Smart classroom multimedia management platform based on centralized management and control of Internet of Things

Abstract

The invention relates to the technical field of smart classrooms, and discloses a smart classroom multimedia management platform for centralized management and control by using the Internet of Things, which comprises an equipment management module and a resource management module, comprising a hardware access unit, a software system unit, a user interaction unit and an authority management unit, the intelligent fault early warning and maintenance submodule comprises a sensor deployment unit, a data transmission unit, a fault model construction unit, an early warning execution unit and a maintenance management unit; and the resource sharing platform sub-module comprises a resource integration unit, a platform development unit, a classification retrieval unit and an auditing evaluation unit. According to the invention, stable and efficient data interaction between the multimedia equipment and the platform is realized, different equipment can be connected with the gateway through adaptive communication modules, a plurality of protocol conversion functions can adapt to communication protocol differences of various equipment, and a foundation is laid for stable operation of the whole smart classroom multimedia management platform.

Description

Technical Field

[0001] The present invention relates to the technical field of smart classrooms, and specifically to a smart classroom multimedia management platform using Internet of Things centralized control. Background Art

[0002] In the traditional way, the connection between multimedia devices and the management platform often lacks standardization and compatibility. Devices such as projectors, audio systems, and electronic whiteboards produced by different manufacturers adopt different communication protocols and interface standards. For example, some old projectors may only support the traditional VGA interface and the communication protocol does not support wireless connection, which leads to the need for additional adapter devices when integrating with the management platform, not only increasing costs but also possibly resulting in unstable signal transmission. Summary of the Invention

[0003] In view of the deficiencies of the prior art, the present invention provides a smart classroom multimedia management platform using Internet of Things centralized control, which solves the problem of the need for additional adapter devices, not only increasing costs but also possibly resulting in unstable signal transmission.

[0004] To achieve the above objectives, the present invention is realized through the following technical solutions: A smart classroom multimedia management platform using Internet of Things centralized control, including a device management module and a resource management module:

[0005] The device management module includes:

[0006] The centralized control platform sub-module, including a hardware access unit, a software system unit, a user interaction unit, and a permission management unit, is respectively used to realize multimedia device access and communication, data collection and processing, cross-terminal interactive interface development, and multi-role permission control;

[0007] The intelligent fault warning and maintenance sub-module, including a sensor deployment unit, a data transmission unit, a fault model construction unit, a warning execution unit, and a maintenance management unit, is used for device status monitoring, fault prediction, and maintenance scheduling;

[0008] The resource management module includes:

[0009] The resource sharing platform sub-module, including a resource integration unit, a platform development unit, a classification and retrieval unit, and an audit and evaluation unit, is used for teaching resource collection, storage, retrieval, and quality control;

[0010] The resource intelligent update and push sub-module, including a data collection and analysis unit, a resource update unit, and an intelligent push unit, is used for dynamic update and personalized recommendation of teaching resources.

[0011] Preferably, the hardware access unit includes:

[0012] The local gateway is configured with a multi-core processor, ECC memory, and high-speed storage media, and can perform various industrial protocol conversions;

[0013] The protocol adaptation unit is used for heterogeneous protocol conversions of different types of multimedia devices;

[0014] The redundancy design unit uses dual power modules and triple network port hot backup to ensure communication stability.

[0015] Preferably, the data acquisition layer of the software system unit adopts a hybrid programming architecture, obtains device data through the bus protocol, uses multi-threading and asynchronous I / O technologies to achieve efficient acquisition, combines a verification mechanism to ensure data integrity, and uses distributed caching and message queues to achieve asynchronous data upload.

[0016] Preferably, the user interaction unit includes:

[0017] The responsive interface development framework is used for multi-terminal adaptive display;

[0018] The multi-modal interaction unit is used for gesture recognition and voice control;

[0019] The personalized setting module is used for interface theme switching and operation guidance functions.

[0020] Preferably, the permission management unit includes:

[0021] The role division module is used to define the hierarchical permissions of teachers, teaching management personnel, and system administrators;

[0022] The authentication and authorization module adopts multi-factor authentication combined with dynamic token management;

[0023] The access control module realizes fine-grained permission allocation through a composite permission model.

[0024] Preferably, the intelligent fault warning and maintenance sub-module includes:

[0025] The multi-type sensor array is deployed at key parts of the device to monitor temperature, vibration, and current parameters;

[0026] The data preprocessing unit uses filtering algorithms and compression encryption technologies to process sensor data;

[0027] The intelligent diagnosis unit uses feature extraction algorithms and deep learning models for fault prediction.

[0028] Preferably, the resource sharing platform sub-module includes:

[0029] The distributed resource acquisition unit uses web crawler technology combined with intelligent annotation to achieve resource integration;

[0030] Multi-dimensional retrieval unit for semantic retrieval and deep learning classification;

[0031] Quality control unit for establishing a multi-level review process and user evaluation system.

[0032] Preferably, the resource intelligent update and push sub-module includes:

[0033] Dynamic monitoring unit for real-time tracking of teaching content and policy changes;

[0034] Version control unit for managing resource versions in a distributed storage system;

[0035] Personalized recommendation unit for accurate push based on user portraits and hybrid recommendation algorithms.

[0036] The present invention provides a smart classroom multimedia management platform using Internet of Things centralized control. It has the following beneficial effects:

[0037] 1. By equipping multimedia devices with specific communication modules and using an industrial-grade gateway with powerful data processing, storage capabilities, and various functions, the present invention realizes stable and efficient data interaction between multimedia devices and the platform. Different devices can be connected to the gateway through adapted communication modules, and multiple protocol conversion functions can adapt to the communication protocol differences of various devices. The redundant power supply and network port backup design ensure that data interaction can still proceed uninterruptedly when the power supply or network fails, laying a foundation for the stable operation of the entire smart classroom multimedia management platform.

[0038] 2. The data acquisition layer of the software system unit of the present invention uses a mixed programming of Java and C++, combined with multi-threading, asynchronous I / O technology, and a verification mechanism, to comprehensively and accurately collect key information such as the operating status of multimedia devices, and efficiently upload it to the cloud through distributed caching and message queues. The data processing layer is based on a big data platform and uses various algorithms to deeply analyze the collected data. It can not only accurately classify device status, mine parameter relationships, but also effectively analyze images and time series, thus providing strong data support for device management and fault warning.

[0039] 3. In the present invention, the user interaction unit uses a responsive interface developed with various technologies, which can adapt to a variety of terminal devices and meet the usage needs of users in different scenarios; multi-language support improves the versatility of the platform and facilitates the operation of users with different language backgrounds; the theme switching and personalized interface setting functions, as well as the integrated gesture recognition and voice control functions, not only conform to the personalized operation habits of users, but also greatly improve the operation convenience; the operation prompt and guidance function reduces the learning cost of users and comprehensively improves the user experience.

[0040] 4. In the present invention, the permission management unit ensures the security and standardization of platform operations by clearly defining roles such as teachers, teaching administrators, and system administrators, assigning detailed and different levels of permissions to each role, and adopting multi-factor authentication combined with relevant protocols, as well as JWT tokens and multiple permission management models. Different roles operate within their respective permission scopes, which not only guarantees the normal development of teaching activities but also effectively manages platform resources and user information, preventing illegal operations and data leakage. BRIEF DESCRIPTION OF THE DRAWINGS

[0041] Figure 1 It is the architecture diagram of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0042] Next, the technical solutions of the present invention will be clearly and completely described in conjunction with the drawings of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all of the embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the protection scope of the present invention.

[0043] Please refer to the attached Figure 1 , the embodiment of the present invention provides a smart classroom multimedia management platform using Internet of Things centralized control, including a device management module and a resource management module:

[0044] The device management module is used to manage the multimedia devices in the smart classroom, and it includes:

[0045] The centralized control platform sub-module, which includes:

[0046] The hardware access unit is used to connect multimedia devices. It equips the projector with a communication module supporting the Wi-Fi6E standard and connects it through the HDMI2.1 interface. For the audio device, it uses a Bluetooth 5.3 module combined with the LDAC high-definition audio coding technology. For the electronic whiteboard, it equips a ZigBee3.1 communication module and connects it through the USB3.2 Gen2 interface, and each device installs a UHF RFID tag. The local gateway selects an industrial-grade gateway equipped with an Intel Xeon D-2700 series multi-core processor. This local gateway is equipped with 64GB ECC memory and 2TB NVMe solid-state drive, supports multiple protocol conversions, uses an FPGA chip for acceleration, has a dual-redundant power module and a triple-network interface hot backup design, and supports IPSec VPN and SSL VPN encryption to achieve stable, efficient, and secure data interaction between multimedia devices and the platform;

[0047] Software system unit, including a data acquisition layer, which develops device drivers using a mixed programming of Java and C++, reads device register information through I2C and SPI bus protocols, applies multi-threading and asynchronous I / O technologies, combines CRC32 and SHA-3 verification mechanisms, uses RedisCluster distributed cache, and asynchronously uploads data to the cloud through a message queue; a data processing layer builds a big data platform based on Hadoop 3.3 and Spark 3.2, stores data using HDFS 3.0, classifies device status using the K-Means combined with the DBSCAN algorithm, mines parameter relationships using the Apriori combined with the FP-growth algorithm, and performs image and time series analysis using deep learning algorithms such as CNN, ResNet, LSTM, and GRU, improving efficiency through distributed and in-memory computing technologies; an application layer builds microservices using the SpringCloud framework, deploys them in Docker containers, and orchestrates and manages them using Kubernetes. It realizes unified management of interfaces through an API gateway, applies OAuth2.0 and OpenIDConnect protocols for authentication and authorization, defines interfaces using the OpenAPI 3.0 specification, designs based on the DDD method, and uses the EDA architecture and a distributed transaction management framework to ensure system performance and scalability;

[0048] User interaction unit, which develops a responsive interface using HTML5, CSS3, JavaScript combined with Vue 3.0, supports multi-terminal use, integrates gesture recognition and voice control, uses natural language processing technology to understand user instructions, and provides personalized interface settings and operation prompt guidance functions;

[0049] Permission management unit, which divides roles such as teachers, teaching management staff, and system administrators, defines a detailed permission list for each role, uses multi-factor authentication, combines OAuth2.0 and OpenIDConnect protocols, manages permissions through JWT tokens, and uses ACL, RBAC combined with ABAC models to ensure flexible and secure permission management;

[0050] Intelligent fault warning and maintenance sub-module, which is used for fault warning and maintenance of multimedia devices, including:

[0051] Sensor deployment unit, which installs various high-precision sensors such as PT1000 temperature sensors, piezoelectric vibration sensors combined with MEMS accelerometers, Hall effect current sensors combined with Rogowski coils, piezoresistive pressure sensors, infrared and capacitive touch sensors, and microphone arrays combined with sound pressure sensors at key parts of devices such as projectors, electronic whiteboards, and speakers, and calibrates and maintains them regularly;

[0052] Data transmission unit, using NI USB-6366 data acquisition card, combined with DMA and FPGA hardware acceleration, collects data at a frequency of tens of thousands of times per second, processes it using Kalman filtering combined with wavelet denoising algorithm, reduces the transmission volume using LZMA compression algorithm, adopts AES-256 encryption algorithm, dynamically generates and updates the key through PBKDF2, transmits data through IPsec VPN and SSL VPN hybrid encryption tunnel, and monitors transmission metrics in real time;

[0053] Fault model construction unit, uses statistical and isolation forest algorithms to clean data, adopts Min-Max combined with Z-Score normalization, extracts features using PCA combined with LDA and wavelet transform, uses RFE and random forest feature selection algorithms to screen key features, trains fault models using deep learning algorithms such as CNN combined with ResNet and attention mechanism, RNN combined with LSTM and GRU, uses TensorFlow 2.0 and PyTorch 1.10 frameworks, optimizes parameters using stochastic gradient descent and its variants, evaluates through cross-validation and multiple evaluation metrics, tunes using grid search, random search, and Bayesian optimization, and improves performance using model fusion techniques such as Bagging, Boosting, and Stacking;

[0054] Early warning execution unit, sets different levels of early warning thresholds, generates early warning information according to preset rules through Drools rule engine combined with EPL, and notifies relevant personnel through various methods such as text messages, emails, system messages, mobile APP push, and voice alerts;

[0055] Maintenance management unit, generates maintenance plans according to fault prediction and operating status using Drools rule engine combined with algorithms, considers factors such as equipment usage frequency and teaching arrangements, optimizes the plans using genetic algorithm, simulated annealing algorithm, and particle swarm optimization algorithm, maintenance personnel confirm tasks through mobile terminals, scan RFID tags to record arrivals, upload maintenance information in real time, the system provides operation guidelines, updates inventory, fills in reports after maintenance is completed, the system generates summaries and evaluations, introduces user satisfaction surveys, and stores the experience in the knowledge base;

[0056] Resource management module, used to manage the teaching resources of the smart classroom, including:

[0057] Resource sharing platform sub-module, including:

[0058] The resource integration unit adopts a distributed crawler architecture, uses the Scrapy framework combined with Scrapy-Redis to crawl resources from multiple data sources, applies machine learning algorithms combined with manual review to clean data, develops a labeling tool based on deep learning, automatically extracts metadata using the BERT model and combines it with manual labeling, introduces knowledge graph technology to construct a knowledge graph in the education field to achieve intelligent classification and recommendation, adopts the Ceph distributed storage system to combine the advantages of object and block storage, deploys Memcached or RedisCluster distributed cache, and establishes a data migration mechanism;

[0059] The platform development unit uses Vue.js 3.0 combined with Vite to build the front-end interface, adopts Spring Boot combined with Spring Cloud to build a microservices architecture, deploys using Docker containerization, and manages using Kubernetes orchestration. It uses MySQL to store metadata and user information, Elasticsearch as a full-text search engine, Redis as a cache database, applies Spring Security for authentication and authorization, introduces circuit breaker, rate limiting, and degradation mechanisms, designs a unified RESTful API interface, follows the OpenAPI 3.0 specification, and manages through an API gateway to provide standard documentation and SDK;

[0060] The classification and retrieval unit uses natural language processing technology combined with CNN and RNN deep learning models to classify resources, introduces reinforcement learning to optimize the classification model in real time according to user feedback, provides multiple retrieval methods such as keywords, classification, advanced, semantic, and image, supports sorting and filtering of retrieval results, constructs a recommendation system based on deep learning, analyzes user behavior and resource characteristics by combining collaborative filtering and deep learning models, and introduces a real-time recommendation mechanism;

[0061] The review and evaluation unit establishes a multi-level review process of preliminary review, re-review, and final review, formulates an evaluation index system including content quality, teaching practicality, technical standardization, and innovation, sets weights to calculate the comprehensive score, introduces user and expert evaluations, and establishes a reward and punishment mechanism;

[0062] The intelligent resource update and push sub-module is used for intelligent update and push of teaching resources, including:

[0063] The data collection and analysis unit collects information such as teaching content updates, education policy changes, and user feedback through multiple channels such as web crawlers, cooperation institutions, and social media, and uses big data analysis and machine learning algorithms to clean and mine data;

[0064] Resource Update Unit: When it detects changes in teaching content or textbook versions, the system automatically searches for resources through the search engine API, filters and evaluates them based on multiple factors, scores them using a machine learning model, automatically downloads and updates the compliant resources to the resource library, and manages the resource versions using the Git version control system;

[0065] Intelligent Push Unit: Builds a user profile based on teachers' teaching information, resource usage history, and feedback, adopts a hybrid recommendation algorithm, combines content-based, collaborative filtering, and model-based recommendation algorithms, introduces a context-aware recommendation mechanism, selects the push timing according to teachers' teaching schedules and habits, and pushes resources through system messages, emails, mobile APP push, etc.

[0066] In a traditional classroom environment, when a device fails or management operations are required, it is difficult to quickly and accurately determine the device's location and identity. The present invention realizes the precise identification and positioning of devices by installing UHF RFID tags on each device, while traditional technologies do not have such efficient device identification and positioning means. The present invention equips the projector with a communication module supporting the Wi-Fi 6E standard and connects it through the HDMI 2.1 interface, adopts the Bluetooth 5.3 module combined with the LDAC high-definition audio coding technology for the audio device, and equips the electronic whiteboard with a ZigBee 3.1 communication module and connects it through the USB 3.2 Gen 2 interface, realizing stable and efficient connection and communication between the device and the platform, and solving the problems of interface incompatibility and communication instability in the traditional method.

[0067] In one implementation, the local gateway of the Hardware Access Unit is equipped with an Intel Xeon D-2700 series multi-core processor, which has 8 physical cores and 16 threads, with a main frequency of 2.5 GHz and a turbo frequency of up to 3.5 GHz, and can efficiently process a large number of data requests generated by the access of multimedia devices. 64GB ECC memory automatically detects and corrects errors in data transmission and storage through the Error-Correcting Code technology, ensuring data accuracy, providing a high-speed storage space for the local gateway to run various protocol conversion programs, data processing algorithms, and cache real-time data of multimedia devices, and ensuring smooth system operation. The 2TB NVMe solid-state drive, with its high-speed read and write characteristics, has a sequential read speed of up to 3500MB / s and a sequential write speed of up to 2800MB / s, meeting the large-capacity data storage requirements generated by the long-term operation of multimedia devices, including device operation logs, multimedia resource caches, etc., and realizing fast data storage and retrieval.

[0068] The local gateway supports the conversion of multiple industrial and Internet of Things (IoT) common protocols such as Modbus TCP, BACnet, and OPC UA into protocols suitable for IoT transmission, such as MQTT and CoAP, to adapt to the communication protocols of different types of multimedia devices such as projectors, audio systems, and electronic whiteboards, and realize the data interaction between the devices and the platform. The FPGA chip it uses implements specific algorithms and logics through hardware programming to process data in parallel. Compared with the traditional CPU processing method, in key processing links such as data filtering, format conversion, and encryption and decryption, the processing speed can be increased by 3-5 times, greatly improving the data transmission and processing efficiency.

[0069] The dual-redundant power supply modules are respectively connected to different mains input lines. When a fault such as overvoltage, undervoltage, or power outage occurs in one power supply, the other power supply can be seamlessly switched and put into use within 50 ms to ensure the continuous and stable operation of the local gateway. Under the three-network-port hot standby design, the three network ports monitor the network status simultaneously. When the main network port fails to work properly due to network faults, physical damage, etc., the standby network port automatically takes over the network connection task within 100 ms to maintain the network connection stability and ensure the uninterrupted data transmission of multimedia devices.

[0070] The supported IPSec VPN encrypts and authenticates the transmitted data through the AH (Authentication Header) and ESP (Encapsulating Security Payload) protocols to prevent the data from being stolen or tampered with during network transmission, and ensure the integrity and confidentiality of the data; the SSL VPN is based on the SSL / TLS protocol to achieve secure communication at the application layer, providing a secure channel for remotely managing the local gateway and multimedia devices. The combination of different encryption methods prevents data leakage and tampering in all aspects.

[0071] In one implementation, the data acquisition layer of the software system unit uses a mixed programming of Java and C++ to develop device drivers. The Java language is responsible for implementing functions related to upper-layer applications and network communication, and ensures the stable operation of the program in different operating system environments by virtue of its cross-platform characteristics; C++ focuses on underlying hardware interaction and quickly reads device register information by using its high efficiency. Through the I2C and SPI bus protocols, the device driver establishes a communication connection with multimedia devices such as projectors, audio systems, and electronic whiteboards, and accurately obtains key information such as the device operation status and parameter settings.

[0072] This data acquisition layer uses multi-threading technology. According to the data acquisition requirements of multimedia devices, an independent thread is allocated for each device or each group of related data acquisition tasks to avoid blocking phenomena during the data acquisition process and improve the acquisition efficiency. At the same time, the asynchronous I / O technology is adopted to make the data read and write operations execute asynchronously in the background without affecting the processing of other tasks in the main thread, further optimizing the system resource utilization and ensuring that the system can still operate efficiently in scenarios of collecting a large amount of device data.

[0073] Integrate the CRC32 and SHA-3 verification mechanisms to verify the integrity and accuracy of the collected data. CRC32 calculates the cyclic redundancy check code of the data to quickly detect whether errors occur during data transmission or storage; SHA-3, as a secure hash algorithm, provides a high-strength encrypted hash value for the data, which is used to verify the authenticity of the data source and prevent data tampering.

[0074] Use RedisCluster distributed caching, which disperses data storage across multiple Redis nodes to build a cluster mode. Set the cache expiration time to 10 minutes. This setting is based on considerations of the data update frequency of multimedia devices and system resource optimization. For device status data and real-time parameters that are frequently accessed in the short term, within the 10-minute cache validity period, subsequent requests can directly obtain data from the cache, reducing the pressure of repeated data collection from devices and data processing, and improving the system response speed. After 10 minutes, the cached data expires, and the system re-collects the latest data to ensure data timeliness. Asynchronously upload data to the cloud through a message queue. The message queue caches the data to be uploaded according to the first-in, first-out principle, decoupling data collection and upload, avoiding data collection blockage caused by temporary failures of the cloud server or network fluctuations, and ensuring the continuous and stable progress of data collection work.

[0075] In one implementation, the user interaction unit: This unit uses HTML5, CSS3, and JavaScript in combination with Vue3.0 to develop a responsive interface, which has excellent cross-platform display capabilities and can adapt to the screen sizes and resolutions of various terminal devices such as computers, tablets, and mobile phones, providing users with a consistent and high-quality visual experience. On the computer side, the interface layout is carefully designed with comprehensive and rich functions, facilitating complex operations and detailed settings for teachers or administrators; the mobile APP side focuses on operational convenience, with a simple and intuitive interface, ensuring that users can quickly complete common function operations in a mobile scenario.

[0076] Multilingual support: To meet the needs of different regions and user groups, the interactive interface supports five languages including Chinese, English, French, German, and Japanese. Based on language pack technology, the system dynamically loads the corresponding language resource files by detecting the user's device language settings or the user's manual selection, realizing real-time language switching of interface text, prompt messages, operation guides, etc., effectively improving the versatility and usability of the platform.

[0077] Theme switching function: Considering the personalized needs of users, multiple themes are provided for users to choose from, such as the classic simple theme, the eye-protecting green theme, the vibrant color theme, etc. Users can easily switch themes through the interface settings according to their personal preferences or usage scenarios. Theme switching is achieved by modifying the CSS style sheet, which globally replaces visual elements such as the color, font, and icons of the interface, creating different visual styles and bringing a personalized operation environment for users.

[0078] Interaction Design: Integrating gesture recognition and voice control functions significantly enhances the convenience of interaction. Gesture recognition technology is based on computer vision algorithms. Through the camera, it captures the user's hand movements. For example, in the interactive whiteboard interface, users can intuitively control teaching resources through simple gesture operations such as zooming, rotating, and flipping pages, without the need to use traditional mice or keyboards. The voice control function utilizes natural language processing technology, with a built-in speech recognition engine and semantic understanding module, which can accurately recognize and understand the voice commands issued by users, supporting various types of commands including daily operation commands (such as turning on the projector, adjusting the volume) and content search commands (such as searching for teaching videos on a certain subject). For voice control, the system has a powerful voice command learning and optimization ability. Through the analysis of a large amount of user voice command data and training with machine learning algorithms, it continuously improves the accuracy of voice command recognition and semantic understanding ability. Currently, the accuracy of voice command recognition for the above five languages has reached over 95%. At the same time, a personalized interface setting function is provided, allowing users to customize the interface layout, the arrangement order of function modules, shortcut settings, etc. according to their own usage habits to meet the operation preferences of different users. In addition, the operation prompt and guidance function runs through the entire process of user use. For users who are using the system for the first time or are not familiar with certain functions, the system will pop up an operation prompt box in a timely manner, guiding users to complete the operation with concise and clear text and animated demonstrations, effectively reducing the user's learning cost and enhancing the user experience.

[0079] In one implementation, the permission management unit ensures the security and standardization of platform operations through rigorous role and permission settings and a complete authentication and authorization mechanism.

[0080] In terms of role and permission settings, three main roles are clearly defined: teachers, teaching administrators, and system administrators. Teachers are given basic device operation permissions, such as turning on or off the projector, adjusting the audio volume, etc., to facilitate their teaching activities; at the same time, they have the management permissions for their personal teaching resources, including uploading, downloading, editing, and deleting, etc. In terms of data access permissions, teachers can view information such as device usage records and resource browsing histories related to their own teaching.

[0081] The teaching administrator role inherits some of the permissions of the teacher role. On this basis, they are given higher-level resource management permissions, such as classifying and organizing teaching resources, and reviewing whether newly uploaded resources meet teaching specifications. For device management, teaching administrators have the right to make regular deployment arrangements for devices, such as adjusting the multimedia devices in a certain classroom to another classroom to meet teaching needs. In terms of data access, teaching administrators can view the summary data of all teachers' teaching resource usage situations for teaching evaluation and optimal resource allocation.

[0082] The system administrator role fully inherits some core permissions of teaching management staff and teachers and has the highest level of management authority. The system administrator can not only deeply manage all devices, such as updating device drivers and configuring system parameters, but also manage platform user information, including creating, modifying, deleting user accounts and resetting user passwords, etc. In terms of data management, the system administrator has the right to access and manage all data on the platform, including but not limited to device operation data, user operation logs, resource library metadata, etc., to ensure the overall stable operation and data security of the platform.

[0083] The authentication and authorization mechanism adopts a multi-factor authentication method and constructs a secure and reliable identity verification system by combining the OAuth2.0 and OpenIDConnect protocols. When a user logs in, in addition to entering the traditional username and password, the user also needs to authenticate their identity through additional factors such as mobile phone verification codes, fingerprint recognition, or facial recognition, greatly enhancing the security of the account. Through the OAuth2.0 protocol, the platform realizes the authorization login function for third-party applications, facilitating users to quickly log in to the platform using their existing third-party accounts (such as the school's unified authentication account), while ensuring the secure sharing of user account information among different applications. The OpenIDConnect protocol further provides the function of verifying and obtaining user identity information on the basis of OAuth2.0, ensuring that the platform can accurately identify the user's identity.

[0084] Permission management uses JWT tokens to manage permissions. After a user is successfully authenticated, the system generates a JWT token containing user role, permission information, etc. and returns it to the client. The client carries this token in subsequent requests, and the server confirms the user's permissions by verifying the signature and validity period of the token, without having to query the database every time, improving the efficiency of permission verification and the system's response speed. At the same time, the ACL (Access Control List), RBAC (Role-Based Access Control) combined with ABAC (Attribute-Based Access Control) model is adopted. The ACL sets fine-grained permission control for specific users or user groups, the RBAC assigns permissions based on user roles, simplifying the permission management process, and the ABAC dynamically adjusts permissions according to the attributes of users, resources, and the environment. The combination of the three ensures that the permission management is both flexible and secure, meeting the complex and changeable permission management requirements of the intelligent classroom multimedia management platform.

[0085] In one implementation, the sensor deployment unit in the intelligent fault warning and maintenance sub-module plays a key role.

[0086] A variety of high-precision sensors are installed at key parts of multimedia devices such as projector bulbs, cooling fans, circuit boards, electronic whiteboard touch areas, and speakers. Among them, the PT1000 temperature sensor is used to accurately monitor temperature changes due to its high sensitivity and stability. The PT1000 temperature sensor works based on the characteristic that the resistance value of platinum resistance changes with temperature, and its measurement accuracy can reach ±0.1°C. This high-precision measurement ability can accurately sense the subtle temperature fluctuations at the key parts of the device in real time. For example, it can promptly detect the abnormal temperature rise of the projector bulb caused by long-term use, providing accurate data support for fault warning.

[0087] The piezoelectric vibration sensor combined with the MEMS accelerometer is used to monitor the vibration state of the device. The piezoelectric vibration sensor converts mechanical vibration into an electrical signal through piezoelectric materials, and the MEMS accelerometer accurately measures the vibration acceleration of the device. The two work together to detect abnormal vibrations during device operation, such as the abnormal vibration of the projector cooling fan caused by unbalanced blades, providing a basis for judging whether the mechanical components of the device are operating normally.

[0088] The Hall effect current sensor combined with the Rogowski coil is used to monitor the current situation of the device. The Hall effect current sensor directly measures DC and low-frequency AC currents using the Hall effect principle, and the Rogowski coil is suitable for measuring high-frequency AC currents. The two cooperate to comprehensively monitor different types of current signals of the device, promptly detect current overload or abnormal fluctuations, and avoid device failures caused by current problems.

[0089] The piezoresistive pressure sensor is used to detect changes in the internal pressure of the device, such as the pressure changes in the electronic whiteboard touch area due to external forces or the air pressure changes inside the speaker device caused by sound vibrations. By accurately measuring the pressure value, it can be determined whether the relevant components of the device are working properly.

[0090] The infrared and capacitive touch sensors are used for touch operation detection on the electronic whiteboard. The infrared touch sensor detects the touch position through infrared emission and reception pairs, and the capacitive touch sensor uses the principle of human electric field and capacitance induction to identify touch actions. The combination of the two sensors improves the accuracy and sensitivity of touch detection, ensuring accurate response to touch operations on the electronic whiteboard.

[0091] The microphone array combined with the sound pressure sensor is used for sound signal monitoring of the speaker device. The microphone array consists of multiple microphones, which can achieve directional acquisition and positioning of sound. The sound pressure sensor accurately measures the pressure changes generated by sound and converts the sound signal into an electrical signal for analyzing problems such as the output sound quality, volume size, and whether there are noises in the speaker device.

[0092] To ensure the accuracy of the sensor measurement data, the sensor is calibrated regularly using standard calibration equipment. At the same time, a detailed database is established to record information such as the installation location of the sensor, calibration time, usage and maintenance records, etc. This facilitates the management of the entire life cycle of the sensor, timely discovery of potential problems of the sensor and maintenance and replacement, ensuring the stable operation of the entire intelligent fault warning and maintenance sub-module, and thus ensuring the reliable operation of the multimedia equipment in the smart classroom.

[0093] In one implementation, when using grid search tuning in the fault model construction unit, the parameter ranges searched are the learning rate [0.001, 0.01, 0.1] and the regularization parameter [0.0001, 0.001, 0.01].

[0094] In one implementation, the erasure code strategy adopted by the Ceph distributed storage system in the resource integration unit is the Reed-Solomon coding strategy;

[0095] The update frequency of the user profile in the resource intelligent update and push sub-module is once every 3 days.

[0096] Although the embodiments of the present invention have been shown and described, those of ordinary skill in the art can understand that various changes, modifications, substitutions and variations can be made to these embodiments without departing from the principle and spirit of the present invention. The scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. A smart classroom multimedia management platform using the Internet of Things for centralized control, characterized in that: Including device management module and resource management module: The device management module includes: The centralized control platform submodule includes a hardware access unit, a software system unit, a user interaction unit, and a permission management unit, which are used to implement multimedia device access and communication, data collection and processing, cross-terminal interactive interface development, and multi-role permission control. Intelligent fault warning and maintenance submodule, including sensor deployment unit, data transmission unit, fault model building unit, warning execution unit and maintenance management unit, used for equipment status monitoring, fault prediction and maintenance scheduling; The resource management module includes: The resource sharing platform submodule includes a resource integration unit, a platform development unit, a classification retrieval unit, and an audit and evaluation unit, which are used for the collection, storage, retrieval, and quality control of teaching resources; The resource intelligent update and push submodule includes a data collection and analysis unit, a resource update unit and an intelligent push unit, which are used for dynamic updating and personalized recommendation of teaching resources.

2. According to claim 1, a smart classroom multimedia management platform using the Internet of Things for centralized control is characterized in that: The hardware access unit comprises: The local gateway is equipped with a multi-core processor, ECC memory and high-speed storage media, capable of converting multiple industrial protocols; Protocol adaptation unit, used for heterogeneous protocol conversion of different types of multimedia devices; Redundant design unit, using dual power modules and three network ports hot backup to ensure communication stability.

3. According to claim 1, a smart classroom multimedia management platform using the Internet of Things for centralized control is characterized in that: The data acquisition layer of the software system unit adopts a hybrid programming architecture, obtains device data through a bus protocol, uses multi-threading and asynchronous I / O technology to achieve efficient acquisition, combines a verification mechanism to ensure data integrity, and uses distributed caching and message queues to achieve asynchronous data upload.

4. According to claim 1, a smart classroom multimedia management platform using the Internet of Things for centralized control is characterized in that: The user interaction unit comprises: Responsive interface development framework for multi-terminal adaptive display; Multimodal interaction unit for gesture recognition and voice control; Personalization settings module, used for interface theme switching and operation guidance functions.

5. According to claim 1, a smart classroom multimedia management platform using the Internet of Things for centralized control is characterized in that: The rights management unit includes: The role division module is used to define the hierarchical permissions of teachers, teaching management personnel, and system administrators; Authentication and authorization module, which uses multi-factor authentication combined with dynamic token management; The access control module implements fine-grained permission allocation through a composite permission model.

6. According to claim 1, a smart classroom multimedia management platform using the Internet of Things for centralized control is characterized in that: The intelligent fault warning and maintenance submodule includes: Multi-type sensor arrays are deployed at key locations on equipment to monitor temperature, vibration, and current parameters; The data preprocessing unit uses filtering algorithms and compression encryption technology to process sensor data; Intelligent diagnosis unit, which uses feature extraction algorithms and deep learning models to predict faults.

7. According to claim 1, a smart classroom multimedia management platform using the Internet of Things for centralized control is characterized in that: The resource sharing platform submodule includes: Distributed resource collection unit, using crawler technology combined with intelligent annotation to achieve resource integration; Multi-dimensional retrieval unit for semantic retrieval and deep learning classification; The quality control unit is used to establish a multi-level review process and user evaluation system.

8. According to claim 1, a smart classroom multimedia management platform using the Internet of Things for centralized control is characterized in that: The resource intelligent update and push submodule includes: Dynamic monitoring unit, used to track teaching content and policy changes in real time; Version control unit, used for managing resource versions in distributed storage systems; Personalized recommendation unit, used for accurate push based on user portrait and hybrid recommendation algorithm.

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