Intelligent exhibition hall control method and system based on Internet of all things

Abstract

The invention provides an intelligent exhibition hall control method and system based on Internet of all things. The method belongs to the technical field of the Internet of Things, and comprises the following steps: constructing an intelligent exhibition hall network architecture based on the Internet of Things, and wirelessly connecting to a central control platform to form a network environment of Internet of all things; acquiring user identity information through an identity recognition device, and constructing a user identity database; and analyzing user preferences through an intelligent algorithm according to the user identity information in combination with user historical behavior data. According to the method, the identity information and the historical behavior data of the user are analyzed through an intelligent algorithm, personalized exhibition recommendation and exhibition routes can be provided for the user, the user can find interested exhibits more quickly, and therefore the visiting experience is improved.

Description

Technical Field

[0001] The present invention proposes a smart exhibition hall control method and system based on the Internet of Everything, belonging to the technical field of Internet of Things. Background Art

[0002] At present, the management of digital exhibition halls mostly relies on manual or simple automated equipment, which has problems such as low management efficiency, poor user experience, and uneven resource allocation. Especially in large exhibitions or fairs, with dense crowds and large amounts of information, traditional management methods are often difficult to cope with, resulting in indoor congestion and increased safety hazards. Therefore, it is particularly important to develop a smart exhibition hall control method based on the Internet of Everything. Summary of the invention

[0003] The present invention provides a smart exhibition hall control method and system based on the Internet of Everything to solve the problems mentioned in the above background technology:

[0004] The present invention proposes a smart exhibition hall control method based on the Internet of Everything, the method comprising:

[0005] S1. Build a smart exhibition hall network architecture based on the Internet of Things, and connect it to the central control platform through wireless to form a network environment where everything is connected;

[0006] S2. Obtain user identity information through an identity recognition device and build a user identity database; analyze user preferences through an intelligent algorithm based on the user identity information and combined with the user's historical behavior data;

[0007] S3. Use environmental sensors to monitor the environmental parameters in the exhibition hall in real time and adjust the equipment according to the preset environmental standards or user comfort requirements;

[0008] S4. Collect crowd flow information in the exhibition hall through the image acquisition device, and analyze the crowd density of each exhibition area in real time based on the crowd counting model; intelligently generate guidance information based on the crowd density data;

[0009] S5. The central control platform conducts comprehensive analysis on various types of collected data and provides decision support for the operation and management of the exhibition hall through data mining and machine learning algorithms.

[0010] Furthermore, the S1 includes:

[0011] S11. Design the deployment plan of IoT devices according to the layout and needs of the exhibition hall, integrate various IoT devices into a unified communication protocol, and build a layered network architecture;

[0012] S12. Deploy wireless network infrastructure, implement network security measures, and conduct equipment joint debugging and testing;

[0013] S13. Simulate data transmission stress tests in different scenarios, evaluate system stability and response speed, and adjust network configuration and equipment parameters based on test results.

[0014] Furthermore, the S2 includes:

[0015] S21. Deploy RFID readers or face recognition cameras at the entrance of the exhibition hall to automatically capture user identity information, compare and verify the collected identity information with the user database, and identify the user identity;

[0016] S22. Collect user historical behavior data and build user portraits. Use intelligent algorithms to deeply mine user preferences and predict the types of exhibits that users may be interested in.

[0017] S23. Based on the analysis results, a personalized exhibition route and exhibit recommendation list are tailored for the user; personalized exhibition information and interactive prompts are pushed to the user through multiple channels.

[0018] Furthermore, the S3 includes:

[0019] S31. Deploy environmental monitoring equipment in the exhibition hall to collect environmental parameter data in real time and upload it to the central control platform;

[0020] S32. Formulate intelligent control strategies based on preset environmental standards or user comfort feedback; dynamically adjust control strategies based on historical data and real-time environmental changes through machine learning algorithms;

[0021] S33. The central control platform automatically sends control instructions to relevant equipment based on the control strategy. The relevant equipment executes the control instructions and adjusts the environmental parameters in the exhibition hall to the preset standards or user comfort requirements.

[0022] Furthermore, the S4 includes:

[0023] S41. Use high-definition cameras to capture the flow of people in the exhibition hall, use image recognition technology to extract crowd information, build a crowd counting model, and combine deep learning algorithms to analyze the density of people in each exhibition area in real time.

[0024] S42. Evaluate the congestion situation of each exhibition area based on crowd density data, predict future crowd flow trends, and formulate intelligent guidance strategies;

[0025] S43. Use the LED display screens in the exhibition hall to update the flow of people in each exhibition area and recommend visiting routes in real time, and guide users to avoid congested areas;

[0026] S44. Through multiple means, personalized tour routes and real-time crowd flow warning information are pushed to users. A voice broadcast system is set up at key locations in the exhibition hall. When the flow of people in a certain exhibition area reaches a threshold, a guiding voice is automatically played to remind users to divert traffic reasonably.

[0027] The present invention proposes an intelligent exhibition hall control system based on the Internet of Everything, the system comprising:

[0028] Architecture building module: Build a smart exhibition hall network architecture based on the Internet of Things, and connect it to the central control platform through wireless to form a network environment where everything is connected;

[0029] Information acquisition module: obtains user identity information through the identity recognition device and builds a user identity database; analyzes user preferences through intelligent algorithms based on user identity information and historical user behavior data;

[0030] Real-time monitoring module: real-time monitoring of environmental parameters in the exhibition hall through environmental sensors, based on preset environmental standards or user comfort requirements;

[0031] Image acquisition module: collects information about the flow of people in the exhibition hall through image acquisition devices, and analyzes the density of people in each exhibition area in real time based on the population statistics model; intelligently generates guidance information based on the density of people;

[0032] Comprehensive analysis module: The central control platform conducts comprehensive analysis on various types of collected data and provides decision support for the operation and management of the exhibition hall through data mining and machine learning algorithms.

[0033] Furthermore, the architecture building module includes:

[0034] Deployment design module: Design deployment plans for IoT devices based on exhibition hall layout and requirements, integrate various IoT devices into a unified communication protocol, and build a hierarchical network architecture;

[0035] Facility deployment module: deploy wireless network infrastructure, implement network security measures, and conduct equipment joint debugging tests;

[0036] Test simulation module: simulates data transmission stress tests in different scenarios, evaluates system stability and response speed, and adjusts network configuration and equipment parameters based on test results.

[0037] Furthermore, the information acquisition module includes:

[0038] Identity recognition module: Deploy RFID readers or face recognition cameras at the entrance of the exhibition hall to automatically capture user identity information, compare and verify the collected identity information with the user database, and identify the user's identity;

[0039] Data collection module: collects user historical behavior data and builds user portraits. It uses intelligent algorithms to deeply mine user preferences and predict the types of exhibits that users may be interested in.

[0040] Recommendation module: Based on the analysis results, tailor personalized exhibition routes and exhibit recommendation lists for users; push personalized exhibition information and interactive prompts to users through multiple channels.

[0041] Furthermore, the real-time monitoring module includes:

[0042] Data upload module: deploy environmental monitoring equipment in the exhibition hall to collect environmental parameter data in real time and upload it to the central control platform;

[0043] User feedback module: formulate intelligent control strategies based on preset environmental standards or user comfort feedback; dynamically adjust control strategies based on historical data and real-time environmental changes through machine learning algorithms;

[0044] Command control module: The central control platform automatically sends control commands to relevant equipment based on the control strategy. The relevant equipment executes the control commands and adjusts the environmental parameters in the exhibition hall to the preset standards or user comfort requirements.

[0045] Furthermore, the image acquisition module includes:

[0046] Crowd analysis module: Use high-definition cameras to capture the flow of people in the exhibition hall, use image recognition technology to extract crowd information, build a headcount model, and combine deep learning algorithms to analyze the density of people in each exhibition area in real time.

[0047] Situation assessment module: Based on crowd density data, evaluate the congestion situation in each exhibition area, predict future crowd flow trends, and formulate intelligent guidance strategies;

[0048] User guidance module: using the LED display screen in the exhibition hall to update the flow of people in each exhibition area and recommend visiting routes in real time, guiding users to avoid congested areas;

[0049] User reminder module: through multiple means, personalized tour routes and real-time crowd warning information are pushed to users. Voice broadcast systems are set up at key locations in the exhibition hall. When the flow of people in a certain exhibition area reaches the threshold, guiding voices are automatically played to remind users to divert traffic reasonably.

[0050] Beneficial effects of the present invention: by analyzing the identity information and historical behavior data of users through intelligent algorithms, personalized exhibition recommendations and exhibition routes can be provided to users, so that users can find exhibits of interest more quickly, thereby improving the visiting experience; by real-time monitoring of the environmental parameters of the exhibition hall and dynamically adjusting them according to the user's comfort level, the comfort and suitability of the environment in the exhibition hall can be effectively maintained, the needs of different users can be met, and the overall exhibition effect can be improved; by analyzing the density of human traffic and real-time human traffic warning, the exhibition hall can better manage and guide the flow of people, avoid congestion, improve the flow of visitors, and improve the operating efficiency of the exhibition hall; the central control platform conducts comprehensive analysis of various data, and can provide data support and decision-making basis for the operation and management of the exhibition hall, thereby optimizing resource allocation and exhibition arrangements, and improving the overall operating efficiency of the exhibition hall; by designing, testing and optimizing the network deployment solution, the stability of the Internet of Things equipment and the response speed of the system are ensured, the reliability and security of the system are enhanced, and the impact of potential technical problems on the operation of the exhibition hall is reduced; by combining the real-time analysis of environmental parameters and user feedback by machine learning algorithms, intelligent regulation of the environment in the exhibition hall is realized, environmental conditions are automatically adjusted, and the comfort and functionality of the exhibition hall are ensured. BRIEF DESCRIPTION OF THE DRAWINGS

[0051] Figure 1 It is a step diagram of the method of the present invention;

[0052] Figure 2 This is a system module diagram of the present invention. DETAILED DESCRIPTION

[0053] In order to more clearly understand the above-mentioned purpose, features and advantages of the present invention, the present invention is described in detail below in conjunction with the accompanying drawings and specific embodiments. It should be noted that the embodiments of the present application and the features in the embodiments can be combined with each other without conflict.

[0054] In the following description, many specific details are set forth to facilitate a full understanding of the present invention. The embodiments described are only a part of the embodiments of the present invention, rather than all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0055] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as those commonly understood by those skilled in the art of the present invention. The terms used in the specification of the present invention herein are only for the purpose of describing specific embodiments and are not intended to limit the present invention.

[0056] One embodiment of the present invention, as Figure 1 As shown, a smart exhibition hall control method based on the Internet of Everything includes:

[0057] S1. Build a smart exhibition hall network architecture based on the Internet of Things, including identity recognition devices, environmental sensors, image acquisition devices, smart access control systems, exhibit interactive devices and other IoT devices, and connect them to the central control platform through wireless to form a network environment where everything is connected;

[0058] S2. Obtain user identity information through identity recognition devices (such as RFID tags, face recognition technology, etc.) and build a user identity database; analyze user preferences through intelligent algorithms based on user identity information and historical user behavior data, and provide users with personalized exhibition route planning, exhibit recommendation and other services;

[0059] S3. Use environmental sensors (such as temperature and humidity sensors, light sensors, etc.) to monitor the environmental parameters in the exhibition hall in real time, such as temperature, humidity, light intensity, etc.; according to the preset environmental standards or user comfort requirements, automatically adjust air conditioning, lighting and other equipment to maintain the comfort of the environment in the exhibition hall and the safety of exhibits;

[0060] S4. Collect crowd flow information in the exhibition hall through image acquisition devices (such as high-definition cameras), and analyze the crowd density of each exhibition area in real time based on the crowd counting model; intelligently generate guidance information based on the crowd density data; guide users to flow reasonably through display screens, voice broadcasts, etc. to avoid congestion;

[0061] S5. The central control platform conducts comprehensive analysis on various types of collected data, including user behavior data, environmental data, exhibit interaction data, etc.; through data mining and machine learning algorithms, it discovers valuable information such as potential market demand and user preferences, and provides decision-making support for the operation and management of the exhibition hall.

[0062] The working principle of the above technical solution is: by integrating multiple IoT devices such as identity recognition devices, environmental sensors, image acquisition devices, intelligent access control systems, and exhibit interactive devices into the smart exhibition hall, and wirelessly connecting them to the central control platform, a comprehensive network environment with interconnected everything is built. These devices each have different functions and jointly provide support for the intelligent management and user experience of the exhibition hall. When a user enters the exhibition hall, the identity recognition device (such as RFID tags, face recognition technology, etc.) will automatically capture the user's identity information and compare and record it with the user's identity database. The system uses the user's historical behavior data and intelligent algorithms to analyze the user's preferences, thereby providing personalized exhibition route planning, exhibit recommendation and other services. This can not only enhance the user's visiting experience, but also enhance the attractiveness of the exhibits and the interactivity of the exhibition. Environmental sensors (such as temperature and humidity sensors, light sensors, etc.) monitor the environmental parameters in the exhibition hall in real time to ensure that the temperature, humidity, light intensity, etc. are within an appropriate range. Once the environmental parameters deviate from the preset standards or user comfort requirements, the system will automatically trigger the adjustment mechanism, such as adjusting the air conditioning temperature, changing the lighting brightness, etc., to maintain the comfort of the environment in the exhibition hall and the safety of the exhibits. Image acquisition devices (such as high-definition cameras) capture the flow of people in the exhibition hall in real time, and analyze the density of people in each exhibition area through the population counting model. The system intelligently generates guidance information based on the flow density data, and conveys it to users through display screens, voice broadcasts, etc. This helps to guide users to flow rationally, avoid congestion, and improve the efficiency and safety of the exhibition hall. As the core of the entire system, the central control platform is responsible for collecting, integrating and processing data from various IoT devices, including user behavior data, environmental data, exhibit interaction data, etc. Through data mining and machine learning algorithms, the system can discover valuable information such as potential market demand and user preferences, and provide data support and decision-making basis for the operation and management of the exhibition hall. This helps to optimize the exhibition layout, improve service quality, enhance user experience, and provide strong support for future exhibition activities.

[0063] The effects of the above technical solutions are as follows: through identity recognition and user behavior analysis, the system can provide users with personalized exhibition route planning and exhibit recommendations to meet the different interests and needs of users, thereby enhancing the user's visiting experience; environmental sensors monitor and automatically adjust the temperature, humidity and light intensity in the exhibition hall in real time to ensure that users are always in a comfortable environment and improve user satisfaction; image acquisition devices and crowd counting models help the system analyze crowd density in real time, and avoid congestion through intelligent guidance information, so that users can visit the exhibition more smoothly; the central control platform conducts comprehensive analysis of various data, so that exhibition hall managers can understand the operation status of the exhibition hall in real time, so as to make more accurate and efficient management decisions; based on crowd density data, the system can intelligently adjust the resource allocation of each exhibition area, such as adding tour guides, adding interactive devices, etc., to cope with the crowd pressure in different exhibition areas; automatic adjustment of air conditioning, lighting and other equipment can It can effectively reduce energy consumption and save operating costs while ensuring environmental comfort; environmental sensors monitor the environmental parameters in the exhibition hall in real time to ensure that the exhibits are in a suitable environment and avoid damage to the exhibits due to factors such as changes in temperature and humidity or excessive light; the density of human traffic is controlled through intelligent guidance information to reduce the risk of exhibits being excessively touched or damaged, and extend the display life of exhibits; the central control platform uses data mining technology to extract valuable information from massive data, such as user preferences and market demand, to provide data support for the future development of the exhibition hall; combined with machine learning algorithms, the system can predict future user behavior and market trends, and provide a more scientific decision-making basis for the operation and management of the exhibition hall; the smart exhibition hall enhances users' awareness and favorability of the exhibition hall and the brands it displays by providing a novel and convenient visiting experience; the smart exhibition hall itself is a high-tech display method that can reflect the brand's technical strength and innovation capabilities and enhance the brand image.

[0064] In one embodiment of the present invention, the S1 includes:

[0065] S11. Design the best deployment plan for IoT devices based on the exhibition hall layout and needs, integrate various IoT devices into a unified communication protocol (such as MQTT or CoAP); and build a layered network architecture; including the perception layer (IoT devices), network layer (wireless LAN, Zigbee, LoRa, etc.), platform layer (central control platform) and application layer (user interaction interface, data analysis system).

[0066] S12. Deploy wireless network infrastructure, including high-performance Wi-Fi APs, IoT gateways, etc., to ensure that IoT devices in the exhibition hall can stably access the network, implement network security measures, such as data encryption transmission, access control list (ACL) settings, to ensure data transmission security and privacy protection. And conduct equipment joint debugging tests; ensure that all IoT devices can correctly access the central control platform and stably transmit data;

[0067] S13. Simulate data transmission stress tests in different scenarios, evaluate system stability and response speed, and adjust network configuration and device parameters based on test results to optimize system performance and improve user experience.

[0068] The working principle of the above technical solution is as follows: First, through market research, understand the advanced IoT devices on the current market, including high-precision RFID tags, multi-modal face recognition terminals, ultra-low power multi-parameter environmental sensors, high-definition smart cameras (with night infrared, face tracking and other functions), smart access control systems and various exhibit interactive devices (such as AR augmented reality glasses, touch screen interactive screens); select the most suitable IoT devices according to the specific layout and needs of the exhibition hall; design the best deployment plan for IoT devices to ensure that the equipment can fully cover the exhibition hall, while considering the collaborative work and data interaction between devices; integrate all IoT devices into a unified communication protocol (such as MQTT or CoAP) to achieve seamless communication and data exchange between devices; build a layered network architecture, including the perception layer (IoT devices), network layer (wireless LAN, Zigbee, LoRa and other communication technologies), platform layer (central control platform, responsible for data processing and decision-making), and application layer (user interaction interface, data analysis system, etc.); deploy high-performance Wi-Fi APs and IoT gateways in the exhibition hall to ensure that IoT devices can stably access the network; The system is equipped with a wireless network that is capable of performing network planning and configuration, optimizing the coverage and signal strength of the wireless network, and reducing interference and blind spots. Encryption technology is used to ensure the security of data transmission and prevent data from being stolen or tampered with. Access control lists are set to restrict illegal devices from accessing the network and ensure the purity and security of the network environment. Equipment joint debugging tests are carried out to ensure that all IoT devices can correctly access the central control platform and achieve stable data transmission. Problems in the device access and communication process are discovered and resolved in a timely manner to ensure the stability and reliability of the system. Data transmission pressures in different scenarios are simulated, such as high traffic density and intensive use of equipment, to evaluate the stability and response speed of the system. Data during the test process, including key indicators such as transmission delay and packet loss rate, are collected for analysis and evaluation. Network configuration is adjusted according to the test results, such as increasing the number of APs and optimizing channel allocation, to improve network performance. Parameter settings of IoT devices, such as sampling frequency and transmission power, are adjusted to balance data transmission quality and equipment energy consumption. System architecture is optimized according to the test results to improve the overall performance and stability of the system. The user experience in the exhibition hall is enhanced by optimizing data transmission and reducing delays.

[0069] The effects of the above technical solutions are as follows: by investigating advanced IoT devices on the market, the technological leadership and functional richness of the equipment used in the exhibition hall are ensured; various IoT devices are integrated into a unified communication protocol (such as MQTT or CoAP), which improves the interoperability and data exchange efficiency between devices and reduces the difficulty of subsequent maintenance and upgrades; the constructed layered network architecture (perception layer, network layer, platform layer, application layer) makes the system structure clear, easy to manage and expand; the optimal deployment plan designed according to the layout and needs of the exhibition hall ensures that the IoT devices can play their full role and facilitates subsequent adjustments and upgrades; the deployed high-performance Wi-Fi AP and IoT gateway ensure the stable access of IoT devices in the exhibition hall and reduce the risk of network failures and interruptions; the implemented security measures such as data encryption transmission and access control list (ACL) settings effectively ensure the security of data transmission and the protection of user privacy, and enhance users' trust in the exhibition hall; by simulating data transmission stress tests in different scenarios, the system stability and response speed are comprehensively evaluated, providing a strong basis for system optimization; the network configuration and equipment parameters are adjusted according to the test results to optimize the system performance and improve the user experience. This includes reducing data transmission delays, improving system response speed, etc., so that users can enjoy smoother and more convenient services during their visit; based on the intelligent recognition and analysis capabilities of IoT devices, the system can provide users with personalized exhibition route planning, exhibit recommendations and other services, improving the user's visiting experience; through real-time monitoring and automatic adjustment of environmental sensors, the system can maintain the comfort of the environment in the exhibition hall and the safety of the exhibits, creating a more pleasant visiting environment for users; the system can collect user behavior data, environmental data, exhibit interaction data, etc. in real time, providing rich data support for the operation and management of the exhibition hall; through data mining and machine learning algorithms, the system can discover valuable information such as potential market demand and user preferences, providing scientific decision-making basis for the operation and management of the exhibition hall, and improving management efficiency and decision-making level.

[0070] In summary, the technical solution of the S1 stage not only improves the advancement and compatibility of equipment in the process of building the network architecture of the smart exhibition hall based on the Internet of Things, but also enhances the flexibility and scalability of the network architecture, ensuring the stability and security of the network. At the same time, through system performance optimization and user experience improvement, it provides strong support for the operation and management of the exhibition hall, and promotes the development of the exhibition hall towards intelligence and efficiency.

[0071] In one embodiment of the present invention, the S2 includes:

[0072] S21. Deploy RFID readers or face recognition cameras at the entrance of the exhibition hall to automatically capture user identity information, compare and verify the collected identity information with the user database, and quickly identify the user identity;

[0073] S22. Collect historical user behavior data, such as visit records, exhibit interaction, etc., and build user portraits. Through intelligent algorithms (such as collaborative filtering and deep learning), deeply mine user preferences and predict the types of exhibits that users may be interested in.

[0074] S23. Based on the analysis results, tailor a personalized exhibition route and exhibit recommendation list for the user; push personalized exhibition information and interactive prompts to the user through multiple channels, including display screens in the exhibition hall, mobile phone apps or AR glasses.

[0075] The working principle of the above technical solution is as follows: RFID readers or multimodal face recognition cameras are deployed at the entrance of the exhibition hall. These devices can automatically capture the identity information of users entering the exhibition hall; when users pass through the entrance, the RFID reader will read the identity information in the RFID tag (such as membership card, ticket, etc.) carried by the user, or the face recognition camera will capture the user's facial features, and compare and verify this information with the data pre-stored in the user database; through efficient algorithms and database query technology, the system can quickly identify the user's identity and provide a basis for subsequent personalized services; the system continuously collects the user's historical behavior data in the exhibition hall, including but not limited to visit records (such as visit time, stay time, visit path, etc.), exhibit interaction (such as which exhibits have been interacted with, interaction methods, interaction duration, etc.); based on the collected data, the system uses big data and artificial intelligence technology to build a personalized portrait of the user. This includes multiple dimensions such as the user's age, gender, interest preferences, and behavior patterns; through intelligent algorithms (such as collaborative filtering, deep learning, etc.), the system conducts in-depth mining of user preferences. Collaborative filtering algorithms can predict the interests of current users based on the behaviors of similar users; while deep learning algorithms can more deeply understand the complex patterns behind user behaviors, thereby more accurately predicting the user's points of interest; based on the results of user portraits and preference analysis, the system tailors personalized exhibition routes and exhibit recommendation lists for users. These routes and lists are designed to meet the specific interests and needs of users and improve their visiting experience and satisfaction; the system pushes personalized exhibition information and interactive prompts to users through multiple channels, including display screens in the exhibition hall (such as electronic guide screens), mobile phone apps (users can view exhibition information, make appointments for exhibit interaction, etc.) or AR glasses (users can get a more immersive exhibition experience through AR glasses); when recommending exhibits, the system will also consider the interactivity and fun of the exhibits, encouraging users to interact with the exhibits to further deepen their understanding and memory of the exhibits.

[0076] The effects of the above technical solutions are as follows: through RFID readers or face recognition cameras, users can quickly complete identity authentication and enter the exhibition hall without waiting, which greatly saves time and improves the user's initial experience; based on the user's preferences and historical behavior data, the system tailors personalized exhibition routes so that users can go directly to the exhibition area they are most interested in, improving the pertinence and efficiency of the visit; the system predicts the types of exhibits that users may be interested in through intelligent algorithms, and pushes relevant exhibit information to help users discover more exhibits of interest, enriching the user's visiting experience; personalized exhibition information and interactive prompts are pushed to users through multiple channels such as display screens in the exhibition hall, mobile phone APPs or AR glasses, increasing the user's interaction opportunities with the exhibition content and improving the user's sense of participation and immersion; the system adjusts the exhibit display method or increases interactive links based on the user's interaction, so that users can The system can help users gain a deeper understanding of the exhibits, thus enhancing the interactivity and fun of the exhibitions. Through personalized exhibition routes and exhibit recommendations, the system can accurately push exhibition information to target user groups, thus increasing the exposure and appeal of the exhibitions. By collecting user behavior data and building user portraits, the system provides valuable data support for exhibition organizers, helping them understand user needs, evaluate exhibition effects, and continuously optimize exhibition content and services. Personalized exhibition experience can enhance user satisfaction and loyalty, prompting users to share exhibition information through channels such as social media, further expanding the influence and popularity of the exhibition. The system can intelligently dispatch staff and exhibit resources based on information such as user traffic and exhibit popularity, ensuring order at the exhibition site and safety of exhibits. Through data analysis, the system can promptly identify problems in operations and make suggestions for improvement, thus helping exhibition organizers achieve efficient operations and refined management.

[0077] In summary, the technical solution of the S2 stage not only improves the user experience and satisfaction in the exhibition hall through user identity recognition, historical behavior data analysis, personalized exhibition routes and exhibit recommendations, but also enhances user interaction and participation, improves the exhibition effect and influence, and optimizes resource allocation and management. These benefits and effects jointly promote the intelligent and personalized development of the exhibition industry.

[0078] In one embodiment of the present invention, S3 includes:

[0079] S31. Deploy environmental monitoring equipment (such as temperature and humidity sensors and light sensors) in the exhibition hall to collect environmental parameter data in real time and upload it to the central control platform;

[0080] S32. Develop intelligent control strategies based on preset environmental standards (such as suitable temperature and humidity range, light intensity threshold) or user comfort feedback; dynamically adjust control strategies based on historical data and real-time environmental changes through machine learning algorithms; and improve control accuracy and efficiency;

[0081] S33. The central control platform automatically sends control instructions to relevant equipment (including air conditioning and lighting equipment) according to the control strategy. The relevant equipment executes the control instructions and adjusts the environmental parameters in the exhibition hall to the preset standards or user comfort requirements.

[0082] The working principle of the above technical solution is as follows: deploy environmental monitoring equipment such as temperature and humidity sensors and light sensors in different areas of the exhibition hall. These devices can sense and collect environmental parameter data in the exhibition hall in real time; the collected environmental parameter data are uploaded to the central control platform in real time through wireless networks or other communication methods. As the core of data processing and decision-making, the central control platform is responsible for receiving, storing and analyzing these data; according to the operation needs of the exhibition hall and the protection requirements of exhibits, the appropriate environmental standards such as temperature and humidity range and light intensity threshold are preset; at the same time, the system will also consider the user's comfort feedback, and obtain the user's subjective evaluation of environmental comfort through questionnaires, user behavior analysis and other methods; combined with the preset environmental standards, user comfort feedback, historical data and real-time environmental changes, the system uses machine learning algorithms to dynamically adjust the control strategy. The machine learning algorithm can identify the laws of environmental changes, predict future environmental trends, and optimize the control strategy accordingly to improve the accuracy and efficiency of control; the central control platform automatically sends control instructions to related equipment (such as air conditioners, lighting equipment, etc.) according to the formulated control strategy. These control instructions include specific control targets (such as lowering the temperature, adjusting the light intensity, etc.) and parameters (such as target temperature value, light intensity value, etc.); after receiving the control instructions, the relevant equipment will perform the corresponding control operations. For example, the air-conditioning equipment will adjust the cooling or heating mode according to the control instructions to adjust the temperature in the exhibition hall; the lighting equipment will adjust the light intensity and color temperature according to the control instructions to improve the lighting environment in the exhibition hall; through the execution of the equipment, the environmental parameters in the exhibition hall are gradually adjusted to the preset standards or user comfort requirements. At the same time, the system will continue to monitor the changes in environmental parameters, and adjust the control strategy and equipment control instructions as needed to ensure the stability and comfort of the environmental parameters in the exhibition hall.

[0083] The effects of the above technical solutions are as follows: by real-time monitoring of the environmental parameters in the exhibition hall and formulating control strategies based on preset standards and user comfort feedback, the system can accurately adjust environmental parameters such as temperature, humidity and light in the exhibition hall to ensure that the environment is always kept in the most suitable state and improve the user's visit comfort; using machine learning algorithms, the system can dynamically adjust the control strategy based on historical data and real-time environmental changes, further improve the accuracy and efficiency of control, and ensure the stability and comfort of environmental parameters; suitable temperature, humidity and light conditions are crucial for the protection of exhibits. Through intelligent control, the system can ensure that the environmental parameters in the exhibition hall are always kept within the appropriate range required by the exhibits, effectively extend the shelf life of the exhibits, and reduce the risk of damage caused by environmental factors; real-time monitoring of environmental parameters can also timely discover potential environmental problems, such as abnormal temperature and humidity, excessive light, etc., so as to take corresponding measures to prevent and deal with them and avoid damage to the exhibits; the system can intelligently control the operation of related equipment according to the actual environmental needs and personnel flow in the exhibition hall to avoid unnecessary energy waste. For example, when there are fewer people in the exhibition hall, the lighting brightness and air conditioning power are automatically reduced to achieve energy conservation and emission reduction; through precise control and dynamic adjustment strategies, the system can optimize resource utilization efficiency and reduce operating costs; the entire environmental control process is managed automatically, reducing manual intervention and operating costs. Staff can focus more on other important tasks and improve overall operational efficiency; the central control platform can monitor the environmental parameters and equipment operating status in the exhibition hall in real time, detect and handle abnormal situations in a timely manner, and ensure the normal operation of the exhibition hall; the system can dynamically adjust environmental parameters based on user comfort feedback to provide a more personalized service experience. Users can adjust the environmental settings in the exhibition hall according to their needs and preferences to improve the satisfaction and comfort of the visit; the intelligent environmental control system can also enhance the sense of technology and modernity of the exhibition hall, attracting more users' attention and participation.

[0084] In summary, the technical solution of the S3 stage not only improves the comfort of the exhibition hall environment and the safety of exhibits through intelligent environmental monitoring and control, but also achieves multiple effects such as energy conservation and emission reduction and improved operational efficiency. These benefits and effects jointly promote the sustainable development of the exhibition hall and the improvement of user experience.

[0085] In one embodiment of the present invention, the S32 includes:

[0086] Collect and analyze the exhibition hall's long-term environmental parameter data (such as temperature, humidity, light intensity, air quality, etc.) and user comfort feedback data;

[0087] Through statistical analysis and data mining technology, the correlation between environmental parameters and user comfort is identified, and an environmental comfort prediction model is constructed;

[0088] Through machine learning algorithms (such as decision trees, random forests, neural networks, etc.), the model is trained and the user's comfort perception under different environmental conditions is predicted;

[0089] Combined with the data collected in real time by current environmental monitoring equipment, time series analysis is used to predict environmental change trends in the future;

[0090] Based on the anomaly detection mechanism, abnormal fluctuations in environmental parameters, such as sudden temperature rise or humidity drop, are discovered and warned in a timely manner, providing a basis for rapid response;

[0091] Dynamically generate control strategies based on prediction models and user comfort preferences; strategies should take into account differentiated needs in different time periods (such as weekdays and weekends, daytime and nighttime).

[0092] Introduce a priority sorting mechanism to ensure that when resources are limited, the environmental factors that have the greatest impact on user comfort (such as temperature) are regulated first;

[0093] Design flexible regulation strategies, such as phased regulation and gradual adjustment, to reduce discomfort during the regulation process.

[0094] Implement online learning mechanisms, continuously incorporate new environmental data and user feedback into the model, and continuously optimize the control strategy; use experimental design methods such as A / B testing to compare the effects of different control strategies and select the best strategy for implementation;

[0095] Through the adaptive learning algorithm, the system can automatically adjust the learning rate and parameters according to the long-term operation effect, thus improving the control efficiency and accuracy;

[0096] Analyze user behavior patterns, such as visiting paths, dwelling time, etc., to predict their possible environmental needs; combine user portraits to provide personalized environmental control solutions for different user groups, such as providing more suitable temperature and lighting environment for elderly visitors, and design interactive interfaces to allow users to fine-tune environmental parameters according to their immediate needs, while collecting these feedbacks to further optimize the control strategy.

[0097] The working principle of the above technical solution is as follows: the system first collects environmental parameter data (such as temperature, humidity, light intensity, air quality, etc.) in real time through the environmental monitoring equipment deployed in the exhibition hall; at the same time, the system collects user comfort feedback data, which may come from questionnaires, user evaluations or direct comfort adjustment requests; statistical analysis and data mining techniques are used to process the collected data to identify the potential correlation between environmental parameters and user comfort; based on the data analysis results, an environmental comfort prediction model is constructed. The model can predict the user's comfort feeling based on current or future environmental parameters; the model is trained using machine learning algorithms (such as decision trees, random forests, neural networks, etc.) to improve the accuracy and robustness of the prediction; after the model training is completed, the user's comfort under different environmental conditions can be predicted in real time or regularly, providing a basis for the formulation of control strategies; through time series analysis technology, combined with current environmental monitoring data, the environmental change trend in the future period is predicted; an anomaly detection mechanism is implemented to monitor the fluctuation of environmental parameters in real time, and once an anomaly is found (such as a sudden increase in temperature or a decrease in humidity), the early warning mechanism is immediately triggered; based on the prediction model and user comfort preferences, a control strategy is dynamically generated. The strategy needs to take into account the differentiated needs of different time periods, such as the control focus may be different on weekdays and weekends, daytime and night; introduce a priority sorting mechanism to ensure that when resources are limited, the control needs of environmental factors that have the greatest impact on user comfort are given priority; design flexible control strategies, such as phased adjustment and gradual adjustment, to reduce discomfort during the control process; implement an online learning mechanism to continuously incorporate new environmental data and user feedback into the model to continuously optimize the control strategy; use experimental design methods such as A / B testing to compare the effects of different control strategies and select the optimal strategy for implementation; use adaptive learning algorithms to automatically adjust the learning rate and parameters based on the long-term operation of the system to improve control efficiency and accuracy; analyze user behavior patterns, such as visiting paths, dwell time, etc., to predict their possible environmental needs; combine user portrait technology to provide personalized environmental control solutions for different user groups. For example, provide elderly visitors with a more suitable temperature and lighting environment; design an interactive interface that allows users to fine-tune environmental parameters according to their immediate needs, and collect these feedbacks to further optimize the control strategy; the central control platform automatically sends control instructions to relevant equipment based on the generated control strategy; the relevant equipment executes the control instructions and adjusts the environmental parameters in the exhibition hall to preset standards or user comfort requirements; the system continuously monitors environmental changes and user feedback, and adjusts the control strategy based on the feedback results to form a closed-loop control.

[0098] The effect of the above technical solution is: through the accurate environmental comfort prediction model, the system can predict and adjust the environmental parameters in advance to ensure that the environment in the exhibition hall is always within the comfort range expected by the user. This not only improves the user's visiting experience, but also enhances user satisfaction and loyalty; the intelligent control strategy is precisely regulated according to real-time environmental data and user needs, avoiding excessive waste of resources. At the same time, by introducing energy-saving technologies and green energy utilization solutions, the system can reduce energy consumption while ensuring comfort, achieve energy conservation and emission reduction and sustainable development; the control strategy is flexible in design and can be adjusted in time according to rapid changes in the environment and user needs. Whether it is staged adjustment or gradual adjustment, it can effectively reduce the discomfort during the control process and improve the user's comfort experience; the anomaly detection mechanism can timely detect and warn of abnormal fluctuations in environmental parameters, providing sufficient response time for exhibition hall managers. This real-time warning capability helps to reduce the inconvenience and losses caused by environmental problems and improve the operational efficiency and safety of the exhibition hall; by analyzing user behavior patterns and building user portraits, the system can provide personalized environmental control solutions for different user groups. This customized service can meet the specific needs of users, enhance their sense of belonging and satisfaction, and thus increase user stickiness; the online learning mechanism and adaptive learning algorithm enable the system to continuously incorporate new environmental data and user feedback into the model and continuously optimize the control strategy. This continuous optimization capability helps to improve the control efficiency and accuracy of the system, enabling it to adapt to more complex and changing environments and user needs; through comprehensive analysis of historical data and real-time data, the system can provide detailed data support and decision-making basis for exhibition hall managers. This helps managers to more accurately grasp the operation status of the exhibition hall and formulate more scientific and reasonable decision-making plans; the design of the interactive interface allows users to fine-tune environmental parameters according to their immediate needs, which enhances the interactivity between users and the system. This sense of participation not only improves user satisfaction, but also helps to collect more user feedback to further optimize the control strategy.

[0099] In one embodiment of the present invention, the S4 includes:

[0100] S41. Use high-definition cameras to capture the flow of people in the exhibition hall, use image recognition technology to extract crowd information, build a crowd counting model, and combine deep learning algorithms to analyze the density of people in each exhibition area in real time.

[0101] S42. Evaluate the congestion situation of each exhibition area based on crowd density data, predict future crowd trends, and formulate intelligent guidance strategies; including dynamically adjusting the opening order of exhibition areas, setting up temporary diversion channels, activating guidance signs for specific exhibition areas, etc.;

[0102] The congestion situation of each exhibition area is evaluated by the following formula:

[0103]

[0104] Among them, CI represents the congestion coefficient. The larger its value, the more serious the congestion. i represents the actual crowd density of the ith exhibition area, RC i represents the capacity of the i-th exhibition hall, SF i It represents the speed factor of the ith exhibition area, α represents the index of density weight, which is used to adjust the influence of crowd density on congestion; β represents the index of speed weight, which is used to adjust the influence of crowd speed on congestion.

[0105] S43. Use the LED display screens in the exhibition hall to update the flow of people in each exhibition area and recommend visiting routes in real time, and guide users to avoid congested areas;

[0106] S44. Through multiple means (such as smart guide APP), personalized tour routes and real-time crowd warning information are pushed to users. A voice broadcast system is set up at key locations in the exhibition hall. When the crowd flow in a certain exhibition area reaches the threshold, a guiding voice is automatically played to remind users to divert traffic reasonably.

[0107] The working principle of the above technical solution is as follows: high-definition cameras are arranged in the exhibition hall to capture the flow of people in the exhibition hall in real time; advanced image recognition technology is used to extract flow information such as the number of people and moving direction from the captured images; based on the extracted flow information, a population statistics model is constructed to conduct real-time analysis of the density of people in each exhibition area in the exhibition hall; combined with deep learning algorithms, the accuracy and real-time analysis of the density of people flow is improved to provide data support for subsequent congestion assessment and guidance strategy formulation; based on the density of people flow data, the congestion situation of each exhibition area is evaluated in real time to identify possible congestion areas; using historical data and real-time flow information, the flow of people in the future is predicted through prediction algorithms to provide a basis for formulating more accurate and effective guidance strategies; based on the results of congestion assessment and flow trend prediction, intelligent guidance strategies are formulated. These strategies may include dynamically adjusting the order of opening exhibition areas, setting temporary diversion channels, activating guidance signs in specific exhibition areas, etc., to effectively alleviate congestion and improve user experience; using the LED display screen in the exhibition hall to update the flow of people in each exhibition area and recommend visiting routes in real time. Users can check the information on the display screen to understand the congestion situation of each exhibition area and adjust their visit plans accordingly; according to the intelligent guidance strategy, adjust the guidance signs in the exhibition hall, such as setting temporary arrow signs, changing the entrance signs of the exhibition area, etc., to guide users to divert reasonably; through multiple means such as the smart guide APP, push personalized tour routes to users. These routes will be customized according to the user's interest preferences and the current congestion situation of the exhibition hall to help users better plan their visit itineraries; set up a voice broadcast system at key locations in the exhibition hall. When the flow of people in a certain exhibition area reaches the preset threshold, the system automatically plays a guiding voice to remind users that the exhibition area is congested and recommends visiting other exhibition areas. In addition, channels such as the smart guide APP will also push crowd warning information in real time to ensure that users can obtain and respond in time.

[0108] The effects of the above technical solutions are as follows: through high-definition cameras and image recognition technology, the crowd density of each exhibition area is analyzed in real time, so that users can understand the degree of crowding in each exhibition area in a timely manner, so as to make more reasonable visiting decisions; the smart guide APP pushes personalized visiting routes according to user interests and current crowd conditions, reducing user waiting time and improving visiting efficiency and satisfaction; the LED display screen and voice broadcast system update the crowd conditions and provide guidance in real time, helping users avoid congested areas and enjoy a smoother visiting experience; according to the crowd density data and predicted trends, the exhibition area opening order is dynamically adjusted, temporary diversion channels are set, etc., effectively alleviating the congestion of the exhibition hall and improving the overall operating efficiency of the exhibition hall; through real-time monitoring and data analysis, the exhibition hall manager can allocate human and material resources more accurately to ensure the efficient operation of each exhibition area; when the crowd flow in a certain exhibition area reaches the threshold , automatically plays guidance voice to remind users to divert reasonably, effectively preventing safety accidents caused by overcrowding; in an emergency, the intelligent guidance system can quickly adjust strategies, provide guidance for personnel evacuation, and ensure the safety of people in the exhibition hall; by collecting and analyzing a large amount of crowd flow data, exhibition hall managers can deeply understand the behavior patterns and preferences of visitors, and provide data support for future exhibition planning and operation management; based on user visit behavior and preference data, the exhibition hall can carry out more precise marketing activities to improve the attractiveness and influence of the exhibition; the application of advanced technologies such as high-definition cameras, image recognition, and deep learning algorithms makes the exhibition hall full of technology and enhances users' interest in visiting; the combination of intelligent guide APP, LED display screen, voice broadcast system and other means provides users with a richer interactive experience and enhances the fun and participation of the exhibition. The above formula provides a quantitative indicator to measure the congestion level of the exhibition area, allowing managers to objectively understand and compare the congestion situation of different exhibition areas. By calculating the congestion index in real time, managers can respond quickly and take measures, such as adjusting the opening order, setting up temporary diversion channels, etc., to improve the visitor experience. The congestion index can help managers identify which exhibition areas require more resources (such as security, tour guides, etc.), so as to allocate resources more effectively. Combining historical data with real-time data, the congestion index can be used to predict future congestion trends and help managers plan exhibition layouts and tour routes in advance. By monitoring and controlling congestion, potential safety risks caused by overcrowding, such as stampedes, can be reduced. Using the congestion index, visitors can be provided with personalized tour routes and early warning information to improve the personalization level of services. The calculation of the congestion index relies on data analysis, which encourages data-based decision-making processes and increases the scientificity and effectiveness of decision-making. By guiding visitors to avoid congested areas, the overall visit experience can be improved, waiting time can be reduced, and visit satisfaction can be increased. Timely response to congestion can reduce potential losses caused by congestion, such as reducing additional operating costs caused by poor crowd management.Effective congestion management can improve the organization level and professional image of the exhibition, attract more visitors and enhance brand reputation.

[0109] In summary, the technical solution of the S4 stage not only improves the user experience and exhibition hall operation efficiency through intelligent crowd flow management and guidance, but also enhances safety and data-driven decision-making capabilities, while giving the exhibition hall a stronger sense of technology and interactivity. These benefits and effects jointly promote the sustainable development and competitiveness of the exhibition hall.

[0110] In one embodiment of the present invention, S5 includes:

[0111] S51. Integrate multi-source data (such as user behavior data, environmental data, and exhibit interaction data) through the data collection platform, and pre-process the integrated multi-source data, including cleaning, deduplication, and format unification;

[0112] S52. Based on big data analysis algorithms, conduct in-depth analysis of user behavior patterns, exhibit popularity, environmental change trends, etc., use machine learning algorithms to identify potential needs and market trends behind user behavior, and predict future visit trends and exhibit popularity;

[0113] S53. In combination with the exhibition hall operation objectives, evaluate the effectiveness of existing strategies and activities, put forward improvement suggestions, and provide scientific decision-making support for the exhibition hall management based on data analysis results; including exhibition layout adjustment, event planning, marketing strategy, etc.;

[0114] S54. Continue to optimize the control system and service process of the smart exhibition hall, introduce new technologies and equipment, improve user experience and exhibition hall operation efficiency; establish a feedback mechanism to collect feedback from users and management on the smart exhibition hall control system, and continuously iterate and optimize system functions and performance.

[0115] The working principle of the above technical solution is: through the data collection platform, multi-source data (such as user behavior data, environmental data, exhibit interaction data, etc.) from different channels and systems are integrated. These data may come from sensors, cameras, smart devices and user interaction systems in the exhibition hall; the integrated multi-source data is pre-processed by cleaning, deduplication and format unification. The cleaning process includes removing invalid, erroneous or duplicated data; deduplication ensures the uniqueness of the data; format unification converts the data into a unified format suitable for subsequent analysis and processing; based on big data analysis algorithms, in-depth analysis of user behavior patterns, exhibit popularity, environmental change trends, etc. These analyses help understand user behavior habits, preferences and the market performance of exhibits; machine learning algorithms are used to deeply mine the pre-processed data to identify the potential needs and market trends behind user behavior. Through training models, future visit trends and exhibit popularity can be predicted, providing forward-looking guidance for the operation and management of the exhibition hall; combined with the operation goals of the exhibition hall, existing strategies and activities are evaluated. By comparing the actual operation results with the expected goals, existing problems and deficiencies are identified; based on the data analysis results, scientific decision-making support is provided for the exhibition hall management. These suggestions may involve multiple aspects such as exhibit layout adjustment, event planning, and marketing strategies, aiming to optimize the operation effect of the exhibition hall and enhance the user experience; based on data analysis results and operational feedback, continuously optimize the control system and service process of the smart exhibition hall. This includes introducing new technologies and equipment to improve the intelligence level and operational efficiency of the system; at the same time, iteratively optimize the system functions and performance to ensure that the system is always in the best condition; establish a feedback mechanism for users and management on the control system of the smart exhibition hall. By collecting and analyzing the opinions and suggestions of users and management, timely discover and solve the problems and deficiencies in the system; at the same time, incorporate the feedback results into the subsequent optimization and improvement plan to form a closed-loop continuous optimization process.

[0116] In summary, the technical solution of the S5 stage has achieved comprehensive management and optimization of the smart exhibition hall through steps such as data integration and preprocessing, big data analysis and prediction, decision support and strategy optimization, and continuous optimization and feedback mechanism. This process not only improves the operational efficiency and user experience of the exhibition hall, but also provides strong data support and decision-making basis for the long-term development of the exhibition hall.

[0117] The effect of the above technical solution is: by integrating multi-source data and pre-processing, the accuracy and reliability of the data are ensured. Based on these data, using big data analysis algorithms and machine learning technology, it is possible to deeply analyze user behavior, the popularity of exhibits and environmental change trends, and provide accurate decision-making support for management; combined with the exhibition hall operation goals, evaluate the effectiveness of existing strategies and activities, and make improvement suggestions based on data analysis results. This scientific decision-making method helps management make more reasonable and effective decisions and improve the overall operation effect of the exhibition hall; by identifying the potential needs and market trends behind user behavior, it can provide users with more personalized services. For example, recommend exhibits or activities based on the user's interests and preferences to improve the user's visiting experience and satisfaction; in-depth analysis of environmental change trends helps to timely adjust the environmental settings in the exhibition hall, such as temperature, humidity, light, etc., to provide a more comfortable and pleasant visiting environment; based on the results of data analysis, the layout of exhibits, human resources, material resources, etc. can be optimized to ensure the efficient use of various resources in the exhibition hall; the effectiveness of event planning and marketing strategies can be evaluated in real time, and strategies can be adjusted in time to respond to market changes and increase the participation and influence of activities; new technologies and equipment can be continuously introduced to improve the intelligence level and operational efficiency of smart exhibition halls. For example, the automation and interactivity of exhibition halls can be improved by using technologies such as artificial intelligence and the Internet of Things; a feedback mechanism can be established to collect feedback from users and management, and the system functions and performance can be continuously optimized iteratively. This continuous improvement method helps to maintain the competitiveness and attractiveness of the exhibition hall; by predicting future visiting trends and exhibit popularity, market changes can be observed, and strategies can be arranged and adjusted in advance to respond to market challenges and opportunities; by providing high-quality visiting experience and services, the brand image and popularity of the exhibition hall can be improved, and market competitiveness can be enhanced.

[0118] In summary, the technical solutions in the S5 stage have brought significant benefits and effects to the operation and management of smart exhibition halls through data-driven decision support, improved user experience, improved operational efficiency, continuous innovation and optimization, and enhanced market competitiveness. These benefits and effects have jointly promoted the sustainable development and competitiveness of exhibition halls.

[0119] One embodiment of the present invention, as Figure 2 As shown, a smart exhibition hall control system based on the Internet of Everything, the system includes:

[0120] Architecture building module: Build a smart exhibition hall network architecture based on the Internet of Things, including identity recognition devices, environmental sensors, image acquisition devices, smart access control systems, exhibit interactive devices and other IoT devices, and connect them to the central control platform through wireless to form a network environment where everything is connected;

[0121] Information acquisition module: obtain user identity information through identity recognition devices (such as RFID tags, face recognition technology, etc.) and build a user identity database; analyze user preferences through intelligent algorithms based on user identity information and historical user behavior data; provide users with personalized exhibition route planning, exhibit recommendation and other services;

[0122] Real-time monitoring module: monitors the environmental parameters in the exhibition hall in real time, such as temperature, humidity, light intensity, etc., through environmental sensors (such as temperature and humidity sensors, light sensors, etc.); automatically adjusts air conditioning, lighting and other equipment according to preset environmental standards or user comfort requirements to maintain the comfort of the environment in the exhibition hall and the safety of exhibits;

[0123] Image acquisition module: collects information about the flow of people in the exhibition hall through image acquisition devices (such as high-definition cameras), and analyzes the density of people in each exhibition area in real time based on the population statistics model; generates guidance information intelligently based on the density of people; guides users to flow reasonably through display screens, voice broadcasts, etc. to avoid congestion;

[0124] Comprehensive analysis module: The central control platform conducts comprehensive analysis on various types of collected data, including user behavior data, environmental data, exhibit interaction data, etc.; through data mining and machine learning algorithms, it discovers valuable information such as potential market demand and user preferences, and provides decision-making support for the operation and management of the exhibition hall.

[0125] The working principle of the above technical solution is: by integrating multiple IoT devices such as identity recognition devices, environmental sensors, image acquisition devices, intelligent access control systems, and exhibit interactive devices into the smart exhibition hall, and wirelessly connecting them to the central control platform, a comprehensive network environment with interconnected everything is built. These devices each have different functions and jointly provide support for the intelligent management and user experience of the exhibition hall. When a user enters the exhibition hall, the identity recognition device (such as RFID tags, face recognition technology, etc.) will automatically capture the user's identity information and compare and record it with the user's identity database. The system uses the user's historical behavior data and intelligent algorithms to analyze the user's preferences, thereby providing personalized exhibition route planning, exhibit recommendation and other services. This can not only enhance the user's visiting experience, but also enhance the attractiveness of the exhibits and the interactivity of the exhibition. Environmental sensors (such as temperature and humidity sensors, light sensors, etc.) monitor the environmental parameters in the exhibition hall in real time to ensure that the temperature, humidity, light intensity, etc. are within an appropriate range. Once the environmental parameters deviate from the preset standards or user comfort requirements, the system will automatically trigger the adjustment mechanism, such as adjusting the air conditioning temperature, changing the lighting brightness, etc., to maintain the comfort of the environment in the exhibition hall and the safety of the exhibits. Image acquisition devices (such as high-definition cameras) capture the flow of people in the exhibition hall in real time, and analyze the density of people in each exhibition area through the population counting model. The system intelligently generates guidance information based on the flow density data, and conveys it to users through display screens, voice broadcasts, etc. This helps to guide users to flow rationally, avoid congestion, and improve the efficiency and safety of the exhibition hall. As the core of the entire system, the central control platform is responsible for collecting, integrating and processing data from various IoT devices, including user behavior data, environmental data, exhibit interaction data, etc. Through data mining and machine learning algorithms, the system can discover valuable information such as potential market demand and user preferences, and provide data support and decision-making basis for the operation and management of the exhibition hall. This helps to optimize the exhibition layout, improve service quality, enhance user experience, and provide strong support for future exhibition activities.

[0126] The effects of the above technical solutions are as follows: through identity recognition and user behavior analysis, the system can provide users with personalized exhibition route planning and exhibit recommendations to meet the different interests and needs of users, thereby enhancing the user's visiting experience; environmental sensors monitor and automatically adjust the temperature, humidity and light intensity in the exhibition hall in real time to ensure that users are always in a comfortable environment and improve user satisfaction; image acquisition devices and crowd counting models help the system analyze crowd density in real time, and avoid congestion through intelligent guidance information, so that users can visit the exhibition more smoothly; the central control platform conducts comprehensive analysis of various data, so that exhibition hall managers can understand the operation status of the exhibition hall in real time, so as to make more accurate and efficient management decisions; based on crowd density data, the system can intelligently adjust the resource allocation of each exhibition area, such as adding tour guides, adding interactive devices, etc., to cope with the crowd pressure in different exhibition areas; automatic adjustment of air conditioning, lighting and other equipment can It can effectively reduce energy consumption and save operating costs while ensuring environmental comfort; environmental sensors monitor the environmental parameters in the exhibition hall in real time to ensure that the exhibits are in a suitable environment and avoid damage to the exhibits due to factors such as changes in temperature and humidity or excessive light; the density of human traffic is controlled through intelligent guidance information to reduce the risk of exhibits being excessively touched or damaged, and extend the display life of exhibits; the central control platform uses data mining technology to extract valuable information from massive data, such as user preferences and market demand, to provide data support for the future development of the exhibition hall; combined with machine learning algorithms, the system can predict future user behavior and market trends, and provide a more scientific decision-making basis for the operation and management of the exhibition hall; the smart exhibition hall enhances users' awareness and favorability of the exhibition hall and the brands it displays by providing a novel and convenient visiting experience; the smart exhibition hall itself is a high-tech display method that can reflect the brand's technical strength and innovation capabilities and enhance the brand image.

[0127] In one embodiment of the present invention, the architecture building module includes:

[0128] Research advanced IoT devices on the market, including high-precision RFID tags, multi-modal face recognition terminals, ultra-low power environmental sensors (supporting multi-parameter monitoring such as temperature, humidity, and CO2 concentration), high-definition smart cameras (supporting night infrared, face tracking and other functions), smart access control systems, and interactive exhibit devices (such as AR augmented reality glasses and touch screen interactive screens).

[0129] Deployment design module: Design the best deployment plan for IoT devices based on the exhibition hall layout and needs, integrate various IoT devices into a unified communication protocol (such as MQTT or CoAP); and build a layered network architecture; including the perception layer (IoT devices), network layer (wireless LAN, Zigbee, LoRa, etc.), platform layer (central control platform) and application layer (user interaction interface, data analysis system).

[0130] Facility deployment module: Deploy wireless network infrastructure, including high-performance Wi-Fi APs, IoT gateways, etc., to ensure that IoT devices in the exhibition hall can stably access the network, implement network security measures, such as data encryption transmission, access control list (ACL) settings, to ensure data transmission security and privacy protection. And conduct equipment joint debugging tests to ensure that all IoT devices can correctly access the central control platform and stably transmit data;

[0131] Test simulation module: simulates data transmission stress tests in different scenarios, evaluates system stability and response speed, and adjusts network configuration and device parameters based on test results to optimize system performance and improve user experience.

[0132] The working principle of the above technical solution is as follows: First, through market research, understand the advanced IoT devices on the current market, including high-precision RFID tags, multi-modal face recognition terminals, ultra-low power multi-parameter environmental sensors, high-definition smart cameras (with night infrared, face tracking and other functions), smart access control systems and various exhibit interactive devices (such as AR augmented reality glasses, touch screen interactive screens); select the most suitable IoT devices according to the specific layout and needs of the exhibition hall; design the best deployment plan for IoT devices to ensure that the equipment can fully cover the exhibition hall, while considering the collaborative work and data interaction between devices; integrate all IoT devices into a unified communication protocol (such as MQTT or CoAP) to achieve seamless communication and data exchange between devices; build a layered network architecture, including the perception layer (IoT devices), network layer (wireless LAN, Zigbee, LoRa and other communication technologies), platform layer (central control platform, responsible for data processing and decision-making), and application layer (user interaction interface, data analysis system, etc.); deploy high-performance Wi-Fi APs and IoT gateways in the exhibition hall to ensure that IoT devices can stably access the network; The system is equipped with a wireless network that is capable of performing network planning and configuration, optimizing the coverage and signal strength of the wireless network, and reducing interference and blind spots. Encryption technology is used to ensure the security of data transmission and prevent data from being stolen or tampered with. Access control lists are set to restrict illegal devices from accessing the network and ensure the purity and security of the network environment. Equipment joint debugging tests are carried out to ensure that all IoT devices can correctly access the central control platform and achieve stable data transmission. Problems in the device access and communication process are discovered and resolved in a timely manner to ensure the stability and reliability of the system. Data transmission pressures in different scenarios are simulated, such as high traffic density and intensive use of equipment, to evaluate the stability and response speed of the system. Data during the test process, including key indicators such as transmission delay and packet loss rate, are collected for analysis and evaluation. Network configuration is adjusted according to the test results, such as increasing the number of APs and optimizing channel allocation, to improve network performance. Parameter settings of IoT devices, such as sampling frequency and transmission power, are adjusted to balance data transmission quality and equipment energy consumption. System architecture is optimized according to the test results to improve the overall performance and stability of the system. The user experience in the exhibition hall is enhanced by optimizing data transmission and reducing delays.

[0133] The effects of the above technical solutions are as follows: by investigating advanced IoT devices on the market, the technological leadership and functional richness of the equipment used in the exhibition hall are ensured; various IoT devices are integrated into a unified communication protocol (such as MQTT or CoAP), which improves the interoperability and data exchange efficiency between devices and reduces the difficulty of subsequent maintenance and upgrades; the constructed layered network architecture (perception layer, network layer, platform layer, application layer) makes the system structure clear, easy to manage and expand; the optimal deployment plan designed according to the layout and needs of the exhibition hall ensures that the IoT devices can play their full role and facilitates subsequent adjustments and upgrades; the deployed high-performance Wi-Fi AP and IoT gateway ensure the stable access of IoT devices in the exhibition hall and reduce the risk of network failures and interruptions; the implemented security measures such as data encryption transmission and access control list (ACL) settings effectively ensure the security of data transmission and the protection of user privacy, and enhance users' trust in the exhibition hall; by simulating data transmission stress tests in different scenarios, the system stability and response speed are comprehensively evaluated, providing a strong basis for system optimization; the network configuration and equipment parameters are adjusted according to the test results to optimize the system performance and improve the user experience. This includes reducing data transmission delays, improving system response speed, etc., so that users can enjoy smoother and more convenient services during their visit; based on the intelligent recognition and analysis capabilities of IoT devices, the system can provide users with personalized exhibition route planning, exhibit recommendations and other services, improving the user's visiting experience; through real-time monitoring and automatic adjustment of environmental sensors, the system can maintain the comfort of the environment in the exhibition hall and the safety of the exhibits, creating a more pleasant visiting environment for users; the system can collect user behavior data, environmental data, exhibit interaction data, etc. in real time, providing rich data support for the operation and management of the exhibition hall; through data mining and machine learning algorithms, the system can discover valuable information such as potential market demand and user preferences, providing scientific decision-making basis for the operation and management of the exhibition hall, and improving management efficiency and decision-making level.

[0134] In summary, the technical solution of the S1 stage not only improves the advancement and compatibility of equipment in the process of building the network architecture of the smart exhibition hall based on the Internet of Things, but also enhances the flexibility and scalability of the network architecture, ensuring the stability and security of the network. At the same time, through system performance optimization and user experience improvement, it provides strong support for the operation and management of the exhibition hall, and promotes the development of the exhibition hall towards intelligence and efficiency.

[0135] In one embodiment of the present invention, the information acquisition module includes:

[0136] Identity recognition module: Deploy RFID readers or face recognition cameras at the entrance of the exhibition hall to automatically capture user identity information, compare and verify the collected identity information with the user database, and quickly identify the user's identity;

[0137] Data collection module: collects user historical behavior data, such as visit records, exhibit interaction, etc., and builds user portraits. Through intelligent algorithms (such as collaborative filtering and deep learning), it deeply mines user preferences and predicts the types of exhibits that users may be interested in.

[0138] Recommendation module: Based on the analysis results, personalized exhibition routes and exhibit recommendation lists are tailored for users; personalized exhibition information and interactive prompts are pushed to users through multiple channels, including display screens in the exhibition hall, mobile phone apps or AR glasses.

[0139] The working principle of the above technical solution is as follows: RFID readers or multimodal face recognition cameras are deployed at the entrance of the exhibition hall. These devices can automatically capture the identity information of users entering the exhibition hall; when users pass through the entrance, the RFID reader will read the identity information in the RFID tag (such as membership card, ticket, etc.) carried by the user, or the face recognition camera will capture the user's facial features, and compare and verify this information with the data pre-stored in the user database; through efficient algorithms and database query technology, the system can quickly identify the user's identity and provide a basis for subsequent personalized services; the system continuously collects the user's historical behavior data in the exhibition hall, including but not limited to visit records (such as visit time, stay time, visit path, etc.), exhibit interaction (such as which exhibits have been interacted with, interaction methods, interaction duration, etc.); based on the collected data, the system uses big data and artificial intelligence technology to build a personalized portrait of the user. This includes multiple dimensions such as the user's age, gender, interest preferences, and behavior patterns; through intelligent algorithms (such as collaborative filtering, deep learning, etc.), the system conducts in-depth mining of user preferences. Collaborative filtering algorithms can predict the interests of current users based on the behaviors of similar users; while deep learning algorithms can more deeply understand the complex patterns behind user behaviors, thereby more accurately predicting the user's points of interest; based on the results of user portraits and preference analysis, the system tailors personalized exhibition routes and exhibit recommendation lists for users. These routes and lists are designed to meet the specific interests and needs of users and improve their visiting experience and satisfaction; the system pushes personalized exhibition information and interactive prompts to users through multiple channels, including display screens in the exhibition hall (such as electronic guide screens), mobile phone apps (users can view exhibition information, make appointments for exhibit interaction, etc.) or AR glasses (users can get a more immersive exhibition experience through AR glasses); when recommending exhibits, the system will also consider the interactivity and fun of the exhibits, encouraging users to interact with the exhibits to further deepen their understanding and memory of the exhibits.

[0140] The effects of the above technical solutions are as follows: through RFID readers or face recognition cameras, users can quickly complete identity authentication and enter the exhibition hall without waiting, which greatly saves time and improves the user's initial experience; based on the user's preferences and historical behavior data, the system tailors personalized exhibition routes so that users can go directly to the exhibition area they are most interested in, improving the pertinence and efficiency of the visit; the system predicts the types of exhibits that users may be interested in through intelligent algorithms, and pushes relevant exhibit information to help users discover more exhibits of interest, enriching the user's visiting experience; personalized exhibition information and interactive prompts are pushed to users through multiple channels such as display screens in the exhibition hall, mobile phone APPs or AR glasses, increasing the user's interaction opportunities with the exhibition content and improving the user's sense of participation and immersion; the system adjusts the exhibit display method or increases interactive links based on the user's interaction, so that users can The system can help users gain a deeper understanding of the exhibits, thus enhancing the interactivity and fun of the exhibitions. Through personalized exhibition routes and exhibit recommendations, the system can accurately push exhibition information to target user groups, thus increasing the exposure and appeal of the exhibitions. By collecting user behavior data and building user portraits, the system provides valuable data support for exhibition organizers, helping them understand user needs, evaluate exhibition effects, and continuously optimize exhibition content and services. Personalized exhibition experience can enhance user satisfaction and loyalty, prompting users to share exhibition information through channels such as social media, further expanding the influence and popularity of the exhibition. The system can intelligently dispatch staff and exhibit resources based on information such as user traffic and exhibit popularity, ensuring order at the exhibition site and safety of exhibits. Through data analysis, the system can promptly identify problems in operations and make suggestions for improvement, thus helping exhibition organizers achieve efficient operations and refined management.

[0141] In summary, the technical solution of the S2 stage not only improves the user experience and satisfaction in the exhibition hall through user identity recognition, historical behavior data analysis, personalized exhibition routes and exhibit recommendations, but also enhances user interaction and participation, improves the exhibition effect and influence, and optimizes resource allocation and management. These benefits and effects jointly promote the intelligent and personalized development of the exhibition industry.

[0142] In one embodiment of the present invention, the real-time monitoring module includes:

[0143] Data upload module: Deploy environmental monitoring equipment (such as temperature and humidity sensors and light sensors) in the exhibition hall to collect environmental parameter data in real time and upload it to the central control platform;

[0144] User feedback module: formulate intelligent control strategies based on preset environmental standards (such as suitable temperature and humidity range, light intensity threshold) or user comfort feedback; dynamically adjust control strategies based on historical data and real-time environmental changes through machine learning algorithms; improve control accuracy and efficiency;

[0145] Command control module: The central control platform automatically sends control commands to relevant equipment (including air conditioning and lighting equipment) according to the control strategy. The relevant equipment executes the control commands and adjusts the environmental parameters in the exhibition hall to the preset standards or user comfort requirements.

[0146] The working principle of the above technical solution is as follows: deploy environmental monitoring equipment such as temperature and humidity sensors and light sensors in different areas of the exhibition hall. These devices can sense and collect environmental parameter data in the exhibition hall in real time; the collected environmental parameter data are uploaded to the central control platform in real time through wireless networks or other communication methods. As the core of data processing and decision-making, the central control platform is responsible for receiving, storing and analyzing these data; according to the operation needs of the exhibition hall and the protection requirements of exhibits, the appropriate environmental standards such as temperature and humidity range and light intensity threshold are preset; at the same time, the system will also consider the user's comfort feedback, and obtain the user's subjective evaluation of environmental comfort through questionnaires, user behavior analysis and other methods; combined with the preset environmental standards, user comfort feedback, historical data and real-time environmental changes, the system uses machine learning algorithms to dynamically adjust the control strategy. The machine learning algorithm can identify the laws of environmental changes, predict future environmental trends, and optimize the control strategy accordingly to improve the accuracy and efficiency of control; the central control platform automatically sends control instructions to related equipment (such as air conditioners, lighting equipment, etc.) according to the formulated control strategy. These control instructions include specific control targets (such as lowering the temperature, adjusting the light intensity, etc.) and parameters (such as target temperature value, light intensity value, etc.); after receiving the control instructions, the relevant equipment will perform the corresponding control operations. For example, the air-conditioning equipment will adjust the cooling or heating mode according to the control instructions to adjust the temperature in the exhibition hall; the lighting equipment will adjust the light intensity and color temperature according to the control instructions to improve the lighting environment in the exhibition hall; through the execution of the equipment, the environmental parameters in the exhibition hall are gradually adjusted to the preset standards or user comfort requirements. At the same time, the system will continue to monitor the changes in environmental parameters, and adjust the control strategy and equipment control instructions as needed to ensure the stability and comfort of the environmental parameters in the exhibition hall.

[0147] The effects of the above technical solutions are as follows: by real-time monitoring of the environmental parameters in the exhibition hall and formulating control strategies based on preset standards and user comfort feedback, the system can accurately adjust environmental parameters such as temperature, humidity and light in the exhibition hall to ensure that the environment is always kept in the most suitable state and improve the user's visit comfort; using machine learning algorithms, the system can dynamically adjust the control strategy based on historical data and real-time environmental changes, further improve the accuracy and efficiency of control, and ensure the stability and comfort of environmental parameters; suitable temperature, humidity and light conditions are crucial for the protection of exhibits. Through intelligent control, the system can ensure that the environmental parameters in the exhibition hall are always kept within the appropriate range required by the exhibits, effectively extend the shelf life of the exhibits, and reduce the risk of damage caused by environmental factors; real-time monitoring of environmental parameters can also timely discover potential environmental problems, such as abnormal temperature and humidity, excessive light, etc., so as to take corresponding measures to prevent and deal with them and avoid damage to the exhibits; the system can intelligently control the operation of related equipment according to the actual environmental needs and personnel flow in the exhibition hall to avoid unnecessary energy waste. For example, when there are fewer people in the exhibition hall, the lighting brightness and air conditioning power are automatically reduced to achieve energy conservation and emission reduction; through precise control and dynamic adjustment strategies, the system can optimize resource utilization efficiency and reduce operating costs; the entire environmental control process is managed automatically, reducing manual intervention and operating costs. Staff can focus more on other important tasks and improve overall operational efficiency; the central control platform can monitor the environmental parameters and equipment operating status in the exhibition hall in real time, detect and handle abnormal situations in a timely manner, and ensure the normal operation of the exhibition hall; the system can dynamically adjust environmental parameters based on user comfort feedback to provide a more personalized service experience. Users can adjust the environmental settings in the exhibition hall according to their needs and preferences to improve the satisfaction and comfort of the visit; the intelligent environmental control system can also enhance the sense of technology and modernity of the exhibition hall, attracting more users' attention and participation.

[0148] In summary, the technical solution of the S3 stage not only improves the comfort of the exhibition hall environment and the safety of exhibits through intelligent environmental monitoring and control, but also achieves multiple effects such as energy conservation and emission reduction and improved operational efficiency. These benefits and effects jointly promote the sustainable development of the exhibition hall and the improvement of user experience.

[0149] In one embodiment of the present invention, the image acquisition module includes:

[0150] Crowd analysis module: Use high-definition cameras to capture the flow of people in the exhibition hall, use image recognition technology to extract crowd information, build a headcount model, and combine deep learning algorithms to analyze the density of people in each exhibition area in real time.

[0151] Situation Assessment Module: Based on crowd density data, evaluate the congestion situation of each exhibition area, predict future crowd flow trends, and formulate intelligent guidance strategies; including dynamically adjusting the opening order of exhibition areas, setting up temporary diversion channels, activating guidance signs for specific exhibition areas, etc.;

[0152] User guidance module: using the LED display screen in the exhibition hall to update the flow of people in each exhibition area and recommend visiting routes in real time, guiding users to avoid congested areas;

[0153] User reminder module: through multiple means (such as smart guide APP), personalized tour routes and real-time crowd warning information are pushed to users. A voice broadcast system is set up at key locations in the exhibition hall. When the flow of people in a certain exhibition area reaches the threshold, a guiding voice is automatically played to remind users to divert traffic reasonably.

[0154] The working principle of the above technical solution is as follows: high-definition cameras are arranged in the exhibition hall to capture the flow of people in the exhibition hall in real time; advanced image recognition technology is used to extract flow information such as the number of people and moving direction from the captured images; based on the extracted flow information, a population statistics model is constructed to conduct real-time analysis of the density of people in each exhibition area in the exhibition hall; combined with deep learning algorithms, the accuracy and real-time analysis of the density of people flow is improved to provide data support for subsequent congestion assessment and guidance strategy formulation; based on the density of people flow data, the congestion situation of each exhibition area is evaluated in real time to identify possible congestion areas; using historical data and real-time flow information, the flow of people in the future is predicted through prediction algorithms to provide a basis for formulating more accurate and effective guidance strategies; based on the results of congestion assessment and flow trend prediction, intelligent guidance strategies are formulated. These strategies may include dynamically adjusting the order of opening exhibition areas, setting temporary diversion channels, activating guidance signs in specific exhibition areas, etc., to effectively alleviate congestion and improve user experience; using the LED display screen in the exhibition hall to update the flow of people in each exhibition area and recommend visiting routes in real time. Users can check the information on the display screen to understand the congestion situation of each exhibition area and adjust their visit plans accordingly; according to the intelligent guidance strategy, adjust the guidance signs in the exhibition hall, such as setting temporary arrow signs, changing the entrance signs of the exhibition area, etc., to guide users to divert reasonably; through multiple means such as the smart guide APP, push personalized tour routes to users. These routes will be customized according to the user's interest preferences and the current congestion situation of the exhibition hall to help users better plan their visit itineraries; set up a voice broadcast system at key locations in the exhibition hall. When the flow of people in a certain exhibition area reaches the preset threshold, the system automatically plays a guiding voice to remind users that the exhibition area is congested and recommends visiting other exhibition areas. In addition, channels such as the smart guide APP will also push crowd warning information in real time to ensure that users can obtain and respond in time.

[0155] The effects of the above technical solutions are as follows: through high-definition cameras and image recognition technology, the crowd density of each exhibition area is analyzed in real time, so that users can understand the degree of crowding in each exhibition area in a timely manner, so as to make more reasonable visiting decisions; the smart guide APP pushes personalized visiting routes according to user interests and current crowd conditions, reducing user waiting time and improving visiting efficiency and satisfaction; the LED display screen and voice broadcast system update the crowd conditions and provide guidance in real time, helping users avoid congested areas and enjoy a smoother visiting experience; according to the crowd density data and predicted trends, the exhibition area opening order is dynamically adjusted, temporary diversion channels are set, etc., effectively alleviating the congestion of the exhibition hall and improving the overall operating efficiency of the exhibition hall; through real-time monitoring and data analysis, the exhibition hall manager can allocate human and material resources more accurately to ensure the efficient operation of each exhibition area; when the crowd flow in a certain exhibition area reaches the threshold , automatically plays guidance voice to remind users to divert reasonably, and effectively prevent safety accidents caused by excessive crowds; in an emergency, the intelligent guidance system can quickly adjust strategies, provide guidance for personnel evacuation, and ensure the safety of people in the exhibition hall; by collecting and analyzing a large amount of crowd flow data, exhibition hall managers can have an in-depth understanding of visitors' behavior patterns and preferences, and provide data support for future exhibition planning and operation management; based on user visiting behavior and preference data, exhibition halls can carry out more precise marketing activities to improve the attractiveness and influence of exhibitions; the application of advanced technologies such as high-definition cameras, image recognition, and deep learning algorithms makes the exhibition hall full of technology and enhances users' interest in visiting; the combined use of smart guide APP, LED display screens, voice broadcast systems and other means provides users with a richer interactive experience and enhances the fun and sense of participation in the exhibition.

[0156] In summary, the technical solution of the S4 stage not only improves the user experience and exhibition hall operation efficiency through intelligent crowd flow management and guidance, but also enhances safety and data-driven decision-making capabilities, while giving the exhibition hall a stronger sense of technology and interactivity. These benefits and effects jointly promote the sustainable development and competitiveness of the exhibition hall.

[0157] Obviously, those skilled in the art can make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if these modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalents, the present invention is also intended to include these modifications and variations.

Claims

1. A smart exhibition hall control method based on the Internet of Everything, characterized in that: The method comprises: S1. Build a smart exhibition hall network architecture based on the Internet of Things, and connect it to the central control platform through wireless to form a network environment where everything is connected; S2. Obtain user identity information through an identity recognition device and build a user identity database; analyze user preferences through an intelligent algorithm based on the user identity information and combined with the user's historical behavior data; S3. Use environmental sensors to monitor the environmental parameters in the exhibition hall in real time and adjust the equipment according to the preset environmental standards or user comfort requirements; S4. Collect crowd flow information in the exhibition hall through the image acquisition device, and analyze the crowd density of each exhibition area in real time based on the crowd counting model; intelligently generate guidance information based on the crowd density data; S5. The central control platform conducts comprehensive analysis on various types of collected data and provides decision support for the operation and management of the exhibition hall through data mining and machine learning algorithms.

2. The intelligent exhibition hall control method based on the Internet of Everything according to claim 1 is characterized in that: Said S1 comprises: S11. Design the deployment plan of IoT devices according to the layout and needs of the exhibition hall, integrate various IoT devices into a unified communication protocol, and build a layered network architecture; S12. Deploy wireless network infrastructure, implement network security measures, and conduct equipment joint debugging and testing; S13. Simulate data transmission stress tests in different scenarios, evaluate system stability and response speed, and adjust network configuration and equipment parameters based on test results.

3. The intelligent exhibition hall control method based on the Internet of Everything according to claim 1 is characterized in that: The S2 comprises: S21. Deploy RFID readers or face recognition cameras at the entrance of the exhibition hall to automatically capture user identity information, compare and verify the collected identity information with the user database, and identify the user's identity; S22. Collect user historical behavior data and build user portraits. Use intelligent algorithms to deeply mine user preferences and predict the types of exhibits that users may be interested in. S23. Based on the analysis results, a personalized exhibition route and exhibit recommendation list are tailored for the user; personalized exhibition information and interactive prompts are pushed to the user through multiple channels.

4. The intelligent exhibition hall control method based on the Internet of Everything according to claim 1 is characterized in that: The S3 includes: S31. Deploy environmental monitoring equipment in the exhibition hall to collect environmental parameter data in real time and upload it to the central control platform; S32. Formulate intelligent control strategies based on preset environmental standards or user comfort feedback; dynamically adjust control strategies based on historical data and real-time environmental changes through machine learning algorithms; S33. The central control platform automatically sends control instructions to relevant equipment based on the control strategy. The relevant equipment executes the control instructions and adjusts the environmental parameters in the exhibition hall to the preset standards or user comfort requirements.

5. The intelligent exhibition hall control method based on the Internet of Everything according to claim 1 is characterized in that: The S4 comprises: S41. Use high-definition cameras to capture the flow of people in the exhibition hall, use image recognition technology to extract flow information, build a population statistics model, and combine deep learning algorithms to analyze the density of people in each exhibition area in real time. S42. Evaluate the congestion situation of each exhibition area based on crowd density data, predict future crowd flow trends, and formulate intelligent guidance strategies; S43. Use the LED display screens in the exhibition hall to update the flow of people in each exhibition area and recommend visiting routes in real time, and guide users to avoid congested areas; S44. Through multiple means, personalized tour routes and real-time crowd flow warning information are pushed to users. A voice broadcast system is set up at key locations in the exhibition hall. When the flow of people in a certain exhibition area reaches a threshold, a guiding voice is automatically played to remind users to divert traffic reasonably.

6. An intelligent exhibition hall control system based on the Internet of Everything, characterized in that: The system comprises: Architecture building module: Build a smart exhibition hall network architecture based on the Internet of Things, and connect it to the central control platform through wireless to form a network environment where everything is connected; Information acquisition module: obtains user identity information through the identity recognition device and builds a user identity database; analyzes user preferences through intelligent algorithms based on user identity information and historical user behavior data; Real-time monitoring module: real-time monitoring of environmental parameters in the exhibition hall through environmental sensors, based on preset environmental standards or user comfort requirements; Image acquisition module: collects information about the flow of people in the exhibition hall through image acquisition devices, and analyzes the density of people in each exhibition area in real time based on the population statistics model; intelligently generates guidance information based on the density of people; Comprehensive analysis module: The central control platform conducts comprehensive analysis on various types of collected data and provides decision support for the operation and management of the exhibition hall through data mining and machine learning algorithms.

7. The intelligent exhibition hall control system based on the Internet of Everything according to claim 6 is characterized in that: The architecture building blocks include: Deployment design module: Design deployment plans for IoT devices based on exhibition hall layout and requirements, integrate various IoT devices into a unified communication protocol, and build a hierarchical network architecture; Facility deployment module: deploy wireless network infrastructure, implement network security measures, and conduct equipment joint debugging tests; Test simulation module: simulates data transmission stress tests in different scenarios, evaluates system stability and response speed, and adjusts network configuration and equipment parameters based on test results.

8. The intelligent exhibition hall control system based on the Internet of Everything according to claim 6 is characterized in that: The information acquisition module comprises: Identity recognition module: Deploy RFID readers or face recognition cameras at the entrance of the exhibition hall to automatically capture user identity information, compare and verify the collected identity information with the user database, and identify the user's identity; Data collection module: collects user historical behavior data and builds user portraits. It uses intelligent algorithms to deeply mine user preferences and predict the types of exhibits that users may be interested in. Recommendation module: Based on the analysis results, tailor personalized exhibition routes and exhibit recommendation lists for users; push personalized exhibition information and interactive prompts to users through multiple channels.

9. The intelligent exhibition hall control system based on the Internet of Everything according to claim 6 is characterized in that: The real-time monitoring module comprises: Data upload module: deploy environmental monitoring equipment in the exhibition hall to collect environmental parameter data in real time and upload it to the central control platform; User feedback module: formulate intelligent control strategies based on preset environmental standards or user comfort feedback; dynamically adjust control strategies based on historical data and real-time environmental changes through machine learning algorithms; Command control module: The central control platform automatically sends control commands to relevant equipment based on the control strategy. The relevant equipment executes the control commands and adjusts the environmental parameters in the exhibition hall to the preset standards or user comfort requirements.

10. The intelligent exhibition hall control system based on the Internet of Everything according to claim 6 is characterized in that: The image acquisition module comprises: Crowd analysis module: Use high-definition cameras to capture the flow of people in the exhibition hall, use image recognition technology to extract crowd information, build a headcount model, and combine deep learning algorithms to analyze the density of people in each exhibition area in real time. Situation assessment module: Based on crowd density data, evaluate the congestion situation in each exhibition area, predict future crowd flow trends, and formulate intelligent guidance strategies; User guidance module: using the LED display screen in the exhibition hall to update the flow of people in each exhibition area and recommend visiting routes in real time, guiding users to avoid congested areas; User reminder module: through multiple means, personalized tour routes and real-time crowd warning information are pushed to users. Voice broadcast systems are set up at key locations in the exhibition hall. When the flow of people in a certain exhibition area reaches the threshold, guiding voices are automatically played to remind users to divert traffic reasonably.

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