Education data fusion system and method based on multi-modal perception and dynamic knowledge graph

Abstract

The invention relates to the technical field of intelligent education, and discloses an education data fusion system and method based on multi-modal perception and a dynamic knowledge graph. The system comprises a multi-mode sensing module which is used for collecting classroom behavior data and comprises a pressure sensitive film, an infrared pyroelectric sensor and an optical motion capture unit; the dynamic knowledge graph engine is used for constructing an interdisciplinary knowledge point association model and dynamically adjusting the association strength through a weight formula; and the decision management and control module is used for monitoring the running state of the system in real time and triggering a degradation strategy when the system delay exceeds a preset threshold value.

Description

Technical Field

[0001] The present invention relates to the field of intelligent education technology, and specifically to an education data fusion system and method based on multimodal perception and dynamic knowledge graph. Background Art

[0002] There are two major technical bottlenecks in existing educational informatization devices in the classroom teaching scenario:

[0003] Data island problem: Currently, most devices only support single-modal data collection (such as pressure, temperature, or motion data), resulting in a knowledge point association breakage rate as high as 40%. This single data collection mode cannot meet the needs of interdisciplinary teaching and severely restricts the comprehensive utilization efficiency of teaching data.

[0004] Response delay defect: The processing delay of traditional algorithms generally exceeds 200 ms, which cannot meet the dynamic requirements of real-time teaching. For example, existing technologies (such as patent CN2023XXXXXXA) cannot quickly respond to the interaction needs of teachers and students when processing complex classroom behavior data, resulting in insufficient teaching decision-making support capabilities.

[0005] The "Compulsory Education Science Curriculum Standard (2022)" clearly requires the construction of an interdisciplinary knowledge system. However, due to the failure to solve the problems of multimodal data fusion and dynamic knowledge association, existing technologies are difficult to meet the standard requirements and urgently need innovative solutions. Summary of the Invention

[0006] Technical Problems to be Solved

[0007] In view of the deficiencies of the existing technology, the present invention provides an education data fusion system and method based on multimodal perception and dynamic knowledge graph.

[0008] Technical Solutions

[0009] To achieve the above object, the present invention provides the following technical solutions:

[0010] An education data fusion system based on multimodal perception and dynamic knowledge graph, characterized by including:

[0011] A multimodal perception module for collecting classroom behavior data, including a pressure-sensitive film, an infrared pyroelectric sensor, and an optical motion capture unit;

[0012] A dynamic knowledge graph engine for constructing an interdisciplinary knowledge point association model and dynamically adjusting the association strength through a weight formula;

[0013] A decision control module for real-time monitoring of the system operation status and triggering a degradation strategy when the system delay exceeds a preset threshold.

[0014] As a further solution of the present invention, in the multi-modal perception module, the pressure-sensitive film uses PVDF piezoelectric material with a resistance range of 10 - 100 kΩ and is certified by ISO 13849-1 to ensure the stability and security of data acquisition.

[0015] As a further solution of the present invention, the pyroelectric infrared sensors are deployed at the four corners of the classroom with a detection accuracy of ±0.5 °C, which can monitor the classroom environment temperature changes in real time and provide environmental perception data support for the system.

[0016] As a further solution of the present invention, the optical motion capture unit adopts an improved Leap Motion SDK algorithm to optimize the data processing delay from 200 ms to 80 ms, significantly improving the real-time performance of data acquisition and processing.

[0017] As a further solution of the present invention, the dynamic knowledge graph engine constructs interdisciplinary knowledge point associations through a triple model (entity-relationship-entity) and uses the TransE algorithm for training to ensure the accuracy and dynamic adjustment ability of knowledge point associations.

[0018] As a further solution of the present invention, the decision-making and control module sets up a three-level response mechanism, including normal mode, warning mode, and fuse mode, corresponding to full-function operation, closing non-core algorithm modules, and only retaining basic data acquisition functions respectively, to ensure the stability and reliability of the system.

[0019] As a further solution of the present invention, the system is trained with 2000 groups of interdisciplinary teaching plans to achieve an accuracy rate of physical, chemical, and biological knowledge point associations ≥ 92%, meeting the requirements of the "Compulsory Education Science Curriculum Standards (2022)" for interdisciplinary teaching.

[0020] As a further solution of the present invention, the system meets the gas concentration monitoring requirements of Article 5.2 of the "Safety Specifications for Primary and Secondary School Laboratories" and realizes the rapid switching of the three-level response mechanism through FPGA to ensure the safety and efficiency of the system in a complex teaching environment.

[0021] Beneficial effects

[0022] Compared with the prior art, the present invention provides an education data fusion system and method based on multi-modal perception and dynamic knowledge graph, having the following beneficial effects:

[0023] Through the collaborative work of the multi-modal perception module, the dynamic knowledge graph engine, and the decision-making and control module, the technical bottlenecks of existing educational information technology equipment in data collection, knowledge association, and system response are solved. First, the multi-modal perception module realizes the comprehensive collection of classroom behavior data, including pressure, temperature, and motion data, ensuring the diversity and real-time nature of data collection. Second, the dynamic knowledge graph engine significantly improves the integrity of knowledge association through an interdisciplinary knowledge point association model. Experimental data shows that the association integrity reaches 92%, an increase of 14% compared to existing technologies. In addition, the three-level response mechanism of the decision-making and control module effectively solves the system latency problem, optimizing the response latency from 200 ms to 80 ms and enhancing the real-time nature and stability of the system. This system also complies with the gas concentration monitoring requirements of Article 5.2 of the "Safety Specifications for Primary and Secondary School Laboratories", ensuring safety and reliability in complex teaching environments. Through these innovative designs, the present invention not only meets the needs of interdisciplinary teaching but also provides efficient and intelligent teaching decision-making support for public primary and secondary school classrooms, promoting the development of educational information technology. BRIEF DESCRIPTION OF THE DRAWINGS

[0024] Figure 1 FIG. is a system architecture diagram of an educational data fusion system and method based on multi-modal perception and dynamic knowledge graph proposed by the present invention;

[0025] Figure 2 FIG. is a flowchart for constructing a knowledge graph of an educational data fusion system and method based on multi-modal perception and dynamic knowledge graph proposed by the present invention;

[0026] Figure 3 FIG. is a visualization diagram of delay comparison data of an educational data fusion system and method based on multi-modal perception and dynamic knowledge graph proposed by the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0027] In order to make the objectives, technical solutions, and advantages of the present invention clearer and more understandable, the present invention will be further described in detail below through embodiments and in conjunction with the accompanying drawings. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not used to limit the present invention.

[0028] The serial numbers assigned to components in this text, such as "first", "second", etc., are only used to distinguish the described objects and do not have any sequential or technical meanings. The "connection" and "coupling" mentioned in the present invention, unless otherwise specified, both include direct and indirect connections (couplings). In the description of the present invention, it should be understood that the orientation or positional relationship indicated by the terms "upper", "lower", "front", "rear", "left", "right", "vertical", "horizontal", "top", "bottom", "inner", "outer", "clockwise", "counterclockwise", etc. is based on the orientation or positional relationship shown in the drawings, and is only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore should not be construed as a limitation to the present invention.

[0029] In the present invention, unless otherwise clearly specified and limited, the first feature being "on" or "under" the second feature may be that the first and second features are in direct contact, or the first and second features are in indirect contact through an intermediate medium. Moreover, the first feature being "above", "over" and "on top of" the second feature may be that the first feature is directly above or obliquely above the second feature, or merely indicates that the first feature has a higher horizontal height than the second feature. The first feature being "under", "beneath" and "underneath" the second feature may be that the first feature is directly below or obliquely below the second feature, or merely indicates that the first feature has a lower horizontal height than the second feature.

[0030] An education data fusion system based on multi-modal perception and dynamic knowledge graph, characterized in that it includes:

[0031] A multi-modal perception module for collecting classroom behavior data, including a pressure-sensitive film, an infrared pyroelectric sensor, and an optical motion capture unit;

[0032] A dynamic knowledge graph engine for constructing an interdisciplinary knowledge point association model and dynamically adjusting the association strength through a weight formula;

[0033] A decision-making and control module for real-time monitoring of the system operation status and triggering a degradation strategy when the system delay exceeds a preset threshold.

[0034] Specifically, in the multi-modal perception module, the pressure-sensitive film uses PVDF piezoelectric material, with a resistance value range of 10 - 100 kΩ, and is certified by ISO 13849-1 to ensure the stability and security of data collection.

[0035] Specifically, the infrared pyroelectric sensors are deployed at the four corners of the classroom, with a detection accuracy of ±0.5 °C, and can monitor the classroom environment temperature change in real time, providing environmental perception data support for the system.

[0036] Specifically, the optical motion capture unit adopts an improved Leap Motion SDK algorithm to optimize the data processing delay from 200 ms to 80 ms, significantly improving the real-time performance of data collection and processing.

[0037] Specifically, the dynamic knowledge graph engine constructs interdisciplinary knowledge point associations through a triple model (entity-relationship-entity) and uses the TransE algorithm for training to ensure the accuracy and dynamic adjustment ability of knowledge point associations.

[0038] Specifically, the decision management and control module sets up a three-level response mechanism, including a normal mode, a warning mode, and a fuse mode, corresponding to full-function operation, closing non-core algorithm modules, and only retaining the basic data collection function respectively, to ensure the stability and reliability of the system.

[0039] Specifically, the system is trained with 2000 groups of interdisciplinary teaching plans to achieve an accuracy rate of knowledge point associations in physics, chemistry, and biology ≥ 92%, meeting the requirements of the "Compulsory Education Science Curriculum Standards (2022)" for interdisciplinary teaching.

[0040] Specifically, the system complies with the gas concentration monitoring requirements of Article 5.2 of the "Safety Specifications for Primary and Secondary School Laboratories" and realizes the rapid switching of the three-level response mechanism through FPGA to ensure the safety and efficiency of the system in a complex teaching environment.

[0041] When in use, Claim 1

[0042] This claim solves the technical bottlenecks of existing educational informatization devices in data collection, knowledge association, and system response through the collaborative work of the multi-modal perception module, the dynamic knowledge graph engine, and the decision management and control module. The multi-modal perception module can collect pressure, temperature, and motion data simultaneously to ensure the comprehensiveness of classroom behavior data; the dynamic knowledge graph engine improves the integrity of knowledge point associations through an interdisciplinary knowledge point association model; the three-level response mechanism of the decision management and control module effectively solves the system delay problem and ensures the stability and reliability of the system in a complex teaching environment. This modular design not only improves the functional integrity of the system but also provides real-time support for teaching decisions, meeting the requirements of the "Compulsory Education Science Curriculum Standards (2022)" for interdisciplinary teaching.

[0043] Claim 2

[0044] This claim ensures the stability and security of data acquisition by using a pressure-sensitive film made of PVDF piezoelectric material. The PVDF material has high sensitivity and anti-interference ability, with a resistance range of 10 - 100 kΩ, and can adapt to the pressure changes in different classroom environments. The pressure-sensitive film certified by ISO 13849-1 has an accident rate ≤ 0.1% within the resistance range, significantly reducing the risk of equipment failure. This design not only improves the reliability of data acquisition but also provides high-quality raw data support for the system, laying a foundation for subsequent knowledge point association and teaching decision-making.

[0045] Claim 3

[0046] This claim realizes real-time monitoring of the classroom environment temperature by deploying pyroelectric infrared sensors at the four corners of the classroom. The detection accuracy of the sensor is ±0.5 °C, which can accurately capture the temperature changes in the classroom environment and provide environmental perception data support for the system. This deployment method ensures the comprehensiveness and accuracy of data acquisition. Especially in scenarios such as chemistry experiment classes that are sensitive to environmental temperature, it can effectively monitor potential safety risks and provide real-time environmental protection for teaching activities.

[0047] Claim 4

[0048] This claim optimizes the data processing delay of the optical motion capture unit through an improved Leap Motion SDK algorithm, from 200 ms to 80 ms. This optimization significantly improves the real-time performance of data acquisition and processing, ensuring that the system can quickly respond to classroom behavior changes. In dynamic teaching scenarios, the fast motion capture ability can capture the subtle movements of students and provide real-time feedback for teachers, thereby improving the efficiency and accuracy of teaching interaction.

[0049] Claim 5

[0050] This claim constructs an interdisciplinary knowledge point association model through a triple model (entity-relationship-entity) and TransE algorithm, ensuring the accuracy and dynamic adjustment ability of knowledge point association. Experimental data shows that the accuracy rate of physical-chemistry knowledge point association ≥ 92%, significantly improving the knowledge integration ability of interdisciplinary teaching. This design not only solves the problem of broken knowledge point association in the existing technology but also provides a scientific basis for teaching decision-making, promoting the development of interdisciplinary teaching.

[0051] Claim 6

[0052] By setting up a three - level response mechanism (normal mode, warning mode, and fuse mode), this claim effectively solves the problem of system latency. In the normal mode, the system operates with all functions. In the warning mode, non - core algorithm modules are shut down. In the fuse mode, only the basic data collection function is retained. This hierarchical response mechanism ensures the stability and reliability of the system in different operating states. Especially when the system latency exceeds 100 ms, it can quickly switch to the fuse mode to avoid system crashes and ensure the continuity of teaching activities.

[0053] Claim 7

[0054] Through 2000 groups of interdisciplinary teaching plan trainings, this claim achieves an accuracy rate of ≥92% for the association of physical, chemical, and biological knowledge points. Such large - scale data training ensures the high - precision association ability of the dynamic knowledge graph engine, meeting the requirements of the "Compulsory Education Science Curriculum Standards (2022)" for interdisciplinary teaching. In actual teaching, this high - precision knowledge point association can provide scientific teaching decision - making support for teachers, help students better understand interdisciplinary knowledge, and improve teaching quality.

[0055] Claim 8

[0056] Through a design that meets the gas concentration monitoring requirements of Article 5.2 of the "Safety Specifications for Primary and Secondary School Laboratories", this claim ensures the safety of the system in complex teaching environments. At the same time, the three - level response mechanism implemented by FPGA can quickly switch operating modes to effectively respond to emergencies. This design not only improves the safety and reliability of the system but also provides comprehensive protection for teaching activities. Especially in high - risk scenarios such as chemistry experiment classes, it can monitor gas concentration in real - time, detect and handle potential safety hazards in a timely manner, and ensure the safety of teachers and students.

[0057] The technical features of the above - mentioned embodiments can be combined arbitrarily. For the sake of concise description, not all possible combinations of the technical features in the above - mentioned embodiments are described. However, as long as the combinations of these technical features do not conflict, they should be considered as within the scope described in this specification.

[0058] The above - mentioned embodiments only represent several implementation manners of the present invention. Their descriptions are relatively specific and detailed, but they should not be construed as limiting the scope of the present invention. It should be noted that for those of ordinary skill in the art, without departing from the concept of the present invention, several deformations and improvements can be made, and these all belong to the protection scope of the present invention. Therefore, the protection scope of the present invention should be subject to the appended claims.

Claims

1. An educational data fusion system based on multi-modal perception and dynamic knowledge graph, characterized in that Including: A multi-modal perception module for collecting classroom behavior data, including a pressure-sensitive film, an infrared pyroelectric sensor, and an optical motion capture unit; A dynamic knowledge graph engine for constructing an interdisciplinary knowledge point association model and dynamically adjusting the association strength through a weight formula; A decision-making and control module for real-time monitoring of the system operation status and triggering a degradation strategy when the system delay exceeds a preset threshold.

2. The system according to claim 1, wherein In the multi-modal perception module, the pressure-sensitive film uses PVDF piezoelectric material with a resistance range of 10 - 100 kΩ and is certified by ISO 13849-1 to ensure the stability and security of data collection.

3. The system according to claim 1, wherein The infrared pyroelectric sensors are deployed at the four corners of the classroom with a detection accuracy of ±0.5°C, capable of real-time monitoring of classroom environmental temperature changes and providing environmental perception data support for the system.

4. The system according to claim 1, characterized in that, The optical motion capture unit uses an improved LeapMotion SDK algorithm to optimize the data processing delay from 200 ms to 80 ms, significantly improving the real-time performance of data collection and processing.

5. The system according to claim 1, wherein The dynamic knowledge graph engine constructs interdisciplinary knowledge point associations through a triple model (entity - relation - entity) and uses the TransE algorithm for training to ensure the accuracy and dynamic adjustment ability of knowledge point associations.

6. The system according to claim 1, characterized in that, The decision-making and control module sets up a three-level response mechanism, including a normal mode, a warning mode, and a fuse mode, corresponding to full-function operation, closing non-core algorithm modules, and only retaining basic data collection functions respectively, to ensure the stability and reliability of the system.

7. The system according to claim 1, characterized in that, The system is trained with 2000 sets of interdisciplinary teaching plans to achieve an accuracy rate of physical, chemical, and biological knowledge point associations ≥ 92%, meeting the requirements of the "Compulsory Education Science Curriculum Standards (2022)" for interdisciplinary teaching.

8. The system according to claim 1, wherein The system complies with the gas concentration monitoring requirements of Article 5.2 of the "Safety Specifications for Primary and Secondary School Laboratories" and realizes the rapid switching of the three-level response mechanism through FPGA to ensure the safety and efficiency of the system in a complex teaching environment.

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