Method for analyzing experience degree of offline experience scene

Abstract

The invention relates to the technical field of data analysis, in particular to an experience degree analysis method for an offline experience scene, and the method comprises the steps: obtaining the stay duration and interaction times of a target; identifying a to-be-monitored area and a temporary monitoring area; abnormal interaction is recognized, and the grid step length is adjusted; obtaining an experience score of the interactive device; the grid step size and the acquisition interval are adjusted to improve the experience score. According to the method, the behavior change of the target can be more flexibly adapted by dynamically adjusting the grid step length and the acquisition interval, so that the accuracy and the real-time performance of data acquisition are improved, the fluctuation condition of target experience can be acquired in different time periods based on analysis of historical data, a powerful basis is provided for subsequent site optimization and equipment improvement, and the method is suitable for popularization and application. According to the method, the exhibition attraction can be increased, scientific decision support is provided for venue managers, the exhibition effect is continuously optimized and improved finally, and the problem that exhibition experience output is fuzzy due to insufficient interaction data analysis is effectively solved.

Description

Technical Field

[0001] The present invention relates to the field of data analysis technology, and in particular to an experience analysis method for an offline experience scenario. Background Art

[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, how to improve the experience of participants and obtain accurate data analysis to optimize subsequent activities has become a key issue that the industry needs to solve. Although existing technologies can provide certain interactions and feedback, they still have limitations in data analysis and experience evaluation, resulting in the final output of experience information that is not clear and effective enough.

[0003] The patent document with the Chinese patent application publication number CN113923246A discloses a method and device for immersive online video scene experience. The method includes: establishing a virtual resource list corresponding to the scene according to the objects in the scene and the dependency class parameters contained in the objects; storing the resources and virtual resource list of the scene on the server according to the preset storage method; setting the call strategy for each content editor in the scene to establish the virtual scene; receiving a request to establish a virtual scene, analyzing the request to obtain the construction strategy, virtual resource list and call strategy of the target scene; according to the virtual resource list and call strategy of the target scene, sequentially downloading the resource data of the scene from the server and storing it locally; according to the construction strategy and call strategy of the target scene, creating a virtual target scene with the resource data stored locally, and cooperating with the real scene to form an immersive scene for display.

[0004] This method relies on a list of virtual resources stored on a server. If the server fails or the network is unstable, the loading and experience of the scene will be affected. This method needs to download resource data from the server during the scene creation process, which causes delays and affects the user's sense of immersion. The scene building strategy and calling strategy of this method are preset and cannot quickly adapt to changes in user needs or personalized customization, resulting in blurred output of the exhibition experience. Summary of the invention

[0005] To this end, the present invention provides an experience analysis method for an offline experience scenario, so as to overcome the problem in the prior art that the output of exhibition experience is fuzzy due to insufficient interactive data analysis.

[0006] To achieve the above object, the present invention provides an experience analysis method for offline experience scenarios, comprising:

[0007] The residence time of each target in each monitoring area constructed based on the preset grid step length in the site and the number of interactions of each interactive device within the residence time are obtained at the preset collection interval;

[0008] Determine a number of temporary monitoring areas according to the length of stay and a preset standard length of stay;

[0009] Determine a number of abnormal interaction areas according to the total number of interactions in each of the temporary monitoring areas within a preset monitoring time, determine an adjustment interval determination result according to the number of abnormal interaction areas and a preset standard abnormal number, and adjust the preset grid step length according to the adjustment interval determination result to form a first grid step length;

[0010] Determine a number of areas to be improved according to the first grid step length, the preset historical duration, and the experience score of the interactive device;

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

[0012] Furthermore, the determining of a number of areas to be improved according to the first grid step, the preset historical duration, and the experience score of the interactive device includes:

[0013] Acquire the residence time of each target in each monitoring area constructed based on the first grid step size at the preset collection interval;

[0014] Determine a number of modified monitored areas according to the length of stay, and determine a number of temporary modified monitored areas according to the number of interactive devices in the modified monitored areas;

[0015] Adjust the first grid step length according to all the temporarily corrected monitoring areas of the target within the preset historical time period in the past until the area overlap rate determined based on the temporarily corrected monitoring areas is greater than the preset standard overlap rate, thereby forming a second grid step length;

[0016] Determine a number of areas to be improved according to the experience scores of all the interactive devices within each monitoring area constructed based on the second grid step size within the residence time;

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

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

[0019] The standard deviation of the number of interactions is calculated to form a standard deviation of the number of interactions. When the standard deviation of the number of interactions is smaller 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 standard deviation of the number of interactions is smaller than the preset difference threshold, the temporary monitoring area is determined to be the first abnormal interaction area.

[0020] Furthermore, the determining of a number of abnormal interaction areas according to all the interaction times in each of the temporary monitoring areas within a preset monitoring time 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] Further, the step of determining the adjustment interval determination result according to the number of abnormal interaction areas and the preset standard abnormal number includes:

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

[0024] Furthermore, the step of determining the adjustment interval determination result according to the number of abnormal interaction areas and the preset standard abnormal number also includes:

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

[0026] Further, adjusting the preset grid step size according to the adjustment interval determination result to form a first grid step size includes:

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

[0028] When the adjustment spacing judgment result is the reduction spacing judgment 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 number of interactions fluctuation range, the preset difference threshold and the preset first spacing adjustment coefficient to form a first grid step size.

[0029] Further, adjusting the first grid step size according to all the temporarily corrected monitoring areas of the target within the preset historical time period in the past until the area overlap rate determined based on the temporarily corrected 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 collection times;

[0031] Obtain the number of overlapping cells of all the temporarily corrected monitoring areas of the target to obtain an overlapping number;

[0032] Calculate the area overlap rate according to the overlap number, the total number of acquisitions, the first grid step size, and a preset site area;

[0033] 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 to form a second grid step size.

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

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

[0036] Furthermore, the determining of a number of temporary monitoring areas according to the stay duration and the preset standard stay duration includes:

[0037] When the stay time is longer than the preset standard stay time, the monitored area is determined to be an area to be monitored, and a number of temporary monitoring areas are determined according to the area to be monitored.

[0038] Furthermore, the determining of a plurality of temporary monitoring areas according to the area to be monitored includes:

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

[0040] Compared with the prior art, the beneficial effect of the present invention is that by dynamically adjusting the grid step size and the collection interval, the method can more flexibly adapt to the behavioral changes of the target, thereby improving the accuracy and real-time performance of data collection. At the same time, based on the analysis of historical data, it is helpful to obtain the fluctuations of the target experience in 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 the exhibition, and provide scientific decision-making support for venue managers, ensuring the rational allocation and use of resources, and ultimately achieving continuous optimization and improvement of the exhibition effect, effectively solving the problem of fuzzy output of exhibition experience due to insufficient interactive data analysis.

[0041] Furthermore, by accurately analyzing the fluctuations in the number of interactions, abnormal interaction areas in the exhibition venue are identified in a timely manner, and the grid step size and collection interval are flexibly adjusted according to actual conditions, the accuracy and efficiency of monitoring are improved.

[0042] Furthermore, by determining the second abnormal interaction area, potential problem areas can be revealed and data support can be provided 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, so that appropriate spacing adjustments can be made.

[0044] Furthermore, by timely adjusting the grid step size, especially when the number of second abnormal interaction areas exceeds the limit, the capture and feedback of target behaviors can be more effectively enhanced, thereby improving the overall experience of the target.

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

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

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

[0048] Furthermore, this method can effectively identify the abnormal stay of the target in a specific area, and then conduct in-depth analysis and monitoring.

[0049] Furthermore, by determining the temporary monitoring area, it is possible to quickly identify areas where equipment is overused, allowing for closer monitoring and analysis. BRIEF DESCRIPTION OF THE DRAWINGS

[0050] Figure 1 This is a flow chart of the experience degree analysis method for offline experience scenarios in this embodiment;

[0051] Figure 2 A decision logic diagram for determining the first abnormal interaction area for this implementation;

[0052] Figure 3 A decision logic diagram for determining a second abnormal interaction area for this implementation;

[0053] Figure 4 Decision logic diagram for determining the adjustment spacing decision result for this implementation. DETAILED DESCRIPTION

[0054] In order to make the objects and advantages of the present invention more clearly understood, the present invention is further described below in conjunction with embodiments; it should be understood that the specific embodiments described herein are only used to explain the present invention and are not used to limit the present invention.

[0055] The preferred embodiments of the present invention are described below with reference to the accompanying drawings. It should be understood by those skilled in the art that these embodiments are only used to explain the technical principles of the present invention and are not intended to limit the protection scope of the present invention.

[0056] It should be noted that, in the description of the present invention, terms such as "up", "down", "left", "right", "inside" and "outside" indicating directions or positional relationships are based on the directions or positional relationships shown in the drawings. This is merely for the convenience of description and does not indicate or imply that the device or element must have a specific orientation, be constructed and operated in a specific orientation. Therefore, it cannot be understood as a limitation on the present invention.

[0057] In addition, it should be noted that in the description of the present invention, unless otherwise clearly specified and limited, the terms "installed", "connected", and "connected" should be understood in a broad sense, for example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be a direct connection, or it can be indirectly connected through an intermediate medium, or it can be the internal communication of two components. For those skilled in the art, the specific meanings of the above terms in the present invention can be understood according to specific circumstances.

[0058] See also Figure 1 As shown, it is a flow chart of the experience degree analysis method of the offline experience scenario of this embodiment;

[0059] This embodiment provides an experience analysis method for an offline experience scenario, including:

[0060] The residence time of each target in each monitoring area constructed based on the preset grid step length in the site and the number of interactions of each interactive device within the residence time are obtained at the preset collection interval;

[0061] Determine a number of temporary monitoring areas according to the length of stay and a preset standard length of stay;

[0062] Determine a number of abnormal interaction areas according to the total number of interactions in each of the temporary monitoring areas within a preset monitoring time, determine an adjustment interval determination result according to the number of abnormal interaction areas and a preset standard abnormal number, and adjust the preset grid step length according to the adjustment interval determination result to form a first grid step length;

[0063] Determine a number of areas to be improved according to the first grid step length, the preset historical duration, and the experience score of the interactive device;

[0064] The determining of a number of areas to be improved according to the first grid step length, the preset historical duration, and the experience score of the interactive device comprises:

[0065] Acquire the residence time of each target in each monitoring area constructed based on the first grid step size at the preset collection interval;

[0066] Determine a number of modified monitored areas according to the length of stay, and determine a number of temporary modified monitored areas according to the number of interactive devices in the modified monitored areas;

[0067] Adjust the first grid step length according to all the temporarily corrected monitoring areas of the target within the preset historical time period in the past until the area overlap rate determined based on the temporarily corrected monitoring areas is greater than the preset standard overlap rate, thereby forming a second grid step length;

[0068] Determine a number of areas to be improved according to the experience scores of all the interactive devices within each monitoring area constructed based on the second grid step size within the residence time;

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

[0070] Measures include: increasing the number of interactive devices and upgrading existing devices to enhance the target experience; regularly evaluating experience scores and analyzing target behavior data, and continuously monitoring improvement effects.

[0071] Specifically, the experience degree analysis method of offline experience scene provided by the embodiment of the present invention is 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 is used to display exhibition content, and a lot of data will be generated in the process of interacting with the control terminal used by the user. These data need to be processed by the background, and then feedback is generated on the user's interaction. When the target enters the exhibition venue, the control terminal is used to interact with the display terminal according to actual needs.

[0072] Adjust the preset collection interval according to all the average values ​​of the area to be improved within the preset score evaluation time 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] The experience score is the score given by the target on the device based on the usage experience, reflecting the target's evaluation of the device interaction effect and satisfaction.

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

[0076] The preset grid step size refers to the grid size for dividing the monitoring area in the exhibition venue, which depends on the size of the exhibition venue 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 can ensure the coverage area while ensuring the monitoring detail.

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

[0078] The preset standard number of devices refers to the number of interactive devices expected to be set in a certain monitoring area, which depends on the layout of the site and the target traffic. It is usually set between 2 and 5, and in this embodiment it is set to 3, 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, which depends on the nature of the activity and the target's participation. It is generally set between ±1 and ±3 times, and is set to ±2 times in this embodiment, which can flexibly cope with normal fluctuations in target behavior.

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

[0081] The preset historical duration refers to the historical data time period used to analyze the 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, generally set between 1 day and 3 days, and this embodiment is set to 2 days, which can reflect the changing trend of the target behavior in a timely manner.

[0082] The preset standard overlap rate refers to the overlap ratio allowed between target areas in the area overlap analysis, for example, 70%. It depends on the interaction habits and spatial layout of the target. It is usually set between 60% and 80%. In this embodiment, it is set to 70%, which can effectively identify the overlap between targets while ensuring the accuracy of the analysis.

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

[0084] The preset scoring evaluation time refers to the time period required to evaluate the target experience score, which depends on the exhibition content and the expected depth of the target's participation. Generally, it is sufficient to ensure that the target's real 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. In this embodiment, it is set to ±1 point, which can flexibly cope with the normal fluctuation of the score, thereby improving the accuracy of the evaluation.

[0086] First, the target dwell time of each monitoring area and the number of interactions of the interactive devices are obtained in the exhibition venue through the preset collection interval. Then, the area to be monitored is identified based on the dwell time and the preset standard dwell time, and the temporary monitoring area is confirmed. By analyzing the number of interactions and the preset standard, the abnormal interaction area is determined, and the grid step size is adjusted according to the number of abnormalities to form the first grid step size. After that, the experience score is re-evaluated using this spacing and the area to be monitored is 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 area to be improved is determined by comparing the average experience score of the interactive device with the preset standard score, and the corresponding improvement measures are output, and finally the collection interval is adjusted to optimize the evaluation process.

[0087] By dynamically adjusting the grid step size and collection interval, this method can more flexibly adapt to the behavioral changes of the target, thereby improving the accuracy and real-time performance of data collection. At the same time, based on the analysis of historical data, it is helpful to obtain the fluctuations of the target experience in 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 the exhibition, and provide scientific decision-making support for venue managers, ensuring the rational allocation and use of resources, and ultimately achieving continuous optimization and improvement of the exhibition effect, effectively solving the problem of fuzzy output of exhibition experience due to insufficient interactive data analysis.

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

[0089] Specifically, the determining of a number of abnormal interaction areas according to the total number of interactions in each of the temporary monitoring areas within a preset monitoring time period includes:

[0090] The standard deviation of the number of interactions is calculated to form a standard deviation of the number of interactions. When the standard deviation of the number of interactions is smaller 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 standard deviation of the number of interactions is smaller than a 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 smaller 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 standard deviation of the number of interactions is greater than or equal to the preset difference threshold, it is determined that there is an equipment failure, and relevant personnel are notified to go to the temporary monitoring area for repairs.

[0092] The preset difference threshold is a threshold used to determine the difference between the extreme value of the interaction frequency fluctuation range and the standard deviation of the actual interaction frequency. It helps determine whether there is abnormal interaction behavior in the temporary monitoring area. Generally, the size of the preset difference threshold depends on factors such as the interaction sensitivity of the device, the expected range of interaction frequency fluctuation, and the scale 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 obtaining the duration of stay and number of interactions of each target in the exhibition venue, a monitoring area is constructed based on the preset grid step size and divided into temporary monitoring areas. By calculating the standard deviation of the number of interactions of each interactive device, it is determined whether there is an abnormal interaction area. When the standard deviation of the number of interactions is less than the minimum value of the preset standard fluctuation range, and the difference between the minimum value and the standard deviation is less than the preset difference threshold, the temporary monitoring area is determined to be the first abnormal interaction area. Based on these determination results, the grid step size and collection interval are dynamically adjusted to ensure the reasonable layout of the exhibition equipment and the optimization of the target experience.

[0094] By accurately analyzing fluctuations in the number of interactions, abnormal interaction areas in the exhibition venue are identified in a timely manner, and the grid step size and collection interval are flexibly adjusted according to actual conditions, the accuracy and efficiency of monitoring are improved.

[0095] Please continue reading Figure 3 As shown, it is a decision logic diagram for determining the second abnormal interaction area in this implementation;

[0096] Specifically, the determining of a number of abnormal interaction areas according to all the interaction times in each of the temporary monitoring areas within a preset monitoring time period also 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 and the difference is less than the preset difference threshold, it is determined to be 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 abnormal interaction area and the second abnormal interaction area lies in the fluctuation characteristics of the number of interactions. The first abnormal interaction area refers to the area where 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 its fluctuation range and the standard deviation is less than the preset difference threshold, which indicates that the interactive 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 with expectations, the number of interactions is lower and lower than the preset standard. A small standard deviation and a small fluctuation range may indicate that the target engagement is low and the number of interactions does not meet expectations, but the overall performance is relatively stable. In contrast, the second abnormal interaction area is where the standard deviation of the number of interactions is greater than the maximum value of the preset standard interaction number fluctuation range, indicating that although the number of interactions in these areas is high, the volatility is too large, which means that the target's participation in these areas is uneven, and the difference between the two is less than the preset difference threshold, indicating that although the volatility in these areas is too large, they have not deviated too far from expectations, so these areas still need to be paid attention to and appropriate optimization measures should be taken. Therefore, the identification of these two types of areas helps managers take corresponding improvement measures for different interaction modes to optimize the overall target experience.

[0099] By identifying the second abnormal interaction area, potential problem areas can be revealed and data support can be provided for subsequent optimization measures.

[0100] Please continue reading Figure 4 As shown, it is a decision logic diagram for determining the result of adjusting the spacing in this implementation;

[0101] Specifically, the step of determining the adjustment interval determination result according to the number of abnormal interaction areas and the preset standard abnormal number includes:

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

[0103] In the comparison between the number of abnormal interaction areas and the preset standard abnormal number, if it is found that the number of the first abnormal interaction areas exceeds the preset standard abnormal number, the system will determine that the preset grid step size needs to be increased to form a determination result of increasing the spacing. This process is intended to timely adjust the grid step size through monitoring of abnormal areas of interactive behavior, so as to ensure that the monitoring system can more effectively capture the true situation of the target interaction.

[0104] By analyzing the number of abnormal interaction areas, it is possible to promptly identify areas with poor target experience and make appropriate spacing adjustments.

[0105] Specifically, the step of determining the adjustment interval determination result according to the number of abnormal interaction areas and the preset standard abnormal number also includes:

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

[0107] During the monitoring process, if the number of second abnormal interaction areas found exceeds the preset standard abnormal number, the system will determine that the current grid step size is too large, resulting in insufficient interaction effect. Therefore, the system will adjust the preset grid step size based on this finding, forming a judgment result of reducing the spacing, so as to better capture the target's behavior and needs in the subsequent interactive experience.

[0108] By timely adjusting the grid step size, especially when the number of second abnormal interaction areas exceeds the limit, the capture and feedback of target behavior can be more effectively enhanced, thereby improving the overall experience of the target.

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

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

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

[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 according to the difference between the standard deviation of the number of interactions and the maximum value of the preset standard number of interactions fluctuation range, thereby optimizing the interactive effect of the monitoring area. It depends 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 can achieve more flexible grid adjustment and effectively cope with the usage fluctuations of interactive devices.

[0113] After determining the result of adjusting the spacing, the system will make corresponding grid step adjustments based on the specific adjustment results. If the result of the determination is to increase the spacing, the system will use the standard deviation of the number of interactions, the maximum value of the preset standard number of interactions fluctuation range, the preset difference threshold, and the preset first spacing adjustment coefficient to increase the grid step to form a new first grid step; if the result of the determination is to reduce the spacing, the system will refer to the standard deviation of the number of interactions, the minimum value of the preset standard number of interactions fluctuation range, the preset difference threshold, and the preset second spacing adjustment coefficient to reduce the grid step, and finally form the first grid step.

[0114] Through flexible adjustment of the grid step size, the system can effectively optimize the interactive effect of the monitoring area, ensuring that the number of interactions and target experience in each area are more in line with actual needs.

[0115] Specifically, determining the regional overlap rate according to all the temporarily corrected monitoring areas of the target within the preset historical time period in the past, adjusting the first grid step length 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, and forming the second grid step length includes:

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

[0117] Obtain the number of overlapping cells of all the temporarily corrected monitoring areas of the target to obtain an overlapping number;

[0118] Calculate the area overlap rate according to the overlap number, the total number of acquisitions, the first grid step size, and a preset site area;

[0119] When the area overlap rate is less than or equal to the preset standard overlap rate, reducing the first grid step length according to the area overlap rate, the preset standard overlap rate and the preset second spacing adjustment coefficient until the area overlap rate is greater than the preset standard overlap rate, thereby forming a second grid step length;

[0120] Calculating the area overlap rate according to the overlap number, the total number of acquisitions, the first grid step size, and the preset site area includes:

[0121] Calculate the square of the first grid step to obtain the area of ​​the grid constructed based on the first grid step, calculate the product of this area and the number of overlaps, obtain the overlapping area of ​​the overlapping grids collected in a single time, calculate the product of this overlapping area and the total number of collections, obtain the total overlapping area of ​​all overlapping grids collected within a preset historical time length, calculate the ratio of the total overlapping area to the preset site area, and obtain the regional overlap rate.

[0122] The preset venue area refers to the total area of ​​the monitoring area or exhibition venue that is preset when performing experience analysis. It depends on the size and layout of the actual exhibition venue and the fluidity of the display method of the exhibition content. It is usually set between tens of square meters and tens of thousands of square meters. In this embodiment, it is set to 500 square meters, which can ensure that the target area can be fully covered in the 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 area overlap rate. It is usually determined based on past experience or test data to achieve an optimized monitoring effect. The common setting range is between 0.1 and 0.5. In this embodiment, it is set to 0.3. Through a reasonable adjustment coefficient, the grid step size can be dynamically optimized to improve the overlap rate of the monitoring area.

[0124] According to the preset historical duration in the past, first calculate the ratio of the preset historical duration to the collection interval to determine the total number of collections; then obtain the number of overlapping cells in the temporarily corrected monitoring area of ​​the target to obtain the number of overlaps. Then calculate the regional overlap rate using the number of overlaps, the total number of collections, the first grid step, 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 is gradually reduced by the preset second spacing adjustment coefficient until the regional overlap rate exceeds the preset standard, thereby forming a new second grid step.

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

[0126] Specifically, determining the experience score fluctuation value according to all the average values ​​of the area to be improved within the preset score evaluation time, and adjusting the preset collection interval according to the experience score fluctuation value and the 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 an experience score fluctuation value; when the experience score fluctuation value is greater than a preset standard experience score fluctuation value, determine that the preset collection interval needs to be adjusted to form an interval correction determination result; and when forming the interval correction determination result, reduce the preset collection interval according to the experience score fluctuation value, the preset standard experience score fluctuation value, and the preset interval adjustment coefficient.

[0128] During the preset score evaluation period, all average scores of the areas to be improved are calculated to obtain their standard deviation, thereby obtaining the experience score fluctuation value. When the fluctuation value exceeds the preset standard experience score fluctuation value, the system determines that the preset collection interval needs to be adjusted and forms an interval correction determination result. In this process, according to 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 evaluating the fluctuation degree of all average scores within the preset scoring evaluation period, the frequency and accuracy of data collection can be improved, and it is also helpful to monitor the changes in target experience in real time.

[0130] Specifically, the determining of a number of temporary monitoring areas according to the stay duration and the preset standard stay duration includes:

[0131] When the stay time is longer than the preset standard stay time, the monitored area is determined to be an area to be monitored, and a number of temporary monitoring areas are determined according to the area to be monitored.

[0132] By comparing the real-time monitored stay time with the preset standard stay time, we can identify areas that need special attention. When the actual stay time exceeds the preset standard, the system will automatically determine that the area is to be monitored. This judgment mechanism ensures a sensitive response to the target behavior and helps to detect potential problems in a timely manner.

[0133] This method can effectively identify abnormal target stays in specific areas, allowing for in-depth analysis and monitoring.

[0134] Specifically, the determining of a number of temporary monitoring areas according to the area to be monitored includes:

[0135] When the number of devices is greater than 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, it is determined whether the area should be designated as a temporary monitoring area. When the number of devices exceeds the set standard, the system will automatically determine the area as a temporary monitoring area. This helps to focus on monitoring specific areas in a timely manner when the devices are used intensively.

[0137] By determining the temporary monitoring area, areas where equipment is overused can be quickly identified, allowing for closer monitoring and analysis.

[0138] So far, the technical solutions of the present invention have been described in conjunction with the preferred embodiments shown in the accompanying drawings. However, it is easy for those skilled in the art to understand that the protection scope of the present invention is obviously not limited to these specific embodiments. Without departing from the principle 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 fall within the protection scope of the present invention.

[0139] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. For those skilled in the art, the present invention may have various modifications and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. A method for analyzing the experience of an offline experience scenario, characterized in that: include: The residence time of each target in each monitoring area constructed based on the preset grid step length in the site and the number of interactions of each interactive device within the residence time are obtained at the preset collection interval; Determine a number of temporary monitoring areas according to the length of stay and a preset standard length of stay; Determine a number of abnormal interaction areas based on the total number of interactions in each temporary monitoring area within a preset monitoring period, determine an adjustment spacing determination result based on the number of abnormal interaction areas and a preset standard abnormal number, and adjust the preset grid step size based on the adjustment spacing determination result to form a first grid step size.

2. The experience analysis method of offline experience scene according to claim 1, characterized in that: Also includes: Determine a number of areas to be improved according to the first grid step length, the preset historical duration, and the experience score of the interactive device; The preset collection interval is adjusted according to all the experience scores of the area to be improved within a preset score evaluation time until an experience score fluctuation value formed based on the experience score is less than or equal to a preset standard experience score fluctuation value.

3. The offline experience scene experience analysis method according to claim 2, characterized in that: The determining of a number of areas to be improved according to the first grid step length, the preset historical duration, and the experience score of the interactive device comprises: Acquire the residence time of each target in each monitoring area constructed based on the first grid step size at the preset collection interval; Determine a number of modified monitored areas according to the length of stay, and determine a number of temporary modified monitored areas according to the number of interactive devices in the modified monitored areas; Adjust the first grid step length according to all the temporarily corrected monitoring areas of the target within the preset historical time period in the past until the area overlap rate determined based on the temporarily corrected monitoring areas is greater than the preset standard overlap rate, thereby forming a second grid step length; Determine a number of areas to be improved according to the experience scores of all the interactive devices within each monitoring area constructed based on the second grid step size within the residence time; The abnormal interaction area includes a first abnormal interaction area and a second abnormal interaction area.

4. The offline experience scenario experience analysis method according to claim 3, characterized in that: Determining a number of abnormal interaction areas according to the total number of interactions in each of the temporary monitoring areas within a preset monitoring time period includes: The standard deviation of the number of interactions is calculated to form a standard deviation of the number of interactions. When the standard deviation of the number of interactions is smaller 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 standard deviation of the number of interactions is smaller than the preset difference threshold, the temporary monitoring area is determined to be the first abnormal interaction area.

5. The offline experience scene experience analysis method according to claim 4, characterized in that: The determining of a number of abnormal interaction areas according to the total number of interactions in each of the temporary monitoring areas within a preset monitoring time period further includes: 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.

6. The offline experience scenario experience analysis method according to claim 5, characterized in that: The step of determining the adjustment interval determination result according to the number of abnormal interaction areas and the preset standard abnormal number includes: When the number of the first abnormal interaction areas is greater than the preset standard abnormal number, it is determined that the preset grid step size needs to be increased, thereby forming the increase interval determination result.

7. The offline experience scenario experience analysis method according to claim 6, characterized in that: The step of determining the adjustment interval determination result according to the number of abnormal interaction areas and the preset standard abnormal number also includes: When the number of the second abnormal interaction areas is greater than the preset standard abnormal number, it is determined that the preset grid step size needs to be reduced, thereby forming the spacing reduction determination result.

8. The offline experience scene experience analysis method according to claim 7, characterized in that: The adjusting the preset grid step size according to the adjustment spacing determination result to form a first grid step size comprises: When the adjustment interval determination result is the increase interval determination result, the preset grid step length is increased according to the standard deviation of the number of interactions, the maximum value of the preset standard number of interactions fluctuation range, the preset difference threshold value and the preset first interval adjustment coefficient to form a first grid step length; When the adjustment spacing judgment result is the reduction spacing judgment 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 number of interactions fluctuation range, the preset difference threshold and the preset first spacing adjustment coefficient to form a first grid step size.

9. The offline experience scenario experience analysis method according to claim 8, characterized in that: The step of adjusting the first grid step size according to all the temporarily corrected monitoring areas of the target within the preset historical time period in the past until the area overlap rate determined based on the temporarily corrected monitoring areas is greater than the preset standard overlap rate to form the second grid step size comprises: Calculate the ratio of the preset historical duration to the preset collection interval to obtain the total number of collection times; Obtain the number of overlapping cells of all the temporarily corrected monitoring areas of the target to obtain an overlapping number; Calculate the area overlap rate according to the overlap number, the total number of acquisitions, the first grid step size, and a 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 to form a second grid step size.

10. The offline experience scenario experience analysis method according to claim 9, characterized in that: The step of adjusting the preset collection interval according to all the experience scores of the area to be improved within the preset score evaluation time 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 score to obtain the experience score fluctuation value. When the experience score fluctuation value is greater than the preset standard experience score fluctuation value, determine that the preset collection interval needs to be adjusted, and reduce the preset collection interval according to the experience score fluctuation value, the preset standard experience score fluctuation value, and the preset interval adjustment coefficient.

11. The experience analysis method of offline experience scene according to claim 10, characterized in that: Determining a number of temporary monitoring areas according to the stay duration and the preset standard stay duration includes: When the stay time is longer than the preset standard stay time, the monitored area is determined to be an area to be monitored, and a number of temporary monitoring areas are determined according to the area to be monitored.

12. The offline experience scenario experience analysis method according to claim 11, characterized in that: Determining a number of temporary monitoring areas according to the area to be monitored includes: When the number of devices is greater than the preset standard number of devices, the area to be monitored is determined to be a temporary monitoring area.

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