Animal experiment teaching demonstration center management device and use method thereof

Abstract

The invention relates to the technical field of animal experiment teaching demonstration, in particular to an animal experiment teaching demonstration center management device and a use method thereof, and the method comprises the following steps: I, device initialization: arranging remote monitoring equipment and close sensing equipment, and ensuring that an animal activity area is covered and no blind area exists; defining monitoring modes in the main control system, wherein the monitoring modes comprise a remote monitoring mode, a close monitoring mode and a cooperative monitoring mode; according to the invention, through the dynamic cooperation of remote and close-range monitoring equipment and in combination with an interference evaluation algorithm, the balance between monitoring accuracy and interference minimization is realized, the natural behavior mode of animals is effectively reserved, and meanwhile, an adaptive mechanism is adopted, so that equipment parameters and a monitoring mode can be adjusted in real time, and the monitoring effect is dynamically optimized according to an experimental scene; manual intervention requirements are greatly reduced, the contradiction between accuracy and interference of an existing animal behavior monitoring system is effectively solved, and the animal behavior monitoring system is suitable for various animal experiment teaching and scientific research scenes.

Description

Technical Field

[0001] The invention relates to the technical field of animal experiment teaching demonstration, in particular to an animal experiment teaching demonstration center management device and a use method thereof. Background Art

[0002] The management devices of the Animal Experiment Teaching Demonstration Center cover animal management, experimental teaching support, safety and standard management, facility and equipment management, data processing and compliance management. These devices improve the management efficiency of the experimental center through information and automation technology, ensure the scientificity, safety and ethical compliance of the experiments, and also provide strong support for teaching activities. The most common management devices usually revolve around animal management (such as environmental monitoring, feeding devices, identification), experimental support (such as multimedia teaching, data collection) and safety assurance (such as biological safety cabinets, emergency alarms). These devices play a basic and key role in the daily operation of the teaching demonstration center, ensuring the efficiency, safety and compliance of the experimental process; To improve the accuracy of behavioral monitoring, the equipment needs to be close to the animals or cover a wide monitoring range, which may interfere with the animal's activities such as stress and behavioral changes. Reducing equipment interference may reduce monitoring accuracy and miss important behavioral data. Therefore, precise monitoring may change the natural behavior patterns of animals, but reducing interference may affect the comprehensiveness and accuracy of the data. Therefore, in response to the above problems, an animal experimental teaching demonstration center management device and its use method are proposed. Summary of the invention

[0003] The purpose of the present invention is to provide an animal experiment teaching demonstration center management device and a method of using the same, so as to solve the problem that in order to improve the accuracy of behavior monitoring, the equipment needs to be close to the animal or cover a wide monitoring range, which may cause interference to the animal activities such as stress, behavior changes, etc. Reducing equipment interference may reduce monitoring accuracy and miss important behavioral data. As a result, there is a problem that accurate monitoring may change the natural behavior patterns of animals, but reducing interference may affect the comprehensiveness and accuracy of the data.

[0004] To achieve the above object, the present invention provides the following technical solutions: An animal experiment teaching demonstration center management device and a method of using the same, comprising the following steps: Step I: Device initialization: Arrange remote monitoring equipment and close-range sensing equipment to ensure coverage of animal activity areas without blind spots; Define monitoring modes in the master control system, including remote monitoring, close monitoring and collaborative monitoring modes; Set the collection frequency, interference threshold, and behavior importance weight; Step II: Behavior data collection: Remote monitoring stage: The remote device collects overall behavior data in low-power mode, including activity range and trajectory. The scene heat dynamically adjusts the focus and angle of the collection device through the following formula:

[0005] In the formula, is the acquisition equipment adjustment factor, Density changes in areas where animals gather; is the weight of environmental change, is the variation range of environmental parameters, is the monitoring time interval; Close monitoring stage: When long periods of inactivity and sudden decreases in activity are detected, the close proximity device automatically activates to record micro-movements and specific behavioral data; Step III: Dynamic Control and Interference Management: Calculate the optimal combination of equipment operating parameters based on animal behavior changes and environmental parameters:

[0006] In the formula, The optimal working parameters of the equipment. is the device power, is the device acquisition frequency, is the interference value, For energy consumption, and are the weight coefficients of interference and energy consumption respectively; The system dynamically adjusts device parameters and switches to low-power or remote monitoring mode when interference values ​​exceed thresholds; Step IV: Data fusion and analysis: Align the remote monitoring and close monitoring data by timestamps, and fuse multi-source data to generate behavioral analysis results; Use the feature mapping formula to calculate the pattern similarity of animal behaviors and mark abnormal behaviors:

[0007] In the formula, is the similarity between the current behavior and the baseline behavior, Behavioral characteristics The weight of is the current behavior feature vector, is the baseline behavior feature vector; Step V: User feedback and strategy optimization: Users review the behavior analysis results to confirm the accuracy of the analysis; Adjust the equipment collection frequency, interference threshold and behavior weight according to the experimental requirements; The system records the adjustment strategy and updates the optimization model for strategy recommendation in subsequent experiments.

[0008] As a further optimization of the present invention, in the dynamic control and interference management step, the following formula is used to calculate the device interference value:

[0009] In the formula, For behavior The weight of For current behavior The observed value of For behavior The baseline value, is the current device power, It is the normalized value of device power.

[0010] As further optimized content of the present invention, among others: in the behavior data collection step, the remote monitoring equipment captures the activity trajectory and overall behavior data of the animal through a high-definition camera and an infrared sensor; the close-range sensing device records the micro-movements and specific behaviors of the animal through a low-power microwave radar and a thermal sensor.

[0011] As a further optimization of the present invention, in the behavior data collection step, the system dynamically adjusts the collection angle, focal length and range of the remote monitoring device according to the scene heat. The calculation formula of the scene heat is:

[0012] In the formula, , and is the weight coefficient, is the animal density, is the activity level, Changes in environmental parameters, including temperature and humidity; As a further optimization of the present invention, in the data fusion and analysis step, the system uses a deep learning algorithm to perform behavioral pattern recognition on the fused data, mark abnormal behaviors and generate a behavioral report containing activity levels, behavioral frequencies and abnormal behaviors.

[0013] As further optimized content of the present invention, the device provides behavioral data visualization function through a user interaction interface, including real-time display of behavior trajectory, heat distribution and abnormal behavior alarm, and the user can adjust the monitoring mode or collection parameters through the interface.

[0014] As further optimized content of the present invention, the behavior data collection and regulation steps adopt a collaborative monitoring mechanism, and the remote monitoring equipment is started first. When abnormal behavior is detected, the proximity sensing device is automatically activated, and the collection frequency and power level are adjusted according to the importance of the behavior.

[0015] As further optimized content of the present invention, among others: the user can optimize the system response sensitivity by adjusting the interference threshold and behavior weight to meet the monitoring needs of different experimental scenarios, and the setting of the interference threshold and weight supports the automatic recommendation function based on historical data.

[0016] As further optimized content of the present invention, it includes: Main control system: including embedded computing unit, data storage module and communication interface; Used to coordinate the operation of monitoring equipment, dynamically adjust acquisition parameters, and optimize the balance between monitoring accuracy and minimizing interference through algorithms; Multimodal behavior monitoring module: including remote monitoring equipment and close sensing equipment; Remote monitoring equipment collects overall animal behavior data through high-definition cameras and infrared sensors; Close sensing devices collect detailed behavioral data of animals through microwave radar and thermal sensors; Dynamic control and interference management module: including interference assessment algorithm module, adaptive control unit and threshold setter; Used to dynamically adjust the acquisition frequency and power according to changes in animal behavior and device status to reduce interference with animal behavior; Data fusion and analysis module: including data fusion algorithm unit and deep learning behavior analysis engine; Used to integrate multi-source data and analyze and generate behavior pattern reports; User interaction and feedback module: including multi-terminal interaction interface and report generation module; Users can view behavioral data in real time, adjust monitoring modes, and review and annotate analysis reports through the interface.

[0017] Compared with the prior art, the present invention has the following beneficial effects: 1. In the present invention, through the dynamic collaboration of remote and close-range monitoring equipment, combined with the interference assessment algorithm, a balance between monitoring accuracy and interference minimization is achieved, and the natural behavior patterns of animals are effectively retained. At the same time, an adaptive mechanism is adopted to adjust the equipment parameters and monitoring modes in real time, dynamically optimize the monitoring effect according to the experimental scene, greatly reduce the need for manual intervention, and effectively solve the contradiction between the accuracy and interference of the existing animal behavior monitoring system. It is suitable for various animal experimental teaching and scientific research scenarios; 2. In the present invention, multimodal behavior monitoring is combined with environmental data, and deep learning algorithms are used to identify behavior patterns to generate high-precision animal behavior analysis reports, providing reliable data support for teaching and research. Through intuitive behavior data visualization and abnormal behavior alarm functions, the device provides students with real-time teaching demonstrations and meets the needs of scientific researchers for refined analysis of behavior data. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] Figure 1 This is a system block diagram of an animal experiment teaching demonstration center management device of the present invention; Figure 2 The present invention is a flowchart of a method for using an animal experiment teaching demonstration center management device. DETAILED DESCRIPTION

[0019] See also Figure 1-2 , the present invention provides a technical solution: An animal experiment teaching demonstration center management device and a method of using the same, comprising the following steps: Step I: Device initialization: Arrange remote monitoring equipment and close-range sensing equipment to ensure coverage of animal activity areas without blind spots; Define monitoring modes in the master control system, including remote monitoring, close monitoring and collaborative monitoring modes; Set the collection frequency, interference threshold, and behavior importance weight; Step II: Behavior data collection: Remote monitoring stage: The remote device collects overall behavior data in low-power mode, including activity range and trajectory. The scene heat dynamically adjusts the focus and angle of the collection device through the following formula:

[0020] In the formula, is the acquisition equipment adjustment factor, Density changes in areas where animals gather; is the weight of environmental change, is the variation range of environmental parameters, is the monitoring time interval; Close monitoring stage: When long periods of inactivity and sudden decreases in activity are detected, the close proximity device automatically activates to record micro-movements and specific behavioral data; Step III: Dynamic Control and Interference Management: Calculate the optimal combination of equipment operating parameters based on animal behavior changes and environmental parameters:

[0021] In the formula, The optimal working parameters of the equipment. is the device power, is the device acquisition frequency, is the interference value, For energy consumption, and are the weight coefficients of interference and energy consumption respectively; The system dynamically adjusts device parameters and switches to low-power or remote monitoring mode when interference values ​​exceed thresholds; Step IV: Data fusion and analysis: Align the remote monitoring and close monitoring data by timestamps, and fuse multi-source data to generate behavioral analysis results; Use the feature mapping formula to calculate the pattern similarity of animal behaviors and mark abnormal behaviors:

[0022] In the formula, is the similarity between the current behavior and the baseline behavior, Behavioral characteristics The weight of is the current behavior feature vector, is the baseline behavior feature vector; Step V: User feedback and strategy optimization: Users review the behavior analysis results to confirm the accuracy of the analysis; Adjust the equipment collection frequency, interference threshold and behavior weight according to the experimental requirements; The system records the adjustment strategy and updates the optimization model for strategy recommendation in subsequent experiments. The method provides a complete and operational process through five steps, including device initialization, behavioral data collection, dynamic control and interference management, data fusion and analysis, and user feedback and strategy optimization, ensuring the comprehensiveness and real-time nature of animal behavior monitoring. The dynamic control mechanism optimizes equipment parameters through formulas, effectively reducing interference to animals while improving monitoring accuracy.

[0023] As a technical solution for further implementation of this solution, in the dynamic control and interference management step, the following formula is used to calculate the equipment interference value:

[0024] In the formula, For behavior The weight of For current behavior The observed value of For behavior The baseline value, is the current device power, The power normalization value of the equipment is used. The interference value calculation formula is used to quantify the interference degree of the equipment on the animal behavior. The power is adjusted by normalization to dynamically optimize the equipment operation status. This mechanism can flexibly adjust the interference intensity of the acquisition equipment in different experimental environments, reduce the risk of interference with animal behavior, and improve the scientific nature of the experiment and the accuracy of the results. As a technical solution for further implementation of this plan, in the behavior data collection step, the remote monitoring equipment captures the activity trajectory and overall behavior data of the animal through high-definition cameras and infrared sensors; the close sensing equipment records the micro-movements and specific behaviors of the animal through low-power microwave radars and thermal sensors. By combining the remote monitoring equipment with high-definition cameras and infrared sensors, and the close sensing equipment with microwave radars and thermal sensors, multimodal behavior monitoring is achieved. The remote equipment ensures the comprehensiveness of macro-behavior collection, while the close sensing equipment enhances the ability to collect fine behavior data, improving the depth and accuracy of monitoring; As a technical solution for further implementation of this solution, in the behavior data collection step, the system dynamically adjusts the collection angle, focal length and range of the remote monitoring device according to the scene heat. The calculation formula of the scene heat is:

[0025] In the formula, , and is the weight coefficient, is the animal density, is the activity level, To accommodate changes in environmental parameters, including temperature and humidity, the scene heat dynamic adjustment formula optimizes the focal length and angle of the monitoring equipment in real time according to animal density, activity level, and environmental changes, ensuring that monitoring resources are concentrated in high-heat areas. This method significantly improves monitoring efficiency and equipment adaptability, reduces resource waste, and is suitable for dynamically changing experimental scenarios; As a technical solution for further implementation of this plan, in the data fusion and analysis step, the system uses deep learning algorithms to identify behavioral patterns of fused data, mark abnormal behaviors and generate behavioral reports containing activity levels, behavioral frequencies and abnormal behaviors. By using deep learning algorithms to identify behavioral patterns of fused data, the system can generate detailed behavioral reports containing activity levels, behavioral frequencies and abnormal behavior markers. This function provides high-quality analytical data support for teaching and scientific research, and enhances the repeatability of experiments and the reliability of results. As a technical solution for further implementation of this solution, the device provides a behavior data visualization function through a user interaction interface, including real-time display of behavior trajectory, heat distribution and abnormal behavior alarm. Users can adjust the monitoring mode or acquisition parameters through the interface. The real-time visualization function of the user interaction interface enables experimenters to dynamically control the behavior data, quickly respond to abnormal situations, and adjust the monitoring mode or acquisition parameters through the interface, which significantly improves the system's operational convenience and user experience, while enhancing the intuitiveness of teaching demonstrations; As a technical solution for further implementation of this solution, the behavior data collection and regulation steps adopt a collaborative monitoring mechanism, which gives priority to starting the remote monitoring device. When abnormal behavior is detected, the proximity sensing device is automatically activated, and the collection frequency and power level are adjusted according to the importance of the behavior. The collaborative monitoring mechanism realizes the dynamic allocation of resources by giving priority to starting the remote monitoring device and automatically activating the proximity sensing device. This mechanism not only ensures the high efficiency of monitoring, but also can adjust the device frequency and power according to the importance of the behavior, effectively reducing energy consumption and improving the intelligence level of the system. As a technical solution for further implementation of this solution, users can optimize the system response sensitivity by adjusting the interference threshold and behavior weight to meet the monitoring needs of different experimental scenarios. The setting of interference threshold and weight supports the automatic recommendation function based on historical data, and supports optimizing the system response sensitivity by adjusting the interference threshold and behavior weight, so that the device can adapt to the needs of different experimental scenarios. The automatic recommendation function based on historical data further enhances the system's intelligent and personalized configuration capabilities, and meets the diverse needs of teaching and scientific research. The technical solutions for further implementation of this plan include: Main control system: including embedded computing unit, data storage module and communication interface; Used to coordinate the operation of monitoring equipment, dynamically adjust acquisition parameters, and optimize the balance between monitoring accuracy and minimizing interference through algorithms; Multimodal behavior monitoring module: including remote monitoring equipment and close sensing equipment; Remote monitoring equipment collects overall animal behavior data through high-definition cameras and infrared sensors; Close sensing devices collect detailed behavioral data of animals through microwave radar and thermal sensors; Dynamic control and interference management module: including interference assessment algorithm module, adaptive control unit and threshold setter; Used to dynamically adjust the acquisition frequency and power according to changes in animal behavior and device status to reduce interference with animal behavior; Data fusion and analysis module: including data fusion algorithm unit and deep learning behavior analysis engine; Used to integrate multi-source data and analyze and generate behavior pattern reports; User interaction and feedback module: including multi-terminal interaction interface and report generation module; Users can view behavioral data in real time through the interface, adjust monitoring modes, and review and annotate analysis reports. The device implements full-process management from behavioral data collection to analysis and feedback through a main control system, multimodal behavior monitoring module, dynamic regulation and interference management module, data fusion and analysis module, and user interaction and feedback module. The modular design ensures the flexibility and stability of the system, and can adapt to experimental teaching scenarios of different scales and needs, providing reliable data support and user operation experience.

[0026] This article uses specific examples to illustrate the principles and implementation methods of the present invention. The above examples are only used to help understand the method and core ideas of the present invention. The above is only a preferred implementation of the present invention. It should be pointed out that due to the limitations of textual expression and the objective existence of infinite specific structures, ordinary technicians in this technical field can make several improvements, modifications or changes without departing from the principles of the present invention, and can also combine the above technical features in an appropriate manner; these improvements, modifications, changes or combinations, or the direct application of the inventive concept and technical solution to other occasions without improvement, should be regarded as the protection scope of the present invention.

Claims

1. A method for using a management device for an animal experiment teaching demonstration center, characterized in that: The following steps are involved: Step I: Device initialization: Arrange remote monitoring equipment and close-range sensing equipment to ensure coverage of animal activity areas without blind spots; Define monitoring modes in the master control system, including remote monitoring, close monitoring and collaborative monitoring modes; Set the collection frequency, interference threshold, and behavior importance weight; Step II: Behavior data collection: Remote monitoring stage: The remote device collects overall behavior data in low-power mode, including activity range and trajectory. The scene heat dynamically adjusts the focus and angle of the collection device through the following formula: In the formula, Heat adjust is the acquisition equipment adjustment coefficient, ΔD heat is the density change of animal gathering area; W env is the weight of environmental change, ΔEnv is the change range of environmental parameters, t interval is the monitoring time interval; Close monitoring stage: When long periods of inactivity and sudden decreases in activity are detected, the close proximity device automatically activates to record micro-movements and specific behavioral data; Step III: Dynamic Control and Interference Management: Calculate the optimal combination of equipment operating parameters based on animal behavior changes and environmental parameters: In the formula, Param opt is the optimal working parameter of the device, P is the device power, F is the device acquisition frequency, Disturbance is the interference value, Energy is the energy consumption, W dist and W energy are the weight coefficients of interference and energy consumption respectively; The system dynamically adjusts device parameters and switches to low-power or remote monitoring mode when interference values ​​exceed thresholds; Step IV: Data fusion and analysis: Align the remote monitoring and close monitoring data by timestamps, and fuse multi-source data to generate behavioral analysis results; Use the feature mapping formula to calculate the pattern similarity of animal behaviors and mark abnormal behaviors: Where Similarity is the similarity between the current behavior and the baseline behavior, W i is the weight of behavior feature i, F i,current is the current behavior feature vector, F i,baseline is the baseline behavior feature vector; Step V: User feedback and strategy optimization: Users review the behavior analysis results to confirm the accuracy of the analysis; Adjust the equipment collection frequency, interference threshold and behavior weight according to the experimental requirements; The system records the adjustment strategy and updates the optimization model for strategy recommendation in subsequent experiments.

2. The method for using the animal experiment teaching demonstration center management device according to claim 1, characterized in that: In the dynamic control and interference management step, the following formula is used to calculate the equipment interference value: In the formula, C i is the weight of behavior i, B i,t is the observed value of the current behavior i, B i,baseline is the baseline value of behavior i, P active is the current device power, E norm It is the normalized value of device power.

3. The method for using the animal experiment teaching demonstration center management device according to claim 1, characterized in that: In the behavioral data collection step, the remote monitoring equipment captures the animal's activity trajectory and overall behavioral data through high-definition cameras and infrared sensors; the close-range sensing equipment records the animal's micro-movements and specific behaviors through low-power microwave radars and thermal sensors.

4. The method for using the animal experiment teaching demonstration center management device according to claim 1, characterized in that: In the behavior data collection step, the system dynamically adjusts the collection angle, focal length, and range of the remote monitoring device according to the scene heat. The calculation formula for scene heat is: Heat region =W1·Density peopie +W2·Activity level +W3·ΔE Where W1, W2 and W3 are weight coefficients, Density peopie is the animal density, Activity level is the activity level, and ΔE is the change in environmental parameters, including changes in temperature and humidity.

5. The method for using the animal experiment teaching demonstration center management device according to claim 1, characterized in that: In the data fusion and analysis step, the system uses deep learning algorithms to perform behavioral pattern recognition on the fused data, mark abnormal behaviors, and generate behavioral reports containing activity levels, behavioral frequencies, and abnormal behaviors.

6. The method for using the animal experiment teaching demonstration center management device according to claim 1, characterized in that: The device provides behavioral data visualization functions through a user interaction interface, including real-time display of behavior trajectories, heat distribution, and abnormal behavior alarms. Users can adjust the monitoring mode or collection parameters through the interface.

7. The method for using the animal experiment teaching demonstration center management device according to claim 1, characterized in that: The behavioral data collection and regulation steps adopt a collaborative monitoring mechanism, with remote monitoring equipment being activated first. When abnormal behavior is detected, the proximity sensing device is automatically activated, and the collection frequency and power level are adjusted according to the importance of the behavior.

8. The method for using the animal experiment teaching demonstration center management device according to claim 1, characterized in that: Users can optimize the system response sensitivity by adjusting the interference threshold and behavior weight to meet the monitoring needs of different experimental scenarios. The setting of interference threshold and weight supports automatic recommendation based on historical data.

9. An animal experiment teaching demonstration center management device according to any one of claims 1 to 8, characterized in that: include: Main control system: including embedded computing unit, data storage module and communication interface; Used to coordinate the operation of monitoring equipment, dynamically adjust acquisition parameters, and optimize the balance between monitoring accuracy and minimizing interference through algorithms; Multimodal behavior monitoring module: including remote monitoring equipment and close sensing equipment; Remote monitoring equipment collects overall animal behavior data through high-definition cameras and infrared sensors; Close sensing devices collect detailed behavioral data of animals through microwave radar and thermal sensors; Dynamic control and interference management module: including interference assessment algorithm module, adaptive control unit and threshold setter; Used to dynamically adjust the acquisition frequency and power according to changes in animal behavior and device status to reduce interference with animal behavior; Data fusion and analysis module: including data fusion algorithm unit and deep learning behavior analysis engine; Used to integrate multi-source data and analyze and generate behavior pattern reports; User interaction and feedback module: including multi-terminal interaction interface and report generation module; Users can view behavioral data in real time, adjust monitoring modes, and review and annotate analysis reports through the interface.

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