the dynamic presentation strategy to adaptively generate based on real-time operating status, improving content matching and audience dwell time.

[0014] This invention achieves full-process traceability management of policies by recording policy versions, issuing and reading back for verification, recalculating the execution process, and iterating or rolling back versions under continuous triggering conditions. It also suppresses system oscillations caused by frequent policy switching and improves the long-term stable operation capability of the system. Attached Figure Description

[0015] Figure 1 This is a schematic diagram of a dynamic presentation strategy generation and management method for cultural relic display according to the present invention. Detailed Implementation

[0016] 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.

[0017] Example 1: As Figure 1 As shown, this embodiment provides a method for generating and managing dynamic presentation strategies for cultural relic displays, including the following steps: S1. Obtain basic information of exhibits, generate exhibit identifiers, establish exhibit configuration records, write display control parameter set, write control parameters into mapping table and allow value range of each parameter, establish exhibit ternary digital twin model and define unified state vector, establish cultural relic protection constraint set and configure risk threshold and operation threshold, configure state update input interface; S2. Collect multi-source data based on the state quantity data mapping table and perform missing completion and anomaly correction. Form an aligned data stream according to the sliding time window and calculate the quality score. Write the aligned data stream into the state update input interface. S3. Based on the aligned data stream, update the three-element digital twin model of the exhibit to obtain the current state snapshot, calculate the cultural relic risk index and obtain the maximum risk within the prediction window, and calculate the audience experience evaluation quantity. S4. With the goal of maximizing the audience experience evaluation volume, and with the constraints that the maximum risk within the prediction window does not exceed the risk threshold and the allowed value range, a dynamic presentation strategy is obtained, and a strategy version record is generated and stored. S5. Distribute the dynamic presentation strategy to the exhibit display terminal and read back for verification. Continuously generate aligned data streams and recalculate the maximum risk and audience experience evaluation within the prediction window. Generate update trigger flags and execute strategy version iteration or rollback when the continuous trigger conditions are met, and write the strategy file.

[0018] S1 specifically includes the following sub-steps: S110. Establishment of the set of control parameters for exhibit object registration and display, and determination of the value range: S1101. Obtain basic information of the exhibit corresponding to the target cultural relic. The basic information includes at least the exhibit location, exhibit display terminal type, lighting equipment type, environmental sensor list, and audience behavior collection device list. Based on the basic information, generate a unique exhibit identifier in the exhibit management module and establish an exhibit configuration record with the exhibit identifier as the primary key. The exhibit configuration record is used to uniformly store the parameter mapping, threshold configuration, and solution configuration required subsequently.

[0019] S1102. Establish a set of display control parameters in the exhibit configuration record. The set of display control parameters is used to directly drive the controllable quantities of the exhibit display terminal and lighting equipment, and includes at least: Display brightness parameters: used to control the brightness output of the exhibit display terminal; Display rhythm parameters: used to control the timing of content switching, animation playback, or explanation segment progression; Content level expansion parameters: used to control the expansion depth and order of content from the overview layer to the detail layer; Trigger interval parameters: used to limit the shortest time interval between two adjacent content triggers or interactive triggers.

[0020] Each of the above parameters is written into the display item configuration record in the form of a "quadruple". The quadruple includes "parameter name, unit, terminal write field name, and allowed value type" in sequence. A control parameter write mapping table is generated and written based on the quadruple. The control parameter write mapping table is used to map each display control parameter to a field that the terminal can write when the subsequent policy is issued.

[0021] S1103. Determine the allowable value range for each parameter in the set of display control parameters. The allowable value range is jointly limited by the cultural relic protection requirements and the equipment capability boundaries: Read the protection threshold entries corresponding to the material type of the target cultural relic from the cultural relic protection rule base to obtain the lower and upper protection limits of the parameters; read the minimum and maximum controllable values ​​of the corresponding equipment from the equipment capability table; take the intersection of the above two types of boundaries as the final allowable value range and write it into the display item configuration record; to ensure that the allowable value range can be directly used for subsequent solution and verification, this embodiment uses the following boundary constraint expression for storage and verification: in, Indicates the first This displays the current value of the control parameter. To display the index number of the control parameter; Indicates the first This displays the minimum allowable value for each control parameter; Indicates the first The maximum allowable value for each display control parameter; and All values ​​are written into the aforementioned item configuration record for subsequent strategy solution value range constraints and parameter validity verification for subsequent strategy issuance.

[0022] This step outputs: exhibit identifier, exhibit configuration record, set of display control parameters, control parameters written to the mapping table, and allowed value range for each parameter (for S410 to build feasible domain and S510 to issue verification).

[0023] For example, in a specific implementation scenario, if the target cultural relic is made of "silk fabric," the upper limit for environmental illuminance protection read from the cultural relic protection rule base is 50 Lux, and the temperature protection range is 18℃-22℃. The system then combines this with the parameters of the exhibit's lighting equipment to map the upper limits of these physical indicators to the allowable range of display control parameters (such as the dimming command value of the lighting equipment) (e.g., setting the dimming duty cycle to 0%-30%), thereby obtaining the corresponding... and .

[0024] S120. Establishment of the ternary digital twin model structure and definition of unified state vector for the exhibit: S1201. Based on the exhibit identifier, create a three-element digital twin model of the exhibit in the digital twin module that corresponds one-to-one with the exhibit. The three-element digital twin model of the exhibit consists of the following three updatable sub-models: the artifact body state sub-model, the microenvironment state sub-model, and the crowd behavior state sub-model; define an updatable state quantity list for each sub-model, which is used to specify how subsequent collected fields are written into the model state.

[0025] S1202. Establish and write a state quantity data mapping table for each sub-model. The state quantity data mapping table is used to define the correspondence between "data source - field name - unit - sampling period - unit conversion rule - physical allowable range - mutation threshold". Among them, the cultural relic body state sub-model corresponds to the body monitoring field near the cultural relic; the micro-environment state sub-model corresponds to the environmental monitoring fields such as temperature, humidity, illuminance, and ultraviolet intensity; the crowd behavior state sub-model corresponds to the behavior monitoring fields such as visitor count, stay time, area occupancy, number of interaction triggers, and content playback progress. Write the state quantity data mapping table into the exhibition item configuration record, as the sole field basis for subsequent data collection, anomaly judgment, and model update in S210–S230.

[0026] Furthermore, the physical allowable range and abrupt change threshold are set based on the sensor's measurement range and the natural gradual change law of the environment. For example, for the "temperature" field, its physical allowable range is configured as 0℃-40℃, and the abrupt change threshold is set as 2℃ / minute. When the time interval between two adjacent temperature samples is 1 minute and the temperature difference exceeds 2℃, it is determined to be an abrupt change.

[0027] S1203. The state variables of the three types of sub-models are concatenated in a fixed order to form a unified state vector, and the structural expression of the unified state vector is defined as follows: in, Indicates time; Indicates time The overall condition of the exhibits; Indicates time The physical condition of the cultural relic; Indicates time The state of the microenvironment; Indicates time The behavior status of the crowd; the field order and storage format of the unified status vector are written into the display item configuration record for subsequent status snapshot solidification and calculation input consistency verification.

[0028] Outputs of this step: ternary digital twin model of the exhibit, state variable data mapping table, and unified state vector definition and storage format (for use by the entire S210–S310 link).

[0029] S130, Establishment of cultural relic protection constraint set, solidification of threshold configuration and configuration of input interface for status update: S1301. Establish a cultural relic protection constraint set bound to the exhibit identifier in the exhibit configuration record. The cultural relic protection constraint set shall at least include the fields of "constraint object, constraint index, constraint threshold, constraint inspection frequency, and triggering action". The constraint object shall at least include one or more parameters in the display control parameter set and the environmental indicators affected by them. The triggering action shall at least include limiting parameter increment, forcing fallback to a safe value, triggering strategy update, and triggering rollback.

[0030] Simultaneously, the necessary running thresholds and number of runs for subsequent processes will be written into the item configuration record. The running thresholds and number of runs configurations will include at least: the quality score threshold and the number of windows corresponding to the prediction window length. Number of consecutively triggered windows Experience lower limit threshold The parameters include: the number of retries for failed deployments, the candidate sampling step interval, the upper limit of discrete gear enumeration, and the solution time budget; among which, The number of windows corresponding to the prediction window length is used for calculating the maximum risk prediction value; This is the number of consecutive trigger windows used for debouncing trigger determination; This is used to test the lower limit threshold for trigger determination.

[0031] As a preferred configuration example, the prediction window length can be set to 5 minutes, corresponding to the number of windows. =5; Number of consecutively triggered windows =3 to trigger debouncing; experience lower threshold. Set to 0.6 (out of 1.0); the solution time budget is set to 200 milliseconds to ensure that the dynamic rendering strategy can respond in real time.

[0032] S1302. To make the protective constraints calculable and verifiable, read the corresponding components of illuminance, temperature, and humidity from the unified state vector and calculate the cultural relic risk indicators: in, For a moment Cultural relic risk indicators; For a moment Light intensity; For a moment Ambient temperature; For a moment The ambient humidity; , , These are the weighting coefficients for the impact of light intensity, ambient temperature, and ambient humidity on the risk to cultural relics; , , Write the item configuration record and bind the item identifier.

[0033] Weighting coefficient , , The sensitivity of the artifact's material to different environmental factors is determined. For example, for paintings and calligraphy made of photosensitive materials, changes in illumination contribute the most to their risk; therefore, an expert scoring method can be used, with weighting coefficients assigned accordingly. =0.6、 =0.2、 =0.2.

[0034] Set risk threshold And it is included in the set of constraints for cultural relic protection if and only if the following conditions are met. The protection constraint is satisfied at that time; The version number is written into the item configuration record for subsequent policy version tracing and constraint consistency verification.

[0035] S1303, Configure the status update input interface: Create a data access buffer for the exhibit's ternary digital twin model and define access field verification rules. The verification rules include at least timestamp monotonicity checks, unit consistency checks, missing field handling rules, and field validity checks. Set the write trigger mechanism to "trigger a status update once for each aligned data stream record written, or only write without triggering if the trigger condition is not met." The trigger condition is determined by the quality score threshold and key field completeness rules in the exhibit configuration record.

[0036] This step outputs: a set of cultural relic protection constraints, the calculation criteria for risk indicators, and risk thresholds. Running threshold and number of times configuration ( , , etc.), status update input interface (for S230 input, S320 / S410 / S530 constraint and triggering).

[0037] S2 specifically includes the following sub-steps: S210. Multi-source data acquisition and item binding (generating raw multi-source data): S2101. Read the state quantity data mapping table in the display item configuration record, determine the list of data sources and field lists to be collected, and load the unit, sampling period, physical allowable range and mutation threshold for each field.

[0038] S2102. Perform data collection on each of the data source lists to generate original collection records. Each original collection record contains at least the following fields and is written to the original data buffer in a fixed order: item identifier, data source identifier, field name, value, unit, timestamp, sampling period, and quality flag. The quality flag is a "single collection record level flag" used to identify whether the record is missing, out of bounds, or suspected of being abnormal. The quality flag is initially set to "valid" and is set to "missing" when the collection device reports a missing record or the timestamp is unavailable.

[0039] S2103, Perform a consistency check on the binding of exhibits: If the exhibit identifier in the original collection record is inconsistent with the exhibit identifier currently being processed, discard the record and record the reason for discarding; if the unit is inconsistent with the state quantity data mapping table, complete the unit conversion according to the unit conversion rules in the mapping table and update the unit field; output "original multi-source data collected by exhibit identifier" as input for S220.

[0040] Output of this step: Raw multi-source data (including quality labels) aggregated by exhibit identifier (for use by S220).

[0041] S220, Data Preprocessing and Anomaly Correction (Generating Preprocessed Multi-Source Data): S2201. Perform timestamp normalization on the original multi-source data: convert all timestamps to a unified time base format and perform monotonicity checks on timestamps from the same data source; when timestamp rollback is detected, mark the quality of the record as "time anomaly" and move the record into the anomaly queue to await correction or discard.

[0042] S2202. Perform missing data completion: Scan in chronological order using field names as indexes. When a field is continuously missing and the missing length does not exceed the missing threshold in the display item configuration record, use linear interpolation of two adjacent valid records to generate a completion value and set the quality mark to "interpolation completion". When the missing length exceeds the missing threshold, do not output the completion value, but mark the field as "unavailable" in the corresponding time window and retain the missing segment length for subsequent quality score calculation.

[0043] S2203. Perform anomaly identification and correction on abnormal data. Anomaly identification includes two types of rules: physical boundary judgment and mutation judgment. When the value of a field exceeds the preset physical allowable range in the state quantity data mapping table, the quality flag is set to "out-of-bounds anomaly". Calculate the mutation amount for adjacent valid samples of the same field. in, For a moment The field value; The time interval between the current sample and the previous valid sample; Mutation level; To represent absolute value operations, when The field corresponding to the state quantity data mapping table is greater than When it is determined to be a mutation anomalous, the quality marker is set to "mutation anomalous". The mutation threshold is set and written into the state quantity data mapping table.

[0044] Perform corrections on out-of-bounds or mutational anomalous samples: prioritize "amplitude limiting correction" to crop values ​​to the physically permissible range and set the quality flag to "amplitude limiting correction"; when the anomalous proportion within the same time window exceeds the anomalous proportion threshold in the item configuration record, mark the field as "unavailable" within that time window and retain the anomalous proportion for subsequent quality score calculation; output "preprocessed multi-source data" as input to S230.

[0045] Output of this step: Preprocessed multi-source data (including quality and unusable tags) (for use by S230).

[0046] S230, Time Synchronization and Sampling Alignment (Generate Aligned Data Stream and Write it to State Update Input Interface): S2301. Establish a unified time window and generate a window index: Read the window length from the display item configuration record and record it as... ,in The length of the sliding time window; the length of the window built with the current time as the end time is... A sliding time window sequence is generated, and a window end timestamp is generated for each time window. As a unified timestamp for aligning data streams; where, The time window index number is used to identify the first time window in the sliding time window sequence. A time window.

[0047] S2302. Perform sampling alignment and aggregation calculations for each field by window: For each field name, in the... Collect all valid samples within a time window to form a sample set. ,in ; Generate window-aligned values ​​by aggregating the mean: in, For fields in time window The alignment value; The number of samples; when Alternatively, if the field is marked as "unavailable" in the window, output a downgraded value according to the field downgrade rules and set the window quality flag of the field to "window unavailable"; the window quality flag is "field-level flag after window aggregation", which is used for subsequent state updates and reliable recalculation.

[0048] S2303, Generate aligned data stream records, calculate quality scores and incorporate model triggers: with window termination timestamps. Generate an aligned data stream record, which includes at least: an item identifier and a unified timestamp. The system generates alignment values ​​for each field and window quality markers for each field. A window quality score is calculated based on the missing rate and anomaly rate of key fields within the window. The missing rate is defined as "the number of unusable fields in the window among the key fields / the total number of key fields," and the anomaly rate is defined as "the number of fields with out-of-bounds or mutation anomalies among the key fields / the total number of key fields." The window quality score is calculated as "100 × (1 − missing rate − anomaly rate)" and truncated to the range of 0–100. The window quality score is written to the alignment data stream record. When the condition "key fields are complete and the window quality score is not lower than the quality score threshold" is met, the alignment data stream record is written to the data access buffer of the state update input interface, triggering a state update. When the condition is not met, only the data stream record is written without triggering, and the trigger result is recorded.

[0049] At the same time, three quality marking levels are defined: quality marking is at the acquisition record level, window quality marking is at the window field level, and subsequent state quality marking is at the state quantity level.

[0050] This step outputs: Aligned data stream (including...) (Window quality mark, quality score, trigger result) and write to the status update input interface (for use by S310–S330 and S520–S530).

[0051] S3 specifically includes the following sub-steps: S310, Model State Update and Current State Snapshot Generation (Output Current State Snapshot): S3101. Read the aligned data stream record of the current window and obtain the unified timestamp. Based on the state quantity data mapping table, the field alignment values ​​of the aligned data stream are written into the corresponding state quantities of the three-element digital twin model of the exhibition item field by field; when the window quality mark of a certain field is "window unavailable", the alignment value of that field is not written, but the value of the state quantity of the previous window is used, and the state quality mark of that state quantity is set to "use the previous snapshot"; whereby the state quality mark is a "state quantity level mark", which is used to describe whether each state quantity in the current state snapshot is updated or used by this window.

[0052] S3102. After completing the field-by-field writing, the artifact's physical state, microenvironmental state, and crowd behavior state are concatenated to generate the time frame according to the unified state vector definition. A unified state vector is generated and solidified into a current state snapshot; the current state snapshot includes at least: an item identifier and a unified timestamp. Unified state vector, state quality label for each state variable, window quality score and trigger result.

[0053] S3103. Perform current state snapshot consistency check: When all key state quantities (including at least the state quantities corresponding to illuminance, temperature, humidity and population occupancy) have valid values ​​or can be reused, mark the current state snapshot as "can be used for prediction and evaluation"; otherwise, mark it as "cannot be used for prediction and evaluation"; output the current state snapshot as input to S320 and S330.

[0054] This step outputs: a snapshot of the current state (including state quality and availability markers) (for use by S320 / S330).

[0055] S320. Risk Prediction Result Calculation (Output Risk Prediction Results): S3201. When the current state snapshot is marked as "available for prediction and evaluation", read the illuminance, temperature, and humidity components from the current state snapshot, and calculate the cultural relic risk index for the current window according to the risk index calculation caliber of S1302. and will Write the risk prediction results to the record; when the current status snapshot is marked as "unavailable for prediction and assessment", mark the risk prediction results record as "risk unavailable".

[0056] S3202, Construct a risk prediction window: Read the number of windows corresponding to the preset prediction window length in the display item configuration record and record it as... ,in The number of windows corresponding to the prediction window length; generating the prediction window time point sequence. For each prediction time point, a risk placeholder is reserved to store the risk indicator value.

[0057] S3203. Calculate the maximum risk within the prediction window and generate a constrained output: Calculate the risk index for each time point within the prediction window. The maximum value is then taken to obtain the maximum risk within the prediction window: in, To predict the maximum risk within the window; To predict the window index number within the window, used to enumerate from the current window to the future window index number. Each window; this embodiment refers to The calculation can be implemented as follows: when a device response table or environmental response model exists, the illuminance, temperature, and humidity increments within the prediction window are obtained based on the display brightness parameters and display rhythm parameters of the candidate strategy, and the calculation is performed accordingly. When no device response table or environmental response model exists, the illuminance, temperature, and humidity within the prediction window are generated using the "keep current window value" method, and calculations are performed accordingly. For prediction time points where key variables are unavailable, the risk indicator of the previous available time point is used and marked as "fill".

[0058] Will , Fill in the risk prediction results record with fill tags and availability tags, and link them with the exhibit identifier and unified timestamp. Binding storage.

[0059] This step outputs: Risk prediction results (at least including...) and (For use with S410 constraints and S530 triggers).

[0060] S330, Audience Experience Evaluation Calculation (Output Audience Experience Evaluation Quantity): S3301: Read the state quantities such as the number of people staying at the window, window occupancy, number of interaction triggers, and content playback progress corresponding to the crowd behavior state from the current state snapshot, and combine them with the window quality score and window quality mark in the aligned data stream record to form the experience evaluation input; when the key indicators of experience evaluation are unavailable and the previous window cannot be used, mark the audience experience evaluation quantity as "experience unavailable".

[0061] S3302. Calculate the experience components and perform normalization: Calculate three components: dwell intensity, attention concentration, and information acquisition sufficiency, and normalize them to the range of 0–1; where, dwell intensity is composed of the number of people staying in the window and the duration of stay in the window, and is normalized according to the maximum reference value in the display item configuration record; attention concentration is composed of the ratio of target area occupancy to total occupancy or the statistical value of gaze direction consistency, and is normalized; information acquisition sufficiency is composed of content level reach rate, key segment playback completion rate, and dwell duration rate after triggering, and is normalized; write the field names used in the calculation of each component and the source of the reference value into the evaluation record for traceability.

[0062] The specific method for obtaining the statistical value of target area occupancy and gaze direction consistency is as follows: real-time video streams are acquired by depth cameras or wide-angle monitoring devices deployed above the exhibits. Target detection algorithms (such as the YOLO series) are used to extract the bounding boxes of the audience in the image. The total area of ​​the bounding boxes in the target area is divided by the total area of ​​the image to obtain the target area occupancy. Furthermore, a head pose estimation algorithm (such as the PnP solution algorithm based on feature point detection) is used to calculate the three-dimensional Euler angles (yaw angle and pitch angle) of each audience member's head orientation. When both the yaw angle and pitch angle fall within the preset effective field of view range of the exhibit, it is determined as a valid gaze. The proportion of valid gazes in the current window to the total number of people is counted, which yields the statistical value of gaze direction consistency.

[0063] S3303. Calculate the overall experience score and generate an optimizable output: Read the experience weight coefficients from the exhibit configuration record and calculate the overall experience score: in, To unify timestamps Corresponding audience experience evaluation metrics; The residence intensity component; To focus on the concentration component; This is a component for information sufficiency. , , These are experience weight coefficients for dwell time intensity, attention concentration, and information sufficiency, respectively, and are written into the display item configuration record; when the window quality score is lower than the quality score threshold, Mark it as "low confidence" and write the low confidence mark into the evaluation record for subsequent conservative strategy processing; , , , Its usability and credibility markers are written into the visitor experience evaluation record, and are linked to exhibit identifiers and a unified timestamp. Binding storage.

[0064] Output of this step: Audience experience evaluation score (including...) (with trusted tags) (for use by S410 targets and S530 triggers).

[0065] The specific construction method of the equipment response table or environmental response model is as follows: during the calibration stage when the venue is closed or there is no audience intervention, the display brightness parameters and display rhythm parameters of the exhibits are output through orthogonal spatial traversal. During continuous operation of each parameter combination, the temperature and humidity change curves within the number of windows (m) corresponding to the prediction window length are recorded synchronously, and the temperature and humidity increments at each time point are calculated. The mapping relationship between the above "parameter combination - running time - temperature and humidity increments" is fitted into a polynomial function or solidified into a multidimensional look-up table and stored in the display item configuration record.

[0066] In real-time prediction, the microenvironmental state in the current state snapshot is used as the baseline value. The corresponding candidate strategy parameters and the temperature and humidity increments of the prediction time j in the multidimensional lookup table are superimposed to obtain the inferred values ​​of illuminance, temperature and humidity within the prediction window.

[0067] S4 specifically includes the following sub-steps: S410. Strategy Optimization Problem Construction (Output Optimization Problem and Feasible Region): S4101. Read the set of display control parameters and their allowed value ranges from the display item configuration record, and assemble them into a display control parameter vector in a fixed order. ;in, To display the control parameter vector, each component of the vector corresponds to a parameter in the set of control parameters, and inherits its unit, value type, and allowed value range.

[0068] S4102. Generate the feasible region of parameters based on the allowed value range. :in, For a parameter, the feasible region is defined as a closed interval; for a continuous parameter, its feasible region is defined as a closed interval. For discrete parameters, their feasible region is defined as an enumerated set of gear positions and mapped to terminal field values ​​by writing control parameters into a mapping table; the feasible regions of all parameters are combined in vector order to obtain... The candidate sampling step interval, enumeration limit, and solution time budget are read from the item configuration record and written into the current solution context.

[0069] S4103. Construct a strategy optimization problem and solidify it into an executable definition: With the goal of "improving the user experience while satisfying protection constraints," the risk prediction results... With risk threshold As a constraint, As a boundary constraint; define the optimal display control parameter vector. ,in To optimally display the control parameter vector, this embodiment defines the strategy optimization problem as follows: When evaluating candidate parameters, A feasible candidate evaluation method is used to generate the candidate evaluation score: taking the current state snapshot and candidate parameters as input, the candidate experience score is calculated based on the experience response rules in the display item configuration record (including the rules on the impact of brightness changes on readability, the rules on the impact of rhythm changes on dwell time, and the rules on the impact of content hierarchy expansion on completion rate). The candidate experience score is then used as the candidate parameter. Write the current state snapshot index, risk prediction result index, audience experience evaluation index, and current solution context into the solution record for future version tracking, where st represents the constraint condition.

[0070] This step outputs: strategy optimization problem, feasible region. Solving context and input index (for use by S420 solver).

[0071] Specifically, the experience response rules are implemented using the following piecewise function and probability product: To address the rule regarding the impact of brightness variations on readability, a piecewise linear mapping function is established between display brightness parameters and readability scores. Full marks are awarded within the optimal reading brightness range, while scores decrease gradually beyond this range. For the rule regarding the impact of content hierarchy expansion on completion rate, a discrete probability mapping table is established based on historical statistical data, representing "content hierarchy expansion depth - historical average playback completion rate." When calculating candidate experience scores, the candidate parameters are substituted into the aforementioned mapping function and mapping table to obtain the expected scores for each dimension. A weighted summation method is then used to output the final candidate experience score.

[0072] S420, Strategy Solving and Dynamic Rendering Strategy Generation (Output Dynamic Rendering Strategy and Verification Results): S4201. Perform a feasibility pre-check before solving: in the feasible region The internal structure requires at least two sets of baseline candidate parameter combinations, one of which is a safety lower limit combination (each parameter takes...). (Or the most conservative setting), the other set is the parameter combination of the previous effective strategy version; calculate the baseline candidate for each set. and Comparison, when at least one set satisfies The solution mode is marked as "normal mode" when it is active, and otherwise marked as "degraded mode" and written into the solution context.

[0073] S4202. Execute strategy solution in normal mode: sample continuous parameters according to the step interval in the solution context, and enumerate discrete parameters according to the enumeration upper limit to generate a candidate parameter set; for each member of the candidate parameter set, calculate the candidate experience score and calculate the corresponding... Remove those that do not meet the requirements. After identifying the candidates, the candidate parameter with the highest candidate experience score is selected from the remaining candidates. If the solution reaches the solution time budget but the full candidate evaluation is not completed, the best candidate among the evaluated candidates will be selected as the optimal candidate. And label it as "Time Budget Truncation Output".

[0074] S4203. Output security degradation strategy in degradation mode or low confidence mode: When the solution mode is "degraded mode" or when the audience experience evaluation record is marked as "low confidence", directly construct a combination of security degradation parameters, in which the display brightness parameter is taken as the minimum allowed value, the display rhythm parameter is taken as the most conservative level, the trigger interval parameter is taken as the maximum interval, and the content level expansion parameter is limited to the overview layer; mark the combination of security degradation parameters as "degraded output"; Regardless of whether it's the normal mode or the downgrade mode, the final parameter combination will be fixed into a dynamic rendering strategy. This dynamic rendering strategy will at least include the full parameter values, the effective start timestamp, and the effective duration, along with the "parameter boundary verification result (whether it meets the requirements)". ")" and "Protection constraint verification results (whether they are satisfied)" ) and downgrade or truncation markers.

[0075] This step outputs: dynamic rendering strategy, boundary and constraint verification results, and downgrade / truncation markers (for use in S430 version registration and S510 distribution).

[0076] S430. Policy versioning registration generates policy version records (outputs policy version records and rollback pointers): S4301. Generate a version number for the dynamic presentation strategy and create a strategy version record: Generate a strategy version number using the display item identifier and generation timestamp, and create a strategy version record corresponding to the strategy version number in the strategy management module; write the effective time window of the dynamic presentation strategy into the strategy version record for subsequent effective control and expiration control.

[0077] S4302. Write traceable input and constraint indexes: Write the current state snapshot index, risk prediction result index, and audience experience evaluation index into the strategy version record to fix the input basis for this strategy; set the risk threshold... Version number, allowed value range (version number), and , , Write the running threshold configuration version number into the policy version record to ensure that the constraints and triggering criteria are consistent during subsequent tracing.

[0078] S4303, Write the solver identifier and rollback pointer and complete full storage: Write the solver mode flag (normal / degraded), candidate generation method flag (sampling / enumeration), whether to handle low-confidence conservatively, and whether to truncate the output according to the time budget into the policy version record; write the rollback pointer into the policy version record, the rollback pointer including at least the previous valid policy version number and the security degradation policy flag; write the full value of the dynamically presented policy parameters, the verification result and the flag into the policy version record and archive it in the database to form the subsequent policy file index.

[0079] This step outputs: Strategy version record (including version number, full parameter value, effective time window, input and constraint index, solver identifier, rollback pointer, and verification result) (for use by S510 for distribution and S530 for rollback).

[0080] S5 specifically includes the following sub-steps: S510, Policy Issuance and Terminal Execution Confirmation (Output Execution Confirmation Result and Error Record): S5101: Read the display item identifier, policy version number, effective time window, and full value of dynamic presentation policy parameters from the policy version record, and read the control parameters from the display item configuration record and write them into the mapping table, mapping each display control parameter to a terminal write field; generate a distribution instruction package, which includes at least: display item identifier, policy version number, effective start timestamp, effective duration, full value of parameter fields, and effective enable field.

[0081] S5102. Write to the display terminal in a fixed writing order: first write the policy version number and effective time window field, then write the full value of each parameter field, and finally write the effective enable field to enable the policy; write a timestamp and return code for each field writing record, and set the writing status of the field to "write failed" when the return code is failure or timeout.

[0082] S5103, Execute Terminal Readback Verification and Retry on Failure: After writing is completed, a readback request is initiated to the terminal to read back the current effective policy version number and parameter readback value set of the terminal; the parameter readback value set is compared field by field with the full field values ​​of the parameters in the policy version record. If they match, an "Execution Confirmation Successful" record is generated and bound to the display item identifier and policy version number; if they do not match or there are fields that failed to be written, the failed fields are rewritten according to the number of retry attempts in the display item configuration record and the readback verification is repeated; if they still do not match after the number of retries, an "Execution Confirmation Failed" record is generated, and the terminal is switched to the security downgrade policy. At the same time, the reason for failure, the list of failed fields and the number of retries are written to the exception record.

[0083] This step outputs: execution confirmation result, the current effective policy version number on the terminal, and exception records (for S520 binding and S530 tracing).

[0084] S520, Continuous data collection and recalculation during execution (outputting recalculation records and trusted markers): S5201. Using the alignment data stream window step size as the recalculation period, continuously collect new multi-source data during the execution of the current policy version on the terminal, and repeatedly execute S220–S230 to generate new alignment data streams; bind each alignment data stream record with the current effective policy version number of the terminal to form a correspondence between "policy version - time window".

[0085] S5202. Repeat steps S310–S330 for the aligned data stream of each time window to obtain the recalculated current state snapshot, risk prediction results, and audience experience evaluation metrics; generate a recalculation record and write it to the recalculation buffer. The recalculation record shall at least include: exhibit identifier, strategy version number, and unified timestamp. Predicting maximum risk within the window Audience experience evaluation Window quality flag, window quality score, current state snapshot availability flag, and low-reliability experience flag.

[0086] S5203. Generate Recalculation Trust Markers: When the window quality is marked as "Window Unavailable" or the window quality score is lower than the quality score threshold, the recalculation record is marked as "Low Trust," and... and Mark as "use the previous available window value" or "unavailable"; when the window quality score is not lower than the quality score threshold and the key state quantity is available, mark the recalculation record as "available"; output the recalculation record for S530 to trigger the judgment.

[0087] This step outputs: Recalculation record (including...) , Quality rating and credibility mark (for use by S530).

[0088] S530, Update Trigger Decision, Version Iteration and Policy File Writing (Output Update Results and Policy File): S5301, Reading the recalculation record and And read the risk threshold from the exhibit configuration record. and the lower limit threshold of experience ; Generate update trigger flag ,in To update the trigger flag, this embodiment uses the following combined trigger criteria: in, This is an indicator function; it returns 1 if the condition within the parentheses is true, and 0 otherwise. When a recalculation record is marked as "low confidence," it will... Marked as "low-trust trigger" and enters the conservative handling path. Represents a logical OR operation.

[0089] S5302, Perform debouncing and trigger type determination: Read the number of consecutive trigger windows from the item configuration record and record it as... ,in The number of consecutively triggered windows; when consecutive occurrences When a window is active, a policy update is triggered; when triggered by... When this occurs, the trigger type will be marked as "risk trigger". When the trigger type is triggered, it is marked as "experience trigger"; when both trigger types are triggered, it is marked as "double trigger". The trigger type is used to determine the priority of subsequent processing.

[0090] S5303, Perform version iteration or rollback and write to the policy file: When the trigger type includes "risk trigger", rollback is performed first: read the rollback pointer in the current policy version record, select the previous valid policy version number as the rollback target version; send the policy corresponding to the rollback target version to the terminal and perform the same readback verification as S510; if the readback verification passes, record "rollback successful", otherwise switch to the security downgrade policy and record "rollback failed and downgraded"; When the trigger type is only "experience trigger" and the recalculation record is marked as "available", the risk prediction result and audience experience evaluation quantity obtained by recalculation in this window are used as input. Then, S410-S430 is executed to generate a new dynamic presentation strategy and a new strategy version record and complete the version iteration. When the trust mark of the recalculation record is "low trust", the regular re-solution is not performed directly. Instead, the security degradation strategy is switched and the regular re-solution is triggered only after the recalculation record in the next window is "available".

[0091] Simultaneously, the following fields will be written into the policy file in a structured manner and archived in the database: Item ID, Execution Terminal ID, Current Policy Version Number, Issuance Time and Execution Confirmation Result, Parameter Readback Verification Result, and Recalculation Record (including...). , (Quality score and trust mark), update trigger mark The policy file includes the continuous trigger judgment result and trigger type, the type of handling action (version iteration / rollback / downgrade), the target version number of the handling, the exception record and the reason for failure; the policy file is used for subsequent policy tracing and rollback management, and provides historical basis for the next round of policy solution.

[0092] This step outputs: update trigger judgment result, version iteration or rollback result, and policy file (closed loop back to S410–S430 or maintain security degradation policy).

[0093] The above formulas are all dimensionless calculations. The formulas are derived from software simulations based on a large amount of collected data to obtain the most recent real-world results. The preset parameters and thresholds in the formulas are set by those skilled in the art according to the actual situation.

[0094] The above embodiments can be implemented, in whole or in part, by software, hardware, firmware, or any other combination thereof. When implemented using software, the above embodiments can be implemented, in whole or in part, as a computer program product. The computer program product includes one or more computer instructions or computer programs. When the computer instructions or computer programs are loaded or executed on a computer, all or part of the processes or functions described in the embodiments of this application are generated. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions can be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another. For example, the computer instructions can be transmitted from one website, computer, server, or data center to another website, computer, server, or data center via wired (e.g., infrared, wireless, microwave, etc.) means. The computer-readable storage medium can be any available medium that a computer can access or a data storage device such as a server or data center that includes one or more sets of available media. The available medium can be a magnetic medium (e.g., floppy disk, hard disk, magnetic tape), an optical medium (e.g., DVD), or a semiconductor medium. The semiconductor medium can be a solid-state drive.

[0095] Those skilled in the art will recognize that the modules and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0096] Those skilled in the art will understand that, for the sake of convenience and brevity, the specific working processes of the systems, devices, and modules described above can be referred to the corresponding processes in the foregoing method embodiments, and will not be repeated here.

[0097] In the several embodiments provided in this application, it should be understood that the disclosed systems, apparatuses, and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of modules is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple modules or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces; the indirect coupling or communication connection between apparatuses or modules may be electrical, mechanical, or other forms.

[0098] The modules described as separate components may or may not be physically separate. The components shown as modules may or may not be physical modules; they may be located in one place or distributed across multiple network modules. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs.

[0099] In addition, the functional modules in the various embodiments of this application can be integrated into one processing module, or each module can exist physically separately, or two or more modules can be integrated into one module.

[0100] If the aforementioned functions are implemented as software functional modules and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or a portion of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0101] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

[0102] In conclusion, the above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A method for generating and managing dynamic presentation strategies for cultural relic displays, characterized in that, Includes the following steps: S1. Obtain basic information of exhibits, generate exhibit identifiers, establish exhibit configuration records, write display control parameter set, write control parameters into mapping table and allow value range of each parameter, establish exhibit ternary digital twin model and define unified state vector, establish cultural relic protection constraint set and configure risk threshold and operation threshold, configure state update input interface; S2. Collect multi-source data based on the state quantity data mapping table and perform missing completion and anomaly correction. Form an aligned data stream according to the sliding time window and calculate the quality score. Write the aligned data stream into the state update input interface. S3. Based on the aligned data stream, update the three-element digital twin model of the exhibit to obtain the current state snapshot, calculate the cultural relic risk index and obtain the maximum risk within the prediction window, and calculate the audience experience evaluation quantity. S4. With the goal of maximizing the audience experience evaluation volume, and with the constraints that the maximum risk within the prediction window does not exceed the risk threshold and the allowed value range, a dynamic presentation strategy is obtained, and a strategy version record is generated and stored.

2. The method for generating and managing dynamic presentation strategies for cultural relic display according to claim 1, characterized in that, Also includes: S5. The dynamic presentation strategy is sent to the exhibit display terminal and read back for verification. The alignment data stream is continuously generated and the maximum risk and audience experience evaluation within the prediction window are recalculated. An update trigger flag is generated and the strategy version is iterated or rolled back when the continuous trigger conditions are met. The strategy file is written.

3. The method for generating and managing dynamic presentation strategies for cultural relic display according to claim 1, characterized in that, S1 specifically includes: Obtain basic information about the target cultural relic exhibits and generate exhibit identifiers, and establish exhibit configuration records with exhibit identifiers as the primary key; Establish a set of display control parameters in the display item configuration record and generate control parameters to write into a mapping table, and determine the allowable value range of each display control parameter; Create a three-element digital twin model of the exhibit corresponding to the exhibit identifier and define a unified state vector, and establish a state quantity data mapping table; establish a set of cultural relic protection constraints, configure risk threshold and quality score threshold, prediction window length corresponding to the number of windows, number of consecutively triggered windows and experience lower limit threshold, and configure the state update input interface.

4. The method for generating and managing dynamic presentation strategies for cultural relic display according to claim 1, characterized in that, S2 specifically includes: Based on the state quantity data mapping table, determine the data source list and field list, collect and generate original collection records containing item identifiers, field names, values, units, timestamps and quality markers, and complete unit conversion and item binding; The system performs missing data completion and anomaly identification and correction based on physical allowable range and mutation threshold for the original acquisition records, and marks the corresponding fields as unavailable when missing or abnormally exceeding the threshold.

5. The method for generating and managing dynamic presentation strategies for cultural relic display according to claim 4, characterized in that, A sliding time window is established according to the window length and a unified timestamp is generated. The alignment values ​​of each field are obtained by aggregating based on the sample set. An aligned data stream record containing window quality markers and quality scores is generated and written to the state update input interface.

6. The method for generating and managing dynamic presentation strategies for cultural relic display according to claim 1, characterized in that, S3 specifically includes: Based on the aligned data stream records, the three-dimensional digital twin model of the exhibition item is written field by field according to the state quantity data mapping table. For fields that are unavailable in the window, the state quantity of the previous window is used and a state quality mark is generated. The data are then spliced ​​together to form a current state snapshot containing a unified state vector and marked for availability. When the current state snapshot is available for prediction and assessment, the cultural relic risk index for the current window is calculated according to the risk index calculation caliber, and the maximum risk within the prediction window is calculated based on the time point sequence of the prediction window.

7. The method for generating and managing dynamic presentation strategies for cultural relic display according to claim 6, characterized in that, Based on the crowd behavior state, the dwell intensity, attention concentration and information acquisition sufficiency are calculated and normalized. The audience experience evaluation is calculated according to the experience weight coefficient and a reliable label is generated.

8. The method for generating and managing dynamic presentation strategies for cultural relic display according to claim 1, characterized in that, S4 specifically includes: Read the set of display control parameters and their allowed value ranges from the display item configuration record, assemble them into a display control parameter vector in a fixed order, and generate a parameter feasible domain composed of a combination of continuous intervals and discrete gear enumerations. With audience experience evaluation as the optimization objective and constraints such as the maximum risk within the prediction window not exceeding the risk threshold and each display control parameter meeting the allowable value range, a strategy optimization problem is constructed and solved to obtain a dynamic presentation strategy. To dynamically present the strategy, generate a strategy version number and create a strategy version record. Write the current state snapshot index, risk prediction result index, audience experience evaluation index, risk threshold version number, allowed value range version number, solution mode identifier, and rollback pointer into the strategy version record.

9. The method for generating and managing dynamic presentation strategies for cultural relic display according to claim 1, characterized in that, S5 specifically includes: Based on the control parameters, the mapping table is written to generate the instruction package and the dynamic presentation strategy is written to the display terminal according to the preset writing order. The version number of the effective strategy and the set of parameter readback values ​​are read back and compared field by field to complete the execution confirmation. If it fails, it will retry according to the number of retries and switch the security degradation strategy. During strategy execution, aligned data streams are continuously generated according to time windows, and the maximum risk and audience experience assessment within the prediction window are recalculated to form recalculation records and credibility markers.

10. A method for generating and managing dynamic presentation strategies for cultural relic display according to claim 9, characterized in that, An update trigger flag is generated based on the maximum risk and risk threshold within the prediction window, as well as the audience experience evaluation quantity and experience lower limit threshold. When the consecutive trigger window condition is met, the strategy version iteration or rollback is executed, and the distribution, recalculation, triggering and handling results are written into the strategy file.

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