A method for analyzing the experience of offline experience scenarios

Abstract

This invention relates to the field of data analysis technology, and in particular to a method for analyzing the experience of offline experience scenarios. The method includes: acquiring the dwell time and number of interactions of the target; identifying areas to be monitored and temporary monitoring areas; identifying abnormal interactions and adjusting the grid step size; acquiring the experience score of interactive devices; and adjusting the grid step size and collection interval to improve the experience score. This invention, by dynamically adjusting the grid step size and collection interval, can more flexibly adapt to changes in the target's behavior, thereby improving the accuracy and real-time nature of data collection. Analysis based on historical data helps to obtain the fluctuations in the target's experience over different time periods, providing a strong basis for subsequent site optimization and equipment improvement. This can increase the attractiveness of exhibitions and provide scientific decision support for venue managers, ultimately achieving continuous optimization and improvement of exhibition effects. It effectively solves the problem of ambiguous exhibition experience output due to insufficient interactive data analysis.

Description

Technical Field

[0001] This invention relates to the field of data analysis technology, and in particular to a method for analyzing the experience of offline experience scenarios. Background Technology

[0002] With the continuous advancement of technology and the diversification of user needs, the design and management of offline experience scenarios have become increasingly important. Especially in the exhibition industry, improving participant experience and obtaining accurate data analysis to optimize subsequent activities have become critical issues that the industry urgently needs to address. While existing technologies can provide some interaction and feedback, they still have limitations in data analysis and experience evaluation, resulting in unclear and ineffective experience information output.

[0003] Chinese patent application publication number CN113923246A discloses a method and apparatus for immersive online video scene experience. The method includes: establishing a virtual resource list corresponding to the scene based on objects within the scene and their dependency class parameters; storing the scene's resources and the virtual resource list on a server according to a preset storage method; setting a calling strategy for editing various content within the scene to create a virtual scene; receiving a request to create a virtual scene, analyzing the request to obtain the target scene's construction strategy, virtual resource list, and calling strategy; sequentially downloading the scene's resource data from the server and storing it locally according to the target scene's virtual resource list and calling strategy; and creating a virtual target scene from the locally stored resource data according to the target scene's construction strategy and calling strategy, which is then combined with the real-world scene to form an immersive scene for display.

[0004] This method relies on a virtual resource list stored on the server. If the server malfunctions or the network is unstable, it will affect the loading of the scene and the user experience. The method needs to download resource data from the server during the scene creation process, which will cause delays and affect the user's immersion. The scene building and calling strategies of this method are preset and cannot quickly adapt to changes in user needs or personalized customization, resulting in a vague exhibition experience output. Summary of the Invention

[0005] To address this issue, the present invention provides a method for analyzing the experience of offline experience scenarios, thereby overcoming the problem of ambiguous output of exhibition experience due to insufficient interactive data analysis in the prior art.

[0006] To achieve the above objectives, the present invention provides a method for analyzing the experience of offline experience scenarios, comprising:

[0007] The dwell time of each target in each monitoring area constructed based on a preset grid step size and the number of interactions of each interactive device within the dwell time are obtained at preset collection intervals.

[0008] Several temporary monitoring areas are determined based on the stated dwell time and the preset standard dwell time.

[0009] Based on the total number of interactions in each of the temporary monitoring areas within the preset monitoring time, several abnormal interaction areas are determined. Based on the number of abnormal interaction areas and the preset standard number of abnormalities, the adjustment interval determination result is determined. Based on the adjustment interval determination result, the preset grid step size is adjusted to form the first grid step size.

[0010] Based on the first grid step size, the preset historical duration, and the experience score of the interactive device, several areas to be improved are determined.

[0011] The preset collection interval is adjusted based on all experience scores of the area to be improved within the preset evaluation period until the fluctuation value of the experience score formed based on the experience score is less than or equal to the preset standard experience score fluctuation value.

[0012] Furthermore, the step of determining several areas for improvement based on the first grid step size, the preset historical duration, and the experience score of the interactive device includes:

[0013] The dwell time of each target in each monitoring area is obtained at the preset acquisition interval based on the first grid step size;

[0014] Based on the dwell time, several corrected monitoring areas are determined, and based on the number of interactive devices in the corrected monitoring areas, several temporary corrected monitoring areas are determined.

[0015] The first grid step size is adjusted according to all the temporary correction monitoring areas of the target within the preset historical time period until the area overlap rate determined based on the temporary correction monitoring area is greater than the preset standard overlap rate, thus forming the second grid step size.

[0016] Based on the experience scores of all interactive devices within each monitoring area constructed based on the second grid step size during the dwell time, several areas to be improved are identified;

[0017] The abnormal interaction area includes a first abnormal interaction area and a second abnormal interaction area.

[0018] Furthermore, determining several abnormal interaction areas based on the total number of interactions in each of the temporary monitoring areas within a preset monitoring period includes:

[0019] Calculate the standard deviation of the number of interactions to form the interaction number standard deviation. When the interaction number standard deviation is less than the minimum value of the preset standard interaction number fluctuation range, and the difference between the minimum value of the interaction number fluctuation range and the interaction number standard deviation is less than the preset difference threshold, the temporary monitoring area is determined to be the first abnormal interaction area.

[0020] Furthermore, the step of determining several abnormal interaction areas based on the total number of interactions in each of the temporary monitoring areas within a preset monitoring period also includes:

[0021] When the standard deviation of the number of interactions is greater than the maximum value of the preset standard interaction number fluctuation range, and the difference between the standard deviation of the number of interactions and the maximum value of the preset standard interaction number fluctuation range is less than the preset difference threshold, the temporary monitoring area is determined to be the second abnormal interaction area.

[0022] Furthermore, the determination of the adjustment spacing based on the number of abnormal interaction areas and the preset standard number of abnormalities includes:

[0023] When the number of the first abnormal interaction areas is greater than the preset standard number of abnormalities, it is determined that the preset grid step size needs to be increased, thus forming the increased spacing determination result.

[0024] Furthermore, the determination of the adjustment spacing based on the number of abnormal interaction areas and the preset standard number of abnormalities also includes:

[0025] When the number of the second abnormal interaction areas is greater than the preset standard number of abnormalities, it is determined that the preset grid step size needs to be reduced, thus forming the reduced spacing determination result.

[0026] Further, the step of adjusting the preset grid step size based on the adjustment spacing determination result to form the first grid step size includes:

[0027] When the adjustment spacing determination result is the increase spacing determination result, the preset grid step size is increased according to the standard deviation of the number of interactions, the maximum value of the preset standard interaction number fluctuation range, the preset difference threshold, and the preset first spacing adjustment coefficient to form the first grid step size;

[0028] When the adjustment spacing determination result is the reduction spacing determination result, the preset grid step size is reduced according to the standard deviation of the number of interactions, the minimum value of the preset standard interaction number fluctuation range, the preset difference threshold, and the preset first spacing adjustment coefficient to form the first grid step size.

[0029] Further, the step of adjusting the first grid step size based on all the temporary correction monitoring areas of the target within a preset historical period until the regional overlap rate determined based on the temporary correction monitoring areas is greater than the preset standard overlap rate, to form the second grid step size, includes:

[0030] Calculate the ratio of the preset historical duration to the preset collection interval to obtain the total number of collections;

[0031] Obtain the number of overlapping cells in all the temporary correction monitoring areas of the target to obtain the overlap count;

[0032] The region overlap rate is calculated based on the number of overlaps, the total number of data collections, the first grid step size, and the preset site area.

[0033] When the region overlap rate is less than or equal to the preset standard overlap rate, the first grid step size is reduced according to the region overlap rate, the preset standard overlap rate and the preset second spacing adjustment coefficient until the region overlap rate is greater than the preset standard overlap rate, thus forming the second grid step size.

[0034] Further, adjusting the preset collection interval based on all experience scores of the area to be improved within the preset evaluation period until the experience score fluctuation value formed based on the experience scores is less than or equal to the preset standard experience score fluctuation value includes:

[0035] Calculate the standard deviation of the average score of the experience rating to obtain the experience rating fluctuation value. When the experience rating fluctuation value is greater than the preset standard experience rating fluctuation value, it is determined that the preset collection interval needs to be adjusted. The preset collection interval is reduced according to the experience rating fluctuation value, the preset standard experience rating fluctuation value and the preset interval adjustment coefficient.

[0036] Furthermore, the determination of several temporary monitoring areas based on the dwell time and the preset standard dwell time includes:

[0037] When the dwell time exceeds the preset standard dwell time, the monitoring area is determined to be the area to be monitored, and several temporary monitoring areas are determined based on the area to be monitored.

[0038] Furthermore, the step of determining several temporary monitoring areas based on the area to be monitored includes:

[0039] When the number of devices exceeds the preset standard number of devices, the area to be monitored is determined to be a temporary monitoring area.

[0040] Compared with existing technologies, the advantages of this invention lie in its ability to more flexibly adapt to changes in target behavior by dynamically adjusting the grid step size and acquisition interval, thereby improving the accuracy and real-time performance of data acquisition. Simultaneously, analysis based on historical data helps to capture fluctuations in the target experience over different time periods, providing a strong basis for subsequent site optimization and equipment improvement. The implementation of this method will significantly improve target satisfaction, increase the attractiveness of exhibitions, and provide venue managers with scientific decision-making support, ensuring the rational allocation and use of resources, ultimately achieving continuous optimization and improvement of exhibition effects, and effectively solving the problem of ambiguous exhibition experience output due to insufficient interactive data analysis.

[0041] Furthermore, by accurately analyzing the fluctuations in the number of interactions, abnormal interaction areas in the exhibition area can be identified in a timely manner, and the grid step size and collection interval can be flexibly adjusted according to the actual situation, thereby improving the accuracy and efficiency of monitoring.

[0042] Furthermore, identifying the second abnormal interaction area can reveal potential problem areas and provide data support for subsequent optimization measures.

[0043] Furthermore, by analyzing the number of abnormal interaction areas, areas with poor target experience can be identified in a timely manner, allowing for appropriate spacing adjustments.

[0044] Furthermore, by adjusting the grid step size in a timely manner, especially when the number of second abnormal interaction areas exceeds the limit, it is possible to more effectively enhance the capture and feedback of target behavior, thereby improving the overall experience of the target.

[0045] Furthermore, by flexibly adjusting the grid step size, the system can effectively optimize the interactive effect of the monitoring area, ensuring that the number of interactions in each area is more in line with the target experience and actual needs.

[0046] Furthermore, by optimizing the grid step size, it is possible to ensure effective overlap between monitoring areas while dynamically adjusting the monitoring area, thereby improving the monitoring accuracy and effectiveness of interactive devices.

[0047] Furthermore, by assessing the fluctuation of all average scores within a preset evaluation period, the frequency and accuracy of data collection can be improved, and it also helps to monitor changes in the target experience in real time.

[0048] Furthermore, this method can effectively identify abnormal stays of targets in specific areas, enabling in-depth analysis and monitoring.

[0049] Furthermore, by determining temporary monitoring areas, areas with excessive equipment usage can be quickly identified, allowing for closer monitoring and analysis. Attached Figure Description

[0050] Figure 1 This is a flowchart of the offline experience scenario experience analysis method in this embodiment;

[0051] Figure 2 This implementation defines the logic diagram for determining the first abnormal interaction region;

[0052] Figure 3 This implementation defines the logic diagram for determining the second abnormal interaction region;

[0053] Figure 4 This is a logic diagram for determining the adjustment spacing result in this implementation. Detailed Implementation

[0054] To make the objectives and advantages of the present invention clearer, the present invention will be further described below with reference to embodiments; it should be understood that the specific embodiments described herein are merely for explaining the present invention and are not intended to limit the present invention.

[0055] Preferred embodiments of the present invention will now be described with reference to the accompanying drawings. Those skilled in the art should understand that these embodiments are merely illustrative of the technical principles of the present invention and are not intended to limit the scope of protection of the present invention.

[0056] It should be noted that in the description of this invention, the terms "upper", "lower", "left", "right", "inner", "outer", etc., which indicate directions or positional relationships, are based on the directions or positional relationships shown in the accompanying drawings. This is only for the convenience of description and is not intended to indicate or imply that the device or element must have a specific orientation, or be constructed and operated in a specific orientation. Therefore, it should not be construed as a limitation of this invention.

[0057] Furthermore, it should be noted that, in the description of this invention, unless otherwise explicitly specified and limited, the terms "installation," "connection," and "linking" should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral connection; they can refer to a mechanical connection or an electrical connection; they can refer to a direct connection or an indirect connection through an intermediate medium; and they can refer to the internal connection of two components. Those skilled in the art can understand the specific meaning of the above terms in this invention according to the specific circumstances.

[0058] Please see Figure 1 As shown, it is a flowchart of the offline experience scenario experience analysis method in this embodiment;

[0059] This embodiment provides a method for analyzing the experience of offline experience scenarios, including:

[0060] The dwell time of each target in each monitoring area constructed based on a preset grid step size and the number of interactions of each interactive device within the dwell time are obtained at preset collection intervals.

[0061] Several temporary monitoring areas are determined based on the stated dwell time and the preset standard dwell time.

[0062] Based on the total number of interactions in each of the temporary monitoring areas within the preset monitoring time, several abnormal interaction areas are determined. Based on the number of abnormal interaction areas and the preset standard number of abnormalities, the adjustment interval determination result is determined. Based on the adjustment interval determination result, the preset grid step size is adjusted to form the first grid step size.

[0063] Based on the first grid step size, the preset historical duration, and the experience score of the interactive device, several areas to be improved are determined.

[0064] The determination of several areas for improvement based on the first grid step size, the preset historical duration, and the experience score of the interactive device includes:

[0065] The dwell time of each target in each monitoring area is obtained at the preset acquisition interval based on the first grid step size;

[0066] Based on the dwell time, several corrected monitoring areas are determined, and based on the number of interactive devices in the corrected monitoring areas, several temporary corrected monitoring areas are determined.

[0067] The first grid step size is adjusted according to all the temporary correction monitoring areas of the target within the preset historical time period until the area overlap rate determined based on the temporary correction monitoring area is greater than the preset standard overlap rate, thus forming the second grid step size.

[0068] Based on the experience scores of all interactive devices within each monitoring area constructed based on the second grid step size during the dwell time, several areas to be improved are identified;

[0069] Calculate the average value of the experience scores. If the average value is less than the preset standard score, the monitored area is determined to be an area to be improved, and corresponding measures are output according to the area to be improved.

[0070] Measures include: increasing the number of interactive devices and upgrading existing devices to improve the target experience; regularly evaluating experience scores and analyzing target behavior data to continuously monitor the effectiveness of improvements.

[0071] Specifically, the offline experience scenario experience analysis method provided in this embodiment of the invention is applied to an exhibition venue equipped with several interactive devices. These interactive devices include a display terminal and a control terminal. The display terminal is used to display exhibition content, and a large amount of data is generated during interaction with the user's control terminal. This data needs to be processed by the backend to provide feedback on the user's interaction. When the target enters the exhibition venue, they interact with the display terminal using the control terminal as needed.

[0072] The preset collection interval is adjusted according to the average value of all the areas to be improved within the preset scoring evaluation period until the experience score fluctuation value formed based on the average value is less than or equal to the preset standard experience score fluctuation value.

[0073] The abnormal interaction area includes a first abnormal interaction area and a second abnormal interaction area.

[0074] Experience ratings are scores that users give based on their experience using the device, reflecting their assessment of the device's interactivity and satisfaction.

[0075] The preset acquisition interval refers to the time interval for data acquisition during the monitoring process, which usually depends on the target's activity frequency and data analysis needs. It is generally set between 10 and 20 seconds; in this embodiment, it is set to 15 seconds, which can effectively capture changes in target activity without causing data redundancy.

[0076] The preset grid step size refers to the grid size used to divide the monitoring area within the exhibition space, which depends on the size of the exhibition space and the distribution of interactive devices. It is usually set between 0.5 meters and 2 meters; in this embodiment, it is set to 1 meter, which ensures both coverage area and monitoring detail.

[0077] The preset standard dwell time refers to the ideal dwell time of a target within a specific monitoring area, which depends on the complexity of the exhibition content and the expected interaction of the target. It is generally set between 40 and 50 seconds; in this embodiment, it is set to 45 seconds, which can better reflect the target's true interest and experience.

[0078] The preset standard number of devices refers to the number of interactive devices expected to be set up in a certain monitoring area, which depends on the layout of the site and the target traffic flow. It is usually set between 2 and 5 units. This embodiment sets it to 3 units, which can balance the target experience and device utilization.

[0079] The preset standard interaction frequency fluctuation range refers to the fluctuation range of the number of interactions between the target and the device within a specific time period, which depends on the nature of the activity and the target's level of participation. It is generally set between ±1 and ±3 times, and this embodiment is set to ±2 times, which can flexibly cope with the normal fluctuations in the target's behavior.

[0080] The preset standard number of anomalies refers to the number of abnormal interaction areas that are acceptable during the monitoring process. It depends on the nature of the exhibition activities and the target behavior patterns, and is usually set between 1 and 3. In this embodiment, it is set to 2, which can effectively identify abnormal behavior without being too sensitive to normal fluctuations.

[0081] The preset historical duration refers to the historical data period used to analyze target behavior, which depends on the amount of available data and the needs of behavior analysis. It can be set according to the exhibition time, and is generally set between 1 and 3 days. In this embodiment, it is set to 2 days, which can reflect the changing trend of target behavior in a timely manner.

[0082] The preset standard overlap rate refers to the allowed overlap ratio between target areas in regional overlap analysis, such as 70%. This depends on the target's interaction habits and spatial layout. It is typically set between 60% and 80%, and in this embodiment, it is set to 70%, which effectively identifies overlap between targets while ensuring the accuracy of the analysis.

[0083] The preset standard score refers to the ideal score for the target experience, which depends on the target satisfaction survey and evaluation criteria. It is usually set between 7 and 9 points, and in this embodiment, it is set to 8 points to ensure a high-quality standard for the target experience.

[0084] The preset rating assessment time refers to the period of time required to evaluate the target experience rating, which depends on the exhibition content and the expected depth of target participation. Generally, it is sufficient to ensure that the target's true experience and feedback are fully captured.

[0085] The preset standard experience score fluctuation value refers to the acceptable fluctuation range of the target experience score, which depends on the reliability of the target feedback and the analysis requirements. It is generally set between ±0.5 and ±2 points. This embodiment sets it to ±1 point, which can flexibly handle normal fluctuations in the score, thereby improving the accuracy of the evaluation.

[0086] First, the target dwell time and number of interactions with interactive devices in each monitoring area within the exhibition space are acquired at preset data collection intervals. Next, areas to be monitored are identified based on the dwell time and a preset standard dwell time, and temporary monitoring areas are confirmed. Abnormal interaction areas are identified by analyzing the number of interactions and the preset standard, and the grid step size is adjusted based on the number of anomalies to form the first grid step size. Then, the experience score is re-evaluated using this interval, and areas to be monitored are identified and corrected. The area overlap rate is calculated based on historical data, and the grid step size is adjusted to form the second grid step size. Finally, the average experience score of the interactive devices is compared with the preset standard score to determine areas needing improvement, and corresponding improvement measures are output. The data collection interval is then adjusted to optimize the evaluation process.

[0087] By dynamically adjusting the grid step size and data collection interval, this method can more flexibly adapt to changes in target behavior, thereby improving the accuracy and real-time performance of data collection. Simultaneously, analysis based on historical data helps to understand fluctuations in the target experience over different time periods, providing a strong basis for subsequent site optimization and equipment improvement. The implementation of this method will significantly improve target satisfaction, increase the attractiveness of exhibitions, and provide venue managers with scientific decision-making support, ensuring the rational allocation and use of resources. Ultimately, it achieves continuous optimization and improvement of exhibition effects, effectively solving the problem of ambiguous exhibition experience output due to insufficient interactive data analysis.

[0088] Please continue reading. Figure 2 As shown, it is the logic diagram for determining the first abnormal interaction area in this embodiment;

[0089] Specifically, determining several abnormal interaction areas based on all interaction counts in each of the temporary monitoring areas within a preset monitoring period includes:

[0090] Calculate the standard deviation of the number of interactions to form the interaction number standard deviation. When the interaction number standard deviation is less than the minimum value of the preset standard interaction number fluctuation range, and the difference between the minimum value of the interaction number fluctuation range and the interaction number standard deviation is less than the preset difference threshold, the temporary monitoring area is determined to be the first abnormal interaction area.

[0091] When the standard deviation of the number of interactions is less than the minimum value of the preset standard range of interaction number fluctuations, and the difference between the minimum value of the range of interaction number fluctuations and the standard deviation of the number of interactions is greater than or equal to the preset difference threshold, it is determined that there is a device malfunction, and relevant personnel are notified to go to the temporary monitoring area for repair.

[0092] The preset difference threshold is a threshold used to determine the difference between the extreme value of the fluctuation range of interaction frequency and the standard deviation of the actual number of interactions. It helps to determine whether there is abnormal interaction behavior in the temporary monitoring area. Typically, the size of the preset difference threshold depends on factors such as the device's interaction sensitivity, the expected range of interaction frequency fluctuations, and the size of the site. It is usually set to 1 to 3; in this embodiment, it is set to 2 to ensure that minor interaction anomalies can be identified in a timely manner.

[0093] By acquiring the dwell time and interaction frequency of each target in the exhibition area, a monitoring area is constructed based on a preset grid step size and divided into temporary monitoring areas. The standard deviation of interaction frequency for each interactive device is calculated to determine if any abnormal interaction areas exist. When the standard deviation of interaction frequency is less than the minimum value of a preset standard fluctuation range, and the difference between this minimum value and the standard deviation is less than a preset difference threshold, the temporary monitoring area is identified as the first abnormal interaction area. Based on these determinations, the grid step size and data collection interval are dynamically adjusted to ensure a reasonable layout of exhibition equipment and optimized target experience.

[0094] By accurately analyzing fluctuations in the number of interactions, abnormal interaction areas in the exhibition area can be identified in a timely manner, and the grid step size and collection interval can be flexibly adjusted according to the actual situation, thereby improving the accuracy and efficiency of monitoring.

[0095] Please continue reading. Figure 3 As shown, this is the logic diagram for determining the second abnormal interaction region in this embodiment;

[0096] Specifically, determining several abnormal interaction areas based on all interaction counts in each of the temporary monitoring areas within a preset monitoring period further includes:

[0097] When the standard deviation of the number of interactions is greater than the maximum value of the preset standard interaction number fluctuation range, and the difference between the standard deviation of the number of interactions and the maximum value of the preset standard interaction number fluctuation range is less than the preset difference threshold, the temporary monitoring area is determined to be the second abnormal interaction area.

[0098] If the standard deviation of the number of interactions is greater than the maximum value of the preset standard fluctuation range but the difference is less than the preset difference threshold, it is identified as the second abnormal interaction area. For these abnormal areas, the target experience is further optimized by adjusting the interactive device or grid step size. The main difference between the first and second abnormal interaction areas lies in the fluctuation characteristics of the number of interactions. The first abnormal interaction area refers to a situation where the standard deviation of the number of interactions is less than the minimum value of the preset standard interaction fluctuation range, and the difference between its fluctuation range and the standard deviation is less than the preset difference threshold. This indicates that the interaction behavior in these areas is relatively stable but lower than expected. This means that in this area, the fluctuation of the number of interactions is relatively small and relatively stable, but compared to expectations, the number of interactions is lower than the preset standard. A small standard deviation and a small fluctuation range may indicate low target engagement and the number of interactions does not meet expectations, but the overall performance is relatively stable. In contrast, the second abnormal interaction area is characterized by a standard deviation of interaction counts exceeding the maximum value of the preset standard interaction count fluctuation range. This indicates that while these areas have a high number of interactions, the volatility is excessive, suggesting uneven participation from the target audience. The difference between the standard deviation and the maximum value is less than the preset threshold, indicating that while these areas exhibit high volatility, they haven't deviated too far from expectations. Therefore, these areas still require attention, and appropriate optimization measures should be taken. Thus, identifying these two types of areas helps managers implement corresponding improvement measures for different interaction patterns to optimize the overall target experience.

[0099] Identifying the second abnormal interaction area can reveal potential problem areas and provide data support for subsequent optimization measures.

[0100] Please continue reading. Figure 4 As shown, it is the determination logic diagram for determining the adjustment spacing result in this embodiment;

[0101] Specifically, the determination of the adjustment spacing based on the number of abnormal interaction areas and the preset standard number of abnormalities includes:

[0102] When the number of the first abnormal interaction areas is greater than the preset standard number of abnormalities, it is determined that the preset grid step size needs to be increased, thus forming the increased spacing determination result.

[0103] By comparing the number of abnormal interaction areas with a preset standard number of abnormalities, if the number of the first abnormal interaction areas exceeds the preset standard number of abnormalities, the system will determine that the preset grid step size needs to be increased to form a judgment result of increased spacing. This process aims to monitor abnormal interaction areas and adjust the grid step size in a timely manner to ensure that the monitoring system can more effectively capture the true situation of target interaction.

[0104] By analyzing the number of abnormal interaction areas, we can promptly identify areas with poor target user experience and make appropriate spacing adjustments.

[0105] Specifically, the determination of the adjustment spacing based on the number of abnormal interaction areas and the preset standard number of abnormalities also includes:

[0106] When the number of the second abnormal interaction areas is greater than the preset standard number of abnormalities, it is determined that the preset grid step size needs to be reduced, thus forming the reduced spacing determination result.

[0107] During monitoring, if the number of second abnormal interaction areas detected exceeds the preset standard number of abnormalities, the system will determine that the current grid step size is too large, resulting in insufficient interaction effects. Therefore, based on this finding, the system will adjust the preset grid step size to reduce the spacing, so as to better capture the target's behavior and needs in subsequent interactive experiences.

[0108] By adjusting the grid step size in a timely manner, especially when the number of second abnormal interaction areas exceeds the limit, it is possible to more effectively enhance the capture and feedback of target behavior, thereby improving the overall experience of the target.

[0109] Specifically, adjusting the preset grid step size based on the adjustment spacing determination result to form the first grid step size includes:

[0110] When the adjustment spacing determination result is the increase spacing determination result, the preset grid step size is increased according to the standard deviation of the number of interactions, the maximum value of the preset standard interaction number fluctuation range, the preset difference threshold, and the preset first spacing adjustment coefficient to form the first grid step size;

[0111] When the adjustment spacing determination result is the reduction spacing determination result, the preset grid step size is reduced according to the standard deviation of the number of interactions, the minimum value of the preset standard interaction number fluctuation range, the preset difference threshold, and the preset first spacing adjustment coefficient to form the first grid step size;

[0112] The preset first spacing adjustment coefficient is an important parameter for dynamically adjusting the grid step size. Its main function is to flexibly adjust the preset grid step size based on the difference between the standard deviation of the number of interactions and the maximum value of the preset standard interaction number fluctuation range, thereby optimizing the interaction effect in the monitoring area. Depending on historical data analysis, target behavior patterns, and specific application scenarios, it is usually set between 0.1 and 1.0. In this embodiment, it is set to 0.5, which enables more flexible grid adjustment and effectively copes with the fluctuation of interactive device usage.

[0113] After determining the adjustment result for the spacing, the system will adjust the grid step size accordingly. If the result is to increase the spacing, the system will use the standard deviation of the number of interactions, the maximum value of the preset standard interaction number fluctuation range, the preset difference threshold, and the preset first spacing adjustment coefficient to increase the grid step size, forming a new first grid step size. If the result is to decrease the spacing, the system will refer to the standard deviation of the number of interactions, the minimum value of the preset standard interaction number fluctuation range, the preset difference threshold, and the preset second spacing adjustment coefficient to decrease the grid step size, ultimately also forming a first grid step size.

[0114] By flexibly adjusting the grid step size, the system can effectively optimize the interaction effect of the monitored area, ensuring that the number of interactions in each area is more in line with the target experience and actual needs.

[0115] Specifically, the step of determining the regional overlap rate based on all the temporary correction monitoring areas of the target within a preset historical period, and adjusting the first grid step size according to the regional overlap rate and the preset standard overlap rate until the regional overlap rate is greater than the preset standard overlap rate, to form the second grid step size includes:

[0116] Calculate the ratio of the preset historical duration to the preset collection interval to obtain the total number of collections;

[0117] Obtain the number of overlapping cells in all the temporary correction monitoring areas of the target to obtain the overlap count;

[0118] The region overlap rate is calculated based on the number of overlaps, the total number of data collections, the first grid step size, and the preset site area.

[0119] When the region overlap rate is less than or equal to the preset standard overlap rate, the first grid step size is reduced according to the region overlap rate, the preset standard overlap rate and the preset second spacing adjustment coefficient until the region overlap rate is greater than the preset standard overlap rate, thus forming the second grid step size;

[0120] The calculation of the regional overlap rate based on the number of overlaps, the total number of data collections, the first grid step size, and the preset site area includes:

[0121] Calculate the square of the first grid step size to obtain the area of ​​the grid constructed based on the first grid step size. Calculate the product of this area and the number of overlaps to obtain the overlapping area of ​​the overlapping grids in a single acquisition. Calculate the product of this overlapping area and the total number of acquisitions to obtain the total overlapping area of ​​all overlapping grids acquired within a preset historical time period. Calculate the ratio of the total overlapping area to the preset site area to obtain the overlap rate of the region.

[0122] The preset site area refers to the total area of ​​the monitoring area or exhibition space pre-defined during experience analysis. It depends on the actual size and layout of the exhibition space and the fluidity of the exhibition content's presentation. It is typically set between tens of square meters and tens of thousands of square meters; in this embodiment, it is set to 500 square meters to ensure comprehensive coverage of the target area during data analysis.

[0123] The preset second spacing adjustment coefficient is a proportional coefficient used to adjust the first grid step size to achieve the desired overlap rate of the area. It is usually determined based on past experience or experimental data to achieve optimized monitoring results. The common setting range is between 0.1 and 0.5. In this embodiment, it is set to 0.3. By adjusting the coefficient reasonably, the grid step size can be dynamically optimized, thereby improving the overlap rate of the monitoring area.

[0124] Based on the preset historical duration, the ratio of the preset historical duration to the acquisition interval is first calculated to determine the total number of acquisitions. Next, the number of overlapping cells within the target's temporary correction monitoring area is obtained, thus determining the overlap count. Then, the area overlap rate is calculated using the overlap count, the total number of acquisitions, the first grid step size, and the preset site area. When the area overlap rate is less than or equal to the preset standard overlap rate, the first grid step size is gradually reduced using a preset second spacing adjustment coefficient until the area overlap rate exceeds the preset standard, thus forming a new second grid step size.

[0125] By optimizing the grid step size, it is possible to ensure effective overlap between monitoring areas while dynamically adjusting the monitoring area, thereby improving the monitoring accuracy and effectiveness of interactive devices.

[0126] Specifically, determining the experience score fluctuation value based on the average value of all areas to be improved within a preset evaluation period, and adjusting the preset collection interval based on the experience score fluctuation value and a preset standard experience score fluctuation value until the experience score fluctuation value is less than or equal to the preset standard experience score fluctuation value includes:

[0127] Calculate the standard deviation of the average score to obtain the experience score fluctuation value. When the experience score fluctuation value is greater than the preset standard experience score fluctuation value, it is determined that the preset collection interval needs to be adjusted to form an interval correction determination result. When forming the interval correction determination result, the preset collection interval is reduced according to the experience score fluctuation value, the preset standard experience score fluctuation value, and the preset interval adjustment coefficient.

[0128] Within a preset evaluation period, the average score of all areas to be improved is calculated to obtain its standard deviation, thus yielding the experience score fluctuation value. When this fluctuation value exceeds the preset standard experience score fluctuation value, the system determines that the preset collection interval needs to be adjusted and generates an interval correction judgment result. During this process, based on the experience score fluctuation value, the preset standard experience score fluctuation value, and the preset interval adjustment coefficient, the preset collection interval is appropriately reduced to achieve a more flexible collection frequency.

[0129] By assessing the fluctuation of all average scores within a preset evaluation period, the frequency and accuracy of data collection can be improved, and it also helps to monitor changes in the target experience in real time.

[0130] Specifically, determining several temporary monitoring areas based on the dwell time and the preset standard dwell time includes:

[0131] When the dwell time exceeds the preset standard dwell time, the monitoring area is determined to be the area to be monitored, and several temporary monitoring areas are determined based on the area to be monitored.

[0132] By comparing the real-time monitored dwell time with a preset standard dwell time, areas requiring focused attention are identified. When the actual dwell time exceeds the preset standard, the system automatically designates that area as a monitoring area. This determination mechanism ensures a sensitive response to target behavior and helps to promptly identify potential problems.

[0133] This method can effectively identify abnormal stays of targets in specific areas, enabling in-depth analysis and monitoring.

[0134] Specifically, determining several temporary monitoring areas based on the area to be monitored includes:

[0135] When the number of devices exceeds the preset standard number of devices, the area to be monitored is determined to be a temporary monitoring area.

[0136] By comparing the actual number of interactive devices in the monitored area with the preset standard number of devices, the system determines whether to designate the area as a temporary monitoring area. When the number of devices exceeds the set standard, the system automatically classifies the area as a temporary monitoring area. This helps to focus monitoring on specific areas in a timely manner when device usage is intensive.

[0137] By identifying temporary monitoring areas, areas with excessive equipment usage can be quickly identified, allowing for closer monitoring and analysis.

[0138] The technical solution of the present invention has been described above with reference to the preferred embodiments shown in the accompanying drawings. However, it will be readily understood by those skilled in the art that the scope of protection of the present invention is obviously not limited to these specific embodiments. Without departing from the principles of the present invention, those skilled in the art can make equivalent changes or substitutions to the relevant technical features, and the technical solutions after these changes or substitutions will all fall within the scope of protection of the present invention.

[0139] The above description is merely a preferred embodiment of the present invention and is not intended to limit the invention. Various modifications and variations can be made to the present invention by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. A method for analyzing the experience of offline experience scenarios, applied in an exhibition venue equipped with several interactive devices, wherein the interactive devices include a display terminal and a control terminal, the display terminal being used to display exhibition content, characterized in that... include: The dwell time of each target in each monitoring area constructed based on a preset grid step size and the number of interactions of each interactive device within the dwell time are obtained at preset collection intervals. Several temporary monitoring areas were determined based on the duration of stay and the preset standard duration of stay. Several abnormal interaction areas are determined based on the total number of interactions in each temporary monitoring area within the preset monitoring period, including: Calculate the standard deviation of the number of interactions to form the standard deviation of the number of interactions. When the standard deviation of the number of interactions is less than the minimum value of the preset standard interaction number fluctuation range, and the difference between the minimum value of the preset standard interaction number fluctuation range and the standard deviation of the number of interactions is less than the preset difference threshold, the temporary monitoring area is determined to be the first abnormal interaction area. When the standard deviation of the number of interactions is greater than the maximum value of the preset standard interaction number fluctuation range, and the difference between the standard deviation of the number of interactions and the maximum value of the preset standard interaction number fluctuation range is less than the preset difference threshold, the temporary monitoring area is determined to be the second abnormal interaction area. The adjustment spacing determination result is determined based on the number of abnormal interaction areas and the preset standard abnormal number. The preset grid step size is then adjusted based on the adjustment spacing determination result to form the first grid step size. Based on the first grid step size, the preset historical duration, and the experience score of the interactive device, several areas to be improved are identified, including: obtaining the dwell time of each target in each monitoring area constructed based on the first grid step size at a preset collection interval; Based on the duration of stay, several areas to be monitored for correction are determined, and based on the number of interactive devices in the areas to be monitored for correction, several temporary areas to be monitored for correction are determined. The first grid step size is adjusted based on all temporary correction monitoring areas of the target within the preset historical time period until the regional overlap rate determined based on the temporary correction monitoring areas is greater than the preset standard overlap rate, forming the second grid step size, including: Calculate the ratio of the preset historical duration to the preset collection interval to obtain the total number of collections; Obtain the number of overlapping cells in the entire temporary correction monitoring area of ​​the target to get the overlap count; The region overlap rate is calculated based on the number of overlaps, the total number of data collections, the first grid step size, and the preset site area. When the regional overlap rate is less than or equal to the preset standard overlap rate, the first grid step size is reduced according to the regional overlap rate, the preset standard overlap rate and the preset second spacing adjustment coefficient until the regional overlap rate is greater than the preset standard overlap rate, thus forming the second grid step size. Based on the experience scores of all interactive devices within each monitoring area constructed based on the second grid step size during the dwell time, several areas to be improved were identified; Adjust the preset collection interval based on all experience scores of the areas to be improved within the preset evaluation period until the fluctuation value of the experience score formed based on the experience score is less than or equal to the preset standard experience score fluctuation value.

2. The method for analyzing the experience of offline experience scenarios according to claim 1, characterized in that, The determination of the adjustment spacing based on the number of abnormal interaction areas and the preset standard number of abnormalities includes: When the number of the first abnormal interaction areas is greater than the preset standard number of abnormalities, it is determined that the preset grid step size needs to be increased, resulting in an increased spacing determination result.

3. The method for analyzing the experience of offline experience scenarios according to claim 2, characterized in that, The determination of the adjustment spacing based on the number of abnormal interaction areas and the preset standard number of abnormalities also includes: When the number of the second abnormal interaction areas is greater than the preset standard number of abnormalities, it is determined that the preset grid step size needs to be reduced, resulting in a reduction in spacing determination result.

4. The method for analyzing the experience of offline experience scenarios according to claim 3, characterized in that, The step of adjusting the preset grid step size according to the adjustment spacing determination result to form the first grid step size includes: When the adjustment spacing determination result is the increase spacing determination result, the preset grid step size is increased according to the standard deviation of the number of interactions, the maximum value of the preset standard interaction number fluctuation range, the preset difference threshold, and the preset first spacing adjustment coefficient to form the first grid step size; When the adjustment spacing determination result is the reduction spacing determination result, the preset grid step size is reduced according to the standard deviation of the number of interactions, the minimum value of the preset standard interaction number fluctuation range, the preset difference threshold, and the preset first spacing adjustment coefficient to form the first grid step size.

5. The method for analyzing the experience of offline experience scenarios according to claim 4, characterized in that, The step of adjusting the preset collection interval based on all experience scores of the area to be improved within a preset evaluation period until the experience score fluctuation value formed based on the experience score is less than or equal to the preset standard experience score fluctuation value includes: Calculate the standard deviation of the average score of the experience rating to obtain the experience rating fluctuation value. When the experience rating fluctuation value is greater than the preset standard experience rating fluctuation value, it is determined that the preset collection interval needs to be adjusted. The preset collection interval is reduced according to the experience rating fluctuation value, the preset standard experience rating fluctuation value and the preset interval adjustment coefficient.

6. The method for analyzing the experience of offline experience scenarios according to claim 5, characterized in that, The determination of several temporary monitoring areas based on the dwell time and the preset standard dwell time includes: When the dwell time exceeds the preset standard dwell time, the monitoring area is determined to be the area to be monitored, and several temporary monitoring areas are determined based on the area to be monitored.

7. The method for analyzing the experience of offline experience scenarios according to claim 6, characterized in that, The determination of several temporary monitoring areas based on the area to be monitored includes: When the number of devices exceeds the preset standard number of devices, the area to be monitored is determined to be a temporary monitoring area.

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