Food video display interaction system and method based on user feedback

Abstract

The invention relates to a food video display interaction system and method based on user feedback, which can form comprehensive feedback data by integrating behavior records and sound signals of visitors, realize dynamic updating of image contents and loop optimization of a playlist, solve the defects in a traditional food video display method, and improve the user experience. By means of the method, the interaction and attraction of exhibition are remarkably improved, the interaction of exhibition is enhanced, the exhibition content can respond to the interest and reaction of visitors in real time, the stopping time of the visitors is effectively prolonged, and the visiting experience quality and satisfaction degree of the visitors are improved; by continuously optimizing the display content, it is ensured that each access can bring fresh and personalized experience to visitors, and the overall attraction and interaction level of exhibition are remarkably improved.

Description

Technical Field

[0001] The present invention belongs to the technical field of display interactive systems, and in particular relates to a food video display interactive system and method based on user feedback. Background Art

[0002] In the current exhibition field, especially in food-themed exhibitions, it is common to pre-set a series of fixed video content and play it on multiple screens in the exhibition hall in a loop. These images usually include exquisite food preparation processes, tempting dishes, and related food culture introductions. However, this traditional display method has a significant technical problem: the lack of responsiveness to real-time feedback from visitors. Since the video content is fixed and cannot be dynamically adjusted according to the interests and behaviors of visitors, the visiting experience is relatively monotonous and it is difficult to effectively attract and maintain the attention of visitors.

[0003] Existing food video display methods mainly rely on preset content planning, ignoring the visitors' immediate feedback and personalized needs. This not only limits the interactivity of the exhibition, but also fails to make full use of modern sensing technology and data analysis methods to optimize the display effect. Therefore, a core problem of the existing technology is that it is impossible to achieve real-time and personalized image content adjustment to adapt to the interests and preferences of different visitors, thus affecting the overall quality of the visiting experience and the attractiveness of the exhibition. Summary of the invention

[0004] The purpose of the present invention is to provide an interactive food video display system and method based on user feedback, which forms comprehensive feedback data by integrating visitors' behavior records and sound signals, realizes dynamic updating of image content and cyclic optimization of playlists, solves the shortcomings of traditional food video display methods, significantly improves the interactivity and attractiveness of the exhibition, and provides visitors with a richer and more personalized visiting experience.

[0005] To achieve the above object, the present invention proposes a food video display interactive method based on user feedback, comprising the following steps: A plurality of screens are arranged in the exhibition hall, and food-related video materials are prepared in advance, and a corresponding preset video sequence is started to play on the screen according to the entrance position selected by the visitor when entering the exhibition area; Recording the visitor's stay behavior and sight direction through a recording device, and adjusting the video content being played according to the behavior record; Using sound sensing equipment to capture sound signals emitted by visitors, integrating the sound signals with the behavior records to form comprehensive feedback data; The playlist is dynamically updated based on the feedback data, and the image display process is cyclically optimized to encourage visitors to extend their stay time and increase interaction.

[0006] Preferably, the multiple screens are arranged in the exhibition hall, and food-related video materials are prepared in advance, including: The exhibition hall is divided into several display areas, and a certain number of display screens are arranged in each area; For each display area, a set of image sequences is arranged, wherein the image sequence is composed of a series of food-related images, and the image themes between adjacent display areas are ensured to be different; Allocate a single screen display time for the image sequence, and adjust this value according to the average stay time of visitors; Establish image switching rules to define how to smoothly transition from the current image to the next image when the display time of a single image ends.

[0007] Preferably, starting the corresponding preset image sequence to play on the screen according to the entrance position selected by the visitor when entering the exhibition area includes: Determine the location of the visitor's entrance to the exhibition area and record this information as an initial reference point; According to the recorded entrance location, a set of matching image sequences is selected for preparation, and the sequence is ensured to be associated with the display screen in the display area; Set up mapping relationships, and match the selected image sequence to the entry position one by one, to ensure that each entry has an independent image playlist; When a visitor appears at the entrance, the corresponding image sequence playback is started according to the mapping relationship, so that the image content responds to the visitor's arrival in real time.

[0008] Preferably, the recording of the visitor's stay behavior and sight direction by recording equipment includes: Start the recording device, which is activated immediately after the visitor enters the exhibition area. The recording device is used to track and capture the visitor's stay position and line of sight movement path to form original behavior trajectory data; Based on the collected behavioral trajectory data, analyze the length of time each visitor stays in front of different images, and associate this information with the corresponding image sequence; Based on the obtained residence time and image association results, a basic data set is prepared for subsequent image adjustment.

[0009] Preferably, adjusting the video content being played according to the behavior record includes: Receive the recorded visitor's stay time and sight direction information as the basis for adjusting the image; Determine visitors’ interests based on their duration and sight direction data and select new video content that matches them; Create update rules to guide the adjustment of image sequences based on identified interests, ensuring that new images are relevant to visitors’ interests; Apply the update rules to the currently playing image sequence to generate an adjusted image sequence to achieve instant content update.

[0010] Preferably, the method of capturing the sound signal emitted by the visitor using the sound sensing device includes: Activate sound sensing devices to capture sound signals from visitors in the exhibition area, analyze the characteristics of the captured sound signals, identify sound patterns that express interest or engagement, and mark them as sound feedback; Combine the sound feedback with the adjusted image sequence to evaluate the synergy between the two, and based on the synergy obtained, formulate an image fine-tuning plan to make subtle adjustments to the currently playing image sequence.

[0011] Preferably, the integrating the sound signal and the behavior record to form comprehensive feedback data includes: Collect sound feedback, dwell time, and line of sight information as basic materials for integration; Construct a comprehensive feedback structure, pair the sound feedback with the duration of stay and the direction of sight, and form a sound-visual correlation record of visitor behavior; Based on the comprehensive feedback structure formed, the engagement index in each exhibition area is calculated, which reflects the overall interaction level of visitors; Based on the obtained engagement indicators, a comprehensive feedback dataset is compiled. The comprehensive feedback dataset contains the engagement evaluation results of all display areas and is used for subsequent image display optimization.

[0012] Preferably, dynamically updating the playlist based on the formed feedback data comprises: Parse the compiled comprehensive feedback dataset to extract engagement metrics for each display area; Based on the extracted engagement metrics, evaluate how well the current playlist matches the visitor’s interests and identify content segments that need to be adjusted; Develop an update strategy to determine how to select and prioritize new image content based on the evaluation results; Apply update strategies to existing playlists to generate optimized playlists, ensuring that new playlists dynamically reflect the latest visitor feedback.

[0013] Preferably, the process of looping and optimizing the image display process to promote visitors to prolong their stay time and increase their interaction includes: Based on the generated optimized playlist, a new round of image display cycle is started; During the new round of exhibitions, real-time feedback data from visitors will continue to be collected, including new stay time and voice feedback; Compare and analyze the collected real-time feedback data with the previous comprehensive feedback data set to evaluate the changing trend of the display effect and record any significant changes; Based on the obtained change trends, the update strategy is adjusted to form an improved update strategy to guide the subsequent optimization of the playlist, ensuring that each cycle can respond to the interests of visitors and promote the increase of dwell time and interaction.

[0014] On the other hand, the present invention provides a food video display interactive system with user feedback, comprising: The display area initialization and image sequence start module is used to set up multiple screens in the exhibition hall and prepare food-related image materials in advance, and start the corresponding preset image sequence to play on the screen according to the entrance position selected by the visitor when entering the exhibition area; A behavior monitoring and image adjustment module is used to record the visitor's stay behavior and sight direction through a recording device, and adjust the image content being played according to the behavior record; A sound feedback collection and integration module is used to capture the sound signals emitted by visitors using sound sensing equipment, integrate the sound signals with the behavior records, and form comprehensive feedback data; The playlist dynamic update and optimization module is used to dynamically update the playlist based on the feedback data formed, to cyclically optimize the image display process, and to encourage visitors to extend their stay time and increase interaction.

[0015] Technical effects and advantages of the present invention: Compared with the prior art, the food video display interactive system and method based on user feedback proposed by the present invention has the following advantages: The present invention integrates the visitor's behavior records and sound signals to form comprehensive feedback data, thus realizing the dynamic update of image content and the cyclic optimization of playlists. This method not only enhances the interactivity of the exhibition, enabling the display content to respond to the visitor's interests and reactions in real time, but also effectively prolongs the visitor's stay time and improves their visit experience quality and satisfaction. By continuously optimizing the display content, it ensures that each visit can bring a fresh and personalized experience to the visitor, significantly improving the overall attractiveness and interactivity level of the exhibition. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] Figure 1 It is a flow chart of the interactive method for food video display based on user feedback of the present invention; Figure 2The block diagram of the food video display interactive system based on user feedback of the present invention. DETAILED DESCRIPTION

[0017] The following will be combined with the accompanying drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, rather than all the embodiments. The specific embodiments described herein are only used to explain the present invention and are not used to limit the present invention. Based on the embodiments in the present invention, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present invention.

[0018] The present invention provides a method for interactive food video display based on user feedback, which aims to form comprehensive feedback data by integrating visitors' behavior records and sound signals, and realize dynamic update of video content and cyclic optimization of playlists. This method can: Enhanced interactivity: By capturing and analyzing visitors’ behaviors and reactions in real time, the system can quickly adjust the image content to make the display more relevant to visitors’ interests and enhance the interactive experience.

[0019] Prolong the stay time: Personalized image display can better attract visitors' attention and increase the time they stay in the exhibition area.

[0020] Improve satisfaction: Continuously optimize the display content based on actual visitor feedback to ensure that each visit can bring visitors a fresh and interesting experience, thereby improving overall satisfaction.

[0021] In summary, the present invention solves the shortcomings of traditional food video display methods, and significantly improves the interactivity and attractiveness of the exhibition by introducing a real-time feedback mechanism and an intelligent optimization algorithm, providing visitors with a richer and more personalized viewing experience. like Figure 1 As shown, the food video display interactive method based on user feedback in the present invention includes the following steps: Step 1: Set up multiple screens in the exhibition hall and prepare food-related video materials in advance; specifically include: The exhibition hall is divided into several display areas, and a certain number of display screens are arranged in each area. By reasonably dividing the display areas and arranging the display screens, it is ensured that each area can independently display content on a specific theme, avoiding content duplication and enhancing the diversity of visitor experience.

[0022] For each display area, a set of image sequences Q is arranged, which consists of a series of food-related pictures to ensure that the image themes between adjacent display areas are different; different image sequences Q can provide diverse content to meet the needs of different visitors, and through thematic differentiation, it can guide visitors to flow between different areas, increasing the selectivity and interest of the visiting route.

[0023] Assign a time parameter T to the image sequence Q, where T represents the display duration of a single image. The T value is adjusted according to the average length of stay of visitors to ensure that each image has enough time to attract attention. The optimized time parameter T ensures that each image has enough display time to attract the attention of visitors, while not being excessively extended, maintaining the display rhythm and improving the overall viewing experience.

[0024] Image switching rule R is established. This rule defines how to smoothly transition from the current image to the next image when T ends. Rule R depends on the set time parameter T to ensure the smoothness of the entire display process. Image switching rule R ensures a smooth transition during the display process, avoids the discomfort caused by sudden changes to visitors, and enhances visual coherence and comfort.

[0025] Formula expression: Let T = average dwell time / number of images in the image sequence Q Let R(T) = if T expires, execute the next image display. Q: image sequence, T: single image display time, R: image switching rule.

[0026] T represents the duration of a single screen, which is calculated by dividing the average duration of a visitor's stay by the number of screens in the image sequence Q. This ensures that each screen has an appropriate amount of time to be displayed, neither too fast nor too slow.

[0027] R defines the image switching logic, that is, when the display time T of a single image expires, the display of the next image is automatically executed. This rule ensures the automation and smoothness of the display process.

[0028] The following are the specific principles and implementation mechanisms of the image switching rule R: 1. Dependence on the time parameter T The image switching rule R strictly depends on the set time parameter T (the display duration of a single screen). When the display time of the current screen reaches the preset T value, the system will trigger the action of switching to the next screen. This means that each screen has a clear display cycle, which ensures the rhythm and consistency of the display process.

[0029] 2. Smooth transition mechanism In order to avoid the discomfort caused by sudden screen switching to visitors, the image switching rule R introduces a smooth transition mechanism. Specifically, this mechanism can include the following methods: Fade-in / Fade-out: The current image gradually fades away, while the next image gradually brightens. This makes the switching between the two images appear natural and smooth.

[0030] Dissolve effect: The switching between the current picture and the next picture is completed through pixel-level blending, producing a soft transition effect.

[0031] Wipe effect: The new picture gradually pushes the old picture away from one side or corner until it completely covers the old picture, giving a sense of advancement.

[0032] Animation effects such as rotation and scaling: Use 3D or 2D animation effects such as rotation, scaling, page turning, etc. to make screen switching more vivid and interesting.

[0033] 3. Automation Logic The image switching rule R contains the automation logic, which ensures that the system can automatically perform the image switching according to the preset time parameter T without human intervention. The key to the automation logic is precise timing and seamless connection: Accurate timing: There is a high-precision timer inside the system to track the actual display time of each picture. Once the time reaches the preset T value, the timer will immediately trigger the switching command.

[0034] Seamless connection: To ensure that the switching process is uninterrupted, the system will prepare the content of the next screen before the end of the T value, and quickly execute the switching action when the T value expires. This can avoid any delay or freeze.

[0035] For example, suppose that in a food exhibition hall, an image sequence Q of a display area contains 10 images related to local specialty snacks. According to preliminary investigation, the average length of stay of visitors in this display area is 5 minutes (300 seconds). According to the above formula: Let T = 300 seconds / 10 screens = 30 seconds Let R (30 seconds) = If 30 seconds expire, execute the next screen display; This means that each screen will be displayed for 30 seconds, after which the system will automatically switch to the next screen. This ensures that each screen has enough display time to attract visitors' attention, while maintaining the fluidity and rhythm of the entire display process. In addition, if the average length of stay of visitors in a certain display area changes, for example, it increases to 6 minutes, the T value can be recalculated by adjusting the formula to ensure the optimal display effect.

[0036] Step 2: Based on the entrance location selected by the visitor when entering the exhibition area, start playing the corresponding preset image sequence on the screen; specifically including: Determine the entrance location of visitors into the exhibition area and record this information as the initial reference point; by identifying and recording the visitor's entrance location, the system is able to create a personalized display starting point for each visitor. This not only improves the relevance and targeting of the display, but also enhances the interactivity and participation of the visiting experience.

[0037] According to the recorded entrance positions, a matching set of image sequences Q is selected for preparation, ensuring that the sequence is linked to the display screen in the exhibition area; the image sequences Q corresponding to different entrance positions can provide the most relevant content based on the visitor's path preference, ensuring that each exhibition area can independently display unique and coherent thematic content, avoiding repetition and monotony, and improving the quality of the overall visiting experience.

[0038] A mapping relationship M is set to correspond the selected image sequence Q to the entrance position one by one, ensuring that each entrance has an independent image playlist; the image sequence Q corresponding to different entrance positions can provide the most relevant content according to the visitor's path preference, ensuring that each display area can independently display unique and coherent thematic content, avoiding repetition and monotony, and improving the quality of the overall visiting experience.

[0039] When a visitor appears at the entrance, the corresponding image sequence Q is started to play according to the mapping relationship M, so that the image content responds to the visitor's arrival immediately. The instant response mechanism ensures that the image content can start playing immediately when the visitor arrives, enhancing the immediacy and interactivity of the display, leaving a deep impression on the visitor and enhancing the attractiveness of the overall visiting experience.

[0040] Formula expression: Let M = entry position -> image sequence Q Let P = current entry position If P corresponds to the position in M, then play M(P).

[0041] M represents the mapping relationship, which defines the correspondence between each entrance position and a specific image sequence Q. P represents the current entrance position, which is the entrance that visitors actually enter. Q represents the image sequence, which contains a series of food-related images. M(P) means searching for the mapping relationship M according to the current entrance position P, finding the corresponding image sequence Q, and starting playback.

[0042] For example, assume that there are three different entrance locations A, B and C in a food exhibition hall, and each entrance location corresponds to a unique set of image sequences Q1, Q2 and Q3. The specific implementation is as follows: Entrance position A: When a visitor enters from entrance A, the system records this entrance position as the initial reference point.

[0043] Select image sequence Q1: Based on the recorded entrance position A, the system selects the matching image sequence Q1 for preparation, ensuring that the sequence is linked to the display screen in the display area.

[0044] Set mapping relationship M: The system sets mapping relationship M, where A corresponds to Q1, B corresponds to Q2, and C corresponds to Q3.

[0045] Start the image sequence Q1: When the visitor appears at the entrance position A, the system starts the playback of the image sequence Q1 according to the mapping relationship M, so that the image content responds to the visitor's arrival in real time.

[0046] Let M = A->Q1, B->Q2, C->Q3 Let P = A (current entry position) If P corresponds to position A in M, then play M(A), which is Q1.

[0047] This means that when a visitor enters from entrance A, the system automatically plays the image sequence Q1, providing unique content related to entrance A, enhancing the visitor's sense of participation and quality of experience. The same logic applies to the other entrance locations B and C, playing the corresponding image sequences Q2 and Q3 respectively.

[0048] Step 3: Record the visitor's stay behavior and sight direction through recording equipment; specifically include: Start the recording device and activate it immediately after the visitor enters the exhibition area to ensure that no behavior record is missed; the instantly activated recording device can capture all the behavior data of the visitor from the moment he enters the exhibition area, ensuring the completeness and accuracy of the behavior record. This provides a detailed data basis for subsequent analysis and improves the accuracy of the adjustment of the display content.

[0049] The recording device is a key tool for capturing and analyzing visitor behavior data. It consists of multiple components and technologies to ensure that visitors' stop behavior and sight direction can be accurately and comprehensively recorded. The following is a detailed introduction to the specific composition of the recording device and its working principle: 1. Hardware composition Camera: Function: Used to capture real-time video images in the exhibition area and track the movement paths of visitors.

[0050] Principle: HD cameras are installed on the top or side of the display area to cover the entire exhibition space. Through video stream analysis technology, the movement trajectory of each visitor can be identified and tracked.

[0051] Infrared Sensors: Function: Detect the specific location and stay time of visitors.

[0052] Principle: Infrared sensors are installed on the floor or wall of the exhibition area. When visitors enter its sensing range, the sensor triggers a timer to start recording the stay time. At the same time, through a multi-point sensor network, the visitor's stay location can be accurately determined.

[0053] Eye-tracking Devices: Function: Capture the visitor's sight direction and gaze point.

[0054] Principle: Non-invasive eye tracking technology, such as infrared light emitters and high-resolution cameras, is used to capture eye movements through reflected light and calculate the direction and point of gaze. These devices are usually installed near the display screen to ensure that the visitor's gaze changes can be accurately captured.

[0055] Radio Frequency Identification (RFID) Tags and Readers: Function: Assist in identifying and tracking the behavior of specific visitors.

[0056] Principle: Visitors wear or carry a card or bracelet with an RFID tag. When they enter the exhibition area, the RFID readers installed in various locations will automatically identify the tag information and record the visitor's identity and path. This helps to associate behavioral data with specific individuals.

[0057] Smart Sensor Nodes: Function: Integrate multiple sensors to provide comprehensive data collection.

[0058] Principle: These nodes integrate multiple sensing devices such as cameras, infrared sensors, temperature and humidity sensors, etc., and are connected to the central control system through a wireless network to achieve real-time data transmission and processing.

[0059] 2. Software and technical principles Computer Vision: Function: Extract and analyze visitor behavior patterns from video captured by cameras.

[0060] Principle: Using advanced image processing algorithms such as target detection, trajectory tracking, posture estimation, etc., the video stream is analyzed in real time to identify the actions, positions and movement paths of each visitor. Through deep learning models, visitors’ points of interest and next actions can also be predicted.

[0061] Data Analysis Platform: Function: Integrate and process data from various sensors to generate information such as behavior trajectory and residence time.

[0062] Principle: The data analysis platform receives raw data from cameras, infrared sensors, eye tracking devices, etc., and builds a detailed visitor behavior model through steps such as data cleaning, feature extraction and pattern recognition. The platform also supports real-time data visualization to help managers intuitively understand the display effect.

[0063] Internet of Things (IoT) Technology: Function: Realize interconnection between devices and ensure real-time transmission and synchronization of data.

[0064] Principle: All recording devices are connected to the central control system through wireless communication protocols such as Wi-Fi, Bluetooth or Zigbee to form a complete IoT network. This not only ensures the stability and efficiency of data transmission, but also facilitates remote management and maintenance.

[0065] Assuming that in a food exhibition hall, the specific application of the recording device is as follows: Cameras and infrared sensors: A network of high-definition cameras and infrared sensors is installed on the top of the display area. When a visitor enters a display area, the system automatically starts recording, capturing their movement trajectory and stay time.

[0066] Eye tracking equipment: An eye tracking device is installed next to each display screen to monitor the visitor's line of sight and gaze point in real time, and record their degree of attention to different images.

[0067] RFID tags and readers: Each visitor is issued a wristband with an RFID tag. When they enter the exhibition area, the RFID reader automatically identifies and records relevant information to ensure that the behavioral data is associated with the individual.

[0068] Data analysis platform: All collected data is transmitted to the data analysis platform, and after processing, a detailed visitor behavior report is generated. For example, the system finds that most visitors stay the longest in front of the image sequence Q2, indicating that this content is more popular, thus providing a basis for subsequent image adjustments.

[0069] Through the combination of the above hardware and technologies, the recording equipment can not only capture visitors' behavioral data comprehensively and accurately, but also provide scientific data support for the optimization of exhibition content, significantly improving the quality and interactivity of the visiting experience.

[0070] The recording equipment used tracks and captures the visitors' stop positions and sight movement paths to form original behavior trajectory data; by tracking the stop positions and sight movement paths, the system can obtain detailed visitor behavior trajectory data. These data not only reflect the specific behaviors of visitors in front of different images, but also reveal their interests and focus, providing an important basis for personalized display.

[0071] Based on the collected behavioral trajectory data, the duration S of each visitor's stay in front of different images is analyzed, and this information is associated with the corresponding image sequence Q; the analysis of the duration S can accurately measure the visitor's interest in each image. By associating the duration S with the image sequence Q, the system can identify which images are more attractive to visitors, thereby providing a scientific basis for subsequent content optimization and ensuring that the display content is more in line with the interests of visitors.

[0072] Based on the obtained dwell time S and image association results, the basic dataset B is prepared for subsequent image adjustment to ensure that the adjusted images are more in line with the interests of visitors. The basic dataset B integrates the information of the dwell time S and the image sequence Q, providing solid data support for subsequent image adjustment. This dataset based on actual behavior makes image adjustment more targeted, which can significantly improve the relevance and attractiveness of the display content and enhance the interactive experience of visitors.

[0073] Formula expression: Let S = dwell time Let Q = image sequence Let B(S,Q) = data set, which contains the combination of dwell time S and corresponding image sequence Q.

[0074] S represents the dwell time, i.e., the time a visitor stays in front of a certain image. Q represents the image sequence, which contains a series of food-related images. B(S,Q) represents the dataset, which consists of the dwell time S and the corresponding image sequence Q, and is used for subsequent image adjustment analysis.

[0075] The dwell time S is an important indicator to measure the visitor's interest in a certain image. By recording the behavioral trajectory data captured by the device, the system can accurately calculate the dwell time of each visitor in front of different images and associate these dwell times with the specific image sequence Q. The generated basic data set B not only records the viewing situation of each image, but also reflects the visitor's preferences and interests, providing strong data support for subsequent image adjustments.

[0076] Assume that in a food exhibition hall, there are three different image sequences Q1, Q2 and Q3, which respectively display different local specialties. The specific implementation is as follows: Start the recording device: When visitors enter the exhibition area, the recording device is immediately activated to start capturing their behavior data.

[0077] Capturing behavior trajectory data: The recording device tracks and captures the visitor's stop position and sight movement path to form the original behavior trajectory data. For example, the visitor stayed in front of image sequence Q1 for 45 seconds, stayed in front of Q2 for 60 seconds, and stayed in front of Q3 for 30 seconds.

[0078] Analyze the duration of stay S: The system analyzes the collected behavior trajectory data and calculates the duration S of each visitor's stay in front of different images. For example: Let S(Q1) = 45 seconds Let S(Q2) = 60 seconds; Assume S(Q3)=30 seconds.

[0079] Establishing data set B: Based on the association results of the dwell time S and the image sequence Q, the system creates a basic data set B for subsequent image adjustment. For example: Let B(S,Q)=dataset B(45 seconds,Q1); B (60 seconds, Q2); B (30 seconds, Q3).

[0080] This means that if multiple visitors show similar behavior patterns (such as staying in Q2 for a longer time), the system can adjust the playlist based on this data, increase the frequency of playing Q2 or extend its display time to better meet the interests of visitors. This image adjustment based on actual behavior data can significantly improve the relevance and attractiveness of the display content and enhance the interactive experience of visitors.

[0081] Step 4: Adjust the video content being played according to the behavior record; specifically including: Receive the recorded visitor's stay time S and sight direction information as the basis for adjusting the image; by receiving detailed stay time S and sight direction data, the system can fully understand the visitor's interests and behavior patterns. These data provide a solid foundation for subsequent image adjustments, ensuring that the adjusted image content is more in line with the actual needs of visitors.

[0082] According to the stay time S and the sight direction data, the visitor's interest tendency is determined, and the new image content Q' that matches it is selected; through in-depth analysis of the stay time S and the sight direction data, the system can accurately identify the visitor's interest tendency. Based on this understanding, the new image content Q' that matches it is selected, making the display content more personalized and targeted, and improving the visitor's participation and satisfaction.

[0083] Create an update rule U, which is based on the determined interest tendency and is used to guide the adjustment of the image sequence Q to ensure that the new image fits the visitor's interest; the update rule U is formulated based on the visitor's interest tendency, which not only guides the adjustment direction of the image sequence Q, but also ensures the scientificity and effectiveness of the adjustment process. In this way, the system can dynamically respond to changes in visitor behavior and provide exhibition content that is more in line with their preferences.

[0084] Apply update rule U to the currently playing image sequence Q to generate the adjusted image sequence Q' to achieve instant content update. Apply update rule U to the currently playing image sequence Q, the system can quickly generate the adjusted image sequence Q' and start playing it immediately. This not only ensures the instant update of the display content, but also enhances the interactivity and real-time nature of the display, giving visitors a more smooth and personalized experience.

[0085] Formula expression: Let U(S,Q)=update rule, where S is the dwell time and Q is the original image sequence. Let Q'=U(S,Q), which represents the new image sequence adjusted by the update rule U.

[0086] S represents the dwell time, i.e., the time a visitor stays in front of a certain image. Q represents the original image sequence, which contains a series of food-related images. Q' represents the adjusted new image sequence, which is the image content adjusted by the update rule U. U(S,Q) represents the update rule, which guides the adjustment of the image content based on the dwell time S and the original image sequence Q.

[0087] The core of the update rule U is to dynamically adjust the display content according to the visitor's stay time S and the original image sequence Q to make it more in line with the visitor's interests. Specifically, when the system receives the visitor's stay time S and sight direction data, it will analyze these data to determine their interest tendencies and select the most suitable new image content Q' accordingly. Then, the system applies these new contents to the currently playing image sequence Q through the update rule U, generates the adjusted image sequence Q', and starts playing it immediately.

[0088] For example, assume that in a food exhibition hall, the image sequence Q in the display area includes three different image segments Q1, Q2 and Q3, which respectively display three different local specialty snacks. The specific implementation is as follows: Receiving behavior records: The system receives records that the visitor stayed in front of image sequence Q1 for 60 seconds, stayed in front of Q2 for 45 seconds, and stayed in front of Q3 for 30 seconds.

[0089] Determine interest tendency: By analyzing these dwell time S and sight direction data, the system finds that the visitor shows the highest interest in image sequence Q1 (stays the longest). Therefore, the system determines that the visitor is interested in one of the local specialty snacks.

[0090] Create update rule U: Based on the above interest tendency, the system creates update rule U, which guides the adjustment of image sequence Q to add more image content related to local specialty snacks.

[0091] Apply update rule U: The system applies update rule U to the currently playing image sequence Q to generate an adjusted image sequence Q', for example: Let U(60 seconds, Q1) = update rule; Let Q' = U(60 seconds, Q1), which represents the new image sequence adjusted by the update rule U; This means that if multiple visitors show similar behavior patterns (such as staying in Q1 for a longer time), the system can adjust the playlist based on this data, increase the frequency of playing Q1-related content or extend its display time to better meet the interests of visitors. For example: The original image sequence Q includes Q1, Q2 and Q3.

[0092] According to the update rule U, the system adds more content related to Q1 and generates a new image sequence Q', and the order becomes Q1, Q1 extended content, Q2, and Q3.

[0093] In this way, the system achieves instant updates of display content, ensuring that each playback can respond to visitors' interests more accurately, significantly improving the relevance and appeal of the display and enhancing the visitor's interactive experience.

[0094] Step 5: Use sound sensing equipment to capture sound signals emitted by visitors; specifically including: Activate the sound sensing device to capture the sound signals emitted by visitors in the display area to ensure that all interactive areas are covered; by activating the sound sensing device, the system can capture various sound signals emitted by visitors in the display area in real time. This not only expands the scope of interaction, but also provides an additional source of behavioral data and enhances the understanding of visitor interest and engagement.

[0095] Sound sensing equipment is a key tool for capturing and analyzing sound signals emitted by visitors in the exhibition area. Through a variety of sensors and technologies, it can accurately record and process various sound information, providing data support for subsequent behavior analysis. The following is a detailed introduction to the specific composition of sound sensing equipment and its working principle: 1. Hardware composition Microphone Array: Function: Used to capture sound signals in the display area.

[0096] Principle: Multiple highly sensitive microphones are installed in different locations of the display area in a specific geometric arrangement to form a microphone array. This layout can localize the sound source, accurately capture sound signals from different directions, and improve the signal-to-noise ratio.

[0097] Audio Amplifier: Function: Enhance the captured sound signal to ensure signal quality.

[0098] Principle: The audio amplifier amplifies the weak sound signal captured by the microphone array to a level suitable for subsequent processing. At the same time, it also has a filtering function to reduce environmental noise interference.

[0099] Analog-to-Digital Converter (ADC): Function: Convert the captured analog audio signal into a digital signal.

[0100] Principle: ADC quantizes analog audio signals into discrete digital values ​​at a certain sampling rate, making it easier for computer systems to process and analyze them.

[0101] Wireless Communication Module: Function: Transmit the processed audio data to the central control system.

[0102] Principle: Wireless communication protocols such as Wi-Fi, Bluetooth or Zigbee are used to transmit audio data to the central control system in real time to ensure the timeliness and reliability of the data.

[0103] Power Management Unit (PMU): Function: Provides a stable power supply for the entire sound sensing equipment.

[0104] Principle: PMU is responsible for managing power input, ensuring that each component works in the best condition, and supports low power consumption mode to extend the battery life of the device.

[0105] 2. Software and technical principles Sound Source Localization (SSL): Function: Determine the specific location of the sound source.

[0106] Principle: By analyzing the time difference and intensity difference of the sound signal captured by the microphone array, algorithms such as generalized cross-correlation method (GCC-PHAT) or beamforming are used to accurately locate the position of the sound source.

[0107] Speech Recognition Technology: Function: Identify and classify various sounds made by visitors.

[0108] Principle: Use deep learning models (such as convolutional neural networks (CNN) or recurrent neural networks (RNN)) to extract features and recognize patterns of captured sound signals, distinguish different types of sounds (such as laughter, discussion, exclamation, etc.), and mark these sounds as sound feedback V.

[0109] Emotion Analysis Technology: Function: Analyze the emotional components in sound signals.

[0110] Principle: By analyzing the voice's tone, volume, frequency changes and other features, combined with machine learning models, the emotional information contained in the voice (such as happiness, surprise, excitement, etc.) can be identified to further enrich the content of the voice feedback.

[0111] Noise Suppression and Enhancement: Function: Remove background noise and enhance useful sound signals.

[0112] Principle: Apply technologies such as adaptive filters and spectrum subtraction to effectively reduce the impact of environmental noise, improve the quality of captured sound signals, and ensure the accuracy of subsequent analysis.

[0113] Real-time Data Analysis Platform: Function: Integrate and process data from multiple microphone arrays to generate comprehensive acoustic feedback reports.

[0114] Principle: The data analysis platform receives audio data from each microphone array and realizes real-time data processing and analysis through distributed computing and storage technology. The platform also supports a visual interface to help managers intuitively understand the display effect.

[0115] Assuming that in a food exhibition hall, the specific application of sound sensing equipment is as follows: Microphone array arrangement: Multiple microphone arrays are installed on the top and sides of the display area to cover the entire exhibition space. Each array consists of 8 high-sensitivity microphones to ensure that sound signals from different directions can be captured.

[0116] Sound source positioning: When a visitor stops in front of an image and makes a sound, the system uses sound source positioning technology to accurately locate the position of the sound source and record the specific image content corresponding to that position.

[0117] Sound classification and sentiment analysis: The system classifies the captured sound signals, identifies different types of sounds such as laughter, discussion, and exclamation, and uses sentiment analysis technology to determine the emotional components (such as happiness, surprise, etc.) expressed by these sounds. For example: Let V = laughter, discussion, exclamation; let emotion = happiness, surprise.

[0118] Real-time data transmission and processing: The captured sound signal is transmitted to the central control system in real time through the wireless communication module, processed and analyzed on the data analysis platform, and a detailed sound feedback report is generated. For example: Let Z = comprehensive feedback structure, which includes sound feedback V, dwell time S and gaze direction information Z(Q1') = (laughter, discussion, 60 seconds, focused gaze).

[0119] Through the combination of the above hardware and technology, the sound sensing equipment can not only comprehensively and accurately capture the sound signals emitted by visitors in the exhibition area, but also provide rich data support for subsequent behavioral analysis, significantly improve the effect of display content optimization, and enhance the interactive experience of visitors.

[0120] Analyze the characteristics of the captured sound signals, identify the sound patterns that express interest or participation, and mark them as sound feedback V; by analyzing the characteristics of the sound signals, the system can identify specific sound patterns (such as laughter, discussion, exclamation, etc.), which usually reflect the interest or participation of visitors. Marking these patterns as sound feedback V provides an important reference for subsequent image adjustments.

[0121] Combine the sound feedback V with the adjusted image sequence Q' to evaluate the synergy E between the two to determine whether the image content needs to be further optimized; by comparing the sound feedback V with the currently playing image sequence Q', the system can evaluate the synergy E between the two. If a significant positive correlation is found between certain image content and the sound feedback V (that is, visitors show a higher interest when watching a certain image), it indicates that the image content has a high appeal, and vice versa. This evaluation helps determine whether the image content needs to be further optimized.

[0122] Based on the obtained synergy effect E, the system will formulate an image fine-tuning plan F to make subtle adjustments to the currently playing image sequence and enhance the visitor's participation experience. Based on the evaluation results of the synergy effect E, the system will formulate an image fine-tuning plan F to make subtle adjustments to the currently playing image sequence. These adjustments are intended to enhance the match between the image content and the interests of the visitors, thereby improving the overall participation experience. For example, increase or extend popular content clips, and reduce or replace less attractive parts.

[0123] Formula expression: Let V = sound feedback Let E(Q',V) = synergy effect evaluation, where Q' is the adjusted new image sequence and V is the sound feedback Let F(E) = image fine-tuning plan, formulated based on the synergy effect E.

[0124] V represents the sound feedback, i.e., the sound pattern captured and analyzed by the sound sensing device. Q' represents the adjusted new image sequence, which is the image content adjusted by the update rule U. E(Q',V) represents the synergy effect evaluation, which is used to measure the relationship between the adjusted image sequence Q' and the sound feedback V. F(E) represents the image fine-tuning scheme, which is formulated according to the synergy effect evaluation result E and is used to make subtle adjustments to the image sequence.

[0125] Sound feedback V is one of the important indicators that reflect the interest and participation of visitors. By combining sound feedback V with the currently playing video sequence Q', the system can evaluate the synergistic effect E of the two. This evaluation helps the system identify which video content can most stimulate the interest of visitors, and formulate a video fine-tuning plan F based on this to further optimize the display content and enhance the visitor's participation experience.

[0126] For example, assume that in a food exhibition hall, the image sequence Q' in the display area includes three different image segments Q1', Q2' and Q3', which respectively show the production process of three different local specialty snacks. The specific implementation is as follows: Activate sound sensing devices: Install multiple sound sensing devices in the exhibition area to ensure that all interactive areas are covered and capture the sound signals emitted by visitors in real time.

[0127] Analyze sound signal characteristics: The system analyzes the captured sound signals, identifies sound patterns that express interest or engagement (such as laughter, discussion, exclamation), and labels these patterns as sound feedback V. For example: Let V = laughter, discussion, and exclamation.

[0128] Evaluate the synergistic effect E: The system combines the sound feedback V with the currently playing video sequence Q' to evaluate the synergistic effect E between the two. For example, when playing the video clip Q1', the system detects more laughter and discussion, indicating that the clip attracted a high degree of interest from visitors; while when playing Q3', there is less sound feedback, indicating that it is less attractive. The specific evaluation results are as follows: Let E(Q1',V) = high synergy effect Let E(Q2',V) = medium synergy effect Let E(Q3',V) = low synergy effect.

[0129] Formulate image fine-tuning plan F: Based on the evaluation results of synergy effect E, the system formulates image fine-tuning plan F to make minor adjustments to the currently playing image sequence. For example, increase the playing frequency of Q1' or extend its display time, while reducing the playing time of Q3' or replacing its content. The specific adjustments are as follows: Assume F(E) = image fine-tuning plan F(high synergy effect) = increase the playback frequency of Q1' or extend the display time F(medium synergy effect) = maintain the existing playback arrangement of Q2' F(low synergy effect) = reduce the playback time of Q3' or replace its content.

[0130] This means that if the system observes similar behavior patterns multiple times (such as Q1' triggering more laughter and discussion), it will dynamically adjust the playlist based on the results of the synergy effect E through the image fine-tuning scheme F, increase popular content and reduce unpopular content, so as to better meet the interests of visitors, significantly improve the relevance and attractiveness of the display, and enhance the visitors' interactive experience.

[0131] Step 6: Integrate the sound signal and the behavior record to form comprehensive feedback data; specifically including: The sound feedback V, the length of stay S and the line of sight direction information collected in step 5 are used as the basic materials for integration; by collecting the sound feedback V, the length of stay S and the line of sight direction information, the system can obtain multi-dimensional visitor behavior data. These basic materials provide detailed information support for subsequent comprehensive analysis, ensuring the comprehensiveness and accuracy of the data, thereby improving the effect of image display optimization.

[0132] The comprehensive feedback structure Z is constructed to pair the sound feedback V with the dwell time S and the sight direction information to form a sound-visual association record of the visitor's behavior; the comprehensive feedback structure Z integrates the sound feedback V, the dwell time S and the sight direction information to create a multi-dimensional association record of the visitor's behavior. This structure not only reflects the specific behavior of visitors in front of different images, but also reveals their emotional reactions and points of interest, laying the foundation for a deeper behavioral analysis.

[0133] According to the formed comprehensive feedback structure Z, the participation index P in each display area is calculated. This index reflects the overall interaction level of visitors. Through the comprehensive feedback structure Z, the system can calculate the participation index P of each display area. This index quantifies the visitor's interaction level, including their stay time in the area, concentration, and emotional response, etc., providing a scientific basis for evaluating the display effect.

[0134] Based on the obtained engagement index P, a comprehensive feedback dataset B is compiled, which contains the engagement evaluation results of all display areas for subsequent image display optimization. The comprehensive feedback dataset B integrates the engagement index P of each display area to form a comprehensive dataset. This dataset not only records the engagement of each area, but also provides solid data support for the subsequent image display optimization, making the optimization process more targeted and scientific.

[0135] Formula expression: Let Z = comprehensive feedback structure, which includes voice feedback V, dwell time S and gaze direction information. Let P(Z) = engagement index, calculated according to the comprehensive feedback structure Z. Let B(P) = comprehensive feedback data set, which consists of the engagement index P of each display area.

[0136] Z represents the comprehensive feedback structure, which includes the sound feedback V, the dwell time S and the sight direction information, and is used to describe the behavior and reaction of visitors. P(Z) represents the engagement index, which is calculated based on the comprehensive feedback structure Z and reflects the overall interaction level of visitors in a specific display area. B(P) represents the comprehensive feedback dataset, which consists of the engagement index P of each display area and is used for subsequent image display optimization.

[0137] The comprehensive feedback structure Z integrates the sound feedback V, the dwell time S and the sight direction information to form a multi-dimensional behavior record. Through the comprehensive analysis of these data, the system can calculate the engagement index P of each display area, so as to fully understand the interaction of visitors. Finally, based on these engagement indexes P, the system compiles a comprehensive feedback data set B to provide data support for the optimization of image display.

[0138] Assume that in a food exhibition hall, there are three different image sequences Q1', Q2' and Q3' in the display area, which respectively show the production process of three local specialty snacks. The specific implementation is as follows: Collect basic materials: The system collects sound feedback V (such as laughter, discussion, and exclamation) from sound sensing devices, as well as the length of time S that visitors stay in front of different images and the direction of their gaze.

[0139] Let V = laughter, discussion, exclamation; Assume S(Q1') = 60 seconds, S(Q2') = 45 seconds, S(Q3') = 30 seconds; Constructing a comprehensive feedback structure Z: The system pairs the sound feedback V, the dwell time S, and the sight direction information to form a comprehensive feedback structure Z. For example, when playing Q1', more laughter and discussion sounds are detected, and the dwell time is longer; while when playing Q3', less sound feedback is detected and the dwell time is shorter.

[0140] Let Z = (V, S, sight direction information); Z(Q1') = (laughter, discussion, 60 seconds, focused attention); Z(Q2')=(mild discussion, 45 seconds, medium gaze); Z(Q3')=(a few exclamations, 30 seconds, distracted gaze); Calculate the engagement index P: The system calculates the engagement index P for each display area based on the comprehensive feedback structure Z. For example: Let P(Z) = participation index; P(Z(Q1')) = high participation; P(Z(Q2')) = medium participation; P(Z(Q3')) = low participation; Compile comprehensive feedback dataset B: Based on the obtained engagement index P, the system compiles a comprehensive feedback dataset B, which contains the engagement evaluation results of all display areas for subsequent image display optimization.

[0141] Let B(P) = comprehensive feedback data set; B (high involvement, Q1'); B (moderate involvement, Q2'); B (low involvement, Q3'); This means that if multiple display areas show similar behavior patterns (such as Q1' receiving high engagement), the system can adjust the playlist based on this data, increase popular content and reduce unpopular content, thereby better meeting the interests of visitors, significantly improving the relevance and appeal of the display, and enhancing the visitor's interactive experience.

[0142] Step 7: Dynamically update the playlist based on the feedback data; specifically including: Parse the compiled comprehensive feedback data set B and extract the engagement index P of each display area; through detailed analysis of the comprehensive feedback data set B, the system can extract the engagement index P of each display area. These indicators quantify the level of visitor interaction in different areas, provide a scientific basis for subsequent evaluation and adjustment, and ensure that the optimization process is targeted.

[0143] Based on the extracted engagement index P, the matching degree between the current playlist L and the visitor's interests is evaluated, and the content segments that need to be adjusted are identified; by comparing the engagement index P with the current playlist L, the system can evaluate the matching degree between the two. If it is found that some content segments have low engagement, these segments are identified as those that need to be adjusted. This evaluation helps to identify deficiencies in the displayed content, so as to optimize them in a targeted manner.

[0144] Formulate an update strategy G, which determines how to select and sort new video content Q' based on the evaluation results to better respond to visitors' preferences; the update strategy G is formulated based on the evaluation results, which not only guides the selection of new video content Q', but also determines the sorting of these contents in the playlist. In this way, the system can more accurately meet the interests and preferences of visitors and improve the relevance and attractiveness of the displayed content.

[0145] Apply update strategy G to the existing playlist L to generate an optimized playlist L', ensuring that the new list can dynamically reflect the latest visitor feedback. Applying update strategy G to the existing playlist L, the system can quickly generate an optimized playlist L'. This not only ensures the instant update of the display content, but also enhances the interactivity and real-time nature of the display, making each playback more in line with the latest feedback from visitors and providing a more personalized experience.

[0146] Formula expression: Let G(P) = update strategy, and let L'=G(L) be formulated according to the participation index P, which means the new list after optimizing the original playlist L through the update strategy G.

[0147] G(P) represents the update strategy, which is formulated according to the engagement index P and is used to guide the selection and sorting of new video content Q'. L represents the original playlist, which contains all the video sequences currently displayed. L' represents the optimized playlist, which is the latest playlist adjusted by the update strategy G.

[0148] The core of the update strategy G is to evaluate the degree of match between the current playlist L and the visitor's interests based on the engagement index P, and select and sort new video content Q' accordingly. Specifically, the system analyzes the engagement index P of each display area, identifies the content segments with low engagement, and replaces or adjusts these contents through the update strategy G to generate an optimized playlist L'. This dynamic update mechanism ensures that the display content is always consistent with the visitor's interests, improving the overall interactive experience.

[0149] For example, suppose that in a food exhibition hall, there are three different image sequences Q1, Q2 and Q3 in the display area, which respectively show the production process of three local specialty snacks. The specific implementation is as follows: Parsing comprehensive feedback dataset B: The system parses the compiled comprehensive feedback dataset B and extracts the engagement index P for each display area. For example: Let P(Q1) = high participation; Let P(Q2) = medium participation; Let P(Q3) = low participation; Evaluate playlist L: The system evaluates the match between the current playlist L and the visitor's interests based on the extracted engagement index P. For example, it is found that the engagement of Q3 is low and needs to be adjusted. The specific evaluation results are as follows: Let L = [Q1, Q2, Q3]; Mark Q3 as the content paragraph that needs to be adjusted; Formulate update strategy G: Based on the evaluation results, the system formulates update strategy G to select and sort new image content Q' to better respond to visitor preferences. For example, add more relevant images about high-engagement content (such as Q1) and reduce or replace low-engagement content (such as Q3). The specific strategies are as follows: Let G(P) = update strategy; G (high engagement) = add more relevant images about Q1; G (low involvement) = reduce or replace Q3; Generate optimized playlist L': The system applies the update strategy G to the existing playlist L to generate an optimized playlist L', ensuring that the new playlist can dynamically reflect the latest visitor feedback. For example: Let L'=G(L); L'=[Q1, Q1 extended content, Q2, new Q3 content]; This means that if multiple display areas show similar behavior patterns (such as Q1 receiving high engagement), the system can adjust the playlist based on this data, increasing popular content and reducing unpopular content, thereby better meeting the interests of visitors, significantly improving the relevance and appeal of the display, and enhancing the visitor's interactive experience.

[0150] Step 8: Optimize the image display process in a loop to encourage visitors to stay longer and increase interaction; specifically include: According to the generated optimized playlist L', a new round of image display cycle is started; by applying the optimized playlist L', the system can start a new round of image display cycle. This not only ensures the instant update of the display content, but also provides a new basis for subsequent feedback collection and analysis, so that each display can respond to the interests of visitors more accurately.

[0151] During the new round of exhibitions, the real-time feedback data R from visitors is continuously collected, which includes the new length of stay S' and voice feedback V'; by continuously collecting real-time feedback data R (including the new length of stay S' and voice feedback V'), the system can dynamically monitor the changes in visitor behavior and obtain the latest interactive information. These real-time data provide detailed information support for subsequent evaluation and optimization, ensuring that the adjustment process is targeted.

[0152] Compare and analyze the collected real-time feedback data R with the previous comprehensive feedback data set B, evaluate the changing trend T of the display effect, and record any significant changes; by comparing and analyzing the real-time feedback data R with the previous comprehensive feedback data set B, the system can evaluate the changing trend T of the display effect. This comparison not only reveals the effect of the improvement of the display content, but also identifies the parts that need further optimization, providing a basis for formulating more effective update strategies.

[0153] Based on the trend T obtained, the update strategy G is adjusted to form an improved update strategy G' to guide the subsequent optimization of the playlist, ensuring that each cycle can more accurately respond to the interests of visitors and promote the increase of dwell time and interaction. According to the change trend T, the system adjusts the original update strategy G to form an improved update strategy G'. This not only improves the matching degree between the display content and the interests of visitors, but also enhances the interactivity and attractiveness of the display, ensuring that each cycle can better meet the expectations of visitors, thereby extending the dwell time and increasing interaction.

[0154] Formula expression: Let R = real-time feedback data, including the new dwell time S' and voice feedback V'. Let T(R,B) = change trend, compare the real-time feedback data R with the comprehensive feedback data set B. Let G'(T) = improved update strategy, adjusted according to the change trend T.

[0155] L': optimized playlist, R: real-time feedback data, S': new stay duration, V': new sound feedback, B: comprehensive feedback data set, T: change trend, G: original update strategy, G': improved update strategy.

[0156] Real-time feedback data R is one of the important indicators for measuring display effects. By comparing and analyzing the real-time feedback data R with the previous comprehensive feedback data set B, the system can evaluate the changing trend T of the display effect. Based on these trends, the system adjusts the original update strategy G to form an improved update strategy G' to achieve continuous optimization of the display content. This approach ensures that each cycle can respond to visitors' interests more accurately, thereby extending the stay time and increasing interaction.

[0157] For example, suppose that in a food exhibition hall, there are three different image sequences Q1, Q2 and Q3 in the display area, which respectively show the production process of three local specialty snacks. The specific implementation is as follows: Start a new round of video display cycle: The system starts a new round of video display cycle based on the generated optimized playlist L'. For example, the new playlist L' is [Q1, Q1 extended content, Q2, new Q3 content].

[0158] Let L' = [Q1, Q1 extended content, Q2, new Q3 content].

[0159] Continuously collect real-time feedback data R: During the new round of exhibitions, the system continuously collects visitors' real-time feedback data R, including new stay time S' and sound feedback V'. For example: Assume R=(S',V')S'(Q1)=70 seconds,S'(Q2)=50 seconds,S'(new Q3 content)=40 secondsV'(Q1)=more laughter and discussion,V'(Q2)=moderate discussion,V'(new Q3 content)=a little exclamation.

[0160] Comparative analysis, evaluation of change trend T: The system compares and analyzes the collected real-time feedback data R with the previous comprehensive feedback data set B to evaluate the change trend T of the display effect. For example, it is found that the engagement of Q1 has further increased, while the engagement of the new Q3 content is still low. The specific evaluation results are as follows: Assume T(R,B) = trend of change T(Q1) = significant increase in participation T(new Q3 content) = no significant improvement in engagement.

[0161] Adjust update strategy G to form improved update strategy G': Based on the obtained change trend T, the system adjusts the original update strategy G to form an improved update strategy G' to guide the subsequent optimization of the playlist. For example, add more relevant images about Q1 and continue to improve the new Q3 content. The specific strategies are as follows: Let G'(T) = improved update strategy G'(high engagement, improvement) = add more relevant images about Q1 G'(low engagement, no improvement) = further improve the new Q3 content or consider replacing it.

[0162] This means that if multiple display areas show similar behavior patterns (such as Q1 receiving higher engagement), the system can adjust the playlist based on this data, increasing popular content and reducing unpopular content, thereby better meeting the interests of visitors, significantly improving the relevance and appeal of the display, and enhancing the visitor's interactive experience.

[0163] In this way, the system achieves continuous optimization of display content, ensuring that each playback can more accurately respond to visitors' interests, provide a more personalized and attractive display experience, and ultimately promote increased dwell time and interaction.

[0164] On the other hand, the present invention proposes a food video display interactive system with user feedback, such as Figure 2 As shown, including: The display area initialization and image sequence start module is used to set up multiple screens in the exhibition hall and prepare food-related image materials in advance, and start the corresponding preset image sequence to play on the screen according to the entrance position selected by the visitor when entering the exhibition area; A behavior monitoring and image adjustment module is used to record the visitor's stay behavior and sight direction through a recording device, and adjust the image content being played according to the behavior record; A sound feedback collection and integration module is used to capture the sound signals emitted by visitors using sound sensing equipment, integrate the sound signals with the behavior records, and form comprehensive feedback data; The playlist dynamic update and optimization module is used to dynamically update the playlist based on the feedback data formed, to cyclically optimize the image display process, and to encourage visitors to extend their stay time and increase interaction.

[0165] In addition, the above-mentioned display area initialization and image sequence startup module, behavior monitoring and image adjustment module, sound feedback collection and integration module, and playlist dynamic update and optimization module are also used to implement the other steps of the above-mentioned user feedback food video display interactive method during execution, which will not be repeated here one by one.

[0166] In summary, the present invention integrates the visitor's behavior records and sound signals to form comprehensive feedback data, thereby realizing dynamic updating of image content and cyclic optimization of playlists. This method not only enhances the interactivity of the exhibition, enabling the display content to respond to the visitor's interests and reactions in real time, but also effectively prolongs the visitor's stay time and improves their visit experience quality and satisfaction. By continuously optimizing the display content, it ensures that each visit can bring a fresh and personalized experience to the visitor, significantly improving the overall attractiveness and interactivity level of the exhibition.

[0167] Finally, it should be noted that the above is only a preferred embodiment of the present invention and is not intended to limit the present invention. Although the present invention has been described in detail with reference to the aforementioned embodiments, it is still possible for those skilled in the art to modify the technical solutions described in the aforementioned embodiments or to make equivalent substitutions for some of the technical features therein. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the protection scope of the present invention.

Claims

1. A food video display interactive method based on user feedback, characterized in that: The following steps are involved: A plurality of screens are arranged in the exhibition hall, and food-related video materials are prepared in advance, and a corresponding preset video sequence is started to play on the screen according to the entrance position selected by the visitor when entering the exhibition area; Recording the visitor's stay behavior and sight direction through a recording device, and adjusting the video content being played according to the behavior record; Using sound sensing equipment to capture sound signals emitted by visitors, integrating the sound signals with the behavior records to form comprehensive feedback data; The playlist is dynamically updated based on the feedback data, and the image display process is cyclically optimized to encourage visitors to extend their stay time and increase interaction.

2. The method for interactive food video display based on user feedback according to claim 1, characterized in that: The exhibition hall is equipped with multiple screens and food-related video materials are prepared in advance, including: The exhibition hall is divided into several display areas, and a certain number of display screens are arranged in each area; For each display area, a set of image sequences is arranged, wherein the image sequence is composed of a series of food-related images, and the image themes between adjacent display areas are ensured to be different; Allocate a single screen display time for the image sequence, and adjust this value according to the average stay time of visitors; Establish image switching rules to define how to smoothly transition from the current image to the next image when the display time of a single image ends.

3. The method for interactive food video display based on user feedback according to claim 2, characterized in that: The method of starting to play a corresponding preset image sequence on the screen according to the entrance position selected by the visitor when entering the exhibition area includes: Determine the location of the visitor's entrance to the exhibition area and record this information as an initial reference point; According to the recorded entrance location, a set of matching image sequences is selected for preparation, and the sequence is ensured to be associated with the display screen in the display area; Set up mapping relationships, and match the selected image sequence to the entry position one by one, to ensure that each entry has an independent image playlist; When a visitor appears at the entrance, the corresponding image sequence playback is started according to the mapping relationship, so that the image content responds to the visitor's arrival in real time.

4. The method for interactive food video display based on user feedback according to claim 3, characterized in that: The recording of the visitor's stay behavior and sight direction by recording equipment includes: Start the recording device, which is activated immediately after the visitor enters the exhibition area. The recording device is used to track and capture the visitor's stay position and line of sight movement path to form original behavior trajectory data; Based on the collected behavioral trajectory data, analyze the length of time each visitor stays in front of different images, and associate this information with the corresponding image sequence; Based on the obtained residence time and image association results, a basic data set is prepared for subsequent image adjustment.

5. The food video display interactive system and method based on user feedback according to claim 4, characterized in that: The adjusting the video content being played according to the behavior record includes: Receive the recorded visitor's stay time and sight direction information as the basis for adjusting the image; Determine visitors’ interests based on their duration and sight direction data and select new video content that matches them; Create update rules to guide the adjustment of image sequences based on identified interests, ensuring that new images are relevant to visitors’ interests; Apply the update rules to the currently playing image sequence to generate an adjusted image sequence to achieve instant content update.

6. The method for interactive food video display based on user feedback according to claim 5, characterized in that: The method of using a sound sensing device to capture the sound signal emitted by the visitor includes: Activate sound sensing devices to capture sound signals from visitors in the exhibition area, analyze the characteristics of the captured sound signals, identify sound patterns that express interest or engagement, and mark them as sound feedback; Combine the sound feedback with the adjusted image sequence to evaluate the synergy between the two, and based on the synergy obtained, formulate an image fine-tuning plan to make subtle adjustments to the currently playing image sequence.

7. The method for interactive food video display based on user feedback according to claim 6, characterized in that: The step of integrating the sound signal with the behavior record to form comprehensive feedback data includes: Collect sound feedback, dwell time, and line of sight information as basic materials for integration; Construct a comprehensive feedback structure, pair the sound feedback with the duration of stay and the direction of sight, and form a sound-visual correlation record of visitor behavior; Based on the comprehensive feedback structure formed, the engagement index in each exhibition area is calculated, which reflects the overall interaction level of visitors; Based on the obtained engagement indicators, a comprehensive feedback dataset is compiled. The comprehensive feedback dataset contains the engagement evaluation results of all display areas and is used for subsequent image display optimization.

8. The method for interactive food video display based on user feedback according to claim 7, characterized in that: The dynamically updating the playlist based on the formed feedback data comprises: Parse the compiled comprehensive feedback dataset to extract engagement metrics for each display area; Based on the extracted engagement metrics, evaluate how well the current playlist matches the visitor’s interests and identify content segments that need to be adjusted; Develop an update strategy to determine how to select and prioritize new image content based on the evaluation results; Apply update strategies to existing playlists to generate optimized playlists, ensuring that new playlists dynamically reflect the latest visitor feedback.

9. The method for interactive food video display based on user feedback according to claim 8, characterized in that: The above-mentioned loop optimizes the image display process to encourage visitors to stay longer and increase interaction, including: Based on the generated optimized playlist, a new round of image display cycle is started; During the new round of exhibitions, real-time feedback data from visitors will continue to be collected, including new stay time and voice feedback; Compare and analyze the collected real-time feedback data with the previous comprehensive feedback data set to evaluate the changing trend of the display effect and record any significant changes; Based on the obtained change trends, the update strategy is adjusted to form an improved update strategy to guide the subsequent optimization of the playlist, ensuring that each cycle can respond to the interests of visitors and promote the increase of dwell time and interaction.

10. A food video display interactive system for user feedback for executing the method according to any one of claims 1 to 9, characterized in that: include: The display area initialization and image sequence start module is used to set up multiple screens in the exhibition hall and prepare food-related image materials in advance, and start the corresponding preset image sequence to play on the screen according to the entrance position selected by the visitor when entering the exhibition area; The behavior monitoring and image adjustment module is used to record the visitor's stay behavior and sight direction through a recording device, and adjust the image content being played according to the behavior record; A sound feedback collection and integration module is used to capture the sound signals emitted by visitors using sound sensing equipment, integrate the sound signals with the behavior records, and form comprehensive feedback data; The playlist dynamic update and optimization module is used to dynamically update the playlist based on the feedback data formed, to cyclically optimize the image display process, and to encourage visitors to extend their stay time and increase interaction.

Images